Computational Engineering Commons^™

Microgravity-Induced Alterations In Left Atrial Hemodynamics And Thrombogenic Risk: Insights From Healthy And Atrial Fibrillation Models, Grace M. Hoeppner

Dissertations, Master's Theses and Master's Reports

Background: Microgravity exposure alters cardiovascular loading, yet its impact on left atrial flow dynamics and thrombotic risk remains poorly understood. This study investigates how spaceflight-relevant microgravity-induced changes in cardiac outflow affect left atrial hemodynamics in healthy individuals and patients with atrial fibrillation.

Methods: Patient-specific left atrial models were generated for three healthy individuals and three AF patients. Computational fluid dynamics (CFD) simulations were performed using each patient’s baseline mitral outflow waveform and two modified waveforms representing short- and long-duration post-flight cardiac loading changes derived from echocardiographic observations. Hemodynamic metrics included left atrial velocity, time averaged wall shear stress, oscillatory shear …

Computational And Ai Frameworks For Identifying Key Regulatory Genes And Their Target Genes In Plants And Humans, Md Khairul Islam

Dissertations, Master's Theses and Master's Reports

This dissertation presents computational and AI-driven frameworks for identifying key regulatory genes and their downstream targets across plant and human biological systems. Three studies address distinct challenges in genomic regulation using advanced machine learning and bioinformatics approaches.

The first study introduces DyGAF (Dynamic Gene Attention Focus), a dual-attention transformer framework that identifies and ranks disease-relevant biomarker genes by simultaneously modeling independent molecular responses and interdependent regulatory network behavior. Two attention models provide complementary perspectives on gene importance and are fused through a novel combination metric. Applied to COVID-19 nasopharyngeal swab profiles, the attention-weighted representations achieved 94.23% classification accuracy, high sensitivity, …

Application Of Fusion Based Deep Learning Models To Improve Millimeter Wave Beamforming, Abishek Subramanian

Dissertations, Master's Theses and Master's Reports

This study addresses the challenge of selecting millimeter Wave (mmWave) beamforming pairs for vehicle-to-infrastructure (V2I) communication, to mitigate latency in highly dynamic vehicular environments. We investigate the use of out-of-band sensor data as side information to model mmWave ray tracing paths and predicting a subset of top-K optimal beamforming pairs for efficient and low-latency searches. Unimodal-Fusion Deep Learning (F-DL) networks was applied to enhance mmWave beamforming process. We started by first investigating the centralized architecture, and then explored a novel distributed architecture through federated learning to minimize resource and latency overheads. The distributed architecture incorporates two biased client selection strategies: …

The Integration Of Neuromorphic Computing In Autonomous Robotic Systems, Md Abu Bakr Siddique

Dissertations, Master's Theses and Master's Reports

Deep Neural Networks (DNNs) have come a long way in many cognitive tasks by training on large, labeled datasets. However, this method has problems in places with limited data and energy, like when planetary robots are used or when edge computing is used [1]. In contrast to this data-heavy approach, animals demonstrate an innate ability to learn by communicating with their environment and forming associative memories among events and entities, a process known as associative learning [2-4]. For instance, rats in a T-maze learn to associate different stimuli with outcomes through exploration without needing labeled data [5]. This learning paradigm …

Remote Sensing Approach For Terramechanics Applications Utilizing Machine And Deep Learning, Jordan J. Ewing

Dissertations, Master's Theses and Master's Reports

Terrain traversability is critical for developing Go/No Go maps, significantly impacting a mission's success. To predict the mobility of a vehicle over a terrain, one must understand the soil characteristics. In situ measurements performed by soldiers in the field are the current method of collecting this information, which is time-consuming, are only point measurements, and can put soldiers in harm's way. Therefore, this study investigates using remote sensing as an alternative approach to characterize terrain properties.

This approach will explore the relationships between electromagnetic radiation and soil types with varying properties. Optical, thermal, and hyperspectral sensors will be used to …

Neuromorphic Computing Applications In Robotics, Noah Zins

Dissertations, Master's Theses and Master's Reports

Deep learning achieves remarkable success through training using massively labeled datasets. However, the high demands on the datasets impede the feasibility of deep learning in edge computing scenarios and suffer from the data scarcity issue. Rather than relying on labeled data, animals learn by interacting with their surroundings and memorizing the relationships between events and objects. This learning paradigm is referred to as associative learning. The successful implementation of associative learning imitates self-learning schemes analogous to animals which resolve the challenges of deep learning. Current state-of-the-art implementations of associative memory are limited to simulations with small-scale and offline paradigms. Thus, …

Capturing Microstructural Heterogeneity And Predicting Local Transport Phenomena In Pemfc Catalyst Layers: A Comprehensive Network Modeling Approach, Shahriar Alam

Dissertations, Master's Theses and Master's Reports

A unique network architecture that captures the microstructural heterogeneity and predicts the local transport properties of PEMFC catalyst layers is proposed. Separate networks containing numerous cylindrical elements and nodes are generated that represent the solid and pore phase of the catalyst layer. Transport resistances are assigned to the elements while the nodes are volumeless. The networks are interlinked through nodes where local properties are stored. The generated computational grid's macroscopic behaviors (percolation behavior, gas diffusivity, and ion conductivity) will be matched against the experimental data for validation. Diffusion-like transport equations are applied to the networks that provide local water balance, …

Molecular Dynamics Modeling Of Polymers For Aerospace Composites, Swapnil Sambhaji Bamane

Dissertations, Master's Theses and Master's Reports

Polymer matrix composite materials are widely used as structural materials in aerospace and aeronautical vehicles. Resin/reinforcement wetting and the effect of polymerization on the thermo-mechanical properties of the resin are key parameters in the manufacturing of aerospace composite materials. Determining the contact angle between combinations of liquid resin and reinforcement surfaces is a common method for quantifying wettability. It is challenging to determine contact angle values experimentally of high-performance resins on CNT materials such as CNT, graphene, bundles or yarns, and BNNT surfaces. It is also experimentally difficult to determine the effect of polymerization reaction on material properties of a …

Semantic Segmentation To Extract Coronary Arteries In Invasive Coronary Angiograms, Chen Zhao, Robert Bober, Haipeng Ang, Jinshan Tang, Minghao Dong, Chaoyang Zhang, Zhuo He, Weihua Zhou, Et. Al.

Michigan Tech Publications, Part 1

Accurate semantic segmentation of each coronary artery using invasive coronary angiography (ICA) is important for stenosis assessment and coronary artery disease (CAD) diagnosis. In this paper, we propose a multi-step semantic segmentation algorithm based on analyzing arterial segments extracted from ICAs. The proposed algorithm firstly extracts the entire arterial binary mask (binary vascular tree) using a deep learning-based method. Then we extract the centerline of the binary vascular tree and separate it into different arterial segments. Finally, by extracting the underlying arterial topology, position, and pixel features, we construct a powerful coronary artery segment classifier based on a support vector …

Novel Methods In Computational Imaging With Applications In Remote Sensing, Adam Webb

Dissertations, Master's Theses and Master's Reports

This dissertation is devoted to novel computational imaging methods with applications in remote sensing. Computational imaging methods are applied to three distinct applications including imaging and detection of buried explosive hazards utilizing array radar, high resolution imaging of satellites in geosynchronous orbit utilizing optical hypertelescope arrays, and characterization of atmospheric turbulence through multi-frame blind deconvolution utilizing conventional optical digital sensors.

The first application considered utilizes a radar array employed as a forward looking ground penetrating radar system with applications in explosive hazard detection. A penalized least squares technique with sparsity-inducing regularization is applied to produce imagery, which is consistent with …

Life Cycle Information Models With Parameter Uncertainty Analysis To Facilitate The Use Of Life-Cycle Assessment Outcomes In Pavement Design Decision-Making, Chaitanya Ganesh Bhat

Dissertations, Master's Theses and Master's Reports

The objective of this dissertation is to develop Life Cycle Information Models (LCIMs) to promote consistent and credible communication of potential environmental impacts quantified through Life-Cycle Assessment (LCA) methodology. The introduction of Life Cycle Information Models (LCIMs) will shift the focus of pavement LCA stakeholders to collect reliable foreground data and adapt to consistent background data present within LCIMs. LCA methodology requires significant Life Cycle Inventory (LCI) data to model real world systems and quantify potential environmental impacts. The lack of guidance in ISO standards on consistently compiling LCI data and defining protocols for modeling lowers the reliability of LCA …

Multiscale Modeling Of Carbon Fibers/Graphene Nanoplatelets/Epoxy Hybrid Composites For Aerospace Applications, Hashim Al Mahmud

Dissertations, Master's Theses and Master's Reports

Significant research effort has been dedicated for decades to improve the mechanical properties of aerospace polymer-based composite materials. Lightweight epoxy-based composite materials have increasingly replaced the comparatively heavy and expensive metal alloys used in aeronautical and aerospace structural components. In particular, carbon fibers (CF)/graphene nanoplatelets (GNP)/epoxy hybrid composites can be used for this purpose owing to their high specific stiffness and strength. Therefore, this work has been completed to design, predict, and optimize the effective mechanical properties of CF/GNP/epoxy composite materials at different length scales using a multiscale modeling approach. The work-flow of modeling involves a first step of using …

Heterogeneous Uncertainty Quantification For Reliability-Based Design Optimization, Mingyang Li

Dissertations, Master's Theses and Master's Reports

Uncertainty is inherent to real-world engineering systems, and reliability analysis aims at quantitatively measuring the probability that engineering systems successfully perform the intended functionalities under various sources of uncertainties. In this dissertation, heterogeneous uncertainties including input variation, data uncertainty, simulation model uncertainty, and time-dependent uncertainty have been taken into account in reliability analysis and reliability-based design optimization (RBDO). The input variation inherently exists in practical engineering system and can be characterized by statistical modeling methods. Data uncertainty occurs when surrogate models are constructed to replace the simulations or experiments based on a set of training data, while simulation model uncertainty …

Experimental And Numerical Simulation Of Split Hopkinson Pressure Bar Test On Borosilicate Glass, Mayank K. Bagaria

Dissertations, Master's Theses and Master's Reports

This study is an extension to the design of ceramic materials component exposed to bullet impact. Owing to the brittle nature of ceramics upon bullet impact, shattered pieces behave as pellets flying with different velocities and directions, damaging surrounding components. Testing to study the behavior of ceramics under ballistic impact can be cumbersome and expensive. Modeling the set-up through Finite Element Analysis (FEA) makes it economical and easy to optimize. However, appropriately incorporating the material in modeling makes laboratory testing essential. Previous efforts have concentrated on simulating crack pattern developed during 0.22 caliber pellet impact on Borosilicate glass. A major …

Integrated Computational Materials Engineering (Icme) Investigation Of Electrical Conductivity And Thermodynamic Stability For Precipitation Strengthened Al-Zn-Zr And Al-Zn-Ni Ternary Alloys, Oladeji Fadayomi

Dissertations, Master's Theses and Master's Reports

High electrical conductivity Al-Zn-TM (TM=Transition metals) alloys with improved mechanical properties and thermal resistance are developed with an integrated computational material engineering (ICME) strategy. From a series of ab initio density functional theory (DFT) simulations assessing combinations of ternary alloys, Al-Zn-Ni and Al-Zn-Zr are determined as alloys with relatively high electrical conductivity compared to several other ternary Al alloy combinations. The zero-temperature stable structure of precipitates formed in these alloys are determined from computed enthalpy of formation as L1₂, with particular focus of examining the influence of Zn on stabilizing the desired L1₂ precipitate phase.

Scanning transmission …

Discontinuous Galerkin Methods For Convection-Diffusion Equations And Applications In Petroleum Engineering, Nattaporn Chuenjarern

Dissertations, Master's Theses and Master's Reports

This dissertation contains research in discontinuous Galerkin (DG) methods applying to convection-diffusion equations. It contains both theoretical analysis and applications. Initially, we develop a conservative local discontinuous Galerkin (LDG) method for the coupled system of compressible miscible displacement problem in two space dimensions. The main difficulty is how to deal with the discontinuity of approximations of velocity, u, in the convection term across the cell interfaces. To overcome the problems, we apply the idea of LDG with IMEX time marching using the diffusion term to control the convection term. Optimal error estimates in L^infinity(0, T; L^{2 …}

Pressure Measurements Inside Multiple Cavities Of A Torque Converter And Cfd Correlation, Edward De Jesus Rivera

Dissertations, Master's Theses and Master's Reports

A torque converter was instrumented with 29 pressure transducers. The pressure transducers were located in multiple cavities. The instrumented cavities included, four transducers mounted on the impeller shell, on the channel between blades. Six transducers mounted on the pressure and suction sides on the middle streamline of a turbine blade. Another seven transducers mounted on the pressure and suction sides of the core, middle and shell streamlines of a stator blade. Seven transducers mounted on the torque converter clutch cavity. Finally, five on the cavity between the pressure plate and the turbine shell. The torque converter was part of a …

Multiscale Modeling: Thermal Conductivity Of Graphene/Cycloaliphatic Epoxy Composites, Sorayot Chinkanjanarot

Dissertations, Master's Theses and Master's Reports

The thermal property of epoxy as the binder in the Carbon Fiber (CF) composites, especially thermal conductivity is important to achieve the advance technology and to improve the performance of materials. Multiscale modeling including molecular dynamic (MD) modeling and micromechanical modeling is used to study the properties of neat Cycloaliphatic Epoxies (CE) and Graphene nanoplatelet (GNP)/CE with and without covalent functionalization.

The thermal properties (glass-transition temperature, thermal expansion coefficient, and thermal conductivity) and mechanical properties of CE system are investigated by MD modeling using OPLS-All Atom force field. A unique crosslinking technique is developed to achieve the cured CE models …

Bruise Detection In Apples Using 3d Infrared Imaging And Machine Learning Technologies, Zilong Hu

Dissertations, Master's Theses and Master's Reports

Bruise detection plays an important role in fruit grading. A bruise detection system capable of finding and removing damaged products on the production lines will distinctly improve the quality of fruits for sale, and consequently improve the fruit economy. This dissertation presents a novel automatic detection system based on surface information obtained from 3D near-infrared imaging technique for bruised apple identification. The proposed 3D bruise detection system is expected to provide better performance in bruise detection than the existing 2D systems.

We first propose a mesh denoising filter to reduce noise effect while preserving the geometric features of the meshes. …

On The Applications Of Interactive Theorem Proving In Computational Sciences And Engineering, Amer Tahat

Dissertations, Master's Theses and Master's Reports

Interactive Theorem Proving (ITP) is one of the most rigorous methods used in

formal verification of computing systems. While ITP provides a high level of confidence in the correctness of the system under verification, it suffers from a steep learning curve and the laborious nature of interaction with a theorem prover. As such, it is desirable to investigate whether ITP can be used in unexplored (but high-impact) domains where other verification methods fail to deliver. To this end, the focus of this dissertation is on two important domains, namely design of parameterized self-stabilizing systems, and mechanical verification of numerical approximations …

A Quantitative Investigation Of The Water Condensation Inside Tubes Of Compact Charge Air Cooler, Robin Cash

Dissertations, Master's Theses and Master's Reports

To address the need of increasing fuel economy requirements, automotive Original Equipment Manufacturers (OEMs) are increasing the number of turbocharged engines in their powertrain line-ups. The turbine-driven technology uses a forced induction device, which increases engine performance by increasing the density of the air charge being drawn into the cylinder. Denser air allows more fuel to be introduced into the combustion chamber, thus increasing engine performance. During the compression process, the air is heated to temperatures that can cause pre-ignition, resulting in reduced engine functionality. The introduction of the charge air cooler (CAC) is therefore, necessary to extract heat from …