scholarly journals Computer model calibration with confidence and consistency

2019 ◽  
Vol 81 (3) ◽  
pp. 519-545
Author(s):  
Matthew Plumlee
Keyword(s):  
Computer Model ◽  
Model Calibration

Simultaneous Bayesian calibration and engineering design with an application to a vibration isolation system

2021 ◽  
Author(s):  
Carl Ehrett ◽  
D. Andrew Brown ◽  
Christopher Kitchens ◽  
Xinyue Xu ◽  
Roland Platz ◽  
...  
Keyword(s):  
Computer Model ◽  
Adaptive Sampling ◽  
Model Calibration ◽  
Vibration Isolation ◽  
Traditional Approach ◽  
Design Procedure ◽  
Parameter Estimates ◽  
Computationally Efficient ◽  
Isolation System ◽  
Vibration Isolation System

Abstract Calibration of computer models and the use of those models for design are two activities traditionally carried out separately. This paper generalizes existing Bayesian inverse analysis approaches for computer model calibration to present a methodology combining calibration and design in a unified Bayesian framework. This provides a computationally efficient means to undertake both tasks while quantifying all relevant sources of uncertainty. Specifically, compared with the traditional approach of design using parameter estimates from previously completed model calibration, this generalized framework inherently includes uncertainty from the calibration process in the design procedure. We demonstrate our approach on the design of a vibration isolation system. We also demonstrate how, when adaptive sampling of the phenomenon of interest is possible, the proposed framework may select new sampling locations using both available real observations and the computer model. This is especially useful when a misspecified model fails to reflect that the calibration parameter is functionally dependent upon the design inputs to be optimized.

Generalized Computer Model Calibration for Radiation Transport Simulation

Technometrics ◽  
2020 ◽  
pp. 1-13
Author(s):  
Michael Grosskopf ◽  
Derek Bingham ◽  
Marvin L. Adams ◽  
W. Daryl Hawkins ◽  
Delia Perez-Nunez
Keyword(s):  
Computer Model ◽  
Model Calibration ◽  
Radiation Transport ◽  
Transport Simulation

Parameter Screening in Statistical Dynamic Computer Model Calibration Using Global Sensitivities

2012 ◽  
Vol 134 (8) ◽  
Author(s):  
Dorin Drignei ◽  
Zissimos P. Mourelatos
Keyword(s):  
Sensitivity Analysis ◽  
Computer Model ◽  
Model Calibration ◽  
Simulation Models ◽  
Computer Models ◽  
Automotive Application ◽  
Transient Signals ◽  
Sensitivity Indices ◽  
Calibration Algorithm ◽  
Computationally Intensive

Computer, or simulation, models are ubiquitous in science and engineering. Two research topics in building computer models, generally treated separately, are sensitivity analysis and computer model calibration. In sensitivity analysis, one quantifies the effect of each input factor on outputs, whereas in calibration, one finds the values of input factors that provide the best match to a set of test data. In this article, we show a connection between these two seemingly separate concepts for problems with transient signals. We use global sensitivity analysis for computer models with transient signals to screen out inactive input factors, thus making the calibration algorithm numerically more stable. We show that the computer model does not vary with respect to parameters having zero total sensitivity indices, indicating that such parameters are impossible to calibrate and must be screened out. Because the computer model can be computationally intensive, we construct a fast statistical surrogate of the computer model which is used for both sensitivity analysis and computer model calibration. We illustrate our approach with both a simple example and an automotive application involving a road load data acquisition (RLDA) computer model.

Multi-Objective Engineering Design Via Computer Model Calibration

2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Carl Ehrett ◽  
D. Andrew Brown ◽  
Evan Chodora ◽  
Christopher Kitchens ◽  
Sez Atamturktur
Keyword(s):  
Computer Model ◽  
Model Calibration ◽  
Material Design ◽  
Fine Tuning ◽  
Tuning Parameter ◽  
Design Problems ◽  
Multi Objective ◽  
Performance Targets ◽  
Calibration Techniques ◽  
Parameter Values

Abstract Computer model calibration typically operates by fine-tuning parameter values in a computer model so that the model output faithfully predicts reality. By using performance targets in place of observed data, we show that calibration techniques can be repurposed for solving multi-objective design problems. Our approach allows us to consider all relevant sources of uncertainty as an integral part of the design process. We demonstrate our proposed approach through both simulation and fine-tuning material design settings to meet performance targets for a wind turbine blade.

scholarly journals Computer Model Calibration Based on Image Warping Metrics: An Application for Sea Ice Deformation

2019 ◽  
Vol 24 (3) ◽  
pp. 444-463 ◽  
Author(s):  
Yawen Guan ◽  
Christian Sampson ◽  
J. Derek Tucker ◽  
Won Chang ◽  
Anirban Mondal ◽  
...  
Keyword(s):  
Sea Ice ◽  
Computer Model ◽  
Model Calibration ◽  
Image Warping

scholarly journals Prediction and Computer Model Calibration Using Outputs From Multifidelity Simulators

Technometrics ◽  
2013 ◽  
Vol 55 (4) ◽  
pp. 501-512 ◽  
Author(s):  
Joslin Goh ◽  
Derek Bingham ◽  
James Paul Holloway ◽  
Michael J. Grosskopf ◽  
Carolyn C. Kuranz ◽  
...  
Keyword(s):  
Computer Model ◽  
Model Calibration

Parameter Screening in Dynamic Computer Model Calibration Using Global Sensitivities

2010 ◽  
Author(s):  
Dorin Drignei ◽  
Zissimos P. Mourelatos ◽  
Ramesh Rebba
Keyword(s):  
Sensitivity Analysis ◽  
Computer Model ◽  
Automotive Industry ◽  
Model Calibration ◽  
Field Data ◽  
Global Sensitivity Analysis ◽  
Transient Responses ◽  
Road Load ◽  
Calibration Algorithm ◽  
Computationally Intensive

Sensitivity analysis and computer model calibration are generally treated as two separate topics. In sensitivity analysis one quantifies the effect of each input factor on outputs, whereas in calibration one finds the values of input factors that provide the best match to a set of field data. In this paper we show a connection between these two seemingly separate concepts, and illustrate it with an automotive industry application involving a Road Load Acquisition Data (RLDA) computer model. We use global sensitivity analysis for computer models with transient responses to screen out inactive input parameters and make the calibration algorithm numerically more stable. Because the computer model can be computationally intensive, we construct a fast statistical surrogate for the computer model with transient responses. This fast surrogate is used for both sensitivity analysis and RLDA computer model calibration.

scholarly journals Computer Model Calibration Using the Ensemble Kalman Filter

Technometrics ◽  
2013 ◽  
Vol 55 (4) ◽  
pp. 488-500 ◽  
Author(s):  
Dave Higdon ◽  
Jim Gattiker ◽  
Earl Lawrence ◽  
Charles Jackson ◽  
Michael Tobis ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Computer Model ◽  
Ensemble Kalman Filter ◽  
Model Calibration
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