Search

Start Over Degree MS Year 2022 Keyword machine learning

1. Physics-Infused Reduced-Order Modeling of Aerothermal Loads for Fluid-Thermal-Structural Interactions

open_access
Open Access
Author:
Vargas Venegas, Carlos
Title:
Physics-Infused Reduced-Order Modeling of Aerothermal Loads for Fluid-Thermal-Structural Interactions
Graduate Program:
Aerospace Engineering (MS)
Keywords:
hypersonic
fluid-thermal-structural
aerothermoelasticity
data-driven
physics-driven
physics-based
reduced-order modeling
machine learning
field inversion
aerothermal
turbulent viscous-inviscid interactions
neural ordinary differential equations
direct collocation
optimization
kriging
proper-orthogonal decomposition
latin hypercube sampling
thermoelastic
hypersonic vehicle
RANS
skin-panel
two-dimensional
gaussian process regression
computational fluid dynamics
supported panel
augmentation
augmented
model augmentation
surrogate
POD-kriging
POD
algebraic
differential
algebraic augmentation
differential augmentation
NODE
PIROM
analysis
File:
Download ms-thesis-corrected.pdf
Committee Members:
Daning Huang, Thesis Advisor/Co-Advisor
Puneet Singla, Committee Member
Amy Pritchett, Program Head/Chair
Sven Schmitz, Committee Member

2. An Analysis and Framework for Multi-label Image Classification of Insect Taxonomy with Convolutional Neural Networks

restricted_to_institution
Restricted (Penn State Only)
Author:
Pham, Viet
Title:
An Analysis and Framework for Multi-label Image Classification of Insect Taxonomy with Convolutional Neural Networks
Graduate Program:
Computer Science and Engineering (MS)
Keywords:
multi-label image classification
image classification
computer vision
machine learning
insect taxonomy
convolutional neural networks
File:
Login to Download
Committee Members:
Chitaranjan Das, Program Head/Chair
Vijaykrishnan Narayanan, Thesis Advisor/Co-Advisor
John Morgan Sampson, Committee Member

3. Machine Learning Approach for Prediction of Relative Permeability

restricted_to_institution
Restricted (Penn State Only)
Author:
Yoga, Hanif
Title:
Machine Learning Approach for Prediction of Relative Permeability
Graduate Program:
Energy and Mineral Engineering (MS)
Keywords:
machine learning
artificial intelligence
artificial neural network
relative permeability
hysteresis
equation of state
multiphase flow in porous media
File:
Login to Download
Committee Members:
Mort Webster, Professor in Charge/Director of Graduate Studies
Russell Taylor Johns, Thesis Advisor/Co-Advisor
Hamid Emami-Meybodi, Committee Member
Yashar Mehmani, Committee Member