Adaptive Kriging for Simulation-based Design under Uncertainty - Development of Metamodels in Augmeted Input Space and Adaptive Tuning of Their Characteristics

Alexandros Taflanidis, Juan Camilo Medina

2014

Abstract

This investigation focuses on design-under-uncertainty problems that employ a probabilistic performance as objective function and consider its estimation through stochastic simulation. This approach puts no constraints on the computational and probability models adopted, but involves a high computational cost especially for design problems involving complex, high-fidelity numerical models. A framework relying on kriging metamodeling to approximate the system performance in an augmented input space is considered here to alleviate this cost. A sub region of the design space is defined and a kriging metamodel is built to approximate the system response (output) with respect to both the design variables and the uncertain model parameters (random variables). This metamodel is then used within a stochastic simulation setting (addressing uncertainties in the model parameters) to approximate the system performance when estimating the objective function for specific values of the design variables. This information is then used to search for a local optimum within the previously established design sub domain. Only when the optimization algorithm drives the search outside this domain, a new metamodel is generated. The process is iterated until convergence is established and an efficient sharing of information across these iterations is established to adaptively tune characteristics of the kriging metamodel.

Paper Citation

in Harvard Style

Taflanidis A. and Medina J. (2014). Adaptive Kriging for Simulation-based Design under Uncertainty - Development of Metamodels in Augmeted Input Space and Adaptive Tuning of Their Characteristics . In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SDDOM, (SIMULTECH 2014) ISBN 978-989-758-038-3, pages 785-797. DOI: 10.5220/0005134007850797

in Bibtex Style

@conference{sddom14,
author={Alexandros Taflanidis and Juan Camilo Medina},
title={Adaptive Kriging for Simulation-based Design under Uncertainty - Development of Metamodels in Augmeted Input Space and Adaptive Tuning of Their Characteristics},
booktitle={Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SDDOM, (SIMULTECH 2014)},
year={2014},
pages={785-797},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005134007850797},
isbn={978-989-758-038-3},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SDDOM, (SIMULTECH 2014)
TI - Adaptive Kriging for Simulation-based Design under Uncertainty - Development of Metamodels in Augmeted Input Space and Adaptive Tuning of Their Characteristics
SN - 978-989-758-038-3
AU - Taflanidis A.
AU - Medina J.
PY - 2014
SP - 785
EP - 797
DO - 10.5220/0005134007850797