Simulation Tests Research Articles

Low-Frequency AC Multiport Asynchronous Grid Connection System to Optimize Generation Costs and Mitigate Bottlenecks

Renewable energy sources continue to increase due to the energy transition; thus, the generation output of conventional power sources is decreasing. The installation of renewable energy sources can lead to the concentration of these sources depending on geographical characteristics, which may cause bottlenecks between the renewable energy generation sites and load centers, and such bottlenecks can result in power shortages in load centers and may cause issues that limit the integration of renewable energy. Thus, this paper proposes the application of an LFAC multiport asynchronous grid connection system to solve these problems, where the frequency conversion device uses a variable frequency transformer (VFT). In addition, the installation location of the proposed LFAC multiport asynchronous grid connection system is selected using a grid partitioning technique, and the optimal power flow is performed to minimize the generation costs. The grid partitioning was conducted using the IEEE 39 bus system, and the feasibility of the proposed LFAC multiport asynchronous grid connection system was verified through simulation tests of the generation and load demands in the grid. In addition, the VFT control and optimal power flow control performances were confirmed through MATLAB/Simulink.

Macroscopic and Mesoscopic Damage Characteristics and Energy Evolution Laws of Rock Mass With Double Arcuate Fractures Under Uniaxial Compression

ABSTRACTIn order to reveal the influence of double arc‐shaped fissure dip angles on the macro‐micro failure and energy evolution laws of rock masses, a numerical model of red sandstone was firstly established using the PFC2D. Moreover, mesoscopic parameters of the numerical model were calibrated based on the uniaxial compression tests on intact and single straight fissure red sandstone specimens. Then, particle flow simulation tests of red sandstone with different arc‐shaped fissure dip angles were carried out. The results show that the peak strength and elastic modulus both increase with the increase of arc‐shaped fissure dip angle α, exhibiting an oblique shear‐tensile failure pattern. Six types of cracks evolved during the instability and rupture of the rock mass with double arc‐shaped fissures. The macroscopic fissures in the rock mass ultimately penetrate along the extension direction of the arc‐shaped fissures. As the arc‐shaped fissure dip angle α increases, the crack evolution is positively correlated with the acoustic emission (AE) of the specimen. When approaching instability failure, the AE ringing count rapidly increases. There is a critical angle limit inflection point for the total energy absorbed by the rock between 60° and 75°, with a total energy increase of about 54%. During instability failure, it is dominated by dissipative energy, with elastic energy as a supplement. This article derived a damage constitutive model of red sandstone with different arc‐shaped fissure dip angles, revealing the damage laws of red sandstone under different arc‐shaped fissure dip angles.

From Detection to Action: A Multimodal AI Framework for Traffic Incident Response

With the rising incidence of traffic accidents and growing environmental concerns, the demand for advanced systems to ensure traffic and environmental safety has become increasingly urgent. This paper introduces an automated highway safety management framework that integrates computer vision and natural language processing for real-time monitoring, analysis, and reporting of traffic incidents. The system not only identifies accidents but also aids in coordinating emergency responses, such as dispatching ambulances, fire services, and police, while simultaneously managing traffic flow. The approach begins with the creation of a diverse highway accident dataset, combining public datasets with drone and CCTV footage. YOLOv11s is retrained on this dataset to enable real-time detection of critical traffic elements and anomalies, such as collisions and fires. A vision–language model (VLM), Moondream2, is employed to generate detailed scene descriptions, which are further refined by a large language model (LLM), GPT 4-Turbo, to produce concise incident reports and actionable suggestions. These reports are automatically sent to relevant authorities, ensuring prompt and effective response. The system’s effectiveness is validated through the analysis of diverse accident videos and zero-shot simulation testing within the Webots environment. The results highlight the potential of combining drone and CCTV imagery with AI-driven methodologies to improve traffic management and enhance public safety. Future work will include refining detection models, expanding dataset diversity, and deploying the framework in real-world scenarios using live drone and CCTV feeds. This study lays the groundwork for scalable and reliable solutions to address critical traffic safety challenges.

Evaluation of automated driving safety in urban mixed traffic environments

AbstractConflicting driving behaviours between automated vehicles and manually driven vehicles may compromise driving safety. The aim of this study is to analyse the safety of mixed traffic on urban roads. The driving simulation tests were conducted using a multi‐agent driving simulator, which allows real‐time synchronization of multiple simulators. These data were further processed to derive the driving behaviour parameters of manually driven vehicles in VISSIM traffic simulations. Driving safety evaluation indicators included conflict‐related indicators, as well as individual safety indicators. The safety evaluation indicators were normalized through min–max normalization, and the risk scores were summed to evaluate the urban roads. The analysis revealed that driving safety was poor at unsignalized intersections with a market penetration rate of 10% and 50% and at signalized intersections with traffic islands and a market penetration rate of 100%, where conflicts arise from the deceleration of leading vehicles and lane changes. This finding is about the driving behaviour of automated vehicles, which maintain a greater distance from the leading vehicle than manually driven vehicles, resulting in poorer driving safety due to lane changes rather than deceleration. Using the findings of this study, criteria for assessing the safety of mixed traffic situations in existing road infrastructures can be established.

Particle Swarm Optimization for k-Coverage and 1-Connectivity in Wireless Sensor Networks

Wireless Sensor Networks are used in an ever-increasing range of applications, thanks to their ability to monitor and transmit data related to ambient conditions in almost any area of interest. The optimization of coverage and the assurance of connectivity are fundamental for the efficiency and consistency of Wireless Sensor Networks. Optimal coverage guarantees that all points in the field of interest are monitored, while the assurance of the connectivity of the network nodes assures that the gathered data are reliably transferred among the nodes and the base station. In this research article, a novel algorithm based on Particle Swarm Optimization is proposed to ensure coverage and connectivity in Wireless Sensor Networks. The objective function is derived from energy function minimization methodologies commonly applied in bounded space circle packing problems. The performance of the novel algorithm is not only evaluated through both simulation and statistical tests that demonstrate the efficacy of the proposed methodology but also compared against that of relative algorithms. Finally, concluding remarks are drawn on the potential extensibility and actual use of the algorithm in real-world scenarios.

Research on Bolt-grouting Reinforcement Technology of Broken Surrounding Rock in Roof of Multiple Disturbance Bottom Drainage Roadway

The coal seam floor layout bottom drainage roadway is one of the effective means of gas outburst elimination in the working face. However, the roof surrounding rock of the bottom drainage roadway will undergo multiple disturbances such as bottom drainage roadway excavation, drilling excavation, roadway excavation and working face mining, which will easily lead to large deformation of the surrounding rock of the bottom drainage roadway, which will greatly affect the safety and stability of the bottom drainage roadway and the safety of the mine. In this process, the fracture of the borehole wall of the extraction borehole expands, and it is subjected to severe dynamic pressure during roadway excavation and working face mining. At the same time, the redistribution of surrounding rock stress brings secondary damage, which will lead to the increase of roof deformation. Based on the maintenance of the roof surrounding rock of the bottom suction roadway in the 14020 working face of Zhaogu No.2 Coal Mine, aiming at the problems of local large deformation of the roof surrounding rock of the bottom suction roadway and the difficulty in maintaining the roadway caused by the mine pressure appearance, in order to reduce the roof disturbance of the bottom suction roadway and strengthen the roof support, the indoor test, numerical simulation, theoretical analysis and industrial test are used to carry out the research on the deformation law of the roof surrounding rock of the bottom suction roadway and the bolt grouting reinforcement technology. A numerical calculation model of multiple disturbances in the bottom drainage roadway considering the construction of drainage boreholes was established. The causes of deformation and failure of the roof of the bottom drainage roadway were analyzed, and the supporting parameters and techniques were improved. The timing and support scheme of the test roadway support ( reinforcement technology ) were determined. Under the condition of high strength support, the influence law of bottom pumping roadway excavation, drilling excavation, roadway excavation and working face mining on the deformation degree of roof surrounding rock is revealed. The active reinforcement technology of bolt-grouting for surrounding rock of test roadway is put forward and applied in the field. According to the feedback of the on-site mine pressure monitoring results, the roof deformation degree of the test roadway after excavation and mining is small, and the roadway section meets the production demand, which verifies the feasibility of the bolt-grouting reinforcement technology.

Development of Immersive 360° Virtual Reality Videos for Intervention with Test Anxiety

This study explores the impact of 360-degree virtual reality (VR) videos on simulating test anxiety in students who already experience it. Using a phenomenological design, participants answered questions about their immersion in the virtual environment, including the realism of visuals, emotional responses, and adaptation. Seven students (four girls and three boys) were selected based on specific criteria, and the collected data underwent content analysis. Findings indicate that 360-degree VR videos effectively simulated test environments, creating a strong sense of realism and immersion. Participants reported that VR exposure elicited test anxiety symptoms similar to those experienced in real tests, with emotional distress intensifying during VR sessions. Test-anxious individuals noted that VR exposure triggered stronger emotional responses compared to imagination-based scenarios. While VR exposure proved effective in evoking realistic experiences and emotions, it was not deemed superior to real-life exposure techniques. This suggests that 360-degree VR has potential as a tool for anxiety interventions.

Markov multi-fault tolerance control of intelligent suspension in blind scenes

This paper focuses on insufficient perception in blind scenes and the failures of the actuator and sensor of vehicle suspension. The safe speed is designed and the fault-tolerant strategy based on the observer is designed when the actuator and sensor fail simultaneously. A speed planning strategy to ensure that vehicles operate at a safe speed is proposed. The Markov suspension fault jump model considering the suspension sensor and actuator faults is established. Based on the fault estimation obtained by the fault observer, a fault tolerance control strategy of sensor signal reconstruction and actuator fault compensation is adopted. The measurement index for evaluating fault tolerance effectiveness has been established, and an exploration of fault tolerance control is conducted across various fault levels, to identify the preferred fault tolerance strategies corresponding to different levels of fault tolerance. The simulation results show that the designed speed control strategy can improve vehicle safety by decelerating in advance, the fault observer is capable of accurately estimating the true values of actuator and sensor faults. The simulation and vehicle test results demonstrate that similar suspension performance has been obtained by fault-tolerant control strategy and preferred fault tolerance under different fault tolerance levels compared with normal fault tolerance.

Hot Deformation Behavior and Hot Processing Map of 50CrVA Spring Steel

It is important to explore the hot deformation behavior and establish the hot processing map of steel to design and optimize the hot rolling process. In this paper, 50CrVA spring steel was used as the experimental material. Single-pass compression tests were performed at 850–1150 °C and 0.01–5 s−1 on an MMS-300 thermo-mechanical simulation testing machine to investigate the hot deformation behavior and establish the hot processing map. The results show that as the strain rate increases and the deformation temperature decreases, the flow stress of 50CrVA spring steel increases. The constitutive equation of 50CrVA spring steel is ε˙=1.01×1014[sinh(0.0094σp)]4.53exp(−364,470RT). The dynamic recrystallization critical strain model is εc=4.19×10−3Z7.31×10−2. A hot processing map of 50CrVA spring steel was constructed to determine the plastic instability region and optimal hot working region.

Complexity Evaluation of Test Scenarios for Autonomous Vehicle Safety Validation Using Information Theory

The validation of autonomous vehicles remains a vexing challenge for the automotive industry’s goal of fully autonomous driving. The systematic hierarchization of the test scenarios would provide valuable insights for the development, testing, and verification of autonomous vehicles, enabling nuanced performance evaluations based on scenario complexity. In this paper, an information entropy-based quantification method is proposed to evaluate the complexity of autonomous vehicle validation scenarios. The proposed method addresses the dynamic uncertainties within driving scenarios in a comprehensive way which includes the unpredictability of dynamic agents such as autonomous vehicles, human-driven vehicles, and pedestrians. The numerical complexity calculation of the approach and the ranking of the scenarios are presented through sample scenarios. To automate processes and assist with the calculations, a novel software tool with a user-friendly interface is developed. The performance of the approach is also evaluated through six example driving scenarios, then through extensive simulation using an open-source microscopic traffic simulator. The performance evaluation results confirm the numerical classification and demonstrate the method’s adaptability to diverse scenarios with a comparison of complexity calculation ranking to the ratio of collision, near collision, and normal operation tests observed during simulation testing. The proposed quantification method contributes to the improvement of autonomous vehicle validation procedures by addressing the multifaceted nature of scenario complexities. Beyond advancing the field of validation, the approach also aligns with the broad and active drive of the industry for the widespread deployment of fully autonomous driving.

Study on the Characteristics of Turn-to-Turn Short Circuit Faults in the Primary Windings of the Generator Terminal Voltage Transformer

Turn-to-turn short circuit faults in the primary winding of generator terminal voltage transformers can lead to erroneous operation of stator grounding protection systems. This paper analyzes the fault characteristics associated with such failures and derives formulas for the fault phase current and zero-sequence voltage during a turn-to-turn short circuit in the primary winding. A 3D finite element model of the generator terminal voltage transformer is established by using Altair Flux 3D, and the accuracy of the model is verified. Based on this model, simulation tests were conducted to investigate turn-to-turn short circuits in the primary winding. The results reveal that as the number of shorted turns increases, the voltage of the fault phase decreases continuously while the voltages of the other two phases increase. The current in the short-circuited phase rises significantly, accompanied by an increase in zero-sequence voltage. Visualizations of magnetic field parameters indicate that as the number of shorted turns increases, the magnetic induction magnitude of the fault phase rises steadily and approaches saturation, resulting in heightened magnetic field intensity near the shorted turns. This analysis of fault characteristics through simulation contributes to the advancement of fault diagnosis systems for generator terminal voltage transformers.

Corrosion test and corrosion fatigue numerical simulation research on marine structures

The corrosion tests on Q235B steel in artificial seawater with conventional room temperature and high-temperature & high-humidity are first conducted. The test results show that increasing the acidity and temperature of the corrosion solution, as well as adopting the alternating dry-wet, can significantly enhance the corrosion rate of materials. In addition, the corrosion tests exhibit good simulation and acceleration characteristics compared to at sea tests. Then, the corrosion and corrosion-fatigue numerical simulation methods based on COMSOL and MATLAB are proposed. Meanwhile, the corrosion of Q235B steel in neutral artificial seawater and corrosion fatigue damage of a T-shaped structure under the coupling of artificial seawater with fatigue load are simulated and analyzed. The corrosion simulation results indicate that when the temperature is 40 °C and 20 °C, the average corrosion rates of specimens increase by 96.61% and 15.25%, respectively. Furthermore, when the temperature is 20 °C, the average corrosion rates obtained from numerical simulation and corrosion test are 0.068 mm/a and 0.062 mm/a, respectively, with a relative error of 9.7%, verifying the validity of the corrosion numerical simulation method. Based on the corrosion fatigue simulation, it is found that the maximum corrosion thickness increases by about 23% compared to pure corrosion condition in the weld region, and the structural fatigue damage increases by about 21.36% compared to pure fatigue condition after 10 years of corrosion.

Evaluation of model precision and performance discrepancies in simulated vs. experimental testing of vertical axis wind turbines

The increasing global demand for clean and renewable energy has driven significant advancements in wind turbine technology. This paper explores innovative approaches to harnessing wind energy, with a particular focus on the deployment of vertical axis wind turbines (VAWTs) in urban environments and highways. By strategically positioning turbines along roadways, where wind generated by moving vehicles offers a reliable energy source, this study investigates the potential for integrating wind energy generation with existing infrastructure. The study compares the power generation of three VAWT designs—Giromill, Windside, and Helicoidal—through both physical prototypes and computational simulations. Utilizing 3D printing technology, scaled prototypes of each turbine were constructed and tested under controlled conditions in road separators to capture the wind generated by vehicular traffic. Computational Fluid Dynamics (CFD) software was used to simulate turbine performance under similar conditions. The primary objective is to evaluate the accuracy and error margin between physical tests and computational models, aiming to assess the feasibility of using CFD simulations as a predictive tool for real-world turbine performance. The results will contribute to bridging the knowledge gap in wind energy research, particularly in Colombia, by providing new insights into the comparative efficiency of experimental and simulated approaches. This work builds on previous studies related to wind turbine aerodynamics and 3D prototyping techniques, with a focus on urban wind energy harvesting solutions.

Severity Estimation of Inter-Turn Short-Circuit Fault in PMSM for Agricultural Machinery Using Bayesian Optimization and Enhanced Convolutional Neural Network Architecture

The permanent magnet synchronous motor (PMSM) is a key power component in agricultural machinery. The harsh and variable working environments encountered during the operation of agricultural machinery pose significant challenges to the safe operation of PMSMs. Early diagnosis of inter-turn short-circuit (ITSC) faults is crucial for improving the safety of the motor. In this study, a fault diagnosis method based on an improved convolutional neural network (CNN) architecture is proposed, featuring two main contributions. First, a dilated convolutional neural network is combined with residual structures, multi-scale structures, and channel attention mechanisms to enhance the training efficiency of the model and the quality of feature extraction. Second, Bayesian optimization algorithms are applied for the automatic tuning of architecture hyperparameters in deep learning models, achieving automatic optimization of the hyperparameters for the fault diagnosis model of ITSCs. To validate the effectiveness of the proposed algorithm, 17 simulated tests of ITSC fault severities were conducted under both constant conditions and dynamic conditions. The results show that the proposed model achieves the best performance regarding the validation accuracy (98.2%), standard deviation, F1 scores, and feature learning capability compared to four other models with different architectures, demonstrating the effectiveness and superiority of the algorithm.

Calibration and experiments of discrete element flexible model parameters for kiwifruit stalk

A method combining experimental and simulation optimization was used to calibrate parameters to enhance the accuracy of discrete element model parameters during kiwifruit stem separation. First, physical experiments were conducted to determine the intrinsic and contact parameters of kiwifruit stalk. Second, the mechanical parameters of the kiwifruit stalks were determined using three-point bending and shear tests. On this basis, simulation tests were conducted on kiwifruit stalks by combining the Hertz-Mindlin model with a bonding model, and the optimal combination of bonding parameters was confirmed using the bending strength and maximum shear force. Finally, a discrete element model of the kiwifruit was built with the determined bonding parameters and simulated, and the reliability of the model was verified through mechanical tests. The results showed that the density was 867.5 kg/m3, Poisson's ratio was 0.26, the modulus of elasticity was 3.25 × 108 Pa, the recovery coefficient between the fruit stalks and steel parts was 0.365, and the average values of the static and dynamic friction coefficients between the kiwifruit stalks and steel parts were 0.268 and 0.152, respectively. The kiwifruit stem bonding parameters were normal stiffness per unit area kn=7.201×1011 N/m3, shear stiffness per unit area kt=2.379×1011 N/m3, critical normal stress σmax=5.937×108 Pa, critical shear stress tmax = 2.354×109 Pa, and bonded disc radius Rj=0.164 mm. Compared with the results of the mechanical tests, the relative errors of the bending strength and maximum shear of the discrete element model were 2.13% and 2.84%, respectively. The results showed that the discrete element model improves the simulation of the bending and shearing processes of kiwifruit stalks and is capable of characterizing the physical properties of kiwifruit stalks. The results of this study provide a theoretical foundation for the optimal design of end effectors.

A cooperative control strategy for balancing SoC and power sharing in multiple energy storage unit within DC microgrids

AbstractThis paper proposes a distributed cooperative control scheme for multiple energy storage unit (ESU) in DC microgrids to achieve the control objectives of SoC balancing, power sharing, and bus voltage recovery. In the primary control part, the proposed scheme constructs a control function between the SoC values of each ESU and the droop coefficients to dynamically adjust the droop coefficients. Through a communication network, information is exchanged with neighbouring ESUs to achieve SoC convergence. In the secondary control part, by exchanging power information with neighbouring ESUs, precise power distribution is achieved. Additionally, the proposed scheme maintains bus voltage stability. Finally, a DC microgrid simulation model and experimental platform were developed, demonstrating the feasibility and plug‐and‐play capability of the proposed control strategy through both simulation and experimental case tests.

Optimising Outpatient Registration System Implementation Using Critical Path Method: A Case Study.

Today, hospital information systems (HISs) play an irreplaceable role in hospital management. At present, HIS construction projects in many hospitals have faced the setback of 'project quagmire' to varying degrees. The critical path method (CPM) mainly aims to find the critical path, thus managing project progress. To explore the importance and practical application of the CPM to the management of HIS project schedules. This study used the construction project of a hospital's outpatient registration subsystem as an example. CPM was used to determine the critical path. The time and workload required for the project were calculated using the forward and backward extrapolation methods. The earliest start time and earliest completion time as well as the latest start time and latest completion time of each task could be calculated using the forward and backward extrapolation methods. The path with the longest construction period was determined to be the critical path, and the unit speed rate of each activity was calculated on this basis. Then, the time schedule of the outpatient registration subsystem was compressed and the project schedule optimised. Path 3 [outpatient registration demand analysis (A)-basic data preparation (C)-subsystem test (F)-simulation test (G)] was determined to be the critical path according to the construction period, and the task time was compressed on this basis. Considering many factors, the time of the subsystem test task (F) was reduced from 7 weeks to 4 weeks. The total cost was saved by 1000 yuan, which not only ensured the progress ahead but also saved the overall cost. The CPM could effectively measure the completion and deviation of each stage of the registration system project, which provided an effective guarantee for the subsequent schedule compression to ensure that the project was completed as scheduled and was of sufficient quality. However, all conditions had to be considered comprehensively; doing otherwise would lead to increased risks and costs.

Impact Analysis of Orthogonal Circular-Polarized Interference on GNSS Spatial Anti-Jamming Array

With the continuous advancement of electromagnetic countermeasures, new types of interference signals (e.g., multi-polarization suppression interference) pose a significant threat to conventional Global Navigation Satellite System (GNSS) services, even when the receiver employs a right-handed circularly polarized (RHCP) anti-jamming array. This paper proposes a receiving signal model for orthogonal circularly polarized (OCP) interference signals based on conventional arrays, following an analysis of the non-ideal characteristics of actual arrays. Furthermore, the mechanism by which OCP interference signals affect anti-jamming performance is examined. Power inversion (PI) and linear constrained minimum variance (LCMV) techniques, applied to both uniform linear arrays and central circular arrays, are utilized to verify the impact of these interference signals. Simulation and physical testing demonstrate that OCP interference significantly affects the interference subspace of the conventional RHCP array, potentially leading to a reduction in the anti-jamming performance of the receiver. To effectively suppress multi-polarization interference, anti-jamming GNSS receivers must either ensure the consistency of cross-polarization among the elements of the array or adopt polarization-sensitive arrays.

Optimization Design and Experimental Study of Solid Particle Spreader for Unmanned Aerial Vehicle

This study designed and investigated a solid particle spreader, as well as parameter optimization and experimental for a groove wheel, to mitigate the problems of low uniformity and poor control accuracy of solid particulate material UAV spreading. The discrete element method was used to simulate and analyze the displacement range and stability of each grooved wheel at low speeds. Furthermore, orthogonal regression and response surface analyses were used to analyze the influence of each factor on the stability of the discharge rate and pulsation amplitude. The results showed that the helix angle, sharpness, and length of the groove significantly influenced the application performance, whereas the number of grooves had no significant influence. The groove shape was eccentric, the helix angle was 50°, the length was 35 mm, and the number of grooves was 7. Additionally, the bench test results showed that in the range of 10–60 rpm, the relative deviation of the discharging rate between the simulation and bench test is from 0.47% to 10.39%, and the average relative deviation is 3.93%. Between the groove wheel rotation speed and discharge rate, R2 was 0.991, and the adjustable range of the discharge amount was between 3.68 and 23.43 g/s. The minimum and maximum variation coefficients of the average discharge rate among individual applicators were 1.01% and 2.79%, respectively, whereas the standard deviations were 0.09 and 0.46 g/s, respectively. In conclusion, the discharge stability and adjustable range of the spreader using the optimized groove wheel satisfied the requirements for solid particulate material discharge.

Large eddy simulations and experimental studies of the influence of equivalence ratio on the combustion characteristics of turbulent NH3–CH4 premixed flames

As one of the most promising zero-carbon fuels, ammonia has attracted widespread attention. However, ammonia combustion faces problems such as high nitrogen oxide emissions. This work aims to investigate the combustion characteristics of fuel gas mixture of 60% NH3 and 40% CH4 by volume, under five different equivalence ratios, i.e., 0.7, 0.85, 1.0, 1.15, and 1.3, respectively. Both large eddy simulation (LES) and experimental test are conducted. The results reveal that flame temperature and nitric oxide (NO) emissions exhibit an initial increase, followed by a decrease with rising equivalence ratios. Notably, the highest temperature is observed at ϕ = 1.0, while peak NO emission is found at ϕ = 0.85. As the equivalence ratio changes, the variation of turbulent flow fields and mass recirculation rates is not significant. On the contrary, NO and OH radicals exhibit distinct shifts in relation to the equivalence ratio. The NO emissions predicted by LES agree well with the experimental results. A chemical reaction network (CRN) analysis is also conducted, which effectively predicts NO variation trends and clarifies NO generation pathways and key mechanisms. The CRN analysis highlights variations in the sensitivities of crucial constituents, such as NH3, OH, and NO, to variations in the equivalence ratio.