Engineering Commons^™

Structure-Aware Image Translation-Based Long Future Prediction For Enhancement Of Ground Robotic Vehicle Teleoperation, Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed M. S. Islam

Research outputs 2022 to 2026

Predicting future frames through image-to-image translation and using these synthetically generated frames for high-speed ground vehicle teleoperation is a new concept to address latency and enhance operational performance. In the immediate previous work, the image quality of the predicted frames was low and a lot of scene detail was lost. To preserve the structural details of objects and improve overall image quality in the predicted frames, several novel ideas are proposed herein. A filter has been designed to remove noise from dense optical flow components resulting from frame rate inconsistencies. The Pix2Pix base network has been modified and a structure-aware …

The Role Of Membrane Porosity In Ion Removal By Ro/Nf Membranes And Development Of A Regenerable Pac-Loaded Membrane, Yizhi Hou

Dissertations (1934 -)

Reverse osmosis (RO) and nanofiltration (NF) membranes are widely used for water treatment applications. They are charged porous materials, in which size exclusion and charge exclusion work together to dictate solute transport. In this study, membrane porosity was primarily determined by pore size. Thicker, more porous membranes with smaller pores had higher NaCl removal and less permeate water flux. Higher porosity membranes have greater inner pore surface area available to support a greater number of functional groups, thereby rejecting ion flux and increasing ion removal. The Donnan steric pore model (DSPM) was used to determine that the contribution of diffusion …

Understanding Melt Pool Characteristics In Laser Powder Bed Fusion: An Overview Of Single- And Multi-Track Melt Pools For Process Optimization, Jincheng Wang, Rui Zhu, Yujing Liu, Laichang Zhang

Research outputs 2022 to 2026

Laser powder bed fusion (LPBF) has made significant progress in producing solid and porous metal parts with complex shapes and geometries. However, LPBF produced parts often have defects (e.g., porosity, residual stress, and incomplete melting) that hinder its large-scale industrial commercialization. The LPBF process involves complex heat transfer and fluid flow, and the melt pool is a critical component of the process. The melt pool stability is a critical factor in determining the microstructure, mechanical properties, and corrosion resistance of LPBF produced metal parts. Furthermore, optimizing process parameters for new materials and designed structures is challenging due to the complexity …

A Review Of The Mechanical Properties Of 17-4ph Stainless Steel Produced By Bound Powder Extrusion, Jaidyn Jones, Ana Vafadar, Reza Hashemi

Research outputs 2022 to 2026

17-4PH Stainless Steel is a mechanically high-performing alloy that is widely used across chemical and mechanical processing industries. The alloy is conventionally fabricated by cast methods, but emerging additive manufacturing techniques are presently offering an economic, efficient, and environmentally friendly alternative. Bound Powder Extrusion (BPE) is a relatively new additive manufacturing technique that is used to fabricate three-dimensional, free-form components. Investigation into the mechanical properties and behavior of 17-4PH stainless steel fabricated by BPE is vital to understanding whether this technique proposes a competitive substitute to the cast alloy within industry. Published literature has investigated the as-fabricated mechanical properties, microstructure, …

Study Of All-Group-Iv Sigesn Mid-Ir Lasers With Dual Wavelength Emission, Grey Abernathy, Solomon Ojo, Abdulla Said, Joshua M. Grant, Yiyin Zhou, Hryhorii Stanchu, Wei Du, Baohua Li, Shui-Qing Yu

Electrical Engineering Faculty Publications and Presentations

Direct band gap GeSn alloys have recently emerged as promising lasing source materials for monolithic integration on Si substrate. In this work, optically pumped mid-infrared GeSn lasers were studied with the observation of dual-wavelength lasing at 2187 nm and 2460 nm. Two simultaneous lasing regions include a GeSn buffer layer (bulk) and a SiGeSn/GeSn multiple quantum well structure that were grown seamlessly using a chemical vapor deposition reactor. The onset of dual lasing occurs at 420 kW/cm². The wider bandgap SiGeSn partitioning barrier enables the independent operation of two gain regions. While the better performance device in terms …

Improving Benign Paroxysmal Positional Vertigo Diagnosis, Sida Zhang

Master's Theses (2009 -)

Benign Paroxysmal Positional Vertigo (BPPV) is one of the most common causes of dizziness. Especially for people over 45, the risk of BPPV is substantial. On the other hand, BPPV is often misdiagnosed and may require expensive examinations. This thesis introduces a prediction model based on machine learning to quickly, inexpensively, and accurately diagnose BPPV. The thesis starts by introducing BPPV and the statistics of BPPV misdiagnosis. Then, a patient survey is introduced. The patient survey includes 50 BPPV-related questions, which are used as training data for the machine learning model. Logistic Regression, Decision Tree, and Naïve Bayes were compared …

Reduced Bias User Preference Methods For Determining The Pareto-Optimal Solution Point, Dylan Thomas Johnson

Master's Theses (2009 -)

Engineering design is filled with tradeoffs between competing objectives such as performance, mass, cost, and schedule. A designer must navigate these complex multi-objective problems and deliver the right solution for their application. Multi-objective optimization techniques are powerful and widely used; however, a key drawback to these techniques is that they often output a set of equivalent solutions called the Pareto Front. The designer must perform an additional multi-objective down selection on the Pareto Front to determine a single Pareto-optimal solution point for their design. Existing Pareto Front processing techniques either use traditional infinitely adjustable weights, which can yield results that …

Design And Validation Of A Variable Stiffness Three Degree Of Freedom Planar Robot Arm, Andrew L. Bernhard

Master's Theses (2009 -)

The need exists for robotic manipulators that can interact with an environment having uncertain kinematic constraints. A robot has been designed and built for proof of concept of a passive variable compliance control strategy that can vary joint stiffness to achieve higher performance dexterous manipulation. This novel planar robot incorporating variable stiffness actuators and common industrial controls allows the robot to comply with its environment when needed but also have high stiffness for precise motion control in free space. To perform both functions well, a high stiffness ratio (max/min stiffness) is required. A stiffness ratio up to 492 was achieved. …

Switching Of Control Mechanisms During The Rapid Solidification Of A Melt Pool, Yijia Gu, Jiandong Yuan, Lianyi Chen

Materials Science and Engineering Faculty Research & Creative Works

The Solidification of Alloys is Typically Controlled by Solute Diffusion Due to the Solute Partitioning Happening at the Solid-Liquid Interface. in This Study, We Show that the Switching from Solute Diffusion-Controlled Growth to Thermal Diffusion-Controlled Growth May Happen at the Solidification Front during Rapid Solidification Processes of Alloys Such as Additive Manufacturing using a Phase-Field Model. the Switching is Found to Be Triggered by the Cooling of the Solid-Liquid Interface When It Becomes Colder Than the Solidus Temperature. the Switching Introduces a Sudden Jump of Growth Velocity, an Increase in Solute Concentration, and the Refining of the Resulting Microstructures. All …

On The Prediction Of The Mechanical Properties Of Limestone Calcined Clay Cement: A Random Forest Approach Tailored To Cement Chemistry, Taihao Han, Bryan K. Aylas-Paredes, Jie Huang, Ashutosh Goel, Narayanan Neithalath, Aditya Kumar

Materials Science and Engineering Faculty Research & Creative Works

Limestone calcined clay cement (LC3) is a sustainable alternative to ordinary Portland cement, capable of reducing the binder's carbon footprint by 40% while satisfying all key performance metrics. The inherent compositional heterogeneity in select components of LC3, combined with their convoluted chemical interactions, poses challenges to conventional analytical models when predicting mechanical properties. Although some studies have employed machine learning (ML) to predict the mechanical properties of LC3, many have overlooked the pivotal role of feature selection. Proper feature selection not only refines and simplifies the structure of ML models but also enhances these models' prediction performance and interpretability. This …

Mechanism Underlying Effect Of Expansive Agent And Shrinkage Reducing Admixture On Mechanical Properties And Fiber-Matrix Bonding Of Fiber-Reinforced Mortar, Kamran Aghaee, Taihao Han, Aditya Kumar, Kamal Khayat

Materials Science and Engineering Faculty Research & Creative Works

Expansive agent (EA) and shrinkage reducing admixture (SRA) are utilized to reduce shrinkage and risk of cracking in concrete. EA compensates shrinkage by initial expansion, and SRA reduces surface tension in the pore fluid. Although EA and SRA effectively reduce shrinkage, they can impair micro-structure of concrete at high contents. The shrinkage reduction effect of EA and SRA is well known; however, there is limited knowledge about their negative effect on microstructure and fiber matrix interfacial transition zone (ITZ). The current study explores the effect of using 10 % CaO-based EA, 2 % SRA, and their combination on mechanical, shrinkage, …

The Investigation Of A Likely Scenario For Natural Tornado Genesis And Evolution From An Initial Instability Profile, Alexios Nicolas Philippou, Kakkattukuzhy M. Isaac

Mechanical and Aerospace Engineering Faculty Research & Creative Works

A likely mechanism for the little-understood tornado genesis is proposed and its numerical implementation is presented. The Burgers-Rott vortex with its axis in the vertical direction is introduced as an instability mechanism, and the flow field then evolves under the influence of the atmospheric pressure, temperature and density variations with altitude. Buoyancy effects are implemented using the Boussinesq model. Results are presented and discussed for a set of conditions including mesh type and size, different turbulence models, and a few different boundary conditions. Post-processed results of the transient simulations including animations contain a wealth of information to help analyze tornado …

2023 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the fall of 2023.

Influence Of Feedstock And Moisture Content In A Continuous Feed Screw Torrefier, Anna H. Partridge, Isabella Casini, Denise A. Mckahn, David Carter, Charles Chamberlin, Arne Jacobson, Kyle Palmer, Yaad Rana, Mark Severy

Engineering: Faculty Publications

This paper investigates the parameters impacting product quality in a pilot scale biomass torrefaction reactor. The system analyzed in this work was designed and manufactured by Norris Thermal Technologies for use in Big Lagoon, California at a remote mill site. The torrefaction unit was a continuous feed reactor with an electrically heated screw, which served the dual purpose of heating and biomass conveyance. The energy and mass yields were found to be highly correlated in this analysis. The best predictor of both energy and mass yield in this study was the steady state temperature measurement in the biomass product closest …

Load Determination, Strengthening, And Behavior Study Of Prestressed Concrete Channel Bridge Girders In South Carolina, Elhussien Khaled Elbatanouny

Theses and Dissertations

The South Carolina Department of Transportation (SCDOT) is currently engaged in a multi-year effort to assess the structural integrity of its inventory of over 9,000 bridges. This assessment process is expected to result in an increase in the number of bridges that require load postings, repairs, or replacements across South Carolina. This could potentially lead to adverse economic repercussions due to restricted truck routes, bridge closures, repair work, and the need for bridge replacements. To alleviate the escalating costs associated with these challenges, it is imperative to explore methods aimed at reducing the need for load postings and bridge closures …

Upscaling Wetland Methane Emissions From The Fluxnet-Ch4 Eddy Covariance Network (Upch4 V1.0): Model Development, Network Assessment, And Budget Comparison, Gavin Mcnicol, Etienne Fluet-Chouinard, Zutao Ouyang, Sara Knox, Zhen Zhang, Tuula Aalto, Sheel Bansal, Kuang Yu Chang, Min Chen, Kyle Delwiche, Sarah Feron, Mathias Goeckede, Jinxun Liu, Avni Malhotra, Joe R. Melton, William Riley, Rodrigo Vargas, Kunxiaojia Yuan, Qing Ying, Qing Zhu, Pavel Alekseychik, Mika Aurela, David Billesbach, David I. Campbell, Jiquan Chen, Housen Chu, Ankur R. Desai, Eugenie Euskirchen, Jordan Goodrich, Timothy Griffis, Manuel Helbig, Takashi Hirano, Hiroki Iwata, Gerald Jurasinski, John King, Franziska Koebsch, Randall Kolka, Ken Krauss, Annalea Lohila, Ivan Mammarella

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ∼0.52–0.63 and 0.53). …

Transition Supply Chain 4.0 To Supply Chain 5.0: Innovations Of Industry 5.0 Technologies Toward Smart Supply Chain Partners, Mona Mohamed, Karam M. Sallam, Ali Wagdy Mohamed

Neutrosophic Systems with Applications

Industry 4.0 provides businesses with the tools they need to meet difficulties such as fluctuating demand and unstable markets. Additionally, Industry 4.0 refers to the connectivity of computers, various materials, and artificial intelligence (AI) with minimum involvement from humans in the decision-making process. Although Industry 4.0 has a significant potential for the expansion of the industrial sector, it faces several hurdles, including integration of technology, problems with human resources, problems with supply chains, and data security concerns. The human-centered approach that Industry 5.0 took meant that many of the problems that plagued Industry 4.0 could finally be solved. In the …

A Novel Method Of Decision Making Based On Plithogenic Contradictions, Nivetha Martin, Florentin Smarandache, Sudha S

Neutrosophic Systems with Applications

Plithogenic decision-making models are evolved integrating the Plithogenic modelling approach with various methods of multi-criteria decision-making (MCDM). The earlier Plithogenic based decision methods are primarily based on the degrees of appurtenance. This paper introduces a novel Plithogenic ranking genre of decision-making paradigm based on degrees of contradiction. The method of Decision Making on Plithogenic Contradictions (DMPC) developed in this research work is indigenous and unique as the modeling procedure doesn’t resemble any of the decision methods. This simple and logical approach proposed in this paper is applied in making optimal decisions on supplier selection. The proposed contradiction based Plithogenic model …

Heart Disease Prediction Under Machine Learning And Association Rules Under Neutrosophic Environment, Ahmed A. El-Douh, Songfeng Lu, Ahmed Abdelhafeez, Ahmed M. Ali, Alber S. Aziz

Neutrosophic Systems with Applications

Early identification and precise prediction of heart disease have important implications for preventative measures and better patient outcomes since cardiovascular disease is a leading cause of death globally. By analyzing massive amounts of data and seeing patterns that might aid in risk stratification and individualized treatment planning, machine learning algorithms have emerged as valuable tools for heart disease prediction. Predictive modeling is considered for many forms of heart illness, such as coronary artery disease, myocardial infarction, heart failure, arrhythmias, and valvar heart disease. Resource allocation, preventative care planning, workflow optimization, patient involvement, quality improvement, risk-based contracting, and research progress are …

Optimal Agricultural Land Use: An Efficient Neutrosophic Linear Programming Method, Maissam Jdid, Florentin Smarandache

Neutrosophic Systems with Applications

The increase in the size of the problems facing humans, their overlap, the division of labor, the multiplicity of departments, as well as the diversity of products and commodities, led to the complexity of business and the emergence of many administrative and production problems. It was necessary to search for appropriate methods to confront these problems. The science of operations research, with its diverse methods, provided the optimal solutions. It addresses many problems and helps in making scientific and thoughtful decisions to carry out the work in the best way within the available capabilities. Operations research is one of the …

Design And Implementation Of An Optimization Platform For Common Fixed Photovoltaic Systems, Amro Ahmad Zahrawi

Mechanical Engineering Theses

Most household photovoltaic (PV) panels are installed in a fixed arrangement (fixed-type) based on a rule of thumb that comes from experience. The azimuth angle is usually set facing south with a tilt angle equivalent to the location's latitude. However, research shows that this is not the best for all geographical locations and during all hours of the day. Consequently, this brings up the hypothesis that optimizing the PV system's azimuth and tilt angles would ensure that the PV panel produces the most possible output as it is adjusted to face the sun most effectively during peak sunlight hours. This …

Heterostructure Engineering In Electrode Materials For Sodium-Ion Batteries: Recent Progress And Perspectives, Eric Gabriel, Chunrong Ma, Kincaid Graff, Angel Conrado, Dewen Hou, Hui Xiong

Materials Science and Engineering Faculty Publications and Presentations

Sodium-ion batteries (SIBs) have stepped into the spotlight as a promising alternative to lithium-ion batteries for large-scale energy storage systems. However, SIB electrode materials, in general, have inferior performance than their lithium counterparts because Na⁺ is larger and heavier than Li⁺. Heterostructure engineering is a promising strategy to overcome this intrinsic limitation and achieve practical SIBs. We provide a brief review of recent progress in heterostructure engineering of electrode materials and research on how the phase interface influences Na⁺ storage and transport properties. Efficient strategies for the design and fabrication of heterostructures (in situ methods) …

Towards Agile Academia: An Approach To Scientific Paper Writing Inspired By Software Engineering, Tyler Procko

Doctoral Dissertations and Master's Theses

The construction of scientific papers is performed in service of the greater scientific community. This iterative process is, in effect, an academic economy, where all members benefit from well-written papers. However, many published scientific papers are poorly written; they often lack sufficient detail to allow replication, there is improper usage of citations or a lack of regard to relevant work, reporting is vague or without linked empirical data to allow verification, figures do not correspond to text or are non-sensical, literary elements, e.g., bulleted lists, are used ineffectively, formatting renders certain sections unreadable, and grammatical errors abound. The issues of …

Introduction To Vacuum Technology, David M. Hata, Elena V. Brewer, Nancy J. Louwagie

Milne Open Textbooks

Vacuum systems are critical to many industries. They are vital to establishing required process pressures, establishing a clean process environment, and removing reaction by-products from the process chamber. This text, a revision and expansion of David Hata’s Introduction to Vacuum Technology published in 2008, addresses basic topics in vacuum technology for individuals tasked with maintaining vacuum systems and instructors teaching technician-level courses. The topics are carefully curated to the needs of technicians in a production environment and the types of vacuum systems used, and the accompanying laboratory manual and instructor’s guide support the delivery of lecture-laboratory courses.

This book approaches …

Prirpt: Practical Blockchain-Based Privacy-Preserving Reporting System With Rewards, Rui. Shi, Yang Yang, Huamin. Feng, Feng. Yuan, Huiqin. Xie, Jianyi. Zhang

Research Collection School Of Computing and Information Systems

In order to obtain evidence of a crime timely, most authorities encourage whistleblowers to provide valuable reports by rewarding them with prizes. However, criminals will try their best to delete or tamper with the reports and even threaten and revenge the whistleblowers to escape punishment. Hence, to make the reporting system work, it is essential to ensure the integrity of reported messages and the anonymity of the reporting and rewarding procedures in the reporting system. Most existing schemes for this problem are generally based on ring signatures, which incur high computational overhead and imperfect anonymity. In this paper, we introduce …

Objectfusion: Multi-Modal 3d Object Detection With Object-Centric Fusion, Q. Cai, Y. Pan, T. Yao, Chong-Wah Ngo, T. Mei

Research Collection School Of Computing and Information Systems

Recent progress on multi-modal 3D object detection has featured BEV (Bird-Eye-View) based fusion, which effectively unifies both LiDAR point clouds and camera images in a shared BEV space. Nevertheless, it is not trivial to perform camera-to-BEV transformation due to the inherently ambiguous depth estimation of each pixel, resulting in spatial misalignment between these two multi-modal features. Moreover, such transformation also inevitably leads to projection distortion of camera image features in BEV space. In this paper, we propose a novel Object-centric Fusion (ObjectFusion) paradigm, which completely gets rid of camera-to-BEV transformation during fusion to align object-centric features across different modalities for …

Owner-Free Distributed Symmetric Searchable Encryption Supporting Conjunctive Queries, Qiuyun Tong, Xinghua Li, Yinbin Miao, Yunwei Wang, Ximeng Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Symmetric Searchable Encryption (SSE), as an ideal primitive, can ensure data privacy while supporting retrieval over encrypted data. However, existing multi-user SSE schemes require the data owner to share the secret key with all query users or always be online to generate search tokens. While there are some solutions to this problem, they have at least one weakness, such as non-supporting conjunctive query, result decryption assistance of the data owner, and unauthorized access. To solve the above issues, we propose an Owner-free Distributed Symmetric searchable encryption supporting Conjunctive query (ODiSC). Specifically, we first evaluate the Learning-Parity-with-Noise weak Pseudorandom Function (LPN-wPRF) …

A Review On Biomass As A Substitute Energy Source: Polygeneration Influence And Hydrogen Rich Gas Formation Via Pyrolysis, Tawanda Matamba, Arash Tahmasebi, Jianglong Yu, Alireza Keshavarz, Hussein R. Abid, Stefan Iglauer

Research outputs 2022 to 2026

Hydrogen rich gas production and advantages of polygeneration during biomass conversation through pyrolysis were extensively reviewed in this paper. Different innovative pyrolysis setups and the effect of reaction conditions such as pressure, temperature, catalyst type, biomass type, and reactor type on the formation of hydrogen and other value-added chemicals has been exploited. High temperatures and pressures together with application of catalysts was reported to favour the enhancement of hydrogen by promoting secondary pyrolysis reactions and hence the production of H2 gas. Compared to one-stage pyrolysis systems, pyrolysis data from two-stage pyrolysis reaction systems reported improved production of hydrogen and value-added …

Optimal Allocation Of Battery Energy Storage Systems To Enhance System Performance And Reliability In Unbalanced Distribution Networks, Dong Zhang, G. M. Shafiullah, Choton K. Das, Kok W. Wong

Research outputs 2022 to 2026

The continuously increasing renewable distributed generation (DG) penetration rate significantly reduces environmental pollution and power generation cost and satisfies society’s rapid growth in electricity demand. Nevertheless, high penetration of renewable DGs, such as wind power and photovoltaics (PV), might deteriorate the system’s efficiency and reliability due to its intermittent and stochastic natures. Introducing battery energy storage systems (BESSs) to the distribution system provides a practical method to compensate for the above deficiency since it can deliver and absorb power when needed. Hence, it is important to determine the optimal allocation of BESS to achieve maximum assistance in the grid. This …

Unlocking Market Secrets: Revealing Wholesale Electricity Market Price Dynamics With A Novel Application Of Spectrum Analysis, Martin J. Maticka, Thair S. Mahmoud

Research outputs 2022 to 2026

Understanding market participants' competitive behaviour is essential for optimising financial performance in liberalised electricity markets. However, this is challenging due to complex market structures, generation dependent on different primary energy sources and lack of transparency. This paper introduces a novel approach using power spectrum analysis applied to wholesale electricity markets to uncover hidden patterns. Applying this novel method to the Western Australian Wholesale Electricity Market (WEM) revealed periodic cycles in different fuel types and technologies that offered insights into competitor behaviour not immediately evident in the dataset. Surprisingly, the approach uncovered that in a power system with high penetration of …