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Articles 1 - 3 of 3
Full-Text Articles in Computational Engineering
Quantifying Hurricane Effects On Housing: Evaluating Damage, Loss, And Shelter Demands Using Historical And Simulated Storm Tracks, Adish Deep Shakya
Quantifying Hurricane Effects On Housing: Evaluating Damage, Loss, And Shelter Demands Using Historical And Simulated Storm Tracks, Adish Deep Shakya
All Theses
This research introduces an advanced framework which employs parametric wind field models for peak wind speeds, and building fragility curves, loss functions, and demographic data to estimate for estimating housing damage and loss. The uninhabitable units immediate displaced households, short-term and long-term shelter need households are determined. with a particular focus on those eligible for FEMA assistance. The framework's validity is reinforced by a high correlation in the analysis of recent hurricane events between estimated numbers of displaced households and actual FEMA aid recipients, where FEMA aids about 20-60% of the predicted long-term displaced households. A novel application of the …
Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin
All Dissertations
Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …
Computational Study Of Dense Gas Dispersion In Urban Areas, Rasna Sharmin
Computational Study Of Dense Gas Dispersion In Urban Areas, Rasna Sharmin
All Dissertations
A series of steady-state simulations have been conducted to investigate removal of dense gas from a simple square canyon formed between two square cross-section obstacles. Due to urbanization and industrialization, there always lies a high risk of exposure to harmful pollutants which can result from accidental release of toxic gasses. Those are often denser than the atmosphere. and can easily get trapped in between buildings in urban canopies. It is important to have full understanding of flushing mechanism of dense fluid inside urban canopies by steady turbulent flow because the exposure to these toxic dense gasses can be catastrophic. There …