The release of the pilot version of a revolutionary tool that is expected to set new standards in the modeling and simulation industry has been announced today by the leading provider of high-performance software tools for engineering, science, and mathematics, Maplesoft™. Dramatically reducing the time taken to bring products to market by using physical modeling techniques, MapleSim™ is a high-performance multi-domain modeling and simulation tool.

The MapleSim model maps directly to the physical components of the model, whereas the traditional block diagram is much more complex, harder to produce, and looks nothing like the original system representation.

Physical modeling, or physics-based modeling, is the process of modeling the dynamic behavior of a system mathematically. This task, traditionally, required significant manual effort to derive equations and manipulate them into a form that could be used by signal-flow simulation tools that employ a block-diagram paradigm. The block diagrams are do not resemble the original system representation, being more complex, harder to produce.

Making it easier to build and understand, users, with the cutting-edge physical modeling techniques in MapleSim, can re-create a system diagram on a screen using compact and intuitive components that represent a physical model. MapleSim has more than 500 components from over 10 domains such as electrical, control design, mechanical, and thermal, organized into easy-to-navigate palettes.

Mathematical equations that represent a model, with MapleSim, are automatically generated, saving weeks, sometimes even months, on complex applications. Yielding concise models and high-speed simulations of sophisticated systems, ehe equations are also simplified automatically.

Maple’s symbolic computation technology is at the core of MapleSim. Symbolic technology, unlike purely numeric computation, can convert a physical system representation directly into mathematical equations. Models created in this way are very concise and do not rely on iterative numeric routines to solve. This provides the best simulation performance without generating errors typical of manual derivations.