Abstract: Synchronous machines are fundamental components. Accurate modelling of nonlinear magnetic saturation characteristics is essential. Traditional models often rely on computationally intensive ...
Artificial intelligence/Machine Learning-driven modeling reduces time-to-market for faster Design Technology Co-Optimization development and accelerates model parameter extraction for advanced nodes, ...
The semiconductor industry is entering an era of unprecedented complexity, driven by advanced architectures such as Gate-All-Around (GAA) transistors, wide-bandgap materials like GaN and SiC, and ...
The simulation tracks a satellite's surface and internal temperature changes as it orbits Earth, considering varying thermal inputs from sunlight and Earth's shadow. Monte Carlo radiation modeling ...
A rotating cylinder with its side cut away to expose the core, showing patches of purple, blue, green, yellow, and orange that are dense in the middle and more diffuse toward the edges. This rotating ...
The key function of banks in the real world is endogenously creating (inside) money. But they do so facing solvency, liquidity and maturity risks and being subject to regulatory and demand constraints ...
Abstract: The objective of this paper is to develop a physics-informed machine learning methodology for parametric modeling of permanent magnet synchronous machines (PMSMs). A deep neural network is ...
Equipment operators can create and modify simple 3D site models directly from Liebherr cabins using the company’s new Free Modeling assistance system. By integrating a GNSS machine control system with ...
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