computational fluid dynamics
PulseAugur coverage of computational fluid dynamics — every cluster mentioning computational fluid dynamics across labs, papers, and developer communities, ranked by signal.
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New AI model improves CFD simulation accuracy for complex flow structures
Researchers have developed a novel physics-informed Fourier-Wavelet Transformer designed to enhance the accuracy of computational fluid dynamics (CFD) simulations, particularly for localized multiscale structures. This …
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Reinforcement learning accelerates aerodynamic shape optimization
Researchers have developed a novel reinforcement learning (RL) algorithm designed to accelerate aerodynamic shape optimization. This method employs an actor-critic policy evaluation approach, allowing for the temporal f…
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Machine Learning Accurately Identifies Ship Hydrodynamics
A new study published on arXiv explores the application of supervised machine learning, specifically regularized regression techniques like Ridge regression, for identifying ship hydrodynamic coefficients. The research …
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New generative model accelerates fluid dynamics simulations
Researchers have adapted a generative drifting framework for fluid mechanics simulations, aiming to accelerate Computational Fluid Dynamics (CFD) processes. Their new conditional architecture operates within a VAE laten…
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AI generates flow fields for faster 3D underwater navigation
Researchers have developed a novel approach to 3D underwater path planning by using generative flow field surrogates, specifically conditional generative adversarial networks (cGANs). These cGANs, including a PatchGAN a…
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AI slashes GM engineering simulation time from hours to minutes
General Motors is significantly accelerating its engineering and design processes through the integration of AI and machine learning. Previously, complex simulations like computational fluid dynamics (CFD) and finite el…
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Multigrid-hierarchical learning speeds up aircraft flow simulations
Researchers have developed a new multigrid-hierarchical learning framework called MHLF to accelerate computational fluid dynamics (CFD) simulations for large-scale 3D aircraft designs. This method combines a geometric m…
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AI framework enhances SMR simulations for digital twins
Researchers have developed a novel framework combining reduced-order models (ROMs) with neural operators for computational fluid dynamics (CFD) simulations. This approach aims to enable real-time thermal-hydraulic simul…
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Neural operators accelerate Bayesian inverse design in CFD by over 1000x
Researchers have developed a method to significantly speed up Bayesian inverse design for computational fluid dynamics (CFD) by integrating neural operators. This approach allows for the inference of aerodynamic geometr…
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Neural fields predict aircraft ditching loads with high accuracy
Researchers have developed a conditional neural field-based reduced-order model for predicting aircraft ditching loads. This approach, when combined with an LSTM network, achieves high spatio-temporal prediction accurac…
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New framework enhances AI simulations with spatial, temporal awareness
Researchers have developed a new framework to enhance machine learning models used for physics simulations, specifically addressing limitations in current training paradigms. Their approach introduces multi-node predict…
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AI-accelerated CFD simulations adapted for IPU platform show performance gains
Researchers have adapted AI-accelerated computational fluid dynamics (CFD) simulations to run on Graphcore's Intelligence Processing Units (IPUs). The study focused on training machine learning models to predict simulat…
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Motorsport teams leverage AI to accelerate aerodynamic simulations
Artificial intelligence is emerging as a powerful new tool in motorsport, aiming to overcome the limitations and costs associated with traditional computational fluid dynamics (CFD) simulations. While CFD has advanced t…
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Faster by Design: Interactive Aerodynamics via Neural Surrogates Trained on Expert-Validated CFD
Researchers have developed a new graph-based neural operator called the Gauge-Invariant Spectral Transformer (GIST) designed to accelerate aerodynamic simulations for motorsport design. This model is trained on a high-f…
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New benchmark suite evaluates LLMs on complex computational fluid dynamics tasks
Researchers have developed CFDLLMBench, a new benchmark suite designed to evaluate the capabilities of large language models in the field of Computational Fluid Dynamics (CFD). The benchmark consists of three parts: CFD…
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AI research explores functorial formulations, causal learning, and adaptive model merging
Researchers have developed a multi-fidelity surrogate modeling framework to predict wind loads on container ships, combining empirical data with CFD simulations for improved accuracy and reduced computational cost. Anot…