Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"multifidelity"”.
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Multifidelity Covariance Estimation Three Ways
… thesis we develop a suite of three methods for multifidelity covariance estimation. We begin with a straightforward extension of scalar multifidelity Monte Carlo to matrices, obtaining what we refer to as the Euclidean or linear control variate mutifidelity covariance estimator. The mean squared …
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Multifidelity optimization methods for interconnected multidisciplinary systems
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-08-01
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Multifidelity methods for multidisciplinary design under uncertainty
… optimization (BMDO) framework for conducting multifidelity design with uncertainty. Fidelity level is associated with the magnitude of model discrepancy. Model selection is determined by apportioning design uncertainty to the disciplines to identify key contributors. As fidelity level …
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Multifidelity Methods for Design of Transition MetalComplexes
The rational design of materials with tightly controlled properties is crucial to addressing future challenges in energy, electronics and catalysis. While improvements in computing power have made simulation with density functional theory (DFT) an essential tool in screening new materials, it …
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An Optimization Centered Approach to Multifidelity Aircraft Design
… algorithms that enable an optimization centered, multifidelity approach to aircraft design. The new al- gorithms are benchmarked against a current state of the art algorithm using a set of example problems, and the new design approach is applied to two representative aircraft design case studies.
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Fusion of correlated information in multifidelity aircraft design optimization
… In this thesis, we present a surrogate-based multifidelity framework that simultaneously accounts for model correlation and accommodates non-hierarchical fidelity specifications. The development of our multifidelity framework can be classified into three stages. The first stage involves the …
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Surrogate-based optimization using multifidelity models with variable parameterization
Engineers are increasingly using high-fidelity models for numerical optimization. However, the computational cost of these models, combined with the large number of objective function and constraint evaluations required by optimization methods, can render such optimization computationally …
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Scaling Bayesian optimization for engineering design : lookahead approaches and multifidelity dimension reduction
… method of Active Subspaces. We propose a multifidelity active subspace algorithm that reduces the computational cost by leveraging a cheap-to-evaluate approximation of the objective function. We analyze the number of evaluations sufficient to control the error incurred, both in expectation …
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Multidelity approaches for design under uncertainty
… costs. This thesis presents rigorous multifidelity approaches to leverage cheap low-fidelity models and other approximations of the expensive high-fidelity model to reduce the computational expense of optimization under uncertainty. Solving an optimization under uncertainty problem can …
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Multidelity methods for multidisciplinary system design
… design, and developing methods that exploit multifidelity information in order to parallelize the optimization of the system and reduce the time needed to find an optimal design. To find high-fidelity optimal designs, Bayesian model calibration is used to improve low- fidelity models and …
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Modeling and sensitivity analysis of aircraft geometry for multidisciplinary optimization problems
… CAD models is presented using concepts of multifidelity/multidisciplinary geometry and design motion. A formalized definition of design intent emerges from this approach that enables CAD models with parameterization flexibility, shape malleability and regeneration robustness for automated …
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Real-time Autonomy and Maneuvering Simulation of an Unmanned Underwater Vehicle Near a Moving Submarine Using Actively Sampled Gaussian Process Surrogate Models
… active learning framework, called Non-Myopic MultiFidelity (NMMF) active learning for GP regression, significantly and parsimoniously accelerates the convergence of the surrogate model by combining the low cost of the low-fidelity, potential flow simulations to explore the domain, as well as …
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Enabling End-to-End Sensitivity Analysis of Integrated Models
… approximate strategies are introduced, including multifidelity surrogate modeling and statistical regression. These methods support both forward uncertainty propagation and variance-based global sensitivity analysis for structurally complex integrated models, without requiring full-system …
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Combining Data-driven and Theory-guided Models in Ensemble Data Assimilation
There once was a dream that data-driven models would replace their theory-guided counterparts. We have awoken from this dream. We now know that data cannot replace theory. Data-driven models still have their advantages, mainly in computational efficiency but also providing us with some special …
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Modelling of Direct Hydrogen Combustion in Jet Engines: System-Level Analysis, Computational Fluid Dynamics and Chemical Reactor Networks
L'abstract è presente nell'allegato / the abstract is in the attachment