Traditionally, model calibration is formulated as a single objective problem, where fidelity to measurements is maximized by adjusting model parameters. In such a formulation however, the model with best fidelity mere...
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Traditionally, model calibration is formulated as a single objective problem, where fidelity to measurements is maximized by adjusting model parameters. In such a formulation however, the model with best fidelity merely represents an optimum compromise between various forms of errors and uncertainties and thus, multiple calibrated models can be found to demonstrate comparable fidelity producing non-unique solutions. To alleviate this problem, the authors formulate model calibration as a multi-objective problem with two distinct objectives: fidelity and robustness. Herein, robustness is defined as the maximum allowable uncertainty in calibrating model parameters with which the model continues to yield acceptable agreement with measurements. The proposed approach is demonstrated through the calibration of a finite element model of a steel moment resisting frame.
validationexperiments are conducted at discrete settings within an operational domain to assess the predictive maturity of a model that is ultimately used to predict over the entire operational domain. Unless this do...
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validationexperiments are conducted at discrete settings within an operational domain to assess the predictive maturity of a model that is ultimately used to predict over the entire operational domain. Unless this domain is sufficiently explored with validationexperiments, satisfactory model performance at these discrete, tested settings would be insufficient to ensure satisfactory model performance throughout the entire operational domain. The goal of coverage metrics is then to reveal how well a set of validationexperiments represents an operational domain. The authors identify the criteria of an exemplary coverage metric, evaluate the ability of existing coverage metrics to fulfill these criteria, and propose a new, improved coverage metric. The proposed metric favors interpolation over extrapolation through a penalty function, causing the metric to prefer a design of validationexperiments near the boundaries of the domain, while simultaneously exploring inside the domain. Furthermore, the proposed metric allows the coverage to account for the relative influence of each dimension of the domain on the model output. Application of the proposed coverage metric on a practical, non-trivial two-dimensional problem is demonstrated on the Viscoplastic Self-Consistent material plasticity code for 5182 aluminum alloy. Furthermore, the proposed metric is compared to existing coverage metrics considering a high dimensional problem with application to the Rosenbrock function. (C) 2014 Elsevier Ltd. All rights reserved.
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