Source code for hensmith.hxn_synthesis

# -*- coding: utf-8 -*-
# hensmith: Heat Exchanger Network Synthesis, Modeling, Integration,
# Thermodynamics, and Heuristics
# Copyright (C) 2020-, Sarang Bhagwat <sarangbhagwat.developer@gmail.com>
#
# This module is under the UIUC open-source license. See
# github.com/BioSTEAMDevelopmentGroup/hensmith/blob/master/LICENSE.txt
# for license details.
"""
Pinch analysis and heat exchanger network synthesis: the problem table
(`problem_table`), the synthesis of a network at minimum energy requirement
(`synthesize_network`, on the planner of `hensmith._planner`), unsplit by
default and with stream splits where needed if `stream_splitting` (on
`hensmith._splitting`; realized splits are `StreamSplit`), stream life
cycles (`StreamLifeCycle`) and pinch diagrams (`plot_pinch_diagram`).
"""
from collections import namedtuple
import heapq
import math
import re
import numpy as np
import biosteam as bst
from warnings import warn
from ._curves import (StreamCurve, stream_curves, _end_state, _T_EQ, _T_SIDE,
                      _copy, _point_load_inlet)
from ._planner import plan_network
from ._splitting import Split, _ISO_TOL, _same_network

__all__ = ('StreamLifeCycle', 'ProblemTable', 'problem_table',
           'synthesize_network', 'plot_pinch_diagram')

#: IDs of the synthesized exchangers: process exchangers above the pinch
#: ``HX_<cold>_<hot>_hs`` and below it ``HX_<hot>_<cold>_cs`` (the first
#: number is the stream at port 0), with ``_<n>`` for the n-th exchanger of a
#: repeated pair; utility exchangers ``Util_<index>_hs|cs``.
_PROCESS_ID = re.compile(r'^HX_(\d+)_(\d+)_(hs|cs)(?:_\d+)?$')
_UTILITY_ID = re.compile(r'^Util_(\d+)_(hs|cs)$')

def _stream_ports(unit):
    """Stream index at each inlet port of a synthesized exchanger, parsed
    from its ID (``(a, b)`` for ``HX_<a>_<b>_...``, ``(a,)`` for
    ``Util_<a>_...``), or None if the ID is not one of the synthesizer's."""
    ID = unit.ID
    match = _PROCESS_ID.match(ID)
    if match: return int(match.group(1)), int(match.group(2))
    match = _UTILITY_ID.match(ID)
    if match: return (int(match.group(1)),)
    return None

#: An inlet port, ``unit.ins[index]`` (see `StreamLifeCycle.entry`).
_Port = namedtuple('_Port', ('unit', 'index'))

def _flow_order(trunk, splits, branches):
    """
    A life cycle with splits in flow order: ``(None, stage)`` for every
    stage of `trunk` (the stages on the whole flow, in flow order, the
    utility last) and ``(split, branches[k])`` for split k of `splits` (in
    flow order; `branches[k]` holds the stages of each of its branches),
    placed after ``split.position`` trunk process stages and before the
    utility.
    """
    flow, k = [], 0
    for t, stage in enumerate(trunk):
        utility = isinstance(stage.unit, bst.HXutility)
        while k < len(splits) and (utility or splits[k].position <= t):
            flow.append((splits[k], branches[k]))
            k += 1
        flow.append((None, stage))
    flow.extend(zip(splits[k:], branches[k:]))
    return flow

def _split_flow(stages, splits, flow_order, index):
    """
    Tag the `stages` of stream `index` on the branches of its `splits` (in
    flow order) with their branch and fraction, sort the others (the
    trunk) by `flow_order` with the utility last, and return
    `_flow_order`'s flow of them.
    """
    tags = {id(hx): (k, b, f) for k, split in enumerate(splits)
            for b, (f, hxs) in enumerate(zip(split.fractions, split.branches))
            for hx in hxs}
    tagged, trunk = {}, []
    for stage in stages:
        if id(stage.unit) in tags: tagged[id(stage.unit)] = stage
        else: trunk.append(stage)
    branches = []
    for split in splits:
        branches.append([])
        for hxs in split.branches:
            branch = []
            for hx in hxs:
                stage = tagged.get(id(hx))
                if stage is None:
                    raise ValueError(f'{hx.ID} of split {split!r} does '
                                     f'not carry stream {index}')
                k, b, stage.fraction = tags[id(hx)]
                stage.branch = (k, b)
                branch.append(stage)
            branches[-1].append(branch)
    trunk.sort(key=flow_order)
    utilities = [s for s in trunk if isinstance(s.unit, bst.HXutility)]
    trunk = [s for s in trunk if not isinstance(s.unit, bst.HXutility)]
    return _flow_order(trunk + utilities, splits, branches)

[docs] class LifeStage: """ One stage of a stream's passage through the synthesized network: the heat exchanger it passes through and which of that exchanger's inlet/outlet pairs carries the stream. Parameters ---------- unit : HXprocess or HXutility Heat exchanger of the synthesized network. index : int Position of the stream in `unit.ins` / `unit.outs` (0 or 1 for an `HXprocess`; always 0 for an `HXutility`). branch : tuple[int, int], optional ``(k, b)`` for a stage on branch b of the stream's split k (see `StreamLifeCycle.splits`); None (the default) for a stage on the whole flow. fraction : float, optional Fraction of the stream's flow through this stage: that of its branch, 1 (the default) on the whole flow. Attributes ---------- s_in : Stream `unit.ins[index]`, the stream entering this stage. s_out : Stream `unit.outs[index]`, the stream leaving this stage. H_in : float Enthalpy of `s_in` [kJ/hr], read from the stream when accessed (on a branch, the branch's: `fraction` of the whole flow's). H_out : float Enthalpy of `s_out` [kJ/hr], read from the stream when accessed. """ def __init__(self, unit, index, branch=None, fraction=1.): self.unit = unit self.index = index self.branch = branch self.fraction = fraction @property def s_in(self): return self.unit.ins[self.index] @property def s_out(self): return self.unit.outs[self.index] @property def H_in(self): return self.s_in.H @property def H_out(self): return self.s_out.H def _branch_info(self): branch = self.branch if branch is None: return '' return f", branch {branch}, fraction {self.fraction:.4g}" def _info(self, N_tabs=1): tabs = N_tabs*'\t' return (f"{type(self).__name__}: {self.unit.ID}{self._branch_info()}\n" + tabs + f"H_in = {self.H_in:.3g} kJ/hr\n" + tabs + f"H_out = {self.H_out:.3g} kJ/hr") def __repr__(self): return (f"<{type(self).__name__}: {repr(self.unit)}{self._branch_info()}, H_in = {round(self.H_in, 4):.3g} kJ/hr, H_out = {round(self.H_out, 4):.3g} kJ/hr>") def show(self): print(self._info()) _ipython_display_ = show
[docs] class StreamLifeCycle: """ The ordered sequence of heat exchangers one process stream passes through in a synthesized heat exchanger network, from its inlet state to its final utility exchanger. Streams are numbered by their position in the rearranged utility list of `synthesize_network` (cold streams first, then hot streams); the network's stream copies and exchanger IDs embed that index (``s_<index>__<exchanger ID>`` for the inlet streams of the exchangers, ``HX_<hot>_<cold>_cs`` / ``HX_<cold>_<hot>_hs`` for process exchangers, with a suffix ``_<n>`` for the n-th exchanger of a repeated pair, ``Util_<index>_cs`` / ``Util_<index>_hs`` for utility exchangers), which is how the life cycle is recovered from the exchangers: the IDs are parsed (the first number is the stream at port 0, the second the stream at port 1), so the stream indices are matched exactly and never as substrings of other indices or of rewired stream IDs. Parameters ---------- index : int Stream index in the synthesized network. cold : bool True for a heated (cold) stream, False for a cooled (hot) stream. Attributes ---------- index : int Stream index in the synthesized network. cold : bool Whether the stream is a heated (cold) stream. name : str ``'s_<index>'``, the prefix of the stream's copies in the network. life_cycle : list[LifeStage] or None Stages in flow order, set by `get_life_cycle`; None until then. Where the stream splits, the stages of every branch follow those before the split, branch by branch (see `get_life_cycle`). splits : list[StreamSplit] The stream's splits in flow order, set by `get_life_cycle`; empty for an unsplit stream. Split k's branch stages have ``branch == (k, b)``. entry : tuple[Unit, int] or None ``(unit, index)``, a named tuple: the inlet port `unit.ins[index]` where the whole stream enters the network, i.e. the first splitter of its first split if it splits at its inlet, else its first stage's. None until `get_life_cycle` runs, and for a life cycle whose `life_cycle` is assigned directly. Notes ----- `HeatExchangerNetwork` builds one life cycle per stream after synthesis and stores them in `HeatExchangerNetwork.stream_life_cycles`, aligned with `HeatExchangerNetwork.original_heat_exchangers`; `plot_pinch_diagram` draws them. """ # Defaults for an instance without them, e.g. one unpickled from before # stream splitting: an unsplit stream with no entry port recorded. splits = () entry = None def __init__(self, index, cold): self.index = index self.name = 's_%s'%index self.cold = cold self.life_cycle = None self.splits = [] self.entry = None @property def H_in(self): """Enthalpy of the stream at `entry` [kJ/hr], read from the stream when accessed: the whole flow's inlet, equal to the first stage's `H_in` unless the stream splits at its inlet. Without an `entry` (a `life_cycle` assigned directly), the first stage's `H_in`.""" entry = self.entry if entry is None: return self.life_cycle[0].H_in unit, index = entry return unit.ins[index].H
[docs] def get_relevant_units(self, index, new_HXs, new_HX_utils): """ Return the process and utility exchangers (two lists) that carry stream `index`: those whose parsed ID (``HX_<a>_<b>_<hs|cs>[_<n>]`` or ``Util_<a>_<hs|cs>``) names it; for any other ID, those whose ID contains ``_<index>_``. """ def relevant(hx): ports = _stream_ports(hx) if ports is None: return '_%s_'%index in hx.ID return index in ports new_HXs_relevant = [hx for hx in new_HXs if relevant(hx)] new_HX_utils_relevant = [hx for hx in new_HX_utils if relevant(hx)] return new_HXs_relevant, new_HX_utils_relevant
[docs] def get_life_cycle(self, new_HXs, new_HX_utils, splits=None): """ Build and return the list of `LifeStage` objects for this stream. Parameters ---------- new_HXs : list[HXprocess] Process exchangers of the synthesized network. new_HX_utils : list[HXutility] Utility exchangers of the synthesized network. splits : list[StreamSplit], optional Splits of the network (``info['splits']`` of `synthesize_network`); those of other streams are ignored. Without any split of this stream, the life cycle is built exactly as for an unsplit network. Returns ------- list[LifeStage] One stage per port that carries this stream: for an exchanger ID of the synthesizer (see the class notes) the port its ID assigns to `index` (0 or 1 for a process exchanger, 0 for a utility exchanger); for any other ID, every port among 0 and 1 (0 for a utility) whose inlet ID contains ``'s_<index>_'``. Sorted in flow direction: by inlet enthalpy, ascending for a cold stream and descending for a hot one; ties (zero-duty stages only) put the stream's first side of the pinch first (cold-side stages for a cold stream, hot-side stages for a hot one) and the utility last. Also stored as `life_cycle`. With splits, only the trunk stages (those on the whole flow, which pass the stream's enthalpies in order) are sorted so; the exchangers of split k's branches (``StreamSplit.branches``, by identity) follow the first ``StreamSplit.position`` trunk process stages, branch by branch and each branch in flow order, as stages with ``branch == (k, b)`` and the branch's `fraction`; the utility stays last. Enthalpies of different branches are never compared. The stream's splits are stored, in flow order, as `splits`, and its entry port as `entry`. Raises ------ ValueError If an exchanger of one of the stream's splits does not carry the stream. """ index = self.index name = self.name cold = self.cold new_HXs_relevant, new_HX_utils_relevant =\ self.get_relevant_units(index, new_HXs, new_HX_utils) life_cycle = [] for units, N_ports in ((new_HXs_relevant, 2), (new_HX_utils_relevant, 1)): for unit in units: ports = _stream_ports(unit) if ports is None: life_cycle.extend([LifeStage(unit, k) for k in range(N_ports) if name + '_' in unit.ins[k].ID]) else: life_cycle.extend([LifeStage(unit, k) for k, i in enumerate(ports) if i == index]) sign = 1. if cold else -1. first_side = '_cs' if cold else '_hs' def flow_order(stage): ID = stage.unit.ID if isinstance(stage.unit, bst.HXutility): rank = 2 else: rank = 0 if first_side in ID else 1 return (sign * stage.H_in, rank) splits = [split for split in splits or () if split.stream == index] if splits: # flow order: by position, then (consecutive splits) by the # enthalpy where they split splits.sort(key=lambda split: (split.position, sign * split.H_split)) flow = _split_flow(life_cycle, splits, flow_order, index) life_cycle = [stage for split, part in flow for stage in ([part] if split is None else [s for b in part for s in b])] else: life_cycle.sort(key=flow_order) flow = [(None, stage) for stage in life_cycle[:1]] self.life_cycle = life_cycle self.splits = splits if flow: split, part = flow[0] self.entry = (_Port(part.unit, part.index) if split is None else _Port(split.splitters[0], 0)) else: self.entry = None return life_cycle
def _flow(self): """The life cycle in flow order as ``(None, stage)`` for every trunk stage and ``(split, branches)`` for every split, `branches` being the stages of each of its branches (see `_flow_order`).""" splits = self.splits branches = [[[] for hxs in split.branches] for split in splits] trunk = [] for stage in self.life_cycle: branch = stage.branch if branch is None: trunk.append(stage) else: branches[branch[0]][branch[1]].append(stage) return _flow_order(trunk, splits, branches)
[docs] def connections(self): """ Yield the stream's connections in flow order, as ``(up_unit, up_port, down_unit, down_port)``: ``up_unit.outs[up_port]`` feeds ``down_unit.ins[down_port]``. Wiring every connection of every life cycle joins the network. For an unsplit stream, these are its consecutive stages. At a split: the stage before it feeds the first splitter (port 0); splitter c's second outlet feeds splitter c + 1; the outlet of branch b (``StreamSplit.outlet``) feeds the branch's first stage, or inlet b of the mixer for a branch without exchangers (a bypass); each branch stage feeds the next, the last one mixer inlet b; the mixer's outlet feeds the next stage (or the next split's first splitter). """ up = None # (unit, port) feeding the next node for split, part in self._flow(): if split is None: if up is not None: yield (*up, part.unit, part.index) up = (part.unit, part.index) continue splitters = split.splitters if up is not None: yield (*up, splitters[0], 0) for a, b in zip(splitters, splitters[1:]): yield (a, 1, b, 0) for b, stages in enumerate(part): end = split.outlet(b) for stage in stages: yield (*end, stage.unit, stage.index) end = (stage.unit, stage.index) yield (*end, split.mixer, b) up = (split.mixer, 0)
[docs] def stage_pairs(self): """ Yield the pairs ``(a, b)`` of stages where the stream flows from `a` into `b` directly or through splitters and mixers only: for an unsplit stream, its consecutive stages. The stage before a split precedes the first stage of every branch, and the last stage of every branch the stage after the split; a bypass carries the stages before its split past it. Stages on sibling branches make no pair. """ frontier = [] # the stages whose outflow reaches the next node for split, part in self._flow(): if split is None: for stage in frontier: yield stage, part frontier = [part] continue ends = [] for stages in part: if stages: for stage in frontier: yield stage, stages[0] yield from zip(stages, stages[1:]) last = [stages[-1]] else: # a bypass last = frontier ends.extend([stage for stage in last if not any(stage is end for end in ends)]) frontier = ends
def __repr__(self): life_cycle = self.life_cycle cold = self.cold if not self.life_cycle: return 'Not initialized; run StreamLifeCycle.get_life_cycle or\ HX_Network.get_stream_life_cycles first.' else: index = self.index name = 'Stream_%s'%index strtype = 'cold' if cold else 'hot' rep = '' for LifeStage in life_cycle: line = '\t\t' + repr(LifeStage) + '\n' rep += line rep = '<StreamLifeCycle: ' + name + ', ' + strtype + '\n\tlife_cycle = [\n' + rep[:-1] + '\n\t]' for k, split in enumerate(self.splits): fractions = ', '.join(f'{f:.4g}' for f in split.fractions) rep += (f'\n\tsplit {k}: {len(split.fractions)} branches ' f'({fractions})') return rep + '>'
[docs] def show(self): """Print the life cycle, one stage per line.""" info = repr(self).replace('[', '').replace(']', '').replace('life_cycle =', 'life_cycle:') print(info[1:-1])
_ipython_display_ = show
ProblemTable = namedtuple( 'ProblemTable', ['Ts', 'interval_H', 'point_H', 'residual', 'hot_util_load', 'cold_util_load', 'pinch_T'] ) ProblemTable.__doc__ = """ Result of `problem_table`: the temperature-interval heat cascade of a set of process streams on the *shifted* temperature scale (hot streams shifted down by the minimum approach temperature, cold streams unshifted). Attributes ---------- Ts : numpy.ndarray Shifted grid temperatures [K], descending: every shifted breakpoint of every stream's temperature-enthalpy curve, i.e. its end temperatures, the phase boundaries inside its range (a pure component's saturation temperature, a mixture's bubble and dew points), the samples of its two-phase glides and of its curved single-phase stretches (temperature-dependent heat capacity), and the outlet temperature of every point-load stream (see `point_H`). Temperatures closer than 1e-9 K are one grid point. interval_H : numpy.ndarray (N streams x n-1 intervals) heat contributed by each stream to each open interval (Ts[k], Ts[k+1]) [kJ/hr]: positive for hot streams (heat released), negative for cold streams (heat required); zero outside the stream's own temperature range. point_H : numpy.ndarray (N x n) heat contributed *at* each grid temperature [kJ/hr], with the same sign convention: the jump of the stream's curve there, i.e. a pure component's latent heat at its (shifted) saturation temperature, the enthalpy by which a non-equilibrium end state departs from equilibrium at its own end temperature, and the whole duty of a point-load stream at its shifted outlet temperature (isothermal streams and streams whose outlet temperature moves against their duty). residual : numpy.ndarray (n,) heat cascaded *leaving* each grid temperature, after its point loads, when no hot utility is supplied [kJ/hr]; negative where that cascade is infeasible. hot_util_load : float Minimum hot utility target [kJ/hr] (zero for a threshold problem). cold_util_load : float Minimum cold utility target [kJ/hr]. pinch_T : float Shifted grid temperature of the pinch [K] (``Ts[0]`` for a threshold problem); the hot-stream pinch temperature is `pinch_T + T_min_app`, the cold-stream one is `pinch_T`. See Also -------- problem_table : builds the table and documents the cascade. """
[docs] def problem_table(streams_inlet, streams_quenched, is_hot, T_min_app, curves=None): """ Energy-consistent problem table (temperature-interval heat cascade). Parameters ---------- streams_inlet : list[Stream] Inlet stream of each utility heat exchanger. streams_quenched : list[Stream] Corresponding outlet streams, re-flashed at their enthalpy. is_hot : Sequence[bool] True where the stream is cooled. T_min_app : float Minimum approach temperature [K]. curves : list, optional Prebuilt temperature-enthalpy curves of the same streams, in the same order (e.g. shared with the network synthesis); built here if not given. Returns ------- ProblemTable Grid temperatures `Ts` (shifted scale, descending), per-stream `interval_H` (N x n-1) and `point_H` (N x n) contributions (+ for hot, - for cold), the cascade `residual` (n) *leaving* each boundary (i.e. after its point loads), `hot_util_load`, `cold_util_load` and the shifted-scale `pinch_T`. Notes ----- Each stream is described by a piecewise-linear temperature-enthalpy curve built once from a handful of flashes: breakpoints at its end temperatures and at every phase boundary inside its range (a pure component's saturation temperature, a mixture's bubble and dew points); a flat (isothermal) segment for a pure component's latent heat, between its saturated-liquid and saturated-vapor enthalpies; samples of each mixture glide (binaries traced along their bubble-point curve); and interior breakpoints of each curved single-phase stretch (temperature-dependent Cp), dense enough that linear interpolation is within 0.002 K of the true curve. Single-phase stretches are evaluated with their phases fixed (no flash), so a grid point exactly at a saturation temperature is never ambiguous. Hot streams are shifted down by `T_min_app`; cold streams are not. The grid is the union of all shifted breakpoints, so every point at which any stream's curve bends or jumps is a grid point, every stream is within 0.002 K of linear between grid points, and the grid minimum of the cascade is the true one to within ``0.002 K * sum(CP)``. At a grid temperature a stream contributes the jump of its curve there as a point load (`point_H`), and between two grid temperatures the heat of its curve in that open interval (`interval_H`). Inside its own temperature range a stream is taken at equilibrium with its enthalpy clipped to its real range, so a non-equilibrium end state (e.g. a superheated liquid from a non-rigorous HXutility) can never inflate the duty; what it departs from equilibrium at its own end temperature is a point load there. Every stream's contributions therefore telescope exactly to ``sign * |H_out - H_in|``. Streams whose outlet temperature does not move with their duty (isothermal, or a heated stream that exits colder than it entered, e.g. a reboiler outlet at VLE) are point loads at their outlet temperature. The cascade starting from zero hot utility is residual[k] = sum(point_H[:, :k+1]) + sum(interval_H[:, :k]), the heat *leaving* boundary Ts[k]. Feasibility must also hold for the heat *arriving* at Ts[k] before its point loads are applied, arriving[k] = residual[k] - sum(point_H[:, k]), because a source at Ts[k] cannot serve a sink above Ts[k]. The minimum over both flows, min(residual, arriving), fixes the hot utility target, `residual[-1] + hot_util_load` the cold one, and its first location the pinch. With the per-stream identity above, hot_util_load - cold_util_load equals the net heating demand. Examples -------- A threshold problem: 1000 kmol/hr of water cooled 400 -> 300 K supplies every interval of 900 kmol/hr of water heated 300 -> 390 K, so no hot utility is needed and the surplus leaves as cold utility. (The grid between the ends holds the breakpoints that follow the curvature of liquid water's enthalpy.) >>> import biosteam as bst >>> from hensmith.hxn_synthesis import problem_table >>> bst.settings.set_thermo(['Water']) >>> hot_in = bst.Stream(Water=1000., T=400., P=5e5, phase='l', units='kmol/hr') >>> hot_out = hot_in.copy(); hot_out.vle(T=300., P=5e5) >>> cold_in = bst.Stream(Water=900., T=300., P=5e5, phase='l', units='kmol/hr') >>> cold_out = cold_in.copy(); cold_out.vle(T=390., P=5e5) >>> table = problem_table([hot_in, cold_in], [hot_out, cold_out], ... [True, False], 5.) >>> table.Ts[[0, -1]] # shifted grid ends (hot streams 5 K down) array([395., 295.]) >>> round(table.hot_util_load, 3) 0.0 >>> round(table.cold_util_load, -1) 1445550.0 >>> table.pinch_T 395.0 """ return _problem_table(streams_inlet, streams_quenched, is_hot, T_min_app, curves)[0]
def _problem_table(streams_inlet, streams_quenched, is_hot, T_min_app, curves=None): """ Return the `ProblemTable` of `problem_table` together with the stream curves it was built from and its grid enthalpies, as ``(table, curves, grid)``. `grid` is a dict with * 'Ts': the table's shifted grid temperatures (descending, n); * 'shift': each stream's shift (`T_min_app` for hot streams, 0 for cold ones; N), so stream j's real temperature at grid index k is ``Ts[k] + shift[j]``; * 'Hl', 'Hr': (N x n) each stream's enthalpy at every grid temperature, left (low-enthalpy) and right (high-enthalpy) limit; they differ only where the stream's curve has a flat (point load) at that grid temperature, and are H_hi above and H_lo below the stream's range; * 'k_hi', 'k_lo': (N,) grid indices of each stream's own T_hi and T_lo breakpoints (``k_hi <= k_lo``; equal for a point-load stream), so its range is selected by position, not by comparing shifted floats. The table is exactly ``point_H = sign * (Hr - Hl)`` and ``interval_H = sign * (Hl[:, :-1] - Hr[:, 1:])`` (sign +1 hot, -1 cold): piecewise- linear curves through the knots (Ts[k] + shift[j], Hl[j, k]) and (Ts[k] + shift[j], Hr[j, k]) reproduce the table's cascade exactly. """ N = len(streams_inlet) is_hot = np.asarray(is_hot, dtype=bool) sign = np.where(is_hot, 1., -1.) shift = np.where(is_hot, T_min_app, 0.) if curves is None: curves = stream_curves(streams_inlet, streams_quenched, is_hot) elif len(curves) != N: raise ValueError(f'{len(curves)} curves given for {N} streams') H_in = np.array([c.H_in for c in curves]) H_out = np.array([c.H_out for c in curves]) shifted = [c.T - shift[j] for j, c in enumerate(curves)] sizes = [x.size for x in shifted] values, inverse = np.unique(np.concatenate(shifted), return_inverse=True) # merge grid temperatures closer than 1e-9 K (ascending clusters) cluster = np.concatenate([[0], np.cumsum(np.diff(values) > _T_EQ)]) n = int(cluster[-1]) + 1 # the highest member of each cluster represents it (selected explicitly: # NumPy does not specify which value a repeated fancy index keeps) top = values[np.flatnonzero(np.append(np.diff(cluster) > 0, True))] Ts = top[::-1].copy() position = (n - 1) - cluster[inverse] # descending grid index of each breakpoint offsets = np.concatenate([[0], np.cumsum(sizes)]) Hl = np.empty((N, n)) Hr = np.empty((N, n)) k_hi = np.empty(N, dtype=int) k_lo = np.empty(N, dtype=int) for j, c in enumerate(curves): index = position[offsets[j]:offsets[j + 1]] Hl[j], Hr[j] = c.grid_limits(Ts, shift[j], index) k_hi[j] = index[-1] k_lo[j] = index[0] point_H = sign[:, None] * (Hr - Hl) interval_H = sign[:, None] * (Hl[:, :-1] - Hr[:, 1:]) point_total = point_H.sum(axis=0) residual = np.cumsum( point_total + np.concatenate([[0.], interval_H.sum(axis=0)]) ) # heat arriving at each boundary, before that boundary's point loads: # a point source at Ts[k] cannot serve sinks above Ts[k], so the cascade # must be non-negative both before and after the point loads arriving = residual - point_total flow = np.minimum(residual, arriving) k_pinch = int(np.argmin(flow)) scale = np.abs(H_out - H_in).sum() if -flow[k_pinch] <= 1e-9 * scale: # threshold problem: no hot utility hot_util_load = 0. k_pinch = 0 else: hot_util_load = -flow[k_pinch] cold_util_load = residual[-1] + hot_util_load if cold_util_load < 0.: # only reachable in the threshold branch, by at most 1e-9 * scale: # absorb the rounding into the hot utility so that # hot_util_load - cold_util_load == sum(unit_duty) stays exact hot_util_load -= cold_util_load cold_util_load = 0. table = ProblemTable(Ts, interval_H, point_H, residual, hot_util_load, cold_util_load, Ts[k_pinch]) grid = dict(Ts=Ts, shift=shift, Hl=Hl, Hr=Hr, k_hi=k_hi, k_lo=k_lo) return table, curves, grid def _pinch_cut(table): """ Return which side of the pinch the point loads *at* the pinch temperature belong to: 'below' if the zero-heat-flow cut is the flow arriving at `pinch_T` (before its point loads), 'above' if it is the flow leaving it (after them); always 'below' for a threshold problem (no hot utility: everything lies below the pinch at ``Ts[0]``). Split every stream with ``side = 'right' if cut == 'below' else 'left'`` (see `pinch_state`) to agree with the table: the heat above the split is then exactly the hot utility target and the heat below it the cold one. (`synthesize_network` does not cut streams at the pinch, even with `stream_splitting`, whose splits are parallel branches: the planner finds the same cut in its own cascade, ``plan.cut``, which reproduces the table's.) """ if table.hot_util_load == 0.: return 'below' k = int(np.flatnonzero(table.Ts == table.pinch_T)[0]) point_total = table.point_H.sum(axis=0) arriving = table.residual - point_total return 'below' if arriving[k] <= table.residual[k] else 'above' def _pinch_analysis(hus, T_min_app=10, force_ideal_thermo=False, sort_hus_by_T=False): """ The first step of `synthesize_network`: prepare the process streams behind `hus` and run the problem table on them. Returns the 12 values of `temperature_interval_pinch_analysis` (which wraps this function) and then the table's ``table, curves, grid`` (see `_problem_table`), on which the network is planned, so that the curves are built only once. """ hx_utils = hus hus_heating = [hu for hu in hx_utils if hu.duty > 0] hus_cooling = [hu for hu in hx_utils if hu.duty < 0] if sort_hus_by_T: hus_heating.sort(key=lambda i: i.unit.ins[0].T, reverse=True) hus_cooling.sort(key=lambda i: i.unit.ins[0].T) hx_utils_rearranged = hus_heating + hus_cooling hxs = [hu.unit for hu in hx_utils_rearranged] # unregistered copies (see `hensmith._curves._copy`); the inlets are # registered under their own IDs below if force_ideal_thermo: streams_inlet = [_copy(hx.ins[0], hx.ins[0].thermo.ideal()) for hx in hxs] streams_quenched = [_copy(hx.outs[0], hx.outs[0].thermo.ideal()) for hx in hxs] else: streams_inlet = [_copy(hx.ins[0]) for hx in hxs] streams_quenched = [_copy(hx.outs[0]) for hx in hxs] for i in streams_quenched: i.vle(H=i.H, P=i.P) for i in range(len(streams_inlet)): stream = streams_inlet[i] ID = 'Util_%s'%i stream.ID = 's_%s__%s'%(i,ID) N_heating = len(hus_heating) cold_indices = list(range(N_heating)) hot_indices = list(range(N_heating, len(hxs))) indices = cold_indices + hot_indices T_in_arr = np.array([stream.T for stream in streams_inlet]) T_out_arr = np.array([i.T for i in streams_quenched]) is_hot = np.zeros(len(hxs), dtype=bool) is_hot[hot_indices] = True table, curves, grid = _problem_table(streams_inlet, streams_quenched, is_hot, T_min_app) hot_util_load = table.hot_util_load cold_util_load = table.cold_util_load pinch_cold_stream_T = table.pinch_T pinch_hot_stream_T = pinch_cold_stream_T + T_min_app # Per-stream pinch temperature, for information only (returned as # `HeatExchangerNetwork.pinch_Ts`; `load_duties` splits a stream there): # the network is planned on the curves (see `synthesize_network`), not # on these temperatures. A stream already entirely on one side of the # process pinch (T_in past pinch_cold_stream_T for a cold stream, or # past pinch_hot_stream_T for a hot stream) is not split; its pinch_T is # its own T_in. So is a non-monotone stream (T_out on the wrong side of # T_in for its duty, e.g. a cold stream whose VLE outlet ends up cooler # than it entered: a point load at T_out), whose whole duty # `load_duties` then puts on a single side (hot side for a cold stream, # cold side for a hot one). pinch_T_arr = [] for i in cold_indices: if T_in_arr[i] > pinch_cold_stream_T or T_in_arr[i] > T_out_arr[i]: pinch_T_arr.append(T_in_arr[i]) elif T_out_arr[i] < pinch_cold_stream_T: pinch_T_arr.append(T_out_arr[i]) else: pinch_T_arr.append(pinch_cold_stream_T) for i in hot_indices: if T_in_arr[i] < pinch_hot_stream_T or T_in_arr[i] < T_out_arr[i]: pinch_T_arr.append(T_in_arr[i]) elif T_out_arr[i] > pinch_hot_stream_T: pinch_T_arr.append(T_out_arr[i]) else: pinch_T_arr.append(pinch_hot_stream_T) pinch_T_arr = np.array(pinch_T_arr) return pinch_T_arr, hot_util_load, cold_util_load, T_in_arr, T_out_arr,\ hxs, hot_indices, cold_indices, indices, streams_inlet, hx_utils_rearranged, \ streams_quenched, table, curves, grid def temperature_interval_pinch_analysis(hus, T_min_app=10, force_ideal_thermo=False, sort_hus_by_T=False): """ Prepare the process streams behind `hus` and run the problem table on them, as `synthesize_network` does first; a standalone pinch analysis (the network itself is planned on the table's stream curves, which this function does not return). Heating utilities (``hu.duty > 0``, cold streams) come first, then cooling utilities; zero-duty utilities are dropped. Each stream is a copy of its exchanger's inlet (renamed ``s_<index>__Util_<index>``) and of its outlet re-flashed at its own enthalpy. Returns ------- pinch_T_arr : numpy.ndarray Per-stream pinch temperature (see `synthesize_network`). hot_util_load, cold_util_load : float MER targets of `problem_table` [kJ/hr]. T_in_arr, T_out_arr : numpy.ndarray Inlet and quenched outlet temperatures [K]. hxs : list[Unit] The original heat exchangers, in stream order. hot_indices, cold_indices, indices : list[int] Stream indices of the hot streams, the cold streams, and all (cold first). streams_inlet, hx_utils_rearranged, streams_quenched : list Inlet copies, heat utilities and quenched outlet copies, in stream order. """ return _pinch_analysis(hus, T_min_app, force_ideal_thermo, sort_hus_by_T)[:12] def pinch_state(stream_in, stream_out, T_pinch, side=None, curve=None): """ Return a copy of the stream in the state it has when it crosses the pinch, with enthalpy guaranteed to lie within [min(H_in, H_out), max(H_in, H_out)]. Parameters ---------- stream_in, stream_out : Stream The stream's real end states (the outlet quenched to equilibrium at its own enthalpy). T_pinch : float The stream's (real, unshifted) pinch temperature [K]. side : str, optional Branch of a flat (isothermal) segment of the stream at `T_pinch` (latent heat or a non-equilibrium end jump): 'right' takes its high-enthalpy end (the load at the pinch goes below the pinch), 'left' its low-enthalpy end (the load goes above). Pass ``side = 'right' if cut == 'below' else 'left'``, with ``cut`` the pinch cut of the table (`_pinch_cut`), to split every stream consistently with the targets. If not given, an end temperature returns that end's state (below) and elsewhere hot streams take 'right' and cold streams 'left'. curve : StreamCurve, optional Prebuilt curve of the stream (e.g. from `_problem_table`); built here if needed and not given. Notes ----- The state comes from the stream's temperature-enthalpy curve (see `problem_table`), so it is deterministic: a pinch at the stream's own saturation temperature is resolved by `side`, never by whatever phase split a previous flash left, and a pinch inside a glide gets the table's enthalpy. Inside the stream's temperature range the enthalpy is clipped to its real range, as in the table: a non-equilibrium inlet (e.g. a superheated liquid from a non-rigorous HXutility) has less enthalpy than the equilibrium fluid at the pinch, so the state returned is instead the equilibrium state at the nearer end enthalpy. Without `side`, `T_pinch` equal to an end temperature returns that end's state (the equilibrium state at the end enthalpy, see `_end_state`), because flashing a non-equilibrium inlet at its own temperature does not reproduce `H_in`. Using the *equilibrium* state at the end enthalpy, rather than the stream as given, keeps the synthesizer consistent with the problem table: the heat is offered at the temperature the equilibrium model says it is available, not at a fictitious one. Either way the hot-side and cold-side loads split `|H_in - H_out|` exactly, and the state never carries heat the real stream does not have. A standalone analysis helper (see also `load_duties`): the network synthesis does not cut streams at a pinch temperature (its only splits, with `stream_splitting`, are parallel branches), it plans on the curves themselves (see `synthesize_network`). """ if side is None: T_lo, T_hi = sorted((stream_in.T, stream_out.T)) if T_pinch == stream_in.T: return _end_state(stream_in, T_lo, T_hi) if T_pinch == stream_out.T: return _end_state(stream_out, T_lo, T_hi) if curve is None: curve = StreamCurve(stream_in, stream_out) if side is None: side = 'right' if curve.is_hot else 'left' return curve.state_at_T(T_pinch, side) def load_duties(streams, streams_quenched, pinch_T_arr, T_out_arr, indices, is_cold, Q_hot_side, Q_cold_side): """ Fill `Q_hot_side` and `Q_cold_side` with each stream's duty above and below its pinch temperature, ``[kind, duty]`` with kind 'heat' (cold streams) or 'cool' (hot streams) and duties below 0.01 kJ/hr set to 0, from the stream's `pinch_state` at ``pinch_T_arr[index]`` (e.g. from `temperature_interval_pinch_analysis`). A standalone analysis helper, like `pinch_state`: `synthesize_network` does not use it. """ for index in indices: H_in = streams[index].H H_out = streams_quenched[index].H H_pinch = pinch_state(streams[index], streams_quenched[index], pinch_T_arr[index]).H if not is_cold(index): dH1 = H_in - H_pinch dH2 = H_pinch - H_out if abs(dH1)<0.01: dH1 = 0 if abs(dH2)<0.01: dH2 = 0 Q_hot_side[index] = ['cool', dH1] Q_cold_side[index] = ['cool', dH2] else: dH1 = H_out - H_pinch dH2 = H_pinch - H_in if abs(dH1)<0.01: dH1 = 0 if abs(dH2)<0.01: dH2 = 0 Q_hot_side[index] = ['heat', dH1] Q_cold_side[index] = ['heat', dH2] # %% Network synthesis #: Exact-state approach acceptance [K]. Synthesized process exchangers get #: ``HXprocess(dT=T_min_app - _APPROACH_TOL)`` as a guard only: the planner #: and the exactness check enforce `T_min_app` on the exact states. _APPROACH_TOL = 1e-6 #: A simulated process-exchanger duty that differs from the planned one by #: more than this times the two streams' total duties is a deviation. _DUTY_TOL = 1e-6 #: Status 'mer' needs the utilities of the realized network (from the #: simulated duties) within this times the total stream duty of the targets: #: the accuracy of the enthalpy flashes that realize the plan (the plan #: itself reaches the targets within `hensmith._planner._MER_TOL`). _ACHIEVED_TOL = 1e-6 #: Rounds of exact-state verification and local knot refinement. _MAX_REFINE = 3 #: Extra rounds with stream splitting after the last refine round, each run #: only if a violating exchanger lies on a split side whose network #: (`hensmith._splitting._same_network`) is newly excluded. The retry #: re-plans that side without its networks excluded so far: another network #: if the side has one left, else the same one on the refined knots (a side's #: last candidate is never excluded), after which no network is new. _MAX_SPLIT_RETRY = 2 #: A split's mixer outlet further than this from the planned temperature [K] #: is a deviation: 133 times the offset of a branch-flow PH flash (7.5e-10 #: K) and 10 times below the approach guard `_APPROACH_TOL`. It catches #: thermosteam's PH flash disagreeing with the stream's curve (risk R-2), #: measured at 0.8-2.4 K inside random water/methanol glides. _MIX_T_TOL = 1e-7 def _grid_knots(curves, grid): """ Knots ``(T, H - H_lo)`` of every stream on the problem-table grid, the planner's model of the stream: at every grid temperature inside the stream's own range, its left and right enthalpy limits there (two knots where the curve has a flat). Every breakpoint of every curve is a grid point and the table is linear between grid points, so the planner's cascade on these knots is exactly the table's. Enthalpies are relative to the stream's H_lo, so that large absolute enthalpies cost the planner no precision. """ Ts, shift, Hl, Hr = grid['Ts'], grid['shift'], grid['Hl'], grid['Hr'] knots = [] for j, curve in enumerate(curves): k = np.arange(grid['k_lo'][j], grid['k_hi'][j] - 1, -1) # ascending T T = np.repeat(Ts[k] + shift[j], 2) H = np.column_stack((Hl[j, k], Hr[j, k])).ravel() - curve.H_lo keep = np.ones(T.size, dtype=bool) keep[1::2] = Hr[j, k] != Hl[j, k] knots.append((T[keep], H[keep])) return knots def _knot_T(knots, H, hot): """ Temperature of a knot curve at enthalpies `H`, linear between knots; a vertical stretch (a clipped non-equilibrium end) counts at its lowest temperature for a hot stream and at its highest for a cold one, as in the planner. """ T, Hk = knots rises = np.diff(Hk) > 0. if hot: keep = np.concatenate(([True], rises)) else: keep = np.concatenate((rises, [True])) return np.interp(H, Hk[keep], T[keep]) def _curve_tol_T(curve): """Largest distance [K] between a stream's linearized curve (and so its grid knots) and its exact states.""" if not curve.monotone: return 0. return max(curve.tol_T, curve.glide_error) def _interval_min(f, a, fa, b, fb): """ Minimum of a smooth function `f` on [a, b], given its end values. A minimum inside the interval shows at an end as a slope that points into it (f falls from `a`, or rises into `b`); both one-sided slopes are taken from a step of 1e-6 of the interval. Without such a slope the minimum is an end (the smooth pieces of temperature-enthalpy curves bend one way over a knot interval). Otherwise a scan of the interval brackets the dip and golden-section search narrows it to 1e-7 of the interval. Returns the smallest value found. """ eps = 1e-6 * (b - a) fa_ = f(a + eps) fb_ = f(b - eps) if fa_ >= fa and fb_ >= fb: return min(fa, fb) xs = [a, a + eps, *np.linspace(a, b, 9)[1:-1].tolist(), b - eps, b] fs = [fa, fa_, *[f(x) for x in xs[2:-2]], fb_, fb] k = int(np.argmin(fs)) if k in (0, len(xs) - 1): return fs[k] lo, x, hi, fx = xs[k - 1], xs[k], xs[k + 1], fs[k] g = 0.5 * (3. - 5.**0.5) # golden section xtol = 1e-7 * (b - a) while hi - lo > xtol: u = x + g * (hi - x) if hi - x > x - lo else x - g * (x - lo) fu = f(u) if fu < fx: if u > x: lo = x else: hi = x x, fx = u, fu elif u > x: hi = u else: lo = u return fx def _exchanger_approach(curves, knots, h, c, H_hot_in, H_cold_in, Q, T_min_app, fh=1., fc=1.): """ Exact-state check of one counter-current exchanger of duty `Q` in which stream `h` enters hot at `H_hot_in` and stream `c` enters cold at `H_cold_in` (enthalpies relative to each stream's H_lo). With stream splitting, `fh` and `fc` are the flow fractions of the hot and the cold branch in the exchanger: a branch at fraction f has its parent's states at f times the parent's enthalpy flow, so the duty moves its parent-equivalent enthalpy by ``Q / f``. The duty position q in [0, Q] (from the hot inlet and the cold outlet end) lies at ``H_hot_in - q / fh`` and ``H_cold_out - q / fc``, a knot H at ``(H_hot_in - H) fh`` or ``(H_cold_out - H) fc``; the states returned are parent-equivalent (what `_refine_knots` takes). At f = 1 every expression is the unsplit one, bit for bit (division and multiplication by 1. are exact). The positions are the ends and every knot and curve breakpoint inside the exchanger. Between two consecutive positions both knot curves are linear, so the planned approach (on the knots) is too, and each stream's exact states are within `_curve_tol_T` of its knots: an interval whose two ends have a planned approach of at least `T_min_app` plus that margin is feasible on the exact states. Every other interval is checked with `StreamCurve.T_exact` at its ends and midpoint and, where the exact approach is not linear (curved single-phase stretches and glides), searched for a minimum inside it (`_interval_min`). Returns the smallest approach found [K] (exact where evaluated) and the exact states ``(T_hot, H_hot, T_cold, H_cold)`` wherever the exact approach is below ``T_min_app - _APPROACH_TOL``. With ``T_min_app = inf`` every interval is checked, so the approach returned is the exact minimum over the exchanger and the states are all those evaluated. This is the only exact internal-approach check of the synthesis (the exchangers themselves, `HXprocess`, check their two terminals only, which misses an internal pinch at a phase change). """ hot, cold = curves[h], curves[c] H_hot_out, H_cold_out = H_hot_in - Q / fh, H_cold_in + Q / fc qs = [0., Q] for H in (knots[h][1], hot.H - hot.H_lo): qs.extend((H_hot_in - H[(H > H_hot_out) & (H < H_hot_in)]) * fh) for H in (knots[c][1], cold.H - cold.H_lo): qs.extend((H_cold_out - H[(H > H_cold_in) & (H < H_cold_out)]) * fc) qs = np.unique(np.clip(qs, 0., Q)) planned = (_knot_T(knots[h], H_hot_in - qs / fh, True) - _knot_T(knots[c], H_cold_out - qs / fc, False)) near = planned < T_min_app + _curve_tol_T(hot) + _curve_tol_T(cold) + 1e-9 limit = T_min_app - _APPROACH_TOL points = [] states = {} def exact(q): if q not in states: qh, qc = q / fh, q / fc T_hot = hot.T_exact(hot.H_lo + H_hot_in - qh, 'low') T_cold = cold.T_exact(cold.H_lo + H_cold_out - qc, 'high') states[q] = dT = T_hot - T_cold if dT < limit: points.append((T_hot, H_hot_in - qh, T_cold, H_cold_out - qc)) return states[q] worst = float(planned[~near].min()) if not near.all() else np.inf if qs.size == 1: if near[0]: worst = min(worst, exact(qs[0])) return worst, points for k in np.flatnonzero(near[:-1] | near[1:]): a, b = qs[k], qs[k + 1] fa, fm, fb = exact(a), exact(0.5 * (a + b)), exact(b) worst = min(worst, fa, fm, fb) if abs(fa + fb - 2. * fm) > 1e-9: # not linear: look for a dip worst = min(worst, _interval_min(exact, a, fa, b, fb)) return worst, points def _exact_approach(plan, duties, ends, curves, knots, T_min_app): """ `_exchanger_approach` of every exchanger in `duties` (duty by index into ``plan.exchangers``) at the enthalpies of the walk `ends` (see `_walk`), with the flow fractions of its branches (1 on a trunk). Returns the smallest approach [K], the violating exact states by stream, ``{stream: [(T_exact, H - H_lo), ...]}``, and the violating exchangers. """ worst = np.inf violations = {} bad = [] for n, Q in duties.items(): e = plan.exchangers[n] h, c = e.hot, e.cold approach, points = _exchanger_approach( curves, knots, h, c, ends[n, h][0], ends[n, c][0], Q, T_min_app, e.hot_frac, e.cold_frac ) worst = min(worst, approach) if points: bad.append(n) for T_hot, H_hot, T_cold, H_cold in points: violations.setdefault(h, []).append((T_hot, H_hot)) violations.setdefault(c, []).append((T_cold, H_cold)) return worst, violations, bad def _shrink(curves, knots, h, c, H_hot_in, H_cold_in, Q, T_min_app, fh=1., fc=1.): """ Largest duty ``Q' <= Q`` (to 1e-9 of Q) at which the exchanger of `_exchanger_approach` (branches at flow fractions `fh` and `fc`) keeps ``T_min_app - _APPROACH_TOL`` on the exact states. With both inlets fixed, a smaller duty lowers the cold stream's enthalpy (so its temperature) at every position and shortens the exchanger, so the approach can only grow: the feasible duties form an interval [0, Q'] and bisection finds its end. On branches too: duty position q lies at ``H_cold_in + (Q - q) / fc`` on the cold branch, which falls with Q, and at ``H_hot_in - q / fh`` on the hot one, whatever Q. """ def ok(x): return not _exchanger_approach(curves, knots, h, c, H_hot_in, H_cold_in, x, T_min_app, fh, fc)[1] lo, hi = 0., Q # a first guess from the local heat capacity flow rates saves most of # the bisection: the violations are within the chord error of the knots approach, _ = _exchanger_approach(curves, knots, h, c, H_hot_in, H_cold_in, Q, T_min_app, fh, fc) CP = 0. # of the branches: f times the parent's for j, f in ((h, fh), (c, fc)): T, H = knots[j] dT = np.diff(T) dH = np.diff(H) slopes = dH[dT > 0.] / dT[dT > 0.] if slopes.size: CP = max(CP, f * float(slopes.max())) guess = Q - 2. * (T_min_app - approach) * CP if 0. < guess < Q and ok(guess): lo = guess while hi - lo > 1e-9 * Q: mid = 0.5 * (lo + hi) if ok(mid): lo = mid else: hi = mid return lo def _repair(plan, duties, knots, is_hot, curves, T_min_app): """ Shrink every exchanger that falls short of ``T_min_app - _APPROACH_TOL`` on the exact states to its largest feasible duty (`_shrink`); the rest of its duty goes to the utilities. Shrinking a match moves the later stages of both its streams toward their inlets, which never reduces another exchanger's approach (the curves are monotone), so one pass suffices; the loop only guards against rounding. A branch exchanger shrinks with its flow fractions; its later branch stages and the mix (at the split enthalpy -/+ the surviving branch duties, see `_walk`) move toward the inlet too. Returns the new duties and the changes, ``[(n, Q_before, Q_after)]``. """ duties = dict(duties) changes = [] for _ in range(len(duties) + 1): ends = _walk(plan, duties, knots, is_hot)[0] bad = _exact_approach(plan, duties, ends, curves, knots, T_min_app)[2] if not bad: break for n in bad: e = plan.exchangers[n] ends = _walk(plan, duties, knots, is_hot)[0] Q = _shrink(curves, knots, e.hot, e.cold, ends[n, e.hot][0], ends[n, e.cold][0], duties[n], T_min_app, e.hot_frac, e.cold_frac) changes.append((n, duties[n], Q)) duties[n] = Q return duties, changes def _refine_knots(knots, violations): """ Return `knots` with the exact states of `violations` inserted (or, at an existing knot, i.e. a chord point inside a glide, corrected), clamped between the neighbouring knot temperatures so that every curve stays monotone. """ knots = list(knots) for j, points in violations.items(): T, H = knots[j] T, H = T.tolist(), H.tolist() for T_new, H_new in sorted(points, key=lambda p: p[1]): i = int(np.searchsorted(H, H_new)) if i < len(H) and H[i] == H_new: lo = T[i - 1] if i > 0 else T_new hi = T[i + 1] if i + 1 < len(T) else T_new T[i] = min(max(T_new, lo), hi) else: lo = T[i - 1] if i > 0 else T_new hi = T[i] if i < len(T) else T_new T.insert(i, min(max(T_new, lo), hi)) H.insert(i, H_new) knots[j] = (np.array(T), np.array(H)) return knots def _enthalpy_limit(curve, s_in, H, hot): """ `H` if `HXprocess` can take it as the enthalpy limit of the stream of `curve` entering an exchanger in state `s_in`, else None (the other stream's limit then sets the duty). `HXprocess` flashes the stream to the limit and rejects an equilibrium state on the wrong side of the inlet temperature (a heated stream colder than its inlet). On a monotone curve that happens only strictly inside a non-equilibrium end jump (see `StreamCurve.jumps`). A point-load stream's (non-monotone curve's) equilibrium states are not ordered with its real inlet temperature: e.g. a liquid fed above its bubble point and boiled to its dew point, colder than its feed, has every state past its real inlet on the wrong side, its outlet included. It enters its first exchanger at equilibrium at its inlet enthalpy instead (see `_first_inlet`), from which its states are ordered, unless that flash failed. So the equilibrium state at `H` is compared with the inlet directly. """ if curve.monotone: tol = curve.tol_H inside = any(H_a + tol < H < H_b - tol for H_a, H_b in curve.jumps) return None if inside else H try: T = curve.state_at_H(H).T except Exception: return None past = T <= s_in.T + _T_SIDE if hot else T >= s_in.T - _T_SIDE return H if past else None def _first_inlet(stream, point_load, T_point, hot): """ Bring `stream`, a copy of a process stream's real inlet, in place to the state in which the stream enters its first process exchanger: the real inlet, except that a point-load stream (non-monotone `StreamCurve`, whose whole duty is planned at its outlet temperature `T_point`; `hot` if it is cooled) enters at equilibrium at its inlet enthalpy and pressure, which lies on the plan's side of `T_point` (see `hensmith._curves._point_load_inlet`; kept as given if that flash fails). The enthalpy is the same either way, so no balance changes. `HXprocess` judges a match by the inlet temperatures (the hotter inlet is the hot stream, no heat moves unless they are more than `dT` apart, and the partner's outlet is capped at the inlet temperature -/+ `dT`), so a point-load stream's real inlet, on the wrong side of `T_point` by definition, would make it refuse or cut short a match that the plan keeps `T_min_app` for at `T_point`. E.g. a reboiler fed as a liquid above its boiling point enters as the vapor-liquid mixture it flashes to, and a vapor fed below its dew point (e.g. the ideal-thermo copy of a saturated vapor whose ideal dew point is higher) as the mixture it partially condenses to, hotter than its feed. """ if point_load: stream.copy_like(_point_load_inlet(stream, T_point, hot)) class _RealizationError(Exception): """An exchanger of the plan could not be simulated.""" def __init__(self, n, ID, error): super().__init__(n, ID, error) self.n, self.ID, self.error = n, ID, error class _SplitRealizationError(Exception): """A splitter or the mixer of split `k` (index into ``plan.splits``) could not be simulated; `branch_exchangers` holds its branch exchangers as ``(index into plan.exchangers, ID)``.""" def __init__(self, k, branch_exchangers, error): super().__init__(k, branch_exchangers, error) self.k, self.branch_exchangers = k, branch_exchangers self.error = error
[docs] class StreamSplit: """ A split of one process stream into parallel branches that re-join in a mixer, as realized by `synthesize_network` (``info['splits']``). Attributes ---------- stream : int The stream's index. side : {'above', 'below'} The side of the pinch. index : int Ordinal of the split among the stream's splits on its side, from 1 in flow order (its IDs end in ``_<index>`` from 2 on). fractions : tuple[float] Flow fraction of every branch; they sum to 1 within round-off. splitters : list[biosteam.Splitter] The splitter chain, IDs ``Split_<stream>_<hs|cs>[_<index>]`` (element 1), then that plus ``_b<c>`` (element c): element c sends ``f_c / (f_c + ... + f_n)`` of its feed to its first outlet (branch c - 1) and the rest, by its second outlet, to element c + 1; the last element's second outlet is the last branch. mixer : biosteam.Mixer The rigorous mixer where the branches re-join (inlet b is branch b), ID ``Mix_<stream>_<hs|cs>[_<index>]``. branches : list[list[HXprocess]] The process exchangers of every branch, in flow order. A branch whose exchangers were all dropped is empty: its splitter outlet feeds the mixer directly (a bypass). position : int Number of the stream's trunk process exchangers before the split. isothermal : bool Every branch ends at the stream's state at `H_mix`: the branches re-join at one temperature. H_split, H_mix : float Planned full-flow enthalpies of the stream where it splits and where it re-joins [kJ/hr]. """ __slots__ = ('stream', 'side', 'index', 'fractions', 'splitters', 'mixer', 'branches', 'position', 'isothermal', 'H_split', 'H_mix') def __init__(self, stream, side, index, fractions, splitters, mixer, branches, position, isothermal, H_split, H_mix): self.stream, self.side, self.index = stream, side, index self.fractions, self.splitters, self.mixer = (fractions, splitters, mixer) self.branches, self.position = branches, position self.isothermal, self.H_split, self.H_mix = isothermal, H_split, H_mix def outlet(self, b): """``(splitter, port)`` where branch `b` leaves the chain.""" return ((self.splitters[b], 0) if b < len(self.splitters) else (self.splitters[-1], 1)) def __repr__(self): fractions = ', '.join(f'{f:.4g}' for f in self.fractions) return (f'<StreamSplit {self.splitters[0].ID}: stream {self.stream} ' f'{self.side}, {len(self.fractions)} branches ({fractions})>')
def _walk(plan, duties, knots, is_hot): """ Enthalpies (relative to each stream's H_lo) at which every stream enters and leaves each of its exchangers in `duties` (duty by index into ``plan.exchangers``), walking it in flow order from its inlet (``plan.stages``), and at which it enters its utility; plus the pair index of every exchanger (its rank among the exchangers of the same (side, hot, cold) pair, in the order the hot stream meets them). A smaller duty (a dropped or shrunk match) shifts the later stages of both streams toward their inlets. With stream splitting (``plan.splits``), every stream is walked along ``plan.paths``: a split's branches start at the split enthalpy and a branch exchanger of flow fraction f moves the branch by its duty over f, so its `ends` are parent-equivalent (the enthalpies of the full flow in the branch's state); the stream re-joins at the split enthalpy -/+ the sum of the surviving branch duties, which the fractions leave free of round-off. A dropped branch exchanger shortens its branch (a branch left without exchangers bypasses), and later stages move toward the inlet by the duty lost (`_split_nodes` gives the split enthalpies). """ ends = {} last = [] if not plan.splits: for j, hot in enumerate(is_hot): H = knots[j][1][-1] if hot else 0. for n in plan.stages[j]: if n not in duties: continue Q = duties[n] H_next = H - Q if hot else H + Q ends[n, j] = (H, H_next) H = H_next last.append(H) else: for j, hot in enumerate(is_hot): H = knots[j][1][-1] if hot else 0. for item in plan.paths[j]: if isinstance(item, Split): H = _walk_split(item, duties, ends, H, hot) continue if item not in duties: continue Q = duties[item] H_next = H - Q if hot else H + Q ends[item, j] = (H, H_next) H = H_next last.append(H) count = {} pair_index = {} for j, hot in enumerate(is_hot): if not hot: continue for n in plan.stages[j]: if n not in duties: continue e = plan.exchangers[n] key = (e.side, e.hot, e.cold) count[key] = pair_index[n] = count.get(key, 0) + 1 return ends, last, pair_index def _branch_duty(split, duties): """Sum (exactly rounded) of the duties of `split`'s branch exchangers in `duties`.""" return math.fsum([duties[n] for ns in split.branches for n in ns if n in duties]) def _walk_split(split, duties, ends, H, hot): """ `_walk` over `split` (a `hensmith._splitting.Split` of a stream that is cooled if `hot`) from the split enthalpy `H`: fill the `ends` of its branch exchangers in `duties`, each branch from `H` by duty over fraction, and return the enthalpy where the branches re-join. """ j = split.stream for f, ns in zip(split.fractions, split.branches): Hb = H for n in ns: if n not in duties: continue Q = duties[n] / f H_next = Hb - Q if hot else Hb + Q ends[n, j] = (Hb, H_next) Hb = H_next D = _branch_duty(split, duties) return H - D if hot else H + D def _split_nodes(plan, duties, ends): """ Where the streams of a plan with splits (``plan.splits``) split and re-join, for the exchangers in `duties` and their walk `ends` (see `_walk`, whose arithmetic this repeats). Returns ------- first_nodes : dict[int, tuple[int]] For every stream, the first exchanger of every branch of the split that is its first node (the first item of ``plan.paths[j]`` with an exchanger in `duties`), in branch order: they all take the stream's real inlet (`_realize`), as that split's splitter chain does (`_realize_splits`). Empty if the first node is not a split. split_ends : list[tuple or None] For every split of ``plan.splits``, ``(H_split, [H_end, ...], H_mix)``: the enthalpies (relative to the stream's H_lo) where it splits, where each branch ends (a parent-equivalent enthalpy; ``H_split`` for a branch without exchangers, which bypasses) and where the branches re-join. None for a split whose branches have no exchanger left: it is not realized, the stream passes it unchanged. first_splits : dict[int, int] For every stream whose first node is a split, that split's index into ``plan.splits`` (the one rule for both of the above). """ split_ends = [] for split in plan.splits: j = split.stream live = [[n for n in ns if n in duties] for ns in split.branches] n = next((ns[0] for ns in live if ns), None) if n is None: split_ends.append(None) continue H = ends[n, j][0] D = _branch_duty(split, duties) H_mix = H - D if plan.exchangers[n].hot == j else H + D split_ends.append((H, [ends[ns[-1], j][1] if ns else H for ns in live], H_mix)) order = {id(split): k for k, split in enumerate(plan.splits)} first_nodes, first_splits = {}, {} for j, path in plan.paths.items(): first_nodes[j] = () for item in path: if not isinstance(item, Split): if item in duties: break continue k = order[id(item)] if split_ends[k] is not None: first_nodes[j] = tuple( next(n for n in ns if n in duties) for ns in item.branches if any(n in duties for n in ns)) first_splits[j] = k break return first_nodes, split_ends, first_splits def _discard(units): """Remove units, and the streams connected to them, from the registry of the active flowsheet (after a failed realization).""" for unit in units: for s in (*unit.ins, *unit.outs): bst.main_flowsheet.stream.discard(s) bst.main_flowsheet.unit.discard(unit) def _realize(plan, duties, curves, knots, streams_inlet, is_hot, T_min_app): """ Build and run one plain `HXprocess` per exchanger in `duties` (duty by index into ``plan.exchangers``), in plan order. Raise `_RealizationError` (after discarding the units built so far) if one of them cannot be simulated. Returns ``(units, first, last)``: the units by exchanger index, each stream's first exchanger (None if it has none) and the enthalpy at which it enters its utility (relative to its H_lo). A branch exchanger of a split stream (flow fraction f) runs f of the stream's flow in the states of the full stream: its inlet is the full stream's state at the branch's (parent-equivalent) inlet enthalpy, scaled by f, and its enthalpy limit f times the full stream's at the planned outlet (`_enthalpy_limit` judges the full-flow state). The first exchanger of every branch of a split at a stream's inlet takes the real inlet (`_split_nodes`). """ ends, last, pair_index = _walk(plan, duties, knots, is_hot) first = [next((n for n in plan.stages[j] if n in duties), None) for j in range(len(is_hot))] first_nodes = _split_nodes(plan, duties, ends)[0] if plan.splits else {} units = {} dT = T_min_app - _APPROACH_TOL for n in sorted(duties): e = plan.exchangers[n] h, c = e.hot, e.cold suffix = '' if pair_index[n] == 1 else f'_{pair_index[n]}' if e.side == 'above': ID = f'HX_{c}_{h}_hs{suffix}' ports = (c, h) fractions = (e.cold_frac, e.hot_frac) else: ID = f'HX_{h}_{c}_cs{suffix}' ports = (h, c) fractions = (e.hot_frac, e.cold_frac) ins, outs, H_lims = [], [], [] for j, f in zip(ports, fractions): curve = curves[j] H_in, H_out = ends[n, j] if first[j] == n or n in first_nodes.get(j, ()): s = _copy(streams_inlet[j]) # the real inlet state _first_inlet(s, not curve.monotone, curve.T_out, is_hot[j]) else: s = curve.state_at_H(curve.H_lo + H_in) s.ID = f's_{j}__{ID}' # a planned outlet whose equilibrium state is not past the inlet # (inside a non-equilibrium end jump, or a point load's): leave # it to the other stream's limit H_lim = _enthalpy_limit(curve, s, curve.H_lo + H_out, is_hot[j]) if f != 1.: # a branch: f of the flow, in the same states s.scale(f) if H_lim is not None: H_lim *= f ins.append(s) outs.append(s.copy(f'{ID}__s_{j}')) H_lims.append(H_lim) hx = bst.HXprocess(ID=ID, ins=ins, outs=outs, H_lim0=H_lims[0], H_lim1=H_lims[1], dT=dT, thermo=ins[0].thermo) units[n] = hx try: hx._run() except Exception as error: _discard(units.values()) raise _RealizationError(n, ID, error) return units, first, last def _realize_splits(plan, duties, units, curves, knots, streams_inlet, is_hot): """ Build and run, once each, the splitter chain and the rigorous mixer of every split of ``plan.splits`` that keeps an exchanger in `duties` (duty by index into ``plan.exchangers``), after `_realize` built its exchangers `units` (by exchanger index). A split without one is not realized: the stream passes it as a trunk. The splitter chain's feed is the stream's real inlet if the split is its first node (as its branches' first exchangers, `_split_nodes`), else its state at the split enthalpy. The mixer's inlet b carries fraction f_b of the flow: all in the stream's state at the mix enthalpy if every branch ends there (an isothermal re-join), else each in the state at its branch's end (parent-equivalent, see `_walk`). Its outlet starts at the planned state (the full stream at the mix enthalpy), which only speeds up the flash: where thermosteam's PH flash disagrees with the stream's curve (inside some two-phase glides), the outlet lands off the plan whatever its start, and the check on T reports it. Such a mixer is reported, not undone: the PH flash at that enthalpy lands there from every start state (measured), so a process exchanger of the stream ending there would too, split or not. Returns ------- splits : list[StreamSplit] The realized splits, in the order of ``plan.splits``. deviations : list[dict] The mixers whose outlet is off the plan, each as ``dict(ID, T_plan, T, H_plan, H)``: ``|H - H_plan|`` above `_DUTY_TOL` times the stream's duty, ``H_plan`` being the sum of its inlets' enthalpies (the binding check for real thermo, whose rigorous outlet is H of the converged T), or ``|T - T_plan|`` above `_MIX_T_TOL`, ``T_plan`` being the planned state's temperature. Raises ------ _SplitRealizationError If a splitter or a mixer cannot be simulated, after discarding the units built for the splits and `units`. """ ends = _walk(plan, duties, knots, is_hot)[0] _, split_ends, first_splits = _split_nodes(plan, duties, ends) tolQ = plan.info['tolQ'] # each realized split's ordinal (per stream and side, from 1 in flow # order) and the stream's trunk exchangers before it order = {id(split): k for k, split in enumerate(plan.splits)} where = {} for path in plan.paths.values(): count, trunk = {}, 0 for item in path: if not isinstance(item, Split): trunk += item in duties continue k = order[id(item)] if split_ends[k] is None: continue count[item.side] = count.get(item.side, 0) + 1 where[k] = (count[item.side], trunk) splits, deviations, built = [], [], [] def run(unit, k, live): try: unit._run() except Exception as error: branch_exchangers = [(n, units[n].ID) for ns in live for n in ns] _discard([*built, *units.values()]) raise _SplitRealizationError(k, branch_exchangers, error) for k, split in enumerate(plan.splits): if split_ends[k] is None: continue H_split, H_ends, H_mix = split_ends[k] j, fractions = split.stream, split.fractions curve = curves[j] index, position = where[k] base = f"Split_{j}_{'hs' if split.side == 'above' else 'cs'}" if index > 1: base += f'_{index}' mix_ID = 'Mix' + base[len('Split'):] live = [[n for n in ns if n in duties] for ns in split.branches] if first_splits.get(j) == k: # the stream's first node s = _copy(streams_inlet[j]) # the real inlet state _first_inlet(s, not curve.monotone, curve.T_out, is_hot[j]) else: s = curve.state_at_H(curve.H_lo + H_split) s.ID = f's_{j}__{base}' splitters = [] for c in range(1, len(fractions)): ID = base if c == 1 else f'{base}_b{c}' # tail sums: no cancellation, and the last element's rest is # exactly its complement r = fractions[c - 1] / math.fsum(fractions[c - 1:]) splitter = bst.Splitter(ID, ins=s, outs=(s.copy(f'{ID}__s_{j}_0'), s.copy(f'{ID}__s_{j}_1')), split=r, thermo=s.thermo) built.append(splitter) splitters.append(splitter) run(splitter, k, live) s = splitter.outs[1] isothermal = all(abs(H - H_mix) <= _ISO_TOL * tolQ for H in H_ends) ins = [] for b, (f, H) in enumerate(zip(fractions, H_ends)): s = curve.state_at_H(curve.H_lo + (H_mix if isothermal else H)) s.ID = f's_{j}_{b}__{mix_ID}' s.scale(f) ins.append(s) outlet = curve.state_at_H(curve.H_lo + H_mix) # the planned state outlet.ID = f'{mix_ID}__s_{j}' T_plan = outlet.T mixer = bst.Mixer(mix_ID, ins=ins, outs=outlet, rigorous=True, thermo=outlet.thermo) built.append(mixer) run(mixer, k, live) out = mixer.outs[0] H_plan = math.fsum([s.H for s in mixer.ins]) if (abs(out.H - H_plan) > _DUTY_TOL * abs(curve.H_out - curve.H_in) or abs(out.T - T_plan) > _MIX_T_TOL): deviations.append(dict(ID=mix_ID, T_plan=T_plan, T=out.T, H_plan=H_plan, H=out.H)) splits.append(StreamSplit( j, split.side, index, tuple(fractions), splitters, mixer, [[units[n] for n in ns] for ns in live], position, isothermal, curve.H_lo + H_split, curve.H_lo + H_mix)) return splits, deviations
[docs] def synthesize_network(hus, T_min_app=5., Qmin=1e-3, force_ideal_thermo=False, avoid_recycle=False, sort_hus_by_T=False, info=None, stream_splitting=False): """ Synthesize a heat exchanger network for the process streams behind a set of utility heat exchangers: pinch analysis (`problem_table`), then a pinch-outward plan that reaches the minimum energy requirement (MER) targets whenever the search finds an unsplit network that does, realized with one `HXprocess` per match and one rigorous `HXutility` per stream. By default no stream is split; with `stream_splitting`, a side of the pinch that no unsplit network serves at MER is planned with stream splits and reaches the targets. Parameters ---------- hus : list[HeatUtility] One heat utility per process stream; `hu.unit` is the original heat exchanger (its `ins[0]`/`outs[0]` are the stream's end states) and the sign of `hu.duty` marks the stream: positive = heated (cold stream), negative = cooled (hot stream); zero-duty utilities are dropped. Heating utilities are placed before cooling utilities; within each group the given order is kept unless `sort_hus_by_T`. All returned per-stream arrays and lists are indexed in that rearranged order (the stream index), which also breaks ties in the planner's search. T_min_app : float, optional Minimum approach temperature [K]: kept on the exact stream states at both ends of and everywhere inside every process exchanger, and used to shift hot streams in the problem table. Defaults to 5. Qmin : float, optional Planned exchangers with a duty below this [kJ/hr] are dropped and their duty left to the utilities (a large value can cost MER). Defaults to 1e-3. force_ideal_thermo : bool, optional Analyze copies of the streams with ideal thermodynamics (``thermo.ideal()``); the synthesized exchangers inherit that thermo. Defaults to False. avoid_recycle : bool, optional Never match the same (hot, cold) pair twice anywhere, so no two exchangers connect the same pair of streams (a second exchanger between them can form a recycle loop in the network). This forbids the repeated matches that some unsplit MER networks need. Defaults to False. sort_hus_by_T : bool, optional Sort the heating utilities by inlet temperature, descending, and the cooling utilities ascending, before analysis. Defaults to False. info : dict, optional If given, filled with the synthesis report: 'status' ('mer' if the realized network's utilities equal the targets, else 'best_effort'), 'Q_hot_target' and 'Q_cold_target' (the problem table's targets), 'Q_hot_plan' and 'Q_cold_plan' (the planned utilities), 'Q_hot' and 'Q_cold' (the utilities of the realized network, from the simulated exchanger duties), 'penalty' (``Q_hot_plan - Q_hot_target``), 'sides' (per side of the pinch: status, method, work, proof of a needed split, gaps, units), 'plan_targets' (the planner's own cascade in the first round: Q_hot, Q_cold, pinch_T, cut), 'refine_rounds', 'min_approach' (the smallest approach inside any process exchanger [K]; exact on the stream states wherever it is within the curves' linearization tolerance of `T_min_app`, else from the knots), 'deviations' (exchangers whose simulated duty differs from the plan), 'qmin_dropped' (matches dropped by `Qmin`), 'repaired' (matches shrunk to keep `T_min_app` on the exact states, see Notes), 'dropped' (matches that could not be simulated; normally empty) and 'point_loads' (the indices of the streams whose outlet temperature does not move with their duty, e.g. an isothermal condenser or a reboiler fed as a liquid above its boiling point, so that their whole duty is a point load at the outlet temperature; each enters its first process exchanger at equilibrium at its inlet enthalpy, see Notes). With `stream_splitting` also 'stream_splitting' (True), 'splits' (the realized splits, a list of `StreamSplit`) and 'split_deviations' (mixers whose outlet is off the planned state; normally empty); each side in 'sides' then also has 'split' (None for a side that did not try to split, else the chosen candidate and its network signature, both None if no candidate was found, see `hensmith._planner.Plan`) and its method is 'split-<candidate>' when it splits. Required with `stream_splitting`, which raises a ValueError without it (the splitters and mixers are returned only there). stream_splitting : bool, optional Allow a process stream to be split into parallel branches that re-join. A side of the pinch that no unsplit network serves at the minimum energy requirement (a pinch-rule proof, or an unsplit search that leaves a utility penalty) is planned with splits instead, and then reaches the MER targets exactly on the planner's knots (see Notes, "Stream splitting"). Sides that an unsplit network serves are never split, so a problem that needs no split gets the same network as with the default. The branches are realized with `biosteam.Splitter` chains and rigorous `biosteam.Mixer` units, which are adiabatic and cost nothing; their structure is reported in ``info['splits']`` (`synthesize_network`) and ``synthesis_info['splits']`` (`HeatExchangerNetwork`). With `avoid_recycle`, a split that would repeat a stream pair is not used, and MER is then not guaranteed. Defaults to False. Returns ------- HXs_hot_side : list[HXprocess] Process exchangers of the hot-side (above-pinch) design, in plan order (from the pinch outward), IDs ``HX_<cold>_<hot>_hs``; ``ins``/``outs`` [0] is the cold stream and [1] the hot stream. HXs_cold_side : list[HXprocess] Process exchangers of the cold-side (below-pinch) design, in plan order, IDs ``HX_<hot>_<cold>_cs``; ``ins``/``outs`` [0] is the hot stream and [1] the cold stream. The n-th exchanger (n >= 2) of the same pair on the same side, counted in the order the hot stream meets them, gets the suffix ``_<n>`` (e.g. ``HX_3_2_cs_2``). new_HX_utils : list[HXutility] One rigorous utility exchanger per stream (possibly of zero duty) bringing it from its last process exchanger to its outlet enthalpy, IDs ``Util_<index>_cs`` (hot streams) / ``Util_<index>_hs`` (cold streams); listed hot streams first. hxs : list[Unit] The original heat exchangers, in stream order. T_in_arr, T_out_arr : numpy.ndarray Inlet and (quenched) outlet temperatures of each stream [K]. pinch_T_arr : numpy.ndarray Per-stream pinch temperature [K] (informational): the process pinch on the stream's own scale when the stream crosses it (`ProblemTable.pinch_T` for a cold stream, that plus `T_min_app` for a hot one); the inlet temperature of a stream whose inlet already lies past the pinch in its direction of flow, or that is isothermal or non-monotone; the outlet temperature of a stream that ends before reaching the pinch. C_flow_vector : numpy.ndarray Heat capacity flow rate of each process stream, ``|H_out - H_in| / |T_in - T_out|`` [kJ/hr/K] from its inlet and quenched outlet (the temperature difference is replaced by 1e-12 for an isothermal stream, which therefore ranks as a very large flow rate). hx_utils_rearranged : list[HeatUtility] The heat utilities of `hus` in stream order. streams_inlet : list[Stream] One copy of each stream's inlet, in stream order, as prepared for the analysis (ideal-thermo copies if `force_ideal_thermo`). The network works on further copies, so these keep their inlet state. stream_HXs_dict : dict[int, list[Unit]] For each stream index, its process exchangers in flow order, then its utility exchanger. With splits, the order is topological: the exchangers before a split, those of its branches (branch by branch, each in flow order), then those after it. hot_indices, cold_indices : list[int] Stream indices of the hot and cold streams. Notes ----- *Curves and targets.* Every stream's outlet is quenched to equilibrium at its own enthalpy and described by a piecewise-linear temperature- enthalpy curve (see `problem_table`), built once. The problem table [Kemp07]_ on the union of all breakpoints gives the targets, the pinch and the side of the pinch that point loads at the pinch temperature belong to. The planner models each stream by its knots on that grid, which reproduces the table's cascade exactly. *Planner.* Each stream is cut at the pinch; above it the hot streams, below it the cold streams must be served completely by process matches ("musts"), while the partners ("flexes") leave any remainder to a utility at their far end. A depth-first search builds each side from the pinch outward, one match at a time. Every match keeps `T_min_app` at every knot (so internal pinches, e.g. a condensing vapor against a boiling mixture, are respected), and every step keeps the problem table of the remaining problem feasible (remaining problem analysis [Smith05]_, as a closed-form bound on the duty). At every level where that table is tight, the pinch design rules [LH83]_ (see also [Seider17]_, Chapter 9; number and heat-capacity-flow rules, generalized to isothermal segments, which can serve several partners in series) must hold; at the pinch itself a violation proves that MER needs stream splitting. Candidate duties are the largest feasible one and a finite set of events (a stream ticked off, a partner saved for another stream, a switch of partner, a return). The same pair may be matched repeatedly, which emulates a split by series alternation. Budgets are counted in deterministic work units, so results do not depend on machine speed. A branch and bound then reduces the number of exchangers. A side that is proven to need splits, or whose search runs out of budget, gets a best-effort plan (unless `stream_splitting`, see "Stream splitting" below): heat a must cannot place is moved to its pinch end, where it crosses the pinch at the cost of an equal amount of extra hot and cold utility (the penalty), minimized by greedy dives and a bisection of these gaps. See `hensmith._planner` for the details. *Realization.* Each stream is walked in flow order from its inlet: a hot stream through its hot-side matches from its inlet end, then its cold-side matches, then its cooler; a cold stream through its cold-side matches, then its hot-side matches, then its heater. Each match becomes a plain `HXprocess` whose two enthalpy limits (`H_lim0`, `H_lim1`) are the planned outlet enthalpies, so that its duty reproduces the plan; its `dT` is ``T_min_app - 1e-6`` K, only a guard against rounding (the approach is enforced by the plan and the check below). A planned outlet whose equilibrium state is not past the stream's state at the exchanger inlet cannot be a limit (`HXprocess` rejects it): one strictly inside a non-equilibrium end jump (see `StreamCurve.jumps`), or on a point-load stream colder (hotter) than its inlet state when heated (cooled). That stream's limit is left out and the other stream's sets the duty; a match in which neither stream can take a limit runs to its `dT` guard (a deviation if its duty differs). A stream's first exchanger gets its real inlet, except a point-load stream (whose outlet temperature does not move with its duty, so the plan places its whole duty there, a temperature its real inlet lies beyond): it enters at equilibrium at its inlet enthalpy, which lies on the plan's side of its outlet temperature (a reboiler fed as a liquid above its boiling point enters as the mixture it flashes to; a vapor fed below its dew point, e.g. under `force_ideal_thermo`, as the mixture it partially condenses to), because `HXprocess` compares the inlet temperatures with `dT` and would refuse or cut short a match planned there. Later exchangers get the stream's exact state at the planned enthalpy. Every exchanger is simulated once; one whose duty differs from the plan is reported in `info`. Each stream ends in one rigorous `HXutility` to its outlet enthalpy; an `AssertionError` is raised if it does not reproduce the quenched outlet within tolerance. *Exactness.* The knots are exact at grid points but chords in between (at most 0.002 K off inside glides and curved single-phase stretches). Every planned exchanger is therefore checked on the exact stream states wherever its planned approach is within that margin of `T_min_app`. Where a MER plan falls short by more than 1e-6 K, the exact states are inserted as knots and the network is planned again (at most three rounds). A best-effort plan (or a MER plan still short after the last round) instead has each violating match shrunk to the largest duty that keeps the approach, the rest going to the utilities: with its inlets fixed a smaller duty can only raise a match's approach, and the later stages of both streams move toward their inlets, which never reduces another match's approach. Constant heat capacity streams never need either step. *Stream splitting.* With `stream_splitting`, a side that no unsplit network serves at MER is planned with splits (see `hensmith._splitting`). A branch exchanger of flow fraction f runs f of its stream's flow in the full stream's states: its inlet is the stream's state at the branch's inlet enthalpy scaled by f, and its enthalpy limit f times the full stream's; the exact check follows each branch on its parent's curve with enthalpy steps of duty over f. Each split becomes a chain of `biosteam.Splitter` units (one fewer than its branches, fed with the real inlet if the split is the stream's first node) and a rigorous `biosteam.Mixer`, whose outlet starts at the planned state; a mixer outlet off that state is reported in ``info['split_deviations']``. Each refine round re-plans a split side's previous pick first and keeps it while it plans the same network (its signature, with the fractions the refined knots move). If exchangers on a split side still violate after the last refine round, that network is excluded and the side re-planned (at most two more rounds): with another network if the side has one left, else with the same one on the refined knots (a side's last candidate is never excluded), which ends the retries. If that does worse, the best MER plan of the rounds is restored. A split whose splitters or mixer cannot be simulated becomes a trunk (its branch exchangers are dropped, as in ``info['dropped']``). *Guarantees and limits.* The utilities are never below the targets. Every process exchanger keeps ``T_min_app - 1e-6`` K on the exact states at its ends and at every checked position inside it, and the heat balance closes on every stream. 'mer' is reported only if the realized network reaches the targets. The result is deterministic. Completeness is empirical, not proven: every pruning test is a necessary condition, so a missed MER network can only come from the finite set of candidate duties, the caps on repeated pairs or the work budgets; the planner reached MER on every unsplit-feasible problem of a certified benchmark of about 1,700 problems with 2-40 streams. Networks whose match order is cyclic cannot be represented. An unsplit MER network can need many exchangers (series alternation approaches a split only in the limit); MER always takes precedence over the number of units. By default, problems that need stream splits get a best-effort network whose penalty is small but not minimal in general, and a side that needs splits without a pinch-rule proof spends its whole MER budget before the best-effort step. With `stream_splitting` (and without `avoid_recycle`), every side that no unsplit network serves has a split plan at MER on the planner's knots: the vertical core of `hensmith._splitting` always yields one (Theorem M there), up to the part of the root deficit that the cascade's own tolerances already absorbed into the targets (at most about 1e-9 of the total duty). The remaining gap is the realization. With constant heat capacities the knots are exact, and the realized network reaches the targets to round-off. With real thermodynamics the knots are chords, so a split plan can fall short of `T_min_app` on the exact states by up to the chords' tolerance; the refine rounds close that as they do for unsplit plans, with up to two more rounds that exclude the violating network (see "Stream splitting" above), and only an exchanger still short after them is shrunk (reported in 'repaired', with status 'best_effort'). A rigorous mixer's outlet enthalpy differs from the sum of its inlets by at most its flash residual, which the stream's utility takes. The test suite reaches 'mer' with splits on all 38 problems of its corpus that provably need them (25 with constant heat capacities, 13 with real thermodynamics) and on the three such regression systems. The number of exchangers is minimized only among the candidate split plans a side generates, and splitters and mixers are not costed. Thermosteam's TP flashes fail silently inside the glides of some mixtures (e.g. water-ethanol with 20-50 % ethanol); an exchanger simulated there can deviate from its plan (reported in `info['deviations']`), and a mixer's outlet can land off its planned state (reported in ``info['split_deviations']``). `HeatExchangerNetwork` calls this function, rewires each stream's stages in series (the branches of a split in parallel, from its splitter chain to its mixer), converges the network as a `System` and costs it. Examples -------- Problem r002: one hot stream against three cold ones (heat capacity flow rates in kW/K, temperatures 300 K above those of the classic problem, T_min_app = 10 K). Its only unsplit MER network matches the hot stream twice with the same cold stream. A constant heat capacity pseudo-component makes 1000 kmol/hr of fluid per kW/K: >>> import biosteam as bst, thermosteam as tmo >>> from hensmith.hxn_synthesis import synthesize_network >>> Fluid = tmo.Chemical('Fluid', search_db=False, phase='l', MW=1., ... Cn=3.6, default=True) >>> bst.settings.set_thermo([Fluid], cache=True) >>> def process_stream(ID, T_in, T_out, CP): ... inlet = bst.Stream(ID + '_in', Fluid=1000. * CP, T=T_in, ... units='kmol/hr') ... hx = bst.HXutility(ID, ins=inlet, T=T_out, rigorous=False) ... hx.simulate() ... return hx >>> units = [process_stream('C1', 440., 470., 1.), ... process_stream('C2', 400., 420., 1.), ... process_stream('C3', 420., 550., 2.), ... process_stream('H1', 520., 350., 4.)] >>> hus = [hx.heat_utilities[0] for hx in units] >>> info = {} >>> result = synthesize_network(hus, T_min_app=10., info=info) >>> HXs_hot_side, HXs_cold_side, new_HX_utils = result[:3] >>> for hx in HXs_hot_side + HXs_cold_side: ... print(hx.ID, round(hx.Q / 3600., 6), 'kW') HX_3_2_cs 160.0 kW HX_3_0_cs 30.0 kW HX_3_2_cs_2 20.0 kW HX_3_1_cs 20.0 kW >>> info['status'] 'mer' The utilities equal the MER targets, 80 kW of heating and 450 kW of cooling: >>> duties = [(hx.outs[0].H - hx.ins[0].H) / 3600. for hx in new_HX_utils] >>> round(sum(Q for Q in duties if Q > 0), 6), round(-sum(Q for Q in duties if Q < 0), 6) (80.0, 450.0) >>> round(info['Q_hot_target'] / 3600., 6), round(info['Q_cold_target'] / 3600., 6) (80.0, 450.0) References ---------- .. [LH83] Linnhoff, B., & Hindmarsh, E. (1983). The pinch design method for heat exchanger networks. Chemical Engineering Science, 38(5), 745-763. .. [Kemp07] Kemp, I. C. (2007). Pinch Analysis and Process Integration (2nd ed.). Butterworth-Heinemann. .. [Smith05] Smith, R. (2005). Chemical Process Design and Integration. Wiley. .. [Seider17] Seider, W. D., Lewin, D. R., Seader, J. D., Widagdo, S., Gani, R., & Ng, M. K. (2017). Product and Process Design Principles. Wiley. Heat Exchanger Networks (Chapter 9). """ if stream_splitting and info is None: raise ValueError('stream_splitting=True needs an info dict: the ' 'splitters and mixers are returned in ' 'info["splits"]') pinch_T_arr, hot_util_load, cold_util_load, T_in_arr, T_out_arr, \ hxs, hot_indices, cold_indices, indices, streams_inlet, \ hx_utils_rearranged, streams_quenched, table, curves, grid = \ _pinch_analysis(hus, T_min_app, force_ideal_thermo, sort_hus_by_T) N = len(hxs) is_hot = [False] * N for i in hot_indices: is_hot[i] = True H_in_arr = np.array([c.H_in for c in curves]) H_out_arr = np.array([c.H_out for c in curves]) dTs = np.abs(T_in_arr - T_out_arr) C_flow_vector = np.abs(H_out_arr - H_in_arr) / np.maximum(dTs, 1e-12) duty = np.abs(H_out_arr - H_in_arr) scale = float(duty.sum()) # Plan on the grid knots and check the plan on the exact states. Where it # falls short, a MER plan is planned again on knots refined with the # exact states (at most _MAX_REFINE rounds); a best-effort plan, or a MER # plan still short after the last round, has its violating matches # shrunk locally instead (a re-plan of a best-effort side repeats its # whole search to recover a duty of the order of the chord error). # With stream splitting, every round re-plans a split side's previous # pick first (stickiness); after the last refine round, up to # _MAX_SPLIT_RETRY more rounds run while violating exchangers lie on # split sides whose networks can still be excluded (_same_network), and # if they end worse, the best MER plan of the rounds is restored. knots = _grid_knots(curves, grid) exclude, prefer, best = {}, {}, None n_rounds = _MAX_REFINE + (_MAX_SPLIT_RETRY if stream_splitting else 0) for refine_round in range(n_rounds + 1): plan = plan_network(knots, is_hot, T_min_app, avoid_recycle=avoid_recycle, Qmin=Qmin, **(dict(stream_splitting=True, _split_exclude=exclude, _split_prefer=prefer) if stream_splitting else {})) if not refine_round: plan_targets = plan.info['cascade'] duties = {n: e.Q for n, e in enumerate(plan.exchangers)} ends = _walk(plan, duties, knots, is_hot)[0] min_approach, violations, bad = _exact_approach( plan, duties, ends, curves, knots, T_min_app ) if stream_splitting and plan.status == 'mer' and ( best is None or len(bad) < best[0]): best = (len(bad), plan, knots, duties, min_approach, bad) if (not violations or plan.status != 'mer' or refine_round == n_rounds): break if refine_round >= _MAX_REFINE: # a retry (stream splitting only): exclude the networks of the # split sides of the violating exchangers; if none is new, stop # where the default loop stops grew = False for n in bad: side = plan.exchangers[n].side split = plan.info['sides'][side]['split'] if split is None or split['candidate'] is None: continue signature = split['signature'] if not any(_same_network(signature, excluded) for excluded in exclude.get(side, ())): exclude.setdefault(side, set()).add(signature) grew = True if not grew: break if stream_splitting: prefer = {} for side, side_info in plan.info['sides'].items(): split = side_info['split'] if split is not None and split['candidate'] is not None: prefer[side] = (split['candidate'], split['signature']) knots = _refine_knots(knots, violations) if (refine_round > _MAX_REFINE and best is not None and (plan.status != 'mer' or len(bad) > best[0])): # the retries did worse: back to the best MER plan (the fewest # violating exchangers, the earliest round), with its knots _, plan, knots, duties, min_approach, bad = best repaired = [] if bad: duties, changes = _repair(plan, duties, knots, is_hot, curves, T_min_app) for n, Q_before, Q_after in changes: e = plan.exchangers[n] repaired.append(dict(side=e.side, hot=e.hot, cold=e.cold, Q_plan=Q_before, Q=Q_after)) if Q_after < Qmin: del duties[n] ends = _walk(plan, duties, knots, is_hot)[0] min_approach = _exact_approach(plan, duties, ends, curves, knots, T_min_app)[0] # Realize; a match that cannot be simulated is dropped (its duty goes to # the utilities: removing a match never reduces another's approach), and # a split whose splitters or mixer cannot be simulated becomes a trunk # (its branch exchangers are dropped). Each failure removes at least one # exchanger, so the loop ends. dropped = [] while True: try: units, first, last = _realize(plan, duties, curves, knots, streams_inlet, is_hot, T_min_app) splits, split_deviations = ( _realize_splits(plan, duties, units, curves, knots, streams_inlet, is_hot) if plan.splits else ([], []) ) except _RealizationError as failure: dropped.append(dict(ID=failure.ID, Q=duties.pop(failure.n), error=repr(failure.error))) except _SplitRealizationError as failure: for n, ID in failure.branch_exchangers: if n in duties: dropped.append(dict(ID=ID, Q=duties.pop(n), error=repr(failure.error))) else: break HXs_hot_side = [units[n] for n in sorted(units) if plan.exchangers[n].side == 'above'] HXs_cold_side = [units[n] for n in sorted(units) if plan.exchangers[n].side == 'below'] deviations = [] for n, hx in units.items(): e = plan.exchangers[n] if abs(hx.Q - duties[n]) > _DUTY_TOL * (duty[e.hot] + duty[e.cold]): deviations.append(dict(ID=hx.ID, Q_plan=duties[n], Q=hx.Q)) # One rigorous utility per stream, hot streams first stream_HXs_dict = {i: [units[n] for n in plan.stages[i] if n in units] for i in indices} new_HX_utils = [] for i in hot_indices + cold_indices: hot = is_hot[i] curve = curves[i] ID = 'Util_%s_cs'%i if hot else 'Util_%s_hs'%i if first[i] is None: s = _copy(streams_inlet[i]) else: s = curve.state_at_H(curve.H_lo + last[i]) s.ID = 's_%s__%s'%(i, ID) outlet = s.copy('%s__s_%s'%(ID, i)) new_HX_util = bst.units.HXutility(ID=ID, ins=s, outs=outlet, H=H_out_arr[i], rigorous=True, thermo=s.thermo) new_HX_util._run() s_out = new_HX_util.outs[0] atol_T = 5. if 's' in hxs[i].outs[0].phases else 0.001 if hot: np.testing.assert_allclose(s_out.H, H_out_arr[i], rtol=5e-3, atol=1.) np.testing.assert_allclose(s_out.T, T_out_arr[i], rtol=5e-3, atol=atol_T) else: np.testing.assert_allclose(s_out.H, H_out_arr[i], rtol=1e-2, atol=1.) np.testing.assert_allclose(s_out.T, T_out_arr[i], rtol=5e-2, atol=atol_T) new_HX_utils.append(new_HX_util) stream_HXs_dict[i].append(new_HX_util) if info is not None: # utilities of the plan and of the realized network: each stream's # duty less what its process exchangers transfer planned = {n: duties[n] for n in units} simulated = {n: hx.Q for n, hx in units.items()} loads = [] for Q_of in (planned, simulated): Q_hot = Q_cold = 0. for i in indices: remaining = duty[i] - sum(Q_of[n] for n in plan.stages[i] if n in units) if is_hot[i]: Q_cold += remaining else: Q_hot += remaining loads.append((Q_hot, Q_cold)) (Q_hot_plan, Q_cold_plan), (Q_hot, Q_cold) = loads tol = _ACHIEVED_TOL * scale mer = (plan.status == 'mer' and abs(Q_hot - table.hot_util_load) <= tol and abs(Q_cold - table.cold_util_load) <= tol) info.update( status='mer' if mer else 'best_effort', Q_hot_target=table.hot_util_load, Q_cold_target=table.cold_util_load, Q_hot_plan=Q_hot_plan, Q_cold_plan=Q_cold_plan, Q_hot=Q_hot, Q_cold=Q_cold, penalty=Q_hot_plan - table.hot_util_load, sides=plan.info['sides'], plan_targets=dict(Q_hot=plan_targets['Qh'], Q_cold=plan_targets['Qc'], pinch_T=plan_targets['pinch_T'], cut=plan_targets['cut']), refine_rounds=refine_round, min_approach=min_approach if duties else None, deviations=deviations, qmin_dropped=plan.info['qmin_dropped'], dropped=dropped, repaired=repaired, point_loads=[i for i in indices if not curves[i].monotone], ) if stream_splitting: info.update(stream_splitting=True, splits=splits, split_deviations=split_deviations) return HXs_hot_side, HXs_cold_side, new_HX_utils, hxs, T_in_arr,\ T_out_arr, pinch_T_arr, C_flow_vector, hx_utils_rearranged, streams_inlet, stream_HXs_dict,\ hot_indices, cold_indices
# Pinch diagram def _order_exchanger_columns(hxs, stream_life_cycles): """ Order heat exchangers left to right so that every stream meets its exchangers in flow direction (cold streams flow left to right, hot streams right to left). The per-stream stage orders define a precedence graph; a topological sort (Kahn's algorithm, ties broken by the given order) yields a consistent layout. Contradictory constraints, which would need a stream to flow backwards, fall back to the given order. Exchangers left out of `hxs` pass the precedence on: two requested exchangers of a stream are ordered whenever the stream flows from one to the other. A life cycle with splits orders its exchangers by `StreamLifeCycle.stage_pairs`, so the exchangers of sibling branches are not ordered by that stream. """ hxs = list(hxs) position = {hx: i for i, hx in enumerate(hxs)} successors = {hx: [] for hx in hxs} N_predecessors = {hx: 0 for hx in hxs} for life_cycle in stream_life_cycles: if getattr(life_cycle, 'splits', None): pairs = _split_precedence(life_cycle, position) else: stages = [i.unit for i in life_cycle.life_cycle if i.unit in position] if not life_cycle.cold: stages.reverse() pairs = zip(stages, stages[1:]) for a, b in pairs: if b not in successors[a]: successors[a].append(b) N_predecessors[b] += 1 ready = [position[hx] for hx in hxs if not N_predecessors[hx]] heapq.heapify(ready) ordered = [] while ready: hx = hxs[heapq.heappop(ready)] ordered.append(hx) for other in successors[hx]: N_predecessors[other] -= 1 if not N_predecessors[other]: heapq.heappush(ready, position[other]) return ordered if len(ordered) == len(hxs) else hxs def _split_precedence(life_cycle, requested): """ Pairs ``(a, b)`` of `requested` exchangers of a life cycle with splits where column `a` goes left of column `b`: the stream flows from `a` to `b` (from `b` to `a` for a hot stream), through `stage_pairs` and the stages not requested. Each requested stage is paired with the nearest requested stages downstream, which gives the same precedence as their transitive closure. """ successors = {} for a, b in life_cycle.stage_pairs(): successors.setdefault(id(a), []).append(b) pairs = [] for stage in life_cycle.life_cycle: if stage.unit not in requested: continue seen, stack = set(), list(successors.get(id(stage), ())) while stack: other = stack.pop() if id(other) in seen: continue seen.add(id(other)) if other.unit in requested: pairs.append((stage.unit, other.unit)) else: stack.extend(successors.get(id(other), ())) if not life_cycle.cold: pairs = [(b, a) for a, b in pairs] return pairs def _format_H(H): mantissa, exponent = f'{H:.2e}'.split('e') return f'{mantissa}E{int(exponent)}' def _auxiliary_name(unit): """ Return the (dotted) name of an auxiliary unit within its owner, e.g. 'condenser' or 'evaporators[0].heat_exchanger', or None if the unit is not auxiliary. """ owner = unit.owner if owner is unit: return None def search(parent, prefix): for name, aux in parent.get_auxiliary_units_with_names(): if aux is unit: return prefix + name if hasattr(aux, 'get_auxiliary_units_with_names'): found = search(aux, prefix + name + '.') if found: return found return search(owner, '') or unit.ID.lstrip('.') def _stream_label(hx, show_units, show_auxiliary_units, show_stream_IDs): """ Label of a stream from its original heat exchanger `hx`: '<owner> - <auxiliary name> (<inlet stream ID>)', with each part optional. """ parts = [] if show_units: parts.append(hx.owner.ID) if show_auxiliary_units: auxname = _auxiliary_name(hx) if auxname: parts.append(auxname) label = ' - '.join(parts) if show_stream_IDs: ID = hx.ins[0].ID if ID: label = f'{label} ({ID})' if label else ID return label
[docs] def plot_pinch_diagram(stream_life_cycles, inlet_Ts, outlet_Ts, hot_side_HXs, cold_side_HXs, Qmin=1e-3, original_hxs=None, show_units=True, show_auxiliary_units=True, show_stream_IDs=True, show_legend=True, ax=None, file=None, dpi=300): """ Draw a pinch diagram of a synthesized heat exchanger network: cold streams (blue, flowing left to right) above hot streams (red, flowing right to left), one vertical connector per process heat exchanger with its duty, a dashed pinch line separating the cold-side from the hot-side exchangers, and circles marking the utility exchangers that bring each stream to its outlet temperature. Parameters ---------- stream_life_cycles : list[StreamLifeCycle] One per stream, as built by HeatExchangerNetwork. inlet_Ts, outlet_Ts : array-like Stream inlet and outlet temperatures [K], indexed like the life cycles. hot_side_HXs, cold_side_HXs : list[HXprocess] Process exchangers above and below the pinch. Qmin : float, optional Utility exchangers with a duty at or below this [kJ/hr] are not marked. original_hxs : list[Unit], optional The original heat exchanger of each stream (indexed like the life cycles). Required for the stream labels below. show_units : bool, optional Label each stream with the unit operation that owns its original heat exchanger (the main unit for auxiliary exchangers). show_auxiliary_units : bool, optional Label each stream with the name of its original heat exchanger within the main unit (e.g. 'condenser'), if it is an auxiliary unit. show_stream_IDs : bool, optional Label each stream with the ID of the original heat exchanger's inlet. show_legend : bool, optional Add a legend of the symbols below the diagram. ax : matplotlib.axes.Axes, optional Axes to draw on; a new figure is created if not given. file : str, optional If given, the figure is saved to this path. dpi : int, optional Resolution used when saving. Returns ------- fig : matplotlib.figure.Figure ax : matplotlib.axes.Axes Notes ----- Temperatures are shown in degC and heat flows in kJ/hr at the inlet and outlet of each stream (of its whole flow, `StreamLifeCycle.H_in` and its utility's outlet). Exchanger columns on each side of the pinch are ordered so that each stream meets them in flow direction whenever the network allows it; the exchangers of a split stream's branches are ordinary columns, with their branch duties, and sibling branches are not ordered by that stream (splits are not drawn). Stream labels read '<unit> - <auxiliary> (<stream>)' next to the stream index at the inlet. Examples -------- >>> import biosteam as bst >>> bst.settings.set_thermo(['Water', 'Methanol', 'Glycerol']) >>> feed1 = bst.Stream('feed1', flow=(8000, 100, 25)) >>> feed2 = bst.Stream('feed2', flow=(10000, 1000, 10)) >>> D1 = bst.ShortcutColumn('D1', ins=feed1, ... outs=('distillate', 'bottoms_product'), ... LHK=('Methanol', 'Water'), ... y_top=0.99, x_bot=0.01, k=2, ... is_divided=True) >>> D1_H1 = bst.HXutility('D1_H1', ins = D1.outs[1], T = 300) >>> D1_H2 = bst.HXutility('D1_H2', ins = D1.outs[0], T = 300) >>> F1 = bst.Flash('F1', ins=feed2, ... outs=('vapor', 'liquid'), V = 0.9, P = 101325) >>> HXN = bst.HeatExchangerNetwork('HXN', T_min_app = 5.) >>> sys = bst.System.from_units('sys', units=[D1, D1_H1, D1_H2, F1, HXN]) >>> sys.simulate() >>> fig, ax = HXN.plot_pinch_diagram() >>> connectors = [i for i in ax.findobj() if (i.get_gid() or '').startswith('HX:')] >>> len(connectors) == len(HXN.new_HXs) True >>> import matplotlib.pyplot as plt >>> plt.close(fig) """ import matplotlib.pyplot as plt # Artists carry stable gids ('HX:<ID>', 'Util:<ID>', 'Label:<index>', # 'H_in:<index>', 'H_out:<index>') so the drawing can be checked # structurally in tests. show_labels = show_units or show_auxiliary_units or show_stream_IDs if show_labels and original_hxs is None: raise ValueError('original_hxs is required to label streams with ' 'units, auxiliary units, or stream IDs') cold_color, hot_color = '#2e6db4', '#d62728' cold_bg, hot_bg = '#e6f0fa', '#fbe9e7' process_hxs = set(hot_side_HXs) | set(cold_side_HXs) # Stream index and stage of each side of every process exchanger, by identity hx_streams = {hx: {} for hx in process_hxs} for index, life_cycle in enumerate(stream_life_cycles): for stage in life_cycle.life_cycle: if stage.unit in hx_streams: hx_streams[stage.unit][life_cycle.cold] = (index, stage) cold_side_HXs = _order_exchanger_columns(cold_side_HXs, stream_life_cycles) hot_side_HXs = _order_exchanger_columns(hot_side_HXs, stream_life_cycles) columns = cold_side_HXs + hot_side_HXs N_cs = len(cold_side_HXs) N_columns = len(columns) # x layout: 0 stream ends | 1 cold utilities | 2..N_cs+1 cold side | # pinch | N_cs+2..N+1 hot side | N+2 hot utilities | N+3 stream ends x_start, x_cold_util = 0., 1. x_columns = {hx: 2. + i for i, hx in enumerate(columns)} x_pinch = N_cs + 1.5 x_hot_util = N_columns + 2. x_end = N_columns + 3. # y layout: cold streams on top, hot streams below, duty labels in between cold_streams = [i for i, lc in enumerate(stream_life_cycles) if lc.cold] hot_streams = [i for i, lc in enumerate(stream_life_cycles) if not lc.cold] N_hot = len(hot_streams) N_cold = len(cold_streams) gap = 2.5 y = {} for k, i in enumerate(hot_streams): y[i] = N_hot - k for k, i in enumerate(cold_streams): y[i] = N_hot + gap + N_cold - k y_label = N_hot + (gap + 1.) / 2. y_top = N_hot + gap + N_cold + 1. y_bottom = 0. if ax is None: fig, ax = plt.subplots( figsize=(max(6., 0.75 * (N_columns + 4) + 3.), 0.4 * y_top + 1.) ) else: fig = ax.figure # Background and pinch line x_min, x_max = x_start - 1.8, x_end + 1.8 ax.axvspan(x_min, x_pinch, color=cold_bg, lw=0, zorder=0) ax.axvspan(x_pinch, x_max, color=hot_bg, lw=0, zorder=0) ax.axvline(x_pinch, color='k', ls='--', lw=1, zorder=1) ax.text(x_min + 0.2, y_bottom + 0.1, 'Cold side', color=cold_color, weight='bold', ha='left', va='bottom') ax.text(x_max - 0.2, y_bottom + 0.1, 'Hot side', color=hot_color, weight='bold', ha='right', va='bottom') # Column headers header_kwargs = dict(ha='center', va='bottom', weight='bold', fontsize=8) for x_T, x_H in ((x_start - 1.3, x_start - 0.6), (x_end + 0.6, x_end + 1.3)): ax.text(x_T, y_top, 'T\n[°C]', **header_kwargs) ax.text(x_H, y_top, 'H\n[kJ·h$^{-1}$]', **header_kwargs) ax.text(x_start - 0.3, y_label, 'ΔH\n[kJ·h$^{-1}$]', ha='right', va='center', weight='bold', fontsize=8) # Streams value_kwargs = dict(ha='center', va='center', fontsize=8) for index, life_cycle in enumerate(stream_life_cycles): cold = life_cycle.cold color = cold_color if cold else hot_color yi = y[index] stages = life_cycle.life_cycle # never empty: each stream has a utility stage # the whole stream's inlet, also where its first stage is a branch H_in = life_cycle.H_in H_out = stages[-1].H_out T_in = inlet_Ts[index] - 273.15 T_out = outlet_Ts[index] - 273.15 # T is the outer column on the left and the inner column on the right T_left, H_left, T_right, H_right = ( (T_in, H_in, T_out, H_out) if cold else (T_out, H_out, T_in, H_in) ) gid_left, gid_right = ('H_in:', 'H_out:') if cold else ('H_out:', 'H_in:') x_in, x_out, sign = (x_start, x_end, 1) if cold else (x_end, x_start, -1) ax.annotate('', xy=(x_out, yi), xytext=(x_in, yi), arrowprops=dict(arrowstyle='-|>', color=color, lw=1.2, shrinkA=0, shrinkB=0), zorder=2) ax.text(x_start - 1.3, yi, f'{T_left:.1f}', color=color, **value_kwargs) ax.text(x_start - 0.6, yi, _format_H(H_left), color=color, gid=gid_left + str(index), **value_kwargs) ax.text(x_end + 0.6, yi, f'{T_right:.1f}', color=color, **value_kwargs) ax.text(x_end + 1.3, yi, _format_H(H_right), color=color, gid=gid_right + str(index), **value_kwargs) # Index and label share a baseline above the stream, clear of the # exchanger circles y_text = yi + 0.25 ax.text(x_in + sign * 0.3, y_text, str(index), color=color, ha='center', va='baseline', weight='bold', fontsize=9) if show_labels: label = _stream_label(original_hxs[index], show_units, show_auxiliary_units, show_stream_IDs) # the smaller label reads as centered with the index when its # baseline is slightly higher ax.text(x_in + sign * 0.6, y_text + 0.08, label, color=color, ha='left' if cold else 'right', va='baseline', fontsize=7, zorder=6, gid=f'Label:{index}', bbox=dict(boxstyle='square,pad=0.15', fc='w', ec='none')) # Utility exchangers: a cold stream ends in a hot utility (red), a # hot stream in a cold utility (blue) x_util, util_color = (x_hot_util, hot_color) if cold else (x_cold_util, cold_color) for stage in stages: unit = stage.unit if unit in process_hxs: continue if abs(stage.H_out - stage.H_in) <= Qmin: continue ax.plot([x_util], [yi], 'o', mfc='w', mec=util_color, mew=1.2, ms=6, zorder=4, gid='Util:' + unit.ID) # Process exchangers for hx in columns: streams = hx_streams[hx] if len(streams) != 2: warn(f'{hx.ID} is not in exactly one hot and one cold stream ' 'life cycle; it is not drawn', RuntimeWarning) continue (i_cold, stage_cold), (i_hot, stage_hot) = streams[True], streams[False] x = x_columns[hx] Q = abs(stage_hot.H_in - stage_hot.H_out) ax.plot([x, x], [y[i_hot], y[i_cold]], '-o', color='k', mfc='w', mew=1.2, ms=6, lw=1.2, zorder=3, gid='HX:' + hx.ID) ax.text(x, y_label, _format_H(Q), rotation=90, ha='center', va='center', fontsize=8, zorder=5, bbox=dict(boxstyle='square,pad=0.25', fc='w', ec='k', lw=0.8)) if show_legend: from matplotlib.lines import Line2D handles = [ Line2D([], [], color=cold_color, lw=1.2, marker='>', markevery=[-1], ms=5, label='Cold stream'), Line2D([], [], color=hot_color, lw=1.2, marker='<', markevery=[0], ms=5, label='Hot stream'), Line2D([], [], color='k', lw=1.2, marker='o', mfc='w', mew=1.2, ms=6, label='Process heat exchange'), Line2D([], [], ls='', marker='o', mfc='w', mec=hot_color, mew=1.2, ms=6, label='Hot utility'), Line2D([], [], ls='', marker='o', mfc='w', mec=cold_color, mew=1.2, ms=6, label='Cold utility'), Line2D([], [], color='k', ls='--', lw=1, label='Pinch'), ] ax.legend(handles=handles, loc='upper center', bbox_to_anchor=(0.5, 0.), ncol=3, fontsize=7, frameon=False, handlelength=2.5, columnspacing=1.5) ax.set_xlim(x_min, x_max) ax.set_ylim(y_bottom, y_top + 1.2) ax.set_axis_off() if file: fig.savefig(file, dpi=dpi, bbox_inches='tight') return fig, ax