Paper
25 October 2002 Virtual prototyping with Data Modeling
Holger M. Jaenisch, James W. Handley, Kent H. White, James W. Watson Jr., Carl T. Case, Claude G. Songy
Author Affiliations +
Abstract
We present an approach to convert slow running, high fidelity simulations into fast running models via analogy. These high order polynomial models use Data Modeling coupled with multivariate regression. Shown are models for individual data sets, field measured data, simulations like the Navy Experimental Dive Unit rebreather model, simulation driver equations for the Kinetic Impact Debris Distribution model, and a model of a terahertz sensor sensing Bt simulant built from a hardcopy only. These equation-based models are easily embedded into larger system simulations as active model components for enabling system performance and trade analysis. Models are fast running, and in the case of simulation and driver equation modeling, provide results that are significantly shorter in lines of software code.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Holger M. Jaenisch, James W. Handley, Kent H. White, James W. Watson Jr., Carl T. Case, and Claude G. Songy "Virtual prototyping with Data Modeling", Proc. SPIE 4772, Electro-Optical System Design, Simulation, Testing, and Training, (25 October 2002); https://doi.org/10.1117/12.451755
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Data modeling

Sensors

Computer simulations

Fractal analysis

Prototyping

Reverse modeling

Electromagnetic simulation

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