Ansys Motor-CAD
Ansys Motor-CAD is a dedicated electric machine design tool for fast multiphysics simulation across the full torque-speed operating range. Motor-CAD enables design engineers to evaluate motor topologies and concepts across the full operating range, to produce designs that are optimized for performance, efficiency and size. Motor-CAD software’s four integrated modules—EMag, Therm, Lab, Mech—enable multiphysics calculations to be performed quickly and iteratively, so users can get from concept to final design in less time. Fast calculations and streamlined data input processes leave time for Motor-CAD users to explore more motor topologies and fully assess the impact of advanced loss effects in the initial stages of an electromechanical design. The release includes powerful new features for design optimization, multi-physics analysis and system modelling for electric motors. Fast multiphysics simulation across a full torque-speed operating range.
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SOLIDWORKS Simulation
Subject your designs to real world conditions to raise product quality while reducing prototyping and physical testing costs. SOLIDWORKS® Simulation is an easy-to-use portfolio of structural analysis tools that use Finite Element Analysis (FEA) to predict a product’s real-world physical behavior by virtually testing CAD models. The portfolio provides linear, non-linear static and dynamic analysis capabilities. SOLIDWORKS Simulation Professional enables you to optimize your design, determine product mechanical resistance, product durability, topology, natural frequencies, and test heat transfer and buckling instabilities. It can also perform sequential multi-physics simulations. SOLIDWORKS Simulation Premium lets you efficiently evaluate your designs for nonlinear and dynamic response, dynamic loading, and composite materials. SOLIDWORKS Simulation Premium includes three advanced studies: Non-Linear Static, Non-Linear Dynamic, and Linear Dynamics.
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DC-E DigitalClone for Engineering
DigitalClone® for Engineering is the world's only gearbox reliability prediction solution integrating multiple scales of analysis in a single software package. In addition to modeling and analysis capabilities at the gearbox and gear/bearing levels, DC-E is the only solution available that models fatigue life based on detailed, physics-based models of the material microstructure (US Patent 10474772B2).
DC-E enables construction of a gearbox digital twin with high value across all stages of the lifecycle of the physical asset - from design and manufacturing optimization to component supplier selection to failure root cause analysis to condition-based maintenance and to prognostics. This computational environment drives down the time and cost to bring new designs to the market and to sustain them over time.
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NVIDIA PhysicsNeMo
NVIDIA PhysicsNeMo is an open source Python deep-learning framework for building, training, fine-tuning, and inferring physics-AI models that combine physics knowledge with data to accelerate simulations, create high-fidelity surrogate models, and enable near-real-time predictions across domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather and climate, and digital twin applications. It provides scalable, GPU-accelerated tools and Python APIs built on PyTorch and released under the Apache 2.0 license, offering curated model architectures including physics-informed neural networks, neural operators, graph neural networks, and generative AI–based approaches so developers can harness physics-driven causality alongside observed data for engineering-grade modeling. PhysicsNeMo includes end-to-end training pipelines from geometry ingestion to differential equations, reference application recipes to jump-start workflows.
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