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This blog discusses how machine learning accelerates tasks like modeling and optimization, showcasing real-world applications such as battery testing. Learn how these innovative updates are transforming workflows, increasing accuracy, and driving efficiencies in industrial optimization, paving the way for future advancements in engineering practices.
Explore how combining AI with Model-Based Design (MBD) in MATLAB & Simulink enhances system accuracy, optimizes control strategies, and accelerates innovation in engineering.
Explore how MATLAB and Simulink enable electrical engineers to design, simulate, and optimize advanced systems efficiently, ensuring reliability and innovation.
COMSOL Multiphysics® version 6.3 is here. It delivers a suite of powerful new features that revolutionize the way engineers and scientists tackle complex simulations. From the groundbreaking Electric Discharge Module to GPU-accelerated simulations, this latest release empowers users to explore new frontiers in physics modeling.
Explore how MATLAB and Simulink empower energy engineers to design, optimize, and simulate renewable energy systems, power grids, and storage solutions.
The product development landscape has undergone a significant shift, driven by new technologies, advanced materials, and complex manufacturing methods. These changes have created unprecedented demands on engineering teams. As a response, simulation has become an indispensable tool for successfully navigating through such challenges.
Explore the transformative impact of COMSOL Multiphysics across various industries, from Samsung’s audio optimization to Volkswagen’s electric vehicle advancements. Through real-world examples, learn how engineers streamline processes, reduce costs, and accelerate timelines while ensuring product quality and reliability.
Mebius has partnered with SciEngineer to optimize the design of bipolar plates using COMSOL Multiphysics software. COMSOL Multiphysics enabled the team to calculate electrochemical, thermal, and fluid dynamics simultaneously and allowed for iterative design refinement.
This step-by-step guide explores how to leverage MATLAB and deep learning to detect audible faults in machinery.
Optimize the fault detection process with deep learning in MATLAB. Explore CNNs, RNNs, and advanced tips for precision and reliability.