To convert the trajectory optimization problem into a parameter optimization problem, a pseudospcetral (PS) method is used, and CFSQP is used as a numerical solver.
The system of ODEs resulting from these sets is then solved using a numerical integration algorithm, in this case the Matlab (The Mathworks) built-in solver ode15s using an implicit integration scheme with numerical differentiation formulas.
The methodology, advantages, and disadvantages of using BEM as a numerical solver were discussed earlier when Poly3D application was introduced.
Additionally, the final reduced model uses a simple numerical solver and runs in less than 1 s without compromising precision for hourly annual simulations being 700 times faster than the detailed model, which is promising for use in urban energy simulation.
A numerical solver for the PDEs was implemented using finite volumes and a weighted essentially non-oscillatory (WENO) scheme.
These differential equations are processed by a numerical solver and a regression algorithm which fits the coefficients of differential equations to experimentally observed time course curves.
We used a numerical cutoff based on the reduced precision of the optimization solver to identify zero and non-zero values.
The coupled equations defined in the model are self-continuously solved using the numerical solver COMSOL [183, 184] Multiphysics.
The advantage of using the numerical solver neBEM in comparison to analytical solutions and other numerical approaches has been discussed in connection to the evaluation of weighting field.
Since the system eigenvalues are widely spread and the problem is of stiff nature, the numerical simulation is conducted using a stiff solver.
