Dynamics Simulation Model Research Articles

Atomistic insights into friction and wear characteristics of M50 bearing steel: a molecular dynamics simulation study

ABSTRACT M50 bearing steel is a typical alloy material widely used in aeroengines due to its high hardness and fatigue life at high temperatures. To reveal the frictional mechanisms and wear behaviours of contact and sliding, a molecular dynamics simulation model consisting of an indenter and substrate is constructed. The results indicate that, during the indentation process, the normal load exhibits a linear relationship with the indentation depth at shallow depths. With further penetration, the substrate generates severe deformations and subsurface damages. Throughout the scratching process, the average friction force exhibits a linear increase with the growing scratching depth, while the coefficient of friction decreases. Surface morphologies and shear strain distributions are analyzed to elucidate plastic deformation and atomic displacement. Moreover, the wear atom shows a linear proportionality to both scratching distance and depth. These findings enhance understanding of frictional properties and atomic wear behaviour of M50 bearing steel during contact and sliding, potentially informing bearing failure prediction and material optimization.

A modified Hertzian-based wheel-rail contact model for vehicle system dynamics simulation

This paper develops a modified Hertzian-based wheel-rail contact model (MHM) to improve the robustness and accuracy of the traditional Hertzian contact model in vehicle-track coupling dynamics simulation. First, the wheel-rail non-Hertzian contact area is estimated based on the virtual penetration (VP) area, and an equivalent ellipse of the non-Hertzian contact area is calculated. Then, taking the equivalent elliptical contact patch as the input, the wheel-rail normal problem is solved by using Hertzian contact theory. Finally, considering the effect of the non-elliptical contact patch on Kalker’s linear coefficient, a modified Shen–Hedrick–Elkins model is proposed. The computation accuracy, robustness, and efficiency of the developed MHM are assessed by comparing it with a robust Kalker variational method (RKVM), a VP-based non-Hertzian contact model RNHM, and two traditional Hertzian-based models. The comparison results show that the MHM improves the computational robustness and accuracy of the traditional Hertzian-based contact models. MHM achieves almost the same computational accuracy as the RNHM, but its computational efficiency is 2.4 times faster than RNHM. The developed MHM is an ideal model for vehicle-track coupling dynamics simulation.

Code for molecular dynamics simulation of two dimensional Mercedes-Benz water model

The Mercedes-Benz (MB) water model is a simple two-dimensional toy model of water that can reproduce many of the anomalous properties of water. Within the model, the water particles are represented as Lennard-Jones disks with explicitly added orientation-dependent interactions that mimic the formation of hydrogen bonds. Due to the simple implementation of the MB model in Monte Carlo simulations, it was mainly studied with Monte Carlo simulations in different ensembles. The implementation of the model in molecular dynamics simulations is not trivial. In this paper we present the code for molecular dynamics simulations. The structural and thermodynamic properties of the model were calculated using molecular dynamics and compared with data from Monte Carlo simulations to confirm that the molecular dynamics code works correctly. We also used molecular dynamics to calculate the dynamic properties of the model. The Fortran source code of our molecular dynamics simulation of the MB water model is provided.

Bioinspired low temperature Cu bonding interfaces with interlocked microstructures to achieve high reliability

The reliability of Cu bonding technology in three-dimensional integration packaging is limited by high sintering temperatures and the growth of oxide at the joining interface. Hence, we propose a bionic adhesion interface of creeper sucker on the Cu substrate and covered with monolayer graphene, which increases the shear strength by 3 times compared to the conventional flat Cu substrate. The covered graphene layer effectively inhibits the generation of oxide at the joint interface and maintains a high shear strength after aging at 300 °C for 48 h Nanoscale Cu particles could reduce the chemical potential energy of the substrate surface, and stable bonding was achieved at 200 °C under a pressure of 2 MPa. Molecular dynamics simulation models reveal crystal structure evolution and residual stresses during the sintering process. This work demonstrates that bionic microstructures applied to copper bonding play an important role in interface enhancement, resulting in reliable bonding of Cu substrate at low temperatures. The method proposed here can provide insight into diversified applications including high-power light-emitting diodes soldering, SiC electronic devices, and flexible electrode interconnects.

Research on rolling bearing fault diagnosis method based on simulation and experiment fusion drive.

Aiming at the problem that the rolling bearing fault data are difficult to obtain and that the traditional fault diagnosis method does not consider the signal uncertainty characteristics and the low accuracy of models in the process of rolling bearing fault, a fault diagnosis method based on simulation and experiment fusion drive is proposed. First, the dynamics simulation model of rolling bearings under different fault conditions is established to obtain the bearing fault simulation signals. Second, a sequence generative adversarial network is used to fuse the simulation and experimental data. Bearing vibration signals are often very uncertain, so considering the probability characteristics of fault signals, the probability box model under different fault states is constructed by the direct probability box modeling method, and its characteristic vectors are extracted. Finally, an extreme gradient boosting Tree model for fault diagnosis classification is constructed to compare and evaluate the classification and diagnosis effects of bearing states before and after data fusion. The results show that the proposed method has a good diagnostic effect and is suitable for solving the fault diagnosis problem under the condition of insufficient data.

Data-model Interactive Health Condition Assessment for Hydropower Unit

Abstract The health condition assessment (HCA) of hydropower unit plays an important role in enhancing safe operation of hydropower stations and reducing maintenance costs. Due to the harsh environment, there are some problems of sensor data during the unit operations, including abnormal data, missing data and high-noise data. Also, it is difficult to obtain complete monitoring data during run-to-failure maintenance. These issues definitely cause the low-confidence HCA. Thus, a data-model-interactive HCA for hydropower unit was proposed. First, a high-fidelity 3D mechanism simulation model, interacting with the actual unit, was built using unit drawing data provided by manufacturers. Average values of the volute inlet pressure and draft tube outlet pressure were fed into the dynamics simulation model to obtain the simulated pressure pulsation data under working conditions (water head H and power P). Then, a long short-term memory based healthy condition model was constructed using the power parameters, simulation and normal pressure pulsation. After model construction, difference values between simulated pressure pulsation dataset and degradation state pressure pulsation dataset were calculated to build the performance degradation index (PDI), describing the HCA of units. Finally, the PDI was fed into the convolutional neural networks and long short-term memory model to achieve degradation trend prediction. Validation experiment was conducted to verify the effectiveness of proposed method using actual monitoring data and operating parameters of 6# unit in the hydropower station.

Prediction of the performance of halal food industry using a system dynamics simulation model

Purpose This study aims to develop a system dynamics (SD) simulation model to forecast the performance of the Indonesian halal industry to verify whether decision-making has been properly executed to increase the contribution of the success factors. Design/methodology/approach This study establishes a SD-based model using three subsystems, namely, the halal assurance and certification process, the government and the export–import subsystem. Findings The best scenario is the third scenario or the combined scenario of providing facilities to accelerate the micro-, small- and medium-sized enterprises (MSMEs), carrying out halal certification, reducing the time for the certification process, increasing the number of the halal auditor and increasing the awareness from enterprises (both MSMEs and large enterprises) to carry out halal certification because of the internal and external motivations. Research limitations/implications First, the demand for certification of the type of food product is acquired using the number of SMEs and large companies. Second, the model does not include the government budget as a constraint. Practical implications This study provides essential insights into implementing the best policies that can increase the performance of the halal industry. Social implications This study revealed that relevant policy scenarios could be built after simulating and analyzing each scenario’s effect on the halal industry’s performance. Originality/value This study will enrich the scientific insight related to institutional theory and resource-based view, as those theories identify success factors associated with the performance of the halal food industry. This study will also enrich the scientific insight related to system dynamic methodology, as it is used to model the performance of the halal industry.

Resilience through appropriate response: a simulation study of disruptions and response strategies – case COVID-19 and the grocery supply chain

In the wake of disruptions such as the COVID-19 pandemic, supply chains (SCs) face unprecedented levels of uncertainty, underscoring the critical need for resilience capabilities. We study how the operational dynamics of SCs influence the efficacy of key resilience capabilities, specifically flexibility and visibility. Utilizing a system dynamics simulation model, we analyze the contingency effects within Finnish grocery SCs, examining how the operational tempo—characterized by lead times, inventory buffers, information updating—affects the efficiency of resilience strategies in response to diverse disruption scenarios. Our model, informed by real-world disruption events and responses, reveals distinct preferences for resilience capabilities based on SC operational dynamics. For fast-moving SCs, flexibility in ramping up capacity emerges as paramount, whereas for slower SCs, enhanced visibility becomes crucial. We contribute to the contingent Resource-Based View (RBV) on SC resilience by proposing that responsiveness is important moderator of flexibility and visibility as resilience capabilities. We highlight the importance of prevention of phantom ordering through improved visibility and caution against destocking following sudden demand declines. By aligning operational dynamics with tailored resilience strategies, our research offers actionable insights for SC managers aiming to navigate future disruptions more effectively.

Study on mechanical properties of high-strength casing milling and mechanisms of high-efficiency windowing drill bit

During breaking window in deep and ultra-deep wells, the cutting teeth of the drill bit are prone to be blunted due to the thickness and high strength of the casing wall and the poor drillability of the rock. A new milling cone bit is innovatively designed. The bit has 9 cutter wings, and double rows of cutting teeth are staggered on each cutter wings to enhance the ability and stability of window breaking. The dynamics simulation model of sidetracking window was established to explore the law of window formation and verify the feasibility of the design of the drill bit and its whipstock. Drill bits and supporting tool structures are optimized with the aid of simulation. The prototypes of drill bit and whipstock were developed to carry out the windowing test of TP155V steel casing (yield strength up to 1068 MPa). It was revealed that the success rate of windowing is 100%. The similarity between the window shape obtained by the experiment and the window shape obtained by simulation is nearly 100%. The bit and its tools provide a new method of casing windowing in deep and ultra-deep wells. Its lays the foundation for further research on the sidetracking process.

Coupled analysis and simulation of safety risk in subway tunnel construction by shallow-buried excavation method based on system dynamics

To address the existing shortcomings in the research on the coupling of safety risk factors in subway tunnel construction using the shallow-buried excavation method, this paper conducts a coupled analysis and dynamic simulation of the safety risks associated with this construction method. Firstly, by analyzing the mechanisms and effects of risk coupling in shallow-buried excavation construction of subway tunnels, this study divides the risk system into four risk subsystems (human, material, management, and environment), establishes an evaluation index system for the coupling of safety risks, calculates the comprehensive weight values of the risk indicators using the AHP-entropy weight method, and constructs a risk coupling degree model by combining the inverse cloud model and efficacy function. Subsequently, based on the principles of system dynamics, a causal relationship diagram and a system dynamics simulation model for the coupling of “human-material” risks in construction are established using Vensim PLE software. Finally, the case study of the underground excavation section of Chengdu Metro Line 2 is employed to perform dynamic simulation using the established model. By adjusting the relevant risk coupling coefficients and simulation duration, the impact of the coupling of various risk factors on the safety risk level of the human-material coupling system is observed. The simulation results demonstrate that: 1) Heterogeneous coupling of human and material risks has a particularly significant effect on the system’s safety risks; 2) Violations by personnel and initial support structure defects are key risk coupling factors. The findings of this study provide new insights for decision-makers to assess the safety risk of shallow-buried excavation construction in subway tunnel.

Permeability modelling in a highly heterogeneous tight carbonate reservoir using comparative evaluating learning-based and fitting-based approaches

Permeability modelling is considered a complex task in reservoir characterization and a key component of reservoir simulation. A common method for permeability modelling involves performing static rock typing (SRT) using routine core analysis data and developing simple fitting-based mathematical relations that link permeability to reservoir rock porosity. In the case of carbonate reservoirs, which are associated with high heterogeneities, fitting-based approaches may fail due to porosity–permeability data scattering. Accurate modelling of permeability using petrophysical well log data seems more promising since they comprise a vast array of information about the intrinsic properties of the geological formations. Furthermore, well log data exhibit continuity throughout the entire reservoir interval, whereas core data are discrete and limited in availability and coverage. In this research work, porosity, permeability and log data of two oil wells from a tight carbonate reservoir were used to predict permeability at un-cored intervals. Machine learning (ML) and fitting models were used to develop predictive models. Then, the developed ML models were compared to exponential and statistical fitting modelling approaches. The integrated ML permeability model based on Random Forest method performed significantly superior to exponential and statistical fitting-based methods. Accordingly, for horizontal and vertical permeability of test samples, the Root Mean Squared Error (RMSE) values were 3.7 and 4.5 for well 2, and 1.7 and 0.86 for well 4, respectively. Hence, using log data, permeability modelling was improved as it incorporates more comprehensive reservoir rock physics. The outcomes of this reach work can be used to improve the distribution of both horizontal and vertical permeability in the 3D model for future dynamic reservoir simulations in such a complex and heterogeneous reservoir system.

Molecular Dynamic Simulation and 3d-pharmacophore Modeling of Alpha Mangostin and Its Derivatives against Estrogen Alpha Receptor

Background: Human estrogen receptor alpha (ERα), which is known to play a role in mediating cell proliferation, metastasis, and resistance to apoptosis, is one of the targets of breast cancer therapies. Alpha mangostin (AM) is an active xanthone compound from Garcinia mangostana L. which has activity as an ERα inhibitor. Objectives: This research aims to predict the pharmacokinetic and toxicity, and to study the molecular interactions of AM derivatives with the ERα using computer-aided simulation approaches through molecular docking, molecular dynamic, and pharmacophore screening to develop novel anti-breast cancer agents. Methods: Marvinsketch and Chimera programs were used to design and optimize the structure of AM and its derivatives. For screening the pharmacokinetic and toxicity profiles, the PreADMET web was used. The AutoDockTools 1.5.6 and LigandScout 4.4.3 Advanced software were used to conduct the molecular docking simulation and pharmacophore screening, respectively, while the molecular dynamic simulation was performed using AMBER 16. The results were visualized by Biovia Discovery Studio. Results: Molecular docking using Autodock showed that FAT10 derivate has lower binding free energy (ΔG) (-12.04 kcal/mol) than AM (-8.45 kcal/mol) when docking to ERα and both performed the same hydrogen bond with Thr347. These support the results of the MMPBSA calculation on dynamic simulation which shows FAT10 (-58.4767 kcal/mol) has lower ΔG than AM (-42.7041 kcal/mol) and 4-OHT (- 49.0821 kcal/mol). The pharmacophore screening results also showed that FAT10 fitted the pharmacophore with a fit score of 47.08. Conclusion: From the results, it can be suggested that FAT10 has promising activity as ERα antagonist. Further in vitro and in vivo experiments should be carried out to support these in silico studies.

Effects of joint invasion: How co-invaders affect each other's success in model food webs?

While there has been considerable research on the interactions between invasive and native species, and on the impact of invasive species on the resident community, there has been less focus on exploring the relationship and interactions among invasive species themselves. Nevertheless, it is widely recognised that invasive species can have either positive or negative effects on each other, as well as neutral outcomes. In the present theoretical study, we compared the success of two invasive non-native species in two scenarios: when they invaded the resident food web separately and simultaneously. We examined the correlations between their direct and indirect ecological relationships and their topological positions in the food web, with the varying outcomes of joint invasion. Using the Allometric Bioenergetic Model (ABM) for dynamic simulations, we determined the success of invasion (presence or absence of invaders) and, in the case of successful co-invasion, the direction of their biomass change, comparing separate and simultaneous invasion scenarios. We studied the relationships between these variables after detailed numerical simulations with variable key parameters of the model.We found that direct and indirect ecological relationships between the two invaders can significantly modifiy the outcomes of the invasion scenarios. For example, their predator-prey relationship increases the probability of invasion success for both invaders, but at the same time the equilibrium biomass of at least one of them is likely to be reduced compared to its separate invasion. Trophic cascade or competitive relationship between them during simultaneous invasion also affects their success rate, with the former having a positive effect and the latter a negative one, as they can hinder each other's spread. Further, we found that higher trophic level and lower betweenness centralities of the invaders reduces the likelihood of invasion success regardless of the presence or absence of another invasive species. The results of the study can be tested experimentally in micro- and mesocosms.

Coupling Process between Droplet and Iron Investigated by Reactive Molecular Dynamics Simulations.

The droplet-to-iron electrochemical reaction is common in nature and industrial production, and it causes damage to the economy, safety, and the environment. The electrochemical reaction of droplet-to-iron is a coupling process of wetting and corrosion. Presently, investigations into electrochemical reactions mainly focus on the corrosions caused by a solution, and wetting is rarely considered. However, for the droplet-to-iron electrochemical reaction, the mechanism of charge transfer in the process is still unclear. In this paper, a reactive molecular dynamics simulation model for the droplet-to-iron electrochemical reaction is developed for the first time. The electrochemical reaction of droplet-to-iron is studied, and the interaction between droplet wetting and corrosion on iron is investigated. The effects of temperature, electric field strength, and salt concentration on the electrochemical reaction are explored. Results show that droplet wetting on the iron surface and the formation of a single-molecular-layer ordered structure are prerequisites for corrosion. The hydroxyl radicals that penetrate the ordered structure acquire electrons from iron atoms on the substrate surface under the action of Coulomb forces and form iron-containing oxides with these iron atoms. The corrosion products and craters lead to a reduced droplet height, which promotes droplet wetting on iron and further intensifies the droplet-to-iron electrochemical reaction.

Conversion of a regular patient room to negative pressure at Ancona university hospital (Italy). A combined experimental and numerical investigation

Negative pressure isolation rooms are employed to prevent the spread of infectious diseases to surrounding spaces. This study reports a combined experimental and numerical analysis aimed at reliably assessing the performance of hospital ventilation systems and effectively reducing the risk of airborne infections. The study appraises the enhancement of the safety conditions by retrofitting an existing, positive pressure room ventilation system with a negative pressure and recirculation one. The assessment consisted in experimental measurements of airborne particle concentration and Computational Fluid Dynamics (CFD) simulations with Lagrangian particle tracking of respiratory droplets. The ventilation performance improvement was quantified in terms of recovery rate, contaminant removal effectiveness, particle transfer toward adjacent spaces and probability of infection.Two experimental campaigns were carried out: an ISO standard recovery assessment and a test in real operational conditions. The negative pressure configuration significantly improved the safety inside the patient ward: the recovery rate for droplets with diameter larger than 5 μm increased by a factor three, and the contaminant removal effectiveness after 15 min increased from 45% to 81%. The numerical model for Computational Fluid Dynamics simulation was successfully validated, confirming the ability of the approach to reproduce the undergoing Physics. The negative pressure design eliminated the particle transmission to surrounding spaces, while 2.5% of the emitted respiratory droplets escaped the room in the original existing scenario. The probability of infection after 15 min exposure was reduced by a factor three and peak values reaching 15% were limited to the immediate vicinity of the patients.

Evaluating solvent efficiency for carbon capture: Comparative analysis of temperature, concentration and diffusivity effects

In the pursuit of efficient carbon capture technologies, the selection and design of solvents play a pivotal role, directly impacting various crucial factors such as CO2 absorption capacity, equipment size, and regeneration energy requirements. The primary focus is on optimizing solvent systems through a comprehensive analysis of intermolecular interaction intensity, diffusion coefficient, and intra-molecular interaction intensity. This study employs a molecular dynamics simulation model to identify the most suitable solvent system by assessing the effect of operating variables like temperature, concentration, interaction intensity, and diffusivity of various single and blended amine systems. The assessment utilizes the radial distribution function and mean square displacement analysis. The results indicate that intermolecular interactions with CO2 are most significant in 30 wt% 2EAE, 40 wt% 2DMAE and 10% DMCA with 20% MCA ratio concentrations. TMPAD, in particular, stands out for its high repulsive interaction and low energy requirement for breaking the carbamate/bicarbonate ion. Diffusion behavior in various observed solvent systems is as follows: EAE > MEA > DMAE > MAE-DEAB > MAE-DMA2P > EAE-TMPAD > AMP-PZ > EAE-DEAB > MAE-TMPAD > EAE-DMA2P > MAE-DMAE > EAE-DMAE > TMPAD > MEA-AMP > DMA2P > DMCA-MCA > DEAB > MEA-PZ. Moreover, elevated temperatures facilitate enhanced diffusivity, leading to accelerated mass transfer rates. This implies the possibility of reducing the size of absorber units and lowering energy consumption. Further studies on heat of absorption and kinetic characteristics of solvent blends are necessary to ensure their practical applicability in carbon capture and industrial operations.

Droplet deposition behavior on the surface of wheat leaves with wind-induced vibration

Droplet impingement on leaf surfaces is a common phenomenon in the spray application process. Most impingements have focused on droplet deposition behavior on stationary leaf surfaces. However, airflow movement and auxiliary airflow during the spray application process create disturbances and generate vibrations on the leaves, which would inevitably affect the deposition conditions of droplets on leaf surfaces. A three-dimensional “droplet-leaf vibration” Computational fluid dynamics (CFD) simulation model is constructed in this paper, and model validation and simulation tests are performed to investigate the effects of leaf vibration on droplet deposition. Experimental results reveal that when the droplet velocity is 1 m/s, with a 60° inclination angle and a vibrational angular velocity of 9 rad/s, the spreading area factor of a 200-μm droplet has the greatest increase up to a value of 1.34, and vibrational effects on the deposition behavior of the three droplet diameters demonstrate a consistent trend.Compared to stationary leaves, vibrating wheat leaves can alter the impingement behavior of droplets close to critical conditions, and vibration can also increase the sliding range for droplets. Vibration in wheat leaves can promote droplet spreading and deposition and increase the spreading area of droplets on the leaf surface. The effects of vibration on large-diameter droplets are more significant compared to small-diameter droplets, where droplet spreading and movement can be effectively enhanced. This paper shall provide a three-dimensional “droplet-leaf vibration” CFD simulation method, providing novel research ideas for the study of droplet deposition behavior on vibrating leaves.

Nonlinear dynamic separation characteristics of friction pair and experimental analysis

This paper aims to reduce friction pair erosion of the clutch in the case of continuous shift; the dynamic separation process of the friction pair is investigated. The temperature of the friction pair, friction torque, and separation speed in the separation process are taken as the research objects, and the dynamics simulation model and finite element thermal coupling simulation model of the clutch separation process are established. The nonlinear dynamic separation characteristics of the friction pair are investigated by comparing and analyzing the effects of control parameters such as rotational speed difference, damping ratio, and lubricant viscosity on the friction torque, friction pair separation speed, separation gap, and contact stress during the separation process. The gap recovery coefficient is proposed as a response indicator for observing the separation process in response to the inability to observe the nonlinear dynamic motion of the friction pair during the separation process and to measure the end time of the separation. Finally, the clutch was subjected to a separation test. The results show that the proposed gap recovery coefficient accurately describes the separation process. The simulation model can simulate the clutch's separation and predict the trend of separation parameters.

Trajectories of socio-ecological systems: A case study in the tropical Andes.

Scenario and policy assessments in socioeconomic and environmental studies face significant challenges in socio-ecological systems (SES). There are a limited number of studies that have looked at the impact of different scenarios within integrated approaches, and many have used a static approach with a single driver of change. The present work analyzes the SES dynamics for a strategic basin in the Colombian Andes when implementing and analyzing scenarios and policies related to land cover and land use change using a system dynamics simulation model. The model includes natural, ecosystem services, sociocultural, and economic components. Scenarios and policy options are analyzed both individually and jointly to identify synergies or trade-off effects between the different SES components. The results showed the different trajectories of the socio-ecological system according to the cases studied, and its impact on different variables in the analyzed components. Some counterintuitive effects were also identified, such as the importance of intrinsic motivations in decision-making processes, and determinants in land management and policy design.

Parametric analysis and optimization of the combustion process and pollutant performance for ammonia-diesel dual-fuel engines

As a low-cost, carbon-free, and widely available hydrogen carrier fuel, ammonia has now regained peoples’ attention in the future development of the carbon-neutral engine. To evaluate the feasibility of ammonia as a carbon-reducing fuel for a high-power diesel engine, a computational fluid dynamics simulation model of a Caterpillar 3401 diesel engine has been established and validated. Initially, an analysis was conducted to examine the effects of different ammonia energy fractions on combustion and the generation of emissions. Subsequently, to address issues related to incomplete ammonia combustion and a decline in engine power performance, a novel fuel injection strategy was developed. This strategy optimizes the distribution of diesel within the combustion chamber and the combustion process of ammonia-diesel dual-fuel by coordinating the injection timing of diesel fuel with the injection angle. The results indicate that an ammonia energy fraction of 40% is deemed to be an optimal mixing ratio for ammonia addition. Compared with pure diesel mode, greenhouse gas emissions are reduced by 34.3%, and the indicated mean effective pressure is only reduced by 4% when the ammonia energy fraction is 40%. Collaborative optimization of fuel injection timing and angle can achieve multi-point pilot ignition, shorten the combustion duration, and thus approach the effect of premixed combustion. This leads to a substantial decrease in unburned ammonia emissions, with the optimal unburned ammonia emission injection scheme registering only 0.279 g/kW·h, a mere 1.63% of the emissions under the original injection scheme with a 40% ammonia energy fraction. Additionally, the rapid combustion contributes to an increase in in-cylinder temperature, resulting in a significant reduction in N2O and CO emissions.