Files
CoolProp/dev/fitter/main.cpp
Julien Marrec 05c8cf503b Lint: use automated tooling to reformat C++ and CMakeLists files (#2103)
* Add initial clang tidy / clang format config files

* Clang format the entire codebase

```
find ./src -regextype posix-extended -regex '.*\.(cpp|hpp|c|h|cxx|hxx)$' | xargs clang-format-12 -style=file -i -fallback-style=none
find ./include -regextype posix-extended -regex '.*\.(cpp|hpp|c|h|cxx|hxx)$' | xargs clang-format-12 -style=file -i -fallback-style=none
find ./Web -regextype posix-extended -regex '.*\.(cpp|hpp|c|h|cxx|hxx)$' | xargs clang-format-12 -style=file -i -fallback-style=none
find ./dev -regextype posix-extended -regex '.*\.(cpp|hpp|c|h|cxx|hxx)$' | xargs clang-format-12 -style=file -i -fallback-style=none
find ./wrappers -regextype posix-extended -regex '.*\.(cpp|hpp|c|h|cxx|hxx)$' | xargs clang-format-12 -style=file -i -fallback-style=none
```

* Add a .cmake-format file and reformat CmakeLists.txt with it

https://github.com/cheshirekow/cmake_format

* Add a clang-format workflow


only runs on PRs, only on touched files
2022-03-31 10:51:48 -04:00

108 lines
4.0 KiB
C++

#include <iostream>
#include "Eigen/Dense"
#include "time.h"
#include "Helmholtz.h"
#include "CoolProp.h"
class EOSFitter;
#include "Fitter.h"
#include "DataTypes.h"
int main() {
double n[] = {0.0, 0.5586817e-3, 0.4982230e0, 0.2458698e-0, 0.8570145e-3, 0.4788584e-3, -0.1800808e-1, 0.2671641e0,
-0.4781652e1, 0.1423987e1, 0.3324062e0, -0.7485907e-2, 0.1017263e-3, -0.5184567e+0, -0.8692288e-1, 0.2057144e+0,
-0.5000457e-2, 0.4603262e-3, -0.3497836e-2, 0.6995038e-2, -0.1452184e-1, -0.1285458e-3};
double d[] = {0, 2, 1, 3, 6, 6, 1, 1, 2, 5, 2, 2, 4, 1, 4, 1, 2, 4, 1, 5, 3, 10};
double t[] = {0.0, -1.0 / 2.0, 0.0, 0.0, 0.0, 3.0 / 2.0, 3.0 / 2.0, 2.0, 2.0, 1.0, 3.0,
5.0, 1.0, 5.0, 5.0, 6.0, 10.0, 10.0, 10.0, 18.0, 22.0, 50.0};
double c[] = {0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0};
std::vector<double> nv(n, n + sizeof(n) / sizeof(double));
double mm = Props1SI("R134a", "molemass");
double rhoL, rhoV;
bool supercritical_T;
double Tr = Props1SI("R134a", "Treduce");
EOSFitter* pEOS = new EOSFitterFixedForm(Props1SI("R134a", "Treduce"), Props1SI("R134a", "rhoreduce") / mm * 1000, 8.314471);
EOSFitter& EOS = *pEOS;
// ----------------------------
// Generate "experimental" data
// ----------------------------
for (double T = 250; T < 500; T += 10) {
if (T < Tr) {
rhoL = PropsSI("D", "T", T, "Q", 0, "R134a");
rhoV = PropsSI("D", "T", T, "Q", 1, "R134a");
supercritical_T = false;
} else {
rhoL = -1;
rhoV = -1;
supercritical_T = true;
}
for (double rho = 1e-10; rho < 1200; rho *= 1.5) {
if (!supercritical_T && (rho < rhoL && rho > rhoV)) {
continue;
}
double p = PropsSI("P", "T", T, "D", rho, "R134a");
double rhobar = rho / mm * 1000;
double cp = PropsSI("C", "T", T, "D", rho, "R134a"); // [J/kg/K]; convert to J/mol/K by *mm/1000
double variance = 1; // TODO; change this
EOS.linear_data_points.push_back(new PressureDataPoint(pEOS, T, rho / mm * 1000, p, variance));
EOS.nonlinear_data_points.push_back(new SpecificHeatCPDataPoint(pEOS, T, rho / mm * 1000, cp * mm / 1000, variance * 100));
}
}
// Setup the EOS
EOS.alphar = phir_power(n, d, t, c, 1, 21, 22);
static const double a0[] = {
0.0, //[0]
-1.019535, //[1]
9.047135, //[2]
-1.629789, //[3]
-9.723916, //[4]
-3.927170 //[5]
};
static const double t0[] = {
0.0, //[0]
0.0, //[1]
0.0, //[2]
0.0, //[3]
-1.0 / 2.0, //[4]
-3.0 / 4.0 //[5]
};
// phi0=log(delta)+a0[1]+a0[2]*tau+a0[3]*log(tau)+a0[4]*pow(tau,-1.0/2.0)+a0[5]*pow(tau,-3.0/4.0);
EOS.alpha0.push_back(new phi0_lead(a0[1], a0[2]));
EOS.alpha0.push_back(new phi0_logtau(a0[3]));
EOS.alpha0.push_back(new phi0_power(a0, t0, 4, 5, 6));
/*for (unsigned int i = 0; i < EOS.nonlinear_data_points.size();i++)
{
std::cout << EOS.nonlinear_data_points[i]->residual(nv) << std::endl;
}*/
// Set the coefficients in the preliminary EOS
EOS.set_n(nv);
std::cout << format("before fit x2 %g\n", EOS.sum_squares(nv, false));
// Solve for n without nonlinear terms to get an approximate solution
EOS.solve_for_n(nv, false);
std::cout << format("solved for n x2 %g\n", EOS.sum_squares(nv, false));
EOS.set_n(nv);
std::cout << format("applied n x2 %g\n", EOS.sum_squares(nv, true));
for (int iter = 0; iter < 5; iter++) {
EOS.set_n(nv);
// Turn on the nonlinear terms and try again
EOS.solve_for_n(nv, true);
std::cout << nv[1] << " " << nv[2] << std::endl;
std::cout << format("iter: %d x2 %g\n", iter, EOS.sum_squares(nv, true));
}
double rr = 0;
}