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Articles 31 - 60 of 710
Full-Text Articles in Mathematics
Exploratory Study Of Semiconductor Nanomembranes In Em Applications, Grant D. Heileman
Exploratory Study Of Semiconductor Nanomembranes In Em Applications, Grant D. Heileman
Electrical and Computer Engineering ETDs
Antenna systems are a cornerstone of modern technologies, playing an increasingly vital role in their advancement. As demand for compact, high-performance, and adaptable communication platforms grows reconfigurable antenna technologies are becoming essential. This research explores a novel front-end reconfigurable antenna system (FERAS) architecture that leverages the mechanical flexibility and photoconductive behavior of semiconductor nanomembrane (SNM) devices. By exploiting the emergent properties of ultra-thin silicon (Si) or gallium arsenide (GaAs) nanomaterials and optically exciting these samples using vertical-cavity surface-emitting laser (VCSEL) arrays, this study develops lightweight, low-cost, deployable antenna structures for satellite communications, remote sensing, GPS, and radar. Despite their significant …
Modeling Synaptic Dysfunction As Neural Contagion: A Graph-Based Sedr Framework For Simulating Signal Spread, Michelle Marfo, Dr. Padmanabhan Seshaiyer, Alonso Ogueda-Oliva
Modeling Synaptic Dysfunction As Neural Contagion: A Graph-Based Sedr Framework For Simulating Signal Spread, Michelle Marfo, Dr. Padmanabhan Seshaiyer, Alonso Ogueda-Oliva
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Site Specific Reliability-Targeted Snow Loads And Winter Wind Parameters Across The World, Brennan Bean, Nicholas Brimhall, Bikram Bhusal, Marc Maguire, Maha Moussa
Site Specific Reliability-Targeted Snow Loads And Winter Wind Parameters Across The World, Brennan Bean, Nicholas Brimhall, Bikram Bhusal, Marc Maguire, Maha Moussa
Mathematics and Statistics Faculty Publications
This report presents a framework for estimating Reliability Targeted Snow Loads (RTSLs) and Winter Wind Parameters (WWPs) at locations outside the Conterminous United States (OCONUS). The methodology integrates ground-based in-situmeasurements with gridded global climate products to generate spatially continuous RTSL estimates for nearly any location in OCONUS. RTSLs are computed at qualifying in-situ stations, and predictive models relating gridded climate products to in-situRTSLs enable estimation at locations lacking direct measurements. This report describes the development of the in-situ annual maximum snow load database, the construction of global gridded climate summaries, the estimation of site-specific RTSLs and Service Targeted …
Fourier Analyses Of Optical Profilometry As An Inferential Measurement For Impact Coverage., Langdon Feltner, Paul Mort
Fourier Analyses Of Optical Profilometry As An Inferential Measurement For Impact Coverage., Langdon Feltner, Paul Mort
15th International Conference on Shot Peening
A critical consideration in peening process design is achieving sufficient impact coverage. Conventional methods for assessing coverage rely on manual inspection, which is time-consuming and poorly suited for automated control. In this work, we investigate the use of frequency-domain analysis to quantify surface modification in peened samples using optical profilometry (OP) data. Three-dimensional surface maps of Almen strips were acquired using a high-resolution OP system and analyzed via fast Fourier transform (FFT) to compute spatial power spectral densities (PSDs). PSD maps and radially averaged profiles reveal consistent amplification of harmonic components similar to the nominal particle size, with increasing intensity …
Reduced Order Models Of Hydrodynamically Interacting Flapping Wings, Jose Pabon
Reduced Order Models Of Hydrodynamically Interacting Flapping Wings, Jose Pabon
Dissertations
Fish schools exhibit a collective behavior and self-organization that is mediated by hydrodynamic interactions between individual fish. However, the long-time evolution of hydrodynamically interacting collectives is challenging to investigate due to the persistent influence of long-lived vortical structures, and the high-resolution requirements of direct numerical simulation at large Reynolds numbers. Reduced-order models have therefore played an important role in theoretical investigations of collectives of swimming bodies. The main results detailed herein are several new reduced-order models of swimmers that self-propel by flapping, i.e., by executing a prescribed periodic rigid body motion. The models are extensions of a discrete-time dynamical system …
Traffic Prediction For Research And Education Networks: Anomaly-Aware Deep Learning And Benchmarking, Mohammad Arafath Uddin Shariff
Traffic Prediction For Research And Education Networks: Anomaly-Aware Deep Learning And Benchmarking, Mohammad Arafath Uddin Shariff
School of Computing: Dissertations, Theses, and Student Research
Research and Education Networks (RENs) and High-Performance Computing (HPC) environments are critical infrastructures for modern scientific discovery, demanding sustained high-throughput and low-latency data transfers. Unlike commercial networks, RENs exhibit unique traffic characteristics, including predominant “elephant flows,” inherent burstiness, and complex temporal-spatial dynamics often decoupled from human-driven cycles. Traditional traffic forecasting methods, tailored for commercial Wide Area Networks (WANs), consistently fail to capture these distinct REN dynamics, leading to inefficient resource management and potential impediments to scientific progress.
This thesis addresses this critical gap by developing and validating a robust, scalable, and anomaly-aware traffic forecasting framework specifically tailored for REN/HPC networks. …
Laser Scan Path Design For Controlled Microstructure In Additive Manufacturing With Integrated Reduced-Order Phase-Field Modeling And Deep Reinforcement Learning, Augustine Twumasi
Laser Scan Path Design For Controlled Microstructure In Additive Manufacturing With Integrated Reduced-Order Phase-Field Modeling And Deep Reinforcement Learning, Augustine Twumasi
Open Access Theses & Dissertations
Laser Powder Bed Fusion (L-PBF) is a well-established additive manufacturing technique for fabricating intricate metal components with exceptional precision. A significant challenge in L-PBF is the formation of complex microstructures that influence final material properties. We propose a physics-guided, machine learning-aided approach to optimize scan paths for desired microstructure outcomes, such as equiaxed grains. We employed a phase-field method (PFM) to model the evolution of the crystalline grain structure. To reduce computational costs, we trained a surrogate machine learning model, a 3D U-Net convolutional neural network, using single-track phase-field simulations with varying laser powers to predict crystalline grain orientations based …
Mathematical Modeling Of Effects Of Tumor Location On Lung Function., Lamargaret Temukisa Johnson
Mathematical Modeling Of Effects Of Tumor Location On Lung Function., Lamargaret Temukisa Johnson
Master of Engineering Theses
Lung cancer has the highest rates of incidence and mortality of all cancers. Most lung cancer tumors are Non-Small Cell Lung Cancer (NSCLC). NSCLC patients with lesions in the upper lobes are found to have better prognosis compared to those with lesions in the middle and lower lobes. Previous studies have suggested various causes for this discrepancy at both the organ-scale and tissue-scale. To model NSCLC growth in different locations within the lung, an organ scale lung model and tissue scale tumor model were coupled through the tissue pressure, and oxygen and carbon dioxide partial pressures. The coupling was used …
Dice Math And Probability, Warren Campbell
Dice Math And Probability, Warren Campbell
SEAS Faculty Publications
The manufacture of dice for tabletop games is a billion-dollar industry. In gaming circles and online forums, the concept of “cursed dice” is a popular topic. Dice are inherently unfair due to the difficulty of manufacturing them with perfect geometric tolerances and uniform material densities. A common method for testing dice fairness is the chi-square statistic, which is typically assumed to follow the chi-square distribution. However, this assumption is only asymptotically valid.
Exact distributions of the statistic can be computed for dice with few sides and a limited number of rolls—such as 2-sided (D2) and 4-sided (D4) dice—but the computational …
Effects Of The Gravity Gradient On The Path Of 1i/‘Oumuamua, Hannah R. Richardson
Effects Of The Gravity Gradient On The Path Of 1i/‘Oumuamua, Hannah R. Richardson
Poster Presentations
In October 2017, the asteroid 1I/’Oumuamua first passed into viewing range [1]. The asteroid is notable for being the first interstellar object to enter the solar system. 1I/’Oumuamua was also unusual in its geometry; it is thought to have an aspect ratio of 6:1 and a length of approximately 400 m [2] [3]. The asteroid was observed to experience a non-Keplerian acceleration estimated to be on the order of 1×10−6 m s-2 Several theories have been proposed for the cause of this acceleration, all of which are non-gravitational in nature: volatile outgassing, photon pressure, and solar winds [1][4]. However, none …
Computer Vision In Soccer: Yolov11 Analytics Engine For Quantifying Game Strategy, Connor S. Maurer
Computer Vision In Soccer: Yolov11 Analytics Engine For Quantifying Game Strategy, Connor S. Maurer
Data Science Undergraduate Honors Theses
Single-shot object detection capabilities significantly reduce computational overhead for real-time computer vision in sports analytics at 60 FPS. YOLO11’s lightweight CNN gives promising accuracy while meeting the low-latency demand of dynamic soccer matches. As data-driven approaches take over the sport of soccer, efficient player tracking systems become critical for informing coach’s strategies. I prototype the ETL (Extract, Transform, Load) process of data collected from a single- shot detection program and evaluate its viability for estimating player fatigue. YOLO11 detects players, the ball, and other characteristics, with the output transformed by homography to estimate the positions in the real world. These …
Decision Space Decomposition For Multiobjective Programs, Emma Soriano
Decision Space Decomposition For Multiobjective Programs, Emma Soriano
All Dissertations
Being inspired by the parametric decomposition theorem for multiobjective optimization problems (MOPs) of Cuenca and Miguel (2017), and by the block- coordinate descent for single objective optimization problems, we present a decom- position theorem for computing the set of minimal elements of a partially ordered set. This set is decomposed into subsets whose minimal elements are used to retrieve the overall minimal elements. We apply this approach to strictly convex MOPs de- composing their decision space into lines. The line decomposition benefits from the fact that a multiobjective line search problem is equivalent to solving a collection of single objective …
Stability Analysis Of Turbulent Fluid Flow, Adam D. Schroeder
Stability Analysis Of Turbulent Fluid Flow, Adam D. Schroeder
Mathematics, Statistics, and Computer Science Honors Projects
Hydrodynamic stability refers to the study of when and how laminar flows transition to turbulence. This includes investigations of the mechanisms of transition, as well as the classification of known flow configurations as either stable or unstable and the identification of critical values of flow parameters at which this bifurcation occurs. In this thesis, we introduce the mathematical theory behind continuum mechanics and fluid dynamics as well as some tools from the study of dynamical systems. We apply these concepts to the linear stability analysis of zero pressure gradient flat plate flow via numerical simulations in OpenFOAM, discussing both the …
The Food Truck: A Multi-Product Newsvendor With Trans-Shipment Cost, Samuel Ajibola
The Food Truck: A Multi-Product Newsvendor With Trans-Shipment Cost, Samuel Ajibola
Electronic Theses and Dissertations
The Newsvendor Problem is a key model in supply chain management that focuses on determining the optimal order quantity to minimize costs under uncertain demand. This thesis introduces the Food Truck Problem, an extension of the Newsvendor model that incorporates nonlinear transshipment costs for inventory transportation. In this context, a Food Truck must determine the optimal stock levels for multiple products while minimizing costs related to stock shortages, excess inventory, and transportation. Unlike traditional Newsvendor models, our approach explicitly considers a quadratic transshipment cost, which necessitates the use of Lagrangian duality and Karush-Kuhn-Tucker (KKT) conditions for analysis. Moreover, we apply …
Data Science For Engineers, Heidi Moulton
Data Science For Engineers, Heidi Moulton
Undergraduate Honors Capstone Projects
Undergraduate research is a core pillar of Utah State University’s College of Engineering. Many students become involved with research during their Junior and Senior years and begin to generate various forms of data. Most students, however, have received little formal education on how to process data, and there are currently no readily available resources within the College of Engineering. As a Mechanical Engineering and Data Science double major, I found the data processing techniques I learned in my Data Science courses invaluable as an undergraduate researcher, and now as a Mechanical Engineer at Apogee Instruments, I frequently draw upon these …
Applications Of Clustered Regularly Interspaced Short Palindromic Repeats In Food Security And Nutraceuticals, Rukayat Abiodun Oyegoke, Jahswill Toluwanimi Osifade, Adenike Temidayo Oladiji
Applications Of Clustered Regularly Interspaced Short Palindromic Repeats In Food Security And Nutraceuticals, Rukayat Abiodun Oyegoke, Jahswill Toluwanimi Osifade, Adenike Temidayo Oladiji
Al-Bahir
The CRISPR/Cas9 system is a revolutionary genome-editing tool that enables precise and inheritable modifications, transforming plant genetic engineering. Previous literature has indicated that, in agriculture, CRISPR has improved crop yield, biofortification, and resistance to environmental stressors, fostering resilient and high-yielding crops essential for sustaining a growing global population. In nutraceuticals, CRISPR has enhanced the biosynthesis of bioactive compounds such as anthocyanins, flavonoids, and omega-3 fatty acids, improving the nutritional and therapeutic value of crops.
Despite its immense potential, CRISPR technology faces technical, ethical, and regulatory challenges, including off-target effects, accessibility concerns, and public acceptance. Addressing these issues is crucial for …
Data Science For Engineers, Heidi Moulton
Data Science For Engineers, Heidi Moulton
Student Research Symposium
30% of USU undergraduate students participate in some sort of research, and for engineering students this often means generating large amounts of data.
Data Science for Engineers is a series of four modules that introduce students to data processing, visualization, and graphing in the Python programming language using Pandas DataFrames and Juypter Notebooks.
The modules are intended for students with a basic understanding of programming in Python, specifically those who have taken CS 1400 Introduction to Computer Science.
Comparative Analysis Of Vertical And Horizontal Subsurface Flow Constructed Wetlands For Eutrophication Mitigation", Ali M. Ahmed
Comparative Analysis Of Vertical And Horizontal Subsurface Flow Constructed Wetlands For Eutrophication Mitigation", Ali M. Ahmed
Al-Bahir
Constructed wetlands (CWs) serve as a sustainable and eco-friendly solution for wastewater treatment, particularly in the removal of eutrophication-causing pollutants. This review focuses on the comparative performance of Vertical Flow (VF) and Horizontal Flow (HF) Subsurface Flow (SSF) systems, assessing their efficiency in removing Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Nitrogen (TN), and Total Phosphorus (TP). VF systems demonstrate superior pollutant removal, particularly for nitrogen, due to enhanced aeration and efficient oxygenation processes. In addition, their compact design reduces land area requirements, making them advantageous in space-limited applications. Conversely, HF systems are more effective at supporting nutrient …
Aqueous Extracts Of Zingiber Officinale Rhizomes And Hibiscus Sabdariffa Leaves Enhanced Plasmodium Berghei-Infected Mice's Hematological Parameters., Fatimah Aluko Abubakar, Raliat Abimbola Aladodo, Aremu Abubakar
Aqueous Extracts Of Zingiber Officinale Rhizomes And Hibiscus Sabdariffa Leaves Enhanced Plasmodium Berghei-Infected Mice's Hematological Parameters., Fatimah Aluko Abubakar, Raliat Abimbola Aladodo, Aremu Abubakar
Al-Bahir
Malaria remains a global health challenge, leading to severe hematological complications. Natural alternatives such as Zingiber officinale and Hibiscus sabdariffa, known for their antioxidant and bioactive properties, are being investigated for their therapeutic potential. This study examines the hematological benefits of Z. officinale and H. sabdariffa in mice infected with the common malaria research model, NK65 chloroquine-sensitive Plasmodium berghei. Forty-two albino mice, averaging 24.5 ± 1.23g, were randomly divided into six groups. Mice in group A were uninfected which served as the normal control group. Mice in groups B, C, D, E, and F were inoculated intraperitoneally with P. …
Robust Spacecraft Autonomy For Deep Space Exploration In Special Euclidean Group Se(3), Matthew Wittal
Robust Spacecraft Autonomy For Deep Space Exploration In Special Euclidean Group Se(3), Matthew Wittal
Doctoral Dissertations and Master's Theses
Over the past half-century, humanity has gained extensive experience conducting manned spaceflight near Earth. Arguably, "near Earth" could even include the Moon — the most distant destination humans have reached. However, "near" in this work primarily refers low Earth orbit (LEO). One could argue that we have not truly left Earth since the Apollo, as spacecraft in some LEOs remain subject to atmospheric drag thus emphasizing their continued connection to Earth's immediate environment. Reflecting on this, it becomes clear that humanity has largely remained bound to Earth’s immediate vicinity since the Apollo missions reached the Moon. However, that is set …
Analysis Of Systematic Trade-Offs Between Military And Healthcare Expenditure Alongside Gdp Growth Of Select Asian And Western Exporting Economies In The 21st Century, Rahul Balamurugan, Carlos Gershenson, Preethi Nanjundan, Hiroki Sayama
Analysis Of Systematic Trade-Offs Between Military And Healthcare Expenditure Alongside Gdp Growth Of Select Asian And Western Exporting Economies In The 21st Century, Rahul Balamurugan, Carlos Gershenson, Preethi Nanjundan, Hiroki Sayama
Northeast Journal of Complex Systems (NEJCS)
This study explores the complexity in the trade-offs between military expenditure, healthcare expenditure, and GDP growth across select Asian nations and major weapon-exporting countries, examining how nations allocate finite resources between national security and human well-being over the past two decades. Using a systems science approach, the research integrates Granger causality testing to analyze temporal and directional relationships among GDP growth, military expenditure, and healthcare expenditure, uncovering their dynamic interdependencies. The methodology includes trend and slope analysis, Granger causality testing, outlier detection, and clustering to identify heterogeneity in resource allocation strategies. Developed, weapon-exporting nations exhibit complementary trends, with strong causality …
Volatility Modelling In Garch Frameworks: A Comparative Analysis Of Non-Gaussian Error Distributions With Skewed Parameters., Olatunbosun Adewale Akanbi, Timothy Olabisi Olatayo, Abass Ishola Taiwo
Volatility Modelling In Garch Frameworks: A Comparative Analysis Of Non-Gaussian Error Distributions With Skewed Parameters., Olatunbosun Adewale Akanbi, Timothy Olabisi Olatayo, Abass Ishola Taiwo
Al-Bahir
Forecasting volatility in financial time series remains challenging due to their asymmetric nature and excess kurtosis. This study evaluates and compares the performance of four variant of GARCH models incorporating skewed non-Gaussian error innovation distribution. The performances of these GARCH family of models under the skewed error innovation distributions were evaluated for three different unique data sets to have a more robust assessment of the performance of these skewed error innovation distributions. This study leverage on daily closing prices of Bitcoin, Naira to Dollar Exchange rates and daily Nigeria All Share Index between January 1, 2015 and January 26, 2024. …
Optimized Hiv/Aids Resource Allocation In Ohio: A Linear Programming Approach, Godfred Ahenkroa Kesse
Optimized Hiv/Aids Resource Allocation In Ohio: A Linear Programming Approach, Godfred Ahenkroa Kesse
Data Science and Data Mining
This study employs a linear and integer programming approach to optimize HIV resource allocation in Ohio, aiming to minimize new infections and enhance the impact of limited resources. With the advances in HIV prevention and treatment, Ohio faces challenges in addressing disparities in access to healthcare, particularly among high-risk populations. The proposed model integrates data on infection rates, transmission patterns, demographic factors, and cost-effectiveness to provide a decision-support framework for policymakers. Using epidemiological data and equity constraints, the model prioritizes high-risk regions and populations while ensuring fair resource distribution. Results indicate that increased funding allocations significantly enhance the potential to …
Ms-Yolo: Infrared Object Detection For Edge Deployment Via Mobilenetv4 And Slideloss, Jiali Zhang, Thomas S. White, Haoliang Zhang, Wenqing Hu, Donald C. Wunsch, Jian Liu
Ms-Yolo: Infrared Object Detection For Edge Deployment Via Mobilenetv4 And Slideloss, Jiali Zhang, Thomas S. White, Haoliang Zhang, Wenqing Hu, Donald C. Wunsch, Jian Liu
Mathematics and Statistics Faculty Research & Creative Works
Infrared imaging has emerged as a robust solution for urban object detection under low-light and adverse weather conditions, offering significant advantages over traditional visible-light cameras. However, challenges such as class imbalance, thermal noise, and computational constraints can significantly hinder model performance in practical settings. To address these issues, we evaluate multiple YOLO variants on the FLIR ADAS V2 dataset, ultimately selecting YOLOv8 as our baseline due to its balanced accuracy and efficiency. Building on this foundation, we present MS-YOLO (MobileNetv4 and SlideLoss based on YOLO), which replaces YOLOv8's CSPDarknet backbone with the more efficient MobileNetV4, reducing computational overhead by 1.5% …
Investigation Of Dynamic Adsorption And Desorption Of Polymer Nanogel In Porous Media Through Microfluidics, Junchen Liu, Fuqiao Bai, Abdulaziz A. Almakimi, Mingzhen Wei, Xiaoming He, Ibnelwaleed A. Hussein, Baojun Bai
Investigation Of Dynamic Adsorption And Desorption Of Polymer Nanogel In Porous Media Through Microfluidics, Junchen Liu, Fuqiao Bai, Abdulaziz A. Almakimi, Mingzhen Wei, Xiaoming He, Ibnelwaleed A. Hussein, Baojun Bai
Mathematics and Statistics Faculty Research & Creative Works
Understanding the transport and retention of elastic nanogel and microgel particles in porous media has been a significant research subject for decades, essential to the application of enhanced oil recovery (EOR). However, a lack of dynamic adsorption and desorption studies, in which the kinetics in porous media are seldom investigated, hinders the design and application of polymer nanogel in underground porous media. In this work, we visualized and quantified the transport and dynamic adsorption of polymer nanogel in 3D glass micromodels that were manufactured by packing glass beads in capillaries. Calibrating the linearity of fluorescence intensity to concentration, we calculated …
Bayesian Networks For Safety-Critical Systems, Joseph Mietkiewicz
Bayesian Networks For Safety-Critical Systems, Joseph Mietkiewicz
Theses
This thesis addresses a operational challenge in modern industrial operations: the increasing complexity of systems and the consequent cognitive burden on operators. As industrial technologies advance, the human-computer interface has become the primary conduit for information flow, playing a pivotal role in operational decision-making. However, the proliferation of data often leads to information overload, potentially compromising rather than enhancing operator performance. This research explores an approach to this pressing issue through the application of Bayesian networks as decision support systems in safety- critical scenarios. Our study employs a multi-faceted approach, combining theoretical modeling with empirical testing. Through collaboration with industry …
Centralized Deep Reinforcement Learning For Homogeneous Multi-Component Maintenance Optimization, Joseph W. Wittrock
Centralized Deep Reinforcement Learning For Homogeneous Multi-Component Maintenance Optimization, Joseph W. Wittrock
Theses and Dissertations
This thesis explores an application of reinforcement learning (RL) in maintenance optimization. Recent advances in hardware-accelerated computation and deep learning have made RL a powerful tool for solving optimization problems which are too complex for traditional methods. Maintenance optimization involves improving the efficiency and effectiveness of maintenance activities through data-driven approaches, ultimately reducing costs and increasing asset availability. Making informed maintenance decisions is crucial to long-term sustainability.
A desirable maintenance policy maximizes a utility signal while minimizing the cost of maintenance. Techniques in sequential decision making such as dynamic programming (DP) and RL have found success in optimizing these maintenance …
Quantized Average Agreement Algorithms With Error Correction For Digraphs, Shuaib A. Mughal
Quantized Average Agreement Algorithms With Error Correction For Digraphs, Shuaib A. Mughal
Honors Undergraduate Theses
Multi-agent systems have become more and more prevalent as technology increasingly gets integrated into our daily lives. Some of these technological systems are large in size; for example, the smart grid where multiple devices are used to monitor and control different aspects of the energy grid. Another example is a team of autonomous systems deployed for a specific task. When these systems are spatially distributed, an important component of distributed algorithms is the ability for the agents to reach consensus on the global state of the system. Reaching agreement enables the spatially distributed agent make decisions or determine the next …
Enhancement Of Mechanical, Structural, And Electrical Properties In Advanced Composites And Vat Photopolymerized 3d Printing Nanocomposites, Poom Narongdej
Enhancement Of Mechanical, Structural, And Electrical Properties In Advanced Composites And Vat Photopolymerized 3d Printing Nanocomposites, Poom Narongdej
CGU Theses & Dissertations
Advanced composites have gained significant attention across various industries, including aerospace, automotive, clean energy, and healthcare, owing to their exceptional mechanical properties and versatility. Fiber-reinforced polymer (FRP) composites, particularly those reinforced with carbon fibers, are extensively used as structural materials in spacecraft, aircraft, high-performance vehicles, and wind turbines due to their high strength-to-weight ratios, stiffness, durability, and tailorable mechanical characteristics. In healthcare, the advent of additive manufacturing (3D printing) has expanded the utility of advanced composites, enabling precise customization of components to meet patient-specific needs while offering design flexibility and ease of fabrication. Despite these advantages, several challenges hinder the …
Optimal Control And Structurally-Informed Gradient Optimization Of A Custom 4-Dof Rigid-Body, Brock Marcinczyk, Logan E. Beaver
Optimal Control And Structurally-Informed Gradient Optimization Of A Custom 4-Dof Rigid-Body, Brock Marcinczyk, Logan E. Beaver
Mechanical & Aerospace Engineering Faculty Publications
This work develops a control-centric framework for a custom 4-DOF rigid-body manipulator by coupling a reduced-order Pontryagin’s Maximum Principle (PMP) controller with a physics-informed Gradient Descent stage. The reduced PMP model provides a closed-form optimal control law for the joint accelerations, while the Gradient Descent module determines the corresponding time horizons by minimizing a cost functional built directly from the full Rigid-Body Dynamics. Structural-mechanics reaction analysis is used only to initialize feasible joint velocities—most critically the azimuthal component—ensuring that the optimizer begins in a physically admissible region. The resulting kinematic trajectories and dynamically consistent time horizons are then supplied to …