Minimum Fatigue Life Research Articles

On the prediction of fatigue life of WAAM-processed Ti-6Al-4V under consideration of manufacturing defects

PurposeThere is still a need for a comprehensive investigation into how wire and arc manufactured (WAAM) parts fail under cyclic loading. This study investigates the effect of process-induced defects on the high-cycle fatigue performance of WAAM-processed Ti-6Al-4V with dedicated thermal treatment. Furthermore, the study assesses the applicability of the fatigue life prediction model, which was originally developed and validated for laser beam-welded Ti-6Al-4V joints, to WAAM-fabricated structures.Design/methodology/approachThe fatigue life assessment model was adapted to WAAM-fabricated Ti-6Al-4V. This model is based on the NASGRO equation, which considers short crack growth from internal and surface defects, such as lack of fusion defects and pores. The model was used to create artificial Wöhler curves, and the results from stress intensity factor range-decreasing fatigue crack propagation rate tests are compared to the experimental data in the form of a Kitagawa–Takahashi (KT) diagram.FindingsThe results demonstrate that the model can accurately predict the minimum fatigue life of specimens extracted from WAAM structures. When considering that the crack from internal defects grows in a vacuum-like environment, accurate Wöhler curves are predicted. The experimental data does not follow the expected trends of the KT diagram. Nonetheless, the measured long crack threshold stress intensity factor range produces a suitable estimate of defect severity.Originality/valueThe study results in a model with which a probabilistic computation of the fatigue life of additively manufactured samples based on the defect size distribution is possible. Furthermore, the KT diagram as a criterion for the assessment of defect severity is evaluated.

Numerical analysis of vortex-induced vibration of deepwater drilling riser based on Van der Pol wake oscillator model

Coupled equations of the dynamic model and the Van der Pol wake oscillator model are solved by the central finite difference method for the deepwater drilling riser. The vortex-induced vibration (VIV) response and fatigue life of the riser are calculated and the model validation is performed by comparing with the published experimental and simulation results. The effects of the top tension, current flow velocity, flow velocity profile, internal flow velocity as well as the installation of buoyancy modules on the VIV are discussed. Dynamic response and fatigue life of the riser under In-Line (IL) and Cross-Flow (CF) VIV are preliminarily analyzed. The results show that the VIV of the riser has multiple modes and exhibits a mixed behavior of standing waves and traveling waves. With the increase of top tension and flow velocity profile coefficient, the order of the VIV dominant mode and the peak values of the root mean square (RMS) of VIV displacement decrease, and the fatigue life of the riser is extended. With the increase of current flow velocity, the order of the VIV dominant mode increases and the riser fatigue life decreases. The effect of internal flow velocity on the riser VIV is neglectable. The installation of buoyancy modules can improve the riser stress state and extend the fatigue life. Compared with the CF VIV model, the calculated minimum fatigue life of the riser is extended under the IL and CF coupled VIV model due to the decrease of bending moment and the changing position of fatigue weak point.

Fatigue failure analysis of bulb turbine sealing gland bolts based on vibration signal

Abstract Aiming at the issue of fatigue fracture of the sealing gland bolts, this paper takes a bulb tubular turbine with frequent breakage of sealing gland bolts as the research object, establishes a finite element model of the sealing gland, and collects the vibration signals of the sealing gland under three common working conditions through vibration tests. Based on the vibration signal data and dynamic analysis, the vibration fatigue load spectrum of the sealing gland is calculated, and then the fatigue analysis of the sealing gland bolts is carried out. The results revealed that vibration of the sealing gland in the -X direction is much more severe than that in the +X direction, and the minimum fatigue life of the sealing gland bolt group in the - X direction is much shorter than that in the +X direction. Comparing the fatigue analysis results of the ±X-direction sealing gland bolts under different working conditions, it is found that under the same test water head, the service life of the sealing gland bolts under stable operation of 15MW is longer than that of 10MW and 20MW. It is recommended to take measures to reduce the problem of excessive vibration in the -X direction of the unit.

Deformation mechanism and life prediction model of titanium alloy laser-arc hybrid welded joint during fatigue

The deformation mechanism and life prediction model of titanium alloy laser-arc hybrid welded joint during fatigue were studied. At the relatively small maximum cyclic stresses σmax (310 MPa to 350 MPa), the fatigue cracks initiated at the interface of lamellar α′ and needle-like α′ around the pore. At σmax=370MPa, the elongated lamellar α′ around the pore promoted fatigue crack propagation, leading to the formation of secondary cracks. At σmax=390MPa, the formation of two fatigue crack initiation locations and the occurrence of secondary cracks led to the maximum fatigue damage and the minimum fatigue life. In addition, the plastic deformation mainly occurred in β at σmax=310MPa, and it transformed into the phase interface of secondary α-β and granular β-α′ at σmax=350MPa. At σmax=390MPa, the main deformation forms were the cross-slip in β and the dislocations entanglement in α′. Finally, the fatigue life prediction model was established based on the equivalent cyclic stress, and the predicted fatigue life fell within a 3-fold error band.

Multi-objective optimization design for anti-fatigue lightweight of dump truck carriage combined with machine learning

As urbanization continues to accelerate, dump trucks assume an increasingly important role in the transportation and construction of infrastructure. The carriage represents a critical structural assembly of dump trucks. One of the primary failure modes of the carriage is weld fatigue failure, which frequently gives rise to the problem of weld fatigue cracking during transportation. To increase the fatigue life of welds and enhance the degree of structural lightweight of a heavy dump truck carriage, a method for anti-fatigue lightweight design based on machine learning and multi-objective optimization is proposed. A high-fidelity finite element model of the carriage is established for static simulation analysis of the typical conditions. Based on the virtual reliability simulation test of the dump truck and the equivalent structural stress method, the fatigue life of the critical welds in the carriage is calculated. The important part thicknesses are selected as design variables through the comprehensive contribution analysis method. The maximum displacement and maximum stress under the dangerous condition are considered as constraints. The mass of the carriage and the minimum fatigue life of the critical welds are considered as optimization objectives. The GA-XGBoost machine learning approximation models (GA-XGBoost-MLAM) and NSGA-II algorithm are employed for multi-objective optimization design of the carriage. The entropy weighted TOPSIS method is utilized for multi-objective decision-making of Pareto solutions. The design after optimization and decision-making shows that, while satisfying the requirements of static structural performance, the minimum fatigue life mileage of the critical welds of the carriage is increased by 157,570 km, representing an increase of 36.58%. Additionally, the mass of the carriage is reduced by 295.69 kg, representing a decrease of 9.47%. Therefore, the proposed design method achieves a good effect in the anti-fatigue lightweight of dump truck carriage.

Design and Fatigue Life Analysis of the Rope-Clamping Drive Mechanism in a Knotter

A knotter is a core component for the automatic bundling of agricultural materials, and a knotter with double-fluted discs is one type. Currently, the research on knotters with double-fluted discs has gradually transitioned from structural design to reliability optimization. To address rope-clamping failures in the rope-clamping drive mechanisms in knotters, the specific failure position of the rope-clamping mechanism and the failure causes were analyzed first. The redesign of the rope-clamping drive mechanism in knotters with double synclastic fluted discs was proposed, including structure optimization and 3D modeling using the GearTrax/KISSsoft and SolidWorks software. A virtual prototype model of a knotter with a flexible rope was established by combining ANSYS with the ADAMS software. A rigid–flexible coupling dynamic simulation of the knotter was carried out using ADAMS, and the simulation results were used as the data input for the ANSYS nCode DesignLife module for the fatigue life simulation of the weak parts (the worm shaft) of the knotter. The operation test results for the rope-clamping drive mechanism indicate that the redesigned rope-clamping drive mechanism is reliable in transmission, with a rope-clamping success rate of 100%. The actual operation times for the worm shaft exceed the minimum fatigue life obtained through joint simulation. The applied joint simulation method has high simulation accuracy.

Study on Flat Die Wear Characteristics in Flat Die Pelletizing with Different Material Ratios Based on DEM-FEM

Wear can occur in flat die pelletizers, often reducing service life. This study explores the issue of die hole wear in the pelletizing process of a standard Total Mixed Ration (TMR) feed. The selected TMR formulation comprises varying proportions of corn, alfalfa hay, and quinoa. A coupled DEM-FEM analysis was used to examine stress–strain conditions in various die hole regions at different material ratios, predict the fatigue life of flat die materials in the pelletizing process, and validate the accuracy of investigating flat die wear through friction wear tests. It was found that the entrance of the die hole experiences the most severe conditions in terms of equivalent stress and elastic strain. The fatigue life is shortest at the entrance, with a maximum equivalent stress of 42.8 MPa, a maximum equivalent elastic strain of 2.5 × 10−3, and a minimum fatigue life stress cycle of 5.0 × 105. In contrast, the equivalent stress and equivalent elastic strain at the middle and upper parts of the die hole are minimal, with an equivalent stress of 4.8 MPa and a minimum equivalent elastic strain of 2.8 × 10−4. Material wear tests revealed that the most severe wear on the flat die specimen occurred when the ratio of corn, alfalfa hay, and quinoa straw was 7:2:1, consistent with the findings from the DEM-FEM coupling method. The pelleting process, arising from the contact between the material and metal, encompasses adhesive wear, abrasive wear, and fatigue wear.

Analyzing Safety Factors and Predicting Fatigue Life of Weak Points in an Electrically Driven, Multi-Purpose Cultivation Tractor

The advancement of agriculture and a shortage of labor have led to an increased use of agricultural machinery. However, the resulting environmental issues have prompted a shift from internal combustion engines to electric drivetrains. The electric drivetrain includes the installation of batteries, which can lead to decreased energy efficiency and significant loads on the vehicle due to their heavy weight. Consequently, the importance of ensuring the safety of agricultural machinery is being increasingly emphasized. The load on the frame of agricultural machinery is not consistent during off-road driving, and the accumulation of load cycles can lead to the destruction and failure of components. Therefore, it is necessary to ensure a level of safety and to predict the fatigue life. In this study, we estimate the safety factor and predict the fatigue life of weak points in an electrically driven, multi-purpose cultivation tractor based on working conditions (width, soil, and drive). Strain gauges were attached to these weak points to measure the strain, which was then converted to von Mises stress. Fatigue life was predicted using the rainflow counting method and the Palmgren–Miner rule. The results showed that the safety factor measured under various working conditions was greater than 1. The estimated minimum fatigue life was 124,176 years. Considering that the cultivator is used for 29.7 h annually and has a durability lifespan of 5 years, it is expected to be safely usable throughout its service life.

Improvement of mechanical properties and corrosion resistance of SLM-AlSi10Mg alloy by an eco-friendly electric pulse treatment

In this study, we aim to effectively improve the mechanical properties and corrosion resistance of SLM-AlSi10Mg ally by electric pulse treatment (EPT), which is an eco-friendly method. The results show that EPT can reduce the micropores and dislocation density in SLM-AlSi10Mg alloy. It makes the dislocation distribution more uniform, without causing obvious effects on the phase composition, grain morphology and size. Compared with the as-printed SLM-AlSi10Mg alloy samples, the elongation the EPTed specimen is increased by 23.9%, while the ultimate tensile strength is only slightly decreased (about 1.2%). The fatigue test results of ten as-printed and EPTed samples selected randomly reveal that the maximum fatigue life of the EPTed sample is not significantly improved, but the minimum fatigue life is improved by about 164.4%, the average fatigue life is improved by about 49.4%, and the standard deviation is reduced by about 34.8%, which means that the EPT reduces the dispersion of fatigue life and improves the service stability. Moreover, electrochemical measurements confirme that the EPTed sample has more positive open circuit potential, corrosion potential, and pitting potential, and smaller corrosion current than those of the as-printed sample, which indicates that EPT enhances the corrosion resistance of SLM-AlSi10Mg alloy. In this paper, the service performance of AlSi10Mg alloys prepared by a clean process (SLM) is improved via an eco-friendly post-treatment process (EPT), which provides a new light to about cleaner production of metal parts.

Deep learning-based vibration stress and fatigue-life prediction of a battery-pack system

The primary concerns of the automotive industry are structural integrity and battery-pack system (BPS) reliability. To ascertain the appropriate thickness of critical BPS components (e.g., the long bracket, crossbeam, and bottom shell), engineers are required to perform several simulations of finite element (FE) analysis. This procedure is laborious and requires a significant amount of time. This study introduces a very effective approach for predicting vibration-induced stress and fatigue life, intending to enhance dependability in the design process. Firstly, a three-layer lithium battery model is utilized to investigate the impact of vibration on the maximal Mises stress at various states of charge. This information is used to model the BPS, including the batteries. The nonlinear FE model of the BPS is validated using the modal test results. Secondly, a sensitivity analysis is performed to ascertain the impact of component thickness on the maximum Mises stress. For vibration simulations, multiple design variables are selected to collect data. Next, the nonlinear relationship between inputs (thicknesses of critical components) and outputs (maximum Mises stress and minimum fatigue life) is described using a deep learning (DL) modeling framework with forward and backward propagation. Finally, the accuracy of the DL model is assessed by measuring error functions and comparing its performance to six commonly employed methods. Furthermore, the inclusion of Gaussian noise is employed to assess the model’s robustness and ability to generalize. Additionally, the establishment of fatigue-life and stress boundaries serves to offer designers valuable insights. The results indicate that the proposed method for predicting vibration stress and fatigue life is highly efficient and cost-effective, making it useful for the design of a robust and reliable BPS.

Statistical evaluation of tubular joint SCFs from test data and finite element analyses

Stress concentration factors (SCF) derived from both FEA and measurements from laboratory experiments are associated with uncertainties. To understand these uncertainties, SCF values can be determined from a series of tests or possibly also several SCF-values estimated from converged finite element analysis. The challenge is to determine a recommended value for the SCF based on these tests or analysis, ensuring that the resulting SCF along with the SN-curve meets the code required 2.3% exceedance probability. In this paper, structural reliability analysis (SRA) methods are employed to model the combined uncertainty of the parameters representing the SN-curve and the measured SCFs from experimental test joints. Based on this analysis, the SCF that, when paired with the design SN-curve, provides the minimum fatigue life is established. From this analysis, a method to provide characteristic values of the SCF is suggested. Finally, FEA of the same detail, with and without modelling the weld, using both first and second-order elements are performed. From these analyses the SCF is estimated using linear extrapolation and direct extraction. Based on these findings and their comparison to the characteristic SCF, a suggested method to extract SCFs from FEA is provided.

Thermal stress simulation and fatigue life of commercial vehicle disk brakes under emergency braking conditions

Commercial vehicle disk brakes operate at a high-temperature and in a heavy-load environment within the braking system. The primary cause of failure is the cracking of the brake disk. In order to study its fatigue damage and service life, a finite element model of disk brake fatigue life was established, and thermal stress coupling simulation analysis was carried out from a practical problem. Based on the temperature and stress fields of the brake disk under emergency braking conditions obtained from the simulation results, the effects of vehicle load, initial speed, temperature, and other factors on brake fatigue life are explored. The fatigue life of the hazardous node can be calculated using the Manson–Coffin model, and then the strain–life (ɛ–N) curve of the material can be fit at high temperature. The fatigue life of brake disks was predicted using the fatigue analysis software FE-SAFE and verified by testing. The results showed that the maximum stress on the surface of the disk brake was the same as the area of the minimum fatigue life, accurately analyzing the fatigue life of the region and predicting the location of fatigue cracks. The results of the research can provide a reference for the design of disk brake engineering and fatigue failure.

Creep–Fatigue Life Estimation of Gr.91 Steel and Its Welded Joints

A series of creep–fatigue tests of Gr.91 steel were performed at 600 °C. Fatigue life was reduced by tensile strain holding. The minimum life reduction factor was approximately 0.3. The creep–fatigue life could not be estimated properly via the conventional linear summation rule of the fatigue damage and creep damage. Since this material is considered to have a large creep–fatigue interaction, it was proposed that the creep–fatigue life should be estimated using the improved linear summation rule of the fatigue damage, the creep damage and the creep–fatigue interaction damage. In the future, it will be necessary to clarify the creep–fatigue interaction mechanism and define its damage value. On the other hand, a series of creep–fatigue tests for Gr.91 steel welded joints were also performed in the strain range of 0.5% at 600 °C. Again, the fatigue life was shortened by the tensile strain holding. The minimum fatigue life reduction factor was approximately 0.2. All the test pieces fractured in the fine-grained HAZ of the welded joints. The creep–fatigue life could not be estimated properly using the linear summation rule of the fatigue damage and creep damage in the HAZ. One possible reason was thought to be the effects of the elastic follow-up phenomena peculiar to welded joints. The creep strain of the HAZ might increase due to the transfer of the elastic strain from both the base metal and the weld metal, according to the elastic follow-up phenomena during strain holding. In the future, it will be important to quantitatively estimate the effects of the elastic follow-up phenomena.

A rapid method to predict biaxial fatigue life of automotive wheels using proper orthogonal decomposition and radial basis function algorithm

This paper presents a rapid method for predicting the biaxial fatigue life of automotive wheels using a combination of proper orthogonal decomposition and radial basis function algorithm. Currently, numerical simulations of biaxial fatigue tests are being developed to evaluate wheel performance. However, these simulations are computationally expensive due to the need to simulate multiple discrete loading cases within a given biaxial spectrum. To address this issue, we propose a novel approach that utilizes proper orthogonal decomposition and radial basis function algorithm to improve computational efficiency. By leveraging high-fidelity simulation results from a small number of loading cases, a reduced order model is constructed to accurately predict the tire-rim interface force fields required for wheel strength calculations. The reduced order model significantly reduces the computational time by 65.4% for simulating all loading cases, while maintaining a maximum predicted error of less than 2% compared to the high-fidelity model. Subsequently, the predicted interface forces are mapped onto the rim surface for strength calculation, and the wheel fatigue life is determined using the Brown-Miller multiaxial damage criterion. Comparative analysis with experimental results demonstrates the desirable accuracy of our method in simulating the stress-strain history, crack initiation position, and minimum fatigue life of the wheel. Overall, the proposed method offers a powerful tool for the rapid fatigue analysis of spectrum-loaded wheels, providing an efficient and accurate means of predicting biaxial fatigue life.

Assessing tunnel basement structure damage under train excitation: Impacts of surrounding rock deterioration

On the ground of preliminary study of the Taihangshan Mountain Tunnel, it was observed that under the water-rich conditions, the long rolling of heavy-haul trains will deteriorate the surrounding rock, thereby causing damage to the bottom structure. Combined with data from long-term field monitoring and discrete element analysis, after clarifying the law of bedrock deterioration, the fuyingzi tunnel of Zhangtang railway in China is taken as the research object of fatigue damage. Ansys Workbench simulation software was used to further compare and analyze the influence of three characteristic deterioration stages of the surrounding rock on the basement structure damage. Based on the results, when the surrounding rock is intact, the basement structure gradually damages and expands from top to bottom, and the structural minimum fatigue life is approximately 76 years. When the surrounding rock is a partial cavity, the damage of the bottom structure intensifies and develops toward the surrounding rock deterioration position. The minimum fatigue life of the structure is 67 years, which decreases by 11.8%. When the surrounding rock is a cavity and connected, the damage of the bottom structure develops downward to a certain extent, which causes the structural damage at the deterioration position of the surrounding rock to develop in the opposite direction, i.e., from bottom to top. The structural minimum fatigue life is 42 years, which is reduced by 44.7% in the better situation.

An Energy-Based Anti-Fatigue Optimization Design Method of Welded Rear Axle Housing in a Mining Dump Truck

In order to improve the life expectancy of the rear axle housing in a mining dump truck, an energy-based anti-fatigue optimization design method was presented in this paper. The finite element model of rear axle housing was constructed and testified by the experimental data. The load history was obtained through multi-body dynamics analysis, and the multi-load step nonlinear finite element analysis was carried out to obtain the stress-strain response under different working conditions. The strain energy density method was used to evaluate the fatigue life of rear axle housing, and the results showed that its fatigue endurance was insufficient. Then, the lifetime of the most dangerous point was taken as the optimization objective, and the different plate thickness was considered as the design variables. The approximate model was constructed based on the response surface method, and the anti-fatigue optimization design was finally conducted on the bearing structure through the multi-island genetic algorithm. The minimum fatigue life of optimized rear axle housing was doubled.

Fatigue life evaluation of bridge stay cables subject to monitoring traffic and considering road roughness

Bridge stay cables are susceptible to fatigue damage caused by cyclic traffic loads. However, the effects of road roughness on fatigue assessment are often ignored, even though it is an essential factor that amplifies the response in vehicle–bridge interaction (VBI) systems. To address this gap, this study proposes a framework for cable fatigue assessment considering road roughness. The framework includes the VBI analysis method accounting for road roughness, the generation of random traffic flow, and the evaluation of cable fatigue. A case study based on a typical cable-stayed bridge is conducted. The results show that the proposed framework can effectively and feasibly evaluate cable fatigue. It is found that a poor road surface can reduce the fatigue life of cables, causing up to 4.47 times more damage compared to smooth road conditions. The decline of cable fatigue life caused by road roughness is primarily concentrated on the cables around the main towers, while the other cables are less affected by road roughness. Based on the measured traffic volume under poor road surface conditions, the estimated minimum fatigue life of the cable is 64 years. Moreover, the study indicates that cable fatigue damage rises with increasing traffic volume. These findings highlight the importance of considering road roughness and maintaining bridge decks to prevent the reduction of cable fatigue life.

Optimized membrane-type acoustic metamaterials for alleviating engineering fatigue damage via lightweight optimization

Currently, most acoustic metamaterials have been designed for ultra-thin sizes to achieve perfect and low-frequency sound absorption or insulation performance, with less attention paid to fatigue damage in practical engineering applications. In this study, a lightweight optimal design for the membrane-type acoustic metamaterial is proposed for alleviating fatigue damage. Normally, the elastic membrane was decorated with several metal platelets for tuning the natural frequencies in the membrane-type acoustic metamaterial. However, the sound waves may cause the fatigue damage to the membrane in the long-term engineering applications. The fatigue damage caused by sound can be significantly alleviated by the proposed lightweight optimization for the membrane-type acoustic metamaterial. To maintainthe low-frequency sound absorption performance while achieving the lightweight purpose, a multi-objective particle swarm optimization algorithm is applied to the lightweight optimization of the proposed structure. The fatigue simulation results showed that the corresponding minimum fatigue life is increased by 10.27% using the proposed lightweight approach. Furthermore, the experiments using the dual port measurement without backing were conducted to investigate sound absorption performance of the proposed structure before and after lightweight optimization. Both of theoretical and experimental results showed that the average sound absorption coefficients of the proposed structure after optimization are 41.6% and 22.2% larger than those before optimization, respectively. The total weight of the proposed structure after optimization is 25.9% lighter than that before optimization.

Deep-learning-based inverse structural design of a battery-pack system

Along with the continuous progress of lithium-ion batteries and the automotive industry, the safety of battery-pack systems (BPSs) is gradually becoming a hot topic of concern for consumers. A number of studies have been conducted on the safety performance of BPSs from various perspectives, with the aim of designing safer and more reliable BPSs. Designing a BPS is time-consuming because it contains numerous components and is located in a complex area. Researchers must conduct extensive finite element analysis (FEA) to select the right thickness of BPS components for a safe pack system. This process is tedious, and the historical data from FEA needs to be fully utilized. This work proposes an inverse prediction method for the BPS design for enhanced reliability. This method combines FEA historical data and a deep neural network (DNN) framework to predict the thickness of components, realizing robust BPS structural design. First, an FE model of a detailed BPS is built, the FEA under vibration conditions is completed, and the basic data for building the DNN model is acquired. Next, a DNN modeling framework, including forward and backward propagations, is developed to train the historical data. A DNN model that can describe the non-linear relationship between the inputs (the three main stresses and the minimum fatigue life) and the outputs (thicknesses of critical components) is obtained. Finally, the accuracy of the DNN model is investigated in terms of error functions, and the prediction accuracy of DNN models with different numbers of hidden layers is compared. The results show that the DNN model can accurately predict the component thickness of the BPS. In addition, a third-order response surface model and a radial basis function neural network model are used for comparison and verification. The prediction accuracy of DNN models built with different amounts of data, training epochs, and Gaussian noise is also compared. A case of structural optimization is given to provide designers with ideas. The proposed inverse prediction method can lead to economical and efficient design process. It can shorten the development cycle and reduce the cost of the BPS.

Study on fatigue life of gun latch based on orthogonal test method

Aiming at the problem of fatigue damage of gun latch caused by long-term impact load, the fatigue life of gun latch was studied. Firstly, the finite element model of gun latch was established by using finite element method. Secondly, the static strength and fatigue life of the gun latch were calculated based on S-N curve and Miner’s linear damage accumulation theory. On this basis, the structural factors affecting the fatigue life of the bolt were analyzed, and four factors including the radial diameter of the latch, the axial bearing thickness of the latch, the spiral Angle of the latch support surface and the gun tail support surface, and the locking clearance between the bolt and the gun tail were set up, as well as three variation levels of each factor. Then, the fatigue life of nine groups of gun latches was simulated by orthogonal test method. In addition, the range analysis method was used to analyze the simulation results, and then the influence law and degree of each factor on the fatigue life of gun latch were obtained. Moreover, the optimal combination scheme of the structure parameters of the gun latch was determined by the comprehensive balance method, and then the finite element simulation was carried out to verify the structure of the gun latch. The results show that the maximum stress of the bolt decreases 21.5% and the maximum stress of the gun tail decreases 28.2%, and the maximum stress of the gun bolt is lower than the yield limit of the material. At the same time, the research also shows that the minimum fatigue life of the bolt increases greatly, the minimum fatigue life of the bolt body is 20.8 times of that before the test, and the minimum fatigue life of the gun tail is 102.1 times of that before the test. The results provide a reference for fatigue life analysis and structural design of gun latch.