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 129 for “"Surrogate Models"”.
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TCAD-Informed Surrogate Models of Semiconductor Devices
… conducted over the last half-century to develop models of semiconductor devices for use in circuit analysis and simulation. Such models typically fall into one of two categories: “Cheap” analytical models that can be solved quickly but introduce significant error, and “expensive” physics-based …
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Surrogate Models for Transonic Aerodynamics for Multidisciplinary Design Optimization
… coefficients. These points are used to generate surrogate models which can be used for the two-dimensional aerodynamic calculations required by the MDO computational design environment. Strip theory is used to relate these two-dimensional results to the three-dimensional wing. Models are …
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HUMAN DPP4/CD26 TRANSGENIC MICE AS SURROGATE MODELS FOR MERS
… an ongoing public health threat. Animal models, especially small animal models that simulate human disease are needed for studies of pathogenesis and development of vaccines and antivirals for prevention and treatment of MERS-CoV infection and disease. Mice and other commonly used …
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Deep learning-based surrogate models for post-earthquake damage assessment
… This study aims to develop deep learning-based surrogate models for widely used fragility curves to achieve more accurate and rapid assessment in practice. These surrogate models are based on artificial neural networks trained from the labelled ground motions whose resulting damage classes on …
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Statistical Surrogate Models for Robust Design Optimisation in Reduced Dimension
… on complex and often deterministic computational models that may be expensive-to-evaluate. Consequently, it is expedient to consider these models as black-box functions, such that they are interrogated by observing the output for prescribed input variables. The inputs of computational models are …
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Tally derivative based surrogate models for faster Monte Carlo multiphysics
Existing neutron transport methods used in the nuclear power industry rely on a complex toolchain of modeling and simulation software. Each link in this chain applies various approximations to the spatial, angular, and energy distributions of the problem variables; and these approximations can …
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Polynomial-based surrogate models for uncertainty quantification of passive electronic systems
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms
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Surrogate models for the design and control of soft mechanical systems
… and controls. This thesis explores the use of surrogate models to approximate the complex physics between the inputs and outputs of a soft mechanical system composed of a ubiquitous soft building block known as Fiber Reinforced Elastomeric Enclosures (FREEs). Towards this the thesis is divided …
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Data Driven Surrogate Models for Faster SPICE Simulation of Power Supply Circuits
… This research implements a system to train surrogate models for an n-type MOSFET that can replace the nMOS device in SPICE simulation to improve performance while maintaining accuracy, regardless of the larger circuit context. We explore a variety of surrogate modeling and adaptive sampling …
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Quantification of Elastic Incompatibilities at Triple Junctions via Physics-Based Surrogate Models
… the practical use of polycrystalline materials. Surrogate models based on machine learning methods have gained broad popularity due to their ability to furnish a functional, albeit approximate, description of complex phenomena. The goal of this thesis is to predict quantitative metrics of …
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Improved methods for fast system reliability analysis through machine-learning-based surrogate models
… itself estimated with a machine-learning-based surrogate model. The framework is applied to networks with both uncorrelated uniform edge failure probability and correlated edge failure probability, and an extension to node clusters is also proposed. The method first uses spectral clustering to …
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Enhancing surrogate models of engineering structures with graph-based and physics-informed learning
… several opportunities in the development of surrogate models used for structural design. Though surrogate models have become an indispensable tool in the design and analysis of structural systems, their scope is often limited by the parametric design spaces on which they were built. In …
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Augmented Neural Network Surrogate Models for Polynomial Chaos Expansions and Reduced Order Modeling
Mathematical models describing real world processes are becoming increasingly complex to better match the dynamics of the true system. While this is a positive step towards more complete knowledge of our world, numerical evaluations of these models become increasingly computationally inefficient, …
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Seismic experimental analyses and surrogate models of multi-component systems in special-risk industrial facilities
… steel frame structure and the most recent surrogate-based UQ forward analysis advancements. Specifically, the framework is applied to a real-world application consisting of seismic shake table tests of a representative industrial multi-storey frame structure equipped with complex process …
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Biomechanical Responses and Functional Outcomes in Large Animal and Human Surrogate Models of Primary Blast Injury
… an acute timepoint. Using an instrumented human surrogate model, the effect of blast intensity, orientation, and the presence of a combat helmet on blast loading was examined. In a frontal blast orientation, peak pressures were shown to be reduced at the forehead and front of the head but …
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Development and Demonstration of Surrogate Models to Predict Energy-Related Building Features from Heating and Cooling Load Signature
… Utilizing inverse model-based machine learning, surrogate models for 12 mid to high-rise buildings were developed to predict energy-related features from widely available heating and cooling load data. The research explores two methodologies: 1) unsupervised learning with clustering to group …
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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
… Computational Fluid Dynamics (CFD) accurately models these hydrodynamic interactions, but a simulation of a single UUV in one specific configuration typically takes hours or days to complete. Therefore, it is not practical for real-time applications. To bridge this gap, a machine learning …
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Hybrid Dynamic Modelling of Engine Emissions on Multi-Physics Simulation Platform. A Framework Combining Dynamic and Statistical Modelling to Develop Surrogate Models of System of Internal Combustion Engine for Emission Modelling
The data-driven models used for the design of powertrain controllers are typically based on the data obtained from steady-state experiments. However, they are only valid under stable conditions and do not provide any information on the dynamic behaviour of the system. In order to capture this …
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Hybrid Dynamic Modelling of Engine Emissions on Multi-Physics Simulation Platform. A Framework Combining Dynamic and Statistical Modelling to Develop Surrogate Models of System of Internal Combustion Engine for Emission Modelling
The data-driven models used for the design of powertrain controllers are typically based on the data obtained from steady-state experiments. However, they are only valid under stable conditions and do not provide any information on the dynamic behaviour of the system. In order to capture this …
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Surrogate modeling of alternative jet fuels for study of autoignition characteristics
Recently published surrogate models are evaluated for their predictive capabilities of autoignition characteristics for alternative jet fuels. Computational simulation results are compared with published data from experimental rapid compression machine (RCM) tests for conventional jet fuel. …
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