Tag: Surrogate Model

Quantum/Chemistry

Proposes using ordinary multilayer perceptrons with finite-group averaging to achieve exact equivariant surrogate models for correlated electron systems, enabling efficient force and transition energy evaluations.

Structural

KATOsuper presents an objective-agnostic framework that couples neural-reparameterized topology optimization with sensitivity-consistent Fourier neural operators, addressing gradient inconsistency between predicted objectives and sensitivities for stable structural optimization.

ScientificML

This paper investigates using artificial neural networks as surrogate models for black-box optimization, enabling efficient optimization when analytical function descriptions are unavailable by obtaining objective values through numerical simulation.

Structural

DeepFEAv2 applies deep learning surrogate models to transient finite element analysis on unstructured meshes, enabling joint prediction of node-based and element-based outputs to reduce computational cost in structural mechanics.

Thermal Management

This research applies Bayesian optimization and surrogate modeling to investigate urban canopy parameter ranges for heat mitigation, analyzing trade-offs among daytime air temperature, nighttime air temperature, and Universal Thermal Climate Index (UTCI) in urban environments.

ScientificML

Proposes the Fractional Fourier Neural Operator (FrFNO) that embeds the analytic Mittag-Leffler propagator to address the computational challenge of memory-dependent time derivatives and nonlocal fractional Laplacians in fractional PDEs, enabling efficient surrogate modeling.

Thermal Management / Physics-Informed ML

A physics-informed convolutional neural network whose loss encodes the finite-difference heat conduction equation, used as a surrogate for the temperature field of a liquid-cooled battery pack and more accurate than a purely data-driven model trained on the same data.

ScientificML

A 36M-parameter UNet-based PDE solver v2 by Los Alamos National Laboratory, designed for surrogate modeling of partial differential equations in scientific computing.

Geophysics

A continually learning neural-operator surrogate model replaces the traditional forward solver for efficient Bayesian inversion of three-dimensional time-domain airborne electromagnetic data, addressing prohibitive computational costs.

CFD Surrogate

A HuggingFace-hosted dataset repository for computational fluid dynamics surrogate modeling, containing data resources for CFD simulation and surrogate model development.

Computational Fluid Dynamics

A computational fluid dynamics surrogate model training dataset hosted on HuggingFace by user harryshah14.

Electromagnetics

Proposes a KAN-based single-parameterized surrogate model to accelerate drift kinetic equation solving for fast neoclassical toroidal viscosity torque calculation in tokamak plasma modeling.

ScientificML

Proposes Adaptive Operator Transformation (AOT) to address structural diversity challenges in multi-PDE pre-training by adapting target solution operators rather than increasing model capacity, improving neural operator generalization across equations.

ScientificML

The Fractional Fourier Neural Operator (FrFNO) integrates the analytic Mittag-Leffler propagator into a Fourier-based neural operator to provide a resolution-robust surrogate for space-time fractional PDEs with memory-dependent derivatives.

Electromagnetics

A novel computationally efficient surrogate model for linear mode coupling in graded-index multimode fibers, tunable via a single measurable parameter, benchmarked numerically and experimentally on a 90-polarization-mode fiber.