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Found 8 papers, 0 papers with code
Virtual Foundry Graphnet for Metal Sintering Deformation Prediction
Metal Sintering is a necessary step for Metal Injection Molded parts and binder jet such as HP's metal 3D printer.
Robust Topology Optimization Using Variational Autoencoders
Robust topology optimization (RTO) also incorporates the effect of input uncertainties and produces a design with the best average performance of the structure while reducing the response sensitivity to input uncertainties.
Efficient training of physics-informed neural networks via importance sampling
This importance sampling approach is straightforward and easy to implement in the existing PINN codes, and also does not introduce any new hyperparameter to calibrate.
NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework
We present real-world use cases that range from challenging forward multi-physics simulations with turbulence and complex 3D geometries, to industrial design optimization and inverse problems that are not addressed efficiently by the traditional solvers.
Adaptive Physics-Informed Neural Networks for Markov-Chain Monte Carlo
In this paper, we propose the Adaptive Physics-Informed Neural Networks (APINNs) for accurate and efficient simulation-free Bayesian parameter estimation via Markov-Chain Monte Carlo (MCMC).
Physics-Driven Regularization of Deep Neural Networks for Enhanced Engineering Design and Analysis
In this paper, we introduce a physics-driven regularization method for training of deep neural networks (DNNs) for use in engineering design and analysis problems.
A Deep Neural Network Surrogate for High-Dimensional Random Partial Differential Equations
Developing efficient numerical algorithms for the solution of high dimensional random Partial Differential Equations (PDEs) has been a challenging task due to the well-known curse of dimensionality.
Deep Learning for Accelerated Reliability Analysis of Infrastructure Networks
This paper presents a deep learning framework for accelerating infrastructure system reliability analysis.
