This paper introduces a hybrid multi-objective optimization algorithm,designated HMODESFO,which amalgamates the exploratory prowess of Differential Evolution(DE)with the rapid convergence attributes of the Sailfish Op...This paper introduces a hybrid multi-objective optimization algorithm,designated HMODESFO,which amalgamates the exploratory prowess of Differential Evolution(DE)with the rapid convergence attributes of the Sailfish Optimization(SFO)algorithm.The primary objective is to address multi-objective optimization challenges within mechanical engineering,with a specific emphasis on planetary gearbox optimization.The algorithm is equipped with the ability to dynamically select the optimal mutation operator,contingent upon an adaptive normalized population spacing parameter.The efficacy of HMODESFO has been substantiated through rigorous validation against estab-lished industry benchmarks,including a suite of Zitzler-Deb-Thiele(ZDT)and Zeb-Thiele-Laumanns-Zitzler(DTLZ)problems,where it exhibited superior performance.The outcomes underscore the algorithm’s markedly enhanced optimization capabilities relative to existing methods,particularly in tackling highly intricate multi-objective planetary gearbox optimization problems.Additionally,the performance of HMODESFO is evaluated against selected well-known mechanical engineering test problems,further accentuating its adeptness in resolving complex optimization challenges within this domain.展开更多
Meshing temperature analyses of polymer gears reported in the literature mainly concern the effects of various material combinations and loading conditions,as their impacts could be seen in the first few meshing cycle...Meshing temperature analyses of polymer gears reported in the literature mainly concern the effects of various material combinations and loading conditions,as their impacts could be seen in the first few meshing cycles.However,the effects of tooth geometry parameters could manifest as the meshing cycles increase.This study investigated the effects of tooth geometry parameters on the multi-cycle meshing temperature of polyoxymethylene(POM)worm gears,aiming to control the meshing temperature elevation by tuning the tooth geometry.Firstly,a finite element(FE)model capable of separately calculating the heat generation and simulating the heat propagation was established.Moreover,an adaptive iteration algorithm was proposed within the FE framework to capture the influence of the heat generation variation from cycle to cycle.This algorithm proved to be feasible and highly efficient compared with experimental results from the literature and simulated results via the full-iteration algorithm.Multi-cycle meshing temperature analyses were conducted on a series of POM worm gears with different tooth geometry parameters.The results reveal that,within the range of 14.5°to 25°,a pressure angle of 25°is favorable for reducing the peak surface temperature and overall body temperature of POM worm gears,which influence flank wear and load-carrying capability,respectively.However,addendum modification should be weighed because it helps with load bearing but increases the risk of severe flank wear.This paper proposes an efficient iteration algorithm for multi-cycle meshing temperature analysis of polymer gears and proves the feasibility of controlling the meshing temperature elevation during multiple cycles by tuning tooth geometry.展开更多
The gear transmission system has been widely applied in mechanical systems,and many high-performance applications of these systems require low weight.With the aid of establishing the optimization model of the gear tra...The gear transmission system has been widely applied in mechanical systems,and many high-performance applications of these systems require low weight.With the aid of establishing the optimization model of the gear transmission system that consists of an objective function and some constraints(for example,the bending stress,the contact stress,the torsional strength,etc.),the optimal weight design of the gear transmission system can be transformed into the optimization problem for the objective function under the constraints.Moreover,both the shaft and the gear of the gear transmission system are considered simultaneously in our design.The hybrid Taguchi-genetic algorithm(HTGA)is employed to find the optimal design variables and the optimal weight of the system.An illustrated example for the single spur gear reducer is given to show that the optimal weight design problem can be successfully solved using the proposed design scheme.It also proves the high efficiency and feasibility of the algorithm in the gear design.展开更多
The wear rate between the rotors of a hypotrochoidal gear pump is characterized.Using the knowledge of shape design on the rotors,the contact stresses without hydrodynamic effect between the rotor teeth were evaluated...The wear rate between the rotors of a hypotrochoidal gear pump is characterized.Using the knowledge of shape design on the rotors,the contact stresses without hydrodynamic effect between the rotor teeth were evaluated through the calculation of the Hertzian contact stress.Based on the above results and the sliding velocity between the rotors,a genetic algorithm (GA) was used as an optimization technique forminimizing the wear rate proportional factor (WRPF).The result shows that the wear rate or the WRPF can be reduced considerably,e.g.approximately 12.8%,throughout the optimization using GA.展开更多
Planetary gear train is a prominent component of helicopter transmission system and its health is of great significance for the flight safety of the helicopter.During health condition monitoring,the selection of a fau...Planetary gear train is a prominent component of helicopter transmission system and its health is of great significance for the flight safety of the helicopter.During health condition monitoring,the selection of a fault sensitive feature subset is meaningful for fault diagnosis of helicopter planetary gear train.According to actual situation,this paper proposed a multi-criteria fusion feature selection algorithm (MCFFSA) to identify an optimal feature subset from the highdimensional original feature space.In MCFFSA,a fault feature set of multiple domains,including time domain,frequency domain and wavelet domain,is first extracted from the raw vibration dataset.Four targeted criteria are then fused by multi-objective evolutionary algorithm based on decomposition (MOEA/D) to find Proto-efficient subsets,wherein two criteria for measuring diagnostic performance are assessed by sparse Bayesian extreme learning machine (SBELM).Further,Fmeasure is adopted to identify the optimal feature subset,which was employed for subsequent fault diagnosis.The effectiveness of MCFFSA is validated through six fault recognition datasets from a real helicopter transmission platform.The experimental results illustrate the superiority of combination of MOEA/D and SBELM in MCFFSA,and comparative analysis demonstrates that the optimal feature subset provided by MCFFSA can achieve a better diagnosis performance than other algorithms.展开更多
To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise mode...To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise modeling strategy,cell array operation principle,and Copula theory.Under this framework,we propose a DSM-based Enhanced Kriging(DSMEK)algorithm to synchronously derive the modeling of multi-objective,and explore an adaptive Copula function approach to analyze the correlation among multiple objectives and to assess the synthetical reliability level.In the proposed DSMEK and adaptive Copula methods,the Kriging model is treated as the basis function of DSMEK model,the Multi-Objective Snake Optimizer(MOSO)algorithm is used to search the optimal values of hyperparameters of basis functions,the cell array operation principle is adopted to establish a whole model of multiple objectives,the goodness of fit is utilized to determine the forms of Copula functions,and the determined Copula functions are employed to perform the reliability analyses of the correlation of multi-analytical objectives.Furthermore,three examples,including multi-objective complex function approximation,aeroengine turbine bladeddisc multi-failure mode reliability analyses and aircraft landing gear system brake temperature reliability analyses,are performed to verify the effectiveness of the proposed methods,from the viewpoints of mathematics and engineering.The results show that the DSMEK and adaptive Copula approaches hold obvious advantages in terms of modeling features and simulation performance.The efforts of this work provide a useful way for the modeling of multi-analytical objectives and synthetical reliability analyses of complex structure/system with multi-output responses.展开更多
At present,the active control of gear vibration mostly relies on existing algorithms.In order to achieve effective vibration reduction of the gear system,particularly during the vibration process,this paper proposes a...At present,the active control of gear vibration mostly relies on existing algorithms.In order to achieve effective vibration reduction of the gear system,particularly during the vibration process,this paper proposes a multi-channel VSMFxLMS algorithm based on the FxLMS algorithm.This novel approach takes into account the time-varying nature of the vibration signal during gear vibration.Adaptive filter power coefficients are updated in a skip-tongue variable-step manner using momentum factors.Firstly,the paper establishes the dynamics model of the gear system and analyzes the nonlinear dynamic characteristics of the system.It then examines the vibration damping effect of the FxLMS algorithm and analyzes its performance under different gear system motion states,considering different step lengths and momentum factors.Lastly,the proposed VSMFxLMS algorithm is compared with the FxLMS algorithm,highlighting the superiority of the former.Overall,this research highlights the potential of a multi-channel VSMFxLMS algorithm in reducing vibrations in gear systems.The study optimizes the performance of gear systems while using advanced control strategies.展开更多
The computational accuracy and efficiency of modeling the stress spectrum derived from bridge monitoring data significantly influence the fatigue life assessment of steel bridges.Therefore,determining the optimal stre...The computational accuracy and efficiency of modeling the stress spectrum derived from bridge monitoring data significantly influence the fatigue life assessment of steel bridges.Therefore,determining the optimal stress spectrum model is crucial for further fatigue reliability analysis.This study investigates the performance of the REBMIX algorithm in modeling both univariate(stress range)and multivariate(stress range and mean stress)distributions of the rain-flowmatrix for a steel arch bridge,usingAkaike’s Information Criterion(AIC)as a performance metric.Four types of finitemixture distributions—Normal,Lognormal,Weibull,and Gamma—are employed tomodel the stress range.Additionally,mixed distributions,including Normal-Normal,Lognormal-Normal,Weibull-Normal,and Gamma-Normal,are utilized to model the joint distribution of stress range and mean stress.The REBMIX algorithm estimates the number of components,component weights,and component parameters for each candidate finite mixture distribution.The results demonstrate that the REBMIX algorithm-based mixture parameter estimation approach effectively identifies the optimal distribution based on AIC values.Furthermore,the algorithm exhibits superior computational efficiency compared to traditional methods,making it highly suitable for practical applications.展开更多
The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimiz...The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.展开更多
With the method of group test, fourty pairs of carburization-quenching gears made from 16NCD13 steel for aerocraft were tested to research the contacting fatigue strength on tooth flank. As a result, the samples of fa...With the method of group test, fourty pairs of carburization-quenching gears made from 16NCD13 steel for aerocraft were tested to research the contacting fatigue strength on tooth flank. As a result, the samples of fatigue life at the moments when the pitting appears and reaches failure criterion were obtained at four stressing levels respectively. The distribution rule of fatigue life were distinguished, and the distribution parameters were estimated by statistical analysis. Based on that, the R-S-N curves with confidence 95% of contacting fatigue on gear tooth flank were evaluated. Therefore, the basic data were provided for the reliability design of the gears and prediction of their life.展开更多
The composite leaf spring landing gear of an electric aircraft is optimized.With the strength and workability as constraints and the minimum structural weight as an objective,the two-stage optimization of the leaf spr...The composite leaf spring landing gear of an electric aircraft is optimized.With the strength and workability as constraints and the minimum structural weight as an objective,the two-stage optimization of the leaf spring landing gear with glass fiber unidirectional prepreg is carried out using a genetic algorithm,namely,the optimization of continuous thickness of layup,and the optimization of the layup sequence and discrete thickness.In the optimization process,the ground loads are calculated according to the structural stiffness of each chromosome,thus the stiffness constraints are relaxed,and the optimization results are compared with those using stiffness constraints.The static experiment verification reveals that the numerical simulation and experimental results are consistent,that is,the optimized leaf spring meets the strength requirements.The results show that the leaf spring landing gear based on two-stage optimization method achieves the objective of weight reduction.展开更多
Smooth constraint is important in linear inversion, but it is difficult to apply directly to model parameters in genetic algorithms. If the model parameters are smoothed in iteration, the diversity of models will be g...Smooth constraint is important in linear inversion, but it is difficult to apply directly to model parameters in genetic algorithms. If the model parameters are smoothed in iteration, the diversity of models will be greatly suppressed and all the models in population will tend to equal in a few iterations, so the optimal solution meeting requirement can not be obtained. In this paper, an indirect smooth constraint technique is introduced to genetic inversion. In this method, the new models produced in iteration are smoothed, then used as theoretical models in calculation of misfit function, but in process of iteration only the original models are used in order to keep the diversity of models. The technique is effective in inversion of surface wave and receiver function. Using this technique, we invert the phase velocity of Raleigh wave in the Tibetan Plateau, revealing the horizontal variation of S wave velocity structure near the center of the Tibetan Plateau. The results show that the S wave velocity in the north is relatively lower than that in the south. For most paths there is a lower velocity zone with 12-25 km thick at the depth of 15-40 km. The lower velocity zone in upper mantle is located below the depth of 100 km, and the thickness is usually 40-80 km, but for a few paths reach to 100 km thick. Among the area of Ando, Maqi and Ushu stations, there is an obvious lower velocity zone with the lowest velocity of 4.2-4.3 km/s at the depth of 90-230 km. Based on the S wave velocity structures of different paths and former data, we infer that the subduction of the Indian Plate is delimited nearby the Yarlung Zangbo suture zone.展开更多
In this work,synchronous cutting of concave and convex surfaces was achieved using the duplex helical method for the hypoid gear,and the problem of tooth surface error correction was studied.First,the mathematical mod...In this work,synchronous cutting of concave and convex surfaces was achieved using the duplex helical method for the hypoid gear,and the problem of tooth surface error correction was studied.First,the mathematical model of the hypoid gears machined by the duplex helical method was established.Second,the coordinates of discrete points on the tooth surface were obtained by measurement center,and the normal errors of the discrete points were calculated.Third,a tooth surface error correction model is established,and the tooth surface error was corrected using the Levenberg-Marquard algorithm with trust region strategy and least square method.Finally,grinding experiments were carried out on the machining parameters obtained by Levenberg-Marquard algorithm with trust region strategy,which had a better effect on tooth surface error correction than the least square method.After the tooth surface error is corrected,the maximum absolute error is reduced from 30.9μm before correction to 6.8μm,the root mean square of the concave error is reduced from 15.1 to 2.1μm,the root mean square of the convex error is reduced from 10.8 to 1.8μm,and the sum of squared errors of the concave and convex surfaces was reduced from 15471 to 358μm^(2).It is verified that the Levenberg-Marquard algorithm with trust region strategy has a good accuracy for the tooth surface error correction of hypoid gear machined by duplex helical method.展开更多
Semi-active landing gear can provide good performance of both landing impact and taxi situation,and has the ability for adapting to various ground conditions and operational conditions.A kind of Nonlinear Model Predic...Semi-active landing gear can provide good performance of both landing impact and taxi situation,and has the ability for adapting to various ground conditions and operational conditions.A kind of Nonlinear Model Predictive Control algorithm(NMPC)for semi-active landing gears is developed in this paper.The NMPC algorithm uses Genetic Algorithm(GA)as the optimization technique and chooses damping performance of landing gear at touch down to be the optimization object.The valve's rate and magnitude limitations are also considered in the controller's design.A simulation model is built for the semi-active landing gear's damping process at touchdown.Drop tests are carried out on an experimental passive landing gear systerm to validate the parameters of the simulation model.The result of numerical simulation shows that the isolation of impact load at touchdown can be significantly improved compared to other control algorithms.The strongly nonlinear dynamics of semi-active landing gear coupled with control valve's rate and magnitude limitations are handled well with the proposed controller.展开更多
基金supported by the Serbian Ministry of Education and Science under Grant No.TR35006 and COST Action:CA23155—A Pan-European Network of Ocean Tribology(OTC)The research of B.Rosic and M.Rosic was supported by the Serbian Ministry of Education and Science under Grant TR35029.
文摘This paper introduces a hybrid multi-objective optimization algorithm,designated HMODESFO,which amalgamates the exploratory prowess of Differential Evolution(DE)with the rapid convergence attributes of the Sailfish Optimization(SFO)algorithm.The primary objective is to address multi-objective optimization challenges within mechanical engineering,with a specific emphasis on planetary gearbox optimization.The algorithm is equipped with the ability to dynamically select the optimal mutation operator,contingent upon an adaptive normalized population spacing parameter.The efficacy of HMODESFO has been substantiated through rigorous validation against estab-lished industry benchmarks,including a suite of Zitzler-Deb-Thiele(ZDT)and Zeb-Thiele-Laumanns-Zitzler(DTLZ)problems,where it exhibited superior performance.The outcomes underscore the algorithm’s markedly enhanced optimization capabilities relative to existing methods,particularly in tackling highly intricate multi-objective planetary gearbox optimization problems.Additionally,the performance of HMODESFO is evaluated against selected well-known mechanical engineering test problems,further accentuating its adeptness in resolving complex optimization challenges within this domain.
基金Supported by National Key R&D Program of China(Grant No.2019YFE0121300)。
文摘Meshing temperature analyses of polymer gears reported in the literature mainly concern the effects of various material combinations and loading conditions,as their impacts could be seen in the first few meshing cycles.However,the effects of tooth geometry parameters could manifest as the meshing cycles increase.This study investigated the effects of tooth geometry parameters on the multi-cycle meshing temperature of polyoxymethylene(POM)worm gears,aiming to control the meshing temperature elevation by tuning the tooth geometry.Firstly,a finite element(FE)model capable of separately calculating the heat generation and simulating the heat propagation was established.Moreover,an adaptive iteration algorithm was proposed within the FE framework to capture the influence of the heat generation variation from cycle to cycle.This algorithm proved to be feasible and highly efficient compared with experimental results from the literature and simulated results via the full-iteration algorithm.Multi-cycle meshing temperature analyses were conducted on a series of POM worm gears with different tooth geometry parameters.The results reveal that,within the range of 14.5°to 25°,a pressure angle of 25°is favorable for reducing the peak surface temperature and overall body temperature of POM worm gears,which influence flank wear and load-carrying capability,respectively.However,addendum modification should be weighed because it helps with load bearing but increases the risk of severe flank wear.This paper proposes an efficient iteration algorithm for multi-cycle meshing temperature analysis of polymer gears and proves the feasibility of controlling the meshing temperature elevation during multiple cycles by tuning tooth geometry.
基金Supported by the Fundamental Research Funds for the Central Universities(20102080201000085)the National Natural Science Foundation of China(50875189)
文摘The gear transmission system has been widely applied in mechanical systems,and many high-performance applications of these systems require low weight.With the aid of establishing the optimization model of the gear transmission system that consists of an objective function and some constraints(for example,the bending stress,the contact stress,the torsional strength,etc.),the optimal weight design of the gear transmission system can be transformed into the optimization problem for the objective function under the constraints.Moreover,both the shaft and the gear of the gear transmission system are considered simultaneously in our design.The hybrid Taguchi-genetic algorithm(HTGA)is employed to find the optimal design variables and the optimal weight of the system.An illustrated example for the single spur gear reducer is given to show that the optimal weight design problem can be successfully solved using the proposed design scheme.It also proves the high efficiency and feasibility of the algorithm in the gear design.
基金supported by Changwon National University in 2010,Korea
文摘The wear rate between the rotors of a hypotrochoidal gear pump is characterized.Using the knowledge of shape design on the rotors,the contact stresses without hydrodynamic effect between the rotor teeth were evaluated through the calculation of the Hertzian contact stress.Based on the above results and the sliding velocity between the rotors,a genetic algorithm (GA) was used as an optimization technique forminimizing the wear rate proportional factor (WRPF).The result shows that the wear rate or the WRPF can be reduced considerably,e.g.approximately 12.8%,throughout the optimization using GA.
基金co-supported by the Equipment Pre-research Foundation Project of China (No. JZX7Y20190243016301)Helicopter Transmission Technology Key Laboratory Foundation of China (No. KY-52-2018-0024)the Fundamental Research Funds for the Central Universities & Funding of Jiangsu Innovation Program for Graduate Education under Grant (No. KYLX16_0336)
文摘Planetary gear train is a prominent component of helicopter transmission system and its health is of great significance for the flight safety of the helicopter.During health condition monitoring,the selection of a fault sensitive feature subset is meaningful for fault diagnosis of helicopter planetary gear train.According to actual situation,this paper proposed a multi-criteria fusion feature selection algorithm (MCFFSA) to identify an optimal feature subset from the highdimensional original feature space.In MCFFSA,a fault feature set of multiple domains,including time domain,frequency domain and wavelet domain,is first extracted from the raw vibration dataset.Four targeted criteria are then fused by multi-objective evolutionary algorithm based on decomposition (MOEA/D) to find Proto-efficient subsets,wherein two criteria for measuring diagnostic performance are assessed by sparse Bayesian extreme learning machine (SBELM).Further,Fmeasure is adopted to identify the optimal feature subset,which was employed for subsequent fault diagnosis.The effectiveness of MCFFSA is validated through six fault recognition datasets from a real helicopter transmission platform.The experimental results illustrate the superiority of combination of MOEA/D and SBELM in MCFFSA,and comparative analysis demonstrates that the optimal feature subset provided by MCFFSA can achieve a better diagnosis performance than other algorithms.
基金co-supported by the National Natural Science Foundation of China(Nos.52405293,52375237)China Postdoctoral Science Foundation(No.2024M754219)Shaanxi Province Postdoctoral Research Project Funding,China。
文摘To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise modeling strategy,cell array operation principle,and Copula theory.Under this framework,we propose a DSM-based Enhanced Kriging(DSMEK)algorithm to synchronously derive the modeling of multi-objective,and explore an adaptive Copula function approach to analyze the correlation among multiple objectives and to assess the synthetical reliability level.In the proposed DSMEK and adaptive Copula methods,the Kriging model is treated as the basis function of DSMEK model,the Multi-Objective Snake Optimizer(MOSO)algorithm is used to search the optimal values of hyperparameters of basis functions,the cell array operation principle is adopted to establish a whole model of multiple objectives,the goodness of fit is utilized to determine the forms of Copula functions,and the determined Copula functions are employed to perform the reliability analyses of the correlation of multi-analytical objectives.Furthermore,three examples,including multi-objective complex function approximation,aeroengine turbine bladeddisc multi-failure mode reliability analyses and aircraft landing gear system brake temperature reliability analyses,are performed to verify the effectiveness of the proposed methods,from the viewpoints of mathematics and engineering.The results show that the DSMEK and adaptive Copula approaches hold obvious advantages in terms of modeling features and simulation performance.The efforts of this work provide a useful way for the modeling of multi-analytical objectives and synthetical reliability analyses of complex structure/system with multi-output responses.
基金Supported by Sichuan Provincial Science and Technology Program(Grant No.2024NSFSC0902)National Natural Science Foundation of China(Grant Nos.52405254,52105108,52375039)+1 种基金the Young Elite Scientists Sponsorship Program by CAST(Grant No.2023QNRC001)Hebei Provincial Natural Science Foundation(Grant No.E2023105039).
文摘At present,the active control of gear vibration mostly relies on existing algorithms.In order to achieve effective vibration reduction of the gear system,particularly during the vibration process,this paper proposes a multi-channel VSMFxLMS algorithm based on the FxLMS algorithm.This novel approach takes into account the time-varying nature of the vibration signal during gear vibration.Adaptive filter power coefficients are updated in a skip-tongue variable-step manner using momentum factors.Firstly,the paper establishes the dynamics model of the gear system and analyzes the nonlinear dynamic characteristics of the system.It then examines the vibration damping effect of the FxLMS algorithm and analyzes its performance under different gear system motion states,considering different step lengths and momentum factors.Lastly,the proposed VSMFxLMS algorithm is compared with the FxLMS algorithm,highlighting the superiority of the former.Overall,this research highlights the potential of a multi-channel VSMFxLMS algorithm in reducing vibrations in gear systems.The study optimizes the performance of gear systems while using advanced control strategies.
基金jointly supported by the Fundamental Research Funds for the Central Universities(Grant No.xzy012023075)the Zhejiang Engineering Research Center of Intelligent Urban Infrastructure(Grant No.IUI2023-YB-12).
文摘The computational accuracy and efficiency of modeling the stress spectrum derived from bridge monitoring data significantly influence the fatigue life assessment of steel bridges.Therefore,determining the optimal stress spectrum model is crucial for further fatigue reliability analysis.This study investigates the performance of the REBMIX algorithm in modeling both univariate(stress range)and multivariate(stress range and mean stress)distributions of the rain-flowmatrix for a steel arch bridge,usingAkaike’s Information Criterion(AIC)as a performance metric.Four types of finitemixture distributions—Normal,Lognormal,Weibull,and Gamma—are employed tomodel the stress range.Additionally,mixed distributions,including Normal-Normal,Lognormal-Normal,Weibull-Normal,and Gamma-Normal,are utilized to model the joint distribution of stress range and mean stress.The REBMIX algorithm estimates the number of components,component weights,and component parameters for each candidate finite mixture distribution.The results demonstrate that the REBMIX algorithm-based mixture parameter estimation approach effectively identifies the optimal distribution based on AIC values.Furthermore,the algorithm exhibits superior computational efficiency compared to traditional methods,making it highly suitable for practical applications.
基金partially supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI(JP23K24899)Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)(JPMJSP2145).
文摘The modeling and optimization of wind farm layouts can effectively reduce the wake effect between turbine units,thereby enhancing the expected output power and avoiding negative influence.Traditional wind farm optimization often uses idealized wake models,neglecting the influence of wind shear at different elevations,which leads to a lack of precision in estimating wake effects and fails to meet the accuracy and reliability requirements of practical engineering.To address this,we have constructed a three-dimensional 3D wind farm optimization model that incorporates elevation,utilizing a 3D wake model to better reflect real-world conditions.We aim to assess the optimization state of the algorithm and provide strong incentives at the right moments to ensure continuous evolution of the population.To this end,we propose an evolutionary adaptation degreeguided genetic algorithm based on power-law perturbation(PPGA)to adapt multidimensional conditions.We select the offshore wind power project in Nantong,Jiangsu,China,as a study example and compare PPGA with other well-performing algorithms under this practical project.Based on the actual wind condition data,the experimental results demonstrate that PPGA can effectively tackle this complex problem and achieve the best power efficiency.
文摘With the method of group test, fourty pairs of carburization-quenching gears made from 16NCD13 steel for aerocraft were tested to research the contacting fatigue strength on tooth flank. As a result, the samples of fatigue life at the moments when the pitting appears and reaches failure criterion were obtained at four stressing levels respectively. The distribution rule of fatigue life were distinguished, and the distribution parameters were estimated by statistical analysis. Based on that, the R-S-N curves with confidence 95% of contacting fatigue on gear tooth flank were evaluated. Therefore, the basic data were provided for the reliability design of the gears and prediction of their life.
基金the Natural Science Foundation of Liaoning (No. 20180550824)。
文摘The composite leaf spring landing gear of an electric aircraft is optimized.With the strength and workability as constraints and the minimum structural weight as an objective,the two-stage optimization of the leaf spring landing gear with glass fiber unidirectional prepreg is carried out using a genetic algorithm,namely,the optimization of continuous thickness of layup,and the optimization of the layup sequence and discrete thickness.In the optimization process,the ground loads are calculated according to the structural stiffness of each chromosome,thus the stiffness constraints are relaxed,and the optimization results are compared with those using stiffness constraints.The static experiment verification reveals that the numerical simulation and experimental results are consistent,that is,the optimized leaf spring meets the strength requirements.The results show that the leaf spring landing gear based on two-stage optimization method achieves the objective of weight reduction.
基金State Natural Science Foundation (49874021).Contribution No. 01FE2002, Institute of Geophysics, China Seismological Bureau.
文摘Smooth constraint is important in linear inversion, but it is difficult to apply directly to model parameters in genetic algorithms. If the model parameters are smoothed in iteration, the diversity of models will be greatly suppressed and all the models in population will tend to equal in a few iterations, so the optimal solution meeting requirement can not be obtained. In this paper, an indirect smooth constraint technique is introduced to genetic inversion. In this method, the new models produced in iteration are smoothed, then used as theoretical models in calculation of misfit function, but in process of iteration only the original models are used in order to keep the diversity of models. The technique is effective in inversion of surface wave and receiver function. Using this technique, we invert the phase velocity of Raleigh wave in the Tibetan Plateau, revealing the horizontal variation of S wave velocity structure near the center of the Tibetan Plateau. The results show that the S wave velocity in the north is relatively lower than that in the south. For most paths there is a lower velocity zone with 12-25 km thick at the depth of 15-40 km. The lower velocity zone in upper mantle is located below the depth of 100 km, and the thickness is usually 40-80 km, but for a few paths reach to 100 km thick. Among the area of Ando, Maqi and Ushu stations, there is an obvious lower velocity zone with the lowest velocity of 4.2-4.3 km/s at the depth of 90-230 km. Based on the S wave velocity structures of different paths and former data, we infer that the subduction of the Indian Plate is delimited nearby the Yarlung Zangbo suture zone.
基金Projects(52075552,51575533,51805555,11662004)supported by the National Natural Science Foundation of China。
文摘In this work,synchronous cutting of concave and convex surfaces was achieved using the duplex helical method for the hypoid gear,and the problem of tooth surface error correction was studied.First,the mathematical model of the hypoid gears machined by the duplex helical method was established.Second,the coordinates of discrete points on the tooth surface were obtained by measurement center,and the normal errors of the discrete points were calculated.Third,a tooth surface error correction model is established,and the tooth surface error was corrected using the Levenberg-Marquard algorithm with trust region strategy and least square method.Finally,grinding experiments were carried out on the machining parameters obtained by Levenberg-Marquard algorithm with trust region strategy,which had a better effect on tooth surface error correction than the least square method.After the tooth surface error is corrected,the maximum absolute error is reduced from 30.9μm before correction to 6.8μm,the root mean square of the concave error is reduced from 15.1 to 2.1μm,the root mean square of the convex error is reduced from 10.8 to 1.8μm,and the sum of squared errors of the concave and convex surfaces was reduced from 15471 to 358μm^(2).It is verified that the Levenberg-Marquard algorithm with trust region strategy has a good accuracy for the tooth surface error correction of hypoid gear machined by duplex helical method.
基金Aeronautical Science Foundation of China(98B52023),(04B52012)
文摘Semi-active landing gear can provide good performance of both landing impact and taxi situation,and has the ability for adapting to various ground conditions and operational conditions.A kind of Nonlinear Model Predictive Control algorithm(NMPC)for semi-active landing gears is developed in this paper.The NMPC algorithm uses Genetic Algorithm(GA)as the optimization technique and chooses damping performance of landing gear at touch down to be the optimization object.The valve's rate and magnitude limitations are also considered in the controller's design.A simulation model is built for the semi-active landing gear's damping process at touchdown.Drop tests are carried out on an experimental passive landing gear systerm to validate the parameters of the simulation model.The result of numerical simulation shows that the isolation of impact load at touchdown can be significantly improved compared to other control algorithms.The strongly nonlinear dynamics of semi-active landing gear coupled with control valve's rate and magnitude limitations are handled well with the proposed controller.
