7 citations · 7 across the 1 of their papers we have counts for
4 papers
Self-Adaptive Model-Order Reduction for Shock-Dominated Problems
Ali Mohaghegh, Cheng Huang
Projection-based model-order reduction (MOR) offers a promising approach for accelerating expensive full-order model (FOM) by constructing reduced-order models (ROMs) that retain t…
CompFlowLab: A Python code to develop and prototype new data-driven models for challenging compressible flow problems with shocks and chemical reactions
Ali Mohaghegh, Cheng Huang
CompFlowLab is an open-source Python environment that is capable of modeling different classes of compressible flow problems (including shocks, flames, and detonation waves) using…
History-aware adaptive reduced-order models via incremental singular value decomposition
Amirpasha Hedayat, Ali Mohaghegh, Laura Balzano +2
Reduced-order models (ROMs) can accelerate high-dimensional dynamical simulations, but their accuracy often deteriorates when online dynamics leave the regime represented by offlin…
Feature-Guided Sampling Strategy for Adaptive Model Order Reduction of Convection-Dominated Problems
Ali Mohaghegh, Cheng Huang
Though high-performance computing enables high-fidelity simulations of complex engineering systems, accurately resolving multi-scale physics for real-world problems remains computa…