Muhammad Akbar Khan

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles

Physics-informed neural networks applied to the level-set formulation of interface advection commonly augment the residual and initial-condition losses with an eikonal regulariser, penalising the deviation of ‖∇φ‖ from unity. A previous two-dimensional study identified this weigh...

A Fourier Neural Operator for Coupled Hygrothermal Ranking of Low-Cost Wall Materials under Measured Climate Forcing

Selecting low-cost indigenous wall materials that limit heat penetration is critical for indoor thermal comfort in hot-dry rural regions, where summer temperatures routinely exceed 45 °C. The thermal performance of the porous earthen materials used in such construction is insepar...

Eikonal Regularisation in Physics-Informed Neural Networks for Three-Dimensional Level-Set Advection: Transferability of Two-Dimensional Design Principles

Physics-informed neural networks applied to the level-set formulation of interface advection commonly augment the residual and initial-condition losses with an eikonal regulariser, penalising the deviation of ‖∇φ‖ from unity. A previous two-dimensional study identified this weigh...

A Fourier Neural Operator for Coupled Hygrothermal Ranking of Low-Cost Wall Materials under Measured Climate Forcing

Selecting low-cost indigenous wall materials that limit heat penetration is critical for indoor thermal comfort in hot-dry rural regions, where summer temperatures routinely exceed 45 °C. The thermal performance of the porous earthen materials used in such construction is insepar...