Mechanical Engineering Commons^™

Autonomous Driving Trajectory Prediction, Carlos Funes

Undergraduate Research Symposium Lightning Talks

Autonomous driving is undoubtedly one of the world's most revolutionary technologies, opening the door to a more secure traffic environment. This innovation has led to vehicles being able to drive by themselves without the necessity of a person behind the wheel, as well as cruise control, lane-keeping assist, and automatic emergency braking. Unfortunately, there is still plenty of work before autonomous driving becomes more popular among drivers. While at UNLV as an undergraduate student/research assistant, one of my goals is to learn how these technologies work to bring ideas into the automotive industry by refining solutions to problems within these …

Computational Design Of Complex Concentrated Alloys, Hamid Sharifi

Doctoral Dissertations

A high-throughput parameterization of modified embedded atom model (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn was carried out using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics. Utilizing the MEAM interatomic potentials and a Monte Carlo scheme, phase segregation in the CrNiCo, CuNiCr and CuNiCo fcc alloys …

Machine Learning-Driven Process Analysis And Optimization In Solid-State Welding And Fusion-Based Additive Manufacturing, Radif Uddin Ahmed

Master's Theses

In the modern era of advanced manufacturing, optimizing process parameters is pivotal in ensuring the quality and reliability of sophisticated component fabrication. This study presents a novel, data-driven approach to parameter optimization in two cutting-edge manufacturing techniques: Friction Stir Welding (FSW) and Laser Powder Bed Fusion (LPBF). By leveraging machine learning methodologies, this research addresses the critical challenge of efficiently determining optimal process parameters, a task traditionally relying on time-consuming and resource-intensive trial-and-error methods. This study will lead to a robust data-driven framework for process analysis of more advanced manufacturing techniques like the Additive Friction Stir Deposition (AFSD) process. Friction …

Lithicone-Protected Lithium Metal Anodes For Lithium Metal Batteries With Nickel-Rich Cathode Materials, Ridwan A. Ahmed, Kevin V. Carballo, Krishna P. Koirala, Qian Zhao, Peiyuan Gao, Ju-Myung Kim, Cassidy S. Anderson, Xiangbo Meng, Chongmin Wang, Ji-Guang Zhang, Wu Xu

Mechanical Engineering Faculty Publications and Presentations

The high energy density advantage of lithium (Li) metal batteries (LMBs) makes them increasingly desirable; however, problems such as strong reactivity and dendrite growth of Li metal anode limit their practical uses. In this work, a novel Li-containing glycerol (LiGL) or lithicone protection layer on a 50 μm thick Li metal anode is employed for improving the performance of LMBs. This LiGL layer was accurately deposited via a molecular layer deposition (MLD) process at 150°C, using lithium tert-butoxide and glycerol as precursors. The as-formed LiGL coating layer is highly tunable in its thickness by simply adjusting MLD cycles and shows …

Review Of Wood Drying Technologies, Mohamed Salah Elmetwaly, Lotfy Hassan Rabie Saker, Mohamed Sameh Salem

Journal of Engineering Research

Abstract- This article provides a comprehensive review of drying optimization in data centers by examining the limitations of drying methods and discussing advances proposed by scientists through whom we can provide a comparison between different drying systems with an emphasis on improving energy efficiency and thermal performance. Wood drying under atmospheric pressure has many advantages, including the ability to dry at lower temperatures (by reducing the likelihood of some drying defects), significantly reduced drying times, color preservation, increased energy efficiency, better control of volatile organic compound emissions, and the ability to dry very large cross sections. Previous studies have achieved …

Basic Psychological Needs Satisfaction And Well-Being Among Seafarers: An Investigation Of Interaction Effects Through The Lens Of Self-Determination Theory, Nong Vuong Phi, Kung Don Ye, Feng Ming Tsai, Hsiao Chao Hsieh, Shiou-Yu Chen

Journal of Marine Science and Technology–Taiwan

Enhancing employee well-being is a primary goal for enterprise sustainable development. Although seafarers represent a major human resource in the maritime industry, the distinctive demands of their profession often compel them to compromise on certain elements in fulfilling their basic psychological needs, thereby contributing to mental health challenges. Recently, COVID-19 and its associated border control measures have prolonged the voyages of seafarers, drawing public attention to the topic of seafarer well-being. In this study, self-determination theory was used to explore the effects of autonomy, competence, and relatedness as fundamental psychological needs on seafarer well-being. After the independent effects of these …

Advancements In The Programmable Hyperspectral Seawater Scanner Measurement Technology For Enhanced Detection Of Harmful Algal Blooms, John J. Langan, Jungyun Bae

Michigan Tech Publications

The Programmable Hyperspectral Seawater Scanner (PHySS) represents a significant breakthrough in monitoring harmful algal blooms (HABs), specifically targeting the “Florida red tide” caused by Karenia brevis. By utilizing a Fourth-Derivative Spectral Similarity Index (SI), this study establishes a strong positive correlation between the SI and phytoplankton counts, underscoring the PHySS’s potential for early detection and effective management of HABs. Our findings suggest that the PHySS could act as a predictive tool, offering crucial lead time to mitigate the ecological and economic repercussions of blooms. However, this study also identifies certain limitations of the PHySS technology, such as its inability to …

Surrogate Models For Stress-Strain Mapping Of Microscale Physics, Samuel Roach, Dr. Eric Ocegueda

College of Engineering Summer Undergraduate Research Program

•Learn the difference between different neural networks within machine learning (ML) •Develop a working understanding of the ML tool Pytorch and machine learning operator: Recurrent Neural Operator •Use MATLAB to create and process time dependent stress/strain matrices to display the hyper-parameters for different RNOs •Apply RNO to train the strain-stress mapping of tri-laminate and granular cases

Seismic Resilience Of Timber Homes, Melia R. Costa

College of Engineering Summer Undergraduate Research Program

The vast majority of residential buildings in California are wood-frame structures. A home is typically a very large investment for families, and damage to the home can be detrimental to a family’s economic success. Thus, reducing the economic impacts of an earthquake on residential timber housing is crucial. A full scale, two-story section of a residential timber house is in construction in the Parson’s Geotechnical and Earthquake Engineering Laboratory on the Cal Poly campus in San Luis Obispo, California. Once built it will be put through earthquake simulation tests on a shake table with various magnitudes of seismic activity. Next, …

Assessing The Impact Of Femur Morphological Variations On Pediatric Hip Joint Biomechanics Using Statistical Shape Modeling, Tamara Chambers

Doctoral Dissertations and Master's Theses

This dissertation aimed to (1) quantify morphological variations in the pediatric hip joint and (2) evaluate the sensitivity of an infant musculoskeletal model (MSM) to these variations, considering hip joint center estimation errors. A shape statistical model (SSM) of decedent infant femurs from the Ortolani collection was created using ShapeWorks, capturing key morphological features, such as variations in the femoral neck-shaft and anteversion angles. Seven synthetic femurs were generated from the SSM to create SSM-informed MSMs, which were systematically evaluated through kinematics and kinetics analyses in OpenSim. Incorporating the SSM led to slight changes in the pediatric MSMs’ kinematics but …

An Optimal Schedule Recovery Model For Transportation Carriers Under Uncertain Typhoon Disruption Periods, Yi-Chun Chen, Shangyao Yan

Journal of Marine Science and Technology–Taiwan

Due to the unsettled weather conditions caused by typhoons, it is not possible to forecast the time when a typhoon will arrive or depart accurately. The uncertainty regarding the duration of typhoon disruptions makes it challenging for transportation carriers to efficiently adjust their schedules. In this study, to deal with the problem of airline fleet rerouting, flight rescheduling, and passenger reassignment for uncertain disruption periods caused by a typhoon, we utilize network flow techniques with the concept of probability to construct a stochastic model for minimizing the total operating costs. A heuristic algorithm based on the divide-and-conquer technique is adopted …

Prediction Of Mooring System Characteristics Of The Floating Barge Using Deep Neural Networks, Janghoon Seo, Dong-Woo Park

Journal of Marine Science and Technology–Taiwan

The present study establishes deep learning models to predict the tensions and inclinations of mooring lines of a floating barge and verifies applicability of these models. Hydrodynamic and mooring analyses are conducted on the dataset used for the deep learning models. Three types of neural network models include a deep neural network (DNN) with input data representing the six degrees of freedom motions of a floating barge, convolutional neural network (CNN) with input images of the floating barge and mooring lines on a horizontal plane, and hybrid neural network (HNN) that consolidates the characteristics of DNN and CNN models. The …

Research On Development Status And Strategy Of Advanced Materials In Guangdong-Hong Kong-Macao Greater Bay Area, Ziwei Zhao, Can Wang, Weihua Wang, Qingli Huang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Advanced materials are an important source of new quality productivity. Guangdong-Hong Kong-Macao Greater Bay Area is now facing the internal and external pressure of manufacturing upgrading, and there is an urgent need to play the leading and supporting role of advanced materials in the construction of modernized industrial system. This study combs through the basic situation of the development of materials science and industry in Guangdong-Hong Kong-Macao Greater Bay Area, analyzes its advantages, characteristics and problems in depth, and puts forward a number of suggestions around how to develop materials science, technology, and industry in the Greater Bay Area.

Implementing Reactivity In Molecular Dynamics Simulations With Harmonic Force Fields, Jordan J. Winetrout, Krishan Kanhaiya, Josh Kemppainen, Pieter J. In ‘T Veld, Geeta Sachdeva, Ravindra Pandey, Behzad Damirchi, Adri Van Duin, Gregory Odegard, Hendrik Heinz

Michigan Tech Publications

The simulation of chemical reactions and mechanical properties including failure from atoms to the micrometer scale remains a longstanding challenge in chemistry and materials science. Bottlenecks include computational feasibility, reliability, and cost. We introduce a method for reactive molecular dynamics simulations using a clean replacement of non-reactive classical harmonic bond potentials with reactive, energy-conserving Morse potentials, called the Reactive INTERFACE Force Field (IFF-R). IFF-R is compatible with force fields for organic and inorganic compounds such as IFF, CHARMM, PCFF, OPLS-AA, and AMBER. Bond dissociation is enabled by three interpretable Morse parameters per bond type and zero energy upon disconnect. Use …

Integrated Environmental Vulnerability Assessment And Adaptation Strategies For Coastal Areas Under Sustainable Development, Lien-Kwei Chien, Yu-Chi Li, Chia-Feng Hsu

Journal of Marine Science and Technology–Taiwan

This research focuses on the holistic management and environmental vulnerability of coastal areas in Taiwan within the framework of sustainable development. With economic and social growth gravitating towards coastal regions, the strain on the natural environment is increasing. Therefore, discovering a balance between economic progress and environmental conservation is paramount. To decipher the vulnerability of Taiwan's coastal zones, this study first defines ‘Integrated Environmental Vulnerability of Coastal Areas.’Key vulnerability factors were identified across environmental, social, and economic dimensions. Seven core determinants were determined using the Fuzzy Delphi method: biodiversity, coastal erosion, water pollution, population density, population aging, land utilization, and …

Evalution Of The Ability To Infer Tilt Angle And Size Distributions Of Fish Using A Broadband Scientific Echosounder Based On Simulation, Jing Liu

Journal of Marine Science and Technology–Taiwan

The biological information, such as species, size, and tilt angle, is crucial for converting the echo data into biomass information in acoustic surveys. Typically, the information can be obtained through trawl net sampling or underwater camera observations. However, both methods have some limitations. To overcome these limitations, scientists have utilized inversion methods with multi-frequency and broadband echosounders to derive biological information about fish, plankton, and krill. However, evaluating the reliability and accuracy of these inversion methods has been challenging due to the difficulty in obtaining accurate biological information. In this study, a numerical simulation method was used to generate fish …

Performance Studies Of An Axial Flow Waterjet Pump Using An Unsteady Reynolds-Averaged Navier-Stokes Model, Stephen E. Monroe, Junfeng Wang, Chunlei Liang

Northeast Journal of Complex Systems (NEJCS)

In this study, an Unsteady Reynolds-Averaged Navier-Stokes (URANS) model is demonstrated its suitability for studying the flow and performance of open marine propellers and waterjet pumps. First, the accuracy of the URANS model is validated by studying turbulent flow past counter-rotating propellers (CRPs). Specifically, experimental data from Miller (1976) is employed for comparison against the URANS results. Subsequently, URANS is used to study the flow and performance of an Office of Naval Research (ONR) axial flow waterjet pump (AxWJ-2). Due to the large number of degrees of freedom for both simulations, parallel computations over 80 cores are performed. For the …

A Marine Knowledge System For Ocean Affairs: Integrating Data, Evaluating Usage, And Enabling Sustainable Marine Management, Yu-Jen Pan

Journal of Marine Science and Technology–Taiwan

This study presents the evolution and assessment of the Marine Knowledge Education System (MKES), designed to improve user acceptance among students in professional marine science courses in Taiwan. The MKES leverages real-world maritime cases from the General Coast Guard Administration and is built upon existing technologies like cloud services, social networks, and data analysis tools. The technology acceptance model (TAM) provides the theoretical underpinning for the assessment of user confidence. Data was collected from 190 participants through purposive sampling. Path analysis confirmed all hypothesized relationships within the TAM with statistical significance (p < 0.001). Additionally, paired-sample t-tests revealed a significant increase in student acceptance of the MKES after integrating it into the marine science curriculum. These findings underscore the capacity of the MKES as a digital learning tool to enrich course pedagogy and improve student learning outcomes, thereby offering valuable support in advancing the education of professional marine managers.

Electrified Membrane For Water Treatment And Resource Recovery: Advancing Multiscale Strategies In Gas-Involving Reactions, Jianan Gao

Dissertations

Multifunctional, modular, and scalable water treatment technologies that operate without chemical additives are crucial for addressing global water pollution challenges. While traditional membrane-based separation processes are crucial for ensuring clean water supplies, they primarily focus on pollutant removal rather than on the upcycling of pollutants into valuable resources. Electrified membrane filtration presents a robust alternative, utilizing minimal or no chemical additives and harnessing electrical power to directly reduce contaminants or produce reactive oxidants or reductants on-site.

This dissertation is dedicated to the development of innovative electrochemically reactive membranes designed to address three major challenges: (1) the engineering of electrocatalysts with …

Evaluation Of Business-Driven Reference Architecture For Big Data Analytics Implementation By Public Sector Organizations In Resource-Constrained Setting: A Case Study Of Uganda, Matendo Didas

Tanzania Journal of Engineering and Technology (TJET)

Big Data Analytics (BDA) is a new area at the nexus of agenda, public sector organizations, and government business. It may satisfy the growing need for trustworthy, cost-effective services in the public sector for better, more informed decision-making processes. BDA has been proposed on the planning schedules of several public sector organizations and the government. Therefore, from the previous work, using Uganda as a case study, specifically the Uganda Bureau of Statistics (UBOS), Ministry of Health (MoH), and Ministry of Education and Sports (MoES), this study aims to evaluate a designed Business-Driven Reference Architecture for Big Data Analytics Implementation (BRABDAI) …

Ai-Driven Innovation And Development In Manufacturing: An Overview Of Trends, Issues, And Suggestions, Rongping Mu, Jingjing Guo, Yuchen Li, Qiang Li, Chun Jiang, Ze Feng, Guowei Dong

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence technology has become a key force in driving innovation and development in global manufacturing industries, and its application in production automation, intelligent management, and other areas has become an important trend for innovation and development of manufacturing in all countries. This study comprehensively analyzes the innovation and development trend driven by artificial intelligence in global manufacturing, outlines the policies and measures of major countries in promoting the innovation and development of the manufacturing industries driven by artificial intelligence. It also points out the current situation and problems of the manufacturing’s innovation and development driven by artificial intelligence in …

Data Communication Over Power-Lines: A Review On Technical, And Applications Challenges, Abdi Abdalla

Tanzania Journal of Engineering and Technology (TJET)

This paper presents a review study on the data communication over power-lines, commonly referred to as power-line carrier, power-line communication (PLC), mains communications, or power-line digital subscriber line (PDSL). This study examines the technical and application advantages and challenges associated with adopting PLC as a preferred alternative technology for wideband or broadband data communication. The broader coverage area of the PLC network gives it a distinct advantage over other communication network technologies. Additionally, implementing a communication system using the existing power-line network is more cost-effective and less time-consuming compared to constructing a new network from scratch. However, the primary challenge …

Assessment Of Web Security Vulnerabilities For Common Open Source Virtualization Software, Said Ally

Tanzania Journal of Engineering and Technology (TJET)

Open-source hypervisors have emerged as an integral technology for virtualizing server resources in cloud and data center computing. Hypervisor security efficiency is determined by virtual machine isolation, which is a de facto adoption factor in the selection process, as well as its ability to respond to web attacks. This paper assesses the security performance of Proxmox VE and XenServer for type 1 hypervisors, and Kernel Virtual Machine and Oracle Virtual Box for type 2 hypervisors. Security analysis was conducted using common exposures extracted from vulnerability databases and mapped against the OWASP 2013 and 2017 projects. For clarity, experiments were carried …

Investigations Of Cell Tower Antennas Parameters On Reduction Of Radio Frequency Radiation Levels From Radio Base Stations, Florence U. Rashidi

Tanzania Journal of Engineering and Technology (TJET)

The widespread deployment of mobile cellular base stations in populated areas has raised public health concerns due to increased exposure to radio frequency (RF) radiation emissions. Exposure to high levels of RF radiation can have potential thermal and non-thermal biological effects. Optimizing the configuration of cell tower antenna parameters is crucial for mitigating these radiation levels. This study therefore aims at systematically investigating the influence of different cell tower antenna parameters on reducing the RF radiation levels from mobile base stations. Field measurements were conducted at two cell sites shared by multiple mobile operators. Electric field strengths were measured at …

Assessing The Importance Of Air-Decking Blasting In Controlling Bigv At An Open Pit Gold Mine In Tanzania Using Ann Model, Karim R. Baruti

Tanzania Journal of Engineering and Technology (TJET)

Air-decking blasting technique is used to control blast induced ground vibration (BIGV) in several mines including open-pit gold mines located in Tanzania. While the importance of air-deck to control BIGV is practically evident, theoretical models such as BIGV prediction models cannot be used to assess the importance of air-decking. The main objective of this study was to assess the importance of the air-decking blasting technique to control BIGV using the artificial neural network (ANN)Model. To achieve this objective, ANNs were modeled and trained to learn the pattern of data using Multilayer Perception with Back Propagation to predict BIGV. The main …

Modular Approach To Soft Mobile Robots, Dimuthu Kodippili Arachchige

College of Computing and Digital Media Dissertations

Soft robot locomotion is a highly promising but under-researched subfield within the field of soft robotics. The compliant limbs and bodies of soft robots offer numerous benefits, including the ability to regulate impacts, tolerate falls, and navigate through tight spaces. These robots have the potential to be used for various applications, such as search and rescue, inspection, surveillance, and more. The state-of-the-art still faces many challenges, including limited degrees of freedom, a lack of diversity in gait trajectories, insufficient limb dexterity, limited payload capabilities, lack of control methods, etc. To address these challenges, this research introduces a modular approach to …

Experimental And Computational Investigation Of Green Laser Propagation Through Turbulent Medium In A Water Tank, Richard Owusu Adansi

Open Access Theses & Dissertations

Turbulence medium poses significant challenges to the propagation of laser beams, impacting applications such as free-space optical communication, remote sensing, and laser weapons systems. Therefore, comprehending and mitigating turbulence effects are vital for enhancing the performance of these systems. Analysis of a strong turbulence impact on electromagnetic wave propagation requires extensive knowledge of the Earth's atmospheric and Oceanic phenomena and Maxwell's electromagnetic theory of light as a propagating wave of electric and magnetic fields. Optical systems' propagation often encounters Strong Turbulence, causing interference and diffraction. Nonetheless, light propagation through randomly fluctuating media has been an exciting and active area of …

Smart Automatic Modal Hammer Predictor–Corrector Approach For Accurate Excitation Of Dynamical Systems, Mohammad Nasr

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

This research introduces an innovative solution that revolutionizes the study of linear and nonlinear dynamical systems—a smart automatic modal hammer. With its affordability and intelligent capabilities, this automatic modal hammer becomes an invaluable tool for research and industry, enabling repeatable strikes with precise force control. This system's significance becomes particularly evident when studying nonlinear systems, which heavily rely on the excitation level for their dynamics. By offering a cost-effective design this proposed system proves to be robust in accelerating research on nonlinear dynamics, providing researchers with an efficient and accessible means to delve deeper into these complex systems. The proposed …

Studies Of Exotic Electronic, Optical, And Electrochemical Properties In Nanoparticle Assembly And Graphene, Jay Min Lim

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

It is well known that exotic properties and phenomena emerge as structural dimensions shrink to nanoscales. We self-assembled one-dimensional chains of gold nanoparticles in solution and quantified the growth process by monitoring the redshift of localized surface plasmon resonance (LSPR). Curiously, the redshift stopped while the chains continued to rearrange as manifested by gradual reduction in the LSPR peak. Using electromagnetic simulations, we quantitatively explained the phenomena as a rapid “addition-polymerization” followed by a sharp transition to “condensation-process.” Next, recognizing the significant electric field enhancement in the interparticle gap, a photoluminescent-active Eu³⁺ ion was used to probe Surface-Enhanced Photoluminescence …

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

Doctoral Dissertations and Master's Theses

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