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 20 of 57 for “"High-Fidelity Simulations"”.
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High fidelity simulations of electrokinetic phenomena in microfluidic devices
… and detection. This dissertation focuses on simulations of two electrokinetic phenomena, isotachophoresis (ITP) and electrokinetic instability (EKI). A set of coupled governing equations including the incompressible Naiver-Stokes equations, Nernst-Planck transport equations and a charge …
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Extraction of turbomachinery loss mechanisms from high-fidelity simulations
With recent advances in high-power computing, Direct Numerical Simulations (DNS), high-fidelity fluids simulations which are able to capture the full turbulence spectrum, are becoming a more common-place tool for the analysis of turbomachinery. As a result, new challenges arise in the management …
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High-fidelity simulations of transverse electric waves propagating through Alcator C-Mod
… of microwaves into Alcator C-Mod's plasma in high fidelity and with a reduced number of degrees of freedom. The success of this endeavor would accelerate progress within the field of fusion energy, as simulations of C-Mod's plasmas, or other plasmas in general, can be run more quickly while …
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Multi-GPU Accelerated High-Fidelity Simulations of Beam-Beam Effects in Particle Colliders
… linac-ring machines (eRHIC) or LHeC. These simulations model the non-linear collision dynamics of two counter rotating beams in particle colliders for millions of turns. In particular, at each turn, the algorithm simulates the collision of two directed beams propagating at different speeds …
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Experimental and Computational Study of Vibration-Based Energy Harvesting Systems for Self-Powered Devices
… aeroelastic vibrations. Given the complexity of high-fidelity simulations of the coupling between the fluid flow, structural response and piezoelectric transduction, we develop and experimentally validate a phenomelogical reduced-order model for energy harvesting from wake galloping. We also …
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Physics-Informed Machine Learning Methodologies Using RAPID for Predicting Eigenvalue and 3-D Fission Distribution in JSI TRIGA Mark-II Research Reactor
The most common methodologies for high-fidelity simulations of nuclear reactors are very slow and require significant computer resources. Machine learning (ML) enables computers the ability to learn from data, allowing well-trained models to produce results quickly and accurately. However, the …
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Improving turbomachinery loss prediction using high fidelity CFD
High fidelity simulations of three compressor cascades and a fundamental trailing edge flow are used to interrogate, and improve upon, the errors present in conventional RANS simulations. Using the optimum turbulence viscosity, calculated from the high fidelity simulations, it is found that error …
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Analysis of Stresses in Metal Sheathed Thermocouples in High-Temperature, Hypersonic Flows
… lifetime of sensors. In contemporary practice, high-fidelity simulations must be run to prove if a new design will work at all, albeit at significant time and expense. Given the time and money it takes to run high-fidelity simulations, rapid optimization of sensor configurations is often …
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Machine learning in ocean applications : wave prediction for advanced controls of renewable energy and modeling nonlinear viscous hydrodynamics
… since data from experiments, field tests or high-fidelity simulations are mostly informative about actual physical systems. Machine learning algorithms, especially kernel based methods have very good generalization capability as well as statistical inference. This thesis targets to establish …
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An evaluation of the construct validity of situational judgment tests
… tests are analogous to earlier forms of "high fidelity" simulations such that an ostensible paradox emerges in the consistent finding of criterion-referenced validity but almost complete lack of construct validity evidence. The present study evaluates the extent to which SJT's can …
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A Deep Learning Approach to Predict Full-Field Stress Distribution in Composite Materials
… of training and validation are generated via high-fidelity simulations of several randomly generated microstructural representations with complex geometries. Two deep learning approaches are employed and their performances are compared: fully convolutional generator and Pix2Pix translation. It …
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The Adaptation of a Situational Judgement Test to Measure Leadership Knowledge in the Workplace
… This emergence is partly due to the high costs associated with developing and conducting high fidelity simulations such as assessment centers, coupled with the recent economic downturn affecting many organizations. The current study sought to validate an SJT as a low cost, alternate …
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Methods for design optimization using high fidelity turbulent flow simulations
Design optimization with high-fidelity turbulent flow simulations can be challenging due to noisy and expensive objective function evaluations. The noise decays slowly as computation cost increases, therefore is significant in most simulations. It is often unpredictable due to chaotic dynamics of …
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Computational Fluid Dynamic Solutions of Optimized Heat Shields Designed for Earth Entry
… the low-order approach matches computational simulations within 10%. Benchmark Apollo 4 solutions show that predicted heat fluxes under-predict convective heating by 30% and over-predict radiative heating by 16% compared to computational results. Parametric studies display a power law reliance …
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Proper orthogonal decomposition & kriging strategies for design
… have facilitated the application of expensive, high fidelity simulations within design optimisation. Taking considerably fewer function evaluations than direct global optimisation techniques, such as genetic algorithms, surrogate models attempt to construct a surrogate of an objective function …
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Leveraging Gaussian Process Sampling for Sensitivity Analysis and Optimization in Engineering Design
High-fidelity simulations and physical experiments are fundamental in engineering analysis and design. However, their high computational cost often prohibits their application in global sensitivity analysis (GSA), optimization, and automated structural health monitoring (SHM). Gaussian processes …
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Multi-fidelity Modeling and Reinforcement Learning for Energy Optimal Planning
… over. We present a sequence-to-sequence multi-fidelity Gaussian process (MFGP) to learn a data-driven model to predict the energy required to fly a given vehicle trajectory. The goal is to create an accurate energy prediction that minimizes the number of expensive high fidelity simulations …
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Classical and Quantum Computational Methods for Predicting Fluid Transport in Fracture Networks
… emulators. In combination with multi-fidelity and quantum techniques, they make physics-informed modeling computationally feasible. One of our studies involves the use of Gaussian process regression to generate Bayesian predictions for gas transport in 3D discrete fracture networks. …
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Numerical Investigations of Thermal-Fluid Phenomena Across Emerging Energy Systems
… and heat transfer behavior under extreme or highly variable conditions. The first portion of the work focuses on supercritical carbon dioxide (sCO<sub>2</sub>), a working fluid of increasing importance in advanced power and refrigeration cycles. A comprehensive historical review of …
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An automatic, multi-fidelity framework for optimizing the performance of super-cavitating hydrofoils using Gaussian process regression and Bayesian optimization
… by the computational resources required for the high precision solvers. Determining an optimum design necessitates high accuracy simulations due to the multi-dimensional design space and the interconnectedness of the constraint and objective quantities. This paper will present an automated …
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