Ship Main Engine Research Articles

Study of ship-based carbon capture optimization considering multiple evaluation factors and main engine loads

Ship-Based Carbon Capture (SBCC) technology presents a promising approach to reduce greenhouse gas emissions in the marine transportation. Solvent-based carbon capture has emerged as a leading technology for SBCC, primarily due to its low retrofit costs and effectiveness in treating flue gas with low carbon content. However, challenges remain in optimizing system operation efficiency under the variable conditions of ship main engine loads and in understanding the mechanisms by which process parameters influence key evaluation factors. Consequently, this study established a pilot-scale experimental platform for solvent-based SBCC and developed a carbon capture model based on it. The influence of process parameters, such as main engine exhaust flow rate and liquid/gas ratio (L/G), on the evaluation factors was thoroughly explored. With the utilization of Shapley Additive Explanations (SHAP) analysis to quantify the influence of process parameters on the evaluation factors, a multi-objective optimization equation is proposed. The combination of machine learning and optimization algorithms offers an efficient approach for determining the optimal process of the SBCC system under different main engine loads. The research results show that the main engine exhaust flow rate is the most important process parameter affecting the carbon capture rate (CR), with an influence ratio as high as 64.33%. As the main engine exhaust flow rate increases, the maximum CR decreases from 97.84% to 61.13%. Although the extreme value of the regeneration energy consumption (REC) also decreases from 6.66 to 4.42 GJ/t CO2, the solvent flow rate's influence on REC is also significant, with influence ratios of 38.49% and 35.53%, respectively. A data-driven approach examined the optimal operating conditions at eight main engine loads, achieving a carbon capture rate prediction error of only 1.42% and a maximum REC error of only 0.55 GJ/t CO2. This study provides essential guidance for assessing the suitability of SBCC systems.

A hybrid predictive maintenance approach for ship machinery systems: a case of main engine bearings

A hybrid maintenance strategy is proposed, combining reliability-centered and condition-based maintenance strategies to prevent engine failures. A case study on the lubrication deficiency of a ship's main engine bearings was conducted. The reliability-centered maintenance phase is based on reliability-increasing rules, equipment facts, and a knowledge base. Then, a strategy is developed where system parameters are continuously monitored. These parameters are evaluated in the inference engine, and maintenance recommendations are provided to the ship operator. The investment cost of th developed system is discussed using a real engine failure case. The study shows that the strategy can improve maintenance on existing ships and system reliability at low costs. The methodology offers a cost-effective approach for the sustainability of the main engine, as demonstrated by a real crankshaft failure report. Unlike existing practices, it provides influential maintenance decisions based on evaluating system parameters within four operation ranges. Simulations show it detects insufficient lubrication faults at low engine loads, superior to current applications. The proposed approach suits different types of existing and newly built ships, engines like dual-fuel, and technologies such as semi-autonomous ships.

Investigation of emission characteristics of a marine cargo ship in real-world conditions

Pollution caused by ship emissions will considerably impact coastal areas. A test system that matched the actual conditions of a ship was designed based on a portable emission measurement system (PEMS), and the emission characteristic of gaseous and particle emissions and the particle size distribution of the ship's main engine were investigated under real-world operating conditions. The results showed that the emission concentrations of the main pollutants fluctuated greatly under the departure, anchoring, and docking conditions, and the peaks of CO, CO2, and NOx emissions appeared under these transient conditions. The emission concentrations of CO2, hydrocarbons, particle number (PN), and particulate mass increased with the increase in speed. The PN-based particle size distribution of the engine presented a unimodal distribution under daily operating conditions. The maximum emission factor of NOx based on the engine power was 29.53 g/kWh at the engine speed of 66 r/min. The results of the study may contribute to supplementing the emission factors of this type of ship, and provide data support for monitoring and assessment of the marine environment.

Particulate Matter (PM) and Parent, Nitrated and Oxygenated Polycyclic Aromatic Hydrocarbon (PAH) Emissions of Emulsified Heavy Fuel Oil in Marine Low-Speed Main Engine.

To understand the influences of emulsified fuel on ship exhaust emissions more comprehensively, the emissions of particulate matter (PM), nitrated, oxygenated and parent polycyclic aromatic hydrocarbons (PAHs) were studied on a ship main engine burning emulsified heavy fuel oil (EHFO) and heavy fuel oil (HFO) as a reference. The results demonstrate that EHFO (emulsified heavy fuel oil) exhibits notable abilities to significantly reduce emissions of particulate matter (PM) and low molecular weight PAHs (polycyclic aromatic hydrocarbons) in the gas phase, particularly showcasing maximum reductions of 13.99% and 40.5%, respectively. Nevertheless, burning EHFO could increase the emission of high molecular weight PAHs in fine particles and pose a consequent higher carcinogenic risk for individual particles. The total average (gaseous plus particulate) ΣBEQ of EHFO exhausts (41.5 μg/m3) was generally higher than that of HFO exhausts (18.7 μg/m3). Additionally, the combustion of EHFO (extra-heavy fuel oil) can significantly alter the emission quantity, composition, and particle-size distribution of PAH derivatives. These changes may be linked to molecular structures, such as zigzag configurations in C=O bonds. Our findings may favor the comprehensive environmental assessments on the onboard application of EHFO.

Prediction of main engine power of oil tankers using artificial intelligence algorithms

In the preliminary ship design, the accurate determination of a vessel’s main engine power is one of the most critical aspects next to service speed, main particulars, and cargo capacity. However, this task can be quite intricate due to its reliance on an extremely great number of influencing factors. In the research that is presented in this paper dataset of 357 oil tankers was gathered and developed to research the idea in which genetic programming is applied to the mentioned dataset to obtain mathematical equations (MEs) that can estimate the ship’s main engine power with high accuracy. The highest estimation accuracy of MEs is achieved by tuning the GP hyperparameter values through the random hyperparameter search (RHS) method. The initial dataset was divided into train and test datasets in a 70:30 ratio. The train dataset was used to train GP in a 5-fold cross-validation process and after the process was done the obtained MEs were evaluated on the test dataset. To evaluate the GP training testing process several evaluation metrics were used i.e., coefficients of determination (R2), mean absolute error (MAE), root mean square error (RMSE), and length of obtained MEs. The conducted investigation showed that GP generated MEs that can estimate ship main engine power with high accuracy.

Bi-objective ship speed optimization based on machine learning method and discrete optimization idea

With the introduction of increasingly stringent carbon dioxide (CO2) emission regulations in the shipping industry, shipping companies face significant pressure to reduce emissions while ensuring profitable ship operations. A practical bi-objective speed optimization (BSO) algorithm for container ships is developed based on the variable weight idea, the discrete optimization idea, and the ideal point method to meet the urgent needs of shipping companies to improve operating profits and reduce emissions. By constructing two BSO models of ship main engine fuel consumption-ship sailing time and ship operating costs (SOC)-ship CO2 emissions (SCE), the effectiveness of the BSO algorithm is confirmed through extensive optimization experiments. The results show that compared to the historical sailing results, the BSO reduces the SOC by 4.43 % without causing a significant increase in the SCE, and reduces the SCE by 0.25 %. Moreover, the results demonstrate the effectiveness and feasibility of the BSO in reducing the cost of ship operations while reducing the impact on the environment. The results provide valuable references for shipping companies in the trade-off analysis between economic and environmental benefits and optimization decision-making.

Analysis Of Ship Main Engine Procurement Process In The Shipyard Industry Using Supply Chain Operation Reference Method (SCOR) (Case Study: PT XYZ)

As a sector playing a crucial role in ship construction and repair, the shipbuilding industry faces significant challenges in material procurement, where materials constitute 50-70% of the total project cost. One of the materials requiring paramount attention is the ship's main engine. Effective supply chain management is critical to enhancing efficiency and effectiveness in the procurement process of ship engines. However, supply chain performance measurement research, especially in ship engine procurement, still needs to be improved. Therefore, this study aims to identify relevant performance metrics, analyze critical performance indicators, and provide recommendations based on the SCOR (Supply et al.) framework to improve ship engine procurement. The research results present 24 metrics distributed into four performance attributes based on SCOR 12.0, with 22 selected metrics aligned with the company's context. Analysis using the AHP method indicates that the reliability attribute has the highest weight (0.296), with the metric "Percentage of procurement received on time as per request" being the top priority (weight 0.143). This study provides a holistic view of crucial aspects of the ship engine procurement supply chain, supporting companies in enhancing their performance in the procurement process.

Efforts to Improve Ship Main Engine Efficiency and Ensure Its Safety

Efforts to improve ship main engine efficiency and ensure its safety have been ongoing endeavors in the maritime industry, driven by the dual imperatives of economic competitiveness and environmental sustainability. The main engine of a ship serves as its heart, propelling it through the vast expanses of the world's oceans while consuming significant quantities of fuel. Therefore, enhancing its efficiency directly impacts operational costs and reduces the environmental footprint associated with maritime transport. One primary focus of improving main engine efficiency lies in the advancement of engine design and technology. Over the years, there has been a concerted effort to develop engines that offer higher power output while consuming less fuel. This has led to the emergence of more efficient engine designs, such as slow-speed two-stroke engines and high-pressure, common-rail fuel injection systems. These innovations optimize fuel combustion, minimize energy losses, and enhance overall propulsion efficiency. Moreover, ongoing research and development efforts are aimed at harnessing alternative fuels and propulsion technologies to further enhance efficiency and reduce environmental impact. LNG (liquefied natural gas) has gained traction as a cleaner-burning fuel alternative, offering significant reductions in sulfur oxides (SOx) and nitrogen oxides (NOx) emissions compared to traditional marine fuels. Additionally, the exploration of hybrid and electric propulsion systems holds promise for reducing greenhouse gas emissions and improving overall energy efficiency. Ensuring the safety of ship main engines is paramount to the reliability and operability of vessels at sea. A robust maintenance regimen is essential to identify and address potential issues before they escalate into costly failures or pose safety hazards. Routine inspections, preventive maintenance, and condition monitoring play crucial roles in detecting abnormalities, wear, and tear, allowing for timely interventions and repairs. Furthermore, advancements in predictive maintenance technologies, such as remote monitoring systems and data analytics, enable real-time assessment of engine performance and early detection of potential malfunctions. The ARAS method lacks the capability to handle ambiguity, subjective judgments, and coping with incomplete information. It relies on unbiased good judgment to address uncertainty, particularly in unknown and complex conditions, making it a valuable approach. The method provides options for sequencing and analysis based on facts and special cases, allowing selectors to express both optimistic and rational attitudes. While it appears numerical on paper, it offers the flexibility to create e-learning pathways tailored to individual needs, emphasizing the importance of mastery. The proposed integrated software for this method is both cost-effective and validated for suitability, ensuring its practical application. Advanced Engine Designs, Improved Monitoring and Maintenance, Enhanced Fuel Management, Innovative Propulsion Technologies, Automation and Remote Monitoring and Advanced Materials and Coatings. the Rank Efforts to improve ship Main Engine efficiency and Ensure its safety for Additive Ratio Assessment method. Advanced Materials and Coatings is showing the highest rank and Advanced Engine Designs is showing the lowest rank. Fuel Efficiency Improvement, Emissions Reduction, Reliability and Maintenance Costs and Safety Performance.

New approaches to assess and improve ship operating performance

The deterioration in the technical conditions of the main engine, hull, and propeller over time in service is natural and causes adverse effects on ship operating performance, so determining and overcoming this phenomenon is necessary. However, effectively solving this problem is not simple because it is affected by many complex and random factors such as engine deterioration, increased roughness of hull and propeller surfaces, changes in sea state and ship load, etc. In this study, our new approach based on the black-box method and detailed propeller diagrams provides an effective way to assess and improve ship performance both under specific operating conditions and after a period of service. This method was verified and validated with the test data of the Glory Star oil tanker and applied to the Duong River dry cargo ship in Vietnam to determine its performance degradation and provide solutions to overcome this problem. The results showed that after 5 years out of dry dock, the study ship's performance or propulsion efficiency was reduced by about 8.6%, resulting in an increase in fuel consumption of about 6.5% and a decrease in ship speed of about 14.7%. By applying technical solutions such as tuning the engine operating mode and choosing a practical propeller design point, the performance of this ship was greatly improved and brought about high economic and technical efficiency. Especially, the cutting of the propeller edges not only solved the torque-rich phenomena occurring on the study ship's main engine after 5 service years, but also saved 5.1% and 4.9% in hourly fuel consumption, and increased 3.9% and 4.9% in ship speed, calculated for ballast and full load sea trials, respectively.

Research on Ship Main Engine Fuel Consumption Model With Data Integration and Noise Cleaning

Research on Ship Main Engine Fuel Consumption Model With Data Integration and Noise Cleaning

Valve Setting Using Fuzzy Logic Method To Control Main Engine Coolant Flow

The main objective of this research is to improve the operating efficiency and performance of ship main engines by optimizing coolant flow. Improper coolant flow can cause excessive temperature rise in the engine, which in turn can reduce engine life and efficiency. In this research, the coolant flow control system is implemented using the fuzzy logic method. Fuzzy logic allows modeling that is more adaptive to parameter variations and uncertainties in the operational environment. Fuzzy rules are developed based on practical knowledge of experts and operational data related to the host machine. The test was carried out through a simulation using a water flow control circuit that supplies the coolant to the ship's main engine with the main components being an ESP32 microcontroller chip and three DS18B20 temperature sensors. The results of this research show that the use of fuzzy logic in regulating coolant flow is able to provide a faster and more accurate response to changes in engine operational conditions. This has the potential to increase cooling efficiency and prevent engine over-temperatures, which can ultimately increase the overall service life and performance of the host engine. The practical implications of the results of this research can be applied in the development of more intelligent and adaptive control systems for various types of host machines, with the potential to increase operating efficiency and reduce the risk of damage due to excessive temperatures

Dynamic Information System for Failure Analysis with It’s Application on Ship Main Engine

Dynamic Information System for Failure Analysis with It’s Application on Ship Main Engine

Evaluation and optimization of an engine waste heat assisted Carnot battery system for ocean-going vessels during harbor stays

The pollution and environmental damage caused by ship emissions during docking is an urgent issues that needs to be addressed. In this study, a jacket water waste heat Carnot battery (JCB) system is designed as an energy storage device to recover the water waste heat of the ship's main engine cylinder liner and as a power output device when the main engine stops in port. The JCB system is evaluated and optimized from the perspectives of thermodynamics, exergy, and cost, with a focus on the performance under different working fluid combinations. The results show that improving the efficiency of the compressor, turbine, and recuperator can significantly enhance the system's performance, with the compressor and turbine being the most expensive components. The heat exchanger has the highest exergy destruction, accounting for almost half of the total system. In the multi-objective optimization of different working fluid combinations, R365mfc/R365mfc is found to be the best choice, with the power-to-power efficiency of the system reaching 110.15 % and the 5-year levelized cost of storage (LCOS) being 0.139 $/kWh. A case study of the actual route shows that the JCB system designed in this paper can meet the power demand of 100 %, 35.5 %, 61.91 %, and 56.9 % in the four segments during harbor stays. The JCB system proposed in this study provides a new solution for the reduction of emissions and environmental protection during the docking of ships.

Waste heat recovery assessment of triple heat-exchanger usage for ship main engine pre-heating and fresh water generation systems

In this study, the applicability, fuel saving and CO2 emission reducing potential of the triple heat-exchanger fed by the diesel generator exhaust gas with and without water steam have been studied for ship’s one and two main engines pre-heating and freshwater generation (FWG) cycles under port conditions with conducting energy and exergy analysis. The performance criteria (PC) and exergy efficiency (ε) values of the main engine pre-heating and freshwater generator systems of the Ro-Ro ship selected for the case study were determined by written Matlab 2021a codes merging CoolProp 6.4.2 database with Python. It was determined that even at the lowest operating load of the diesel generator (25%), the exhaust heat energy would be sufficient to preheat the main engine and generating fresh water with also saving fuel consumption. As a result, during the 12-h port period, each 1 kW heat energy reduction on steam will provide 0.0853 kg/h fuel saving in the boiler. Thus, 273 kg CO2 emission will be reduced for each kW of heat energy to be obtained. Considering the comparatively increased PC and ε values of whole system cycle containing common triple heat-exchanger for two main engines, it can be used conveniently and reliably on ships.

Thermodynamic and feasibility analysis of using diesel generator exhaust gases for ship main engine preheating at port periods

In this study, the feasibility and potential impact on fuel consumption of the proposed preheating system driven by diesel generator exhaust gas instead of steam to satisfy main engine pre-heating demands especially under port operation conditions have been analyzed according to the 1st and 2nd laws of thermodynamics. The proposed novel term named performance criteria (PC) and exergy efficiency (ε) values of the main engine preheating and cooling water systems of the Ro-Ro ship selected for the case study under the existing voyage and port operating conditions have been determined by written Matlab-2021a codes merging CoolProp-6.4.2 database with Python. It was determined that even at the lowest operating load of the diesel generator (25%), the exhaust heat energy would be sufficient to preheat the main engine with also reducing the fuel consumption. As a result, during the 12-hour port period, 22% of the boiler fuel consumption and 8% of the ship's fuel consumption can be saved. Accordingly, if a shipping company uses Mine Gas Oil as fuel, it will be able to achieve fuel savings of approximately US$ 32.000 on annual basis. Considering the fuel saving values, it has been determined that 1.016 tons of CO2 emissions for per port operation and 106 tons of annual CO2 emissions can be reduced. It was determined that, the PC and Ɛ values of the system decrease as the ambient temperature increases. In this context, there is a 7% decrease in the PC and a 5% decrease in the Ɛ for existing system and 8% decrease in the PC and a 2.5% decrease in the Ɛ for proposed system. It was also determined that the proposed new system is both physically and economically feasible and that the investment cost, which was determined to be in the range of US$ 30.000-US$ 35.000, can pay for itself after 1 year.

Research on the Operational Performance of Organic Rankine Cycle System for Waste Heat Recovery from Large Ship Main Engine

Based on the analysis of the waste heat distribution characteristics of a typical ship two-stroke low-speed main engine (model: MAN 8S65ME-C8.6HL, the specified maximum continuous rating SMCR: 21,840 kW) under different loads, two different types of organic Rankine cycle (ORC) systems, namely the basic system (BORC) and the preheated system(PORC), were constructed to recover the ship main engine’s exhaust gas waste heat and jacket cooling water waste heat. Using the thermodynamic simulation model of the system, the main performance indexes, including net output power of the two ORC systems were studied with the variation of seawater temperature and main engine load, and the annual ship fuel saving and annual carbon emission reduction generated by the two systems were compared and analyzed. It was found that the maximum net output power of the BORC system and PORC system were 445.3 kW and 491.3 kW, respectively, when the ship’s main engine load was 100%, and the outboard seawater temperature was 20 °C; the maximum thermal efficiency was 12.84% and 12.71%, respectively; under the annual operation, the fuel saving of BORC system and PORC system can be 456 tons and 510 tons, respectively, and the carbon emission reduction was 1416 tons and 1581 tons, respectively. The analysis found that the net output power of the PORC system is always greater than that of the BORC system. When the outboard seawater is lower, and the main engine load is more than 80%, the net output power difference between the PORC system and BORC system gradually expands, and the improvement of ORC system performance is more evident by adding a preheater. It can be concluded that when the ship was mainly operated in the sea area with low seawater temperature and the main engine was running under high load most of the time, selecting the PORC system to recover the waste heat of the main engine was more advantageous.

Features of low-temperature corrosion protection of cylinder sleeves of ship low-speed engines

The article examines the specifics of solving one of the problems of low-speed marine engines, during which low-temperature corrosion of cylinder liners occurs during operation at minimum and partial load modes. An overview of the cooling systems of ship's main engines was conducted and possible prospects for improving the cooling systems of ship's diesel engines were considered. Attention is paid to the causes and methods of combating low-temperature corrosion of ship's main engines. The methods of regulating the cooling system of marine diesel engines were considered, and it was determined that the modern concept of regulation in the cooling system should include both automatic regulation of operational parameters due to the installation of frequency-regulated cooling system pumps, and regulation of the water-chemical parameters of the cooling system. Methods of regulating the operating parameters of the pumps in the cooling system of the ship's main engine were also considered, which use the principle of frequency regulation of centrifugal pumps to ensure the modes of operation with the highest efficiency. Thus, frequency regulation is an energy-efficient way of regulating centrifugal pumps with variable coolant flows in ship engine cooling systems and one of the ways to maintain an optimal temperature state. The possibility of modernizing the cooling system of cylinders of low-speed engines according to the principle of the LDCL system to reduce the impact and occurrence of low-temperature corrosion was considered

Maintenance Design of The Main Engine Support Systems on KMP. Kormomolin Under System Dynamics Scheme

The operational activities of the ship's main engine support system elevated the possibility of failure. The main engine support system at KMP. Cormomolin, which belongs to PT. ASDP Indonesia Ferry (Persero), is extremely crucial to the ship's operation. Once the ship is not sailing, maintenance and repair can be handled. The component evaluation engine can be employed to accurately estimate inadequacies in the main support system. Failure Mode Effect and Critical Analysis (FMECA) identifies the root cause of critical component failures such as filters in the fuel system and cooler and sea chest filters in the cooling system. This study generates maintenance recommendations for the main engine support system for five years, including: fuel oil filter maintenance intervals every 151 hours at a cost of IDR 14,169,072, cooler maintenance intervals every 2481 hours at a cost of IDR 16,313,508, and sea chest filter maintenance intervals every 722 hours at a cost of IDR 11,167,152. For the fuel system, the cost care percentage is 81%, and for the cooling system, it is 46% after 5 years.

Big data-driven carbon emission traceability list and characteristics of ships in maritime transportation-a case study of Tianjin Port.

As China's shipping industry continues to develop, ship emissions have become a significant source of pollutants. Consequently, it has become imperative to comprehend accurately the nature and attributes of ship pollutant emissions and understand their causation and effect as a crucial aspect of pollution control and legislation. This paper employs high-precision automatic identification system (AIS) dynamic and static data, along with pollutant emission parameters, to estimate the pollutant emissions from a ship's main engine, auxiliary engine, and boiler using a dynamic approach. Additionally, the study considers the sailing state and trajectory of the vessel and analyzes the characteristics of ship carbon emissions. Taking Tianjin Port as an example, this study conducts a multi-dimensional analysis of pollutant emissions to gain insight into the causation and effect of pollutants based on the collected big AIS data. The results show that the pollutant emissions in this region are mainly concentrated in the vicinity of Tianjin Port land port area, Dagusha Channel, and the Main Shipping Channel of Tianjin Xingang Fairway. Carbon emissions peak in September and are lower in June and December. Through accurate analysis of pollutant emission sources and emission characteristics in the region, this paper establishes the regular relationship between pollutant emissions and possible influencing factors and provides data support for China to formulate accurate pollutant emission reduction policies and regulate ship construction technology and carbon trading.

Research on Online Diagnosis of Ship Main Engine with Unbalanced Sample

The traditional ship main engine fault diagnosis model is difficult to update in real time. In addition, the main engine also has the problem of more monitoring parameters and less fault samples. In order to eliminate the influence of the above problems, improve the diagnostic accuracy. Firstly, in order to solve the problem that the traditional diagnosis model is difficult to update online in real time, Online Sequence Extreme Learning Machine is adopted as the diagnosis model, which can update the model directly online by using real-time samples. Then, for the problem that the sample set collected in the online update process is much smaller than the normal sample set, BorderlineSMOTE is used to generate fault samples to balance the sample set, and feature extraction and dimension reduction are carried out in combination with KPCA to further improve the training speed and diagnostic accuracy of the model. Taking the main engine fuel system as an example, the experimental results show that the proposed algorithm has high diagnostic accuracy and good stability, and is suitable for the research of ship main engine fault diagnosis.