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Found 5 papers, 1 papers with code
Elicitron: An LLM Agent-Based Simulation Framework for Design Requirements Elicitation
Second, we show how our framework effectively mimics empathic lead user interviews, identifying a greater number of latent needs than conventional human interviews.
Reduced-order modeling of unsteady fluid flow using neural network ensembles
When applied to two unsteady fluid dynamics problems, our results show that the presented framework effectively reduces error propagation and leads to more accurate time-series prediction of latent variables at unseen points.
XLB: A differentiable massively parallel lattice Boltzmann library in Python
The lattice Boltzmann method (LBM) has emerged as a prominent technique for solving fluid dynamics problems due to its algorithmic potential for computational scalability.
A Deep Learning Algorithm for Piecewise Linear Interface Construction (PLIC)
Given the volume fraction and interface normal, the location of a linear interface is uniquely defined.
NPLIC: A Machine Learning Approach to Piecewise Linear Interface Construction
Volume of fluid (VOF) methods are extensively used to track fluid interfaces in numerical simulations, and many VOF algorithms require that the interface be reconstructed geometrically.
