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+%global _empty_manifest_terminate_build 0
+Name:		python-PyREMOT
+Version:	1.0.17
+Release:	1
+Summary:	Python Reactor Modeling Tools (PyREMOT)
+License:	MIT
+URL:		https://pyremot.herokuapp.com/
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/ca/fb/67ad7824ae88160d1964c94035ffe370b6ae0b7e57d1d36c6262d6bd220b/PyREMOT-1.0.17.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-scipy
+Requires:	python3-matplotlib
+
+%description
+
+# Python Reactor Modeling Tools
+
+
+
+Python Reactor Modeling Tools (PyREMOT) is an open-source package which can be used for process simulation, optimization, and parameter estimation. The current version consists of homogenous models for steady-state and dynamic conditions.
+
+
+
+You can visit [dashboard](https://pyremot.herokuapp.com/) to build model input and load examples!
+
+
+
+## Installation
+
+
+
+You can install this package
+
+
+
+```bash
+
+  pip install PyREMOT
+
+```
+
+
+
+## Documentation
+
+
+
+The main method is called as:
+
+
+
+```python
+
+    from PyREMOT import rmtExe
+
+
+
+    # model inputs
+
+    # using dashboard to build model inputs
+
+    modelInput = {...}
+
+
+
+    # run
+
+    res = rmtExe(modelInput)
+
+```
+
+
+
+Check component list available in the current version:
+
+
+
+```python
+
+    from PyREMOT import rmtCom
+
+
+
+    # display component list
+
+    res = rmtCom()
+
+    print(res)
+
+
+
+```
+
+
+
+PyREMOT UI dashboard conatins some panels as:
+
+
+
+1- MODEL SELECTION
+
+
+
+2- COMPONENTS
+
+
+
+    H2;CO2;H2O;CO;CH3OH;DME
+
+
+
+this code is automaticly converted to python as:
+
+
+
+```python
+
+  compList = ["H2","CO2","H2O","CO","CH3OH","DME"]
+
+```
+
+
+
+3- REACTIONS
+
+
+
+define reacions as:
+
+
+
+    CO2 + 3H2 <=> CH3OH + H2O;
+
+    CO + H2O <=> H2 + CO2;
+
+    2CH3OH <=> DME + H2O
+
+
+
+then:
+
+
+
+```python
+
+    reactionSet = {
+
+    "R1":"CO2+3H2<=>CH3OH+H2O",
+
+    "R2":"CO+H2O<=>H2+CO2",
+
+    "R3":"2CH3OH<=>DME+H2O"
+
+    }
+
+```
+
+
+
+In order to define reaction rate expressions, there are two code sections as
+
+
+
+a) define parameters:
+
+
+
+    "RT": x['R_CONST']*x['T'];
+
+    "K1": 35.45*math.exp(-1.7069e4/x['RT']);
+
+    "K2": 7.3976*math.exp(-2.0436e4/x['RT']);
+
+    "K3": 8.2894e4*math.exp(-5.2940e4/x['RT']);
+
+    "KH2": 0.249*math.exp(3.4394e4/x['RT']);
+
+    "KCO2": 1.02e-7*math.exp(6.74e4/x['RT']);
+
+    "KCO": 7.99e-7*math.exp(5.81e4/x['RT']);
+
+    "Ln_KP1": 4213/x['T'] - 5.752 *     math.log(x['T']) - 1.707e-3*x['T'] + 2.682e-6 *     (math.pow(x['T'], 2)) - 7.232e-10*(math.pow(x['T'], 3)) + 17.6;
+
+    "KP1": math.exp(x['Ln_KP1']);
+
+    "log_KP2": 2167/x['T'] - 0.5194 *     math.log10(x['T']) + 1.037e-3*x['T'] - 2.331e-7 *     (math.pow(x['T'], 2)) - 1.2777;
+
+    "KP2": math.pow(10, x['log_KP2']);
+
+        "Ln_KP3":  4019/x['T'] + 3.707 *     math.log(x['T']) - 2.783e-3*x['T'] + 3.8e-7 *     (math.pow(x['T'], 2)) - 6.56e-4/(math.pow(x['T'], 3)) - 26.64;
+
+    "KP3":  math.exp(x['Ln_KP3']);
+
+    "yi_H2":  x['MoFri'][0];
+
+    "yi_CO2":  x['MoFri'][1];
+
+    "yi_H2O":  x['MoFri'][2];
+
+    "yi_CO":  x['MoFri'][3];
+
+    "yi_CH3OH":  x['MoFri'][4];
+
+    "yi_DME":  x['MoFri'][5];
+
+    "PH2":  x['P']*(x['yi_H2'])*1e-5;
+
+    "PCO2":  x['P']*(x['yi_CO2'])*1e-5;
+
+    "PH2O":  x['P']*(x['yi_H2O'])*1e-5;
+
+    "PCO": x['P']*(x['yi_CO'])*1e-5;
+
+    "PCH3OH":  x['P']*(x['yi_CH3OH'])*1e-5;
+
+    "PCH3OCH3":  x['P']*(x['yi_DME'])*1e-5;
+
+    "ra1":  x['PCO2']*x['PH2'];
+
+    "ra2":  1 + (x['KCO2']*x['PCO2']) + (x['KCO']*x['PCO']) + math.sqrt(x['KH2']*x['PH2']);
+
+    "ra3": (1/x['KP1'])*((x['PH2O']*x['PCH3OH'])/(x['PCO2']*(math.pow(x['PH2'], 3))));
+
+    "ra4":  x['PH2O'] - (1/x['KP2'])*((x['PCO2']*x['PH2'])/x['PCO']);
+
+    "ra5": (math.pow(x['PCH3OH'], 2)/x['PH2O'])-(x['PCH3OCH3']/x['KP3'])
+
+
+
+then converted:
+
+
+
+```python
+
+   varis0 = {
+
+   "RT": lambda x: x['R_CONST']*x['T'],
+
+   "K1": lambda x: 35.45*math.exp(-1.7069e4/x['RT']),
+
+   "K2": lambda x: 7.3976*math.exp(-2.0436e4/x['RT']),
+
+   "K3": lambda x: 8.2894e4*math.exp(-5.2940e4/x['RT']),
+
+   "KH2": lambda x: 0.249*math.exp(3.4394e4/x['RT']),
+
+   "KCO2": lambda x: 1.02e-7*math.exp(6.74e4/x['RT']),
+
+   "KCO": lambda x: 7.99e-7*math.exp(5.81e4/x['RT']),
+
+   "Ln_KP1": lambda x: 4213/x['T'] - 5.752 *     math.log(x['T']) - 1.707e-3*x['T'] + 2.682e-6 *     (math.pow(x['T'], 2)) - 7.232e-10*(math.pow(x['T'], 3)) + 17.6,
+
+   "KP1": lambda x: math.exp(x['Ln_KP1']),
+
+   "log_KP2": lambda x: 2167/x['T'] - 0.5194 *     math.log10(x['T']) + 1.037e-3*x['T'] - 2.331e-7 *     (math.pow(x['T'], 2)) - 1.2777,
+
+   "KP2": lambda x: math.pow(10, x['log_KP2']),
+
+       "Ln_KP3": lambda x:  4019/x['T'] + 3.707 *     math.log(x['T']) - 2.783e-3*x['T'] + 3.8e-7 *     (math.pow(x['T'], 2)) - 6.56e-4/(math.pow(x['T'], 3)) - 26.64,
+
+   "KP3": lambda x:  math.exp(x['Ln_KP3']),
+
+   "yi_H2": lambda x:  x['MoFri'][0],
+
+   "yi_CO2": lambda x:  x['MoFri'][1],
+
+   "yi_H2O": lambda x:  x['MoFri'][2],
+
+   "yi_CO": lambda x:  x['MoFri'][3],
+
+   "yi_CH3OH": lambda x:  x['MoFri'][4],
+
+   "yi_DME": lambda x:  x['MoFri'][5],
+
+   "PH2": lambda x:  x['P']*(x['yi_H2'])*1e-5,
+
+   "PCO2": lambda x:  x['P']*(x['yi_CO2'])*1e-5,
+
+   "PH2O": lambda x:  x['P']*(x['yi_H2O'])*1e-5,
+
+   "PCO": lambda x: x['P']*(x['yi_CO'])*1e-5,
+
+   "PCH3OH": lambda x:  x['P']*(x['yi_CH3OH'])*1e-5,
+
+   "PCH3OCH3": lambda x:  x['P']*(x['yi_DME'])*1e-5,
+
+   "ra1": lambda x:  x['PCO2']*x['PH2'],
+
+   "ra2": lambda x:  1 + (x['KCO2']*x['PCO2']) + (x['KCO']*x['PCO']) + math.sqrt(x['KH2']*x['PH2']),
+
+   "ra3": lambda x: (1/x['KP1'])*((x['PH2O']*x['PCH3OH'])/(x['PCO2']*(math.pow(x['PH2'], 3)))),
+
+   "ra4": lambda x:  x['PH2O'] - (1/x['KP2'])*((x['PCO2']*x['PH2'])/x['PCO']),
+
+   "ra5": lambda x: (math.pow(x['PCH3OH'], 2)/x['PH2O'])-(x['PCH3OCH3']/x['KP3'])
+
+   }
+
+```
+
+
+
+b) define the final form of reaction rate expressions:
+
+
+
+    "r1": 1000*x['K1']*(x['ra1']/(math.pow(x['ra2'], 3)))*(1-x['ra3'])*x['CaBeDe'];
+
+    "r2": 1000*x['K2']*(1/x['ra2'])*x['ra4']*x['CaBeDe'];
+
+    "r3": 1000*x['K3']*x['ra5']*x['CaBeDe']
+
+
+
+then converted:
+
+
+
+```python
+
+   rates0 = {
+
+   "r1": lambda x: 1000*x['K1']*(x['ra1']/(math.pow(x['ra2'], 3)))*(1-x['ra3'])*x['CaBeDe'],
+
+   "r2": lambda x: 1000*x['K2']*(1/x['ra2'])*x['ra4']*x['CaBeDe'],
+
+   "r3": lambda x: 1000*x['K3']*x['ra5']*x['CaBeDe']
+
+   }
+
+```
+
+
+
+4- PROPERTIES
+
+
+
+feed properties:
+
+
+
+```python
+
+   # species-concentration [mol/m^3]
+
+   SpCoi = [574.8978, 287.4489, 1.15e-02, 287.4489, 1.15e-02, 1.15e-02]
+
+   # flowrate @ P & T [m^3/s]
+
+   VoFlRa = 0.000228
+
+   # pressure [Pa]
+
+   P = 5000000
+
+   # temperature [K]
+
+   T = 523
+
+   # process-type [-]
+
+   PrTy = "non-iso-thermal"
+
+```
+
+
+
+5- REACTOR
+
+
+
+reactor and catalyst characteristics:
+
+
+
+```python
+
+   # reactor-length [m]
+
+   ReLe = 1
+
+   # reactor-inner-diameter [m]
+
+   ReInDi = 0.0381
+
+   # bed-void-fraction [-]
+
+   BeVoFr = 0.39
+
+   # catalyst bed density [kg/m^3]
+
+   CaBeDe = 1171.2
+
+   # particle-diameter [m]
+
+   PaDi = 0.002
+
+   # particle-density [kg/m^3]
+
+   CaDe = 1920
+
+   # particle-specific-heat-capacity  [J/kg.K]
+
+   CaSpHeCa = 960
+
+```
+
+
+
+6- HEAT-EXCHANGER
+
+
+
+```python
+
+    # overall-heat-transfer-coefficient [J/m^2.s.K]
+
+    U = 50
+
+    # medium-temperature [K]
+
+    Tm = 523
+
+```
+
+
+
+7- SOLVER
+
+
+
+```python
+
+    # ode-solver [-]
+
+    ivp = "default"
+
+    # display-result [-]
+
+    diRe = "True"
+
+```
+
+
+
+After setting all modules, you can find 'model input' in python format in the summary panel. Then, copy the content of this file in your python framework and run it!
+
+
+
+You can also find an example on PyREMOT dashboard, load it and then have a look at the summary panel.
+
+
+
+## Run
+
+
+
+As the downloaded python file contains modelInput varibale, you can directly run the model as:
+
+
+
+```python
+
+    # model input
+
+    modelInput = {...}
+
+    # start modeling
+
+    res = rmtExe(modelInput)
+
+```
+
+
+
+## Result Format
+
+
+
+For steady-state cases, the modeling result is stored in an array named dataPack:
+
+
+
+```python
+
+    # res
+
+    dataPack = []
+
+    dataPack.append({
+
+        "modelId": modelId,
+
+        "processType": processType,
+
+        "successStatus": successStatus,
+
+        "computation-time": elapsed,
+
+        "dataShape": dataShape,
+
+        "labelList": labelList,
+
+        "indexList": indexList,
+
+        "dataTime": [],
+
+        "dataXs": dataXs,
+
+        "dataYCons1": dataYs_Concentration_DiLeVa,
+
+        "dataYCons2": dataYs_Concentration_ReVa,
+
+        "dataYTemp1": dataYs_Temperature_DiLeVa,
+
+        "dataYTemp2": dataYs_Temperature_ReVa,
+
+        "dataYs": dataYs_All
+
+    })
+
+```
+
+
+
+And for dynamic cases,
+
+
+
+```python
+
+    # res
+
+    resPack = {
+
+        "computation-time": elapsed,
+
+        "dataPack": dataPack
+
+    }
+
+```
+
+
+
+Concentration results:
+
+
+
+    dataYCons1: dimensionless concentration
+
+
+
+    dataYCons2: concentraton [mol/m^3.s]
+
+
+
+Temperature results:
+
+
+
+    dataYTemp1: dimensionless temperature
+
+
+
+    dataYTemp2: Temperature [K]
+
+
+
+All modeling results is also saved in dataYs.
+
+
+
+## FAQ
+
+
+
+For any question, you can conatct me on [LinkedIn](https://www.linkedin.com/in/sina-gilassi/) or [Twitter](https://twitter.com/sinagilassi).
+
+
+
+## Authors
+
+
+
+- [@sinagilassi](https://www.github.com/sinagilassi)
+
+
+
+
+
+%package -n python3-PyREMOT
+Summary:	Python Reactor Modeling Tools (PyREMOT)
+Provides:	python-PyREMOT
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-PyREMOT
+
+# Python Reactor Modeling Tools
+
+
+
+Python Reactor Modeling Tools (PyREMOT) is an open-source package which can be used for process simulation, optimization, and parameter estimation. The current version consists of homogenous models for steady-state and dynamic conditions.
+
+
+
+You can visit [dashboard](https://pyremot.herokuapp.com/) to build model input and load examples!
+
+
+
+## Installation
+
+
+
+You can install this package
+
+
+
+```bash
+
+  pip install PyREMOT
+
+```
+
+
+
+## Documentation
+
+
+
+The main method is called as:
+
+
+
+```python
+
+    from PyREMOT import rmtExe
+
+
+
+    # model inputs
+
+    # using dashboard to build model inputs
+
+    modelInput = {...}
+
+
+
+    # run
+
+    res = rmtExe(modelInput)
+
+```
+
+
+
+Check component list available in the current version:
+
+
+
+```python
+
+    from PyREMOT import rmtCom
+
+
+
+    # display component list
+
+    res = rmtCom()
+
+    print(res)
+
+
+
+```
+
+
+
+PyREMOT UI dashboard conatins some panels as:
+
+
+
+1- MODEL SELECTION
+
+
+
+2- COMPONENTS
+
+
+
+    H2;CO2;H2O;CO;CH3OH;DME
+
+
+
+this code is automaticly converted to python as:
+
+
+
+```python
+
+  compList = ["H2","CO2","H2O","CO","CH3OH","DME"]
+
+```
+
+
+
+3- REACTIONS
+
+
+
+define reacions as:
+
+
+
+    CO2 + 3H2 <=> CH3OH + H2O;
+
+    CO + H2O <=> H2 + CO2;
+
+    2CH3OH <=> DME + H2O
+
+
+
+then:
+
+
+
+```python
+
+    reactionSet = {
+
+    "R1":"CO2+3H2<=>CH3OH+H2O",
+
+    "R2":"CO+H2O<=>H2+CO2",
+
+    "R3":"2CH3OH<=>DME+H2O"
+
+    }
+
+```
+
+
+
+In order to define reaction rate expressions, there are two code sections as
+
+
+
+a) define parameters:
+
+
+
+    "RT": x['R_CONST']*x['T'];
+
+    "K1": 35.45*math.exp(-1.7069e4/x['RT']);
+
+    "K2": 7.3976*math.exp(-2.0436e4/x['RT']);
+
+    "K3": 8.2894e4*math.exp(-5.2940e4/x['RT']);
+
+    "KH2": 0.249*math.exp(3.4394e4/x['RT']);
+
+    "KCO2": 1.02e-7*math.exp(6.74e4/x['RT']);
+
+    "KCO": 7.99e-7*math.exp(5.81e4/x['RT']);
+
+    "Ln_KP1": 4213/x['T'] - 5.752 *     math.log(x['T']) - 1.707e-3*x['T'] + 2.682e-6 *     (math.pow(x['T'], 2)) - 7.232e-10*(math.pow(x['T'], 3)) + 17.6;
+
+    "KP1": math.exp(x['Ln_KP1']);
+
+    "log_KP2": 2167/x['T'] - 0.5194 *     math.log10(x['T']) + 1.037e-3*x['T'] - 2.331e-7 *     (math.pow(x['T'], 2)) - 1.2777;
+
+    "KP2": math.pow(10, x['log_KP2']);
+
+        "Ln_KP3":  4019/x['T'] + 3.707 *     math.log(x['T']) - 2.783e-3*x['T'] + 3.8e-7 *     (math.pow(x['T'], 2)) - 6.56e-4/(math.pow(x['T'], 3)) - 26.64;
+
+    "KP3":  math.exp(x['Ln_KP3']);
+
+    "yi_H2":  x['MoFri'][0];
+
+    "yi_CO2":  x['MoFri'][1];
+
+    "yi_H2O":  x['MoFri'][2];
+
+    "yi_CO":  x['MoFri'][3];
+
+    "yi_CH3OH":  x['MoFri'][4];
+
+    "yi_DME":  x['MoFri'][5];
+
+    "PH2":  x['P']*(x['yi_H2'])*1e-5;
+
+    "PCO2":  x['P']*(x['yi_CO2'])*1e-5;
+
+    "PH2O":  x['P']*(x['yi_H2O'])*1e-5;
+
+    "PCO": x['P']*(x['yi_CO'])*1e-5;
+
+    "PCH3OH":  x['P']*(x['yi_CH3OH'])*1e-5;
+
+    "PCH3OCH3":  x['P']*(x['yi_DME'])*1e-5;
+
+    "ra1":  x['PCO2']*x['PH2'];
+
+    "ra2":  1 + (x['KCO2']*x['PCO2']) + (x['KCO']*x['PCO']) + math.sqrt(x['KH2']*x['PH2']);
+
+    "ra3": (1/x['KP1'])*((x['PH2O']*x['PCH3OH'])/(x['PCO2']*(math.pow(x['PH2'], 3))));
+
+    "ra4":  x['PH2O'] - (1/x['KP2'])*((x['PCO2']*x['PH2'])/x['PCO']);
+
+    "ra5": (math.pow(x['PCH3OH'], 2)/x['PH2O'])-(x['PCH3OCH3']/x['KP3'])
+
+
+
+then converted:
+
+
+
+```python
+
+   varis0 = {
+
+   "RT": lambda x: x['R_CONST']*x['T'],
+
+   "K1": lambda x: 35.45*math.exp(-1.7069e4/x['RT']),
+
+   "K2": lambda x: 7.3976*math.exp(-2.0436e4/x['RT']),
+
+   "K3": lambda x: 8.2894e4*math.exp(-5.2940e4/x['RT']),
+
+   "KH2": lambda x: 0.249*math.exp(3.4394e4/x['RT']),
+
+   "KCO2": lambda x: 1.02e-7*math.exp(6.74e4/x['RT']),
+
+   "KCO": lambda x: 7.99e-7*math.exp(5.81e4/x['RT']),
+
+   "Ln_KP1": lambda x: 4213/x['T'] - 5.752 *     math.log(x['T']) - 1.707e-3*x['T'] + 2.682e-6 *     (math.pow(x['T'], 2)) - 7.232e-10*(math.pow(x['T'], 3)) + 17.6,
+
+   "KP1": lambda x: math.exp(x['Ln_KP1']),
+
+   "log_KP2": lambda x: 2167/x['T'] - 0.5194 *     math.log10(x['T']) + 1.037e-3*x['T'] - 2.331e-7 *     (math.pow(x['T'], 2)) - 1.2777,
+
+   "KP2": lambda x: math.pow(10, x['log_KP2']),
+
+       "Ln_KP3": lambda x:  4019/x['T'] + 3.707 *     math.log(x['T']) - 2.783e-3*x['T'] + 3.8e-7 *     (math.pow(x['T'], 2)) - 6.56e-4/(math.pow(x['T'], 3)) - 26.64,
+
+   "KP3": lambda x:  math.exp(x['Ln_KP3']),
+
+   "yi_H2": lambda x:  x['MoFri'][0],
+
+   "yi_CO2": lambda x:  x['MoFri'][1],
+
+   "yi_H2O": lambda x:  x['MoFri'][2],
+
+   "yi_CO": lambda x:  x['MoFri'][3],
+
+   "yi_CH3OH": lambda x:  x['MoFri'][4],
+
+   "yi_DME": lambda x:  x['MoFri'][5],
+
+   "PH2": lambda x:  x['P']*(x['yi_H2'])*1e-5,
+
+   "PCO2": lambda x:  x['P']*(x['yi_CO2'])*1e-5,
+
+   "PH2O": lambda x:  x['P']*(x['yi_H2O'])*1e-5,
+
+   "PCO": lambda x: x['P']*(x['yi_CO'])*1e-5,
+
+   "PCH3OH": lambda x:  x['P']*(x['yi_CH3OH'])*1e-5,
+
+   "PCH3OCH3": lambda x:  x['P']*(x['yi_DME'])*1e-5,
+
+   "ra1": lambda x:  x['PCO2']*x['PH2'],
+
+   "ra2": lambda x:  1 + (x['KCO2']*x['PCO2']) + (x['KCO']*x['PCO']) + math.sqrt(x['KH2']*x['PH2']),
+
+   "ra3": lambda x: (1/x['KP1'])*((x['PH2O']*x['PCH3OH'])/(x['PCO2']*(math.pow(x['PH2'], 3)))),
+
+   "ra4": lambda x:  x['PH2O'] - (1/x['KP2'])*((x['PCO2']*x['PH2'])/x['PCO']),
+
+   "ra5": lambda x: (math.pow(x['PCH3OH'], 2)/x['PH2O'])-(x['PCH3OCH3']/x['KP3'])
+
+   }
+
+```
+
+
+
+b) define the final form of reaction rate expressions:
+
+
+
+    "r1": 1000*x['K1']*(x['ra1']/(math.pow(x['ra2'], 3)))*(1-x['ra3'])*x['CaBeDe'];
+
+    "r2": 1000*x['K2']*(1/x['ra2'])*x['ra4']*x['CaBeDe'];
+
+    "r3": 1000*x['K3']*x['ra5']*x['CaBeDe']
+
+
+
+then converted:
+
+
+
+```python
+
+   rates0 = {
+
+   "r1": lambda x: 1000*x['K1']*(x['ra1']/(math.pow(x['ra2'], 3)))*(1-x['ra3'])*x['CaBeDe'],
+
+   "r2": lambda x: 1000*x['K2']*(1/x['ra2'])*x['ra4']*x['CaBeDe'],
+
+   "r3": lambda x: 1000*x['K3']*x['ra5']*x['CaBeDe']
+
+   }
+
+```
+
+
+
+4- PROPERTIES
+
+
+
+feed properties:
+
+
+
+```python
+
+   # species-concentration [mol/m^3]
+
+   SpCoi = [574.8978, 287.4489, 1.15e-02, 287.4489, 1.15e-02, 1.15e-02]
+
+   # flowrate @ P & T [m^3/s]
+
+   VoFlRa = 0.000228
+
+   # pressure [Pa]
+
+   P = 5000000
+
+   # temperature [K]
+
+   T = 523
+
+   # process-type [-]
+
+   PrTy = "non-iso-thermal"
+
+```
+
+
+
+5- REACTOR
+
+
+
+reactor and catalyst characteristics:
+
+
+
+```python
+
+   # reactor-length [m]
+
+   ReLe = 1
+
+   # reactor-inner-diameter [m]
+
+   ReInDi = 0.0381
+
+   # bed-void-fraction [-]
+
+   BeVoFr = 0.39
+
+   # catalyst bed density [kg/m^3]
+
+   CaBeDe = 1171.2
+
+   # particle-diameter [m]
+
+   PaDi = 0.002
+
+   # particle-density [kg/m^3]
+
+   CaDe = 1920
+
+   # particle-specific-heat-capacity  [J/kg.K]
+
+   CaSpHeCa = 960
+
+```
+
+
+
+6- HEAT-EXCHANGER
+
+
+
+```python
+
+    # overall-heat-transfer-coefficient [J/m^2.s.K]
+
+    U = 50
+
+    # medium-temperature [K]
+
+    Tm = 523
+
+```
+
+
+
+7- SOLVER
+
+
+
+```python
+
+    # ode-solver [-]
+
+    ivp = "default"
+
+    # display-result [-]
+
+    diRe = "True"
+
+```
+
+
+
+After setting all modules, you can find 'model input' in python format in the summary panel. Then, copy the content of this file in your python framework and run it!
+
+
+
+You can also find an example on PyREMOT dashboard, load it and then have a look at the summary panel.
+
+
+
+## Run
+
+
+
+As the downloaded python file contains modelInput varibale, you can directly run the model as:
+
+
+
+```python
+
+    # model input
+
+    modelInput = {...}
+
+    # start modeling
+
+    res = rmtExe(modelInput)
+
+```
+
+
+
+## Result Format
+
+
+
+For steady-state cases, the modeling result is stored in an array named dataPack:
+
+
+
+```python
+
+    # res
+
+    dataPack = []
+
+    dataPack.append({
+
+        "modelId": modelId,
+
+        "processType": processType,
+
+        "successStatus": successStatus,
+
+        "computation-time": elapsed,
+
+        "dataShape": dataShape,
+
+        "labelList": labelList,
+
+        "indexList": indexList,
+
+        "dataTime": [],
+
+        "dataXs": dataXs,
+
+        "dataYCons1": dataYs_Concentration_DiLeVa,
+
+        "dataYCons2": dataYs_Concentration_ReVa,
+
+        "dataYTemp1": dataYs_Temperature_DiLeVa,
+
+        "dataYTemp2": dataYs_Temperature_ReVa,
+
+        "dataYs": dataYs_All
+
+    })
+
+```
+
+
+
+And for dynamic cases,
+
+
+
+```python
+
+    # res
+
+    resPack = {
+
+        "computation-time": elapsed,
+
+        "dataPack": dataPack
+
+    }
+
+```
+
+
+
+Concentration results:
+
+
+
+    dataYCons1: dimensionless concentration
+
+
+
+    dataYCons2: concentraton [mol/m^3.s]
+
+
+
+Temperature results:
+
+
+
+    dataYTemp1: dimensionless temperature
+
+
+
+    dataYTemp2: Temperature [K]
+
+
+
+All modeling results is also saved in dataYs.
+
+
+
+## FAQ
+
+
+
+For any question, you can conatct me on [LinkedIn](https://www.linkedin.com/in/sina-gilassi/) or [Twitter](https://twitter.com/sinagilassi).
+
+
+
+## Authors
+
+
+
+- [@sinagilassi](https://www.github.com/sinagilassi)
+
+
+
+
+
+%package help
+Summary:	Development documents and examples for PyREMOT
+Provides:	python3-PyREMOT-doc
+%description help
+
+# Python Reactor Modeling Tools
+
+
+
+Python Reactor Modeling Tools (PyREMOT) is an open-source package which can be used for process simulation, optimization, and parameter estimation. The current version consists of homogenous models for steady-state and dynamic conditions.
+
+
+
+You can visit [dashboard](https://pyremot.herokuapp.com/) to build model input and load examples!
+
+
+
+## Installation
+
+
+
+You can install this package
+
+
+
+```bash
+
+  pip install PyREMOT
+
+```
+
+
+
+## Documentation
+
+
+
+The main method is called as:
+
+
+
+```python
+
+    from PyREMOT import rmtExe
+
+
+
+    # model inputs
+
+    # using dashboard to build model inputs
+
+    modelInput = {...}
+
+
+
+    # run
+
+    res = rmtExe(modelInput)
+
+```
+
+
+
+Check component list available in the current version:
+
+
+
+```python
+
+    from PyREMOT import rmtCom
+
+
+
+    # display component list
+
+    res = rmtCom()
+
+    print(res)
+
+
+
+```
+
+
+
+PyREMOT UI dashboard conatins some panels as:
+
+
+
+1- MODEL SELECTION
+
+
+
+2- COMPONENTS
+
+
+
+    H2;CO2;H2O;CO;CH3OH;DME
+
+
+
+this code is automaticly converted to python as:
+
+
+
+```python
+
+  compList = ["H2","CO2","H2O","CO","CH3OH","DME"]
+
+```
+
+
+
+3- REACTIONS
+
+
+
+define reacions as:
+
+
+
+    CO2 + 3H2 <=> CH3OH + H2O;
+
+    CO + H2O <=> H2 + CO2;
+
+    2CH3OH <=> DME + H2O
+
+
+
+then:
+
+
+
+```python
+
+    reactionSet = {
+
+    "R1":"CO2+3H2<=>CH3OH+H2O",
+
+    "R2":"CO+H2O<=>H2+CO2",
+
+    "R3":"2CH3OH<=>DME+H2O"
+
+    }
+
+```
+
+
+
+In order to define reaction rate expressions, there are two code sections as
+
+
+
+a) define parameters:
+
+
+
+    "RT": x['R_CONST']*x['T'];
+
+    "K1": 35.45*math.exp(-1.7069e4/x['RT']);
+
+    "K2": 7.3976*math.exp(-2.0436e4/x['RT']);
+
+    "K3": 8.2894e4*math.exp(-5.2940e4/x['RT']);
+
+    "KH2": 0.249*math.exp(3.4394e4/x['RT']);
+
+    "KCO2": 1.02e-7*math.exp(6.74e4/x['RT']);
+
+    "KCO": 7.99e-7*math.exp(5.81e4/x['RT']);
+
+    "Ln_KP1": 4213/x['T'] - 5.752 *     math.log(x['T']) - 1.707e-3*x['T'] + 2.682e-6 *     (math.pow(x['T'], 2)) - 7.232e-10*(math.pow(x['T'], 3)) + 17.6;
+
+    "KP1": math.exp(x['Ln_KP1']);
+
+    "log_KP2": 2167/x['T'] - 0.5194 *     math.log10(x['T']) + 1.037e-3*x['T'] - 2.331e-7 *     (math.pow(x['T'], 2)) - 1.2777;
+
+    "KP2": math.pow(10, x['log_KP2']);
+
+        "Ln_KP3":  4019/x['T'] + 3.707 *     math.log(x['T']) - 2.783e-3*x['T'] + 3.8e-7 *     (math.pow(x['T'], 2)) - 6.56e-4/(math.pow(x['T'], 3)) - 26.64;
+
+    "KP3":  math.exp(x['Ln_KP3']);
+
+    "yi_H2":  x['MoFri'][0];
+
+    "yi_CO2":  x['MoFri'][1];
+
+    "yi_H2O":  x['MoFri'][2];
+
+    "yi_CO":  x['MoFri'][3];
+
+    "yi_CH3OH":  x['MoFri'][4];
+
+    "yi_DME":  x['MoFri'][5];
+
+    "PH2":  x['P']*(x['yi_H2'])*1e-5;
+
+    "PCO2":  x['P']*(x['yi_CO2'])*1e-5;
+
+    "PH2O":  x['P']*(x['yi_H2O'])*1e-5;
+
+    "PCO": x['P']*(x['yi_CO'])*1e-5;
+
+    "PCH3OH":  x['P']*(x['yi_CH3OH'])*1e-5;
+
+    "PCH3OCH3":  x['P']*(x['yi_DME'])*1e-5;
+
+    "ra1":  x['PCO2']*x['PH2'];
+
+    "ra2":  1 + (x['KCO2']*x['PCO2']) + (x['KCO']*x['PCO']) + math.sqrt(x['KH2']*x['PH2']);
+
+    "ra3": (1/x['KP1'])*((x['PH2O']*x['PCH3OH'])/(x['PCO2']*(math.pow(x['PH2'], 3))));
+
+    "ra4":  x['PH2O'] - (1/x['KP2'])*((x['PCO2']*x['PH2'])/x['PCO']);
+
+    "ra5": (math.pow(x['PCH3OH'], 2)/x['PH2O'])-(x['PCH3OCH3']/x['KP3'])
+
+
+
+then converted:
+
+
+
+```python
+
+   varis0 = {
+
+   "RT": lambda x: x['R_CONST']*x['T'],
+
+   "K1": lambda x: 35.45*math.exp(-1.7069e4/x['RT']),
+
+   "K2": lambda x: 7.3976*math.exp(-2.0436e4/x['RT']),
+
+   "K3": lambda x: 8.2894e4*math.exp(-5.2940e4/x['RT']),
+
+   "KH2": lambda x: 0.249*math.exp(3.4394e4/x['RT']),
+
+   "KCO2": lambda x: 1.02e-7*math.exp(6.74e4/x['RT']),
+
+   "KCO": lambda x: 7.99e-7*math.exp(5.81e4/x['RT']),
+
+   "Ln_KP1": lambda x: 4213/x['T'] - 5.752 *     math.log(x['T']) - 1.707e-3*x['T'] + 2.682e-6 *     (math.pow(x['T'], 2)) - 7.232e-10*(math.pow(x['T'], 3)) + 17.6,
+
+   "KP1": lambda x: math.exp(x['Ln_KP1']),
+
+   "log_KP2": lambda x: 2167/x['T'] - 0.5194 *     math.log10(x['T']) + 1.037e-3*x['T'] - 2.331e-7 *     (math.pow(x['T'], 2)) - 1.2777,
+
+   "KP2": lambda x: math.pow(10, x['log_KP2']),
+
+       "Ln_KP3": lambda x:  4019/x['T'] + 3.707 *     math.log(x['T']) - 2.783e-3*x['T'] + 3.8e-7 *     (math.pow(x['T'], 2)) - 6.56e-4/(math.pow(x['T'], 3)) - 26.64,
+
+   "KP3": lambda x:  math.exp(x['Ln_KP3']),
+
+   "yi_H2": lambda x:  x['MoFri'][0],
+
+   "yi_CO2": lambda x:  x['MoFri'][1],
+
+   "yi_H2O": lambda x:  x['MoFri'][2],
+
+   "yi_CO": lambda x:  x['MoFri'][3],
+
+   "yi_CH3OH": lambda x:  x['MoFri'][4],
+
+   "yi_DME": lambda x:  x['MoFri'][5],
+
+   "PH2": lambda x:  x['P']*(x['yi_H2'])*1e-5,
+
+   "PCO2": lambda x:  x['P']*(x['yi_CO2'])*1e-5,
+
+   "PH2O": lambda x:  x['P']*(x['yi_H2O'])*1e-5,
+
+   "PCO": lambda x: x['P']*(x['yi_CO'])*1e-5,
+
+   "PCH3OH": lambda x:  x['P']*(x['yi_CH3OH'])*1e-5,
+
+   "PCH3OCH3": lambda x:  x['P']*(x['yi_DME'])*1e-5,
+
+   "ra1": lambda x:  x['PCO2']*x['PH2'],
+
+   "ra2": lambda x:  1 + (x['KCO2']*x['PCO2']) + (x['KCO']*x['PCO']) + math.sqrt(x['KH2']*x['PH2']),
+
+   "ra3": lambda x: (1/x['KP1'])*((x['PH2O']*x['PCH3OH'])/(x['PCO2']*(math.pow(x['PH2'], 3)))),
+
+   "ra4": lambda x:  x['PH2O'] - (1/x['KP2'])*((x['PCO2']*x['PH2'])/x['PCO']),
+
+   "ra5": lambda x: (math.pow(x['PCH3OH'], 2)/x['PH2O'])-(x['PCH3OCH3']/x['KP3'])
+
+   }
+
+```
+
+
+
+b) define the final form of reaction rate expressions:
+
+
+
+    "r1": 1000*x['K1']*(x['ra1']/(math.pow(x['ra2'], 3)))*(1-x['ra3'])*x['CaBeDe'];
+
+    "r2": 1000*x['K2']*(1/x['ra2'])*x['ra4']*x['CaBeDe'];
+
+    "r3": 1000*x['K3']*x['ra5']*x['CaBeDe']
+
+
+
+then converted:
+
+
+
+```python
+
+   rates0 = {
+
+   "r1": lambda x: 1000*x['K1']*(x['ra1']/(math.pow(x['ra2'], 3)))*(1-x['ra3'])*x['CaBeDe'],
+
+   "r2": lambda x: 1000*x['K2']*(1/x['ra2'])*x['ra4']*x['CaBeDe'],
+
+   "r3": lambda x: 1000*x['K3']*x['ra5']*x['CaBeDe']
+
+   }
+
+```
+
+
+
+4- PROPERTIES
+
+
+
+feed properties:
+
+
+
+```python
+
+   # species-concentration [mol/m^3]
+
+   SpCoi = [574.8978, 287.4489, 1.15e-02, 287.4489, 1.15e-02, 1.15e-02]
+
+   # flowrate @ P & T [m^3/s]
+
+   VoFlRa = 0.000228
+
+   # pressure [Pa]
+
+   P = 5000000
+
+   # temperature [K]
+
+   T = 523
+
+   # process-type [-]
+
+   PrTy = "non-iso-thermal"
+
+```
+
+
+
+5- REACTOR
+
+
+
+reactor and catalyst characteristics:
+
+
+
+```python
+
+   # reactor-length [m]
+
+   ReLe = 1
+
+   # reactor-inner-diameter [m]
+
+   ReInDi = 0.0381
+
+   # bed-void-fraction [-]
+
+   BeVoFr = 0.39
+
+   # catalyst bed density [kg/m^3]
+
+   CaBeDe = 1171.2
+
+   # particle-diameter [m]
+
+   PaDi = 0.002
+
+   # particle-density [kg/m^3]
+
+   CaDe = 1920
+
+   # particle-specific-heat-capacity  [J/kg.K]
+
+   CaSpHeCa = 960
+
+```
+
+
+
+6- HEAT-EXCHANGER
+
+
+
+```python
+
+    # overall-heat-transfer-coefficient [J/m^2.s.K]
+
+    U = 50
+
+    # medium-temperature [K]
+
+    Tm = 523
+
+```
+
+
+
+7- SOLVER
+
+
+
+```python
+
+    # ode-solver [-]
+
+    ivp = "default"
+
+    # display-result [-]
+
+    diRe = "True"
+
+```
+
+
+
+After setting all modules, you can find 'model input' in python format in the summary panel. Then, copy the content of this file in your python framework and run it!
+
+
+
+You can also find an example on PyREMOT dashboard, load it and then have a look at the summary panel.
+
+
+
+## Run
+
+
+
+As the downloaded python file contains modelInput varibale, you can directly run the model as:
+
+
+
+```python
+
+    # model input
+
+    modelInput = {...}
+
+    # start modeling
+
+    res = rmtExe(modelInput)
+
+```
+
+
+
+## Result Format
+
+
+
+For steady-state cases, the modeling result is stored in an array named dataPack:
+
+
+
+```python
+
+    # res
+
+    dataPack = []
+
+    dataPack.append({
+
+        "modelId": modelId,
+
+        "processType": processType,
+
+        "successStatus": successStatus,
+
+        "computation-time": elapsed,
+
+        "dataShape": dataShape,
+
+        "labelList": labelList,
+
+        "indexList": indexList,
+
+        "dataTime": [],
+
+        "dataXs": dataXs,
+
+        "dataYCons1": dataYs_Concentration_DiLeVa,
+
+        "dataYCons2": dataYs_Concentration_ReVa,
+
+        "dataYTemp1": dataYs_Temperature_DiLeVa,
+
+        "dataYTemp2": dataYs_Temperature_ReVa,
+
+        "dataYs": dataYs_All
+
+    })
+
+```
+
+
+
+And for dynamic cases,
+
+
+
+```python
+
+    # res
+
+    resPack = {
+
+        "computation-time": elapsed,
+
+        "dataPack": dataPack
+
+    }
+
+```
+
+
+
+Concentration results:
+
+
+
+    dataYCons1: dimensionless concentration
+
+
+
+    dataYCons2: concentraton [mol/m^3.s]
+
+
+
+Temperature results:
+
+
+
+    dataYTemp1: dimensionless temperature
+
+
+
+    dataYTemp2: Temperature [K]
+
+
+
+All modeling results is also saved in dataYs.
+
+
+
+## FAQ
+
+
+
+For any question, you can conatct me on [LinkedIn](https://www.linkedin.com/in/sina-gilassi/) or [Twitter](https://twitter.com/sinagilassi).
+
+
+
+## Authors
+
+
+
+- [@sinagilassi](https://www.github.com/sinagilassi)
+
+
+
+
+
+%prep
+%autosetup -n PyREMOT-1.0.17
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-PyREMOT -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.17-1
+- Package Spec generated