Ocean Engineering Commons^™

Empowering Shipping Management Competence With Artificial Intelligence: A Strategic Approach To External Environmental Volatility, Yu-Kai Huang, Cheng-Hsien Hsieh, Chi-Chang Lin, Yu-Tzu Chang, Yu-Chao Cheng

Journal of Marine Science and Technology–Taiwan

The shipping industry is undergoing significant transformation with advancements in artificial intelligence (AI), yet challenges remain in effectively adopting AI technologies. This study addresses the key concerns influencing AI adoption in shipping management. Using the Analytic Hierarchy Process (AHP) integrated with the PEST model, an evaluation framework was developed to assess AI applications in shipping companies. Based on expert input collected through the Delphi method, four constructs and twelve criteria were identified, with the 'Technological' dimension being the most critical. 'Robustness,' 'Costs,' and 'Data quality' emerged as the top factors affecting AI implementation. The framework offers practical insights for shipping …

Comparative Evaluation Of Deep Learning Models For Predicting Skipjack Tuna (Katsuwonus Pelamis) Catch Based On Climatic Factors, Peng Ding, Hui Xu, Xin Zhuang, Yan-Lun Wu, Fengyuan Shen, Yujie Xiao, Jiensi Zhulidezi, Wei-Yu Lee

Journal of Marine Science and Technology–Taiwan

To investigate the impact of climatic factors on skipjack tuna catch, this study collected and analyzed annual global skipjack tuna catch data spanning from 1960 to 2021, along with corresponding monthly data for the key indicator of El Nino events (Niño1+2, Niño3, Niño4, and Niño3.4), the Southern Oscillation Index (SOI), the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), the North Pacific Index (NPI), and the global sea-air temperature anomaly index (dT). The optimal lag years of climatic factors were identified by selecting the maximum absolute cross- correlation coefficients. Subsequently, the predictive performance of LSTM, BiLSTM, and CNN-BiLSTM models …

Effects Of Train-Ship Direct Transshipment On Container Terminal Operational Efficiency And Energy Consumption: From A Scheduling Perspective, Yiying Du, Yaozong Wang, Zhongzhen Yang

Journal of Marine Science and Technology–Taiwan

On-dock rail integration positions terminals as critical hubs for rail-sea transshipment, which necessitates efficient scheduling for rapid container transfers. Given the strict schedules and batch arrival of railway containers, in this study, we propose a train-ship direct transshipment (TSDT) mode to eliminate nonproductive yard rehandling. To comprehensively evaluate the impact of the proposed mode on terminal handling operations, we developed an operational scheduling model for the entire process of the simultaneous loading of yard containers and railway-handling area (RHA) containers. The model comprises two stages. Stage 1 models the pre-reshuffling operations in the yard before loading, and Stage 2 implements …

Key Success Factors In Using The Lifting Method To Construct A Steel Bridge Pylon, Ming-Chao Su, Hui-Ping Tserng

Journal of Marine Science and Technology–Taiwan

Constructing the inclined steel pylon of cable-stayed bridges is challenging because of the pylon’s height, spatial limitations, and safety concerns. To address these challenges, this study developed a modular lifting method that can enhance the efficiency and precision of pylon construction. The proposed method involves using rotation jigs to temporarily assemble the pylon, horizontal positioning on temporary supports, and synchronized lifting through computer-controlled hydraulic systems. Field implementation on a large-span bridge project revealed that compared with the traditional method, the proposed method resulted in higher welding quality, lower risks associated with great-height operations, and a shorter on-site assembly time. The …

Deep Learning-Based Model For Automated Prediction Of Coastal Changes: A Robust Approach To Environmental Forecasting, Tsair-Fwu Lee, Chu-Ho Chang, Chin-Shiuh Shieh, Chih-Hsien Wu, Jen-Chung Shao, Chien-Liang Chiu

Journal of Marine Science and Technology–Taiwan

The coastline stands as a critical domain encompassing industry and the environment. The escalating global warming, leading to elevated sea levels and intensified wave-current interactions, has given rise to substantial coastal erosion. This predicament, in conjunction with excessive human development and Taiwan's coastal areas' extreme climatic impact, accentuates the perceptibility of coastal beach alterations. As a result, coastal erosion has emerged as a pressing issue necessitating resolution. Traditional methodologies for assessing coastline changes have conventionally relied on manual measurements. However, owing to the fluctuating distance of coastlines, influenced by tidal patterns, extended measurement processes over several months are susceptible to …

Hydrographic Influences On Seasonal Variations In Zooplankton Communities Of Taiwan Bank (Southern Taiwan Strait), Bor-Shyr Chen, Frank Paolo Jay B. Albarico, Mark Ariel D. Malto, Aiza D. Gabriel, Chiu-Wen Chen, Cheng-Di Dong

Journal of Marine Science and Technology–Taiwan

Understanding the factors that control ocean productivity is crucial in fisheries management. Taiwan Bank, located between the Taiwan Strait and the South China Sea, is a highly productive ecosystem due to upwelling events. The total zooplankton community (holozooplankton and merozooplankton), diversity, seasonal changes, and environmental drivers remain unexplored despite its productivity. This study evaluates the seasonal and vertical environmental dynamics in the Taiwan Bank and their impacts on the zooplankton community structure. We collected zooplankton and basic water parameters in March, July, and September 2017 at 5, 25, and 50 meters. We recorded significant seasonal changes in zooplankton composition and …

Model Performance For Predicting Trends And Analyzing The Impacts Of Sea Surface Temperature Changes In The Gulf Of Thailand, Tanatpong Udomchaipitak, Nathaphon Boonnam

Journal of Marine Science and Technology–Taiwan

This study focuses on assessing and improving the predictive performance of sea surface temperature (SST) in the Gulf of Thailand under unique environmental challenges. Data from the Hybrid Coordinate Ocean Model (HYCOM) were utilized, covering the period from July 1994 to June 2024 at depths ranging from 0 to 30 meters. After cleaning the data using the Interquartile Range (IQR) method, the processed dataset was tested using four models: Recurrent Neural Network (RNN) architectures, including Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), as well as Convolutional Neural Networks (CNNs). Model performance was enhanced by tuning the parameters over …

Dynamic Beamforming And Array Shape Estimation, Nicholas Ryan Costick

Open Access Master's Theses

The accurate estimation of towed sonar array shapes during complex maneuvers is a critical challenge affecting beamforming and target localization performance. When underwater arrays experience sharp turns or rapid movements, sensor positions become difficult to track precisely, negatively impacting the reliability of beamforming methods. This thesis addresses the issue of dynamic array shape uncertainty, motivated by operational challenges faced by the Navy.

A maximum-likelihood estimation (MLE) method is developed to simultaneously estimate the array shape and field directionality (spatial spectrum) during maneuvers. The proposed solution expands upon previous research, specifically the dynamic spatial spectrum estimation techniques described by Rogers and …

Experimental Validation Of Model Predictive Control For Roll Attenuation Of Scale Model Barge In Beam Sea Conditions, Callum Robbins

Open Access Master's Theses

Floating offshore wind turbines (FOWTs) are the next great frontier in the offshore energy world. However, for these machines to be safe, effective, and reliable, they must be stable. In this thesis, an active control strategy is developed that uses future wave information and model predictive control to attenuate wave induced motions of a floating platform, such as a FOWT. The future wave information is provided by a wave reconstruction and prediction (WRP) algorithm which allows for wave events to be calculated faster than real-time. This wave information is provided to a nonlinear model predictive controller (NMPC) that uses a …

Safety And Sustainability In The Domestic Ferry Sector : A Pci Framework For Esg-Aligned Maritime Governance, Mirza Zeeshan Baig

World Maritime University Ph.D. Dissertations

The domestic ferry sector is a significant component of maritime transportation. It strengthens social ties, supports economic growth and connects communities. Despites its importance, this industry faces ongoing challenges. These include fragmented governance, operational adequacies, safety risks and environmental concerns. The study deals with these issues by combining a systems-based approach with governance and change management theories. It examines the interplay between human, technical and organizational aspects. The study integrates the rule-based and rights-based maritime governance along with the Lewin’s three stage change management model (Unfreeze, Change, and Refreeze).

At the core of the study is the development of a …

Design, Fabrication, & Laboratory Testing Of A Strain Gage Instrumentation System For Marine Applications, Salem C. Homrighausen

UNF Graduate Theses and Dissertations

A strain gage-based instrumentation system was designed and fabricated to measure the moment present at the base of a mock, diesel-engine snorkel for a submerged vehicle designed to operate in the surf zone. Afterwards, a lab experiment was designed and executed to determine the accuracy of the instrument and a 2-dimensional, matrix-vector equation was formulated to relate pairs of voltages, Vx and Vy, to moments, Mx and My for the experiment. Three versions of this model were built. The first model was created using traditional statics equations governing strain, stress, moment, force. The second and third models were built directly …

Continuing Development Of An Unmanned Vehicle For Conducting Scientific And Engineering Operations In The Littoral Zone, Peter S. Bohn

UNF Graduate Theses and Dissertations

The beach and near shore are among the most economically and environmentally important regions on earth, yet they remain poorly understood due to the challenges of surveying the surf zone and obtaining other important data during high-energy events. Traditional methods such as wading surveys, small watercraft, and specialized vehicles like the coastal research amphibious buggy (CRAB) are limited by safety risks, high mobilization costs, and restricted operating windows. The work conducted in this effort addresses these limitations by continuing development of a remotely operated vehicle (ROV) intended to be operational in harsh surf conditions to collect high-resolution bathymetric and hydrodynamic …

Knowledge Integrated Deep Learning For Enhanced Fault Diagnosis And Prognosis For Rotating Machinery And Its Applications On Marine Systems, Yunsheng Su

Dissertations, Master's Theses and Master's Reports

This dissertation develops a knowledge-informed deep learning framework for robust fault diagnosis and prognosis across various engineered systems, including bearings, lithium-ion batteries, and mooring systems in wave energy converters (WECs). A deep transfer learning (DTL) method is first developed to improve bearing fault diagnosis by fusing data from multiple sources and extracting key features using convolutional neural networks (CNNs). Building upon this, a knowledge-informed deep network (KIDN) framework is proposed, integrating physics-based features with deep learning to enhance diagnostic accuracy and generalizability. A constrained Gaussian process (CGP) model is further employed to guide adaptive network design and reduce model tuning …

Developing A Roadmap For Green Port In Timor-Leste, Emanuel Da Silva Maia

World Maritime University Dissertations

No abstract provided.

The Waterbug: Adaptive Paddle Board Frame, Remy James Elio Lacchia, Katie Kellum, Madeline Evenson, Shelbi Sullaway

Mechanical Engineering

People with disabilities, particularly wheelchair users, face limitations in participating in outdoor activities like paddleboarding. Central Cal Adaptive, a nonprofit organization, aims to bridge this gap by offering adapted paddleboarding experiences. However, their current paddleboard presents challenges such as portability, range of motion, stability, and safety. Our team, comprising Madeline Evenson, Remy Lacchia, Katie Kellum, and Shelbi Sullaway, has collaborated with Central Cal Adaptive to refine the existing paddleboard design. The team’s goal is to enhance the paddleboard's functionality to better cater to wheelchair users' needs, ensuring lightweight, portable, and safe features for an improved outdoor experience.

Our paddleboard concept …

Swim Fly Drone, Alia Wolken, Sha'anan Levy, Andrew Jwaideh, Eduardo Santos

Mechanical Engineering

This project addresses the need for a versatile drone that is capable of operation in both air and water environments, with potential applications in infrastructure inspection, defense, search and rescue, and ocean exploration. This project focuses on the design and development of a waterproof aerial drone capable of floating on the water surface and submerging underneath to controlled depths with the integration of a custom detachable buoyancy chamber. The buoyancy chamber design utilizes syringes to compress and decompress air inside of the chamber, changing the volume of the chamber, with an actuation system controlled by a closed-loop control system that …

Evaluating The Multi-Valued Bartlett Processor, Daniel Robert Frister

Dissertations and Theses

A variety of approaches exist to track targets in the ocean using acoustic sensors, and the complex mix of source characteristics, environmental effects, and sensor array limitations can make the selection of an appropriate algorithm challenging. This thesis models in simulation a recently proposed signal processing method that is intended for use with a large rectangular sensor array to track the bearings of multiple sources. The method, referred to as the Multi-Valued Bartlett (MVB) processor, is an eigenvector beamformer that leverages the capabilities of large arrays to locate in bearing multiple sources simultaneously. The analysis of this thesis details the …

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 …

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 …