Optimizing Average Electric Power During the Charging of Lithium-Ion Batteries Through the Taguchi Method

In recent times, lithium-ion batteries have been widely used owing to their high energy density, extended cycle lifespan, and minimal self-discharge rate. The design of high-speed rechargeable lithium-ion batteries faces a significant challenge owing to the need to increase average electric power during charging. This challenge results from the direct influence of the power level on the rate of chemical reactions occurring in the battery electrodes. In this study, the Taguchi optimization method was used to enhance the average electric power during the charging process of lithium-ion batteries. The Taguchi technique is a statistical strategy that facilitates the systematic and efficient evaluation of numerous experimental variables. The proposed method involved varying seven input factors, including positive electrode thickness, positive electrode material, positive electrode active material volume fraction, negative electrode active material volume fraction, separator thickness, positive current collector thickness, and negative current collector thickness. Three levels were assigned to each control factor to identify the optimal conditions and maximize the average electric power during charging. Moreover, a variance assessment analysis was conducted to validate the results obtained from the Taguchi analysis. The results revealed that the Taguchi method was an eff ective approach for optimizing the average electric power during the charging of lithium-ion batteries. This indicates that the positive electrode material, followed by the separator thickness and the negative electrode active material volume fraction, was key factors significantly infl uencing the average electric power during the charging of lithium-ion batteries response. The identification of optimal conditions resulted in the improved performance of lithium-ion batteries, extending their potential in various applications. Particularly, lithium-ion batteries with average electric power of 16 W and 17 W during charging were designed and simulated in the range of 0-12000 s using COMSOL Multiphysics software. This study efficiently employs the Taguchi optimization technique to develop lithium-ion batteries capable of storing a predetermined average electric power during the charging phase. Therefore, this method enables the battery to achieve complete charging within a specific timeframe tailored to a specificapplication. The implementation of this method can save costs, time, and materials compared with other alternative methods, such as the trial-and-error approach.

To improve robustness of mechanical properties of semi-solid cast A356 alloy using taguchi design method

Mechanical properties of semi-solid casting are dependent on multiple processing parameters,and improper processing parameters will not only reduce mean data but also increase variations.The present study investigated the impact of parameters in slurry preparation and heat treatment on the yield strength and ductility of T6 heat-treated A356 Al-Si alloy using rapid slurry forming(RSF)semi-solid casting.The focus was primarily on the robustness of mechanical properties based on Taguchi design method.By analyzing signal-to-noise ratio and minimum value calculated from-3S,the optimum slurry preparation parameters and heat treatment parameters were determined to be no quench,enthalpy exchange material(EEM)temperature of 140℃,EEM-to-melt ratio of 6mass%,stirring time of 18 s,solution heat treated at 520℃ for 2 h,and ageing heat treated at 190℃ for 6 h.In a small batch validation,the-3S yield strength and-3S elongation reach 256.1 MPa and 5.03% respectively,showing a satisfactory robustness.The hardness and microstructure of heat-treated samples with the best and worst properties were characterized to gain insight into the underlying mechanisms affecting the mean value and variations of mechanical properties.

Multi-Objective Optimization of Fused Deposition Modeling for Mechanical Properties of Biopolymer Parts Using the Grey-Taguchi Method

The urgent need to develop customized functional products only possible by 3D printing had realized when faced with the unavailability of medical devices like surgical instruments during the coronavirus-19 disease and the ondemand necessity to perform surgery during space missions.Biopolymers have recently been the most appropriate option for fabricating surgical instruments via 3D printing in terms of cheaper and faster processing.Among all 3D printing techniques,fused deposition modelling(FDM)is a low-cost and more rapid printing technique.This article proposes the fabrication of surgical instruments,namely,forceps and hemostat using the fused deposition modeling(FDM)process.Excellent mechanical properties are the only indicator to judge the quality of the functional parts.The mechanical properties of FDM-processed parts depend on various process parameters.These parameters are layer height,infill pattern,top/bottom pattern,number of top/bottom layers,infill density,flow,number of shells,printing temperature,build plate temperature,printing speed,and fan speed.Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of polylactic acid(PLA)parts printed by FDM.The experiments have performed through Taguchi’s L27orthogonal array(OA).Variance analysis(ANOVA)ascertains the significance of the process parameters and their percent contributions to the evaluation indexes.Finally,as a multiobjective optimization technique,grey relational analysis(GRA)obtains an optimal set of FDM process parameters to fabricate the best parts with comprehensive mechanical properties.Scanning electron microscopy(SEM)examines the types of defects and strong bonding between rasters.The proposed research ensures the successful fabrication of functional surgical tools with substantial ultimate tensile strength(42.6 MPa)and modulus of elasticity(3274 MPa).

Optimum Design of Stair-Climbing Robots Using Taguchi Method

Environmental issues like pollution are major threats to human health.Many systems are developed to reduce pollution.In this paper,an optimal mobile robot design to reduce pollution in Green supply chain management system.Green supply chain management involves as similating environmentally and eco-nomically feasible solutions into the supply chain life-cycle.Smartness,advanced technologies,and advanced networks are becoming pillars of a sustainable supply chain management system.At the same time,there is much change happening in the logistics industry.They are moving towards a new logistics model.In the new model,robotic logistics has a vital role.The reasons for this change are the rapid growth of the e-commerce business and the shortage of workers.The advantages of using robotic logistics are reduction in human errors,faster delivery speed,better customer satisfaction,more safety for workers,and high workforce adaptability.A robot with rocker-bogie suspension is a six-wheeled mobile platform that has a distinctive potential to keep all wheels on the ground continuously.It has been designed to traverse rough and uneven terrain by distributing the load over its wheels equally.However,there is a limitation to achieving high-speed mobility against vertical barriers.In this research,an optimal design of product delivery wheeled robots for a sustainable supply chain system is proposed to ensure higher adaptability and maximum stability during climbing staircases.The design parameters of the proposed robot are optimized using Taguchi Method.The aim is to get a smooth trajectory of the robot’s center-of-mass.The proposed approach realizes a robot with much-improved stability which can climb over heights more than the size of the wheel(i.e.,3 times the radius of wheels).The results reveal that the modified rocker-bogie system not only increases the stair-climbing capability but also thwarts instability due to overturning of a wheel of the robot.

Design of Rotor Magnetic Barrier Structure of Built-in Permanent Magnet Motor Based on Taguchi Method

In this paper,a 20kW vehicle built-in permanent magnet synchronous motor is taken as an example,and a magnetic barrier structure is added to the rotor of the motor to solve the uneven saturation problem of the rotor side magnetic bridge.This structure improves the air-gap flux density waveform of the motor by influencing the internal magnetic flux path of the motor rotor,thus improving the sine of the no-load back EMF waveform of the motor and reducing the torque ripple of the motor.At the same time,Taguchi method is used to optimize the structural parameters of the added magnetic barrier.In order to facilitate the analysis of its uneven saturation phenomenon and improve the optimization effect,a simple equivalent magnetic network(EMN)model considering the uneven saturation of rotor magnetic bridge is established in this paper,and the initial values of optimization factors are selected based on this model.Finally,the no-load back EMF waveform distortion rate,torque ripple and output torque of the optimized motor are compared and analyzed,and the influence of magnetic barrier structure parameters on the electromagnetic performance of the motor is also analyzed.The results show that the optimized motor can not change the output torque of the motor as much as possible on the basis of reducing the waveform distortion rate of no-load back EMF and torque ripple.

Optimization of chemistry and process parameters for control of intermetallic formation in Mg sludges

Intermetallic formation in sludge during magnesium(Mg)melting,holding and high pressure die casting practices is a very important issue.But,very often it is overlooked by academia,original equipment manufacturers(OEM),metal ingot producers and even die casters.The aim of this study was to minimize the intermetallic formation in Mg sludge via the optimization of the chemistry and process parameters.The Al8Mn5 intermetallic particles were identified by the microstructure analysis based on the Al and Mn ratio.The design of experiment(DOE)technique,Taguchi method,was employed to minimize the intermetallic formation in the sludge of Mg alloys with various chemical compositions of Al,Mn,Fe,and different process parameters,holding temperature and holding time.The sludge yield(SY)and intermetallic size(IS)was selected as two responses.The optimum combination of the levels in terms of minimizing the intermetallic formation were 9 wt.%Al,0.15 wt.%Mn,0.001 wt.%(10 ppm)Fe,690℃ for the holding temperature and holding at 30 mins for the holding time,respectively.The best combination for smallest intermetallic size were 9 wt.%Al,0.15 wt.%Mn,0.001 wt.%(10 ppm)Fe,630℃ for the holding temperature and holding at 60 mins for the holding time,respectively.Three groups of sludge factors,Chemical Sludge(CSF),Physical Sludge(PSF)and Comprehensive Sludge Factors(and CPSF)were established for prediction of sludge yields and intermetallic sizes in Al-containing Mg alloys.The CPSF with five independent variables including both chemical elements and process parameters gave high accuracy in prediction,as the prediction of the PSF with only the two processing parameters of the melt holding temperature and time showed a relatively large deviation from the experimental data.The Chemical Sludge Factor was primarily designed for small ingot producers and die casters with a limited melting and holding capacity,of which process parameters could be fixed easily.The Physical Sludge Factor could be used for mass production with a single type of Mg alloy,in which the chemistry fluctuation might be negligible.In large Mg casting suppliers with multiple melting and holding furnaces and a number of Mg alloys in production,the Comprehensive Sludge Factor should be implemented to diminish the sludge formation.

Performance Investigation of Cone Dielectric Elastomer Actuator Using Taguchi Method

Dielectric elastomer actuator （DEA） show promise for mechatronic applications due to the advantages of dielectric elastomer, such as lightweight, flexible, low cost, high strain, etc, and many configurations of DEAs have been demonstrated. As a kind of linear actuator, cone DEAs are studied in some laboratory prototypes due to easy manufacturing, however, their performance have not been exploited fully. Based on the working principle of DEA, a four-bar linkage mechanism is designed to provide negative stiffness preload, which can increase displacement output of actuator （outer diameter 100 mm） to 17 mm. Three cone actuating units are assembled in parallel to enhance the maximum force output to 5.07 N. Loading experiments of actuator in forward and backward strokes are performed, the experimental results show that backward stroke has stronger actuating capability than forward stroke, accordingly application of actuator is recommended. Four factors rather than applied voltage, i.e., number of actuating units, pre-stretch ratio, inner diameter, and outer diameter, are determined as influencing factors for Taguchi method. Then the performance objectives of actuator, i.e., displacement output, maximum force output, and maximum work in backward stroke, are investigated based on L9（34） Taguchi orthogonal design. The mean signal-to-noise （S/N） ratio based on the larger-the-better criterion is calculated according to the acquired displacement and force output. Analytical results show that outer diameter has the most significant influence on displacement output, and maximum force out and work output are influenced most by number of actuating units. Inner diameter also has an important effect on the performance objectives of actuator, while pre-stretch ratio has the least influence. The proposed performance investigation is helpful for the design and application of cone actuator in mechatronic system.

Wear Studies on Metal Matrix Composites: a Taguchi Approach

An attempt has been made to study the influence of wear parameters like applied load, sliding speed, sliding distance and percentage of reinforcement on the dry sliding wear of the metal matrix composites. A plan of experiments, based on techniques of Taguchi, was performed to acquire data in controlled way. An orthogonal array and the analysis of variance were employed to investigate the influence of process parameters on the wear of composites. The objective is to establish a correlation between dry sliding wear of composites and wear parameters. These correlations were obtained by multiple regressions. Finally, confirmation tests were conducted to verify the experimental results foreseen from the mentioned correlations.

Optimization of Polishing Parameters with Taguchi Method for LBO Crystal in CMP

Chemical mechanical polishing （CMP） was used to polish Lithium triborate （LiB3O5 or LBO） crystal. Taguchi method was applied for optimization of the polishing parameters. Material removal rate （MRR） and surface roughness are considered as criteria for the optimization. The polishing pressure, the abrasive concentration and the table velocity are important parameters which influence MRR and surface roughness in CMP of LBO crystal. Experiment results indicate that for MRR the polishing pressure is the most significant polishing parameter followed by table velocity; while for the surface roughness, the abrasive concentration is the most important one. For high MRR in CMP of LBO ctystal the optimal conditions are： pressure 620 g/cm^2, concentration 5.0 wt pct, and velocity 60 r/min, respectively. For the best surface roughness the optimal conditions are： pressure 416 g/cm^2, concentration 5.0 wt pct, and velocity 40 r/min, respectively. The contributions of individual parameters for MRR and surface roughness were obtained.

Determining the Effect of Cutting Fluids on Surface Roughness in Turning AISI 1330 Alloy Steel Using Taguchi Method

Taguchi method has been employed to investigate the effects of cutting fluids on surface roughness in turning AISI 1330 alloy steel, using manually operated lathe machine. Experiments have been conducted using L27 (34) orthogonal array and each experiment was repeated three times and each test used a new cutting tool, High Speed Steel (HSS), to ensure accurate readings of the surface roughness. The statistical methods of Signal-to-Noise (S/N) ratio and the Analysis of Variance (ANOVA) were applied to investigate effects of cutting speed, feed rate and depth of cut on surface roughness under different cutting fluids. Minitab 14 software was used to analyze the effect of variables on the surface roughness. Results obtained indicated that optimal variables for the minimum surface roughness were cutting speed of 35 m/min (level 2), feed of 0.124 mm/rev (level 1), depth of cut of 0.3 mm (level 1) and a cutting fluid with a viscosity of 2.898 mm2/s (level 3). Hence, the optimal parameters to obtain better surface roughness of the workpiece material were obtained when groundnut oil based cutting fluid was used. Analysis of variance shows that feed rate has the most significant effect on surface roughness.

Synthesis of the CuInSe_2 thin film for solar cells using the electrodeposition technique and Taguchi method

The Taguchi method was used to obtain the optimum electrodeposition parameters for the synthesis of the CuInSe2 thin film for solar cells. The parameters consist of annealing temperature, current density, CuCl2 concentration, FeCl3 concentration, H2SeO3 concentration, TEA amount, pH value, and deposition time. The experiments were carried out according to an L18（2^13^7） table An X-ray diffractometer （XRD） and a scanning electron microscope （SEM） were respectively used to analyze the phases and observe the microstructure and the grain size of the CuInSe2 film before and after annealing treatment. The results showed that the CuInSe2 phase was deposited with a preferred plane （112） parallel to the substrate surface. The optimum parameters are as follows： current density, 7 mA/cm^2; CuCl2 concentration, 10 mM; FeCl3 concentration, 50 mM; H2SeO3 concentration, 15 mM; TEA amount, 0 mL; pH value, 1.65; deposition time, 10 min; and annealing temperature, 500℃.

TOPSIS based Taguchi design optimization for CVD growth of graphene using different carbon sources: Graphene thickness, defectiveness and homogeneity

Chemical inhomogeneity of chemical vapor deposition(CVD) grown graphene compromises its usage in highperformance devices. In this study, TOPSIS based Taguchi optimization was performed to improve thickness uniformity and defect density of CVD grown graphene. 1.56% decrease in the mean 2 D/G intensity ratio, 87.96% improvement in the mean D/G intensity ratio, 56.07% improvement in the standard deviation D/G intensity ratio, 25.21%improvement in the standard deviation 2 D/G intensity ratio, and 69.32% improvement in the surface roughness were achieved with TOPSIS based Taguchi optimization. The statistical differences between the copper and silicon substrates have been found significantly in terms of their impacts on the graphene's properties with the0.000 p-value for the mean D/G intensity ratio and with the 0.009 p-value for the mean 2 D/G intensity ratio, respectively. Graphene having 11% lower mean D/G intensity ratio(low defective graphene products) compared to the values given in the literature using single-response optimization was obtained using multi-response optimization.

The Interaction Effects of the Parameters on Optimization Design in Paper Production Waste Usage on Alkali-Activated Slag with Taguchi Method

The paper investigates the second-order interactions of parameters in an alkali-activated mixture of paper production waste(PPW)and blast furnace slag(BFS)in Taguchi method.The PPW including lime mud(LM)and paper sludge(PS).This paper provides the experimental models to assess the compressive and flexural strength of them at 7-day and 28-day.The results have shown that the second-order interactions between PPW and alkali-activated activator exists in each experimental model,and the significant interactions affect the selection of optimal compositions.Compared with the interactions between the PPW themselves,the interactions between PPW and alkali-activated parameters are the main significant factors affecting its physical properties.In each experimental model,the maximum compressive strength was 47.41 MPa in 7-day and 65.64 MPa in 28-day.Compared with the confirmatory experiments,the deviation of prediction calculated by experimental models was 3.08%and 0.56%,respectively.The maximum flexural strength was 5.74 MPa in 7-day and 5.96 MPa in 28-day;compared with the confirmatory experiments,the deviation of prediction calculated by experimental models was 5.40%and 0.17%.Considering the influence of circular materials,30%of PPW should be a suitable ratio to replace BFS as the raw material of alkali-activated slag(AAS).

Application for Optimization of New Soft Magnetic Material Motor by Taguchi Method

The application of new soft magnetic materials in permanent magnet motor can effectively reduce the loss of motor and improve the efficiency of motor. Taguchi method is a local multivariable and multi-objective optimization method widely used in various engineering problems, which can effectively improve the efficiency of engineering optimization. In this paper, based on a 25 kW, 1700 r/min three-phase permanent magnet motor, the relevant motor model is established in the finite element simulation software, and the relevant simulation analysis is carried out. Combined with Taguchi method optimization, the local optimal structure scheme is obtained. Through optimization, the motor can maintain high efficiency, reduce the cogging torque of the motor by 53.45%, reduce the torque ripple by 36.79%, and increase the torque generated by the permanent magnet per unit mass by 21.42%. Through this optimization, the overall performance of the motor has been significantly improved. The research content of this paper verifies the feasibility of the application of Taguchi method in the optimization of new soft magnetic material motor, provides a new idea for the optimization design of new soft magnetic material motor, and also provides a certain reference for the local multi-objective optimization of the electromagnetic structure of other similar motors.

Evaluation of microstructure and mechanical properties of squeeze overcast Al7075-Cu composite joints

Al7075-Cu composite joints were prepared by the squeeze overcast process.The effects of melt temperature,die temperature,and squeeze pressure on hardness and ultimate tensile strength(UTS)of squeeze overcast Al7075-Cu composite joints were studied.The experimental results depict that squeeze pressure is the most significant process parameter affecting the hardness and UTS.The optimal values of UTS(48 MPa)and hardness(76 HRB)are achieved at a melt temperature of 800℃,a die temperature of 250℃,and a squeeze pressure of 90 MPa.Scanning electron microscopy(SEM)shows that fractured surfaces show flatfaced morphology at the optimal experimental condition.Energy-dispersive spectroscopy(EDS)analysis depicts that the atomic weight percentage of Zn decreases with an increase in melt temperature and squeeze pressure.The optimal mechanical properties of the Al7075-Cu overcast joint were achieved at the Al2Cu eutectic phase due to the large number of copper atoms that dispersed into the aluminum melt during the solidification process and the formation of strong intermetallic bonds.Gray relational analysis integrated with the Taguchi method was used to develop an optimal set of control variables for multi-response parametric optimization.Confirmatory tests were performed to validate the effectiveness of the employed technique.The manufacturing of squeeze overcast Al7075-Cu composite joints at optimal process parameters delivers a great indication to acknowledge a new method for foundry practitioners to manufacture materials with superior mechanical properties.

Artificial Intelligence in Internet of Things System for Predicting Water Quality in Aquaculture Fishponds

Aquaculture has long been a critical economic sector in Taiwan.Since a key factor in aquaculture production efficiency is water quality,an effective means of monitoring the dissolved oxygen content(DOC)of aquaculture water is essential.This study developed an internet of things system for monitoring DOC by collecting essential data related to water quality.Artificial intelligence technology was used to construct a water quality prediction model for use in a complete system for managing water quality.Since aquaculture water quality depends on a continuous interaction among multiple factors,and the current state is correlated with the previous state,a model with time series is required.Therefore,this study used recurrent neural networks(RNNs)with sequential characteristics.Commonly used RNNs such as long short-term memory model and gated recurrent unit(GRU)model have a memory function that appropriately retains previous results for use in processing current results.To construct a suitable RNN model,this study used Taguchi method to optimize hyperparameters(including hidden layer neuron count,iteration count,batch size,learning rate,and dropout ratio).Additionally,optimization performance was also compared between 5-layer and 7-layer network architectures.The experimental results revealed that the 7-layer GRU was more suitable for the application considered in this study.The values obtained in tests of prediction performance were mean absolute percentage error of 3.7134%,root mean square error of 0.0638,and R-value of 0.9984.Therefore,thewater qualitymanagement system developed in this study can quickly provide practitioners with highly accurate data,which is essential for a timely response to water quality issues.This study was performed in collaboration with the Taiwan Industrial Technology Research Institute and a local fishery company.Practical application of the system by the fishery company confirmed that the monitoring system is effective in improving the survival rate of farmed fish by providing data needed to maintain DOC higher than the standard value.

Cooling System Design Optimization of an Enclosed PM Traction Motor for Subway Propulsion Systems

This paper presents the design optimization of a self-circulated ventilation system for an enclosed permanent magnet(PM)traction motor utilized in the propulsion systems for subway trains.In order to analyze accurately the machine's inherent cooling capacity when the train is running,the ambient airflow and the related heat transfer coefficient(HTC)are numerically investigated considering synchronously the bogie installation structure.The machine is preliminary cooled with air ducts set on the motor shell,and the fluidic-thermal field distributions with only the shell air duct cooling are numerically calculated.During simulations,the HTC obtained in the former steps is applied to the external surface of the machine to model the inherent cooling characteristic caused by the train movement.To reduce the temperature rise and thus guarantee the motor's working reliability,an internal self-circulated air cooling system is proposed according to the machine temperature distribution.The air enclosed in the end-caps is driven by the blades mounted on both sides of the rotor core and forms two air circuits to bring the excessive power losses generated in the heating components to cool regions.The fluid flow and temperature rise distributions of the cooling system's structural parameters are further improved by the Taguchi method in order to confirm the efficacy of the internal air cooling system.

Characterization of Unsaturated Polyester Filled with Waste Coconut Shells, Walnut Shells, and Carbon Fibers

This study aims to evaluate the erosion behavior and the hardness of hybrid composites made of varying amounts of coconut shells,walnut shells,and carbonfibers dispersed in a polyester matrix.MINITAB(L16)Taguchi experiments were used to determine the optimal combination of parameters.In particular,an erosion device con-sisting of a motor with a constantflow rate of 45 L/min,a pump with a diameter of 40 mm,a nozzle with a dia-meter of 5 mm,and a tank made of“perspex glass”55 cm long,30 cm tall,and 25 cm wide was used.The tests were conducted by varying the sample-to-nozzle distance,the pattern angle,and the sand particle size.The results have revealed that the presence of 7.5%by weight of waste coconut shell,for conditions corresponding to 90°angle,sand size 425μm,stand distance 30 cm,gives the best wear resistance(3.04×10^(-5) g/g).Thefiller content and sand particle size affect the erosive rate,with the angle playing a secondary role.The distance between the sample and the nozzle has a weaker effect on erosive wear.The hardness results show that the models(UP-5%carbonfiber-2.5-3.5-4.5-5.5-6.5-7.5 wt.%waste coconut shell)give the best values for prayer compared to the samples(UP-5 wt.%carbonfiber-2.5-3.5-4.5-5.5-6.5-7.5 wt.%waste walnut shell).

Simulation-based Optimal Design of α-β-γ-δ Filter

The existing third-order tracker known as α-β-γ-δ filter has been used for target tracking and predicting for years. The filter can track the target＇s position and velocity, but not the acceleration. To extend its capability, a new fourth-order target tracker called α-β-γ-δ filter is proposed. The main objective of this study was to find the optimal set of filter parameters that leads to minimum position tracking errors. The tracking errors between using the α-β-γ-δ filter and the α-β-γ-δ filter are compared. As a result, the new filter exhibits significant improvement in position tracking accuracy over the existing third-order filter, but at the expense of computational time in search of the optimal filter. To reduce the computational time, a simulation-based optimization technique via Taguchi method is introduced.

Optimization for aerodynamic performance of double serpentine nozzles with spanwise offsets using Taguchi-based CFD analysis

Serpentine nozzles are widely used in combat aircraft to realize strong stealth characteristics.Based on the layout characteristics within a confined space,a series of double serpentine nozzles with spanwise offsets are established.Using computational fluid dynamics and Taguchi method,the influence mechanisms of the Distribution of Area(DA),Distributions of Centerline for the first and second‘S’sections in the Vertical direction(DCV1 and DCV2),and Distribution of Centerline in the Spanwise direction(DCS)are analyzed.The impact of these factors on the total pressure recovery coefficient can be ranked as DA>DCV2>DCS>DCV1,whereas their impacts on the discharge coefficient and axial thrust coefficient can be ranked as DCV2>DCS>DA>DCV1.Considering the statistical significance of these factors,a nozzle in which DA changes rapidly at the exit and DCV1,DCV2,and DCS change rapidly at the entrance gives the best aerodynamic performance.Compared to the worst configuration,the total pressure recovery coefficient,discharge coefficient,and axial thrust coefficient are improved by 1.6%,3.5%and 3.6%,respectively.DA influences the gas flow acceleration in the entire serpentine channel,resulting in different wall shear stress and friction losses.The various centerline distributions influence the gas flow acceleration effects and form complex wave structures in the constantarea extension section,resulting in different local and friction losses.