/***
\brief This file contains the contributions that can be composed together to form SAFT models
*/
#pragma once
#include "nlohmann/json.hpp"
#include "teqp/types.hpp"
#include "teqp/json_tools.hpp"
#include "teqp/exceptions.hpp"
#include "teqp/constants.hpp"
#include "teqp/math/quadrature.hpp"
#include "teqp/models/saft/polar_terms.hpp"
#include <optional>
#include <variant>
namespace teqp {
namespace SAFTVRMie {
/// Coefficients for one fluid
struct SAFTVRMieCoeffs {
std::string name; ///< Name of fluid
double m = -1, ///< number of segments
sigma_m = -1, ///< [m] segment diameter
epsilon_over_k = -1, ///< [K] depth of pair potential divided by Boltzman constant
lambda_a = -1, ///< The attractive exponent (the 6 in LJ 12-6 potential)
lambda_r = -1, ///< The repulsive exponent (the 12 in LJ 12-6 potential)
mustar2 = 0, ///< nondimensional, the reduced dipole moment squared
nmu = 0, ///< number of dipolar segments
Qstar2 = 0, ///< nondimensional, the reduced quadrupole squared
nQ = 0; ///< number of quadrupolar segments
std::string BibTeXKey; ///< The BibTeXKey for the reference for these coefficients
};
/// Manager class for SAFT-VR-Mie coefficients
class SAFTVRMieLibrary {
std::map<std::string, SAFTVRMieCoeffs> coeffs;
public:
SAFTVRMieLibrary() {
insert_normal_fluid("Methane", 1.0000, 3.7412e-10, 153.36, 12.650, 6, "Lafitte-JCP-2001");
insert_normal_fluid("Ethane", 1.4373, 3.7257e-10, 206.12, 12.400, 6, "Lafitte-JCP-2001");
insert_normal_fluid("Propane", 1.6845, 3.9056e-10, 239.89, 13.006, 6, "Lafitte-JCP-2001");
}
void insert_normal_fluid(const std::string& name, double m, const double sigma_m, const double epsilon_over_k, const double lambda_r, const double lambda_a, const std::string& BibTeXKey) {
SAFTVRMieCoeffs coeff;
coeff.name = name;
coeff.m = m;
coeff.sigma_m = sigma_m;
coeff.epsilon_over_k = epsilon_over_k;
coeff.lambda_r = lambda_r;
coeff.lambda_a = lambda_a;
coeff.BibTeXKey = BibTeXKey;
coeffs.insert(std::pair<std::string, SAFTVRMieCoeffs>(name, coeff));
}
const auto& get_normal_fluid(const std::string& name) {
auto it = coeffs.find(name);
if (it != coeffs.end()) {
return it->second;
}
else {
throw std::invalid_argument("Bad name:" + name);
}
}
auto get_coeffs(const std::vector<std::string>& names){
std::vector<SAFTVRMieCoeffs> c;
for (auto n : names){
c.push_back(get_normal_fluid(n));
}
return c;
}
};
/// Things that only depend on the components themselves, but not on composition, temperature, or density
struct SAFTVRMieChainContributionTerms{
private:
/// The matrix of coefficients needed to evaluate f_k
const Eigen::Matrix<double, 7, 7> phi{(Eigen::Matrix<double, 7, 7>() <<
7.5365557, -359.44, 1550.9, -1.19932, -1911.28, 9236.9, 10,
-37.60463, 1825.6, -5070.1, 9.063632, 21390.175, -129430, 10,
71.745953, -3168.0, 6534.6, -17.9482, -51320.7, 357230, 0.57,
-46.83552, 1884.2, -3288.7, 11.34027, 37064.54, -315530, -6.7,
-2.467982, -0.82376, -2.7171, 20.52142, 1103.742, 1390.2, -8,
-0.50272, -3.1935, 2.0883, -56.6377, -3264.61, -4518.2, 0,
8.0956883, 3.7090, 0, 40.53683, 2556.181, 4241.6, 0 ).finished()};
/// The matrix used to obtain the parameters c_1, c_2, c_3, and c_4 in Eq. A18
const Eigen::Matrix<double, 4, 4> A{(Eigen::Matrix<double, 4, 4>() <<
0.81096, 1.7888, -37.578, 92.284,
1.0205, -19.341, 151.26, -463.50,
-1.9057, 22.845, -228.14, 973.92,
1.0885, -6.1962, 106.98, -677.64).finished()};
// Eq. A48
auto get_lambda_k_ij(const Eigen::ArrayXd& lambda_k) const{
Eigen::ArrayXXd mat(N,N);
for (auto i = 0; i < lambda_k.size(); ++i){
for (auto j = i; j < lambda_k.size(); ++j){
mat(i,j) = 3 + sqrt((lambda_k(i)-3)*(lambda_k(j)-3));
mat(j,i) = mat(i,j);
}
}
return mat;
}
/// Eq. A3
auto get_C_ij() const{
Eigen::ArrayXXd C(N,N);
for (auto i = 0; i < N; ++i){
for (auto j = i; j < N; ++j){
C(i,j) = lambda_r_ij(i,j)/(lambda_r_ij(i,j)-lambda_a_ij(i,j))*pow(lambda_r_ij(i,j)/lambda_a_ij(i,j), lambda_a_ij(i,j)/(lambda_r_ij(i,j)-lambda_a_ij(i,j)));
C(j,i) = C(i,j); // symmetric
}
}
return C;
}
// Eq. A26
auto get_fkij() const{
std::vector<Eigen::ArrayXXd> f_(8); // 0-th element is present, but not initialized
for (auto k = 1; k < 8; ++k){
f_[k].resize(N,N);
};
for (auto k = 1; k < 8; ++k){
auto phik = phi.col(k-1); // phi matrix is indexed to start at 1, but our matrix starts at 0
Eigen::ArrayXXd num(N,N), den(N,N); num.setZero(), den.setZero();
for (auto n = 0; n < 4; ++n){
num += phik[n]*pow(alpha_ij, n);
}
for (auto n = 4; n < 7; ++n){
den += phik[n]*pow(alpha_ij, n-3);
}
f_[k] = num/(1 + den);
}
return f_;
}
/// Eq. A45
auto get_sigma_ij() const{
Eigen::ArrayXXd sigma(N,N);
for (auto i = 0; i < N; ++i){
for (auto j = i; j < N; ++j){
sigma(i,j) = (sigma_A(i) + sigma_A(j))/2.0;
sigma(j,i) = sigma(i,j); // symmetric
}
}
return sigma;
}
/// Eq. A55
auto get_epsilon_ij() const{
Eigen::ArrayXXd eps_(N,N);
for (auto i = 0; i < N; ++i){
for (auto j = i; j < N; ++j){
eps_(i,j) = (1.0-kmat(i,j))*sqrt(pow(sigma_ij(i,i),3)*pow(sigma_ij(j,j),3)*epsilon_over_k(i)*epsilon_over_k(j))/pow(sigma_ij(i,j), 3);
eps_(j,i) = eps_(i,j); // symmetric
}
}
return eps_;
}
std::size_t get_N(){
auto sizes = (Eigen::ArrayXd(5) << m.size(), epsilon_over_k.size(), sigma_A.size(), lambda_a.size(), lambda_r.size()).finished();
if (sizes.mean() != sizes.minCoeff()){
throw teqp::InvalidArgument("sizes of pure component arrays are not all the same");
}
return sizes[0];
}
/// Eq. A18 for the attractive exponents
auto get_cij(const Eigen::ArrayXXd& lambdaij) const{
std::vector<Eigen::ArrayXXd> cij(4);
for (auto n = 0; n < 4; ++n){
cij[n].resize(N,N);
};
for (auto i = 0; i < N; ++i){
for (auto j = i; j < N; ++j){
using CV = Eigen::Vector<double, 4>;
const CV b{(CV() << 1, 1.0/lambdaij(i,j), 1.0/pow(lambdaij(i,j),2), 1.0/pow(lambdaij(i,j),3)).finished()};
auto c1234 = (A*b).eval();
cij[0](i,j) = c1234(0);
cij[1](i,j) = c1234(1);
cij[2](i,j) = c1234(2);
cij[3](i,j) = c1234(3);
}
}
return cij;
}
/// Eq. A18 for the attractive exponents
auto get_canij() const{
return get_cij(lambda_a_ij);
}
/// Eq. A18 for 2x the attractive exponents
auto get_c2anij() const{
return get_cij(2.0*lambda_a_ij);
}
/// Eq. A18 for the repulsive exponents
auto get_crnij() const{
return get_cij(lambda_r_ij);
}
/// Eq. A18 for the 2x the repulsive exponents
auto get_c2rnij() const{
return get_cij(2.0*lambda_r_ij);
}
/// Eq. A18 for the 2x the repulsive exponents
auto get_carnij() const{
return get_cij(lambda_r_ij + lambda_a_ij);
}
public:
// One entry per component
const Eigen::ArrayXd m, epsilon_over_k, sigma_A, lambda_a, lambda_r;
const Eigen::ArrayXXd kmat;
const std::size_t N;
// Calculated matrices for the ij pair
const Eigen::ArrayXXd lambda_r_ij, lambda_a_ij, C_ij, alpha_ij, sigma_ij, epsilon_ij; // Matrices of parameters
const std::vector<Eigen::ArrayXXd> crnij, canij, c2rnij, c2anij, carnij;
const std::vector<Eigen::ArrayXXd> fkij; // Matrices of parameters
SAFTVRMieChainContributionTerms(
const Eigen::ArrayXd& m,
const Eigen::ArrayXd& epsilon_over_k,
const Eigen::ArrayXd& sigma_m,
const Eigen::ArrayXd& lambda_r,
const Eigen::ArrayXd& lambda_a,
const Eigen::ArrayXXd& kmat)
: m(m), epsilon_over_k(epsilon_over_k), sigma_A(sigma_m*1e10), lambda_a(lambda_a), lambda_r(lambda_r), kmat(kmat),
N(get_N()),
lambda_r_ij(get_lambda_k_ij(lambda_r)), lambda_a_ij(get_lambda_k_ij(lambda_a)),
C_ij(get_C_ij()), alpha_ij(C_ij*(1/(lambda_a_ij-3) - 1/(lambda_r_ij-3))),
sigma_ij(get_sigma_ij()), epsilon_ij(get_epsilon_ij()),
crnij(get_crnij()), canij(get_canij()),
c2rnij(get_c2rnij()), c2anij(get_c2anij()), carnij(get_carnij()),
fkij(get_fkij())
{}
/// Eq. A2 from Lafitte
template<typename RType>
auto get_uii_over_kB(std::size_t i, const RType& r) const {
auto rstarinv = forceeval(sigma_A[i]/r);
return forceeval(C_ij(i,i)*epsilon_over_k[i]*(pow(rstarinv, lambda_r[i]) - pow(rstarinv, lambda_a[i])));
}
/// Solve for the value of \f$j=\sigma/r\f$ for which the integrand in \f$d_{ii}\f$ becomes equal to 1 to numerical precision
template <typename TType>
auto get_j_cutoff_dii(std::size_t i, const TType &T) const {
auto lambda_a_ = lambda_a(i), lambda_r_ = lambda_r(i);
auto EPS = std::numeric_limits<decltype(getbaseval(T))>::epsilon();
auto K = forceeval(log(-log(EPS)*T/(C_ij(i,i)*epsilon_ij(i,i))));
auto j0 = forceeval(exp(K/lambda_r_)); // this was proposed by longemen3000 (Andrés Riedemann)
auto kappa = C_ij(i,i)*epsilon_ij(i,i);
// Function to return residual and its derivatives w.r.t.
auto fgh = [&kappa, &lambda_r_, &lambda_a_, &T, &EPS](auto j){
auto jlr = pow(j, lambda_r_), jla = pow(j, lambda_a_);
auto u = kappa*(jlr - jla);
auto uprime = kappa*(lambda_r_*jlr - lambda_a_*jla)/j;
auto uprime2 = kappa*(lambda_r_*(lambda_r_-1.0)*jlr - lambda_a_*(lambda_a_-1.0)*jla)/(j*j);
return std::make_tuple(forceeval(-u/T-log(EPS)), forceeval(-uprime/T), forceeval(-uprime2/T));
};
TType j = j0;
for (auto counter = 0; counter <= 3; ++counter){
// Halley's method steps
auto [R, Rprime, Rprime2] = fgh(j);
auto denominator = 2.0*Rprime*Rprime-R*Rprime2;
if (getbaseval(denominator) < EPS){
break;
}
j -= 2.0*R*Rprime/denominator;
}
double jbase = getbaseval(j);
if (jbase < 1.0){
throw teqp::IterationFailure("Cannot obtain a value of j");
}
return j;
}
/**
\note Eq. A9 from Lafitte
The calculation of the diameter is based upon
\f[
d_{ii} = \int_0^{\sigma_{ii}}(1-\exp(-\beta u_{ii}^{\rm Mie}(r)){\rm d}r
\f]
which is broken up into two parts:
\f[
d = \int_0^{r_{\rm cut}} 1 {\rm d} r + \int_{r_{\rm cut}}^{\sigma_{ii}} [1-\exp(-\beta u_{ii}^{\rm Mie}(r))] {\rm d}r
\f]
but the integrand is basically constant (to numerical precision) from 0 to some cutoff value of \f$r\f$, which we'll call \f$r_{\rm cut}\f$. So first we need to find the value of \f$r_{\rm cut}\f$ that makes the integrand take its constant value, which is explained well in the paper from Aasen (https://github.com/ClapeyronThermo/Clapeyron.jl/issues/152#issuecomment-1480324192). Finding the cutoff value is obtained when
\f[
\exp(-\beta u_{ii}^{\rm Mie}(r)) = EPS
\f]
where EPS is the numerical precision of the floating point type. Taking the logs of both sides,
\f[
-\beta u_{ii}^{\rm Mie} = \ln(EPS)
\f]
To get a starting value, it is first assumed that only the repulsive contribution contributes to the potential, yielding \f$u^{\rm rep} = C\epsilon(\sigma/r)^{\lambda_r}\f$ (with \f$C\f$ the same as the full potential with attraction) which yields
\f[
-\beta C\epsilon(\sigma/r)^{\lambda_r} = \ln(EPS)
\f]
and
\f[
(\sigma/r)_{\rm guess} = (-\ln(EPS)/(\beta C \epsilon))^{1/\lambda_r}
\f]
Then we solve for the residual \f$R(r)=0\f$, where \f$R_0=\exp(-u/T)-EPS\f$. Equivalently we can write the residual in logarithmic terms as \f$R=-u/T-\ln(EPS)\f$. This simplifies the rootfinding as you need \f$R\f$, \f$R'\f$ and \f$R''\f$ to apply Halley's method, which are themselves quite straightforward to obtain because \f$R'=-u'/T\f$, \f$R''=-u''/T\f$, where the primes are derivatives taken with respect to \f$\sigma/r\f$.
*/
template <typename TType>
TType get_dii(std::size_t i, const TType &T) const{
std::function<TType(TType)> integrand = [this, i, &T](const TType& r){
return forceeval(1.0-exp(-this->get_uii_over_kB(i, r)/T));
};
// Sum of the two integrals, one is constant, the other is from integration
auto rcut = forceeval(sigma_A[i]/get_j_cutoff_dii(i, T));
auto integral_contribution = quad<10, TType, TType>(integrand, rcut, sigma_A[i]);
auto d = forceeval(rcut + integral_contribution);
if (getbaseval(d) > sigma_A[i]){
throw teqp::IterationFailure("Value of d is larger than sigma; this is impossible");
}
return d;
}
template <typename TType>
auto get_dmat(const TType &T) const{
Eigen::Array<TType, Eigen::Dynamic, Eigen::Dynamic> d(N,N);
// For the pure components, by integration
for (auto i = 0; i < N; ++i){
d(i,i) = get_dii(i, T);
}
// The cross terms, using the linear mixing rule
for (auto i = 0; i < N; ++i){
for (auto j = i+1; j < N; ++j){
d(i,j) = (d(i,i) + d(j,j))/2.0;
d(j,i) = d(i,j);
}
}
return d;
}
// Calculate core parameters that depend on temperature, volume, and composition
template <typename TType, typename RhoType, typename VecType>
auto get_core_calcs(const TType& T, const RhoType& rhomolar, const VecType& molefracs) const{
if (molefracs.size() != N){
throw teqp::InvalidArgument("Length of molefracs of "+std::to_string(molefracs.size()) + " does not match the model size of"+std::to_string(N));
}
using FracType = std::decay_t<decltype(molefracs[0])>;
using NumType = std::common_type_t<TType, RhoType, FracType>;
// Things that are easy to calculate
// ....
auto dmat = get_dmat(T); // Matrix of diameters of pure and cross terms
auto rhoN = forceeval(rhomolar*N_A); // Number density, in molecules/m^3
auto mbar = forceeval((molefracs*m).sum()); // Mean number of segments, dimensionless
auto rhos = forceeval(rhoN*mbar/1e30); // Mean segment number density, in segments/A^3
auto xs = forceeval((m*molefracs/mbar).eval()); // Segment fractions
constexpr double MY_PI = static_cast<double>(EIGEN_PI);
auto pi6 = MY_PI/6;
using TRHOType = std::common_type_t<std::decay_t<TType>, std::decay_t<RhoType>, std::decay_t<decltype(molefracs[0])>, std::decay_t<decltype(m[0])>>;
Eigen::Array<TRHOType, 4, 1> zeta;
for (auto l = 0; l < 4; ++l){
TRHOType summer = 0.0;
for (auto i = 0; i < N; ++i){
summer += xs(i)*powi(dmat(i,i), l);
}
zeta(l) = forceeval(pi6*rhos*summer);
}
NumType summer_zeta_x = 0.0;
TRHOType summer_zeta_x_bar = 0.0;
for (auto i = 0; i < N; ++i){
for (auto j = 0; j < N; ++j){
summer_zeta_x += xs(i)*xs(j)*powi(dmat(i,j), 3)*rhos;
summer_zeta_x_bar += xs(i)*xs(j)*powi(sigma_ij(i,j), 3);
}
}
auto zeta_x = forceeval(pi6*summer_zeta_x); // Eq. A13
auto zeta_x_bar = forceeval(pi6*rhos*summer_zeta_x_bar); // Eq. A23
auto zeta_x_bar5 = forceeval(POW2(zeta_x_bar)*POW3(zeta_x_bar)); // (zeta_x_bar)^5
auto zeta_x_bar8 = forceeval(zeta_x_bar5*POW3(zeta_x_bar)); // (zeta_x_bar)^8
// Coefficients in the gdHSij term, do not depend on component,
// so calculate them here
auto X = forceeval(POW3(1.0 - zeta_x)), X3 = X;
auto X2 = forceeval(POW2(1.0 - zeta_x));
auto k0 = forceeval(-log(1.0-zeta_x) + (42.0*zeta_x - 39.0*POW2(zeta_x) + 9.0*POW3(zeta_x) - 2.0*POW4(zeta_x))/(6.0*X3)); // Eq. A30
auto k1 = forceeval((POW4(zeta_x) + 6.0*POW2(zeta_x) - 12.0*zeta_x)/(2.0*X3));
auto k2 = forceeval(-3.0*POW2(zeta_x)/(8.0*X2));
auto k3 = forceeval((-POW4(zeta_x) + 3.0*POW2(zeta_x) + 3.0*zeta_x)/(6.0*X3));
// Pre-calculate the cubes of the diameters
auto dmat3 = dmat.array().pow(3).eval();
NumType a1kB = 0.0;
NumType a2kB2 = 0.0;
NumType a3kB3 = 0.0;
NumType alphar_chain = 0.0;
NumType K_HS = get_KHS(zeta_x);
NumType rho_dK_HS_drho = get_rhos_dK_HS_drhos(zeta_x);
for (auto i = 0; i < N; ++i){
for (auto j = i; j < N; ++j){
NumType x_0_ij = sigma_ij(i,j)/dmat(i, j);
// -----------------------
// Calculations for a_1/kB
// -----------------------
auto I = [&x_0_ij](double lambda_ij){
return forceeval(-(pow(x_0_ij, 3-lambda_ij)-1.0)/(lambda_ij-3.0)); // Eq. A14
};
auto J = [&x_0_ij](double lambda_ij){
return forceeval(-(pow(x_0_ij, 4-lambda_ij)*(lambda_ij-3.0)-pow(x_0_ij, 3.0-lambda_ij)*(lambda_ij-4.0)-1.0)/((lambda_ij-3.0)*(lambda_ij-4.0))); // Eq. A15
};
auto Bhatij_a = this->get_Bhatij(zeta_x, X, I(lambda_a_ij(i,j)), J(lambda_a_ij(i,j)));
auto Bhatij_2a = this->get_Bhatij(zeta_x, X, I(2*lambda_a_ij(i,j)), J(2*lambda_a_ij(i,j)));
auto Bhatij_r = this->get_Bhatij(zeta_x, X, I(lambda_r_ij(i,j)), J(lambda_r_ij(i,j)));
auto Bhatij_2r = this->get_Bhatij(zeta_x, X, I(2*lambda_r_ij(i,j)), J(2*lambda_r_ij(i,j)));
auto Bhatij_ar = this->get_Bhatij(zeta_x, X, I(lambda_a_ij(i,j)+lambda_r_ij(i,j)), J(lambda_a_ij(i,j)+lambda_r_ij(i,j)));
auto one_term = [this, &x_0_ij, &I, &J, &zeta_x, &X](double lambda_ij, const NumType& zeta_x_eff){
return forceeval(
pow(x_0_ij, lambda_ij)*(
this->get_Bhatij(zeta_x, X, I(lambda_ij), J(lambda_ij))
+ this->get_a1Shatij(zeta_x_eff, lambda_ij)
)
);
};
NumType zeta_x_eff_r = crnij[0](i,j)*zeta_x + crnij[1](i,j)*POW2(zeta_x) + crnij[2](i,j)*POW3(zeta_x) + crnij[3](i,j)*POW4(zeta_x);
NumType zeta_x_eff_a = canij[0](i,j)*zeta_x + canij[1](i,j)*POW2(zeta_x) + canij[2](i,j)*POW3(zeta_x) + canij[3](i,j)*POW4(zeta_x);
NumType dzeta_x_eff_dzetax_r = crnij[0](i,j) + crnij[1](i,j)*2*zeta_x + crnij[2](i,j)*3*POW2(zeta_x) + crnij[3](i,j)*4*POW3(zeta_x);
NumType dzeta_x_eff_dzetax_a = canij[0](i,j) + canij[1](i,j)*2*zeta_x + canij[2](i,j)*3*POW2(zeta_x) + canij[3](i,j)*4*POW3(zeta_x);
NumType a1ij = 2.0*MY_PI*rhos*dmat3(i,j)*epsilon_ij(i,j)*C_ij(i,j)*(
one_term(lambda_a_ij(i,j), zeta_x_eff_a) - one_term(lambda_r_ij(i,j), zeta_x_eff_r)
); // divided by k_B
NumType contribution = xs(i)*xs(j)*a1ij;
double factor = (i == j) ? 1.0 : 2.0; // Off-diagonal terms contribute twice
a1kB += contribution*factor;
// --------------------------
// Calculations for a_2/k_B^2
// --------------------------
NumType zeta_x_eff_2r = c2rnij[0](i,j)*zeta_x + c2rnij[1](i,j)*POW2(zeta_x) + c2rnij[2](i,j)*POW3(zeta_x) + c2rnij[3](i,j)*POW4(zeta_x);
NumType zeta_x_eff_2a = c2anij[0](i,j)*zeta_x + c2anij[1](i,j)*POW2(zeta_x) + c2anij[2](i,j)*POW3(zeta_x) + c2anij[3](i,j)*POW4(zeta_x);
NumType zeta_x_eff_ar = carnij[0](i,j)*zeta_x + carnij[1](i,j)*POW2(zeta_x) + carnij[2](i,j)*POW3(zeta_x) + carnij[3](i,j)*POW4(zeta_x);
NumType dzeta_x_eff_dzetax_2r = c2rnij[0](i,j) + c2rnij[1](i,j)*2*zeta_x + c2rnij[2](i,j)*3*POW2(zeta_x) + c2rnij[3](i,j)*4*POW3(zeta_x);
NumType dzeta_x_eff_dzetax_ar = carnij[0](i,j) + carnij[1](i,j)*2*zeta_x + carnij[2](i,j)*3*POW2(zeta_x) + carnij[3](i,j)*4*POW3(zeta_x);
NumType dzeta_x_eff_dzetax_2a = c2anij[0](i,j) + c2anij[1](i,j)*2*zeta_x + c2anij[2](i,j)*3*POW2(zeta_x) + c2anij[3](i,j)*4*POW3(zeta_x);
NumType chi_ij = fkij[1](i,j)*zeta_x_bar + fkij[2](i,j)*zeta_x_bar5 + fkij[3](i,j)*zeta_x_bar8;
auto a2ij = 0.5*K_HS*(1.0+chi_ij)*epsilon_ij(i,j)*POW2(C_ij(i,j))*(2*MY_PI*rhos*dmat3(i,j)*epsilon_ij(i,j))*(
one_term(2.0*lambda_a_ij(i,j), zeta_x_eff_2a)
-2.0*one_term(lambda_a_ij(i,j)+lambda_r_ij(i,j), zeta_x_eff_ar)
+one_term(2.0*lambda_r_ij(i,j), zeta_x_eff_2r)
); // divided by k_B^2
NumType contributiona2 = xs(i)*xs(j)*a2ij; // Eq. A19
a2kB2 += contributiona2*factor;
// --------------------------
// Calculations for a_3/k_B^3
// --------------------------
auto a3ij = -POW3(epsilon_ij(i,j))*fkij[4](i,j)*zeta_x_bar*exp(
fkij[5](i,j)*zeta_x_bar + fkij[6](i,j)*POW2(zeta_x_bar)
); // divided by k_B^3
NumType contributiona3 = xs(i)*xs(j)*a3ij; // Eq. A25
a3kB3 += contributiona3*factor;
if (i == j){
// ------------------
// Chain contribution
// ------------------
// Eq. A29
auto gdHSii = exp(k0 + k1*x_0_ij + k2*POW2(x_0_ij) + k3*POW3(x_0_ij));
// The g1 terms
// ....
// This is the function for the second part (not the partial) that goes in g_{1,ii},
// divided by 2*PI*d_ij^3*epsilon*rhos
auto g1_term = [&one_term](double lambda_ij, const NumType& zeta_x_eff){
return forceeval(lambda_ij*one_term(lambda_ij, zeta_x_eff));
};
auto g1_noderivterm = -C_ij(i,i)*(g1_term(lambda_a_ij(i,i), zeta_x_eff_a)-g1_term(lambda_r_ij(i,i), zeta_x_eff_r));
// Bhat = B*rho*kappa; diff(Bhat, rho) = Bhat + rho*dBhat/drho; kappa = 2*pi*eps*d^3
// This is the function for the partial derivative rhos*(da1ij/drhos),
// divided by 2*PI*d_ij^3*epsilon*rhos
auto rhosda1iidrhos_term = [this, &x_0_ij, &I, &J, &zeta_x, &X](double lambda_ij, const NumType& zeta_x_eff, const NumType& dzetaxeff_dzetax, const NumType& Bhatij){
auto I_ = I(lambda_ij);
auto J_ = J(lambda_ij);
auto rhosda1Sdrhos = this->get_rhoda1Shatijdrho(zeta_x, zeta_x_eff, dzetaxeff_dzetax, lambda_ij);
auto rhosdBdrhos = this->get_rhodBijdrho(zeta_x, X, I_, J_, Bhatij);
return forceeval(pow(x_0_ij, lambda_ij)*(rhosda1Sdrhos + rhosdBdrhos));
};
// This is rhos*d(a_1ij)/drhos/(2*pi*d^3*eps*rhos)
auto da1iidrhos_term = C_ij(i,j)*(
rhosda1iidrhos_term(lambda_a_ij(i,i), zeta_x_eff_a, dzeta_x_eff_dzetax_a, Bhatij_a)
-rhosda1iidrhos_term(lambda_r_ij(i,i), zeta_x_eff_r, dzeta_x_eff_dzetax_r, Bhatij_r)
);
auto g1ii = 3.0*da1iidrhos_term + g1_noderivterm;
// The g2 terms
// ....
// This is the second part (not the partial deriv.) that goes in g_{2,ii},
// divided by 2*PI*d_ij^3*epsilon*rhos
auto g2_noderivterm = -POW2(C_ij(i,i))*K_HS*(
lambda_a_ij(i,j)*one_term(2*lambda_a_ij(i,j), zeta_x_eff_2a)
-(lambda_a_ij(i,j)+lambda_r_ij(i,j))*one_term(lambda_a_ij(i,j)+lambda_r_ij(i,j), zeta_x_eff_ar)
+lambda_r_ij(i,j)*one_term(2*lambda_r_ij(i,j), zeta_x_eff_2r)
);
// This is [rhos*d(a_2ij/(1+chi_ij))/drhos]/(2*pi*d^3*eps*rhos)
auto da2iidrhos_term = 0.5*POW2(C_ij(i,j))*(
rho_dK_HS_drho*(
one_term(2.0*lambda_a_ij(i,j), zeta_x_eff_2a)
-2.0*one_term(lambda_a_ij(i,j)+lambda_r_ij(i,j), zeta_x_eff_ar)
+one_term(2.0*lambda_r_ij(i,j), zeta_x_eff_2r))
+K_HS*(
rhosda1iidrhos_term(2.0*lambda_a_ij(i,i), zeta_x_eff_2a, dzeta_x_eff_dzetax_2a, Bhatij_2a)
-2.0*rhosda1iidrhos_term(lambda_a_ij(i,i)+lambda_r_ij(i,i), zeta_x_eff_ar, dzeta_x_eff_dzetax_ar, Bhatij_ar)
+rhosda1iidrhos_term(2.0*lambda_r_ij(i,i), zeta_x_eff_2r, dzeta_x_eff_dzetax_2r, Bhatij_2r)
)
);
auto g2MCAij = 3.0*da2iidrhos_term + g2_noderivterm;
auto betaepsilon = epsilon_ij(i,i)/T; // (1/(kB*T))/epsilon
auto theta = exp(betaepsilon)-1.0;
auto phi7 = phi.col(6);
auto gamma_cij = phi7(0)*(-tanh(phi7(1)*(phi7(2)-alpha_ij(i,j)))+1.0)*zeta_x_bar*theta*exp(phi7(3)*zeta_x_bar + phi7(4)*POW2(zeta_x_bar)); // Eq. A37
auto g2ii = (1.0+gamma_cij)*g2MCAij;
NumType giiMie = gdHSii*exp((betaepsilon*g1ii + POW2(betaepsilon)*g2ii)/gdHSii);
alphar_chain -= molefracs[i]*(m[i]-1.0)*log(giiMie);
}
}
}
auto ahs = get_a_HS(rhos, zeta);
// Eq. A5 from Lafitte, multiplied by mbar
auto alphar_mono = forceeval(mbar*(ahs + a1kB/T + a2kB2/(T*T) + a3kB3/(T*T*T)));
using dmat_t = decltype(dmat);
using rhos_t = decltype(rhos);
using rhoN_t = decltype(rhoN);
using mbar_t = decltype(mbar);
using xs_t = decltype(xs);
using zeta_t = decltype(zeta);
using zeta_x_t = decltype(zeta_x);
using zeta_x_bar_t = decltype(zeta_x_bar);
using alphar_mono_t = decltype(alphar_mono);
using a1kB_t = decltype(a1kB);
using a2kB2_t = decltype(a2kB2);
using a3kB3_t = decltype(a3kB3);
using alphar_chain_t = decltype(alphar_chain);
struct vals{
dmat_t dmat;
rhos_t rhos;
rhoN_t rhoN;
mbar_t mbar;
xs_t xs;
zeta_t zeta;
zeta_x_t zeta_x;
zeta_x_bar_t zeta_x_bar;
alphar_mono_t alphar_mono;
a1kB_t a1kB;
a2kB2_t a2kB2;
a3kB3_t a3kB3;
alphar_chain_t alphar_chain;
};
return vals{dmat, rhos, rhoN, mbar, xs, zeta, zeta_x, zeta_x_bar, alphar_mono, a1kB, a2kB2, a3kB3, alphar_chain};
}
/// Eq. A21 from Lafitte
template<typename RhoType>
auto get_KHS(const RhoType& pf) const {
return forceeval(pow(1.0-pf,4)/(1.0 + 4.0*pf + 4.0*pf*pf - 4.0*pf*pf*pf + pf*pf*pf*pf));
}
/**
\f[
\rho_s\frac{\partial K_{HS}}{\partial \rho_s} = \zeta\frac{\partial K_{HS}}{\partial \zeta}
\f]
*/
template<typename RhoType>
auto get_rhos_dK_HS_drhos(const RhoType& zeta_x) const {
auto num = -4.0*POW3(zeta_x - 1.0)*(POW2(zeta_x) - 5.0*zeta_x - 2.0);
auto den = POW2(POW4(zeta_x) - 4.0*POW3(zeta_x) + 4.0*POW2(zeta_x) + 4.0*zeta_x + 1.0);
return forceeval(num/den*zeta_x);
}
/// Eq. A6 from Lafitte, accounting for the case of rho_s=0, for which the limit is zero
template<typename RhoType, typename ZetaType>
auto get_a_HS(const RhoType& rhos, const Eigen::Array<ZetaType, 4, 1>& zeta) const{
constexpr double MY_PI = static_cast<double>(EIGEN_PI);
if (getbaseval(rhos) == 0){
// The way in which the function goes to zero is subtle, and the factor of 4 accounts for the contributions from each term
return forceeval(4.0*zeta[3]);
}
else{
return forceeval(6.0/(MY_PI*rhos)*(3.0*zeta[1]*zeta[2]/(1.0-zeta[3]) + POW3(zeta[2])/(zeta[3]*POW2(1.0-zeta[3])) + (POW3(zeta[2])/POW2(zeta[3])-zeta[0])*log(1.0-zeta[3])));
}
}
/**
\note Starting from Eq. A12 from Lafitte
Defining:
\f[
\hat B_{ij} \equiv \frac{B_{ij}}{2\pi\epsilon_{ij}d^3_{ij}\rho_s} = \frac{1-\zeta_x/2}{(1-\zeta_x)^3}I-\frac{9\zeta_x(1+\zeta_x)}{2(1-\zeta_x)^3}J
\f]
*/
template<typename ZetaType, typename IJ>
auto get_Bhatij(const ZetaType& zeta_x, const ZetaType& one_minus_zeta_x3, const IJ& I, const IJ& J) const{
return forceeval(
(1.0-zeta_x/2.0)/one_minus_zeta_x3*I - 9.0*zeta_x*(1.0+zeta_x)/(2.0*one_minus_zeta_x3)*J
);
}
/**
\f[
B = \hat B_{ij}\kappa \rho_s
\f]
\f[
\left(\frac{\partial B_{ij}}{\partial \rho_s}\right)_{T,\vec{z}} = \kappa\left(\hat B + \zeta_x \frac{\partial \hat B}{\partial \zeta_x}\right)
\f]
and thus
\f[
\rho_s \left(\frac{\partial B_{ij}}{\partial \rho_s}\right)_{T,\vec{z}} = \hat B + \zeta_x \frac{\partial \hat B}{\partial \zeta_x}
\f]
*/
template<typename ZetaType, typename IJ>
auto get_rhodBijdrho(const ZetaType& zeta_x, const ZetaType& one_minus_zeta_x3, const IJ& I, const IJ& J, const ZetaType& Bhatij) const{
auto dBhatdzetax = (-3.0*I*(zeta_x - 2.0) - 27.0*J*zeta_x*(zeta_x + 1.0) + (zeta_x - 1.0)*(I + 9.0*J*zeta_x + 9.0*J*(zeta_x + 1.0)))/(2.0*POW4(1.0-zeta_x));
return forceeval(Bhatij + dBhatdzetax*zeta_x);
}
/**
\note Starting from Eq. A16 from Lafitte
\f[
\hat a^S_{1,ii} = \frac{a^S_{1,ii}}{2\pi\epsilon_{ij}d^3_{ij}\rho_s}
\f]
so
\f[
a^S_{1,ii} = \kappa\rho_s\hat a^S_{1,ii}
\f]
*/
template<typename ZetaType>
auto get_a1Shatij(const ZetaType& zeta_x_eff, double lambda_ij) const{
return forceeval(
-1.0/(lambda_ij-3.0)*(1.0-zeta_x_eff/2.0)/POW3(forceeval(1.0-zeta_x_eff))
);
}
/**
\f[
\left(\frac{\partial a^S_{1,ii}}{\partial \rho_s}\right)_{T,\vec{z}} = \kappa\left(\hat a^S_{1,ii} + \rho_s\frac{\partial \hat a^S_{1,ii}}{\partial \rho_s} \right)
\f]
\f[
\left(\frac{\partial a^S_{1,ii}}{\partial \rho_s}\right)_{T,\vec{z}} = \kappa\left(\hat a^S_{1,ii} + \rho_s\frac{\partial \hat a^S_{1,ii}}{\partial \zeta_{x,eff}}\frac{\partial \zeta_{x,eff}}{\partial \zeta_x}\frac{\partial \zeta_x}{\partial \rho_s} \right)
\f]
since \f$\rho_s\frac{\partial \zeta_x}{\partial \rho_s} = \zeta_x\f$
*/
template<typename ZetaType>
auto get_rhoda1Shatijdrho(const ZetaType& zeta_x, const ZetaType& zeta_x_eff, const ZetaType& dzetaxeffdzetax, double lambda_ij) const{
auto zetaxda1Shatdzetax = ((2.0*zeta_x_eff - 5.0)*dzetaxeffdzetax)/(2.0*(lambda_ij-3)*POW4(zeta_x_eff-1.0))*zeta_x;
return forceeval(get_a1Shatij(zeta_x_eff, lambda_ij) + zetaxda1Shatdzetax);
}
};
/**
\brief A class used to evaluate mixtures using the SAFT-VR-Mie model
*/
class SAFTVRMieMixture {
private:
std::vector<std::string> names;
const SAFTVRMieChainContributionTerms terms;
const std::optional<SAFTpolar::multipolar_contributions_variant> polar; // Can be present or not
static void check_kmat(const Eigen::ArrayXXd& kmat, std::size_t N) {
if (kmat.size() == 0){
return;
}
if (kmat.cols() != kmat.rows()) {
throw teqp::InvalidArgument("kmat rows and columns are not identical");
}
if (kmat.cols() != N) {
throw teqp::InvalidArgument("kmat needs to be a square matrix the same size as the number of components");
}
};
static auto get_coeffs_from_names(const std::vector<std::string> &names){
SAFTVRMieLibrary library;
return library.get_coeffs(names);
}
public:
static auto build_chain(const std::vector<SAFTVRMieCoeffs> &coeffs, const std::optional<Eigen::ArrayXXd>& kmat){
if (kmat){
check_kmat(kmat.value(), coeffs.size());
}
const std::size_t N = coeffs.size();
Eigen::ArrayXd m(N), epsilon_over_k(N), sigma_m(N), lambda_r(N), lambda_a(N);
auto i = 0;
for (const auto &coeff : coeffs) {
m[i] = coeff.m;
epsilon_over_k[i] = coeff.epsilon_over_k;
sigma_m[i] = coeff.sigma_m;
lambda_r[i] = coeff.lambda_r;
lambda_a[i] = coeff.lambda_a;
i++;
}
if (kmat){
return SAFTVRMieChainContributionTerms(m, epsilon_over_k, sigma_m, lambda_r, lambda_a, std::move(kmat.value()));
}
else{
auto mat = Eigen::ArrayXXd::Zero(N,N);
return SAFTVRMieChainContributionTerms(m, epsilon_over_k, sigma_m, lambda_r, lambda_a, std::move(mat));
}
}
auto build_polar(const std::vector<SAFTVRMieCoeffs> &coeffs) -> decltype(this->polar){
Eigen::ArrayXd mustar2(coeffs.size()), nmu(coeffs.size()), Qstar2(coeffs.size()), nQ(coeffs.size());
auto i = 0;
for (const auto &coeff : coeffs) {
mustar2[i] = coeff.mustar2;
nmu[i] = coeff.nmu;
Qstar2[i] = coeff.Qstar2;
nQ[i] = coeff.nQ;
i++;
}
bool has_dipolar = ((mustar2*nmu).cwiseAbs().sum() == 0);
bool has_quadrupolar = ((Qstar2*nQ).cwiseAbs().sum() == 0);
if (!has_dipolar && !has_quadrupolar){
return std::nullopt; // No dipolar or quadrupolar contribution is present
}
else{
// The dispersive and hard chain initialization has already happened at this point
return SAFTpolar::MultipolarContributionGrossVrabec(terms.m, terms.sigma_A, terms.epsilon_over_k, mustar2, nmu, Qstar2, nQ);
}
}
public:
SAFTVRMieMixture(const std::vector<std::string> &names, const std::optional<Eigen::ArrayXXd>& kmat = std::nullopt) : SAFTVRMieMixture(get_coeffs_from_names(names), kmat){};
SAFTVRMieMixture(const std::vector<SAFTVRMieCoeffs> &coeffs, const std::optional<Eigen::ArrayXXd> &kmat = std::nullopt) : terms(build_chain(coeffs, kmat)), polar(build_polar(coeffs)) {};
SAFTVRMieMixture(SAFTVRMieChainContributionTerms&& terms, std::optional<SAFTpolar::multipolar_contributions_variant> &&polar = std::nullopt) : terms(std::move(terms)), polar(std::move(polar)) {};
// PCSAFTMixture( const PCSAFTMixture& ) = delete; // non construction-copyable
SAFTVRMieMixture& operator=( const SAFTVRMieMixture& ) = delete; // non copyable
auto chain_factory(const std::vector<SAFTVRMieCoeffs> &coeffs, const std::optional<Eigen::ArrayXXd>& kmat){
SAFTVRMieMixture::build_chain(coeffs, kmat);
}
const auto& get_polar(){ return polar; }
// Checker for whether a polar term is present
bool has_polar() const{ return polar.has_value(); }
const auto& get_terms() const { return terms; }
auto get_core_calcs(double T, double rhomolar, const Eigen::ArrayXd& mole_fractions) const {
auto val = terms.get_core_calcs(T, rhomolar, mole_fractions);
auto fromArrayX = [](const Eigen::ArrayXd &x){std::valarray<double>n(x.size()); for (auto i =0; i < n.size(); ++i){ n[i] = x[i];} return n;};
auto fromArrayXX = [](const Eigen::ArrayXXd &x){
std::size_t N = x.rows();
std::vector<std::vector<double>> n; n.resize(N);
for (auto i = 0; i < N; ++i){
n[i].resize(N);
for (auto j = 0; j < N; ++j){
n[i][j] = x(i,j);
}
}
return n;
};
return nlohmann::json{
{"dmat", fromArrayXX(val.dmat)},
{"rhos", val.rhos},
{"rhoN", val.rhoN},
{"mbar", val.mbar},
{"xs", fromArrayX(val.xs)},
{"zeta", fromArrayX(val.zeta)},
{"zeta_x", val.zeta_x},
{"zeta_x_bar", val.zeta_x_bar},
{"alphar_mono", val.alphar_mono},
{"a1kB", val.a1kB},
{"a2kB2", val.a2kB2},
{"a3kB3", val.a3kB3},
{"alphar_chain", val.alphar_chain}
};
}
auto get_m() const { return terms.m; }
auto get_sigma_Angstrom() const { return (terms.sigma_A).eval(); }
auto get_sigma_m() const { return terms.sigma_A/1e10; }
auto get_epsilon_over_k_K() const { return terms.epsilon_over_k; }
auto get_kmat() const { return terms.kmat; }
auto get_lambda_r() const { return terms.lambda_r; }
auto get_lambda_a() const { return terms.lambda_a; }
// template<typename VecType>
// double max_rhoN(const double T, const VecType& mole_fractions) const {
// auto N = mole_fractions.size();
// Eigen::ArrayX<double> d(N);
// for (auto i = 0; i < N; ++i) {
// d[i] = sigma_Angstrom[i] * (1.0 - 0.12 * exp(-3.0 * epsilon_over_k[i] / T));
// }
// return 6 * 0.74 / EIGEN_PI / (mole_fractions*m*powvec(d, 3)).sum()*1e30; // particles/m^3
// }
template<class VecType>
auto R(const VecType& molefrac) const {
return get_R_gas<decltype(molefrac[0])>();
}
template<typename TTYPE, typename RhoType, typename VecType>
auto alphar(const TTYPE& T, const RhoType& rhomolar, const VecType& mole_fractions) const {
// First values for the Mie chain with dispersion (always included)
error_if_expr(T); error_if_expr(rhomolar);
auto vals = terms.get_core_calcs(T, rhomolar, mole_fractions);
using type = std::common_type_t<TTYPE, RhoType, decltype(mole_fractions[0])>;
type alphar = vals.alphar_mono + vals.alphar_chain;
type packing_fraction = vals.zeta[3];
if (polar){ // polar term is present
using mas = SAFTpolar::multipolar_argument_spec;
auto visitor = [&T, &rhomolar, &mole_fractions, &packing_fraction](const auto& contrib) -> type {
constexpr mas arg_spec = std::decay_t<decltype(contrib)>::arg_spec;
if constexpr(arg_spec == mas::TK_rhoNA3_packingfraction_molefractions){
RhoType rho_A3 = rhomolar*N_A*1e-30;
type alpha = contrib.eval(T, rho_A3, packing_fraction, mole_fractions).alpha;
return alpha;
}
else if constexpr(arg_spec == mas::TK_rhoNm3_rhostar_molefractions){
RhoType rhoN_m3 = rhomolar*N_A;
auto rhostar = contrib.get_rhostar(rhoN_m3, packing_fraction, mole_fractions);
return contrib.eval(T, rhoN_m3, rhostar, mole_fractions).alpha;
}
else{
throw teqp::InvalidArgument("Don't know how to handle this kind of arguments in polar term");
}
};
alphar += std::visit(visitor, polar.value());
}
return forceeval(alphar);
}
};
inline auto SAFTVRMiefactory(const nlohmann::json & spec){
std::optional<Eigen::ArrayXXd> kmat;
if (spec.contains("kmat") && spec.at("kmat").is_array() && spec.at("kmat").size() > 0){
kmat = build_square_matrix(spec["kmat"]);
}
if (spec.contains("names")){
std::vector<std::string> names = spec["names"];
if (kmat && kmat.value().rows() != names.size()){
throw teqp::InvalidArgument("Provided length of names of " + std::to_string(names.size()) + " does not match the dimension of the kmat of " + std::to_string(kmat.value().rows()));
}
return SAFTVRMieMixture(names, kmat);
}
else if (spec.contains("coeffs")){
bool something_polar = false;
std::vector<SAFTVRMieCoeffs> coeffs;
for (auto j : spec["coeffs"]) {
SAFTVRMieCoeffs c;
c.name = j.at("name");
c.m = j.at("m");
c.sigma_m = (j.contains("sigma_m")) ? j.at("sigma_m").get<double>() : j.at("sigma_Angstrom").get<double>()/1e10;
c.epsilon_over_k = j.at("epsilon_over_k");
c.lambda_r = j.at("lambda_r");
c.lambda_a = j.at("lambda_a");
c.BibTeXKey = j.at("BibTeXKey");
// These are legacy definitions of the polar moments
if (j.contains("(mu^*)^2") && j.contains("nmu")){
c.mustar2 = j.at("(mu^*)^2");
c.nmu = j.at("nmu");
something_polar = true;
}
if (j.contains("(Q^*)^2") && j.contains("nQ")){
c.Qstar2 = j.at("(Q^*)^2");
c.nQ = j.at("nQ");
something_polar = true;
}
if (j.contains("Q_Cm2") || j.contains("Q_DA") || j.contains("mu_Cm") || j.contains("mu_D")){
something_polar = true;
}
coeffs.push_back(c);
}
if (kmat && kmat.value().rows() != coeffs.size()){
throw teqp::InvalidArgument("Provided length of coeffs of " + std::to_string(coeffs.size()) + " does not match the dimension of the kmat of " + std::to_string(kmat.value().rows()));
}
if (!something_polar){
// Nonpolar, just m, epsilon, sigma and possibly a kmat matrix with kij coefficients
return SAFTVRMieMixture(SAFTVRMieMixture::build_chain(coeffs, kmat));
}
else{
// Polar term is also provided, along with the chain terms
std::string polar_model = "GrossVrabec"; // This is the default, as it was the first one implemented
if (spec.contains("polar_model")){
polar_model = spec["polar_model"];
}
// Go back and extract the dipolar and quadrupolar terms from
// the JSON, in base SI units
const double D_to_Cm = 3.33564e-30; // C m/D
const double mustar2factor = 1.0/(4*static_cast<double>(EIGEN_PI)*8.8541878128e-12*1.380649e-23); // factor=1/(4*pi*epsilon_0*k_B), such that (mu^*)^2 := factor*mu[Cm]^2/((epsilon/kB)[K]*sigma[m]^3)
const double Qstar2factor = 1.0/(4*static_cast<double>(EIGEN_PI)*8.8541878128e-12*1.380649e-23); // same as mustar2factor
auto N = coeffs.size();
Eigen::ArrayXd ms(N), epsks(N), sigma_ms(N), mu_Cm(N), Q_Cm2(N), nQ(N), nmu(N);
Eigen::Index i = 0;
for (auto j : spec["coeffs"]) {
double m = j.at("m");
double sigma_m = (j.contains("sigma_m")) ? j.at("sigma_m").get<double>() : j.at("sigma_Angstrom").get<double>()/1e10;
double epsilon_over_k = j.at("epsilon_over_k");
auto get_dipole_Cm = [&]() -> double {
if (j.contains("(mu^*)^2") && j.contains("nmu")){
// Terms defined like in Gross&Vrabec; backwards-compatibility
double mustar2 = j.at("(mu^*)^2");
return sqrt(mustar2*(m*epsilon_over_k*pow(sigma_m, 3))/mustar2factor);
}
else if (j.contains("mu_Cm")){
return j.at("mu_Cm");
}
else if (j.contains("mu_D")){
return j.at("mu_D").get<double>()*D_to_Cm;
}
else{
return 0.0;
}
};
auto get_quadrupole_Cm2 = [&]() -> double{
if (j.contains("(Q^*)^2") && j.contains("nQ")){
// Terms defined like in Gross&Vrabec; backwards-compatibility
double Qstar2 = j.at("(Q^*)^2");
return sqrt(Qstar2*(m*epsilon_over_k*pow(sigma_m, 5))/Qstar2factor);
}
else if (j.contains("Q_Cm2")){
return j.at("Q_Cm2");
}
else if (j.contains("Q_DA")){
return j.at("Q_DA").get<double>()*D_to_Cm*1e10;
}
else{
return 0.0;
}
};
ms(i) = m; sigma_ms(i) = sigma_m; epsks(i) = epsilon_over_k; mu_Cm(i) = get_dipole_Cm(); Q_Cm2(i) = get_quadrupole_Cm2();
nmu(i) = (j.contains("nmu") ? j["nmu"].get<double>() : 0.0);
nQ(i) = (j.contains("nQ") ? j["nQ"].get<double>() : 0.0);
i++;
};
using namespace SAFTpolar;
if (polar_model == "GrossVrabec"){
auto mustar2 = (mustar2factor*mu_Cm.pow(2)/(ms*epsks*sigma_ms.pow(3))).eval();
auto Qstar2 = (Qstar2factor*Q_Cm2.pow(2)/(ms*epsks*sigma_ms.pow(5))).eval();
auto polar = MultipolarContributionGrossVrabec(ms, sigma_ms*1e10, epsks, mustar2, nmu, Qstar2, nQ);
return SAFTVRMieMixture(SAFTVRMieMixture::build_chain(coeffs, kmat), std::move(polar));
}
if (polar_model == "GubbinsTwu+Luckas"){
using MCGTL = MultipolarContributionGubbinsTwu<LuckasJIntegral, LuckasKIntegral>;
auto mubar2 = (mustar2factor*mu_Cm.pow(2)/(epsks*sigma_ms.pow(3))).eval();
auto Qbar2 = (Qstar2factor*Q_Cm2.pow(2)/(epsks*sigma_ms.pow(5))).eval();
auto polar = MCGTL(sigma_ms, epsks, mubar2, Qbar2, multipolar_rhostar_approach::use_packing_fraction);
return SAFTVRMieMixture(SAFTVRMieMixture::build_chain(coeffs, kmat), std::move(polar));
}
if (polar_model == "GubbinsTwu+GubbinsTwu"){
using MCGG = MultipolarContributionGubbinsTwu<GubbinsTwuJIntegral, GubbinsTwuKIntegral>;
auto mubar2 = (mustar2factor*mu_Cm.pow(2)/(epsks*sigma_ms.pow(3))).eval();
auto Qbar2 = (Qstar2factor*Q_Cm2.pow(2)/(epsks*sigma_ms.pow(5))).eval();
auto polar = MCGG(sigma_ms, epsks, mubar2, Qbar2, multipolar_rhostar_approach::use_packing_fraction);
return SAFTVRMieMixture(SAFTVRMieMixture::build_chain(coeffs, kmat), std::move(polar));
}
if (polar_model == "GubbinsTwu+Luckas+GubbinsTwuRhostar"){
using MCGTL = MultipolarContributionGubbinsTwu<LuckasJIntegral, LuckasKIntegral>;
auto mubar2 = (mustar2factor*mu_Cm.pow(2)/(epsks*sigma_ms.pow(3))).eval();
auto Qbar2 = (Qstar2factor*Q_Cm2.pow(2)/(epsks*sigma_ms.pow(5))).eval();
auto polar = MCGTL(sigma_ms, epsks, mubar2, Qbar2, multipolar_rhostar_approach::calculate_Gubbins_rhostar);
return SAFTVRMieMixture(SAFTVRMieMixture::build_chain(coeffs, kmat), std::move(polar));
}
if (polar_model == "GubbinsTwu+GubbinsTwu+GubbinsTwuRhostar"){
using MCGG = MultipolarContributionGubbinsTwu<GubbinsTwuJIntegral, GubbinsTwuKIntegral>;
auto mubar2 = (mustar2factor*mu_Cm.pow(2)/(epsks*sigma_ms.pow(3))).eval();
auto Qbar2 = (Qstar2factor*Q_Cm2.pow(2)/(epsks*sigma_ms.pow(5))).eval();
auto polar = MCGG(sigma_ms, epsks, mubar2, Qbar2, multipolar_rhostar_approach::calculate_Gubbins_rhostar);
return SAFTVRMieMixture(SAFTVRMieMixture::build_chain(coeffs, kmat), std::move(polar));
}
throw teqp::InvalidArgument("didn't understand this polar_model:"+polar_model);
}
}
else{
throw std::invalid_argument("you must provide names or coeffs, but not both");
}
}
} /* namespace SAFTVRMie */
}; // namespace teqp