benchmarkfcns.multifidelity.wingweight

benchmarkfcns.multifidelity.wingweight(arg0: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous']) → Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]']

Computes the value of the multi-fidelity Wing Weight function. SCORES = wingweight(X) computes the value of the Wing Weight function at point X. multifidelity.wingweight accepts a matrix of size M-by-10 and returns a matrix SCORES of size M-by-2.

Mathematical Definition

\[\begin{aligned}\]

f_{hf}(mathbf{x}) &= 0.036 S_w^{0.758} W_{fw}^{0.0035} left(frac{A}{cos^2(Lambda)}right)^{0.6} q^{0.006} lambda^{0.04} left(frac{100 t_c}{cos(Lambda)}right)^{-0.3} (N_z W_{dg})^{0.49} + S_w W_p \ f_{lf}(mathbf{x}) &= 0.9 f_{hf}(mathbf{x}) + 10.0 end{aligned}

Visualization

No visualization available for this function.