surrogate-model

A curated list of 100+ AI-ready tools for Computer-Aided Engineering, ranked by an AI-Readiness Score (agent-callability: MCP, Python API, CLI, pip). CFD, FEA, SPH, DEM, differentiable simulation, neural operators, PINNs, MCP servers.

[ESWA] NeuroXAI: Adaptive, Robust, Explainable Surrogate Framework for Determination of Channel Importance in EEG Application

A Keysight ADS/RFPro-based workflow for RFIC pixel-layout generation, EM simulation automation, HDF5 dataset creation, and CNN-based surrogate modeling.

An extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.

WinDiNet: Pretrained Video Models as Differentiable Physics Simulators for Urban Wind Flows

Signal Filtering and Generation of Synthetic Time-Series.

Claude Code agent skills bridging Abaqus FEA and ML surrogates: LHS batch dataset generation + ODB to ML-ready grid CSVs.

A core library for engineering surrogate modeling and operator learning

Source code for Surrogate Modeling of Melt Pool Temperature Field using Deep Learning

NVIDIA PhysicsNeMo 中文教程书 · 8 章 + 4 附录 · PINN 与神经算子三种实现（裸 PyTorch / SDK / GPU production）

Fast, memory-efficient exact Gaussian processes in C++ and Python

Curiosity → Perseverance rover wheel skin: Ansys FEA, analytical failure analysis, and a PCA–Gaussian-process surrogate model with a MATLAB GUI for instant stress/strain prediction.

Python package for Surrogate-Assisted Evolutionary Algorithms (SAEAs).

An interactive Python dashboard for planning space missions. It features orbital maneuver calculations, animated 2D flight paths, and an AI model for predicting fuel needs, all wrapped in a clean, user-friendly interface.

A workshop covering the calibration of agent-based models.

Autonomous engineering design agent: reason, design, GPU physics, optimize, learn. Evidence-graded engineering brain with external solver cross-validation. All results simulated, not physically validated.

Training code for CBAM-based PHVI classification and pitting-damage morphology regression associated with IJMS 2026.

Tesseract Hackathon Submission - Track 04.

Deep-RL control of liquid rocket engines, built on DLR's LUMEN Control Challenge: literature review, domain primer, a labelled LUMEN-like surrogate with PI, PPO and SAC baselines, and an in-browser Engine Lab with an animated test stand

Surrogate-assisted optimisation agent for CST Studio Suite: trains a surrogate on your saved full-wave runs, optimises on it with SB-SADEA, and spends each simulation on a frozen, audited prediction. Works on any parametric frequency-domain model whose goals come from 1D results.