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Investigation Of Its-Cvo Technologies, Mallory Brown, Andrew Martin, Valerie Keathley-Helil, Jennifer Walton
Investigation Of Its-Cvo Technologies, Mallory Brown, Andrew Martin, Valerie Keathley-Helil, Jennifer Walton
Kentucky Transportation Center Research Report
Staff shortages and reduced budgets have made transportation agencies increasingly reliant on intelligent transportation systems (ITS) for commercial motor (CMV) vehicle enforcement activities. Technologies such as license plate readers, US Department of Transportation (USDOT) number readers, weigh-in-motion scales, static scales, and preclearance systems like PrePass and Drivewyze help automate enforcement and free up personnel to focus on inspecting those vehicles most likely to pose compliance and/or safety risks. To document adoption rates of different technologies, researchers surveyed transportation agencies, vendors, and law enforcement agencies. Surveys responses provided useful insights into how jurisdictions are approaching the use of advanced technologies to …
Aligning Aviation Safety Reporting System Anomaly Codes For Crew Communication And Coordination With Human Factors Taxonomies, Jennifer Rose Herr
Aligning Aviation Safety Reporting System Anomaly Codes For Crew Communication And Coordination With Human Factors Taxonomies, Jennifer Rose Herr
Doctoral Dissertations and Master's Theses
This study addresses the lack of theoretical grounding and definitions for the Aviation Safety Reporting System (ASRS) anomaly codes, particularly those related to pilot communication and coordination errors. To improve the conceptual consistency and analytical usability of ASRS data, the research developed a framework that maps ASRS codes to three established theory-based human factors taxonomies: the Human Factors Analysis and Classification System (HFACS), Threat and Error Management (TEM), and Aviation Causal Contributors for Error Reporting Systems (ACCERS). The study used qualitative text mining to systematically code communication and coordination errors submitted by Part 121 pilots for a stratified sample of …
Additively Manufactured Bioinspired Microstructures For Active Surface Modification, Zefu Ren
Additively Manufactured Bioinspired Microstructures For Active Surface Modification, Zefu Ren
Doctoral Dissertations and Master's Theses
Advancements in additive manufacturing have facilitated the development of bioinspired microstructures, which hold promise for applications, such as liquid transport, self-cleaning, and anti-icing. However, the controllability of these microstructures remains an area requiring further exploration. This research explores the design, fabrication, and active control of 3D-printed bioinspired microstructures for dynamic wettability modulation. First, the anisotropic scales of butterfly wings were replicated through optimized two-photon polymerization printing strategies, achieving directional droplet motion controlled by structural geometry and arrangement. The reversed wetting trend compared with natural wings revealed key insights into the structure–performance relationship. Next, microstructures were integrated with dielectric elastomer actuators …
Perturbation Solution Of Air-Water Mixture For Jet Noise Reduction, Juan Felipe Uribe Cifuentes
Perturbation Solution Of Air-Water Mixture For Jet Noise Reduction, Juan Felipe Uribe Cifuentes
Doctoral Dissertations and Master's Theses
This work investigates passive jet-noise mitigation using externally positioned air–water curtains that attenuate radiated sound without altering the underlying jet dynamics. Two classes of multiphase media are examined: a gaseous carrier phase containing dispersed liquid droplets, and a liquid carrier phase containing entrained air bubbles. For both systems, suspended and dispersed regimes are represented through a generalized perturbation formulation derived from the volume-averaged multiphase equations, incorporating finite volume fractions, interphase momentum coupling, and slip between phases. Analytical and numerical solutions demonstrate that acoustic attenuation is primarily governed by dispersed-phase diameter, volume fraction, and excitation frequency, with additional sensitivity to phase-interaction …
A Study In Object Detection And Classification Performance By Sensing Modality For Autonomous Surface Vessels, Daniel Lane
A Study In Object Detection And Classification Performance By Sensing Modality For Autonomous Surface Vessels, Daniel Lane
Doctoral Dissertations and Master's Theses
This research presents a quantitative performance comparison between light detection and ranging (LiDAR) and vision-based sensing for real-time maritime object detection on autonomous surface vessels. Using Embry-Riddle Aeronautical University’s (ERAU) Minion platform and 2024 Maritime RobotX Challenge data, this study evaluates the detection of six maritime object categories using two representative models. YOLOv8 provides a neural network vision-based method, and GB-CACHE provides a deterministic LiDAR-based method. Both models have been previously demonstrated to run in real time on uncrewed surface vessels (USVs). The evaluation methodology encompasses multi-sensor calibration, real-time performance analysis, and the introduction of a late-fusion strategy in the …
Adaptive Control For Spacecraft With Flexible Appendages With Unknown Parameters, Nicolo Woodward
Adaptive Control For Spacecraft With Flexible Appendages With Unknown Parameters, Nicolo Woodward
Doctoral Dissertations and Master's Theses
Flexible spacecraft pose several challenges in control design due to the uncertain dynamical model and the underactuated nature of these systems. Adaptive and robust controllers are the common choice for these systems to either meet operational requirements like attitude pointing or to suppress vibrations. However, these controllers add complexity in the design of onboard Attitude Determination and Control Systems (ADCS) and the Reaction Control Systems (RCS) for spacecraft maneuvering. The objective of this research is to control a system that undergoes unpredictable and unknown disturbances through onboard derivation of an equivalent reduced order model designed around mounted sensors. The proposed …
Autonomous Landing Of An Unmanned Aerial Vehicle On An Unmanned Surface Vessel Using Model Predictive Control With An Adaptive-Covariance Extended Kalman Filter, Jorge Estupinan
Doctoral Dissertations and Master's Theses
This thesis presents the development of vision-based estimation and model predictive control (MPC) strategies to enable an Unmanned Aerial Vehicle (UAV) to land autonomously on an Unmanned Surface Vessel (USV) subjected to wave-induced motion. An innovative Adaptive-Covariance Extended Kalman Filter (AEKF) implementation was developed for the estimation of the 6 degree-of-freedom USV states using GPS and vision-based measurements of AprilTag markers on the USV landing platform. The AEKF employs an uncontrolled 6 degree-of-freedom nonlinear model augmented with second-order harmonic wave-induced motion dynamics. The AEKF implements two correction techniques: an adaptive covariance adjustment and an artificial covariance inflation regulated by a …
Validation And Trend Analysis Of Satellite-Derived Surface Water Temperature Observations Over Adirondack Lakes, Marzi Azarderakhsh, Carolien Mossel, Abdou Rachid Bah, Aisha Malik, Fahmeda Khanom, Jonathan Borrelli, Pete Mcintyre, Hamidreza Norouzi, Kevin Rose
Validation And Trend Analysis Of Satellite-Derived Surface Water Temperature Observations Over Adirondack Lakes, Marzi Azarderakhsh, Carolien Mossel, Abdou Rachid Bah, Aisha Malik, Fahmeda Khanom, Jonathan Borrelli, Pete Mcintyre, Hamidreza Norouzi, Kevin Rose
Publications and Research
This study aims to validate and evaluate satellite remote sensing observations from the Landsat series over 135 lakes in the Adirondack State Park, located in upstate New York, and to examine their surface temperature trends over the past 40 years. It utilizes data from the Moderate Resolution Imaging Spectroradiometer (MODIS), along with Landsat 5 and 7. Park-scale results were derived by extracting MODIS surface temperatures within the park boundary, while lake-scale results were estimated using Landsat 5 (1984-2012) and Landsat 7 (1999-2023) observations. In addition, field observations were utilized to perform a comprehensive validation and evaluation of satellite-based surface temperature …
Deep Learning-Based Change Detection In High-Resolution Remote Sensing Imagery, Hazem Badawy
Deep Learning-Based Change Detection In High-Resolution Remote Sensing Imagery, Hazem Badawy
Theses and Dissertations
Remote sensing has become a key tool for monitoring Earth’s surface over time, offering valuable insights into both natural and human-driven changes. Among its many applications, change detection focuses on analyzing multi-temporal imagery to reveal how specific areas evolve across different time periods. It plays a pivotal role in Earth observation applications, including urban development monitoring, environmental degradation assessment, and disaster response. However, existing approaches often struggle with limited contextual awareness, high sensitivity to noise, and imprecise localization of change boundaries, especially with high-resolution imagery. This thesis investigates the complex problem of change detection in remote sensing imagery by proposing …
Freer Arrows And Why You Need Them In Haskell, Grant Vandomelen, Gan Shen, Lindsey Kupur, Yao Li
Freer Arrows And Why You Need Them In Haskell, Grant Vandomelen, Gan Shen, Lindsey Kupur, Yao Li
Computer Science Faculty Publications and Presentations
Freer monads are a useful structure commonly used in various domains due to their expressiveness. However, a known issue with freer monads is that they are not amenable to static analysis. This paper explores freer arrows, a relatively expressive structure that is amenable to static analysis. We propose several variants of freer arrows. We conduct a case study on choreographic programming to demonstrate the usefulness of freer arrows in Haskell.
Exploring Object Status Recognition For Recipe Progress Tracking In Non-Visual Cooking, Franklin Mingzhe Li, Kaitlyn Ng, Bin Zhu, Patrick Carrington
Exploring Object Status Recognition For Recipe Progress Tracking In Non-Visual Cooking, Franklin Mingzhe Li, Kaitlyn Ng, Bin Zhu, Patrick Carrington
Research Collection School Of Computing and Information Systems
Cooking plays a vital role in everyday independence and well-being, yet remains challenging for people with vision impairments due to limited support for tracking progress and receiving contextual feedback. Object status — the condition or transformation of ingredients and tools — offers a promising but underexplored foundation for context-aware cooking support. In this paper, we present OSCAR (Object Status Context Awareness for Recipes), a technical pipeline that explores the use of object status recognition to enable recipe progress tracking in non-visual cooking. OSCAR integrates recipe parsing, object status extraction, visual alignment with cooking steps, and time-causal modeling to support real-time …
Machine Learning Classification Of Eeg Responses To Pain-Related Vs Non-Pain-Related Stimulus In Preterm Infants, Lojain Hamwi, Hang Du, Sara Jasim, Xiaogang Wang, Vibhuti Shah, Carol Cheng, Lorenzo Fabrizi, Maria Fitzgerald, Judith Meek, Nicole Racine, Ian Stedman, Rebecca Pillai Riddell
Machine Learning Classification Of Eeg Responses To Pain-Related Vs Non-Pain-Related Stimulus In Preterm Infants, Lojain Hamwi, Hang Du, Sara Jasim, Xiaogang Wang, Vibhuti Shah, Carol Cheng, Lorenzo Fabrizi, Maria Fitzgerald, Judith Meek, Nicole Racine, Ian Stedman, Rebecca Pillai Riddell
Michigan Tech Publications
INTRODUCTION: Unmanaged pain in preterm infants can lead to long-term developmental consequences. Current pain assessment methods lack specificity, resulting in possible pain mismanagement in Neonatal Intensive Care Units (NICUs). This study explores the application of machine learning (ML) to differentiate between pain-related and non-pain-related cortical activity in preterm infants. OBJECTIVE: To evaluate the performance of ML models in distinguishing cortical EEG activity during a painful procedure in preterm infants across different postmenstrual ages (PMAs). METHODS: This observational study was conducted from June 2015 to May 2024 at Mount Sinai Hospital in Toronto, Canada, and University College London Hospital, United Kingdom. …
Impact Of Multiple Mining Subsidence On Large Diameter Steel Pipelines: The Upper Silesian Coal Basin Case Study, Piotr Kalisz, Magdalena Zięba, Marcin Grygierek
Impact Of Multiple Mining Subsidence On Large Diameter Steel Pipelines: The Upper Silesian Coal Basin Case Study, Piotr Kalisz, Magdalena Zięba, Marcin Grygierek
Journal of Sustainable Mining
The article concerns the impact of multiple mining subsidence on pipeline expansion capacity based on the analysis of the field research results. The article presents a case study related to a water mains system that supplies drinking water to approximately 3.5 million consumers. These pipelines are made of steel with diameters of 1600 mm and 1400 mm. The water mains partly run through mining and post-mining areas in the Upper Silesian Coal Basin in Poland. These pipelines are equipped with expansion joints to protect them against the impact of ground deformations. The field research concerned the assessment of the position …
Stabilized Weak-Gradient Discontinuous Finite Elements With Optimal Error Estimates For Second-Order Elliptic Pdes, Aymen Laadhari
Stabilized Weak-Gradient Discontinuous Finite Elements With Optimal Error Estimates For Second-Order Elliptic Pdes, Aymen Laadhari
Mathematical Modelling and Numerical Simulation with Applications
This work introduces an accurate finite element approach employing a new stabilized discrete weak gradient, designed for second-order elliptic problems on arbitrary conforming meshes. We formulate the approach within a discontinuous Galerkin framework and derive a consistent and coercive bilinear form. Appropriate error analysis on a model problem confirms optimal convergence. Building on the core analysis, we extend the method to more challenging settings, including time-dependent heterogeneous scenarios and a biophysically realistic optimal-control model of photobleaching in the budding yeast cell. We further illustrate the versatility of the weak-gradient construction by applying it to an unsteady level-set equation relevant to …
Drawing On Uncertainty Methodologies Of Neutrosophic Hypersoft Sets In Cognitive Computing-Driven Healthcare Systems, Mona Mohamed, Nurhan Alaa
Drawing On Uncertainty Methodologies Of Neutrosophic Hypersoft Sets In Cognitive Computing-Driven Healthcare Systems, Mona Mohamed, Nurhan Alaa
Neutrosophic Systems with Applications
A new paradigm called cognitive computing simulates human reasoning and decision-making through integrating advanced techniques such as artificial intelligence (AI) and natural language processing (NLP). Cognitive computing systems, in contrast to traditional systems, can handle both structured and unstructured data, adjust to new information, and offer context-sensitive insights. This study examines how cognitive computing improves decision-making, personalization, and human-machine collaboration in various fields. Cognitive computing in the healthcare sector processes clinical notes, imaging data, and electronic health records to help physicians with diagnosis, treatment planning, and patient engagement. This study examines key applications, including their role in diagnostic support, where …
Evaluating And Ranking Genai Chatbots Under Uncertainty: A Type-2 Neutrosophic Rancom–Marcos Mcdm Framework, Hend Ahmed, Abduallah Gamal
Evaluating And Ranking Genai Chatbots Under Uncertainty: A Type-2 Neutrosophic Rancom–Marcos Mcdm Framework, Hend Ahmed, Abduallah Gamal
Neutrosophic Systems with Applications
Owing to integrate GenAI chatbots to enhance productivity across various tasks, this research presents T2NN-RANCOM-MARCOS multi-attribute decision-making model, which employs Type-2 Neutrosophic Number (T2NN) to handle uncertain data, the RANCOM method, distinguished by its easy, highly repeatable, less time consuming, more appropriate to deal with problems exceeds 5 criteria with expert errors to assign subjective weights to criteria and MARCOS method to evaluate and rank eight GenAI chatbots against six main criteria are included 23 sub-criteria: Quality of Information, Understanding and Reasoning, Expression Style and Persona, Safety and Harm, Trust and Confidence and Economic are primarily derived from QUEST evaluation …
Durable Low-Friction Graphite Coatings Enabled By A Polydopamine Adhesive Underlayer, Adedoyin Ayomide Abe, Fernando Maia De Oliveira, Deborah Okyere, Mourad Benamara, Jingyi Chen, Yuriy I. Mazur, Min Zou
Durable Low-Friction Graphite Coatings Enabled By A Polydopamine Adhesive Underlayer, Adedoyin Ayomide Abe, Fernando Maia De Oliveira, Deborah Okyere, Mourad Benamara, Jingyi Chen, Yuriy I. Mazur, Min Zou
Mechanical Engineering Faculty Publications and Presentations
This study investigates the tribological performance and wear mechanisms of graphite and polydopamine/graphite (PDA/graphite) coatings on stainless steel under dry sliding conditions. While graphite is widely used as a solid lubricant, its poor adhesion to metal substrates limits long-term durability. Incorporating an adhesion-promoting PDA underlayer significantly improved coating lifetime and wear resistance. Tribological testing revealed that PDA/graphite coatings maintained a coefficient of friction (COF) below 0.15 for over seven times longer than graphite-only coatings. High-resolution scanning electron microscopy, SEM, and profilometry showed that PDA improved coating adhesion and suppressed lateral debris transport, confining wear to a narrow zone. Surface and …
Iot-Enabled Machine Learning Framework For Prediction Of Eutrophication, Hocine Dai, Akli Abbas, Houssam Eddine-Othman Lachemat, Aicha Aid
Iot-Enabled Machine Learning Framework For Prediction Of Eutrophication, Hocine Dai, Akli Abbas, Houssam Eddine-Othman Lachemat, Aicha Aid
Iraqi Journal for Computer Science and Mathematics
This study presents an innovative predictive monitoring framework that integrates the Internet of Things (IoT) with advanced machine learning (ML) techniques to model the relationship between oxidized nitrate (NOX)—employed as the sole predictor—and chlorophyll a (CHLA), a key proxy for algal biomass. By utilising a single optimally selected parameter, the approach significantly reduces sensor deployment complexity and instrumentation costs, while minimising data acquisition and computational requirements. Logarithmic and Yeo-Johnson transformations were applied to the predictor and target variables, respectively, to address distributional skewness and enhance variance homogeneity. An optimised Random Forest model demonstrated strong predictive performance, achieving a coefficient of …
Multi Features Data Clustering Using Novel Statistical Method With Application To Color Images, Husham Y. A. Alameen, Ali Karah Bash
Multi Features Data Clustering Using Novel Statistical Method With Application To Color Images, Husham Y. A. Alameen, Ali Karah Bash
Iraqi Journal for Computer Science and Mathematics
The efficiency and performance of the color image clustering algorithms are determined by various factors, including accuracy, data size, speed, and reliability (the absence of randomness in the results). Some applications, like microscopes analyzing images of biological objects or telescopes observing planetary motion prioritize accuracy over execution time. In contrast, surveillance cameras and moving object tracking prioritize speed and reliability over accuracy. This study introduces a novel algorithm that balances these four factors by clustering data with multiple features linked through specific relationships. The proposed algorithm has been practically applied to RGB color images. Traditional clustering methods, such as K-means, …
Quantifying The Decay Timescale Of Volcanic Sulfur Dioxide In The Stratosphere, Paul A. Nicknish, Kane Stone, Susan Solomon, Simon Carn
Quantifying The Decay Timescale Of Volcanic Sulfur Dioxide In The Stratosphere, Paul A. Nicknish, Kane Stone, Susan Solomon, Simon Carn
Michigan Tech Publications
The injection of sulfur dioxide (SO2) into the stratosphere and its subsequent oxidation to form sulfate aerosols after large volcanic eruptions can have profound effects on Earth's climate. The removal of volcanic SO2 in the stratosphere is thought to be driven by its gas-phase oxidation by the hydroxyl radical (OH); once oxidized, it goes on to form sulfate aerosols. However, it has also been suggested that heterogeneous oxidation on ash could also be important or even dominant, which would imply the faster removal of SO2 and thus the faster formation of aerosols, at least in ash-rich plumes. Additionally, recent work …
Series Reports From Professor Wei’S Group Of Chongqing University: Advancements In Electrochemical Energy Conversions (2/4): Report 2: High-Performance Water Splitting Electrocatalysts, Ling Zhang, Wang-Yang Wu, Qiu-Yue Hu, Shi-Dan Yang, Li Li, Rui-Jin Liao, Zi-Dong Wei
Series Reports From Professor Wei’S Group Of Chongqing University: Advancements In Electrochemical Energy Conversions (2/4): Report 2: High-Performance Water Splitting Electrocatalysts, Ling Zhang, Wang-Yang Wu, Qiu-Yue Hu, Shi-Dan Yang, Li Li, Rui-Jin Liao, Zi-Dong Wei
Journal of Electrochemistry
The unavailability of high-performance and cost-effective electrocatalysts has impeded the large-scale deployment of alkaline water electrolyzers. Professor Zidong Wei’s group has focused on resolving critical challenges in industrial alkaline electrolysis, particularly elucidating hydrogen and oxygen evolution reaction (HER/OER) mechanisms while addressing the persistent activity-stability trade-off. This review summarizes their decade-long progress in developing advanced electrodes, analyzing the origins of sluggish alkaline HER kinetics and OER stability limitations. Professor Wei proposes a unifying “12345 Principle” as an optimization framework. For HER electrocatalysts, they have identified that metal/metal oxide interfaces create synergistic “chimney effect” and “local electric field enhancement effect”, enhancing selective …
Local Electric Fields Coupled With Cl− Fixation Strategy For Improving Seawater Oxygen Reduction Reaction Performance, Yu-Rong Liu, Miao Zhang, Yan-Hui Yu, Ya-Lin Liu, Jing Li, Xiao-Dong Shi, Zhen-Ye Kang, Dao-Xiong Wu, Peng Rao, Ying Liang, Xin-Long Tian
Local Electric Fields Coupled With Cl− Fixation Strategy For Improving Seawater Oxygen Reduction Reaction Performance, Yu-Rong Liu, Miao Zhang, Yan-Hui Yu, Ya-Lin Liu, Jing Li, Xiao-Dong Shi, Zhen-Ye Kang, Dao-Xiong Wu, Peng Rao, Ying Liang, Xin-Long Tian
Journal of Electrochemistry
Development of robust electrocatalyst for oxygen reduction reaction (ORR) in a seawater electrolyte is the key to realize seawater electrolyte-based zinc-air batteries (SZABs). Herein, constructing a local electric field coupled with chloride ions (Cl−) fixation strategy in dual single-atom catalysts (DSACs) was proposed, and the resultant catalyst delivered considerable ORR performance in a seawater electrolyte, with a high half-wave potential (E1/2) of 0.868 V and a good maximum power density (Pmax) of 182 mW·cm−2 in the assembled SZABs, much higher than those of the Pt/C catalyst (E1/2: 0.846 V; Pmax: 150 mW·cm−2 …
Wmu Maritime Affairs Conference 2025 : Transforming A Maritime Future : Digitalization And Decarbonization, World Maritime University
Wmu Maritime Affairs Conference 2025 : Transforming A Maritime Future : Digitalization And Decarbonization, World Maritime University
Books
No abstract provided.
Warpage-Resistant, Under-Extrusion-Free, High-Surface-Quality Additive Manufacturing Process For Polyethylene-Based Composite Radiation Shielding Material, Duo Xu, Volodymyr Korolovych, You Lyu, Jacqueline Aslarus, Domingo R. Flores-Hernandez, Simo Pajovic, William T. Heller, Lembit Sihver, Svetlana V. Boriskina
Warpage-Resistant, Under-Extrusion-Free, High-Surface-Quality Additive Manufacturing Process For Polyethylene-Based Composite Radiation Shielding Material, Duo Xu, Volodymyr Korolovych, You Lyu, Jacqueline Aslarus, Domingo R. Flores-Hernandez, Simo Pajovic, William T. Heller, Lembit Sihver, Svetlana V. Boriskina
Informatics and Engineering Systems Faculty Publications
Polyethylene (PE) is one of the best shielding materials for primary space radiation due to its high hydrogen content. For effective secondary neutron shielding, boron-rich fillers are incorporated to enhance performance. The semicrystalline nature and high thermal expansion coefficient of PE impede its adoption for in situ additive manufacture in space via the fused deposition modeling (FDM) 3D printing. We developed an optimized PE blend to mitigate the effects of under-extrusion and warpage. Guided by studies on extrusion and warpage, we developed an optimal set of printing parameters for the proposed PE blend. The optimum PE blend─both in its pure …
Pendant Micro-Droplet Evaporation Fabricates Fiber-Optic Mof Gas Sensor In Seconds, Abhishek Prakash Hungund, Bohong Zhang, Narasimman Subramaniyam, Thomas Spudich, Ryan O'Malley, Farhan Mumtaz, Rex E. Gerald, Jie Huang
Pendant Micro-Droplet Evaporation Fabricates Fiber-Optic Mof Gas Sensor In Seconds, Abhishek Prakash Hungund, Bohong Zhang, Narasimman Subramaniyam, Thomas Spudich, Ryan O'Malley, Farhan Mumtaz, Rex E. Gerald, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
The development of photonic-based gas sensors using metal–organic frameworks (MOFs) and other microporous solids is often a multistep, complex process, typically involving MOF synthesis, purification, and attachment of microcrystals to an optical fiber end face. This study introduces a one-step method that integrates MOF synthesis and sensor head fabrication directly onto the fiber end face, forming an extrinsic Fabry–Perot interferometer (EFPI) with a thin film of MOF microcrystals. The resulting film, only 3–10-μm-thick, enhances sensor response by enabling rapid gas detection within seconds. Utilizing a pendant micro-droplet evaporation technique, this method forms a microporous MOF layer in situ, allowing unreacted …
Polymorphism Crystal Structure Prediction With Adaptive Space Group Diversity Control, Sadman Saadeed Omee, Lai Wei, Jianjun Hu
Polymorphism Crystal Structure Prediction With Adaptive Space Group Diversity Control, Sadman Saadeed Omee, Lai Wei, Jianjun Hu
Faculty Publications
Crystalline materials can form different structural arrangements (i.e., polymorphs) with the same chemical composition, exhibiting distinct physical properties depending on how they are synthesized or the conditions under which they operate. For example, carbon can exist as graphite (soft, conductive) or diamond (hard, insulating). Computational methods that can predict these polymorphs are vital in materials science, which help understand stability relationships, guide synthesis efforts, and discover new materials with desired properties without extensive trial-and-error experimentation. However, effective crystal structure prediction (CSP) algorithms for inorganic polymorph structures remain limited. ParetoCSP2 is proposed, a multi-objective genetic algorithm for polymorphism CSP that incorporates …
Anisotropic Residual Stress Measurements In Additively Manufactured 316 Stainless Steel Parts, Rajeshree Varma, Donovan Stumpf, Paul R. Mort
Anisotropic Residual Stress Measurements In Additively Manufactured 316 Stainless Steel Parts, Rajeshree Varma, Donovan Stumpf, Paul R. Mort
15th International Conference on Shot Peening
Additive manufacturing (AM) using laser powder bed fusion (L-PBF) is increasingly used to produce complex parts for industries like aerospace and medical devices. The intrinsic characteristics of AM – layer-wise deposition and rapid thermal cycling – generate significant, anisotropic, residual stresses that can compromise part quality and performance. Recent studies highlight how these stresses are strongly influenced by process parameters and build orientation. X-ray diffraction (XRD) techniques, including sin²ψ and advanced two-dimensional approaches, have become the preferred methods for non-destructive, directionally resolved measurement of residual stress in AM metals. This review surveys advancements in XRD residual stress methods with a …
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 …
Enhancing High Cycle Fatigue Perfomance Of Electron Beam Melted Ti6al4v: A Study On Shot Peening And Hot Isostatic Pressing, Naghmeh M. Mojib, Dwayne D. Arola, Ramulu Mamidala
Enhancing High Cycle Fatigue Perfomance Of Electron Beam Melted Ti6al4v: A Study On Shot Peening And Hot Isostatic Pressing, Naghmeh M. Mojib, Dwayne D. Arola, Ramulu Mamidala
15th International Conference on Shot Peening
The qualification of electron beam powder bed fusion (PBF-EB) for safety-critical applications is hindered by variability in high cycle fatigue performance, largely due to surface roughness and internal defects. While Hot Isostatic Pressing (HIP) effectively reduces internal porosity, it does not address surface-initiated fatigue failures. This study investigated the combined effects of HIP and shot peening on enhancing the fatigue performance of PBF-EB Ti6Al4V. Over 50 specimens, including both vertical and horizontal build orientations, underwent high cycle fatigue testing per ASTM E466. X-Ray computed tomography confirmed decrease in defect distribution following HIP, while shot peening resulted in a more uniform …
Investigations On The Fatigue Strength Of Threads Produced By Different Fabrication Techniques, Philippe Du Maire, Jürgen Hoffmeister, Andreas Öchsner, Michael Johlitz
Investigations On The Fatigue Strength Of Threads Produced By Different Fabrication Techniques, Philippe Du Maire, Jürgen Hoffmeister, Andreas Öchsner, Michael Johlitz
15th International Conference on Shot Peening
The increasing importance of sustainability in engineering demands the development of long-lasting, high-performance components that reduce material and energy consumption over time. This study investigates how different thread manufacturing processes, i.e., cutting, rolling, and deep rolling, affect the fatigue strength of bolts made from 42CrMo4+QT steel. Cylindrical specimens with M12 threads were subjected to cyclic tensile loading with constant mean stress. Fatigue strength was evaluated using the staircase method, and supporting analyses included X-ray diffraction for residual stress, and full width half maximum examination and Vickers microhardness measurements. Results show that thread rolling significantly improves fatigue strength, achieving 113.8 MPa …