One-dimensional Simulation Model Research Articles

Numerical simulation of underwater explosive shock wave with gas layer charge

Abstract To investigate the effect of the gas layer on the explosive’s underwater explosion shock wave load, based on AUTUODYN kinetic analysis software, we establish a one-dimensional underwater explosion numerical simulation model with a gas layer charge and study underwater explosion with a gas layer charge on the impact of the peak pressure and specific impulse of the shock wave underwater explosion. The results show that the gas’s low impedance and the continuous reciprocal reflection of the shock wave in the layer of the shock wave in the water led to a lower pressure Peak pressure of the shock wave in the water and its post-wave oscillatory decay waveform. With the increase of the uncoupling coefficient, the peak pressure of the shock wave in the water decreases, and the specific impulse increases and then decreases, through the range of 5∼1, 000 kg of TNT spherical charge underwater explosion calculations, to verify the reliability of the conclusions. The study’s conclusion shows that applying an underwater blast protection project with a gas layer charge should be reasonably designed for gas layer thickness to avoid the enhancement of the impulse but increase the harm of the shock wave.

Prediction of Pollutant Emissions from a Low-Speed Marine Engine Based on Harris Hawks Optimization and Lightgbm

With the rapid development of data science, machine learning has been widely applied to research on pollutant emission prediction in internal combustion engines due to its excellent responsiveness and generalization ability. This article introduces Lightgbm (LGB), which belongs to ensemble learning, to predict the pollutant emissions from a low-speed two-stroke marine engine. The dataset used to train LGB was derived from a one-dimensional performance simulation model of the engine, which was rigorously verified for its reliability by experimental data. To further improve the forecast performance of the LGB model, we used Harris Hawks Optimization (HHO) to automatically optimize the hyperparameters of the model, and finally, we analyzed the importance of the model features. The results show that changes in engine control parameters have significant influences on NOx and soot emissions from the engine, which can serve as the basis for the selection of the LGB model features; the LGB model was able to accurately predict pollutant concentrations from the engine with much higher accuracy than a single decision tree (DT) model; combining with HHO, the predictive ability of the LGB model was significantly improved, such as for the validation set prediction results, the mean absolute error (MAE) was reduced by about 20%, the mean squared error (MSE) was reduced by about 30%, and the coefficient of determination (R2) was increased by about 0.005; and the importance analysis of the model features indicated that the combustion condition of the fuel was highly correlated with the generation of the pollutants, and the fuel injection phases can be adjusted in practice to achieve highly efficient and low-emission processes of combustion. The results of this study can provide references for the development of a new generation of highly efficient and low-pollution marine engines.

Analysis of Species Concentrations in Bifunctional Air Electrodes Using Mathematical Modeling and Simulation

Metal-air secondary batteries using aqueous alkaline solutions are attracting attention as a next-generation large-scale energy storage system. However, the large overpotential of the bifunctional air electrode is a challenge for its practical application. In order to reduce the overvoltage, one approach is to optimize the design of the electrode to enhance both electrochemical as well as transport properties within. We have previously estimated the oxygen diffusion resistance in bifunctional air electrodes with different thicknesses and electrolyte solutions from the difference in the steady state potential under air and oxygen flow. We identified that the reaction zone for the oxygen reduction and evolution reactions concentrated on the gas and electrolyte sides of the catalyst layer, respectively. 1 On the other hand, it is difficult to analyze local reaction rates in more detail since gas diffusion electrodes have a complex structure with a mixture of solid, gas, and liquid. In this study, we analyzed the local conditions in gas diffusion electrodes by combining digital simulations using finite difference methods and electrochemical measurements. The electrolyte solution's distribution significantly affects the simulation result since the electrolyte solution works as both an ionic conductiont and an obstacle to oxygen transport.2 Therefore, the electrolyte solution distribution in the electrode was determined by impedance analysis using a transmission line model, and a simulation model was constructed based on this impedance analysis.Figure 1 shows the Nyquist plot of a gas diffusion electrode at OCV. A transmission line-type frequency dependency is observed in the high-frequency region. The impedance simulated with an equivalent circuit where the ion transport resistance in the electrode does not change in the thickness direction shows a relatively significant difference from the measured one. On the other hand, the impedance simulated with an equivalent circuit with the linear decrease in the ionic conductance from the electrolyte to gas diffusion layer sides showed good agreement with the measured one. This result indicates that the amount of electrolyte in the gas diffusion electrode decreases from the electrolyte side to the gas diffusion layer side. Simplifying the pore structure with the porosity and average pore size obtained with the Barrett-Joyner-Halenda (BJH) method and the tortuosity calculated from the Bruggeman’s equation, the electrolyte thickness was calculated to be 2.1 and 1.1 nm at the electrolyte and gas sides, respectively. The local conditions in the electrode obtained with a one-dimensional simulation model based on the obtained electrolyte solution distribution will be presented at the site. Acknowledgment This work was financially supported by RP-LEAD with DFG (JPJSJRP20221602 and SCHR 1756/1-1).

Research on control strategy of electric vehicle thermal management system motor

Abstract The low efficiency and difficulty in low-temperature heating are the challenges currently faced by the thermal management system of new energy vehicles. A multi-heat source vehicle thermal management system for waste heat cascade recovery and utilization was proposed, and the performance of the vehicle thermal management system was studied through a combination of component testing and one-dimensional simulation. Based on a one-dimensional simulation model, the characteristics of the motor waste heat source are analyzed. The increase in the inlet water temperature of the motor coolant will lead to enhanced heat dissipation of the motor to the air, resulting in a waste of motor waste heat. Based on the results of the analysis, an energy cascade management strategy is constructed. The optimal heating mode is selected by collecting temperature signals such as motors, and the cut-off valve is controlled through logic gates to achieve flexible switching of different modes. The system effectively reduces the energy consumption of thermal management systems, which is of great significance for developing thermal management systems for new energy vehicles.

Analysis of cooperative cooling performance between the battery and cabin of pure electric vehicles

Abstract The cooperative cooling of the cabin and battery in pure electric vehicles (PEVs) is crucial for the comfort, thermal safety of the occupants, and the lifespan of the batteries. Therefore, a well-designed thermal management system (TMS) is particularly important. Thus, this paper constructs an cooperative cooling for the battery pack circuit and the cabin circuit in parallel, aiming to enhance the vehicle system’s integration and reduce energy consumption. Firstly, a one-dimensional simulation model of the cooperative TMS is established, and the model is calibrated through experiments. Subsequently, the system’s performance is analyzed under different ambient temperatures. The study finds that as the ambient temperature increases, the system’s energy consumption rises, and the Coefficient of Performance (COP) decreases. Moreover, when the system switches from the simultaneous cooling mode of the cabin and battery to the sole cooling mode of the cabin, the temperature of the cabin will fluctuate to a certain extent, within a range of 2°C. At same time, the COP value also increases with the switch of the mode. Finally, the analysis of the simultaneous cooling mode of the cabin and battery side under different ambient temperatures reveals that as the ambient temperature increases from 34°C to 42°C, the exhaust temperature, pressure ratio, and compressor speed increase accordingly, while the compressor efficiency decreases. The condenser and chiller experience a reduction in their heat transfer efficiency by 59.4 watts per degree Celsius and 218.5 watts per degree Celsius, respectively. Conversely, the evaporator’s heat transfer efficiency undergoes an enhancement of 6.77 watts per degree Celsius.

Monitoring and control of air filtration systems: Digital twin based on 1D computational fluid dynamics simulation and experimental data

This study presents the development of a digital model based on one-dimensional computational fluid dynamics for the monitoring and control of filtering systems used for removing flour, dust, and other particulates from the airflow arriving from various sections of industrial production plants.Focusing on a pilot plant equipped with a cyclone bag filter, historical experimental data was integrated with the results of a one-dimensional fluid dynamics simulation model to create a digital twin capable of real-time control and regulation of industrial plants. In particular, measured pressure drop data under different clogging conditions were interpolated to generate the characteristic curves of the filter under various clogging conditions, to be implemented within the digital model of the plant. The generated model, validated through a dedicated experimental campaign, accurately predicted the airflow rate and pressure distribution across the plant. The system’s capability to adapt to changing operational conditions, such as clogging, was demonstrated through simulation, highlighting the model’s utility in maintaining the desired operation levels while minimizing the need for extensive sensor networks.The analyzed case study in the field of air filtration systems aims to fill the gap in the scientific literature related to the application of Digital Twin technology to the control of industrial manufacturing plants. The findings highlight the potential of digital twins in monitoring and control, as well as predictive maintenance, of industrial systems. The findings highlight the potential of Digital Twins in monitoring and control, as well as predictive maintenance, of industrial systems. Future research activities will explore the model’s applicability in failure and anomaly detection, to further enhance predictive maintenance of air filtering systems.

Variance-based global sensitivity analysis of the performance of a proton exchange membrane water electrolyzer

This study is threefold objective. First, a nonlinear one-dimensional steady-state simulation model for hydrogen production from proton exchange membrane water electrolyzer (PEMWE) is established. The model comprehensively addresses activation, diffusion overpotentials and ohmic potential drop, and particularly incorporating Nafion membrane properties in the presence of liquid water. The model is enhanced by analyzing the hydrogen crossover, introducing corresponding diffusion equations to evaluate Faraday efficiency. The model accurately quantifies voltage efficiency, hydrogen production rate and specific energy consumption, and it is validated with published experimental data found in the scientific literature. Second, a variance-based global sensitivity analysis (GSA) on the model, is employed as a metric to assess the impact of operating conditions and material characteristics on three objective functions: the hydrogen production rate; the voltage efficiency and the specific energy consumption. Third, to support the GSA analysis, genetic algorithm (GA) technique is performed to maximize hydrogen production rate while minimizing specific energy consumption. In the course of this novel investigation, it was discerned that the number of cells, the cross-sectional area of the electrolyzer, the current density and temperature all exerted a significant impact on the three objective functions. This combined approach GSA-GA provides a thorough exploration of parameter influences and an efficient optimization strategy for enhancing the model's performance. These findings provide valuable insights that can guide analysis of the performance and the optimization of the PEMWE system.

Thermal effect of VIPV modules in refrigerated trucks

The integration of Photovoltaic (PV) modules within the outer structure of commercial transporters offers a great potential as an additional source of energy that can be utilized, for example, directly by the drive train of the vehicle, or by accessory equipment. However, to understand the benefits of such a system, the effect and relevance of some thermodynamic variables introduced by the Vehicle Integrated Photovoltaic (VIPV) system must be assessed. Particularly, the share of the solar irradiance that cannot be converted into electricity by the solar cell and is instead transformed into heat must be considered for certain applications such as the transportation of goods that require a controlled temperature. A one-dimensional thermal simulation model based on a Resistance-Capacitance methodology was created and validated experimentally. The model was used to predict the thermal behavior of the box-body of a truck for a representative year in three cities in Europe (Stockholm, Freiburg, and Seville), with a known Bill of Materials (BOM), and a set of given assumptions and constraints. It was found that, under the simulated conditions laid in this study, the additional heat generated by the PV modules that manages to go through the insulation material and reach the refrigerated cargo area, may raise the temperature of the contained air by an average of 0.36 °C, 0.5 °C, and 0.67 °C, respectively for the observed cities, and as much as 3.12 °C, 2.98 °C and 2.61 °C. When forced convection caused by the movement of the truck was applied into the model (with a constant wind speed of 50 km/h), the temperature of the solar cell dropped significantly, which, for the case of Freiburg, meant an increase in the contained air temperature of a maximum of 0.6 °C. A refrigeration system was subsequently considered for a target air temperature of 2 °C and −18 °C, and it was found that for the simulated scenarios, the harvested solar energy could easily offset the additional energetic demand caused by the PV system, and, in most cases, completely balance out the total annual demand of the chiller.

Simulation Study on Combustion Performance of Ammonia-Hydrogen Fuel Engines

Ammonia is a very promising alternative fuel for internal combustion engines, but there are some disadvantages, such as difficulty in ignition and slow combustion rate when ammonia is used alone. Aiming to address the problem of ammonia combustion difficulty, measures are proposed to improve ammonia combustion by blending hydrogen. A one-dimensional turbocharged ammonia-hydrogen engine simulation model was established, and the combustion model was corrected and verified. Using the verified one-dimensional model, the effects of different ratios of hydrogen to ammonia, different rotational speeds and loads on the combustion performance are investigated. The results show that the ignition delay and combustion duration is shortened with the increase of the hydrogen blending ratio. The appropriate amount of hydrogen blending can improve the brake’s thermal efficiency. With the increase in engine speed, increasing the proportion of hydrogen blending is necessary to ensure reliable ignition. In conclusion, the ammonia-hydrogen fuel engine has good combustion performance, but it is necessary to choose the appropriate hydrogen blending ratio according to the engine’s operating conditions and requirements.

Analysis of the interactive effects of scavenge parameters on spark ignition two-stroke diesel engines

The scavenging efficiency of a two-stroke diesel engine affects the formation of the mixture in the engine cylinder, which in turn affects the engine’s performance. A one-dimensional simulation model of a two-stroke diesel engine is established using GT-POWER, and the model with original experimental data is calibrated as boundary conditions. Firstly, the influence of crankcase compression ratio on engine performance of the two-stroke engine was investigated to obtain an appropriate crankcase compression ratio; Then, based on the optimization index of scavenging efficiency, the optimal combination of engine air port structure and timing is obtained through orthogonal optimization calculation method. To achieve higher scavenging efficiency, when the phase of the air port remains unchanged, a scavenging port width ratio of 1.0 and an exhaust port width ratio of 0.8 can achieve a scavenging efficiency of 97.2%; When the air port size remains unchanged, the engine scavenging efficiency reaches 96.44% when the scavenging port timing is 123° CA and the exhaust port timing is 89° CA.

Multi-objective optimisation of heat transfer and structural strength of aero-piston air-cooled engine cylinder based on orthogonal test

Owing to their compact and lightweight structure, air-cooled aviation piston engines are used in general aviation, agriculture, and military fields. To address the kind of engine thermal load problem, this study used a horizontal four-cylinder four-stroke aviation piston air-cooled gasoline engine as the research object. Tested the engine cylinder temperature and pressure under calibrated power conditions, built a one-dimensional simulation model and a fluid–structure interaction simulation model. Four main structural parameters—fin thickness, fin spacing, fin length, and cylinder wall thickness—were considered as factors. Each factors have five levels to construct orthogonal tests to analyse their influence on the cylinder heat transfer and structural strength performance. A range analysis of the orthogonal test showed that the fin thickness had the most significant influence on the thermal stress, while the fin length most significantly influenced the temperature and cylinder hole deformation. A comprehensive frequency analysis method combining intuitive and range analyses is used to determine the optimal combination scheme, and the heat transfer and strength performance of the engine cylinder before and after optimization is compared. The results indicated that the fin thickness and length had the most influence on cylinder performance. After optimisation, the temperature decreased by 3.3 % from 198.3 ℃ to 191.8 ℃, while the thermal stress decreased by 21.9 % from 100.5 MPa to 78.5 MPa. In addition, the cylinder hole deformation decreased by 11 %, from 0.273 mm to 0.243 mm. These research results can provide a reference for the design and optimisation of heat fins of air-cooled aviation piston engines.

Numerical study on the effect of intermediate pressure pulsation on COP in the vapor injection cycle

The vapor injection cycle with flash tank and two stage compressor is known as an efficient cycle. It is known that the intermediate pressure is a key factor for COP improvement and pressure change during the injection process could reduce the COP. However, the effect of the pulsating intermediate pressure of a two-stage compressor on COP is not clear. In a previous study, the authors experimentally showed that COP varied with injection pipe length. There seemed to be a correlation between COP and the resonance phenomenon caused by pressure pulsation in the injection pipe. However, the mechanism of COP improvement is not well understood. In this study, a one-dimensional simulation model was developed to clarify the mechanism and was verified with the experimental results. The simulation results show that resonance in the injection pipe does not increase the injection mass flow rate into the suction pipe. On the contrary, backflow occurs in the injection pipe and the backflow ratio is minimum in the resonant condition. Due to the high temperature of the backflow coming from the discharge pipe, the saturated vapor from the flash tank is easily heated, causing heat loss and lower COP. It was found that COP can be improved by using resonance to suppress the backflow.

Energy-based cold-start strategies for diesel engines at extreme low temperature

The cold start of diesel engines at extreme low temperatures is currently one of the most critical problems in the field of transportation. An experiment on the cold start was conducted in a controlled environment, and a one-dimensional simulation model was built to study diesel engine cold start performance based on energy analysis. The cyclic energy loss of cold start failure and success cases, ramp-up-speed period characteristic of diesel engine were studied by using special low temperature diesel and adopting two pilots and one main injection control strategy at −43 ℃. The numerical calculation and analysis results show that when the exhaust energy is high and the heat transfer loss energy is very low, there may be a misfire cycle in the cylinder. The increase in the pilot injection 1 mass, main injection mass, pilot injection 1 timing, and main injection timing within certain limits can significantly increase the fuel vapor fraction during the ramp-up-speed period (maximum of 66.67%). The speed of ramp-up-speed period and idle steady phase faster obviously, the maximum increase is 300 r/min (30%). The fuel vapor fraction increases as the pilot injection 2 mass increases during the ramp-up-speed period but slows down the speed of ramp-up and idle phase, with a maximum decrease of 300 r/min (23.07%).

Research on Heat Generation Law and Cooling System Performance of Hydraulic System of Combined Machine Tool

After the machine tool works continuously, the temperature of the hydraulic system continues to rise, which affects the work efficiency of the machine tool. Therefore, it is very important to control the temperature within a reasonable range. This paper proposes an improved scheme to replace a single fan with dual fans to improve the heat dissipation capacity of the radiator. Starting from the principle of heat exchange between oil and air, the relationship between the oil temperature and the wind speed on the face of the heat exchanger is derived, and the theoretical basis of the cooling system is given. Combined with logic control, the fan has the advantages of fast action, high efficiency and low energy consumption, which ensures the efficient and reliable operation of the machine tool. A one-dimensional simulation model of the thermal hydraulic system is established, and the heat generation and heat dissipation power of each element are calculated. Among them, the heat dissipation of the radiator is the largest, accounting for about 55% of the total heat dissipation. The experimental results show that the optimal fan speed is 3200 r/min and the flow rate is 0.2 m3/s at 26 °C. The thermal balance temperature of the hydraulic system is reduced from the original 65 °C to 58 °C, and its cooling capacity meets the requirements of a high-altitude and high-temperature environment.

Study on thermal-hydraulic performance of printed circuit heat exchangers with supercritical methane based on machine learning methods

In this study, a machine learning approach was used to predict thermal-hydraulic performance of supercritical methane flow in a printed circuit heat exchanger (PCHE). Local multiple physical parameters within the PCHE semicircular straight channel obtained from numerical simulations were employed and data of 6213 micro segments were obtained. Four machine learning models were used to predict local heat transfer coefficient and unit pressure drop at different operating conditions. By comparing the predicted results obtained after hyperparameter optimization, it shows that artificial neural network (ANN) can predict the parameters with higher accuracy. The ANN model can achieve a coefficient of determination (R2) of 0.9994 with mean absolute percentage error (MAPE) of 0.252% for the heat transfer coefficient, and R2 of 0.9996 with MAPE of 1.749% for the unit pressure drop. To verify the accuracy of machine learning model, a one-dimensional simulation model embedded with ANN model was built to calculate the temperature and pressure distribution in the entire PCHE channel. The results show the temperature and pressure distribution agree well with numerical results. This work provides an accurate machine learning approach to predict flow and heat transfer parameters, which is of great value for the simulation and design of the PCHE.

Non-ideal explosive underwater explosion shockwave model

The non-ideal behavior of aluminized explosives significantly affects the characteristics of underwater explosion shockwaves, rendering the classical model for underwater explosion shockwaves difficult to apply. In this paper, we analyze the underwater explosion shockwave characteristics of a new generation of aluminized explosives and propose a non-ideal explosive underwater explosion shockwave model incorporating a non-ideal explosive shockwave parameter correction function controlled by the Al/O ratio. First, we conducted underwater explosion tank experiments to obtain four groups of Al/O ratios of shockwave parameters of underwater explosion with aluminized explosives and analyzed the effect of the Al/O ratio on them. Subsequently, we calculated the equation of state of aluminized explosives and established a one-dimensional simulation model of underwater explosion. We verified the reliability of the mesh quality and equation of state using the experimental data. Finally, we used the model to calculate the underwater explosion shockwave parameters of aluminized explosives with Al/O ratios of 0.1–1.3. Based on data analysis, we established a calculation model of the pressure peak and energy flow density of the underwater explosion shockwave of aluminized explosives containing non-ideality correction functions. Our results demonstrate that shockwave pressure peak and energy increase and then decrease with an increase in the Al/O ratio, and the non-ideal behavior of aluminized explosives makes the shockwave energy of underwater explosion more sensitive to the Al/O ratio. The proposed model can better predict the experimental results and can be of high practical value as a general structure for underwater explosion shockwave models of other aluminized or metalized explosives.

Структурно-имитационная модель деформирования сплавов с памятью формы. Часть I. Описание эффекта ориентированного превращения

A one-dimensional structural simulation model for deformation of shape-memory alloys under thermoelastic phase transformations is presented, taking into account the origin and development of martensitic mesoelements during direct transformation and their degradation and disappearance during reverse transformation. An adequate description of the effects of oriented transformation within the framework of the model is given.

Numerical Investigation on the Impact of Exergy Analysis and Structural Improvement in Power Plant Boiler through Co-Simulation

In current power station boilers, fuel burns at a low temperature, which results in low exergy efficiency. This research combined the second law of t with the boiler structure to maximize the efficiency of a 350 MW power plant boiler. A three-dimensional simulation of the combustion process at the power plant boiler is performed. A one-dimensional simulation model of the boiler is then constructed to calculate the combustion exergy loss, heat transfer exergy loss, and boiler exergy efficiency. Under the principle of high-temperature air combustion technologies, this paper also proposes a new structure and improved operating parameters to improve the exergy efficiency of boilers by reducing the heat exchange area of the economizer and increasing the heat exchange area of the air preheater. Simulation results show that the exergy efficiency of the boiler increased from 47.29% to 48.35% through the modified model. The simulation outcomes can instruct future optimal boiler design and controls.

A combined model approach to optimize surface irrigation practice: SWAP and WinSRFR

Surface irrigation worldwide exhibits low efficiency due to excessively deep percolation and runoff. To optimize surface irrigation practice, two questions must be answered simultaneously: when to irrigate and how to irrigate (what stream size to use and for how long) to meet crop water requirements. Current surface irrigation optimization models are one-dimensional, meaning they can only simulate surface water flow, neglecting subsurface flow. They therefore indicate only how to irrigate, not when to irrigate. Furthermore, the required depth of irrigation is needed as input data for optimization, though this parameter is difficult to establish accurately. In addition, the effects of different irrigation practices on crop transpiration and yield, and variations in these across an irrigated field, are unknown. The present study adopts two one-dimensional simulation models – WinSRFR (for surface flow) and SWAP (for subsurface flow) – to determine when and how best to irrigate in a blocked-end furrow irrigation system for sugarcane cultivation in southwestern Iran. SWAP is used to determine irrigation schedule, required irrigation depth and crop transpiration along furrows, while WinSRFR is used to determine the soil infiltration function and evaluate and optimize irrigation practice. The results of the combined model approach indicate that some 2.7 times more water is applied than required in current practice, imposing high waterlogging stress on sugarcane crops. According to the SWAP simulations, the required irrigation depth is some 75 mm and the number of irrigation applications can be reduced from 26 to 19. The irrigation optimization in WinSRFR indicates that irrigation depth can be reduced from 162 mm to 81 mm, resulting in application efficiency increasing from 47% to 92%. Furthermore, as furrow slope increases from 0.02% to 0.12%, optimized stream size decreases from 3.0 to 1.6 l/s and optimized irrigation cutoff times increase from 3.2 to 6.5 hrs. Overall, optimization of irrigation practice using the combined model approach could result in 63% water conservation and 22% higher sugarcane yield.

Parameter investigation of the pilot fuel post-injection strategy on performance and emissions characteristics of a large marine two-stroke natural gas-diesel dual-fuel engine

This study aimed to conduct a parametric study to investigate the effect arising from pilot fuel post-injection strategy on engine combustion, performance, and emissions of a large two-stroke natural gas-diesel dual-fuel engine for marine applications. The one-dimensional and three-dimensional simulation models were built in AVL-BOOST and CONVERGE, respectively, and validated according to experimental results. The effects of post-injection strategies on post-injection timing and mass ratio on engine combustion, performance, and emissions were investigated. As revealed by the results, an appropriate pilot fuel post-injection strategy could achieve lower NOx emissions with less loss of performance. As post-injection timing was delayed, the NOx emission first decreased and then increased. Subsequently, it decreased to the lowest and finally increased. With the increase in the post-injection mass ratio, the NOx emission was kept decreasing. Compared with the original engine, the NOx emission decreased by 81.85 ppm with a post-injection timing of 18 deg after top dead center and with a mass ratio of 0.7. However, the indicated power only decreased by 4.82 kW, and the indicated specific fuel consumption only increased by 0.2 g/kWh. This study can provide some theoretical guidance for the injection strategy optimization of the marine two-stroke natural gas-diesel dual-fuel engines and provide technical suggestions for practical application.