Co-Active Subspace Methods for the Joint Analysis of Adjacent Computer Models

Active subspace (AS) methods are a valuable tool for understanding the relationship between the inputs and outputs of a Physics simulation. In this article, an elegant generalization of the traditional ASM is developed to assess the co-activity of two computer models. This generalization, which we refer to as a Co-Active Subspace (Co-AS) Method, allows for the joint analysis of two or more computer models allowing for thorough exploration of the alignment (or non-alignment) of the respective gradient spaces. We define co-active directions, co-sensitivity indices, and a scalar “concordance” metric (and complementary “discordance” pseudo-metric) and we demonstrate that these are powerful tools for understanding the behavior of a class of computer models, especially when used to supplement traditional AS analysis. Details for efficient estimation of the Co-AS and an accompanying R package (concordance) are provided. Practical application is demonstrated through analyzing a set of simulated rate stick experiments for PBX 9501, a high explosive, offering insights into complex model dynamics.

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Publication Details

Journal
Technometrics
Published
2024-09-23
DOI
https://doi.org/10.1080/00401706.2024.2407314
Citations
1
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
0.46
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article

Co-Active Subspace Methods for the Joint Analysis of Adjacent Computer Models

Cory Ahrens, Scott Vander Wiel, Kellin Rumsey, Zachary K. Hardy
1 citations
Technometrics
Probabilistic and Robust Engineering Design
0.46
article

Co-Active Subspace Methods for the Joint Analysis of Adjacent Computer Models

Cory Ahrens, Scott Vander Wiel, Kellin Rumsey, Zachary K. Hardy
article en
1 citations

Abstract

Active subspace (AS) methods are a valuable tool for understanding the relationship between the inputs and outputs of a Physics simulation. In this article, an elegant generalization of the traditional ASM is developed to assess the co-activity of two computer models. This generalization, which we refer to as a Co-Active Subspace (Co-AS) Method, allows for the joint analysis of two or more computer models allowing for thorough exploration of the alignment (or non-alignment) of the respective gradient spaces. We define co-active directions, co-sensitivity indices, and a scalar “concordance” metric (and complementary “discordance” pseudo-metric) and we demonstrate that these are powerful tools for understanding the behavior of a class of computer models, especially when used to supplement traditional AS analysis. Details for efficient estimation of the Co-AS and an accompanying R package (concordance) are provided. Practical application is demonstrated through analyzing a set of simulated rate stick experiments for PBX 9501, a high explosive, offering insights into complex model dynamics.

TechnometricsVol. 67(1)
Los Alamos National Laboratory (US)
Openalex Percentile: Top 28%
Probabilistic and Robust Engineering Design
0.46
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