Internal combustion engines (ICE), especially diesel engines, require additional (secondary) fuel to improve their gas emissions. The selection of hydrogen as a secondary fuel in a diesel dual fuel (DDF) system is meaningful because it does not contain carbon to support exhaust gas decarbonization. Hydrogen also has a high calorific value, which can be a threat of knocking in the engine during operation. Early detection of knocking can prevent further damage to the piston and cylinder. Experts apply pressure and frequency calculations to measure the intensity of knocking. The results obtained in a homogeneous charge compression ignition (HCCI) engine were that slight knocking occurred at a hydrogen-air ratio above 0.3, and heavy knocking rose at a hydrogen-air ratio of 0.45.
The marine ecosystem is vital for sustaining life on Earth, yet its vastness and complexity present significant challenges for effective monitoring and management. Integrated Marine Observing Systems (IMOS) have emerged as essential tools for understanding and protecting marine environments. This study aims to systematically review the integration of artificial intelligence (AI) into IMOS, focusing on its contributions to data processing, biodiversity monitoring, and environmental change analysis. A systematic literature review (SLR) method is employed to analyze existing research and identify key AI techniques and their applications in marine and oceanographic studies. Results indicate that deep learning is the most widely used AI method, with marine research being the primary application domain. Other areas, such as environmental monitoring and industrial systems, also demonstrate considerable potential. However, data inconsistency, operational limitations, and the lack of standardized frameworks remain significant barriers. This review highlights the transformative role of AI in enhancing IMOS capabilities and provides recommendations for addressing existing challenges to support sustainable marine management.
River water quality monitoring aims to determine the state of river water quality and to ensure its safety for human health and the sustainability of its use. Some important parameters that are often used to measure river water quality include chemical oxygen demand (COD), biological oxygen demand (BOD), total suspended solids (TSS), pH, Temperature, and microplastic content. This study uses multiple linear regression to determine which factors contribute significantly to river water quality. Samples were collected from the Winongo, Gadjah Wong, Bulus, Oyo, Belik, Tambakbayan, Opak, and Kuning rivers in Daerah Istimewa Yogyakarta (DIY) and distributed in 20 points. The results of the correlation matrix show the relationships between the variables in the data. The DO variable has the most substantial relationship with microplastics, suggesting that water quality, measured by oxygen levels, may be related to microplastic pollution. The relationship between pH and Temperature is also moderate. However, other relationships tend to be weak, suggesting that other factors may be more influential in determining these variables' relationships. The multiple linear regression model shows that an increase in pH, a decrease in Temperature, an increase in DO, and a decrease in TSS will increase the amount of microplastics. Furthermore, through spatial analysis and geographically Weighted Regression (GWR) modelling, DO significantly affects 12 observation points and does not affect eight. The spatial approach shows that the causes of river water pollution are different in each location. Therefore, each site's treatment is also different according to its characteristics.
Aquaculture plays a vital role in global food supply, contributing nearly 43% of the food consumed by humans. The rapid growth in aquaculture production demands a significant amount of electricity, which accounts for approximately 40% of the total energy costs. The primary energy sources in aquaculture used fossil fuels, it can be reduced by utilizing alternative energy sources. This research aims to develop a prototype of a floating net cage using an Internet of Things (IoT)-based water quality monitoring system powered by solar energy. The water quality parameters monitored in this study include temperature, pH, salinity, and dissolved oxygen levels. The sensors used for monitoring these parameters have undergone testing. The results indicate that the sensors can perform accurate measurements with over 90% accuracy. The solar panels installed in the system are capable of generating sufficient power to meet the operational demands, allowing the system to operate for approximately two days without sunlight. By maintaining well-controlled aquatic environmental conditions through IoT-based monitoring and control systems supported by renewable photovoltaic solar energy, environmentally friendly aquaculture operations can be conducted efficiently and productively. Ultimately, this leads to the production of high-quality aquaculture products, cost-effective operations, and the utilisation of eco-friendly energy sources.
Offshore jacket structures are essential components in platform construction, requiring optimization due to high material, fabrication, and coating costs. The objective of this research is to achieve cost-effective designs without compromising safety. The methodology employs Sequential Quadratic Programming (SQP) with a surrogate-based approach to optimize structural dimensions, while reliability is assessed using Monte Carlo Simulation to account for uncertainties. Optimization conducted in MATLAB resulted in significant improvements in the dimensional reduction of most design variables, including a 20.32% reduction in total construction costs. Material, fabrication, and coating costs decreased by 19.05%, 28.11%, and 6.14%, respectively. The reliability index (Beta) of critical members improved to a range of 3.12–3.29, exceeding the safety threshold of 3.09.
The development of tourism areas in the Gunungkidul coastal zone was a potential threat that can affect the marine macroalgae diversity. In order to prevent the decline of macroalgae diversity from these anthropological threats, a comprehensive study is needed to record the population dynamics that occur. The objective of this study is revealing the species diversity and phenetic relationship of the sea lettuce (Ulva spp.). Phenetic analysis of sea lettuce was conducted by observing morphological, anatomical, and biochemical characters. Clustering analysis was done by the UPGMA method, whereas ordination analysis was conducted using the PCA (Principal Component Analysis) method; both of them were calculated using the MVSP 3.1 program. The result of the study discovered four species of Ulva, i.e., Ulva lactuca, Ulva rigida, Ulva compressa, and Ulva linza. The reconstruction of phenetic relationships revealed two main clusters of sea lettuce, exhibiting a percentage difference of 75.2. The PCA analysis exhibited eight characters that significantly influence clustering patterns, including thallus color, blade width, blade thickness, blade hole, stiff edge cells, cell surface diameter, elongated cell shape, and the presence of violaxanthin and neoxanthin.
Indonesia shares borders with Papua New Guinea, Malaysia, and Timor Leste, where border markers often face displacement or disputes due to challenging and inaccessible terrain. This research develops a waypoint navigation system on a quadcopter, integrating computer vision to enhance the detection and monitoring of border markers. The system leverages the Robot Operating System (ROS) as middleware for seamless integration and control, while a camera detects ArUco markers placed on boundary markers. Image processing, implemented using OpenCV integrated with ROS, facilitates efficient data conversion. The quadcopter autonomously navigates to target coordinates based on marker detection, with an average percentage error of 3.3% for the X-axis and 2.5% for the Y-axis. Tests showed the system could detect a 40x40 cm marker from a height of 5 meters up to a distance of 14 meters, with an average position error of 3.75%. The communication range was effective up to 150 meters before timing out. Despite the computational limitations of the Raspberry Pi hardware, the system demonstrated efficiency, scalability, and ease of deployment. Future research will focus on hardware enhancements, the exploration of advanced image processing methodologies, improved camera resolutions, and the extension of communication networks to support deployment in national boundary monitoring operations.
This paper presents a comprehensive structural integrity assessment of a 50,000-kiloliter aboveground steel storage tank that experienced shell denting during hydrostatic testing. Dents and geometric imperfections are known to significantly affect the buckling behavior and load-bearing capacity of storage tanks. To evaluate the tank’s fitness for service (FFS), a Level 3 assessment was conducted following API 579-1/ASME FFS-1 Part 8 standards. Finite element analysis was employed to simulate the elastic stress distribution and fatigue behavior under various loading conditions, including hydrostatic pressure, wind, and seismic loads. Results revealed that shell course 7 and 8 experienced stress increases of up to 2282% compared to the undistorted condition, with von Mises stress remaining below the allowable limits. A fatigue analysis confirmed that stress amplitudes were below the fatigue threshold, resulting in infinite fatigue life. Furthermore, discharge simulation indicated that improper dewatering could induce external pressure exceeding the material’s yield strength, leading to localized plastic deformation. Nevertheless, the dented tank was found to be structurally sound and compliant with API 650 and API 579-1/ASME FFS-1 criteria. The study highlights the importance of proper discharge procedures and confirms that no immediate repair is required for continued safe operation of the tank.
Shipbuilding projects frequently encounter delays and cost overruns as a result of unpredictability in the construction process. This paper aims to explore the potential of Critical Chain Project Management (CCPM) and buffer planning to enhance scheduling in complex shipbuilding project. The research approach involves a case study of a Security Accommodation Vessel (SAV) construction project, complemented by expert interviews which were conducted to assess the risks and uncertainties affecting activity durations. The buffer sizes were then calculated using the Root Square Error Method (RSEM). Qualitative data was gathered through interviews with the expert to identify and assess potential risks and uncertainties impacting activity durations. This qualitative insight informed the application of the RSEM to determine appropriate buffer sizes. The planned project duration was reduced from 790 days to 678 days, representing a 14,5% improvement. The study focuses on the planning phase of CCPM and demonstrates the potential of combining CCPM, buffer planning, and expert input to create more reliable schedules for complex shipbuilding projects like SAV construction.
This study comprehensively assesses safe loading conditions for the Self-Propelled Crane Barge (SPCB) Deck Crane by integrating detailed hydrostatic calculations with righting-arm (GZ) curve analysis. At the designated summer draft of 2.75 m, baseline parameters—displacement (1 716 t), centre of buoyancy (KB = 0.765 m), transverse metacentre (KM = 2.780 m), and metacentric height (GM = 1.23 m)—were established from the vessel’s stability booklet. Four loading scenarios (lightship, full ballast, crane at maximum outreach, and cargo distribution) were defined, with updated displacement and vertical centre of gravity (KG) values used to recompute hydrostatic parameters (BM, KM, free-surface corrections) and generate full GZ curves. Intact-stability criteria (GM >= 0.15 m, area under GZ curve >= 0.08 m·rad, angle of vanishing stability >= 25°, and GZmax >= 0.25 m) were evaluated for each case. Results indicate that the ballast condition yields the highest stiffness (GM approximately equal to 1.50 m) and energy absorption (AUC approximately equal to 1.15 mrad). The crane-outreach scenario represents the narrowest margin (GM approximately equal to 0.90 m, AUC approximately equal to 0.60 mrad). A safe-loading envelope was developed, showing permissible crane loads of up to 100 t at 10 m outreach and limiting lifts beyond 20 m to 50 t or less. Mitigation measures—ballast management, outreach/load restrictions, optimized cargo stowage, and real-time monitoring—are recommended to ensure regulatory compliance and operational safety.
Mobile crane lifting activities carry a significant accident risk, especially when performed in tandem configurations. The main risk comes from the possibility of failure of the load cell component which plays an important role in actual load measurement. This research aims to analyze the potential failure of the load cell function in tandem lifting operations using the Fuzzy Fault Tree Analysis (FFTA) method. Data were collected through literature studies, field observations, and interviews. The FFTA method is used to identify factors that cause failure and calculate the probability of failure quantitatively. The investigation identified that the primary variables leading to load cell failure include overload situations, internal component damage, and external impacts. The highest probability of failure was recorded in the material fatigue scenario due to damage to the cable. These findings highlight the need of instituting preventative maintenance programs and conducting frequent inspections of load cell components to reduce the risk of workplace accidents.
Lake Sunter, an man-made lake built since the 1970s and covering approximately 33 hectares, is commonly referred to as Lake Podomoro. Positioned as an urban recreational space, its scenic vistas offer potential for diverse water-based activities. In order to increase tourist engagement with the lake, it is imperative to diversify the available attractions. Among these attractions, tourist boats emerge as a viable option to capture public interest. Accordingly, this study attempts to design a catamaran tour boat equipped with motorcycle propulsion, tailored for operation on Lake Sunter. In the first stage, the primary dimensions of the catamaran vessel are determined using the linear regression method, resulting in dimensions of L = 3.2m, H = 1.15m and T = 0.4m, with a passenger capacity of 3 persons. The ship's stability is then assessed in accordance with the criteria of the IMO A.749 (18) Code On Intact Stability, Chapter 3, which applies to all ship designs. This assessment includes Load Case I and Load Case II conditions to determine the stability of the ship under different scenarios.
This research aims to analyze the factors that cause overflow in the fuel oil purifier system and to identify measures that can be taken to address this issue using the Failure Mode and Effect Analysis (FMEA) method. Overflow in the fuel oil purifier can disrupt the fuel purification process, which is crucial for engine performance. Therefore, understanding the causes and appropriate solutions is essential. The analysis results indicate that the factors causing overflow include leakage or wear of vital components such as O-rings, gravity discs, belts, bowls, main seal rings, ball bearings, nozzles, and pilot valves, as well as improper installation of components or blockages due to debris obstructing the flow. Overflow can be managed through regular inspections of components prone to wear or damage, routine cleaning of components that are susceptible to clogging, and continuous monitoring and calibration of the system to ensure the purifier operates optimally. By implementing these measures, the fuel oil purifier system is expected to function efficiently, reduce the risk of overflow, and enhance the reliability of the fuel purification process.
With the depletion of mineral resources in Indonesia, the need for effective renewable energy alternatives has become critical. Solar energy, harnessed through photovoltaic panels, presents significant potential. However, the widespread adoption of solar panels remains limited due to their large land area requirements and susceptibility to damage. Floating solar panels, installed on water surfaces, offer a promising solution by enhancing energy efficiency through natural cooling while addressing land constraints. This study aims to analyze the motion dynamics of floating solar panels in Semangka Bay and identify the most effective design for open water conditions. Three models were tested: rectangular, kite-shaped, and perforated, using 3D simulation software. The analysis focused on the Response Amplitude Operator (RAO) under regular wave conditions at a 180° angle. The results revealed that Model 3, with 8 mooring points, exhibited the best performance in mitigating rolling, pitching, and heaving motions. The maximum rolling value reached 826.24 cm at 81 seconds, with a minimum of -735.36 cm at 86.7 seconds. Pitching peaked at 390.30 cm at 61.4 seconds and fell to -376.42 cm at 63.9 seconds. Heaving values ranged from a maximum of 17.64 cm at 62.8 seconds to a minimum of -220.94 cm at 83 seconds. This study concludes that Model 3 with 8 moorings offers superior stability, making it the optimal design for floating solar panels in open waters like Semangka Bay. By addressing environmental and implementation challenges, this research contributes significantly to advancing floating solar energy technology in Indonesia. The findings highlight the potential of efficient and resilient designs to harness Indonesia’s abundant solar energy resources effectively.
Energy affordability and financial inclusion remain critical challenges for small island communities, where reliance on imported fossil fuels and high energy costs disproportionately impact low-income households. At the same time, high-income households and the growing tourism sector on these islands hold significant financial capacity to drive equitable energy transitions. This perspective explores the role of high-income stakeholders and tourism operators in promoting energy affordability through retribution mechanisms, adaptive service assets, and flexible organizational models. By leveraging financial resources and investing in clean energy solutions, high-income households and tourism businesses can contribute to a sustainable energy future that benefits all members of the community, bridging the gap between economic growth, energy equity, and environmental sustainability.
Oil spills are a major environmental issue that requires prompt detection and effective response strategies. Remote sensing technologies have shown great potential in improving oil spill detection and management. This paper aims to review and compare various remote sensing techniques and models used for oil spill detection and response, with a focus on evaluating their effectiveness in preventing offshore oil spills. The study involves a comprehensive review of recent research on remote sensing methods, such as neural network-based detection, Synthetic Aperture Radar (SAR), and optical sensors, alongside oil spill response techniques. The paper also utilizes the Publish or Perish (PoP) tool to analyze scientific papers related to oil spill detection and response. The PoP tool was employed to examine citation metrics, methodologies, and trends from 187 studies, including 16 focused on remote sensing techniques, 21 on oil spill methods, and 47 on related concerns. Results indicate that neural network-based methods are effective in high-risk areas, while SAR-based detection is recommended for regions with high sea states or cloud cover. The study also finds that a combination of response techniques, such as containment booms and bioremediation, can significantly improve the effectiveness of oil spill management. Moreover, the integration of multi-sensor data and machine learning techniques shows promise in enhancing detection accuracy and reducing false positives. In conclusion, the paper highlights the need for improved sensor technologies and the integration of various detection and response methods to enhance oil spill management efforts. Future research should focus on refining these techniques and developing cost-effective solutions to enable more efficient and timely responses to oil spills.
This study investigates the integration of a solar photovoltaic system on the passenger ferry E.V. Calestia operating along Manila’s Pasig River. The ferry, equipped with dual 400 kW electric motors and a battery bank of 1848 kWh, is supplemented by 20 solar panels installed on its top deck. Using a Simulink-based simulation model, the research estimates the power output and cumulative energy generation based on panel specifications, solar irradiance, and system efficiency. Results show a maximum instantaneous power output of approximately 3 kW during peak sunlight and a total weekly energy generation of around 150 kWh. These findings demonstrate the potential of solar power to enhance the ferry’s energy sustainability by reducing reliance on conventional charging and lowering emissions, thus promoting greener maritime transport solutions in urban river environments.
Calcium silicate boards (CSB) are being explored in the maritime industry due to the mechanical strength and its resintance to humidity. The common CSB comprises fiber, silica sand, and portland cement. Clamshell is one of marine waste, who has a high calcium carbonate (CaCO3) content. Coconut fiber, a natural fiber known for its high strength and durability, presents sustainable solutions for enhancing the material properties of CSB. This study explores the forming mechanism and mechanical properties of the CSB in the usage and varied volume fraction addition of coconut fiber with the varied portion replacement silica sand using clamshell powder. The bending test was performed, and the experimental results were analyzed using ANOVA, to understand the effect of the mixture composition on the bending strength of the CSB. The addition of volume fraction coconut fiber significantly improve the bending strength of the boards, while the replacement of silica sand using clamshell powder gives various result. The maximum bending strength was 13.87 ± 0.64 Mpa by 0% clamshell powder replacement in 9% coconut fiber, and significantly drop at 8.26 ± 2.20 MPa by 50% clamshell powder with 50% silica sand. In fully portion replacement of silica sand, in which the addition of 100% clamshell powder, with 9% coconut fiber, the bending strength measured at 10.29 ± 1.31 MPa. The highest results exceeding the minimum requirement in ISO-8336 category A and B (saturated condition) , class 3 (>13 MPa) standards for interior wall installations. This study providing a more robust and eco-friendly materials alternatives that supports non or maritime industry needs in while resolve the environmental issue.
This work focuses on the analysis of emergency piping systems connected to flares and pressure vessels at oil and gas facilities in West Papua. The main objective is to determine support placement, and analyze pipe stress on flares and pressure vessels. The methods used include calculating the maximum allowable pipe span, stress analysis based on ASME B31.3. The results of the research show that a 6 in emergency pipe line requires a minimum of 2 supports with a maximum allowable pipe span of 36.967 ft. The pipe flexibility value of 0.00146 is still below the limit of 0.02582 set by ASME B31.3. Stress analysis due to sustained, occasional, and thermal expansion loading shows the highest values respectively of 2572.5 lb/in² (12.6% of the permit limit), 1294.0 lb/in² (18.9% of the permit limit for seismic loads), 595.0 lb/in² (2.2% of the permit limit for wind loads), and 23921.3 lb/in² (49.3% of the permit limit).
The ballast control management system plays a vital role in maritime operations by ensuring vessel stability and safety while minimizing environmental risks associated with ballast water transfer. Effective ballast management regulates the filling and emptying of ballast tanks to maintain proper trim, draft, and balance during navigation and docking. With the enforcement of the Ballast Water Management (BWM) Convention by the International Maritime Organization (IMO), vessels must implement a Ballast Water Management Plan (BWMP) and maintain a Ballast Water Record Book to comply with international regulations. This study aims to develop a PLC- and HMI-based ballast control system that enhances monitoring and automation of ballast operations. The system is designed to improve control accuracy, diagnostic capabilities, and operational flexibility while ensuring compliance with IMO regulations. The research methodology involves system design, hardware integration, and software programming to create an automated control and monitoring solution. The PLC system utilizes digital inputs to operate pumps and valves, while analog sensors measure tank levels and pressure. The HMI interface displays real-time data, enabling seamless user interaction. The results demonstrate that the proposed system significantly enhances ballast operations by improving automation, control accuracy, and monitoring capabilities. The system ensures safe and efficient ballast management while facilitating regulatory compliance. These findings highlight the potential of PLC and HMI technologies in advancing maritime automation and control systems.
