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Large language models can reduce the manual effort required to set up finite element simulations, but they introduce reliability risks when generated solver code lies on the critical path. We present a constrained natura...
High-fidelity computational fluid dynamics (CFD) is crucial to vehicle aerodynamic analysis, but its cost still constrains early-stage design exploration. Machine-learning-based surface-field prediction offers a faster a...
{"institution":[{"name":"Research Square"}],"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:02:22Z","timestamp":1781222542397,"version":"3.54.1"},"posted":{"date-parts":[[2026,6,11]]},"group-title":"In R...
Abstract Recent advances in artificial intelligence offer considerable promise for enhancing industrial computational simulation workflows, yet practical adoption is limited by a shortage of high-quality, real-world data...
Abstract This study examines the architectural design of laminated composite beams with surface bonded PZT 5A layers, focusing on the previously overlooked electromechanical role of the non piezoelectric substrate. The r...
Artificial intelligence (AI) has transformed orthodontic diagnosis, yet its application to orthodontic materials science remains critically underexplored. This perspective identifies and characterizes the AI–materials in...
Abstract A species-specific multi-vibrational model for hypersonic non-equilibrium flows is presented in this work, along with a systematic analysis of its impact across multiple cases, ranging from zero-dimensional adia...
This repo contains a simple way to simulate user drawn 2D converging/diverging nozzle shapes by means of CFD (SU2 solver). The goal is to develop a 2D (and later a 3D) CFD dataset for Machine Learning
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Abstract Reliable evaluation of mechanical performance is a central constraint for structural reuse of reclaimed timber. This study provides a controlled comparative assessment of non-destructive indicators for piece-wis...
Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería
This dataset archives all numerical values presented in ASME Turbo Expo paper GT2026-177135 and ASME Journal of Turbomachinery paper TURBO-26-1211. This includes the coordinate sets for the 2D vane and blade profiles use...
Turbulence is ubiquitous in engineering and science, yet direct simulation is prohibitively expensive. The Reynolds-averaged Navier-Stokes (RANS) equations provide savings exceeding ten orders of magnitude but introduce...
High-resolution flow fields are essential for understanding, predicting, and controlling fluid systems, yet they remain difficult to obtain from either experiments or high-fidelity simulations. Deep-learning-based flow-f...
January 8, 2026 - Update: Added "repobundle_A1_Sensor.zip" The original confirmatory analysis (preregistration-Locked) has been packaged (while maintaining all previous versions) for ease of reproducing the confirmatory...
Sample public preview for an ML-ready CFD dataset. Direct source URL is locked for verified subscribers.
Abstract Industrial processes involving packed beds with gaseous flow are often associated with high energy and resource consumption. A detailed understanding of the flow behaviour within such systems is essential for op...
The accurate ability to predict the distribution of contact stress under reinforced concrete (RC) footings is important for the safety and serviceability of shallow foundations. Conventional analytical models idealizing...
Abstract As the demand for edge computing grows, there is a critical need for learning mechanisms that offer both energy efficiency and temporal predictability. In this study, we present a single-board implementation of...
Silicon carbide is a key wide-bandgap semiconductor material for next-generation power electronics, yet the Physical Vapor Transport (PVT) method used for bulk crystal growth remains constrained by complex thermal-chemic...
Underwater images suffer from wavelength dependent attenuation and multiple scattering, which often lead to severe color casts, veiling effects, and reduced contrast. These degradations weaken the stability of key vision...
GitHub Advanced Security Find and fix vulnerabilities Fix vulnerabilities and safeguard your software supply chain with built-in, AI-powered security. GitHub Advanced Security · Built-in protection for every repository ·...
Overview This dataset provides the results of a high-fidelity cosmological simulation exploring the non-linear dynamics of a universe dominated by Primordial Black Holes (PBHs). The simulation was executed on NVIDIA Blac...
The use of deep learning (DL) in disaster research has rapidly emerged as a key approach. In this study, we systematically compiled 247 scientific publications using the terms DL and disaster, published between 2016 and...
This dataset provides computational fluid dynamics (CFD) simulation snapshots of a decaying CO gas plume in a 10 × 10 m² indoor environment. It is used as the physical simulation backend for training and evaluating deep...
In the context of the energy transition, lithium-ion batteries have become indispensable, from consumer electronics to electric vehicles; however, their safe and optimal operation relies on reliable models for state esti...
neurodatax is a modular software toolkit for managing Deep Brain Stimulation (DBS) datasets using a BIDS-style data organisation. It supports structured data ingestion, sidecar metadata generation, downstream processing...
Water scarcity has emerged as a critical global challenge, particularly for countries situated in arid and semi-arid regions. Desalination has become the most promising non-traditional solution for securing a reliable an...
Journal of Advances in Environmental Health Research {"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T23:35:02Z","timestamp":1767915302406,"version":"3.49.0"},"reference-count":0,"publisher":"Maad Rayan Publ...
Complex network analysis and dynamic process simulation (SIR and SEIS model) on the PainterPallet artwork dataset. Final project for the Dynamic Processes in Complex Networks course.
The integration of machine learning (ML) in the design and/or simulation of drug delivery systems is a rapidly growing area within the pharmaceutical sciences. This review paper discusses how supervised learning, reinfor...
The predictive capability crisis in drug discovery and development remains a significant factor hindering medical progress. Among emerging solutions, organoids offer the ability to reflect the biological fidelity of tiss...
A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
Abstract This study presents a surrogate-based computational framework for the thermo-hydraulic optimization of spiral conformal cooling channels (CCCs) used in injection moulding applications. Sixteen design configurati...
Abstract. Inverting point-source emissions from sparse atmospheric observations is difficult because emission rate, release height, wind speed, turbulence, and plume morphology can compensate for one another. We present...
This project implements a parametric analysis of wall thermal conductivity on the operational stability of methanol steam reforming reactors by utilizing a CFD simulation dataset. The study quantifies the transition from...
{"institution":[{"name":"Research Square"}],"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T10:59:26Z","timestamp":1781175566547,"version":"3.54.1"},"posted":{"date-parts":[[2026,6,11]]},"group-title":"In R...
This dataset provides experimental quasi-static axial compression data for 40 FDM-printed sinusoidally-corrugated multi-cell (SCMC) PLA+ energy absorbers generated through Latin Hypercube Sampling (LHS), along with data...
Trajectory similarity join is a fundamental problem in spatiotemporal data management, aimed at identifying pairs of similar trajectories within two trajectory datasets. With the growth of mobile devices, streaming traje...
This project applies machine learning to predict the average Nusselt number using a multi-parameter CFD-inspired dataset. Multiple regression models are trained and compared to capture nonlinear heat transfer behavior, d...
Synthetic CFD dataset for predicting average Nusselt number using machine learning models. Features include Reynolds number, Richardson number, Prandtl number, and nanoparticle volume fraction.
This review investigates how the synergistic integration of porous material science and machine learning can be combined for designing and optimising next-generation UAV propellers. UAV propulsion must be disrupted with...
Folding-wing aircraft enhance flight performance across diverse mission profiles, representing a key development trend for next-generation variable-configuration aircraft. However, current research predominantly focuses...
This is R language project. This is R language project. Contribute to Rifah22/Caesarian-Section-Classification-Dataset development by creating an account on GitHub. GitHub - Rifah22/Caesarian-Section-Classification-Datas...
Rapid progress in aerodynamic shape optimization (ASO) has outpaced currently-available standardized evaluation frameworks. Fair comparison requires a unified benchmark spanning diverse shape classes, objective formulati...
In this paper, the unsupervised learning spectral methods Principal Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA) were explored. PCA captured the maximum variance of MNIST images, including thei...
Abstract Despite widespread research on surrogate modelling in sheet metal forming processes based on finite element simulation data, validating such simulation-based surrogate models against real production data remains...
Structural Health Monitoring 2015
Journal of Advances in Environmental Health Research
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CFD–ANN surrogate model for fixing-angle optimisation of a Darrieus vertical axis wind turbine, including Python notebook, CFD dataset, and Zenodo DOI.
IntelliML is an end-to-end AI-assisted analytics and AutoML platform. It supports dataset upload, cleaning, EDA, feature engineering, training, SHAP-style explanations, what-if simulation, chat/voice assistant workflows,...
Cohesive soil erosion remains a critical yet insufficiently resolved challenge in geotechnical engineering, particularly in the context of climate change and sustainable civil infrastructure. Increasing frequency and int...
Advances in Theoretical & Computational Physics {"indexed":{"date-parts":[[2023,10,31]],"date-time":"2023-10-31T10:05:14Z","timestamp":1698746714062},"reference-count":98,"publisher":"Opast Group LLC","issue":"2","conten...
Curated research tools and datasets for bubble dynamics, boiling, imaging, acoustics, thermal diagnostics, and multiphase simulation.
This dataset includes 5050 finite element models of pile composite foundation (PCF) with varying embankment loads and geological conditions. The above model is based on the Abaqus platform. This dataset can provide data...
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Computational fluid dynamics datasets for ML based surrogate modeling! Computational fluid dynamics datasets for ML based surrogate modeling! - VortexyAether/CFD_Datasets_for_ML GitHub - VortexyAether/CFD_Datasets_for_ML...
A machine learning project for computational fluid dynamics (CFD) using Graph Neural Networks. The system learns to simulate fluid flow around objects by training on OpenFOAM-generated datasets and uses finite volume met...
Burgers' equation dataset. Burgers' equation dataset. Contribute to ajthor/datasets-burgers-fenics development by creating an account on GitHub. GitHub - ajthor/datasets-burgers-fenics: Burgers' equation dataset. · GitHu...
Built a scalable machine learning pipeline using PySpark to predict turbulent kinetic energy from large CFD datasets.
Structural engineers analyze large simulation datasets. Structural engineers analyze large simulation datasets. - arsalan0708/engineering-data-analysis GitHub - arsalan0708/engineering-data-analysis: Structural engineers...
foam-openfoam-agent We’re on a journey to advance and democratize artificial intelligence through open source and open science. arungovindneelan/openfoam-Agent-Dataset · Datasets at Hugging Face Hugging Face Models Datas...
auto-created seed Large-scale Computational Fluid Dynamics (CFD) and Finite-Element Structural Analysis (FEA) datasets to aid the research and development of data-driven and physics-driven Machine Learning methods CAE ML...
C++ data simulation and Multiple Linear Regression (MLR) dataset for predicting heat transfer enhancement in bioconvective nanofluids.
An open, reproducible benchmark for neural‑network surrogates of automotive CFD. Same dataset, same hardware — the model architecture is the only variable. We report the honest speed / accuracy / cost / failure picture,...
A Graph Neural Network (GNN)-based surrogate modeling framework for structural frame analysis using beam elements. The project includes automated dataset generation, finite element analysis (FEA) for structural response...
Extensions for Fluent Assertions for working with DataSet, DataTable and DataRow
Dataset of 1,500 Finite Element (FE) simulations and MATLAB scripts for training Machine Learning (ML) surrogate models to evaluate rail-wheel contact mechanics and wear.
Generates FEA datasets of a 3D rack using PyNite, trains global and local neural surrogate models, and performs mass-minimizing structural design optimization using PyTorch autograd. Enables fast exploration of lightweig...
codes to process OpenFOAM DNS/LES/DES/URANS datasets codes to process OpenFOAM DNS/LES/DES/URANS datasets - justinh2002/Foam_analysis_codes justinh2002/Foam_analysis_codes · GitHub Skip to content Navigation Menu Toggle...
This repo contains the datasets to generate results presented in "On the proper computation of coupled adjoint-based shape sensitivity derivatives for fluid-structure interaction with large displacements"
This repository contains the source code, dataset, and simulation results used in the study: “Shear capacity assessment of perforated steel plate shear wall based on the combination of verified finite element analysis, m...
A pipeline for building large-scale structural simulation datasets from jet engine bracket (JEB) finite element models. Designed to support machine learning models that predict structural performance from geometry.
region:us We’re on a journey to advance and democratize artificial intelligence through open source and open science. orange67/alpaca-fenics-dataset3 · Datasets at Hugging Face Hugging Face Models Datasets Spaces Buckets...
Dataset Card for "CFD_Dataset" More Information needed We’re on a journey to advance and democratize artificial intelligence through open source and open science. rishitunu/CFD_Dataset · Datasets at Hugging Face Hugging...
Contribute to sandialabs/WEC-OpenFOAM-Open-Datasets development by creating an account on GitHub. GitHub - sandialabs/WEC-OpenFOAM-Open-Datasets · GitHub Skip to content Navigation Menu Toggle navigation Sign in Appearan...
Contribute to scalemailted/openfoam-dataset development by creating an account on GitHub. GitHub - scalemailted/openfoam-dataset · GitHub Skip to content Navigation Menu Toggle navigation Sign in Appearance settings Plat...
User-level churn prediction on the Synerise RecSys 2025 dataset with DuckDB feature engineering, XGBoost modeling, rolling backtest, and ROI simulation.
Sim2Learn is a data generation platform based on the Finite Element Method (FEM), designed to provide high-quality simulated data for CNNs. These virtual data are generated computationally, simulating the deformation of...