Néstor V. Queipo

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OBJECTIVES This study presents a reliable index inspired by the total variability concept of real analysis in mathematics, called average real variability (ARV), for the prognostic significance of blood pressure variability (BPV) overcoming the pitfalls of the commonly used standard deviation (SD). BACKGROUND Recent studies have suggested that an increase(More)
This paper presents a general approach toward the optimal selection and ensemble (weighted average) of surrogates (kernel-based approximations) to address the issue of model uncertainty (model selection); that is, depending on the problem under consideration and loss function (i.e., quadratic, Laplace, e-insensitive) a particular modeling scheme (e.g.,(More)
Contact occurs in a wide variety of multibody dynamic systems, including the human musculoskeletal system. However, sensitivity and optimization studies of such systems have been limited by the high computational cost of repeated contact analyses. This study presents a novel surrogate modeling approach for performing computationally efficient(More)
Computational speed is a major limiting factor for performing design sensitivity and optimization studies of total knee replacements. Much of this limitation arises from extensive geometry calculations required by contact analyses. This study presents a novel surrogate contact modeling approach to address this limitation. The approach involves fitting(More)
This paper presents a solution methodology for multiobjective optimization problems in the context of models for the placement of components on printed wiring boards (PWB’s). The methodology combines the use of a flow and heat transfer solver, a genetic algorithm for the adaptive search of optimal or near-optimal solutions, and a multiobjective optimization(More)
This paper presents an efficient shape optimization technique based on stochastic response surfaces (polynomial chaos expansion) constructed using performance and local sensitivity data at heuristically selected collocation points. The cited expansion uses Hermite polynomial bases for the space of square-integrable probability density functions and provides(More)
This paper presents an integrated approach for the solution of complex optimization problems in thermoscience research. The cited approach is based on the design of computational experiments (DOE), surrogate modeling, and optimization. The DOE/surrogate modeling techniques under consideration include: A-optimal/classical linear regression, Latin(More)
A three-dimensional computational model of an experimental rectangular combustion chamber was developed to explore the wall heat transfer of a GO2/GH2 shear coaxial single element injector. The CFD model allowed for the direct analysis of heat transfer effects due to flow dynamics—an analysis that would be very difficult using experimental studies alone.(More)
A typical approach in surrogate-based modeling is to assess the performance of alternative surrogate models and select the model that performs the best. In this paper, we extend the utility of an ensemble of surrogates to: i) identify regions of high uncertainties at locations where predictions of surrogates widely differ, and ii) provide a more robust(More)