Engineering Commons^™

Drag Reduction In Ground Vehicles Using A Model Porous Medium, Abdullah Ikram Nabi

Master’s Theses

This research investigates aerodynamic drag reduction on a 25° Slanted Ahmed Body (SAB) by integrating porous media model rods through combined experimental and computational methods at a Reynolds number of 1.16×10⁴. Two porous media configurations: short rods (6.75% of the model height) and long rods (20.0% of the model height), both featuring cylindrical rods with 80% porosity, were systematically compared against a baseline SAB. In-depth analyses were performed to investigate the wake flow topology, recirculation region characteristics, pressure coefficient distribution, Reynolds stress distributions and drag coefficient. Experimental investigations employed particle image velocimetry for precise flow visualization, while Reynold Averaged Navier-Stokes …

Using Post-Supercritical Co2-Assisted Method To Deposit Niep Alloy Coating On The Micro-Arc Oxidation Layer Of Az31 Magnesium Alloy And Its Corrosion Behavior Analysis, Kang-Yu Liao, Hung-Hua Sheu, Ming-Yuan Lin, Ming-Chih Kuo, Po-Hsun Wu, Hung-Bin Lee

Journal of Marine Science and Technology–Taiwan

In this study, a Ni-P alloy coating was deposited on the micro arc oxidation (MAO) layer of AZ31 magnesium alloy to improve its corrosion resistance. The MAO layers were prepared under different operated voltages from 300 to 400 V. The results indicated that the optimize operated parameters for MAO layer is at 350 V, the MAO coatings had the most compact microstructure and superior corrosion resistance. In order to improve the corrosion resistance of MAO coating, this study chose to deposit Ni-P alloy coating on the surface of MAO coating via the post supercritical CO₂-assisted electroless plating (PSC-CO …

The Effect Of Feedback On A Remote Operator’S Maneuvering Control For Mass Remote Navigation Competency, Hyoseon Hwang, Ik-Hyun Youn

Journal of Marine Science and Technology–Taiwan

The rapid advancement of Maritime Autonomous Surface Ships (MASS) technology has highlighted the growing need for Remote Operators (ROs) to manage MASS effectively. ROs possess specialized competencies in areas such as situational awareness, crisis management, and system operation. Despite the introduction of competency-based training and assessment in the maritime sector through the international convention on standards of training, certification, and watchkeeping for seafarers convention, the framework's implementation remains incomplete, particularly in remote operator training for MASS. This study is purpose to identify which competencies improve rapidly with performance feedback and which improve slowly. This study conducted an experiment to quantitatively …

Evaluation Of Carbon Sequestration In Seagrass Meadows Of Kenting: A Comparative Study With Penghu And Dongsha Island, Zih-Wei Tang, Huei-Fen Chen, Jordi Mahardika Puntu, Ping-Yu Chang, Li Lo, Jian-Jhih Chen, Wen-Chen Chou, Lan-Feng Fan, Ying-Ju Chang

Journal of Marine Science and Technology–Taiwan

This study investigates the controlling factors of carbon sequestration (CS) in seagrass bed sediments across three distinct environments in Taiwan: the Kenting (KT) coastal area, the Penghu (PH) open inner bay, and the Dongsha (DS) Atoll lagoon. Actual measurements of the substrate depth beneath the sediment and ground-penetrating radar (GPR) scans of the beach reveal that the coral reef bedrock in KT slopes landward. A field survey of the seagrass area in KT was conducted, and three cross-sectional profiles were analyzed to determine their topography, yielding a median sediment thickness of 88.2cm. Based on these measurements, the sediment volume was …

Calculation Of Aquifer Transmissivity From Borehole Resistance Measurements And Pumping Test Results, Fen-Rong Yang, Chien-Wei Huang, Tien-Kuen Huang

Journal of Marine Science and Technology–Taiwan

Transmissivity is a crucial hydrogeological parameter for evaluating groundwater resources. This parameter is conventionally evaluated using pumping tests; however, these tests are costly and can be conducted at few sites. Many researchers have used ground resistance and pumping test data to estimate various hydrogeological parameters. In this study, borehole resistance survey and pumping test data collected by the Taiwan Groundwater Monitoring Network were used to establish the relationship between transmissivity and formation factor for aquifers in the Zhuoshui River alluvial fan. This relationship was then used to estimate the water output of the aforementioned aquifers in a cost-effective manner from …

A Neural Network-Based Sliding Mode Adaptive Control System For Unmanned Surface Vehicles, Sun Qiaomei, An Liang, Jiang Linglin

Journal of Marine Science and Technology–Taiwan

Over the past decades, numerous studies have explored the use of autonomous unmanned surface vehicles (USVs). Successful USV operation requires a robust tracking control system to perform a range of tasks. However, USV dynamics are uncertain, time-varying, and nonlinear. This paper presents a neural network-based sliding mode adaptive control (NNSMAC) system to enhance USV tracking performance. Trajectories were generated using spline and polynomial interpolation based on a set of N predefined waypoints. Simulation results show that the proposed method outperforms traditional sliding mode control in error reduction, enabling more effective tracking.

A Blueprint To Greener Shorelines: Advancing The Effectiveness, Sustainability, And Widespread Adoption Of Coastal Nature-Based Solutions Through Transdisciplinary Research, Taylor M. Sloey, Sierra Hildebrandt, Rebecca L. Morris, Matthew V. Bilskie, Aaron Bland, David Bushek, Gabriella Dipetto, Daniel Elefant, Vincent Encomio, Ramin Familkhalili, Christine Hladik, Danielle Kreeger, Avery B. Paxton, Cindy M. Palinkas, Latina Steele, Andrew Scheld, Daisuke Taira, Jason D. Toft, Armando J. Ubeda, Christine Whitcraft, Donna Marie Bilkovic

Biological Sciences Faculty Publications

Coastal nature-based solutions (NbS) have emerged as powerful tools to enhance sustainable development and ecological restoration goals. As a rapidly growing field spanning across social, political, ecological, economic, and engineering disciplines, it is critical that researchers working in coastal NbS regularly attempt to identify emerging focal areas for scientific inquiry. Following the 27th Biennial meeting of the Coastal and Estuarine Research Federation, we provide a transdisciplinary perspective (including biologists, engineers, oceanographers, geoscientists, economists, and facilitators of workforce training programs) of pertinent research questions that, if answered, will advance the effectiveness, sustainability, and widespread adoption of coastal NbS. These suggestions for …

Expanding The Vibrating Sharp-Edge Spray Ionization Toolkit For Oligonucleotide Characterization, Sultan Mahmud

Graduate Theses, Dissertations, and Problem Reports (ETD)

A gentle or soft Ionization process is a critical component in native mass spectrometry (MS) to lift the biomolecules from the bulk solution into the gas phase environment of the mass spectrometer preserving their shape, topology and non-covalent interactions. Electrospray ionization (ESI) facilitates structural preservation of proteins, nucleic acids and their complexes and as a result it has been extensively used in native MS. However, in negative ion mode, ESI is somewhat limited in sensitivity due to corona discharge effect resulting from the requirement of a high amount of voltage. This often disrupts the ESI process and may not preserve …

Characterization And Optimization Of Sand And Tung Oil-Based Resins For Binder-Jet 3d Printing, Daniel I. Ajiola

College of Graduate Studies: Theses & Dissertations

Binder-jet 3D printing as a transformative technology in additive manufacturing, offers the ability to fabricate complex structures with diverse materials. This thesis investigates the use of a sustainable tung oil-based resin to create composites, exploring the potential for an eco-friendly alternative to synthetic binders.

The aim of this research is to develop and characterize a bio-based resin formulation, using tung oil as the primary binder, for application in binder-jet 3D printing with sand as the reinforcement. The resin formulation was prepared by combining tung oil, n-butyl methacrylate, divinylbenzene, and di-tert-butyl peroxide in precise proportions, ensuring a balanced mixture that supports …

Synthesis And Assessment Of Biobased Acrylated Epoxidized Soybean Oil Resins For Stereolithography 3d Printing Of Microfluidic Devices, Natalie S. Romero Figueroa

College of Graduate Studies: Theses & Dissertations

This research focuses on the development and characterization of a biobased photocurable resin synthesized from soybean oil for use in stereolithography (SLA) 3D printing of microfluidic devices. The study explores a sustainable alternative to petroleum-based resins by performing an acrylation reaction on epoxidized soybean oil (ESO) to produce acrylated epoxidized soybean oil (AESO), which was then formulated into a photocurable resin with the addition of a photo initiator. The fabrication process involved designing microfluidic molds in SolidWorks and printing them using an Elegoo Mars 4 SLA printer under various exposure and layer thickness parameters. The printed samples consisted of microchannels …

In Vitro Microfluidics System For Mechanobiologic Investigations, Michael A. Daanen

Honors Theses

Mechanobiology is an emerging field that aims to study the relationships between mechanical forces and cellular behavior. Such mechanobiological relationships are especially critical in the cardiovascular system, where endothelial cells lining the vasculature align in response to fluid shear stresses from blood flow (Sinha, 2016). Implanted flow devices, diabetes, chronic hypertension, and various other diseases and pathophysiologies alter vessel geometries and flow dynamics. Such alterations impact fluid shear stress and endothelial cell behavior, leading to microcirculatory dysfunction, vessel leakage, and organ failure (Poredos, 2021; Papadaki, 1999; Leitschuh, 1987). To simulate dysfunctional endothelial cell behavior in vitro and evaluate novel therapeutic …

Evaluation Of Practical Methods To Determine If A Karst Creek Is Gaining Or Losing: Case Study Of Leith Creek, Elizabeth Jones

Graduate Theses/Dissertations

Karst landscapes are abundant in Missouri, with features such as caves, springs, and sinkholes that form through the dissolution of limestone. Leith Creek is a small stream in Polk County, Missouri fed by two springs and the shallow unconfined Springfield Plateau aquifer, a highly karstified aquifer which is made up of limestone and minor interbedded shale-mudstone units. To determine if Leith Creek is gaining or losing, stream flow, water chemistry and temperature sensors were monitored. Stream flow results required multiple visits to take measurements while temperature sensors required two visits, one to install the dataloggers and another to remove the …

Integrated Valuation Of The Ecological, Social And Economic Benefits Provided By A Multifunctional Nature-Based Solution, Laura Costadone, Shan Zhang

ODU Articles

Nature-based Solutions (NbS) offer multifunctional approaches to address climate change and environmental challenges, providing a sustainable alternative to traditional gray infrastructure. Despite their promise, widespread adoption remains limited, in part due to an incomplete understanding of their full costs and benefits relative to conventional infrastructure. Traditional benefit–cost analyses often overlook non-monetized benefits and the interconnected ecosystem services provided by NbS. This study introduces a methodological approach to quantify both the physical and monetary value of ecosystem services and co-benefits delivered by an NbS project. We applied an integrated valuation framework to a case study in Virginia Beach, VA, USA, where …

Heuristic Approaches For Coordination Of Heterogeneous Robotic Systems In Harvesting Automation With Size Constraints, Hyeseon Lee

Dissertations, Master's Theses and Master's Reports

This thesis presents the development of path planning algorithms for the coordination of heterogeneous robotic systems while considering size constraints. The objective is to generate practical and efficient solutions for real-world applications. The use of heterogeneous collaborative robots is beneficial in many applications, such as transportation operations in warehouses or manufacturing environments, surveillance, and monitoring, and task allocation and path planning are critical techniques that need to be addressed to deploy in real-world applications. This research focuses on automating lavender harvesting, where robots with varying capabilities must collaboratively navigate complex field layouts to efficiently complete harvesting tasks.

The problem considers …

Foreign Object Detection System Development Using Edge Devices Integrated With Quadcopter Autonomous Tracking, Chi-Chia Huang, Ching-Hung Lee

Journal of Marine Science and Technology–Taiwan

This study proposes an all-weather autonomous foreign-object detection system capable of operating in low-light environments. We used a highly mobile quadcopter equipped with an edge-computing device as the inspection platform. On the software side, we integrated a low-light image enhancement model, a path-tracking algorithm, and a foreign object detection model to achieve rapid object detection. A lightweight, low-light image-enhancement model reduces the need for additional lighting equipment, thereby enabling reliable detection under low-light conditions. The path-tracking algorithm integrates a lightweight semantic segmentation model with traditional image-processing techniques to establish flight paths efficiently and reliably. The foreign-object detection component employs state-of-the-art …

Optimization Of Underactuated Ship Sliding Mode Controller Based On The Ddpg Algorithm, Lin Ma, Mingzhe Qi, Shicai Chen, Hongwei Bian, Jian Zhang

Journal of Marine Science and Technology–Taiwan

Due to the development of ship intelligence, the demand for precise controllers is increasing day by day. In traditional design, the trial-and-error method often leads to the use of inaccurate controller parameters, causing oscillations when environmental disturbances are present. To address these issues, this study introduces deep learning to optimize the controller parameters, particularly those used for sliding mode controllers in underactuated ships. We adopt the Deep Deterministic Policy Gradient (DDPG) algorithm based on the Actor Critic framework. By freely setting the reward function to match the control objective, the trained model can output more accurate controller parameters, with the …

Experiments On Aluminum Alloy Additive Layer Waam Lamination Using The Arc Current Reduction Technique, Jukkapun Greebmalai, Eakkachai Warinsiriruk, Chao-Hsiang Hsiao, Yin-Tien Wang

Journal of Marine Science and Technology–Taiwan

Recent advancements in additive manufacturing have been propelled by innovations in processes, materials, and fabrication techniques. This study specifically focuses on the optimizing Wire and Arc Additive Manufacturing (WAAM) within the Gas Metal Arc Welding (GMAW) process. The goal is to build laminated layers using aluminum alloy from the five-thousand series. In this research, a novel technique is introduced that employs a reduced arc-current during the additive layer progress for aluminum alloys, along with a double pulse current in the GMAW process to enhance weldability. The material used for addition is ER5356 aluminum wire, which is applied to an Al-5083 …

An Optimization Model For Supporting Bunkering Decisions In Bulk Shipping, Chung-Cheng Lu, Hui-Chieh Li, Hung-Yu Chen

Journal of Marine Science and Technology–Taiwan

This study addresses a bunkering optimization problem for bulk shipping carriers that explores route deviation to find optimal bunkering locations and amounts. A mixed integer linear programming (MILP) model is developed to determine optimal bunkering decisions that minimize total operating costs, including total daily operating costs, bunkering costs, port charges and surcharges, while observing time window constraints at loading/unloading ports. The proposed model is evaluated using instances generated from real data provided by H company with its operational headquarters in Taipei, Taiwan, which operates a fleet of handysize ships in East and South Asia. The results indicate that optimization models …

Assessment Of Coastal Navigation Safety: A Case Study Of Boka Bay With Stakeholder Perspectives, Ivan Mraković, Rino Bošnjak

Journal of Marine Science and Technology–Taiwan

The navigational safety of Boka Bay, i.e., a critical maritime area along the Adriatic coast, is of great importance owing to its ecological sensitivity, diverse marine traffic, and significant economic activity. This study provides a comprehensive assessment by analyzing the perspectives of various stakeholders, including seafarers, local pilots, skippers, regulatory authorities, and others engaged in maritime activities within the bay. Using a structured questionnaire survey, both quantitative and qualitative data were collected in formats such as descriptive responses, Yes/No choices, and Likert scale ratings, ensuring a well-rounded understanding of navigational practices and challenges. The data were analyzed using descriptive statistics, …

A Hybrid Model To Assess Commercial Port Resilience In Taiwan, Po-Hsing Tseng, James J.H. Liou

Journal of Marine Science and Technology–Taiwan

Since 2021, international commercial ports have faced unprecedented challenges (e.g., COVID-19 pandemic, Suez Canal congestion), impacting daily life, work, human well-being, properties, the environment, and socio-economic activities. The adaptation capability resilience of international commercial ports to respond to external changes has become crucial. This study develops an expert knowledge-based hybrid multi-criteria decision-making model integrating Best-Worst Method (BWM), Rough Dombi Aggregator, and Combined Compromise Solution (CoCoSo) to evaluate port resilience capabilities, using Taiwan's international commercial ports as a case study. We propose four evaluation dimensions encompassing 13 indicators: detection capability, resistance capability, resource integration capability, and recovery capability. The BWM determined …

An Evaluation Of The Possibility And Effectiveness Of Renewable Energy In Container Terminal At Jinhae New Port, Min-Seop Sim, Yul-Seong Kim, Chang-Hee Lee

Journal of Marine Science and Technology–Taiwan

The international goals of combating climate change and reducing greenhouse gas emissions are driving container terminal operators to adopt renewable energy solutions. This study evaluated the feasibility and effectiveness of introducing renewable energy and eco-fuels for energy independence at the Jinhae New Port Container Terminal, South Korea. Using portfolio analysis, eight renewable energy technologies (solar power, solar thermal energy, wind energy, hydropower, marine energy, geothermal energy, bioenergy, and waste-to-energy) and seven eco-friendly fuels (electricity, liquefied natural gas, liquefied petroleum gas, hydrogen fuel cells, ammonia fuel cells, bioenergy, and hybrid systems) were assessed. Survey data from stakeholders identified solar, wind, and …

Exploring Research And Tools In Ai Security: A Systematic Mapping Study, Sidhant Narula, Mohammad Ghasemigol, Javier Carnerero-Cano, Amanda Minnich, Emil Lupu, Daniel Takabi

School of Cybersecurity Faculty Publications

With the pervasive integration of artificial intelligence (AI) in various facets of modern technology, the importance of AI security has been thrust into the spotlight. The field is rapidly evolving, with new challenges and solutions emerging at a swift pace. However, the breadth and depth of AI security research have not been comprehensively mapped in recent times, presenting a crucial need for an extensive review and synthesis of existing literature. Given the increasing reliance on AI in critical domains such as healthcare, finance, and national security, ensuring the resilience and trustworthiness of these systems is imperative. This survey fulfills the …

Long-Term Traffic Prediction Using Deep Learning Long Short-Term Memory, Ange-Lionel Toba, Sameer Kulkarni, Wael Khallouli, Timothy Pennington

School of Cybersecurity Faculty Publications

Traffic conditions are a key factor in our society, contributing to quality of life and the economy, as well as access to professional, educational, and health resources. This emphasizes the need for a reliable road network to facilitate traffic fluidity across the nation and improve mobility. Reaching these characteristics demands good traffic volume prediction methods, not only in the short term but also in the long term, which helps design transportation strategies and road planning. However, most of the research has focused on short-term prediction, applied mostly to short-trip distances, while effective long-term forecasting, which has become a challenging issue …

Security Enhancement In Uav Swarms: A Case Study Using Federated Learning And Shap Analysis, Sushmitha Halli Sudhakara, Lida Haghnegahdar

School of Cybersecurity Faculty Publications

As cyber-physical systems (CPSs) increasingly integrate physical and digital realms, securing critical infrastructure, such as the Port of Virginia, becomes paramount. Among CPSs, Unmanned Aerial Vehicles (UAVs) are vital for monitoring, communication, and supporting the command and control through remote reconnaissance and surveillance missions. These UAV applications often require coordination, planning, and runtime reconfiguration, traditionally managed by human decision-makers. However, this approach has limitations, as extensively documented in the literature. Artificial Intelligence (AI) has emerged as a pivotal tool to address these limitations, enhancing risk mitigation and informed decision-making. This research proposes a machine learning (ML) based security mechanism, leveraging …

Security Enhancement In Aav Swarms: A Case Study Using Federated Learning And Shap Analysis, Sushmitha Halli Sudhakara, Lida Haghnegahdar

School of Cybersecurity Faculty Publications

As cyber-physical systems (CPSs) increasingly integrate physical and digital realms, securing critical infrastructure, such as the Port of Virginia, becomes paramount. Among CPSs, Autonomous Aerial Vehicles (AAVs) are vital for monitoring, communication, and supporting the command and control through remote reconnaissance and surveillance missions. These AAV applications often require coordination, planning, and runtime reconfiguration, traditionally managed by human decision-makers. However, this approach has limitations, as extensively documented in the literature. Artificial Intelligence (AI) has emerged as a pivotal tool to address these limitations, enhancing risk mitigation and informed decision-making. This research proposes a machine learning (ML) based security mechanism, leveraging …

Tl-Convlstm: A Transfer-Learning-Based Convolutional Lstm To Identify And Forecast Traffic In The Nextg Environments, Bikash Chandra Singh, Peter Foytik, Rafael Diaz, Sachin Shetty

School of Cybersecurity Faculty Publications

Forecasting and categorizing cellular traffic flows and their types are essential functions in intelligent network systems to ensure efficient network optimization. The ever-evolving nature of 5G networks results in fluctuations in traffic patterns over time, leading to a phenomenon known as model drift. Consequently, accurately predicting and identifying cellular traffic patterns becomes a complex task. To tackle this challenge, this article introduces an innovative approach called TL-ConvLSTM, which combines transfer learning with convolutional long short-term memory (ConvLSTM) to effectively combat model drift and provide precise forecasting and recognition of cellular traffic within the network. To accomplish this, we initiate the …

Leaf-Based Varietal Categorization Of Sweetpotato (Ipomoea Batatas L. Lam.), A Potentially Healthful Vegetable, Using Image Processing And K-Means Clustering, Shahidul Islam, Md Towfiqur Rahman, Md Hamidul Rahman, Abdul Momin

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Sweetpotato (Ipomoea batatas Lam) leaves contain higher concentrations of phenolic compounds, flavonoids, and carotenoids that are remarkable in health promotion. However, the nutrient content in sweetpotato leaves varies from variety to variety, and leaf shape and color are the key identifying factors for the varietal classification of sweetpotatoes. So, detecting sweetpotato leaves is essential for the in-situ identification of sweetpotato varieties and for developing intelligent agricultural systems. This study aimed to create a leaf-shape-based varietal classification technique for sweetpotato using image processing techniques coupled with a K-means clustering algorithm. 38 leaf images (RGB) of two sweetpotato cultivars were collected …

In-Season Nitrogen Mmanagement: Leveraging Data Visualization For Precision Agriculture, Chathurika Harshani Narayana

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Effective nitrogen management is vital for sustainable agriculture, impacting both crop yield and environmental health. Traditional methods often use fixed application rates set before planting, which do not adapt to changing crop needs during the season. This can lead to over- or under-application, reducing efficiency and sustainability. While modern tools like sensors, satellites, and UAVs provide valuable real-time data on crop and field conditions, integrating and using this data to guide timely nitrogen decisions remains a major challenge. In-season nitrogen management offers a solution by allowing for dynamic adjustments to nitrogen applications, addressing crop needs as they arise. This approach …

Engagement In Practice: Partnering With Communities To Address Nuisance Flooding Challenges, Carol L. Considine, Mujde Erten-Unal, Dalya Ismael, Luka Alandra Hamal-Serenity, Farzaneh Soflaei

Engineering Technology Faculty Publications

Many communities are already experiencing the impacts of climate change that disrupt their daily lives. In Coastal Virginia, these impacts take the form of nuisance and stormwater flooding caused by sea level rise and changes in precipitation. Coastal Virginia has one of the highest relative sea level rise rates on the Atlantic Coast and the regional planning district commission recommends that Atlas 14 rainfall intensity, duration, and frequency curves be increased by 20% to account for changes in rainfall. The Coastal Community Design Collaborative (CCDC), a partnership between Hampton University Architecture and Old Dominion University Engineering & Technology, has had …

Leveraging Transformer-Based Ocr Model With Generative Data Augmentation For Engineering Document Recognition, Wael Khallouli, Mohammad Shahab Uddin, Andres Sousa-Poza, Jiang Li, Samuel Kovacic

Engineering Management & Systems Engineering Faculty Publications

The long-standing practice of document-based engineering has resulted in the accumulation of a large number of engineering documents across various industries. Engineering documents, such as 2D drawings, continue to play a significant role in exchanging information and sharing knowledge across multiple engineering processes. However, these documents are often stored in non-digitized formats, such as paper and portable document format (PDF) files, making automation difficult. As digital engineering transforms processes in many industries, digitizing engineering documents presents a crucial challenge that requires advanced methods. This research addresses the problem of automatically extracting textual content from non-digitized legacy engineering documents. We introduced …