Useful Links for Bio-Robot Design

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Physics-Based Modeling


Physics-Based Models

Physics-based models are in principle no different from other software. Their parts consist of input, processing, and output, and are all supported by an infrastructure. However, these models do not include hardware-in-the-loop simulations or other real-time modeling. Typically speaking, the models of most interest at the workshops run so slowly compared to real time that the kind of linking often used in real-time applications cannot be made.

The input phase can be characterized as the process of describing the physical traits of the system in terms the software understands. This often laborious task can represent a significant fraction of the human effort in the process. This is particularly true for physics-based models because a computational structure must be constructed in addition to the detailed geometric description; a process that can require extensive user interactions.

Physics-based modeling tools are further distinguished from engineering models or heuristic design tools by the computational resources devoted to processing. Since fundamental conservation equations are solved for the physical state within a computational cell or element, complex global states can be accurately represented by applying a highly resolved computational template. Numerical methods for solving the very large numbers of equations required are the source of continual research and development, which extends from basic software algorithms to specialized hardware designs.

One byproduct of highly resolved physics-based calculations is an extreme amount of output data. The quantities of data which can be produced routinely by physics-based codes would overloaded the mass storage capabilities of just a few computer generations ago. To gain insight from the modeling process, this data must be made accessible by interactive, or at least rapid, interrogation by the user. This is a vital step if the modeling and simulation is used to support T&E. Analytical measures of performance have to be developed which can be related to performance metrics measurable during testing.

The explicit inclusion of well-understood basic physics in the processing algorithms should produce results that are understandable, trustworthy, readily extrapolated to new conditions, and provide the most utility to V/L assessments, particularly in LFT&E. The modeling detail required to realize this expectation is typically only practical in the high performance computing (HPC) or supercomputing environments. Recent advances in HPC horsepower have made computing more affordable and allowed researchers to work problems that were unmanageable in the past.