ChemNODE: A neural ordinary differential equations framework for efficient chemical kinetic solvers
Solving for detailed chemical kinetics remains one of the major bottlenecks for
computational fluid dynamics simulations of reacting flows using a finite-rate-chemistry …
computational fluid dynamics simulations of reacting flows using a finite-rate-chemistry …
An adaptive time-integration scheme for stiff chemistry based on computational singular perturbation and artificial neural networks
We leverage the computational singular perturbation (CSP) theory to develop an adaptive
time-integration scheme for stiff chemistry based on a local, projection-based, reduced order …
time-integration scheme for stiff chemistry based on a local, projection-based, reduced order …
Stiffness-reduced neural ODE models for data-driven reduced-order modeling of combustion chemical kinetics
HE Dikeman, H Zhang, S Yang - AIAA SCITECH 2022 Forum, 2022 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2022-0226. vid A novel methodology for
data-driven reduced-order modeling of stiff ODE systems was developed. A combination of a …
data-driven reduced-order modeling of stiff ODE systems was developed. A combination of a …
Feature extraction and artificial neural networks for the on-the-fly classification of high-dimensional thermochemical spaces in adaptive-chemistry simulations
The integration of Artificial Neural Networks (ANNs) and Feature Extraction (FE) in the
context of the Sample-Partitioning Adaptive Reduced Chemistry approach was investigated …
context of the Sample-Partitioning Adaptive Reduced Chemistry approach was investigated …
Chemnode: A neural ordinary differential equations approach for chemical kinetics solvers
Solving for detailed chemical kinetics remains one of the major bottlenecks for
computational fluid dynamics simulations of reacting flows using a finite-rate-chemistry …
computational fluid dynamics simulations of reacting flows using a finite-rate-chemistry …
Predictive simulations of ammonia spray dynamics and multi-regime combustion: fundamental physics and modeling aspects
L Angelilli - 2023 - repository.kaust.edu.sa
Because of its thermochemical qualities, ammonia is an attractive alternative to carbon-
based fuels. Indeed, the lack of carbon atoms in its molecular structure and the ease of …
based fuels. Indeed, the lack of carbon atoms in its molecular structure and the ease of …
[PDF][PDF] Energy and AI
Solving for detailed chemical kinetics remains one of the major bottlenecks for
computational fluid dynamics simulations of reacting flows using a finite-rate-chemistry …
computational fluid dynamics simulations of reacting flows using a finite-rate-chemistry …
[PDF][PDF] FLAMELET MODELING OF SPRAY FLAMES WITH MIXTURE OF EXPERTS-BASED LEARNING OF COMBUSTION MANIFOLDS
This work presents an a posteriori assessment of a novel Mixture of Experts (MoE) approach
for learning tabulated combustion manifolds. The goal is motivated by the poor scaling of …
for learning tabulated combustion manifolds. The goal is motivated by the poor scaling of …
[PDF][PDF] Unsteady Flamelet/Progress Variable Modeling of Spray Flames with Mixture of Experts-Based Representation of Combustion Manifold
This work presents an a posteriori assessment of a novel Mixture of Experts (MoE) approach
for learning tabulated flamelet manifolds. The goal is motivated by the poor scaling of …
for learning tabulated flamelet manifolds. The goal is motivated by the poor scaling of …
[PDF][PDF] A Posteriori Validation of a Data-Driven Mixture of Experts Approach for Tabulation of Combustion Manifolds
This work presents an a posteriori assessment of a novel Mixture of Experts (MoE) approach
for learning tabulated flamelet manifolds. The goal is motivated by the poor scaling of …
for learning tabulated flamelet manifolds. The goal is motivated by the poor scaling of …