Dai Liu

The problem of global climate change is becoming increasingly serious, drawing worldwide attention to the need for carbon emissions reduction. As a primary mode of transport, maritime shipping accounts for 2% of global carbon emissions. Therefore, researchers have turned their attention to marine carbon emissions. Specifically, lifecycle assessment (LCA) has attracted wide attention due to its comprehensiveness and objectivity. This article reviews alternate fuels like biodiesel, liquefied natural gas (LNG), methanol, ammonia, and hydrogen. These fuels generate fewer Tank-to-Wake (TTW) carbon emissions than conventional diesel but higher emissions in the Well-to-Tank (WTT) stage owing to production-related emissions, resulting in varying overall carbon footprints. Most carbon emissions in marine transportation come from fuel consumption. Selecting the shortest route can cut fuel use and emissions. Port greening and electrification are vital for emission cuts. Current marine LCA research exhibits key gaps, including fragmented case studies, a lack of methodological standardization, and insufficient dynamic predictive capacity, severely constraining its guiding value for industry decarbonization pathways. This study systematically reviews and categorizes marine LCA research from the past decade in both Chinese and English from the Web of Science and CNKI databases through a Ship-Route-Port framework. Specifically, 34 papers underwent quantitative or qualitative analysis, comprehensively comparing the full lifecycles of six mainstream marine alternative fuels: biodiesel, LNG, methanol, ammonia, hydrogen, and electricity. This study also underscores the need for unified standards to boost low-carbon fuel use and explores the unique challenges and uncertainties involved in applying LCA to the marine sector. LCA applied to the maritime sector shows promise as a valuable tool for guiding low-carbon transition strategies.

The marine large-bore low-speed engines face challenges such as complex testing and large computational workload. A feasible solution is to adopt a combined optimization approach using one-dimensional performance simulation and three-dimensional computational fluid dynamics (CFD) simulation. This paper utilizes a one-dimensional full-cycle simulation model of a marine large-bore low-speed engine with a complete scavenging and combustion coupling process. Combined with the Non-dominated Sorting Genetic Algorithm II (NSGA-II), it conducts multi-objective optimization based on the controlled variables such as the closing time of the exhaust valve, the injection timing, and the injection duration. Within a short period of time, it obtains the optimized boundary conditions. In the three-dimensional CFD simulation, the indicated thermal efficiency was increased by 1.139% and 1.264% respectively, and the maximum error compared with the one-dimensional simulation results was 1.33% and in the three-dimensional CFD simulation, the CO2 emissions were reduced by 2.2052% and 2.4886% respectively, with a maximum error of 1.69% compared to the one-dimensional simulation results. Ultimately, the results of the one-dimensional optimization were consistent with those of the three-dimensional CFD simulation. Moreover, the computing time required was significantly less than that of the traditional optimization based on three-dimensional CFD simulation.

In large-bore two-stroke diesel/nature gas dual-fuel marine engines, a certain quantity of diesel is injected into the cylinder to satisfy the full-power output engine rated power of the gas mixture. However, the ignition and flame propagation process based on the injection strategy of diesel direct injection combined with diesel jet flame on the ignition and combustion of natural gas is unclear, which directly affects the power and the thermal efficiency of engine and emissions. Therefore, this work numerically investigates the flame propagation characteristic under the strategy of the main and pilot diesel modes. The influence of the injection timing and proportion of diesel on combustion and emission performance are further analyzed. The results show that the influence of the injection timing of main diesel (MDIT) on the combustion process and emission performance is more obvious than that of the injection timing of pilot diesel (PDIT). The results indicate that the MDIT increased from −2°CA to −8°CA, the power increased by 316 kW, and the thermal efficiency improved by 1.5%. However, the CO₂ emissions increased by 10.5 g/kWh, and the NOx emissions increased by 0.7 g/kWh. Additionally, an early PDIT is not conducive to the rapid organization of combustion, resulting in decreased engine power and thermal efficiency. Furthermore, it was found that the power improved by 50 kW and the thermal efficiency improved by 0.6%, with a decrease in the main diesel ratio (MDR) from 100% to 90%. Meanwhile, the CO₂ emissions decreased by 4 g/kWh, although there was no obvious change in NOx emissions with the advance of MDR.

Considering the trade-off relationship between brake specific fuel consumption (BSFC), combustion noise (CN) and NOx emission, it is a difficult task to optimize them simultaneously in a marine diesel engine. In order to overcome this problem, a novel genetic algorithm and improved chicken swarm optimization (GA-ICSO) hybrid algorithm was proposed, where the enhanced Levy flight and adaptive self-learning factor were introduced in this algorithm. Computational comparisons between GA-ICSO and other effective optimization algorithms were performed using four standard test functions, validating the improvements in both accuracy and stability for GA-ICSO. Furthermore, a predictive engine model based on a phenomenological approach was developed and validated. This model coupled the proposed algorithm for the optimization of a marine diesel engine. In the optimization process, five control parameters were selected as design variables, including injection timing (IT), intake cam phasing (ICP), intake valve closing (IVC), intake temperature and pressure. Results show that, a lower objective value can be obtained by GA-ICSO than other widely used optimization algorithms for all the operating conditions. Besides, by comparing the results between the optimal generations and baselines, it could be found that, under the condition of 50%, 75% and 100%load, CN is reduced by 10.7%, 4.9% and 3.9%, NOx is decreased by 15%, 31% and 33%, and BSFC is suppressed by 10.8%, 13.3% and 9.5%, respectively. Finally, heat release rates, noise spectrums, cylinder pressures and temperatures were all employed to discuss the optimization results of a marine diesel engine under different working conditions.