Black Forest Labs' new Self-Flow technique makes training multimodal AI models 2.8x more efficient

This efficiency makes it viable for enterprises to move beyond generic off-the-shelf solutions and develop specialized models ...
IEEE

Knowledge-Based Convolutional Neural Network for the Simulation and Prediction of Two-Phase Darcy Flows

Abstract: Physics-informed neural networks (PINNs) have gained significant prominence as a powerful tool in the field of scientific computing and simulations. Their ability to seamlessly integrate ...
IEEE

Quasi-Convex NoC Optimization in the Active Multiphase Probabilistic Power Flow

Abstract: This article proposes a new method to optimize the number of clusters (NoC) in the active distance-based clustering multiphase probabilistic power flow (MPPF). The objective is to determine ...
Oak Ridge National Lab

Frontier simulations test turbulence theories at record 35 trillion grid points

The scale of the simulations on Frontier has reached such a point that we are within reach of experiments as far as the range of scales that can be simulated numerically or can be made to happen in ...
GitHub

An extensible framework for multiphase flows with complex rheology, built on Basilisk C

MultiRheoFlow is an open-source multiphase, multirheology extension of the ElastoFlow solver. It provides a catalogue of models implemented in Basilisk C, leveraging adaptive mesh refinement for ...
早稲田大学

Workshop Report: “International Workshop on Multiphase Flows: Analysis, Modelling and Numerics 2025”

The International Workshop on Multiphase Flows: Analysis, Modelling and Numerics 2025, organized by the Mathematics and Physics Unit “Multiscale Analysis, Modelling and Simulation” of Waseda ...
C&EN

Application of Smoothed Particle Hydrodynamics for Modeling of Multiphase Fluid Flow in Non-Uniform Porous Media

Department of Petroleum Engineering, School of Chemical and Petroleum Engineering, Shiraz University, Shiraz 7193616511, Iran ...