Probabilistic Modeling of Discrete Structural Response with Application to Composite Plate Penetration Models
Publication: Journal of Engineering Mechanics
Volume 147, Issue 11
Abstract
Discrete response of structures often is a key probabilistic quantity of interest. For example, one may need to identify the probability of a binary event, such as whether a structure has buckled. This study used an adaptive domain-based decomposition and classification method, combined with sparse grid sampling, to develop an efficient classification surrogate modeling algorithm for such discrete outputs. An assumption of monotonic behavior of the output with respect to all model parameters, based on the physics of the problem, helps to reduce the number of model evaluations and makes the algorithm more efficient. As an application problem, this paper developed a computational framework for generation of a probabilistic penetration response of S--15 epoxy composite plates under ballistic impact. This enables the computationally feasible generation of the probabilistic velocity response (PVR) curve, or the curve, as a function of the impact velocity, and prediction of the ballistic limit velocity as a function of the model parameters. The PVR curve incorporates the variability of the model input parameters and describes the probability of penetration of the plate as a function of impact velocity.
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Data Availability Statement
The data that support the findings of this study are available from the author Lori Graham-Brady upon reasonable request.
Acknowledgments
This research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Nos. W911NF-12-2-0023 and W911NF-12-2-0022. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the US Government. The US Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.
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© 2021 American Society of Civil Engineers.
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Received: Dec 15, 2020
Accepted: Jun 3, 2021
Published online: Aug 23, 2021
Published in print: Nov 1, 2021
Discussion open until: Jan 23, 2022
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