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Brigham Young University

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Articles 571 - 600 of 4850

Full-Text Articles in Engineering

Aerostructural Predictions Combining Fenics And A Viscous Vortex Particle Method, Ryan Anderson, Andrew Ning, Ru Xiang, Sebastiaan P. C. Van Schie, Mark Sperry, Darshan Sarojini, David Kamensky, John T. Hwang Jan 2023

Aerostructural Predictions Combining Fenics And A Viscous Vortex Particle Method, Ryan Anderson, Andrew Ning, Ru Xiang, Sebastiaan P. C. Van Schie, Mark Sperry, Darshan Sarojini, David Kamensky, John T. Hwang

Faculty Publications

Electric Vertical Takeoff and Landing (eVTOL) aircraft experience complex, unsteady aerodynamic interactions between rotors, wings, and fuselage that can make design difficult. We introduce a new framework for predicting aerostructural interactions. Specifically, we demonstrate the coupling of a finite element solver with Reissner-Mindlin shell theory for computing deflections and a viscous vortex particle for capturing wakes. We perform convergence studies of the aerodynamics and the coupled aerostructural model. Finally, we share some preliminary results of the dynamic aeroelastic response of Uber’s eCRM-002 main wing, and share some qualitative observations.

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Sparsity For Gradient-Based Optimization Of Wind Farm Layouts, Benjamin T. Varela, Andrew Ning Jan 2023

Sparsity For Gradient-Based Optimization Of Wind Farm Layouts, Benjamin T. Varela, Andrew Ning

Faculty Publications

Optimizing wind farm layouts is an important step in designing an efficient wind farm. Optimizing wind farm layouts is also a difficult task due to computation times increasing with the number of turbines present in the farm. The most computationally expensive part of gradient- based optimization is calculating the gradient. In order to reduce the expense of gradient calculation, we performed a study on the use of sparsity in wind farm layout optimization. This paper presents the findings of the sparsity study and provides a method to use sparsity in wind farm layout optimization. We tested this sparsity method by …

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Surface Modification Of 3d Printed Microfluidic Devices For Controlled Wetting In Two-Phase Flow, Chandler A. Warr, Nicole G. Crawford, Gregory P. Nordin, William G. Pitt Dec 2022

Surface Modification Of 3d Printed Microfluidic Devices For Controlled Wetting In Two-Phase Flow, Chandler A. Warr, Nicole G. Crawford, Gregory P. Nordin, William G. Pitt

Faculty Publications

Microfluidic devices (MFDs) printed in 3-D geometry using digital light projection to polymerize monomers often have surfaces that are not as hydrophobic as MFDs made from polydimethylsiloxane. Droplet microfluidics in these types of devices are subject to droplet adhesion and aqueous spreading on less hydrophobic MFD surfaces. We have developed a post-processing technique using hydrophobic monomers that renders the surfaces of these devices much more hydrophobic. The technique is fast and easy, and involves flowing monomer without initiator into the channels and then exposing the entire device to UV light that generates radicals from the initiator molecules remaining in the …

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Low Noise Front End Signal Transport Design For L-Band Phased Array Receivers, Spencer M. Ammermon Dec 2022

Low Noise Front End Signal Transport Design For L-Band Phased Array Receivers, Spencer M. Ammermon

Theses and Dissertations

RF receiver improvements in size, weight, power, and sensitivity are constant goals in the wireless communications community. The combination of phased array antenna systems with high speed analog to digital converters helps engineers meet these goals, because many of the analog components and tasks found in a traditional receive chain are moved into the digital domain. Although the hard work of signal reception is moved into digital signal processing, digital receivers rely on a high performance analog front end to properly condition a signal before analog to digital conversion. In this thesis, two RF front ends are developed for direct …

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Leveraging Fpga Primitives To Improve Word Reconstruction During Netlist Reverse Engineering, Reilly Mckendrick, Corey Simpson, Brent Nelson, Jeffrey Goeders Dec 2022

Leveraging Fpga Primitives To Improve Word Reconstruction During Netlist Reverse Engineering, Reilly Mckendrick, Corey Simpson, Brent Nelson, Jeffrey Goeders

Faculty Publications

While attempting to perform hardware trojan detection, or other low-level design analyses, it is often necessary to inspect and understand the gate-level netlist of an implemented hardware design. Unfortunately this process is challenging, as at the physical level, the design does not contain any hierarchy, net names, or word groupings. Previous work has shown how gate-level netlists can be analyzed to restore high-level circuit structures, including reconstructing multi-bit signals, which aids a user in understanding the behavior of the design. In this work we explore improvements to the word reconstruction process, specific to FPGA platforms. We demonstrate how hard-block primitives …

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Computational Tools For Modeling And Simulation Of Sooting Turbulent Non-Premixed Flames, Victoria B. Stephens Dec 2022

Computational Tools For Modeling And Simulation Of Sooting Turbulent Non-Premixed Flames, Victoria B. Stephens

Theses and Dissertations

Turbulent combustion systems are physically complex processes that involve many interdependent phenomena---including turbulent fluid dynamics, multi-component mass transfer, convective and radiative heat transfer, and multiphase flow---that occur over a wide range of length and time scales. Modeling and simulation studies complement experimental work by implementing and validating models and providing predictive capabilities, but current software tools are often limited by a lack of standardization and best practices, non-robust implementation, or over-specialization. Some topics in combustion CFD research, notably radiative heat transfer and soot modeling, are critically underrepresented in simulation studies as a result of software limitations. This project establishes and …

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Developing An Accurate Simulation Model For Predicting Friction Stir Welding Processes In 2219 Aluminum Alloy, Kennen Brooks Dec 2022

Developing An Accurate Simulation Model For Predicting Friction Stir Welding Processes In 2219 Aluminum Alloy, Kennen Brooks

Theses and Dissertations

Modeling of friction stir welding (FSW) is challenging, as there are large gradients in both strain rate and temperature that must be accounted for in the constitutive law of the material being joined. Constitutive laws are most often calibrated using flow stresses from hot compression or hot torsion testing, where strain rates are much lower than those of the FSW process. As such, the current work employed a recently developed method to measure flow stresses in AA 2219-T67 at the high strain rates typical of FSW. These data were used in the development of a finite element simulation of FSW …

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Advanced Isogeometric Discretization Techniques, Kyle Dennis Richardson Dec 2022

Advanced Isogeometric Discretization Techniques, Kyle Dennis Richardson

Theses and Dissertations

In this dissertation, I provide a robust, efficient inverse mapping algorithm for use in immersed simulation methods, specifically in the Flex Representation Method. I also explore a structural theory that unifies the theories of solids, shells, beams, and rigid bodies. As part of this, I preform a preliminary exploration of applying the Flex Representation Method to shells. Finally, I explore why higher order elements suffer from small critical time steps in explicit dynamics. I then propose a simple method of remedying this issue by exploiting the properties of U-splines.

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Retention Forces For Drops On Microstructured Superhydrophobic Surfaces, Shaur Humayun, R. Daniel Maynes, Julie Crockett, Brian D. Iverson Dec 2022

Retention Forces For Drops On Microstructured Superhydrophobic Surfaces, Shaur Humayun, R. Daniel Maynes, Julie Crockett, Brian D. Iverson

Faculty Publications

Accurate models of retention forces between drops and superhydrophobic (SH) surfaces are required to predict drop dynamics on the surface. This retention force is, in turn, useful in modeling heat transfer rates for dropwise condensation on a SH surface. Drop contact angle distribution and base area on SH surfaces are essential factors for predicting retention forces. The present work measures the contact angle distribution and base area shapes of various drop sizes over a wide range of solid fraction for inclined microstructured SH surfaces at the point of drop departure. Base area shape was found to be well approximated using …

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Parametric Structural Optimization Of A Wheel Using The Flex Representation Method, Gregory John Vernon Dec 2022

Parametric Structural Optimization Of A Wheel Using The Flex Representation Method, Gregory John Vernon

Theses and Dissertations

The use of the finite element method within an optimization workflow is fraught with challenges that limit the automation of such workflows. These challenges are inherent to the traditional finite element formulations which are heavily dependent on a manual meshing process that introduces variability that is challenging to account for within an automated workflow. The recently developed flex representation method (FRM) provides a salient solution to the manual meshing process without sacrificing solution accuracy. In response to the development of FRM a global automotive company requested a study to explore the applicability of FRM to one of their sizing-optimization problems: …

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Methemoglobin Formation Via Nitric Oxide And Comparison Of Methemoglobin, Deoxyhemoglobin, And Ferrous Nitrosyl Hemoglobin As Potential Mri Contrast Agents, Roya Ayati Dec 2022

Methemoglobin Formation Via Nitric Oxide And Comparison Of Methemoglobin, Deoxyhemoglobin, And Ferrous Nitrosyl Hemoglobin As Potential Mri Contrast Agents, Roya Ayati

Theses and Dissertations

Gadolinium-based contrast agents (GBCAs) are in widespread use to enhance magnetic resonance angiography images for evaluating vascular pathology. However, there are safety concerns and limitations regarding the use of GBCAs. It has been shown that the magnetic resonance imaging (MRI) signal intensity (T1-weighted images) in some of the brain's tissues is higher for patients who had multiple exposures to GBCAs compared to patients who had never had exposure to GBCAs. This implies that GBCAs are not sufficiently removed from body such that GBCAs may potentially have long-term effects on the human body. These potential safety concerns have led to an …

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Evaluating Equitable Access To Nutrition In Utah, Emma Stucki Dec 2022

Evaluating Equitable Access To Nutrition In Utah, Emma Stucki

Theses and Dissertations

One of the more recent topics in transportation policy making and project prioritization in DOT's across the United States is how to improve quality of life. This quality of life focus is an intersection of public health and transportation and has many different branches including traffic safety, pollution, active transportation, equity, and accessibility to resources. The topic among these that seems to receive the least attention is equitable access to resources. However, with the proven impact that equitable access to resources has on physical and emotional well-being, as well as economic opportunity it is important to ensure that all populations, …

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The Flex Representation Method: Versatile Modeling For Isogeometric Analysis, Christopher David Whetten Dec 2022

The Flex Representation Method: Versatile Modeling For Isogeometric Analysis, Christopher David Whetten

Theses and Dissertations

The Flex Representation Method (FRM) leverages unique computational advantages of splines to address limitations in the process of building CAE simulation models from CAD geometric models. Central to the approach is the envelope CAD domain that encapsulates a CAD model. An envelope CAD domain can be of arbitrary topological and geometric complexity. Envelope domains are constructed from spline representations, like U-splines, that are analysis-suitable. The envelope CAD domain can be used to approximate none, some, or all of the features in a CAD model. This yields additional simulation modeling options that simplify the model-building process while leveraging the properties of …

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A Machine Learning Approach For Identification Of Low-Head Dams, Salvador Augusto Vinay Mollinedo Dec 2022

A Machine Learning Approach For Identification Of Low-Head Dams, Salvador Augusto Vinay Mollinedo

Theses and Dissertations

Identifying Low-head dams (LHD) and creating an inventory become a priority as fatalities continue to occur at these structures. Because obstruction inventories do not specifically identify LHDs, and they are not assigned a hazard classification, there is not an official inventory of LHD. However, there is a multi-agency taskforce that is creating an inventory of LHD. All efforts have been performed by manually identifying LHD on Google Earth Pro (GE Pro). The purpose of this paper is to assess whether a machine learning approach can accelerate the national inventory. We used a machine learning approach to implement a high-resolution remote …

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An Augmented Reality Maintenance Assistant With Real-Time Quality Inspection On Handheld Mobile Devices, James Thomas Frandsen Dec 2022

An Augmented Reality Maintenance Assistant With Real-Time Quality Inspection On Handheld Mobile Devices, James Thomas Frandsen

Theses and Dissertations

With the advances of industry 4.0, augmented reality (AR) devices are being deployed across the manufacturing sector to enhance worker perception and efficiency. AR is often used to deliver spatially relevant work instructions on mobile devices for maintenance procedures on the factory floor. In these situations, workers use their mobile devices to view instructions in the form of 3D animations and annotations that directly overlay the equipment being maintained. Workers then follow the AR instructions and must ultimately rely on their own judgement and knowledge of the procedure as they progress from step to step. An AR assistant that could …

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Performance Criteria For Knee-Brace Timber Frames With Mortise And Tenon Joints, Zachary J. Halisky Dec 2022

Performance Criteria For Knee-Brace Timber Frames With Mortise And Tenon Joints, Zachary J. Halisky

Theses and Dissertations

Traditional mortise and tenon timber frames have been used in modern construction for a substantial period of time with acceptable performance against weather phenomena and other hazards. However, performance criteria for this style of timber framing are not well defined in current codes and standards. To determine performance criteria for free-standing timber frames with knee-braces, three tasks were undertaken: (1) Two timber frame specimens were tested under cyclic loads to determine hysteretic behavior, damage states, and to explore rehabilitation of a damaged member using self-tapping screws. Three damage states for were identified: peg shear, tenon tearout, and post or beam …

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Principles For Using Remote Data Collection Devices And Deep Learning In Evaluating Social Impact Indicators Of Engineered Products For Global Development, Bryan J. Stringham Dec 2022

Principles For Using Remote Data Collection Devices And Deep Learning In Evaluating Social Impact Indicators Of Engineered Products For Global Development, Bryan J. Stringham

Theses and Dissertations

Evaluating the social impacts of engineered products, or effects products have on the daily lives of individuals, is critical to ensuring that products are having positive impacts while avoiding negative impacts and to learning how to improve product designs for a more positive social impact. One approach to quantifying a product's social impact is to use social impact indicators that combine user data in a meaningful way to give insight into the current social condition of an individual or population. However, determining social impact indicators relative to engineered products and individuals in developing countries can be difficult when there is …

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Development Of A 3d-Printed Microfluidic Droplet-On-Demand System For The Deterministic Encapsulation And Processing Of Biological Materials, Chandler A. Warr Dec 2022

Development Of A 3d-Printed Microfluidic Droplet-On-Demand System For The Deterministic Encapsulation And Processing Of Biological Materials, Chandler A. Warr

Theses and Dissertations

The growing threat of antimicrobial resistance is among the largest concerns in the world today. One method under development to combat this issue is the encapsulation of microbes in microfluidic droplets for single-cell testing. This method may be able to circumvent the need for a traditional positive cell culture which consumes the majority of the testing time using current diagnostic methods. This dissertation presents a method by which to deterministically encapsulate microbes using an artificial intelligence object detection algorithm and a Droplet-On-Demand microfluidic device. To accomplish this, the Droplet-On-Demand microfluidic device was first developed using a unique 3D-printing manufacturing method. …

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Friction Taper Plug Welding As A Repair Method For Fatigue Damage Around Fastener Holes In Aerospace Structures, David Carl Sumsion Dec 2022

Friction Taper Plug Welding As A Repair Method For Fatigue Damage Around Fastener Holes In Aerospace Structures, David Carl Sumsion

Theses and Dissertations

This work details an adaptation of the friction taper plug welding (FTPW) process to repair fatigue damage in 6.35mm AA 7050 t-7451 plate. Aircraft components experience fatigue damage around fastener holes. This damage can be mitigated by enlarging fastener holes. There is no effective repair procedure once holes reach a maximum allowable size. Damaged components must be replaced. A suitable repair process would lead to substantial savings in both time and money. A simulated repair process was developed by machining holes in 6.35mm AA 7050 t-7451 plate. These hoes were then plugged using the FTPW process. Microhardness testing and metallographic …

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Methods For Engineers To Understand, Predict, And Influence The Social Impacts Of Engineered Products, Phillip Douglas Stevenson Dec 2022

Methods For Engineers To Understand, Predict, And Influence The Social Impacts Of Engineered Products, Phillip Douglas Stevenson

Theses and Dissertations

Engineered products can impact the day-to-day life of their users and other stakeholders. These impacts are often referred to as the product's social impacts. Products have been known to impact the people who use them, design them, manufacture them, distribute them, and the communities where they exist. Currently, there are few methods that can help an engineer identify, quantify, predict, or improve a product's social impact. Some companies and organizations have tried to identify their impacts and, for example, set goals for achieving more sustainable business practices. However, engineers, in large part, do not have methods that can help improve …

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Transforming Gps Points To Daily Activities Using Simultaneously Optimized Dbscan-Te Parameters, Gillian Michele Riches Dec 2022

Transforming Gps Points To Daily Activities Using Simultaneously Optimized Dbscan-Te Parameters, Gillian Michele Riches

Theses and Dissertations

With the recent upsurge in mental health concerns and ongoing isolation regulations brought about by the COVID-19 pandemic, it is important to understand how an individual's daily travel behavior can affect their mental health. Before finding any correlations to mental health, researchers must first have individual travel behavior information: an accurate number of activities and locations of those activities. One way to obtain daily travel behavior information is through the interpretation of cellular Global Positioning System (GPS) data. Previous methods that interpret GPS data into travel behavior information have limitations. Specifically, rule-based algorithms are structured around subjective rule-based tests, clustering …

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Forecasting Ride-Hailing Across Multiple Model Frameworks, Christopher Stephen Day Dec 2022

Forecasting Ride-Hailing Across Multiple Model Frameworks, Christopher Stephen Day

Theses and Dissertations

The advent of on-demand transport modes such as ride-hailing and microtransit has challenged forecasters to develop new methods of forecasting the use and impacts of such modes. In particular, there is some professional disagreement about the relative role of activity-based transportation behavior models -- which have detailed understanding of the person making a trip and its purpose -- and multi-agent demand simulations which may have a better understanding of the availability and service characteristics of on-demand services. A particular question surrounds how the relative strengths of these two approaches might be successfully paired in practice. Using daily plans generated by …

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An Investigation Into The Role Of Geometrically Necessary Dislocations In Multi-Strain Path Deformation In Automotive Sheet Alloys, Rishabh Sharma Dec 2022

An Investigation Into The Role Of Geometrically Necessary Dislocations In Multi-Strain Path Deformation In Automotive Sheet Alloys, Rishabh Sharma

Theses and Dissertations

Multiple strain path changes during forming lead to complex geometrically necessary dislocation (GND) development in strain gradient fields, inducing internal stresses that contribute to the Bauschinger effect, residual stresses, and springback which alters the final geometrical shape of the part. In order to analyze and design improved processing routes, models must capture the evolution of these internal stresses. However, most models capture the effects of these stresses via phenomenological approaches that require calibration to each new material and strain path. The development of models that capture the underlying physics at the sub-grain level is underway but requires in-depth studies of …

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Fault Tolerant Robotics Using Active Diagnosis Of Partially Observable Systems And Optimized Path Planning For Underwater Message Ferrying, Devon M. Webb Dec 2022

Fault Tolerant Robotics Using Active Diagnosis Of Partially Observable Systems And Optimized Path Planning For Underwater Message Ferrying, Devon M. Webb

Theses and Dissertations

Underwater robotic vehicles are used in a variety of environments that would be dangerous for humans. For these vehicles to be successful, they need to be tolerant of a variety of internal and external faults. To be resilient to internal faults, the system must be capable of determining the source of faulty behavior. However many different faults within a robotic vehicle can create identical faulty behavior, which makes the vehicles impossible to diagnose using conventional methods. I propose a novel active diagnosis method for differentiating between faults that would otherwise have identical behavior. I apply this method to a communication …

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Ascat Wind Estimation At 2.5 Km Resolution Supported By Machine Learning Rain Detection, Joshua Benjamin Kjar Dec 2022

Ascat Wind Estimation At 2.5 Km Resolution Supported By Machine Learning Rain Detection, Joshua Benjamin Kjar

Theses and Dissertations

The Advanced Scatterometer (ASCAT) is a C-band scatterometer designed to be less sensitive to rain contamination than other higher frequency scatterometers. However, the radar backscatter is still affected by rain which increases error during wind estimation. The error can be reduced in rainy conditions by combining a rain backscatter model with the existing wind only (WO) backscatter model to perform simultaneous wind and rain (SWR) estimation. I derive and test several 2.5 km resolution rain backscatter models for ASCAT data which are used with the WO model to estimate the near surface winds. Various rain models optimal for different purposes …

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The Applicability Of Joint Source-Channel Coding Systems To Aeronautical Mobile Telemetry Data, Jesse Richmond Dec 2022

The Applicability Of Joint Source-Channel Coding Systems To Aeronautical Mobile Telemetry Data, Jesse Richmond

Theses and Dissertations

Broadcast spectrum restrictions require greater efficiency from wireless transmission systems, particularly in applications where sections of spectrum previously reserved for military purposes have been sold to private interests. A joint source-channel coding system, in tandem with smart data selection techniques, is proposed as a potential solution to this problem. The workings of this joint source-channel coding system are detailed, with particular attention given to the decoding process.

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Building Software Compliant Multidimensional Datasets Through Programmatic Solutions, Jon Enoch Jones Dec 2022

Building Software Compliant Multidimensional Datasets Through Programmatic Solutions, Jon Enoch Jones

Theses and Dissertations

Meteorological and other multidimensional, georeferenced data is used extensively in science and engineering. These datasets are produced, shared, and used by organizations all over the world. Conventions have been developed specifying the metadata and format of these datasets in an effort to standardize the data and make it compatible with current and future software and web services. By necessity, the conventions are complex and difficult to implement correctly, resulting in useful datasets that are unusable in many applications due to lack of compliance with the conventions. By programmatically assigning metadata and guiding the dataset creator through the dataset creation process, …

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Hybrid Machine Learning And Physics-Based Modeling Approaches For Process Control And Optimization, Junho Park Dec 2022

Hybrid Machine Learning And Physics-Based Modeling Approaches For Process Control And Optimization, Junho Park

Theses and Dissertations

Transformer neural networks have made a significant impact on natural language processing. The Transformer network self-attention mechanism effectively addresses the vanishing gradient problem that limits a network learning capability, especially when the time series gets longer or the size of the network gets deeper. This dissertation examines the usage of the Transformer model for time-series forecasting and customizes it for a simultaneous multistep-ahead prediction model in a surrogate model predictive control (MPC) application. The proposed method demonstrates enhanced control performance and computation efficiency compared to the Long-short term memory (LSTM)-based MPC and one-step-ahead prediction model structures for both LSTM and …

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Modeling Of High-Pressure Entrained-Flow Char Oxidation, Daniel Gundersen Nov 2022

Modeling Of High-Pressure Entrained-Flow Char Oxidation, Daniel Gundersen

Theses and Dissertations

Coal plays a significant role in electricity production worldwide and will into the foreseeable future. Technologies that improve efficiency and lower emissions are becoming more popular. High pressure reactors and oxyfuel combustion can offer these benefits. Designing new reactors effectively requires accurate single particle modeling. This work models a high-pressure, high-temperature, high-heating rate, entrained-flow, char oxidation data set to generate kinetic parameters. Different modeling methods were explored and a sensitivity analysis on char burnout was performed by varying parameters such as total pressure, O2 partial pressure, O2 and CO2 mole fractions, gas temperature, diameter, and pre-exponential factor. Pressure effects on …

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Machine Learning With Gradient-Based Optimization Of Nuclear Waste Vitrification With Uncertainties And Constraints, Lagrande Gunnell, Kyle Manwaring, Xiaonan Lu, Jacob Reynolds, John Vienna, John Hedengren Nov 2022

Machine Learning With Gradient-Based Optimization Of Nuclear Waste Vitrification With Uncertainties And Constraints, Lagrande Gunnell, Kyle Manwaring, Xiaonan Lu, Jacob Reynolds, John Vienna, John Hedengren

Faculty Publications

Gekko is an optimization suite in Python that solves optimization problems involving mixed-integer, nonlinear, and differential equations. The purpose of this study is to integrate common Machine Learning (ML) algorithms such as Gaussian Process Regression (GPR), support vector regression (SVR), and artificial neural network (ANN) models into Gekko to solve data based optimization problems. Uncertainty quantification (UQ) is used alongside ML for better decision making. These methods include ensemble methods, model-specific methods, conformal predictions, and the delta method. An optimization problem involving nuclear waste vitrification is presented to demonstrate the benefit of ML in this field. ML models are compared …

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