Engineering Commons^™

Hybrid Physics-Infused Machine Learning Framework For Fault Diagnostics And Prognostics In Cyber-Physical System Of Diesel Engine, Shubhendu Kumar Singh

All Dissertations

Fault diagnosis is required to ensure the safe operation of various equipment and enables real-time monitoring of associated components. As a result, the demand for new cognitive fault diagnosis algorithms is the need of the hour. Existing deep learning algorithms can detect, classify, and isolate faults. Still, most depend solely on data availability and do not incorporate the system's underlying physics into their prediction. Therefore, the results generated by these fault-detecting algorithms sometimes need to make more sense and deliver when tested in actual operating conditions.

Similar to diagnosis, the fault prognosis of diesel engines is paramount in numerous industries. …

Investigation Of Transport Phenomena In High-Performance Pem Water Electrolyzers, Anirban Roy

Doctoral Dissertations

The increasing demand for renewable energy sources to replace fossil fuels, requires a growing need for a steady energy supply from source to power distribution. Renewable energy often relies on intermittent natural sources or is geographically bound, necessitating energy storage solutions. Polymer Electrolyte Water Electrolyzers (PEWEs) offer a promising solution but require performance enhancements for economic viability. This study focuses on applying distributed diagnostic techniques for PEWEs to gain insights into improving their performance.

The research aims to investigate transport phenomena in high-performance PEWEs, utilizing a segmented cell approach to probe different aspects of transport within a single cell. This …

Feasibility And Uncertainty Evaluation Of Sequential Hybrid Manufacturing Using Optical Coordinate Metrology, Jake Dvorak

Doctoral Dissertations

Hybrid manufacturing has been suggested as a solution to global manufacturing challenges including stock availability, manufacturing costs, and difficulty in production of complex parts. However, feasibility and validation of hybrid manufacturing remain open research opportunities.

This research evaluates measurement uncertainty for optical coordinate metrology (OCM) within a sequential hybrid manufacturing (SHM) framework where a primary manufacturing process, a part geometry measurement, and a secondary manufacturing process are performed sequentially on optionally separate machine tools. In this work, an additively manufactured preform is produced, the part geometry is measured using structured light optical coordinate metrology, and the final geometry is obtained …

Reactive Processing Of Hf-Nb-Ti-Ta Melts Into A B4c/C Packed Bed, Laura Leticia Sandoval

Open Access Theses & Dissertations

The reactivity of liquid Hf-Nb-Ti-Ta alloy in B4C/C packed bed to form boride-carbide precipitates for ultra-high temperature ceramics was investigated at 2800 K. The objectives were to predict the thermodynamic phases formed and verify them with microstructural characterization. A pseudo-isopiestic technique was used to significantly lower the oxygen potential as the liquid Hf alloy infused and reacted into a B4C packed bed within a graphite enclosure. The technique had a low temperature region (at 1300 K) to control the oxygen potential with a Y-Al/Y2O3-Al2O3/carbide mixture as a liquid Hf alloy at 2800 K and reacted with B4C/C. In addition, any …

Fused Filament Fabrication Of Ceramic Matrix Composite Preforms Via Thermo-Oxidative Stabilization Of Polyetheretherketone, Samuel Pankratz

Masters Theses

Carbon-fiber-reinforced ceramic matrix composites (CMCs) are frequently used in applications where high thermo-mechanical loads are induced along with weight limitations. The first step of producing the fibrous preform allows the near-net shape of the final part to be formed with fibers placed in the desired orientation, typically relying on traditional polymer matrix composite (PMC) manufacturing methods. Recent work has demonstrated a new method to produce discontinuous fiber preforms through various forms of additive manufacturing including fused filament fabrication (FFF). This work uses Polyetheretherketone with carbon fibers (CF PEEK) for additive manufacturing of the carbon-rich polymer precursor. Critically, thermoplastic precursor materials …

Low-Cost Image Collection And Compilation For Enhanced In-Situ Monitoring In Laser-Powder Bed Fusion, Brett Eugene Brady

Masters Theses

Laser-Powder Bed Fusion (L-PBF) additive manufacturing relies on precise control for quality assurance and reproducibility, necessitating advanced in-situ monitoring techniques. Presented is a novel low-cost approach to image collection and compilation to enable in-situ monitoring in L-PBF in ways not performed to date, i.e., at a lower cost. The research incorporates optical, near-infrared (NIR), and infrared (IR) imaging modalities to record and, in the future, analyze and detect defects during the L-PBF process. Off-axis cameras with different spectral sensitivities complicates the comparison of images due to differing image planes. A low-cost, calibration plate is used to create common image planes …

Machine Learning For Stability Analysis Of Milling Process, Katy Daniels

Masters Theses

The properties related to chatter and the stability of manufacturing milling machines are dependent primarily on parameters such as axial depth of cut, rotary speed rpm, and cutting force. These parameters are used to calculate the milling process and avoid certain cuts that would result in unstable milling. Using applied data science tools for statistical analysis and machine learning models like SHapley Additive exPlanations (SHAP), this research will produce valuable insight into two stability testing methods used in milling machining operations. By leveraging the data, a partitioning model can be used with known stable and unstable points under certain conditions …

2d Temperature Map Acquisition Using Hyperspectral Imaging System (Hsis), Anthony Kim

Masters Theses

Imaging techniques are close to our lives and are used for various applications. In the engineering field, one of the dominant techniques is hyperspectral imaging. It is a necessary tool that combines spectroscopy and digital photography and provides additional information on what is imaged by the imaging system. Hyperspectral imaging has been applied to various fields including remote sensing, cultural relic conservation, food microbiology, forensic science, biomedicine, etc.

In particular, work was done to apply hyperspectral imaging to measure the temperature and emissivity of an object. Due to its ability to measure temperature and emissivity without being in contact with …

Utilizing Bayesian Optimization In Technoeconomic Analyses For Integrated Energy Systems, Anthoney Griffith

All Graduate Theses and Dissertations, Fall 2023 to Present

Technoeconomic analysis is a key element in the study of integrated energy systems. The goal of this analysis is the sizing of technologies resulting in the best economic outcome for the system. The evaluation of this system involves sizing the components and simulating the resulting market to determine an outcome. This simulation incorporates multiple possible values of uncertain parameters like grid price and wind generation. This problem is currently approached with the gradient descent optimization method. An alternative approach, Bayesian optimization, sees success on simple problems of a similar nature to technoeconomic analyses. These results motivate applying Bayesian optimization as …

Development Of A High-Throughput Methodology For Vibration-Based Fatigue Tests, Brandon Alexander Furman

All Graduate Theses and Dissertations, Fall 2023 to Present

Global efforts towards the development of additively manufactured materials, biomaterials, metamaterials, self-healing materials, and composites have reached a staggering pace. With new materials being developed on a near-daily basis, it is more important than ever to be able to quickly and precisely quantify their mechanical performance. However, one of the most important mechanical properties, fatigue life, is notoriously time consuming to measure. Consequently, fatigue parameters are often calculated based on small sample sizes, resulting in high uncertainty of the measured parameters. In this dissertation a high-throughput approach to fatigue measurements is developed. This technique allows for multiple samples to accumulate …

Developing An Assessment Tool For Ideation Effectiveness: A Survey-Based Approach For The Shah’S Method Of Design Space Exploration, Venkat Jaya Deep Jakka

All Theses

The research is focused on creativity in engineering design. The goal is to understand if creativity in engineering design can be assessed using a less resource-intensive approach, specifically a survey, compared to design exercises. The survey builds on the metrics established by Shah and colleagues. The four metrics are Novelty, Quality, Variety and Quantity. The metrics are measured with the help of a design activity that is deployed to the participants. These metrics have been used in comparative analysis to assess treatments such as new design methods and personality types. However, the downside of the metrics is that they require …

Deep-Learning Assisted Short-Wave Infrared Hyperspectral Imaging For Microplastic Classification, Melisa Nyakuchena

Theses and Dissertations

Microplastics are small plastics with a size between a few microns and about 5mm. Due to their small size, microplastics can be ingested by living organisms including humans, which has become a global concern and a heated area of research. Various methods have been proposed to detect and characterize microplastics. In this study, we demonstrate a hyperspectral transmission imaging system operating in the short-wave range of 1100 nm–1650nm. The developed system incorporates Fourier-transform spectroscopy (FTS) to acquire a hyperspectral data cube at high spectral resolution and signal-to-noise ratio. Using the developed system, we characterize six types of microplastic powders of …

Disproportionation Of Polysulfides Facilitated By A Bi-Functional Carbon Host In Li-S Batteries, Dantong Qiu

Theses and Dissertations

Lithium-sulfur (Li-S) batteries are regarded as one of the promising alternatives to conventional lithium-ion batteries (LIBs) due to their high theoretical energy density (2600 Wh kg-1), abundant resources on Earth, and low cost of sulfur. Nevertheless, several significant challenges persist in the practical application of Li-S batteries, including the insulating nature of sulfur, volume changes of cathodes, and, most critically, the shuttle effect of dissolved long-chain lithium polysulfide (PS) species during cycling. In this thesis, a novel carbon host for sulfur cathode, derived from natural silk and denoted as NC, was developed. This carbon host possesses excellent cycling performance because …

Process-Property-Structure Relationships In Advanced Rare Earth Magnet Manufacturing: Towards Enhanced Performance And Developing Application, Kaustubh Vidyadhar Mungale

Doctoral Dissertations

This research aims to study advanced rare earth magnet manufacturing, focusing on the structure-process-property relationships that govern their performance and applications. Rare earth minerals are classified as critical materials because they are essential in manufacturing products across numerous cutting-edge technologies including electric vehicles, renewable energy systems, and high-performance electronics.

Bonded magnets are composites with permanent magnet powder embedded in a polymer matrix. Finely powdered (3-300 microns) rare earth based intermetallics such as neodymium iron boron (NdFeB) and samarium iron nitride (SmFeN) are blended with engineering polymers such as epoxy, polyamides (PA6/PA12) and polyphenylene sulfide (PPS), followed by molding the compound …

Cruising Towards Durability: Investigating Degradation In Polymer Electrolyte Fuel Cells (Pefcs) For Sustainable Vehicle Power, Preetam Sharma

Doctoral Dissertations

Energy production is central to the climate challenge, as a significant portion of greenhouse gases responsible for trapping heat in the Earth's atmosphere arises from burning fossil fuels to generate electricity and heat. To mitigate the adverse effects of climate change, emissions must be reduced by almost half by 2030 and achieve net-zero emissions by 2050. Polymer electrolyte fuel cells (PEFCs) offer numerous advantages compared to traditional internal combustion engines in vehicles. Fuel cell electric vehicles are known for their exceptional operating efficiency (over 60%), impressive driving range (more than 400 miles), and quick refueling times (under 5 minutes).

Automotive …

Understanding The Microstructure And Tribological Performance Of Cocrfeni-Based High Entropy Alloys, Ali Azarmi

All Theses

Due to their higher wear resistance compared to conventional alloys, high entropy alloys (HEAs) are now being considered as candidates for parts undergoing sliding contact during their lifetimes. While the engineering field has built some knowledge related to the performance of selected high entropy alloys, such as the CoCrFeNi alloy, more research is needed to determine if (how) expansions from four to five principal alloying elements alter the performance compared to the initial alloy. In this study, we started this research effort by investigating the relative performance of CoCrFeNiMn and CoCrFeNiTi with respect to CoCrFeNi. The two primary alloying elements …

Linear And Nonlinear Topology Optimization With Morphing Beam Networks, Andrew S. Montalbano

All Dissertations

Topology optimization (TO) is an engineering design discipline dedicated to optimizing material distribution within a given domain. In traditional gradient-based topology optimization, the solid domain is discretized into small volumetric elements. Using finite element analysis (FEA) of the structure, the gradient of the objective function with respect to the design variables (the pseudo densities) is computed, and these design variables are updated iteratively until convergence is achieved. Although gradient-based TO methods are well-established, sensitivity analyses of objective functions and constraints can be both mathematically complex and computationally intensive. The nonconvex nature of most TO problems often complicates efficient convergence. Furthermore, …

Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator, Joseph Raphel Moyalan

All Dissertations

This thesis is concerned with the data-driven solution to the optimal control problem with safety constraints for a class of control-affine nonlinear systems. Designing optimal control satisfying safety constraints is a problem of interest in various applications, including robotics, power systems, transportation networks, and manufacturing. This problem is known to be non-convex. One of this thesis's main contributions is providing a convex formulation to this non-convex problem. The second main contribution is providing a data-driven framework for solving the control problem with safety constraints. The linear operator theoretic framework involving Perron-Frobenius and Koopman operators provides the convex formulation and associated …

Predicting The Ductility Of Tungsten Based Bcc Refractory High Entropy Alloys: A Computational Science Driven Study, Akshay Korpe

All Theses

Bcc refractory high entropy alloys (HEAs) are a relatively new category of metallic alloys that promise excellent irradiation resistance and strength retention at high temperatures but exhibit brittle behavior at room temperatures limiting their formability. Understanding the deformation mechanisms and predicting their ductility at room temperature is a topic of interest in contemporary research.

In this work, multiple independent ductility criteria for quantifying the ductility of these HEAs were studied, calculated and compared using Density Functional Theory (DFT) calculations and continuum mechanics frameworks. These ductility parameters were calculated for various W-Ta-Cr-V alloys and the trends were analyzed for each criteria …

Dynamic Modeling Of A Nuclear Integrated Energy System With Thermal Energy Storage And Hydrogen Production, Seth J. Dana

All Graduate Theses and Dissertations, Fall 2023 to Present

Historically, nuclear reactors have used water for cooling and moderating the nuclear reaction within the core. Advanced generation IV nuclear reactors currently under development are designed with different coolants which enable operation at higher temperatures. A higher operating temperature makes nuclear power suitable for co-located hydrogen production via high temperature electrolysis. Natrium, an advanced reactor design by TerraPower and GE Hitachi, combines a sodium fast reactor with molten salt thermal energy storage. The work presented in this thesis models and analyzes three Natrium systems which integrate hydrogen production with the Natrium nuclear power plant. The first two configurations focus on …

The Role Of Sensing Modalities In Shaping Collective Motion And Group Behavior, Poorendra P. Ramlall

Doctoral Dissertations and Master's Theses

Collective behavior refers to the coordinated movements that emerge from simple interactions between individuals within a group. Traditionally, researchers have modeled these interactions assuming individuals can sense their surroundings in all directions, like having eyes all around their heads. While this is a useful simplification, it does not capture the diverse ways animals actually sense the world. In this thesis, we take inspiration from the natural world, particularly from animals like bats and dolphins that use a combination of hearing and sight to navigate their environments. We explore how combining these sensory cues in a three-dimensional space affects the way …

Improving Biomimetic Passive Dynamics Of A Quadruped Robot Hind Leg Hip Joint With A 3d Printed Torsion Spring, Haonan Zheng

Dissertations and Theses

The Agile and Adaptive Robotics Lab is interested in researching the neuromuscular control network of legged animal locomotion. To validate the lab's understanding of biological neural control, synthetic neural networks are developed and applied to biologically inspired legged robots. For a synthetic neural network to operate in the same manner as a biological neural network and produce the same locomotor behavior, the robot that the synthetic neural network is controlling must also mimic its biological counterpart. Previous research produced a quadruped robot hind leg designed with biomimetic passive dynamics by installing spring and damper pairs at each joint, however, an …

Simulation Of Delta Winglets To Improve Heat Transfer In Solar Air Heaters, Mehrnaz Mehdizadeh Farsangi

Major Papers

Solar air heaters (SAHs) offer a sustainable energy solution, but their efficiency in using solar radiation to heat air can be further optimized. Delta winglet vortex generators (WVG) have proven effective in enhancing heat transfer from the SAH absorber plate to the air passing through the SAH, yet a comprehensive understanding of how different WVG arrangements impact both heat transfer and pressure drop is lacking. This research investigates pairs of WVGs in a common flow-up arrangement at various attack angles and Reynolds numbers (Re), aiming to bridge this knowledge gap and guide the improvement of SAH design.

Numerical …

Formula Integrated Monocoque Development, Hayden Wagner, Aaron Fang, Elijah Schulz, Carson Smith

Mechanical Engineering

Every year the Cal Poly Racing FSAE club set out to create two separate race cars to compete in the upcoming formula combustion and formula electric competitions. Both the combustion and electric formula cars operated on the same vehicle platform with the powertrain systems being the main difference between the two cars. Cal Poly Racing FSAE is the only school in California to run a full carbon fiber monocoque chassis, with each chassis design operating on a roughly four year design cycle. A new FSAE senior project team has set out to improve upon the previous chassis design as the …

Investigation Of Emissions Characteristics Of Natural Gas Engines With Prechamber Enabled Mixing Controlled Combustion, Johnathan Michael Ronsman

Master's Theses (2009 -)

Increasingly stringent emissions regulations have motivated the exploration of ways to decarbonize the internal combustion engine (ICE). Alternative fuels are of interest as they can easily be implemented with existing infrastructure. Among these alternative fuels, natural gas stands out due to its large abundance and high hydrogen-to-carbon ratio, which can significantly reduce CO2 emissions. Due to its low reactivity, most natural gas engines today are premixed lean burn spark ignited (SI) engines. These engines produce criteria pollutants, such as nitrogen oxides (NOx) and carbon monoxide (CO), but due to their premixed nature, also produce relatively large amounts of unburned methane …

Design And Verification Of A Planar, Programmable, Compliant Hand For Use In General Open-Loop Constrained Manipulation, Jacob Frye

Master's Theses (2009 -)

Conventional robots are adept at performing tasks where the desired absolute position of the robot's end effector is well defined. However, these robots will struggle with tasks in which the desired position is poorly defined, subject to variation, or determined by contact with a constraint with positional uncertainty. This problem can be solved by introducing compliance to the system, either active or passive. Active compliance uses force feedback to make corrective motions, but is limited in speed and experiences higher contact forces than passive systems. Passively compliant systems are capable of realizing the necessary compliance for a given task but …

Studying The Performance Of Object Recognition With Fusion Of Visible Light And Infrared Images With Neural Networks, Plamen Petkov

Doctoral Dissertations and Master's Theses

Neural networks have been used for object detection and recognition in both color and intensity camera images. As the use of infrared cameras, colloquially termed thermal cameras, has increased and costs have decreased, object detection and recognition in infrared camera images have been increasingly studied. An infrared image is treated as an intensity image, just like a grayscale camera image, except the intensity corresponds to infrared radiation instead of visible light. The information provided by these two types of images are different, especially in different lighting and environmental situations, and some types of objects are more easily recognized in visible …

Study Of Polymer-On-Polymer Cold Spray Deposition Windows Under Apparently Similar Conditions, Ülar Tiitma

Theses and Dissertations

The purpose of this thesis is to explore and expand the capabilities of polymer-on-polymer cold spray demonstrated herein using polyamide 6 (PA6)-based powder and substrates. Experiments were conducted using three different cold spray systems described in this work, permitting more in-depth examination of process response to different cold spray process control parameters, such as nominal system pressure and temperature. Two specific responses of interest were the deposition window (DW) and deposition efficiency (DE) of PA6. The DW was determined by performing several sprays at different calculated particle impact velocities and temperatures. The composite result from these experiments was identification of …

Design And Characterization Of 3d-Printed Hydrogel Lattices With Consistent Structural And Mechanical Anisotropy, Daniel Yoon

McKelvey School of Engineering Theses & Dissertations

This thesis explores the use of 3D printing to fabricate soft hydrogel lattice structures with consistent properties, including varying levels of mechanical anisotropy. Magnetic resonance elastography (MRE) is a non-invasive imaging tool to estimate and characterize the mechanical properties of tissue. MRE “phantoms” (physical surrogate models) have been used to assess how well MRE can measure and estimate mechanical properties. While gel phantoms generally simulate brain tissue, almost all have been isotropic. Prior studies have shown that white matter brain tissue is structurally and mechanically anisotropic. To validate anisotropic MRE, phantoms with controllable, reproducible anisotropic material properties are needed. This …

Capstone Review: Filament Unit Multiplexing Engine, Gal Cohen

University Honors Theses

The Filament Unit Multiplexing Engine (FUME) is a Mechanical Engineering capstone project sponsored by Portland State University's Electronic Prototyping Lab (EPL). The project addresses the need for an automated system to manage 3D printing operations. The current manual process of selecting and routing a spool of filament to one of the available 3D printers is labor-intensive and limits the efficiency of the lab's 3D printing farm. FUME aims to create a custom solution tailored for a multi-user, multi-spool, and multi-printer environment. The designed system includes key components: a spool holder, an engine, a track and shuttle system, and a funnel. …