Hasil untuk "Naval architecture. Shipbuilding. Marine engineering"

Jorge Melegati

The adoption of Generative AI (GenAI) suggests major changes for software engineering, including technical aspects but also human aspects of the professionals involved. One of these aspects is how individuals perceive themselves regarding their work, i.e., their work identity, and the processes they perform to form, adapt and reject these identities, i.e., identity work. Existent studies provide evidence of such identity work of software professionals triggered by the adoption of GenAI, however they do not consider differences among diverse roles, such as developers and testers. In this paper, we argue the need for considering the role as a factor defining the identity work of software professionals. To support our claim, we review some studies regarding different roles and also recent studies on how to adopt GenAI in software engineering. Then, we propose a research agenda to better understand how the role influences identity work of software professionals triggered by the adoption of GenAI, and, based on that, to propose new artifacts to support this adoption. We also discuss the potential implications for practice of the results to be obtained.

Mohammad Javad Bayat, Amin Kalhori, M. Babaei et al.

Spherical shells exhibit superior strength-to-geometry efficiency, making them ideal for industrial applications such as fluid storage tanks, architectural domes, naval vehicles, nuclear containment systems, and aeronautical and aerospace components. Given their critical role, careful attention to the design parameters and engineering constraints is essential. The present paper investigates the buckling responses of bio-inspired helicoidal laminated composite spherical shells under normal and torsional loading, including the effects of a Winkler elastic medium. The pre-buckling equilibrium equations are derived using linear three-dimensional (3D) elasticity theory and the principle of virtual work, solved via the classical finite element method (FEM). The buckling load is computed using a nonlinear Green strain formulation and a generalized geometric stiffness approach. The shell material employed in this study is a T300/5208 graphite/epoxy carbon fiber-reinforced polymer (CFRP) composite. Multiple helicoidal stacking sequences—linear, Fibonacci, recursive, exponential, and semicircular—are analyzed and benchmarked against traditional unidirectional, cross-ply, and quasi-isotropic layups. Parametric studies assess the effects of the normal/torsional loads, lamination schemes, ply counts, polar angles, shell thickness, elastic support, and boundary constraints on the buckling performance. The results indicate that quasi-isotropic (QI) laminate configurations exhibit superior buckling resistance compared to all the other layup arrangements, whereas unidirectional (UD) and cross-ply (CP) laminates show the least structural efficiency under normal- and torsional-loading conditions, respectively. Furthermore, this study underscores the efficacy of bio-inspired helicoidal stacking sequences in improving the mechanical performance of thin-walled composite spherical shells, exhibiting significant advantages over conventional laminate configurations. These benefits make helicoidal architectures particularly well-suited for weight-critical, high-performance applications in aerospace, marine, and biomedical engineering, where structural efficiency, damage tolerance, and reliability are paramount.

Lara Mills, Juan L. Garzon, Flávio Martins

Simulating wave propagation is crucial for forecasting processes offshore and near the coast. Many operational wave models consider only atmospheric and wave forcing as boundary conditions. However, waves and currents are interdependent, and simulating their interaction is crucial for accurately representing wave propagation. This study examines the influences of the current velocity and water levels on waves on the southern coast of the Iberian Peninsula. These forcing elements were simulated by a 3D hydrodynamic model (MOHID) and included in the Simulating WAves Nearshore (SWAN) model. The standalone SWAN model was calibrated and validated by comparing results of significant wave height, mean wave direction, and peak period with in situ observations. Then, the effects of water levels and current velocities on wave propagation were assessed by forcing the SWAN model with water levels as well as current velocities extracted from different depths: the surface layer and depth-averaged velocities from the surface down to 10 m, 20 m, and the full water column. The results revealed that incorporating the current velocity and water levels from MOHID into the SWAN model reduced the root mean square error (RMSE) between 1.6% and 27.6%. The most accurate results were achieved with model runs that included both the current velocity from the surface layer and water levels. Opposing currents resulted in increases in wave height, whereas following currents resulted in decreases in wave height. This work presents novel results on the effects of hydrodynamics on wave propagation along the southern coast of the Iberian Peninsula, a region of key importance for the blue economy.

Wenbo Dong, Jiaming Chen, Yufei Zhang et al.

During polar navigation, icebreakers frequently encounter ice ridges, which can significantly reduce navigation efficiency and even pose threats to structural safety. Therefore, studying the ramming of ice ridges by the icebreaker is of great importance. In this study, the ice ridge is decoupled into the consolidated layer and the keel for modeling. The consolidated layer is simplified as layered ice, and an innovative hybrid empirical–numerical method is used to determine the icebreaking loads. For the keel, a failure model is developed using the Mohr–Coulomb criterion in combination with the effective stress principle, accounting for shear failure in porous media and incorporating both cohesion and internal friction angle. The ship is restricted to surge motion only. A comparative analysis with the model test results was conducted to assess the accuracy of the method, with the predicted ice resistance showing deviation of 9.85% in the consolidated ice area and 10.48% in the keel area. Ablation studies were conducted to investigate the effects of different ice ridge shapes, varying retreat distances, and different ship drafts on the performance of ramming the ice ridge. The proposed method can quickly and accurately calculate ice ridge loads and predict their motion responses, providing a suitable tool for on-site rapid navigability assessment and for the design of icebreakers.

Haibo Wang, Zhuolin Xu, Shin Hwei Tan

Refactoring is the process of restructuring existing code without changing its external behavior while improving its internal structure. Refactoring engines are integral components of modern Integrated Development Environments (IDEs) and can automate or semi-automate this process to enhance code readability, reduce complexity, and improve the maintainability of software products. Similar to traditional software systems such as compilers, refactoring engines may also contain bugs that can lead to unexpected behaviors. In this paper, we propose a novel approach called RETESTER, a LLM-based framework for automated refactoring engine testing. Specifically, by using input program structure templates extracted from historical bug reports and input program characteristics that are error-prone, we design chain-of-thought (CoT) prompts to perform refactoring-preserving transformations. The generated variants are then tested on the latest version of refactoring engines using differential testing. We evaluate RETESTER on two most popular modern refactoring engines (i.e., ECLIPSE, and INTELLIJ IDEA). It successfully revealed 18 new bugs in the latest version of those refactoring engines. By the time we submit our paper, seven of them were confirmed by their developers, and three were fixed.

It is a great honor and privilege to welcome you to the 9th International Conference on Marine Technology (SENTA 2024), organized by the Faculty of Marine Technology, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia. With the theme “Innovations in Sustainable Marine Technology for Resilient Maritime Industry,” this conference serves as a platform for researchers, professionals, and policymakers to exchange insights and breakthroughs that address challenges in achieving sustainable and resilient maritime solutions. SENTA 2024 underscores its commitment to advancing knowledge in marine technology, focusing on critical areas such as low-carbon ship design, smart port operations, decarbonization in logistics, and the adoption of renewable energy in offshore engineering. By fostering interdisciplinary collaborations, this event aspires to contribute significantly to sustainable development goals while enhancing the maritime industry’s resilience. We are delighted to host prominent keynote speakers, including Prof. Osman Turan (Naval Architecture, Ocean and Marine Engineering, The University of Strathclyde Glasgow, UK), Yuen Kum Fai, Ph.D. (Director Maritime Energy and Sustainable Development Center of Excellence), Ruri Indrasari Rachmaputri (Commercial and Technical Director, PT Pelindo Solusi Logistik and Head of Mutiara Pelindo), Lucia Karina (Director of Public Affairs, Communications, Sustainability, Coca Cola Europasicfic Partners) who will share their expertise on groundbreaking innovations. With over 100 participants and technical paper sessions, SENTA 2024 promises a dynamic exchange of ideas. On behalf of the organizing committee, I extend my deepest gratitude to all contributors, sponsors, and participants for their invaluable support in making this event a success. We look forward to a fruitful and inspiring conference that drives forward the future of sustainable marine technology. List of Editors and Committee are available in this pdf.

V. Kanuri, K.V.Chandra Sekhar, P.S.Brahmanandam et al.

Poiseuille flow are considered as flows of Newtonian fluids through stationary pipes, with applications ranging from the pharmaceutical industries to manufacturing companies. These flows have been extensively studied in several works of literature due their relevance in many spheres of life. However, the Poiseuille flow for non-Newtonian flows have not gained much attention, despite the fact that most fluids are non-Newtonian. Based on this, this study investigates the Poiseuille flow of the second-grade fluid. Second-grade fluid are viscoelastic non-Newtonian fluids that exhibit both shear-thinning and shear-thickening with applications found in several industrial applications such as pharmaceutical, cosmetics and polymer processing. The Poiseuille flow of second-grade fluid is formulated from the underlying Navier-Stokes’ equations and the general assumptions of Poiseuille flow are invoked to reduce the equations to the regular ordinary differential equations. Analytical solution for the flow problem is sought using the method of separation of variables and the results are graphed to show the response of velocity and flow rate to the parameters of the flow. The outcomes show that velocity distribution reduces as the pipe radius increases and second-grade fluid have lower velocity than the Newtonian fluid. Journal of Naval Architecture and Marine Engineering, 21(1), 2024, P: 67-77

Rehena Nasrin, Saima Sawmpa

A three-dimensional thermal-electric including a four-tiny radiofrequency probe, hepatic tissue, and an integrated model of a large blood vessel are investigated numerically. The FEM is employed in the determination of the distribution of tissue temperature during radiofrequency hepatic tumor ablation through the heated targeted cells that are supposed to kill and the healthy surrounding tissues are supposed to save. The mathematical reproduction is led for various times from 0 s to 1000 s and electric voltage from 22 V to 50 V with good convergence of the iterative scheme.  In terms of temperature fields at different times, iso-surfaces with temperatures of 50°C at various times, iso-surfaces at different temperatures, and the temperature distribution over time are displayed graphically. Temperature distribution against time at the tip of one of the electrodes arms at a fixed voltage and various voltages are also demonstrated. Results from the RF simulation specify that temperature increases due to increasing time of ablation of tumor and electric voltage. The tumor cell is killed approximately at 50°C with 22 V after 480 s heating. The proposed model may be a new tool for physicians for the efficient thermal insulation of tumors without any significant damage in healthy tissues. Journal of Naval Architecture and Marine Engineering, 21 (1), 2024, pp. 51–66

Joseph Daiz, Elisa Vinco-Garcia

<p><strong>Purpose:</strong> This study aimed to investigate the teaching strategies, pedagogical competence, and challenges encountered by maritime professional instructors in Maritime Higher Education Institutions (MHEIs) to inform the development of an enhancement program.</p><p><strong>Methods:</strong> A descriptive-comparative design was employed, utilizing a quantitative approach to examine the teaching strategies, pedagogical competence, and challenges faced by 75 maritime professional instructors selected through stratified random sampling. Data were gathered using a researcher-made instrument consisting of four parts, with its validity established through expert validation and reliability ensured via pilot testing using Cronbach's Alpha method.</p><p><strong>Findings:</strong> The results indicated that the most prevalent teaching strategies among maritime professional instructors included quizzes, tests, discussions, demonstrations, hands-on activities, practical exercises, and lectures enhanced by interactive techniques. The instructors exhibited a very high level of pedagogical competence overall and across various categories, including rank, teaching experience, educational attainment, and classification. Nonetheless, they encountered significant challenges such as financial concerns, limited resources and skills, and fatigue stemming from inadequate sleep.</p><p><strong>Research Implications:</strong> The study underscores the importance of a balanced approach that integrates traditional and interactive teaching methods to foster comprehensive learning in maritime education. The high level of pedagogical competence among instructors highlights their effectiveness in facilitating meaningful learning experiences. Furthermore, the findings suggest that factors such as training in instructional methods and industry expertise may be more critical in developing effective teaching skills than conventional indicators like rank, experience, or educational background.</p><p><strong>Practical Implications:</strong> Educational institutions should consider addressing the challenges faced by maritime professional instructors by providing support systems and resources that enhance teaching efficacy and well-being. Additionally, promoting ongoing professional development focused on instructional methods and practical skills can further strengthen the pedagogical competence of instructors, ultimately benefiting student learning outcomes in maritime education.</p><p> </p><p><strong>Received: 05 August 2024 </strong></p><p><strong>Accepted: 02 September 2024 </strong></p><p><strong>Published: 22 September 2024</strong></p>

Lichao Jiang, Zhi Zhang, Lingyun Lu et al.

Ship dynamic models serve as the foundation for designing ship controllers, trajectory planning, and obstacle avoidance. Support vector regression (SVR) is a commonly used nonparametric modelling method for ship dynamics. Achieving high accuracy SVR models requires a substantial amount of training samples. Additionally, as the number of training samples increases, the computational efficiency for solving the quadratic programming problem (QPP) of SVR decreases. Ship controllers demand dynamic models with both high accuracy and computational efficiency. Therefore, to enhance the prediction accuracy and computational efficiency of SVR, this paper proposes a nonparametric modelling method based on twin SVR (TSVR). TSVR replaces a large QPP with a set of smaller QPPs, significantly enhancing generalizability and computational efficiency. To further improve the predictive accuracy of TSVR, the puma optimizer algorithm is employed to determine the optimal hyperparameters. The performance of the proposed method is validated using a Mariner class vessel. Gaussian white noise is introduced into the modelling data to simulate measurement error. The TSVR model accurately predicts various zigzag and turning circle manoeuvring motions under disturbance conditions, demonstrating its robustness and generalizability. Compared to the SVR model, the TSVR model achieves lower root mean square error and computational time, confirming its superior predictive accuracy and computational efficiency.

Xiaodi LIANG, Yindong LIU

ObjectiveTo address the issue of assessing structural breach damage in ships under underwater explosion, a breach prediction method based on the PCA-BOA-KNN model is established. MethodsFirst, finite element models for five-compartment and seven-compartment segments are constructed, and explosion simulation analysis is carried out for 21 sets of underwater explosion conditions. Subsequently, principal component analysis (PCA) is employed to reduce the dimensionality of the peak acceleration, peak velocity, peak displacement, peak stress and peak overpressure values, resulting in two principal features. Finally, the PCA results are integrated into a Bayesian optimization algorithm (BOA) K-Nearest Neighbors (KNN) model. The established breach prediction model is used to predict the breach conditions at different ship cross-sections under a set of conditions. ResultsThe results show that by using PCA to extract the first two factors, the cumulative contribution rate is 85.165%. Therefore, the first two factors can represent the primary information of the five features. The results obtained using the PCA-BOA-KNN breach prediction model are generally consistent with the simulation results. ConclusionThe proposed prediction model approach is effective for predicting ship structural breaches and has reference value for predicting breachs in ship structures with different principal dimensions.

Jianfeng Liu, Wang Xi, Weigang Lu

Influenced by the clearance flow between stator and rotor, the operational performance and hydraulic performance of full cross-flow pump units are often worse than that of semi-cross-flow pumps. In order to explore the influence mechanism of clearance structural parameters on clearance flow and provide a reliable scientific support for the improvement of both external and internal characteristics of full cross-flow pump units, firstly, the optimization of the stator–rotor clearance structure was studied as research entry point and the radial inlet and outlet clearance width were taken to set up design variables. Secondly, to establish a comprehensive optimization objective function considering both the operational performance and the hydraulic performance of the pump, the information weight method was adopted by weighting four evaluation indexes, namely, head coefficient, efficiency coefficient, vortex average radial deflection coefficient and axial velocity uniformity coefficient, which were calculated by numerical simulation. Finally, the relevant optimization design analysis was carried out by establishing the response surface model, with the optimal objective value obtained by conducting the steepest-descent method. The results show that the response of the radial inlet and outlet clearance width coefficient between stator and rotor to the comprehensive objective function is not directly coupled and the influence of the radial inlet clearance width coefficient on the objective function is higher than that of the radial outlet clearance width coefficient. The parameter optimization outcomes are as follows: the width coefficient of radial inlet clearance between stator and rotor is 2.2 and that of radial outlet clearance is 3.6, in which case the disturbance effect of clearance flow on the mainstream flow pattern in the pump can be significantly reduced, with the export cyclic quantity of the guide vane obviously decreased and the outlet flow pattern of the pump unit greatly improved. Verified by the model test, the average lift of the pump unit was increased by about 7.6% and the maximum promotion of the unit efficiency reached 5.2%.

Achmad Riadi, Muhammad Hanif Fajri Ramadhan

This paper presents the application of strategic ship fleet planning for the maritime transportation of crude palm oil. This study aims to determine the optimal number of chemical tankers required, their capacity (in deadweight tonnage), and the appropriate timing for chartering, buying, or selling vessels within the fleet. To achieve this, mixed integer linear programing is utilized as the optimization framework for strategic ship fleet planning. To ensure a more authentic approach, the investigation utilized a case study focused on the export of Indonesian crude palm oil. The research findings indicate that several export routes cannot be serviced due to higher transportation costs, which could potentially be anticipated through an increase in freight rates. In addition, decisions regarding the quantity and categories of fleets required for each transportation route were also made. The importance of this study is highlighted by its capacity to offer valuable insights to exporters, shipping companies, and the government regarding tanker fleet deployment, management, and regulatory considerations. Furthermore, these findings provide a clearer understanding of the necessity of a tanker fleet for transporting crude palm oil. This supports the Indonesian government's 'beyond cabotage' policy, which mandates the use of vessels operated by national shipping companies for crude palm oil exports, making it a relevant case study for examining the effectiveness of such measures.

Wenhui Wang, Jiahui Li, Xiaodong Huang

Multiwave interference plays a crucial role in shaping the spatial variations of internal tides. Based on a combination of in situ mooring and altimeter data, interference of semidiurnal internal tides was investigated in the northern South China Sea. Mooring observations indicate the observed kinetic-to-potential energy ratio and group speed are both relatively lower than the theoretical values of mode-1 semidiurnal internal tides, indicating the presence of partly-standing waves. This is consistent with the altimeter result that the mooring was located at the antinode within the interference pattern formed by the superposition of the westward and southward semidiurnal internal tides from the Luzon Strait and the continental slope of the southern Taiwan Strait. However, the kinetic-to-potential energy ratio and group velocity were notably changed when an anticyclonic eddy passed by the mooring. By employing the ray-tracing method, we identified that mesoscale processes may induce a phase difference in the semidiurnal internal tides between the Luzon Strait and the continental slope of the southern Taiwan Strait. This alteration further leads to changes in the positions of nodes and antinodes within the interference pattern of the semidiurnal internal tides.

Ranim Khojah, Mazen Mohamad, Philipp Leitner et al.

Large Language Models (LLMs) are frequently discussed in academia and the general public as support tools for virtually any use case that relies on the production of text, including software engineering. Currently there is much debate, but little empirical evidence, regarding the practical usefulness of LLM-based tools such as ChatGPT for engineers in industry. We conduct an observational study of 24 professional software engineers who have been using ChatGPT over a period of one week in their jobs, and qualitatively analyse their dialogues with the chatbot as well as their overall experience (as captured by an exit survey). We find that, rather than expecting ChatGPT to generate ready-to-use software artifacts (e.g., code), practitioners more often use ChatGPT to receive guidance on how to solve their tasks or learn about a topic in more abstract terms. We also propose a theoretical framework for how (i) purpose of the interaction, (ii) internal factors (e.g., the user's personality), and (iii) external factors (e.g., company policy) together shape the experience (in terms of perceived usefulness and trust). We envision that our framework can be used by future research to further the academic discussion on LLM usage by software engineering practitioners, and to serve as a reference point for the design of future empirical LLM research in this domain.

Cuiyun Gao, Xing Hu, Shan Gao et al.

With the advent of large language models (LLMs) in the artificial intelligence (AI) area, the field of software engineering (SE) has also witnessed a paradigm shift. These models, by leveraging the power of deep learning and massive amounts of data, have demonstrated an unprecedented capacity to understand, generate, and operate programming languages. They can assist developers in completing a broad spectrum of software development activities, encompassing software design, automated programming, and maintenance, which potentially reduces huge human efforts. Integrating LLMs within the SE landscape (LLM4SE) has become a burgeoning trend, necessitating exploring this emergent landscape's challenges and opportunities. The paper aims at revisiting the software development life cycle (SDLC) under LLMs, and highlighting challenges and opportunities of the new paradigm. The paper first summarizes the overall process of LLM4SE, and then elaborates on the current challenges based on a through discussion. The discussion was held among more than 20 participants from academia and industry, specializing in fields such as software engineering and artificial intelligence. Specifically, we achieve 26 key challenges from seven aspects, including software requirement & design, coding assistance, testing code generation, code review, code maintenance, software vulnerability management, and data, training, and evaluation. We hope the achieved challenges would benefit future research in the LLM4SE field.

Umm-e- Habiba, Markus Haug, Justus Bogner et al.

Artificial intelligence (AI) permeates all fields of life, which resulted in new challenges in requirements engineering for artificial intelligence (RE4AI), e.g., the difficulty in specifying and validating requirements for AI or considering new quality requirements due to emerging ethical implications. It is currently unclear if existing RE methods are sufficient or if new ones are needed to address these challenges. Therefore, our goal is to provide a comprehensive overview of RE4AI to researchers and practitioners. What has been achieved so far, i.e., what practices are available, and what research gaps and challenges still need to be addressed? To achieve this, we conducted a systematic mapping study combining query string search and extensive snowballing. The extracted data was aggregated, and results were synthesized using thematic analysis. Our selection process led to the inclusion of 126 primary studies. Existing RE4AI research focuses mainly on requirements analysis and elicitation, with most practices applied in these areas. Furthermore, we identified requirements specification, explainability, and the gap between machine learning engineers and end-users as the most prevalent challenges, along with a few others. Additionally, we proposed seven potential research directions to address these challenges. Practitioners can use our results to identify and select suitable RE methods for working on their AI-based systems, while researchers can build on the identified gaps and research directions to push the field forward.

M. Radhakrishnan, G. Palani

An investigation is made to discuss the effects of Magnetohydrodynamic and nanofluid particles on unstable two-dimensional free convective flow through a vertical plate in the existence of thermal source, radiation effect, and chemical reaction effect with varying thermal and mass flux. The guiding unsteady equations were cracked using the implied finite-difference method. Here we considered four dissimilar nanofluids including Cu, Al2O3, TiO2, and Ag with water as base fluid. The flow pattern employed incorporates the result of dissimilar non-dimensional parameters for instance volume fraction, magnetic field, heat source parameter, Prandtl number, radiation effect, Schmidt number, and chemical reaction effect. The impacts of the above-mentioned parameters on the boundary layer flow characteristics (velocity, temperature, concentration, skin friction coefficient, Nusselt number, and Sherwood number) are intentional. The impact of the velocity profile is highest in silver-water nanofluids and lowest in Al2O3 water nanofluids among the nanofluids considered in this study but the reverse trend is observed with respect to temperature. Moreover, the outcomes are explained through graphs. Journal of Naval Architecture and Marine Engineering, 21(1), 2024, P: 15- 26

Jian Zheng, Wenjun Sun, Yun Li et al.

In order to solve the multi-objective planning and trajectory tracking control problem related to maritime autonomous surface ships (MASSs), a new design scheme for autonomous navigation is proposed in this paper, with a receding horizon navigation and control (RHNC) system that contains navigation and control modules. In the navigation module, we designed a superposition field gradient descent local search algorithm based on the cost field, emission field, and guidance field to navigate the MASS reference path, and in the control module, we designed a nonlinear controller that can handle multiple constraints based on the NMPC framework. Under the new scheme, the navigation module completes local path planning to reduce costs and emissions, the control module accomplishes accurate trajectory tracking and real-time collision avoidance, and the information is transmitted in both directions between the two modules to collaboratively complete the MASS navigation and control tasks. We conducted a simulation study of the navigation algorithm and controller and the autonomous navigation system using a Kriso Container ship (KCS). The simulation results demonstrate the effectiveness of the proposed cooperative design scheme in reducing navigation costs and emissions and avoiding autonomous collision avoidances.

Suhyeon Park, Jongwon Seok, Jungpyo Hong

Snapping Shrimps (SSs) live in a warm ocean except the North and South Poles, and they are characterized by generating strong shock waves underwater using large claws. Shock waves generated by these SSs are used for marine noise research as a signal and as a noise source, because they cause a decrease in the Signal-to-Noise Ratio (SNR), acting as one of the disruptors in fields such as sonar for target detection and underwater communication. A state-of-the-art technique to detect Snapping Shrimp Noise (SSN) is Linear Prediction (LP) analysis. Using the feature where SSN occurs for a very short time, the SSN interval was detected based on the phenomenon where the residuals appear large in the SSN interval when the LP analysis is used. In this paper, we propose an SSN interval detection technique using the Likelihood Ratio (LR) as a follow-up study to the LP-analysis-based method for further performance improvements. The proposed method was used to analyze the statistical distribution characteristics of the LP residual of SSNs compared to Gaussian, Laplace, and Gamma distributions through the Goodness-Of-Fit test. Based on this, the statistical-model-based LRs of the three distributions were computed to detect the SSN interval. Comparing the proposed method with the state-of-the-art method, the proposed method achieved 0.0620, 0.0675, and 0.0662 improvements in Gaussian, Laplace, and Gamma distributions in the Receiver Operating Characteristic curve and Area Under Curve, respectively. The study results confirmed that the proposed method can operate effectively in the marine acoustic environment. This can help find accurate intervals for the automatic labeling of or reduction in SSN.