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Full-Text Articles in Engineering

Acoustic Design Optimization With Isogeometric Analysis And Differential Evolution, Garrett W. Dodgen Dec 2019

Acoustic Design Optimization With Isogeometric Analysis And Differential Evolution, Garrett W. Dodgen

Mechanical Engineering Theses

The objective of this study is to utilize shape optimization to enhance the performance of devices relying on acoustic wave propagation. Particularly, the shape of a horn speaker and an acoustic energy harvester were optimized to enhance their performance at targeted frequencies. High order Isogeometric Analysis (IGA) was performed to estimate the acoustic pressure with minimum geometry and pollution errors [1]. The analysis platform was then combined with Differential Evolution (DE) to optimize the geometry of the horn speaker and energy harvester at a given frequency. These cases effectively demonstrate two applications of Isogeomtric shape optimization for devices relying on …


Gearbox Baffle Optimization, Megan Arduin Dec 2019

Gearbox Baffle Optimization, Megan Arduin

Masters Theses

Current literature reveals there is limited consensus on the placement of baffles within a gearbox to reduce churning losses. Thus, there is a need for a process to identify baffle clearances that result in maximum and minimum churning losses. There are two types of baffles: axial and radial. While both axial and radial baffles cause reductions in churning losses to various degrees, the focus is on the effect of radial baffles. The effect of a board (rectangular plate) baffle location on the churning losses of a single gear gearbox are evaluated using computational fluid dynamics (CFD) implemented in Ansys. Several …


A Reinforcement Learning Approach To Spacecraft Trajectory Optimization, Daniel S. Kolosa Dec 2019

A Reinforcement Learning Approach To Spacecraft Trajectory Optimization, Daniel S. Kolosa

Dissertations

This dissertation explores a novel method of solving low-thrust spacecraft targeting problems using reinforcement learning. A reinforcement learning algorithm based on Deep Deterministic Policy Gradients was developed to solve low-thrust trajectory optimization problems. The algorithm consists of two neural networks, an actor network and a critic network. The actor approximates a thrust magnitude given the current spacecraft state expressed as a set of orbital elements. The critic network evaluates the action taken by the actor based on the state and action taken. Three different types of trajectory problems were solved, a generalized orbit change maneuver, a semimajor axis change maneuver, …


Design, Analysis, And Optimization Of Compactible Origami-Inspired Shelters, Anthony M. Verzoni Aug 2019

Design, Analysis, And Optimization Of Compactible Origami-Inspired Shelters, Anthony M. Verzoni

Electronic Theses and Dissertations

Origami-inspired design is a growing field with numerous engineering applications, including rapidly compactable and erectable shelters with nondeformed flat panels, which are considered in this research. Shelter geometry is controlled by the shape, size, and connectivity of individual panels that must fold and unfold in a kinematically compliant manner resulting in no panel intersection. Panel size and shape are altered to yield shelter designs with varying volumetric capacities. Thin panels are initially used to study the kinematics of shelter concepts as traditional origami. With increasing panel thickness, the location of fold or hinge lines exerts a large influence on the …


Unsupervised-Learning Assisted Artificial Neural Network For Optimization, Varun Kote Jul 2019

Unsupervised-Learning Assisted Artificial Neural Network For Optimization, Varun Kote

Mechanical & Aerospace Engineering Theses & Dissertations

Innovations in computer technology made way for Computational Fluid Dynamics (CFD) into engineering, which supported the development of new designs by reducing the cost and time by lowering the dependency on experimentation. There is a further need to make the process of development more efficient. One such technology is Artificial Intelligence. In this thesis, we explore the application of Artificial Intelligence (AI) in CFD and how it can improve the process of development.

AI is used as a buzz word for the mechanism which can learn by itself and make the decision accordingly. Machine learning (ML) is a subset of …


Application And Evaluation Of Full-Field Surrogate Models In Engineering Design Space Exploration, Christopher Murray Thelin Jul 2019

Application And Evaluation Of Full-Field Surrogate Models In Engineering Design Space Exploration, Christopher Murray Thelin

Theses and Dissertations

When designing an engineering part, better decisions are made by exploring the entire space of design variations. This design space exploration (DSE) may be accomplished manually or via optimization. In engineering, evaluating a design during DSE often consists of running expensive simulations, such as finite element analysis (FEA) in order to understand the structural response to design changes. The computational cost of these simulations can make thorough DSE infeasible, and only a relatively small subset of the designs are explored. Surrogate models have been used to make cheap predictions of certain simulation results. Commonly, these models only predict single values …


Gaussian Process Regression Applied To Marine Energy Turbulent Source Tuning Via Metamodel Machine Learning Optimization, Sterling Olson Apr 2019

Gaussian Process Regression Applied To Marine Energy Turbulent Source Tuning Via Metamodel Machine Learning Optimization, Sterling Olson

Mechanical Engineering ETDs

Converting energy from the currents found within tidal channels, open ocean, rivers, and canals is a promising yet untapped source of renewable energy. In order to permit current energy converters for installation in the environment, the CECs must be shown to non-negatively impact the environment. While developing these model increased utility may be gained if researchers may optimize mechanical power while constraining environmental effects. Surrogate models have garnered interest as optimization tools because they maximize the utility of expensive information by building predictive models in place of computational or experimentally expensive model runs. Marine hydrokinetic current energy converters require large-domain …


Characterization And Optimization Of A Propeller Test Stand, Colin Bruce Leighton Benjamin Apr 2019

Characterization And Optimization Of A Propeller Test Stand, Colin Bruce Leighton Benjamin

Mechanical & Aerospace Engineering Theses & Dissertations

In recent history, there has been a rapid rise in the use of drones, and they are expanding in popularity each year. The widespread use and future capabilities of these unmanned aerial vehicles (UAVs) will call for increased study and classification of propellers to maximize their performance. As a result, it is necessary to have continuity in the development, maximization, and optimization of propeller test stand’s capability to collect accurate and precise measurements. It is of significant advantage to have the capability of accurately characterizing a propeller based on its thrust and torque. In this study, a propeller test stand …


Design And Process Of 3d-Printed Parts Using Composite Theory, Jordan Garcia Jan 2019

Design And Process Of 3d-Printed Parts Using Composite Theory, Jordan Garcia

Theses and Dissertations--Mechanical Engineering

3D printing is a revolutionary manufacturing method that allows the productions of engineering parts almost directly from modeling software on a computer. With 3D printing technology, future manufacturing could become vastly efficient. However, it is observed that the procedures used in 3D printing differ substantially among the printers and from those used in conventional manufacturing. In this thesis, the mechanical properties of engineering products fabricated by 3D printing were comprehensively evaluated and then compared with those made by conventional manufacturing. Three open-source 3D printers, i.e., the Flash Forge Dreamer, the Tevo Tornado, and the Prusa, were used to fabricate the …


Optimal Power Flow Control Of Networked Dc Microgrids, Eddy H. Trinklein Jan 2019

Optimal Power Flow Control Of Networked Dc Microgrids, Eddy H. Trinklein

Dissertations, Master's Theses and Master's Reports

The US military is moving toward the electrification of many weapon systems and platforms. Advanced weapon systems such as high energy radar, electro-magnetic kinetic weapons and directed energy pose significant integration challenges due to their pulsed power electrical load profile. Additionally, the weapons platforms, including ships, aircraft, and vehicles can be studied as a mobile microgrids with multiple generation sources, loads, and energy storage. There is also a desire to extend the mission profile and capabilities of these systems. Common goals are to increase fuel efficiency, maintaining system stability, and reduce energy storage size as typically required to enable pulsed …


Optimization And Control Of Arrays Of Wave Energy Converters, Jianyang Lyu Jan 2019

Optimization And Control Of Arrays Of Wave Energy Converters, Jianyang Lyu

Dissertations, Master's Theses and Master's Reports

Wave Energy Converter Array is a practical approach to harvest ocean wave energy. To leverage the potential of the WEC array in terms of energy extraction, it is essential to have a properly designed array configuration and control system. This thesis explores the optimal configuration of Wave Energy Converters (WECs) arrays and their optimal control. The optimization of the WEC array allows both dimensions of individual WECs as well as the array layout to varying. In the first optimization problem, cylindrical buoys are assumed in the array where their radii and drafts are optimization parameters. Genetic Algorithms are used for …


Time-Dependent Reliability Methodologies With Saddlepoint Approximation, Zhangli Hu Jan 2019

Time-Dependent Reliability Methodologies With Saddlepoint Approximation, Zhangli Hu

Doctoral Dissertations

"Engineers always encounter time-dependent uncertainties that ubiquitously exist, such as the random deterioration of material properties and time-variant loads. Therefore the reliability of engineering systems becomes time-dependent. It is crucial to predict the time-dependent reliability in the design stage, given possible catastrophic consequences of a failure. Although extensive research has been conducted on reliability analysis, estimating the reliability accurately and efficiently is still challenging. The objective of this work is to develop accurate and efficient reliability methodologies for engineering design. The basic idea is the integration of traditional reliability methods with saddlepoint approximation (SPA), which can accurately approximate the tail …