Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Malé, Quentin, Lapeyre, Corentin J, Noiray, Nicolas |
|---|---|
| Format: | Preprint |
| Publié: |
2024
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Domain decomposition of large neural network surrogate models
par: Gödde, Timm, et autres
Publié: (2026)
par: Gödde, Timm, et autres
Publié: (2026)
Automated machine learning for physics-informed convolutional neural networks
par: Zhou, Wanyun, et autres
Publié: (2024)
par: Zhou, Wanyun, et autres
Publié: (2024)
Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls
par: Chen, Jungang, et autres
Publié: (2023)
par: Chen, Jungang, et autres
Publié: (2023)
PyTOaCNN: Topology optimization using an adaptive convolutional neural network in Python
par: Chadha, Khaish Singh, et autres
Publié: (2024)
par: Chadha, Khaish Singh, et autres
Publié: (2024)
Multiscale graph neural networks with adaptive mesh refinement for accelerating mesh-based simulations
par: Perera, Roberto, et autres
Publié: (2024)
par: Perera, Roberto, et autres
Publié: (2024)
Deep encoder-decoder hierarchical convolutional neural networks for conjugate heat transfer surrogate modeling
par: Ebbs-Picken, Takiah, et autres
Publié: (2023)
par: Ebbs-Picken, Takiah, et autres
Publié: (2023)
Convolutional neural network based reduced order modeling for multiscale problems
par: Zhang, Xuhan, et autres
Publié: (2024)
par: Zhang, Xuhan, et autres
Publié: (2024)
Tensor-decomposition-based A Priori Surrogate (TAPS) modeling for ultra large-scale simulations
par: Guo, Jiachen, et autres
Publié: (2025)
par: Guo, Jiachen, et autres
Publié: (2025)
I-FENN for thermoelasticity based on physics-informed temporal convolutional network (PI-TCN)
par: Abueidda, Diab W., et autres
Publié: (2023)
par: Abueidda, Diab W., et autres
Publié: (2023)
Crack detection by holomorphic neural networks and transfer-learning-enhanced genetic optimization
par: Hund, Jonas, et autres
Publié: (2025)
par: Hund, Jonas, et autres
Publié: (2025)
On instabilities in neural network-based physics simulators
par: Floryan, Daniel
Publié: (2024)
par: Floryan, Daniel
Publié: (2024)
Multiscale topology optimization of functionally graded lattice structures based on physics-augmented neural network material models
par: Stollberg, Jonathan, et autres
Publié: (2024)
par: Stollberg, Jonathan, et autres
Publié: (2024)
Perturbative Analytical Framework for Thermal Wave Diffusion in Non-linear Building Envelopes
par: Guigot, Corentin
Publié: (2026)
par: Guigot, Corentin
Publié: (2026)
Data-driven methods for computational mechanics: A fair comparison between neural networks based and model-free approaches
par: Zlatić, Martin, et autres
Publié: (2024)
par: Zlatić, Martin, et autres
Publié: (2024)
Physics-augmented neural networks for constitutive modeling of hyperelastic geometrically exact beams
par: Schommartz, Jasper O., et autres
Publié: (2024)
par: Schommartz, Jasper O., et autres
Publié: (2024)
Nonlinear electro-elastic finite element analysis with neural network constitutive models
par: Klein, Dominik K., et autres
Publié: (2024)
par: Klein, Dominik K., et autres
Publié: (2024)
A dual-stage constitutive modeling framework based on finite strain data-driven identification and physics-augmented neural networks
par: Linden, Lennart, et autres
Publié: (2025)
par: Linden, Lennart, et autres
Publié: (2025)
Test-time data augmentation: improving predictions of recurrent neural network models of composites
par: Uvdal, Petter, et autres
Publié: (2024)
par: Uvdal, Petter, et autres
Publié: (2024)
Fitting micro-kinetic models to transient kinetics of temporal analysis of product reactors using kinetics-informed neural networks
par: Nai, Dingqi, et autres
Publié: (2024)
par: Nai, Dingqi, et autres
Publié: (2024)
Graph convolutional network as a fast statistical emulator for numerical ice sheet modeling
par: Rahnemoonfar, Maryam, et autres
Publié: (2024)
par: Rahnemoonfar, Maryam, et autres
Publié: (2024)
Parameter conditioned interpretable U-Net surrogate model for data-driven predictions of convection-diffusion-reaction processes
par: Kastor, Michael Urs Lars, et autres
Publié: (2026)
par: Kastor, Michael Urs Lars, et autres
Publié: (2026)
Gaussian process regression + deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids
par: Deshpande, Saurabh, et autres
Publié: (2024)
par: Deshpande, Saurabh, et autres
Publié: (2024)
Energy-based physics-informed neural network for frictionless contact problems under large deformation
par: Bai, Jinshuai, et autres
Publié: (2024)
par: Bai, Jinshuai, et autres
Publié: (2024)
A novel Taguchi-based approach for optimizing neural network architectures: application to elastic short fiber composites
par: Nikzad, Mohammad Hossein, et autres
Publié: (2024)
par: Nikzad, Mohammad Hossein, et autres
Publié: (2024)
Cross-attention-based bipartite graph neural network for coupled nodal and elemental field prediction in large-deformation sheet material forming
par: Zhao, Yingxue, et autres
Publié: (2026)
par: Zhao, Yingxue, et autres
Publié: (2026)
Inverse design of anisotropic microstructures using physics-augmented neural networks
par: Jadoon, Asghar A., et autres
Publié: (2024)
par: Jadoon, Asghar A., et autres
Publié: (2024)
Real-time design of architectural structures with differentiable mechanics and neural networks
par: Pastrana, Rafael, et autres
Publié: (2024)
par: Pastrana, Rafael, et autres
Publié: (2024)
PINN-MG: A physics-informed neural network for mesh generation
par: Wang, Min, et autres
Publié: (2025)
par: Wang, Min, et autres
Publié: (2025)
A hybrid global local computational framework for ship hull structural analysis using homogenized model and graph neural network
par: Cai, Yuecheng, et autres
Publié: (2025)
par: Cai, Yuecheng, et autres
Publié: (2025)
Physics-informed neural networks with curriculum training for poroelastic flow and deformation processes
par: Bekele, Yared W.
Publié: (2024)
par: Bekele, Yared W.
Publié: (2024)
Surface profile recovery from electromagnetic field with physics--informed neural networks
par: Chen, Yuxuan, et autres
Publié: (2024)
par: Chen, Yuxuan, et autres
Publié: (2024)
A physics-augmented neural network framework for finite strain incompressible viscoelasticity
par: Kalina, Karl A., et autres
Publié: (2025)
par: Kalina, Karl A., et autres
Publié: (2025)
A remedy to mitigate tensile instability in SPH for simulating large deformation and failure of geomaterials
par: Jana, Tapan, et autres
Publié: (2024)
par: Jana, Tapan, et autres
Publié: (2024)
A surrogate model for computational homogenization of elastostatics at finite strain using the HDMR-based neural network approximator
par: Nguyen-Thanh, Vien Minh, et autres
Publié: (2019)
par: Nguyen-Thanh, Vien Minh, et autres
Publié: (2019)
GrainGNN: A dynamic graph neural network for predicting 3D grain microstructure
par: Qin, Yigong, et autres
Publié: (2024)
par: Qin, Yigong, et autres
Publié: (2024)
VW-PINNs: A volume weighting method for PDE residuals in physics-informed neural networks
par: Song, Jiahao, et autres
Publié: (2024)
par: Song, Jiahao, et autres
Publié: (2024)
An energy-based material model for the simulation of shape memory alloys under complex boundary value problems
par: Erdogan, C., et autres
Publié: (2024)
par: Erdogan, C., et autres
Publié: (2024)
On the feasibility of foundational models for the simulation of physical phenomena
par: Tierz, Alicia, et autres
Publié: (2024)
par: Tierz, Alicia, et autres
Publié: (2024)
Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables
par: Rosenkranz, Max, et autres
Publié: (2024)
par: Rosenkranz, Max, et autres
Publié: (2024)
A physics-enhanced multi-modal fused neural network for predicting contamination length interval in pipeline
par: Du, Jian, et autres
Publié: (2024)
par: Du, Jian, et autres
Publié: (2024)
Documents similaires
-
Domain decomposition of large neural network surrogate models
par: Gödde, Timm, et autres
Publié: (2026) -
Automated machine learning for physics-informed convolutional neural networks
par: Zhou, Wanyun, et autres
Publié: (2024) -
Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls
par: Chen, Jungang, et autres
Publié: (2023) -
PyTOaCNN: Topology optimization using an adaptive convolutional neural network in Python
par: Chadha, Khaish Singh, et autres
Publié: (2024) -
Multiscale graph neural networks with adaptive mesh refinement for accelerating mesh-based simulations
par: Perera, Roberto, et autres
Publié: (2024)