From c3d7bab5a367e654377438cf95e056d791e7df3b Mon Sep 17 00:00:00 2001 From: Yalin Li Date: Tue, 7 Mar 2023 18:59:23 -0600 Subject: [PATCH 1/6] extremely minor updates for ocd --- setup.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/setup.py b/setup.py index b80eb0fb..b0c9557d 100644 --- a/setup.py +++ b/setup.py @@ -5,6 +5,7 @@ QSDsan: Quantitative Sustainable Design for sanitation and resource recovery systems This module is developed by: + Yalin Li This module is under the University of Illinois/NCSA Open Source License. @@ -40,8 +41,8 @@ 'seaborn', 'sympy>=1.8', ], - package_data= - {'qsdsan': [ + package_data={ + 'qsdsan': [ 'data/*', 'data/process_data/*', 'data/sanunit_data/*', @@ -52,7 +53,7 @@ 'processes/*', 'sanunits/*', 'utils/*', - ]}, + ]}, classifiers=[ 'License :: OSI Approved :: University of Illinois/NCSA Open Source License', 'Environment :: Console', From 77983b597ee10cd0c3cbc42e8105d194dbb2a7fe Mon Sep 17 00:00:00 2001 From: Yalin Li Date: Sun, 19 Mar 2023 08:24:52 -0500 Subject: [PATCH 2/6] update for newer biosteam --- qsdsan/sanunits/_heat_exchanging.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/qsdsan/sanunits/_heat_exchanging.py b/qsdsan/sanunits/_heat_exchanging.py index a3f74199..ecd9f745 100644 --- a/qsdsan/sanunits/_heat_exchanging.py +++ b/qsdsan/sanunits/_heat_exchanging.py @@ -23,8 +23,8 @@ import biosteam as bst from warnings import warn from math import ceil, pi +from biosteam.facilities import HeatExchangerNetwork as HXN from biosteam.units import HXprocess as HXP, HXutility as HXU -from biosteam.units.facilities import HeatExchangerNetwork as HXN from biosteam.units.design_tools.specification_factors import material_densities_lb_per_ft3 from biosteam.exceptions import bounds_warning, DesignWarning from biosteam.units.design_tools import flash_vessel_design From 7faee04901e102a531e1ef5bbd1ea803a8294740 Mon Sep 17 00:00:00 2001 From: Yalin Li Date: Sun, 19 Mar 2023 08:31:56 -0500 Subject: [PATCH 3/6] update to be compatible with the `facilities` module move in newer biosteam --- qsdsan/sanunits/_heat_exchanging.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/qsdsan/sanunits/_heat_exchanging.py b/qsdsan/sanunits/_heat_exchanging.py index ecd9f745..07afec13 100644 --- a/qsdsan/sanunits/_heat_exchanging.py +++ b/qsdsan/sanunits/_heat_exchanging.py @@ -23,8 +23,7 @@ import biosteam as bst from warnings import warn from math import ceil, pi -from biosteam.facilities import HeatExchangerNetwork as HXN -from biosteam.units import HXprocess as HXP, HXutility as HXU +from biosteam import HeatExchangerNetwork as HXN, HXprocess as HXP, HXutility as HXU from biosteam.units.design_tools.specification_factors import material_densities_lb_per_ft3 from biosteam.exceptions import bounds_warning, DesignWarning from biosteam.units.design_tools import flash_vessel_design From 09255c2aab7296df7c58d56d9c53e6aa9cf618f3 Mon Sep 17 00:00:00 2001 From: Yalin Li Date: Sun, 19 Mar 2023 09:03:46 -0500 Subject: [PATCH 4/6] remove redundant importing --- qsdsan/sanunits/_heat_exchanging.py | 1 - 1 file changed, 1 deletion(-) diff --git a/qsdsan/sanunits/_heat_exchanging.py b/qsdsan/sanunits/_heat_exchanging.py index 07afec13..d539d8b7 100644 --- a/qsdsan/sanunits/_heat_exchanging.py +++ b/qsdsan/sanunits/_heat_exchanging.py @@ -20,7 +20,6 @@ for license details. ''' -import biosteam as bst from warnings import warn from math import ceil, pi from biosteam import HeatExchangerNetwork as HXN, HXprocess as HXP, HXutility as HXU From 96a61e6e260180cf7974418c036cd715f019e2a9 Mon Sep 17 00:00:00 2001 From: Yalin Li Date: Sun, 19 Mar 2023 09:03:58 -0500 Subject: [PATCH 5/6] fix broken link in TEA tutorial --- docs/source/tutorials/7_TEA.ipynb | 260 ++++++++++++++++++++++++++---- 1 file changed, 233 insertions(+), 27 deletions(-) diff --git a/docs/source/tutorials/7_TEA.ipynb b/docs/source/tutorials/7_TEA.ipynb index 07800654..559b9b74 100755 --- a/docs/source/tutorials/7_TEA.ipynb +++ b/docs/source/tutorials/7_TEA.ipynb @@ -12,8 +12,8 @@ "\n", "* **Covered topics:**\n", "\n", - " - [1. Using the SimpleTEA class](#s1)\n", - " - [2. Developing your own TEA or SimpleTEA subclass](#s2)\n", + " - [1. Using the TEA class](#s1)\n", + " - [2. Developing your own TEA subclass](#s2)\n", " \n", "- **Video demo:**\n", "\n", @@ -35,7 +35,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "This tutorial was made with qsdsan v1.2.0.\n" + "This tutorial was made with qsdsan v1.2.5.\n" ] } ], @@ -48,7 +48,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 1. Using the `SimpleTEA` class " + "## 1. Using the `TEA` class " ] }, { @@ -57,13 +57,9 @@ "source": [ "TEA can be performed through subclasses of the `TEA` class in `biosteam`, but you cannot just use the `TEA` class (it's an abstract class, see later part of this tutorial for details).\n", "\n", - "In `qsdsan`, a `SimpleTEA` class is included for basic TEA, you can use it if:\n", + "In `qsdsan`, there is a `TEA` class (used to be called `SimpleTEA` but now the `Simple` part is dropped since it's not a \"simple\" version of fewer functions) that is based on the `TEA` class of `biosteam`.\n", "\n", - "- You don't need to consider financing\n", - "- The system does not have a start-up stage (i.e., all operating cost and sales stay the same year-to-year)\n", - "- Your do not have additional capital costs (e.g., indirect costs such as piping, contingency) other than the ones already considered in the equipment of each unit\n", - "\n", - "If you need more than `SimpleTEA` provides, you should consider making your own `TEA` subclass (see [Section 2](#s2) of this tutorial)." + "You can directly use the default `qsdsan.TEA` class, and you can make your own `TEA` subclass if you want to include customize cost calculations (see [Section 2](#s2) of this tutorial)." ] }, { @@ -79,7 +75,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "In `SimpleTEA`, there are two attributes related to annual capital cost: `annualized_equipment_cost` and `annualized_CAPEX`.\n", + "In `qsdsan.TEA`, there are two attributes related to annual capital cost: `annualized_equipment_cost` and `annualized_CAPEX`.\n", "\n", "`annualized_equipment_cost` is calculated as the sum of annualized capital cost of each equipment. The annualized capital cost of each equipment is calculated as:\n", "\n", @@ -88,7 +84,7 @@ "where `r` is the discount rate, and `lifetime` will be:\n", "- lifetime of the equipment (if provided)\n", "- lifetime of the unit (if provided)\n", - "- lifetime given in initializing the `SimpleTEA` instance" + "- lifetime given in initializing the `TEA` instance" ] }, { @@ -108,7 +104,7 @@ "annualized\\ NPV = \\frac{NPV*r}{(1-(1+r)^{-lifetime})}\n", "$$\n", "\n", - "and the lifetime would be the lifetime of the TEA (i.e., the one provided when initializing the `SimpleTEA` instance).\n", + "and the lifetime would be the lifetime of the TEA (i.e., the one provided when initializing the `qsdsan.TEA` instance).\n", "\n", "So\n", "\n", @@ -127,7 +123,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "If unsure, it is always best to look at the [source code](https://github.com/QSD-Group/QSDsan/blob/main/qsdsan/_simple_tea.py) and determine what is right for your system." + "If unsure, it is always best to look at the [source code](https://github.com/QSD-Group/QSDsan/blob/main/qsdsan/_tea.py) and determine what is right for your system." ] }, { @@ -146,15 +142,225 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/yalinli_cabbi/opt/anaconda3/envs/demo/lib/python3.8/site-packages/qsdsan/_sanstream.py:59: RuntimeWarning: has been replaced in registry\n", + "C:\\Users\\Yalin\\anaconda3\\envs\\bq\\lib\\site-packages\\qsdsan\\_sanstream.py:67: RuntimeWarning: has been replaced in registry\n", " super().__init__(ID=ID, flow=flow, phase=phase, T=T, P=P,\n" ] }, { "data": { - "image/png": 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fugative\n", + " N2O\n", + "\n", + "\n", + "\n", + "" + ], "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -196,7 +402,7 @@ "text": [ "Excretion Units U1\n", "Total purchase cost USD 0\n", - "Utility cost USD/hr 0\n", + "Utility cost USD/hr NaN\n", "Additional OPEX USD/hr 0\n" ] } @@ -251,14 +457,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "SimpleTEA: sys1\n", + "TEA: sys1\n", "NPV : -4,642 USD at 5.0% discount rate\n" ] } ], "source": [ "# With some assumptions, we can calculate costs associated with this system\n", - "tea1 = qs.SimpleTEA(system=sys1, discount_rate=0.05, lifetime=10)\n", + "tea1 = qs.TEA(system=sys1, discount_rate=0.05, lifetime=10)\n", "tea1.show()" ] }, @@ -305,14 +511,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 2. Developing your own `TEA` or `SimpleTEA` subclass " + "## 2. Developing your own `TEA` subclass " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "But you may need to consider additional cost items when doing TEA, to do so, you can make your own subclasses of `TEA` or `SimpleTEA`.\n", + "But you may need to consider additional cost items when doing TEA, to do so, you can make your own subclasses of `biosteam.TEA` or `qsdsan.TEA` (`qsdsan.TEA` is a subclass of `biosteam.TEA` with some more assumptions, so you should decide which class to base on according to your needs).\n", "\n", "For making subclasses of `TEA`, you can check out this [tutorial](https://biosteam.readthedocs.io/en/latest/tutorial/Techno-economic_analysis.html) in BioSTEAM's documentation, but since you have learned how to make a subclass (see the advanced [tutorial](https://github.com/QSD-Group/QSDsan/blob/main/docs/source/tutorials/5_SanUnit_advanced.ipynb) on SanUnit if you are not sure), let's go through a simple example to create a subclass of `TEA`." ] @@ -458,9 +664,9 @@ "output_type": "stream", "text": [ "Original VOC is 365.0000002919999.\n", - "Random VOC is 45.655570210024834.\n", + "Random VOC is 87.31253134353302.\n", "NewTEA: sys1\n", - " NPV: -6,097 USD at 5.0% IRR\n" + " NPV: -6,418 USD at 5.0% IRR\n" ] } ], @@ -478,13 +684,13 @@ "output_type": "stream", "text": [ "Original VOC is 365.0000002919999.\n", - "Random VOC is 65.80430515967058.\n" + "Random VOC is 32.651031716658096.\n" ] }, { "data": { "text/plain": [ - "430.80430545167053" + "397.65103200865804" ] }, "execution_count": 12, @@ -522,7 +728,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.12" + "version": "3.9.13" } }, "nbformat": 4, From 882386c86c8077b178b2d2cfb8697df36792781c Mon Sep 17 00:00:00 2001 From: Jianan Feng Date: Sat, 25 Mar 2023 15:07:49 -0500 Subject: [PATCH 6/6] remove vle for HT, HC, and CHG --- qsdsan/sanunits/_hydroprocessing.py | 6 +++--- qsdsan/sanunits/_hydrothermal.py | 8 ++++++-- 2 files changed, 9 insertions(+), 5 deletions(-) diff --git a/qsdsan/sanunits/_hydroprocessing.py b/qsdsan/sanunits/_hydroprocessing.py index e8ee3dc4..44ce7ad0 100644 --- a/qsdsan/sanunits/_hydroprocessing.py +++ b/qsdsan/sanunits/_hydroprocessing.py @@ -172,8 +172,8 @@ def _run(self): hc_out.P = heavy_oil.P hc_out.T = self.HCrxn_T - hc_out.vle(T=hc_out.T, P=hc_out.P) - + # hc_out.vle(T=hc_out.T, P=hc_out.P) + cmps = self.components C_in = 0 total_num = len(list(cmps)) @@ -430,7 +430,7 @@ def _run(self): ht_out.T = self.HTrxn_T - ht_out.vle(T=ht_out.T, P=ht_out.P) + # ht_out.vle(T=ht_out.T, P=ht_out.P) if self.HTaqueous_C < -0.1*self.HTL.WWTP.sludge_C: raise Exception('carbon mass balance is out of +/- 10% for the whole system') diff --git a/qsdsan/sanunits/_hydrothermal.py b/qsdsan/sanunits/_hydrothermal.py index d39fdc57..39a02717 100644 --- a/qsdsan/sanunits/_hydrothermal.py +++ b/qsdsan/sanunits/_hydrothermal.py @@ -165,7 +165,9 @@ def _run(self): catalyst_out.copy_like(catalyst_in) # catalysts amount is quite low compared to the main stream, therefore do not consider # heating/cooling of catalysts - + + chg_out.phase='g' + cmps = self.components gas_C_ratio = 0 for name, ratio in self.gas_composition.items(): @@ -181,7 +183,9 @@ def _run(self): chg_out.T = self.cool_temp chg_out.P = self.pump_pressure - + + # chg_out.vle(T=chg_out.T, P=chg_out.P) + @property def CHGout_C(self): # not include carbon in gas phase