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Home : Company : Maplesoft Webinars : Web Seminar Categories : Online Webinar : Physical Modeling: Next Generation Modeling and Simulation

Physical Modeling: Next Generation Modeling and Simulation

SAE International
November 18, 2008: 11:30 AM - 12:30 PM (UTC-05:00) Eastern Time (US & Canada) Related Products

Webinar hosted by SAE International

Physical modeling refers to modeling techniques that better represent the physics and the mathematics of a system. The concept is simple: develop virtual models of things before committing them to metal or plastic. This way, if there are any conceptual flaws, they reveal themselves in a virtual environment where they are much easier to fix. In this presentation, Dr. Laurent Bernardin, Chief Scientist and Vice-President of Research and Development at Maplesoft, will discuss the future of modeling and simulation, and how, as the complexity of design tasks increase each year, new techniques are necessary for capturing the complex details of next-generation systems.

Toyota has been at the forefront of implementing physical modeling techniques. Dr. Ken Butts, Executive Engineer at the Toyota Technical Center, will present the High Level Modeling paradigm by example. The High Level Modeling paradigm is a systematic physical modeling procedure that enforces conservation principles. The paradigm is realized by the High Level Modeling Tool, which is currently in development at Maplesoft. Here he’ll consider a conceptual Variable Valve Timing actuator with conservation of mass, energy, momentum, and mechanical enthalpy. Dr. Butts will also discuss the Plant Modeling Consortium. Founded by Toyota and Maplesoft, the Plant Modeling Consortium (PMC) promotes the development of new design techniques for the automotive and related industries.

Dr. Chad Schmitke, Chief Developer at MotionPro, will present examples of physical modeling taken from real-world applications, using MapleSim, Maplesoft’s new modeling and simulation software tool. Dr. Schmitke will show how advanced engineering systems can be more efficiently designed, modeled and simulated, improving their overall quality and reliability.

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