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International Society of Science and Applied Technologies |
| A Moving Least Squares Methodology for Dynamic Systems with Parameter and Excitation Inputs | ||||
| Author | Gordon J. Savage
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| Co-Author(s) | Young Kap Son
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| Abstract | Meta-models have a valuable place in the efficient design and optimization of many probabilistic engineering systems wherein numerous iterations are required. Meta-models are simple to form, typically much faster and usually as accurate as the original mechanistic model. The Least Squares (LS) approach is one of the oldest means of forming meta-models. Further, a modification of the original model, called the Moving Least-Squares (MLS) method, is a more compact, and usually a more accurate model since it uses only localized data near the query point. Herein we expand the single parameter MLS method to accommodate systems with both multiple parameters and multiple excitations. In a novel manner, the parameters and excitations with different sizes and units are scaled to a common range and combined into a distance metric via a 2 -Norm computation. Only the training sets within a critical distance are retained for the reduced meta-model. Static and dynamic examples show the accuracy and efficiency of the method.
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| Keywords | Meta-model, Multiple parameters and excitations, Moving Least-Squares, Distance metrics | |||
| Article #: RQD2024-83 | ||||
Proceedings of 29th ISSAT International Conference on Reliability & Quality in Design |