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SimScale Partners with AI Engineering GmbH to Unlock Ultra-Fast, Meshless SPH Simulation in the Cloud, Powered by NVIDIA AI Infrastructure
Globenewswire· 2026-03-16 20:30
Core Insights - SimScale has announced a strategic collaboration with AI Engineering GmbH to integrate the PAMICS® solver into its cloud engineering simulation platform, enhancing simulation speeds by 10-20 times for complex industrial applications [2][4]. Company Overview - SimScale is recognized as the world's first AI-native cloud platform for engineering simulation, serving over 800,000 users globally and enabling rapid exploration of design decisions [10]. - AI Engineering GmbH specializes in advanced simulation solutions, particularly in Smoothed Particle Hydrodynamics (SPH) and AI-enhanced engineering tools [11]. Technological Advancements - The integration of AI Engineering's PAMICS solver with SimScale's infrastructure aims to democratize access to high-fidelity, meshless Computational Fluid Dynamics (CFD) [3]. - The PAMICS solver utilizes a Lagrangian SPH approach, allowing for direct simulation of fluid dynamics from raw CAD geometries, thus eliminating the need for meshing [6]. - This collaboration supports advanced visualization workflows compatible with NVIDIA Omniverse libraries, facilitating photorealistic rendering and immersive review of simulation results [5]. Industry Applications - The PAMICS solver is designed to handle complex fluid dynamics scenarios, including multiphase flows, fluid-structure interactions, and arbitrary motion, which are challenging for traditional methods [6][9]. - Key use cases include accurately predicting oil lubrication in gearboxes, modeling multiphase flows in industrial mixers, and simulating vehicle wading and contamination management [9]. Strategic Goals - The partnership aims to empower engineers to explore thousands of engineering decisions rapidly, thereby accelerating the development of predictive Digital Twins [7]. - By leveraging NVIDIA's accelerated computing infrastructure, the integration is expected to enhance the performance of simulation workflows significantly [4][7].