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Solving Large Dynamical Systems by Constraint Sampling

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Book cover Applied Computer Sciences in Engineering (WEA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1052))

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Abstract

The ability to conduct fast and reliable simulations of dynamic systems is of special interest to many fields of operations. Such simulations can be very complex and, to be thorough, involve millions of variables, making it prohibitive in CPU time to run repeatedly for many different configurations. Reduced-Order Modeling (ROM) provides a concrete way to handle such complex simulations using a realistic amount of resources. However, when the original dynamical system is very large, the resulting reduced-order model, although much “thinner”, is still as tall as the original system, i.e., it has the same number of equations. In some extreme cases, the number of equations is prohibitive and cannot be loaded in memory. In this work, we combine traditional interval constraint solving techniques with a strategy to reduce the number of equations to consider. We describe our approach and report preliminary promising results.

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Author information

Authors and Affiliations

  1. The University of Texas at El Paso, El Paso, TX, 79968, USA

    Omeiza Olumoye, Angel Garcia, Leobardo Valera & Martine Ceberio

  2. New Mexico State University, 1780 E University Avenue, Las Cruces, NM, 88003, USA

    Glen Throneberry & Abdessattar Abdelkefi

Authors
  1. Omeiza Olumoye
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  2. Glen Throneberry
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  3. Angel Garcia
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  4. Leobardo Valera
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  5. Abdessattar Abdelkefi
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  6. Martine Ceberio
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Corresponding author

Correspondence to Omeiza Olumoye .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Juan Carlos Figueroa-García

  2. Universidad Antonio Nariño, Bogotá, Colombia

    Mario Duarte-González

  3. Universidad Antonio Nariño, Bogotá, Colombia

    Sebastián Jaramillo-Isaza

  4. Universidad del Rosario, Bogotá, Colombia

    Alvaro David Orjuela-Cañon

  5. Corporación Unificada Nacional CUN, Bogotá, Colombia

    Yesid Díaz-Gutierrez

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Olumoye, O., Throneberry, G., Garcia, A., Valera, L., Abdelkefi, A., Ceberio, M. (2019). Solving Large Dynamical Systems by Constraint Sampling. In: Figueroa-García, J., Duarte-González, M., Jaramillo-Isaza, S., Orjuela-Cañon, A., Díaz-Gutierrez, Y. (eds) Applied Computer Sciences in Engineering. WEA 2019. Communications in Computer and Information Science, vol 1052. Springer, Cham. https://doi.org/10.1007/978-3-030-31019-6_1

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  • DOI: https://doi.org/10.1007/978-3-030-31019-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31018-9

  • Online ISBN: 978-3-030-31019-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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