/***
\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/exceptions.hpp"
#include "teqp/constants.hpp"
#include "teqp/math/quadrature.hpp"
#include <optional>
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)
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_a, const double lambda_r, 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. A45
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_A(i,i),3)*pow(sigma_A(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::ArrayXd& 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);
}
template<typename X>
auto POW2(const X& x) const{
return forceeval(x*x);
};
template<typename X>
auto POW3(const X& x) const{
return forceeval(x*POW2(x));
};
template<typename X>
auto POW4(const X& x) const{
return forceeval(POW2(x)*POW2(x));
};
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> canij, crnij, c2anij, c2rnij, 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::ArrayXd& 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())
{}
template<typename R>
R get_uii_over_kB(std::size_t i, const R& r) const {
auto rstarinv = sigma_A[i]/r;
return C_ij(i,i)*epsilon_over_k[i]*(::pow(rstarinv, lambda_r[i]) - ::pow(rstarinv, lambda_a[i]));
}
template <typename TType>
auto get_dii(std::size_t i, const TType &T) const{
std::function<TType(double)> integrand = [this, i, &T](const double& r){
return forceeval(1.0-exp(-this->get_uii_over_kB(i, r)/T));
};
return forceeval(quad<7, TType>(integrand, 0.0, sigma_A[i]));
}
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{
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_xi_x = 0.0;
TRHOType summer_xi_x_bar = 0.0;
for (auto i = 0; i < N; ++i){
for (auto j = 0; j < N; ++j){
summer_xi_x += xs(i)*xs(j)*powi(dmat(i,j), 3)*rhos;
summer_xi_x_bar += xs(i)*xs(j)*powi(sigma_ij(i,j), 3);
}
}
auto xi_x = forceeval(pi6*summer_xi_x); // Eq. A13
auto xi_x_bar = forceeval(pi6*rhos*summer_xi_x_bar); // Eq. A23
auto xi_x_bar5 = forceeval(POW2(xi_x_bar)*POW3(xi_x_bar)); // (xi_x_bar)^5
auto xi_x_bar8 = forceeval(xi_x_bar5*POW3(xi_x_bar)); // (xi_x_bar)^8
// Coefficients in the gdHSij term, do not depend on component,
// so calculate them here
auto X = forceeval(POW3(1.0 - xi_x)), X3 = X;
auto X2 = forceeval(POW2(1.0 - xi_x));
auto k0 = forceeval(-log(1.0-xi_x) + (42.0*xi_x - 39.0*POW2(xi_x) + 9.0*POW3(xi_x) - 2.0*POW4(xi_x))/(6.0*X3)); // Eq. A30
auto k1 = forceeval((POW4(xi_x) + 6.0*POW2(xi_x) - 12.0*xi_x)/(2.0*X3));
auto k2 = forceeval(-3.0*POW2(xi_x)/(8.0*X2));
auto k3 = forceeval((-POW4(xi_x) + 3.0*POW2(xi_x) + 3.0*xi_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(xi_x);
NumType rho_dK_HS_drho = get_rhos_dK_HS_drhos(xi_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(xi_x, X, I(lambda_a_ij(i,j)), J(lambda_a_ij(i,j)));
auto Bhatij_2a = this->get_Bhatij(xi_x, X, I(2*lambda_a_ij(i,j)), J(2*lambda_a_ij(i,j)));
auto Bhatij_r = this->get_Bhatij(xi_x, X, I(lambda_r_ij(i,j)), J(lambda_r_ij(i,j)));
auto Bhatij_2r = this->get_Bhatij(xi_x, X, I(2*lambda_r_ij(i,j)), J(2*lambda_r_ij(i,j)));
auto Bhatij_ar = this->get_Bhatij(xi_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, &xi_x, &X](double lambda_ij, const NumType& xi_x_eff){
return forceeval(
pow(x_0_ij, lambda_ij)*(
this->get_Bhatij(xi_x, X, I(lambda_ij), J(lambda_ij))
+ this->get_a1Shatij(xi_x_eff, lambda_ij)
)
);
};
NumType xi_x_eff_r = crnij[0](i,j)*xi_x + crnij[1](i,j)*POW2(xi_x) + crnij[2](i,j)*POW3(xi_x) + crnij[3](i,j)*POW4(xi_x);
NumType xi_x_eff_a = canij[0](i,j)*xi_x + canij[1](i,j)*POW2(xi_x) + canij[2](i,j)*POW3(xi_x) + canij[3](i,j)*POW4(xi_x);
NumType dxi_x_eff_dxix_r = crnij[0](i,j) + crnij[1](i,j)*2*xi_x + crnij[2](i,j)*3*POW2(xi_x) + crnij[3](i,j)*4*POW3(xi_x);
NumType dxi_x_eff_dxix_a = canij[0](i,j) + canij[1](i,j)*2*xi_x + canij[2](i,j)*3*POW2(xi_x) + canij[3](i,j)*4*POW3(xi_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), xi_x_eff_a) - one_term(lambda_r_ij(i,j), xi_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 xi_x_eff_2r = c2rnij[0](i,j)*xi_x + c2rnij[1](i,j)*POW2(xi_x) + c2rnij[2](i,j)*POW3(xi_x) + c2rnij[3](i,j)*POW4(xi_x);
NumType xi_x_eff_2a = c2anij[0](i,j)*xi_x + c2anij[1](i,j)*POW2(xi_x) + c2anij[2](i,j)*POW3(xi_x) + c2anij[3](i,j)*POW4(xi_x);
NumType xi_x_eff_ar = carnij[0](i,j)*xi_x + carnij[1](i,j)*POW2(xi_x) + carnij[2](i,j)*POW3(xi_x) + carnij[3](i,j)*POW4(xi_x);
NumType dxi_x_eff_dxix_2r = c2rnij[0](i,j) + c2rnij[1](i,j)*2*xi_x + c2rnij[2](i,j)*3*POW2(xi_x) + c2rnij[3](i,j)*4*POW3(xi_x);
NumType dxi_x_eff_dxix_ar = carnij[0](i,j) + carnij[1](i,j)*2*xi_x + carnij[2](i,j)*3*POW2(xi_x) + carnij[3](i,j)*4*POW3(xi_x);
NumType dxi_x_eff_dxix_2a = c2anij[0](i,j) + c2anij[1](i,j)*2*xi_x + c2anij[2](i,j)*3*POW2(xi_x) + c2anij[3](i,j)*4*POW3(xi_x);
NumType chi_ij = fkij[1](i,j)*xi_x_bar + fkij[2](i,j)*xi_x_bar5 + fkij[3](i,j)*xi_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), xi_x_eff_2a)
-2.0*one_term(lambda_a_ij(i,j)+lambda_r_ij(i,j), xi_x_eff_ar)
+one_term(2.0*lambda_r_ij(i,j), xi_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)*xi_x_bar*exp(
fkij[5](i,j)*xi_x_bar + fkij[6](i,j)*POW2(xi_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& xi_x_eff){
return forceeval(lambda_ij*one_term(lambda_ij, xi_x_eff));
};
auto g1_noderivterm = -C_ij(i,i)*(g1_term(lambda_a_ij(i,i), xi_x_eff_a)-g1_term(lambda_r_ij(i,i), xi_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, &xi_x, &X](double lambda_ij, const NumType& xi_x_eff, const NumType& dxixeff_dxix, const NumType& Bhatij){
auto I_ = I(lambda_ij);
auto J_ = J(lambda_ij);
auto rhosda1Sdrhos = this->get_rhoda1Shatijdrho(xi_x, xi_x_eff, dxixeff_dxix, lambda_ij);
auto rhosdBdrhos = this->get_rhodBijdrho(xi_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), xi_x_eff_a, dxi_x_eff_dxix_a, Bhatij_a)
-rhosda1iidrhos_term(lambda_r_ij(i,i), xi_x_eff_r, dxi_x_eff_dxix_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), xi_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), xi_x_eff_ar)
+lambda_r_ij(i,j)*one_term(2*lambda_r_ij(i,j), xi_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), xi_x_eff_2a)
-2.0*one_term(lambda_a_ij(i,j)+lambda_r_ij(i,j), xi_x_eff_ar)
+one_term(2.0*lambda_r_ij(i,j), xi_x_eff_2r))
+K_HS*(
rhosda1iidrhos_term(2.0*lambda_a_ij(i,i), xi_x_eff_2a, dxi_x_eff_dxix_2a, Bhatij_2a)
-2.0*rhosda1iidrhos_term(lambda_a_ij(i,i)+lambda_r_ij(i,i), xi_x_eff_ar, dxi_x_eff_dxix_ar, Bhatij_ar)
+rhosda1iidrhos_term(2.0*lambda_r_ij(i,i), xi_x_eff_2r, dxi_x_eff_dxix_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)*xi_x_bar*theta*exp(phi7(3)*xi_x_bar + phi7(4)*POW2(xi_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 = a_HS(rhos, zeta);
auto alphar_mono = mbar*(ahs + a1kB/T + a2kB2/(T*T) + a3kB3/(T*T*T));
struct vals{
decltype(dmat) dmat;
decltype(rhos) rhos;
decltype(rhoN) rhoN;
decltype(mbar) mbar;
decltype(xs) xs;
decltype(zeta) zeta;
decltype(xi_x) xi_x;
decltype(xi_x_bar) xi_x_bar;
decltype(alphar_mono) alphar_mono;
decltype(a1kB) a1kB;
decltype(a2kB2) a2kB2;
decltype(a3kB3) a3kB3;
decltype(alphar_chain) alphar_chain;
};
return vals{dmat, rhos, rhoN, mbar, xs, zeta, xi_x, xi_x_bar, alphar_mono, a1kB, a2kB2, a3kB3, alphar_chain};
}
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} = \xi\frac{\partial K_{HS}}{\partial \xi}
\f]
*/
template<typename RhoType>
auto get_rhos_dK_HS_drhos(const RhoType& xi_x) const {
auto num = -4.0*POW3(xi_x - 1.0)*(POW2(xi_x) - 5.0*xi_x - 2.0);
auto den = POW2(POW4(xi_x) - 4.0*POW3(xi_x) + 4.0*POW2(xi_x) + 4.0*xi_x + 1.0);
return forceeval(num/den*xi_x);
}
template<typename RhoType, typename XiType>
auto a_HS(const RhoType& rhos, const Eigen::Array<XiType, 4, 1>& xi) const{
constexpr double MY_PI = static_cast<double>(EIGEN_PI);
return forceeval(6.0/(MY_PI*rhos)*(3.0*xi[1]*xi[2]/(1.0-xi[3]) + POW3(xi[2])/(xi[3]*POW2(1.0-xi[3])) + (POW3(xi[2])/POW2(xi[3])-xi[0])*log(1.0-xi[3])));
}
/**
\note Eq. A12 from Lafitte
Defining:
\f[
\hat B_{ij} \equiv \frac{B_{ij}}{2\pi\epsilon_{ij}d^3_{ij}\rho_s} = \frac{1-\xi_x/2}{(1-\xi_x)^3}I-\frac{9\xi_x(1+\xi_x)}{2(1-\xi_x)^3}J
\f]
*/
template<typename XiType, typename IJ>
auto get_Bhatij(const XiType& xi_x, const XiType& one_minus_xi_x3, const IJ& I, const IJ& J) const{
return forceeval(
(1.0-xi_x/2.0)/one_minus_xi_x3*I - 9.0*xi_x*(1.0+xi_x)/(2.0*one_minus_xi_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 + \xi_x \frac{\partial \hat B}{\partial \xi_x}\right)
\f]
and thus
\f[
\rho_s \left(\frac{\partial B_{ij}}{\partial \rho_s}\right)_{T,\vec{z}} = \hat B + \xi_x \frac{\partial \hat B}{\partial \xi_x}
\f]
*/
template<typename XiType, typename IJ>
auto get_rhodBijdrho(const XiType& xi_x, const XiType& one_minus_xi_x3, const IJ& I, const IJ& J, const XiType& Bhatij) const{
auto dBhatdxix = (-3.0*I*(xi_x - 2.0) - 27.0*J*xi_x*(xi_x + 1.0) + (xi_x - 1.0)*(I + 9.0*J*xi_x + 9.0*J*(xi_x + 1.0)))/(2.0*POW4(1.0-xi_x));
return forceeval(Bhatij + dBhatdxix*xi_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 XiType>
auto get_a1Shatij(const XiType& xi_x_eff, double lambda_ij) const{
return forceeval(
-1.0/(lambda_ij-3.0)*(1.0-xi_x_eff/2.0)/POW3(forceeval(1.0-xi_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 \xi_{x,eff}}\frac{\partial \xi_{x,eff}}{\partial \xi_x}\frac{\partial \xi_x}{\partial \rho_s} \right)
\f]
since \f$\rho_s\frac{\partial \xi_x}{\partial \rho_s} = \xi_x\f$
*/
template<typename XiType>
auto get_rhoda1Shatijdrho(const XiType& xi_x, const XiType& xi_x_eff, const XiType& dxixeffdxix, double lambda_ij) const{
auto xixda1Shatdxix = ((2.0*xi_x_eff - 5.0)*dxixeffdxix)/(2.0*(lambda_ij-3)*POW4(xi_x_eff-1.0))*xi_x;
return forceeval(get_a1Shatij(xi_x_eff, lambda_ij) + xixda1Shatdxix);
}
};
/**
\brief A class used to evaluate mixtures using the SAFT-VR-Mie model
*/
class SAFTVRMieMixture {
private:
std::vector<std::string> names;
const SAFTVRMieChainContributionTerms terms;
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");
}
};
auto get_coeffs_from_names(const std::vector<std::string> &names){
SAFTVRMieLibrary library;
return library.get_coeffs(names);
}
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{
return SAFTVRMieChainContributionTerms(m, epsilon_over_k, sigma_m, lambda_r, lambda_a, std::move(Eigen::ArrayXXd::Zero(N,N)));
}
}
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)) {};
// PCSAFTMixture( const PCSAFTMixture& ) = delete; // non construction-copyable
SAFTVRMieMixture& operator=( const SAFTVRMieMixture& ) = delete; // non copyable
const auto& get_terms() const { return terms; }
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);
auto alphar = vals.alphar_mono + vals.alphar_chain;
return forceeval(alphar);
}
};
} /* namespace SAFTVRMie */
}; // namespace teqp