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Study of the mechanical properties of articular chondrocytes undergoing large deformations via the inverse finite element method combined with numerical optimization 认领 引用
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作者 Yongsheng Li Quanyou Zhang +2 位作者 Dan Zhao Jing Chen Weiyi Chen 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第7期571-583,共13页
The mechanical properties of chondrocytes are closely related to the onset and progression of osteoarthritis;however,current research on the mechanical behavior of chondrocytes undergoing large deformations is insuffi... The mechanical properties of chondrocytes are closely related to the onset and progression of osteoarthritis;however,current research on the mechanical behavior of chondrocytes undergoing large deformations is insufficient.In this work,via micropipette aspiration(MPA)and atomic force microscopy(AFM)experiments on chondrocytes,finite element simulations combined with numerical optimization were conducted to obtain the mechanical parameters of three viscohyperelastic models(neo-Hookean(NH),Mooney-Rivlin(MR),and Arruda-Boyce(AB)).The results showed that for the elastic responses of chondrocytes,all three models can capture the mechanical behaviors of cells with good accuracy for both the MPA and AFM experiments,among which the AB model had the best fit.In terms of the viscoelastic behavior of chondrocytes,the single-term Prony series of the three models can describe the creep response of the MPA experiment well,whereas for the pressure relaxation behavior of the AFM experiment,the fitting degree of the single-term Prony series of the three models was low.However,the prediction ability can be significantly improved by using the two-term Prony series,for both the MPA and the AFM experiments,the AB model still yielded the best prediction of viscoelastic responses.Thus,compared with the NH and MR models,the AB model is more suitable for characterizing the elastic and viscoelastic mechanical responses of chondrocytes undergoing large deformations.This study provides an alternative methodology for investigating the large deformation mechanical properties of chondrocytes,which may help to further study and reveal the mechanotransduction mechanisms of chondrocytes. 展开更多
关键词 Chondrocytes Large deformation Finite element simulation Mechanical properties Numerical optimization
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The Optimization Design of Particle-Reinforced Composite Materials Based on the Artificial Fish Swarm Algorithm and Voronoi Cell Finite Element Method 认领 引用
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作者 Peng Zhang Ran Guo 《Acta Mechanica Solida Sinica》 SCIE EI CSCD 2026年第3期316-328,共13页
In this study,a collaborative optimization framework combining artificial fish swarm algorithm(AFSA)and Voronoi cell finite element method(VCFEM)is proposed to solve the problem of the influence of microstructure dist... In this study,a collaborative optimization framework combining artificial fish swarm algorithm(AFSA)and Voronoi cell finite element method(VCFEM)is proposed to solve the problem of the influence of microstructure distribution on the macroscopic mechanical properties of particle-reinforced composites.Compared with the traditional displacement-based finite element method,VCFEM significantly improves the computational efficiency of multi-inclusion problems by means of generalized stress function and element local adaptation technology,and accurately captures the stress field discontinuity and interface stress concentration phenomenon.At the same time,AFSA abandons the dependence of traditional optimization methods on simplified models,and directly searches for the global optimal solution through discrete topological variables(particle positions).Its natural selection mechanism and swarm intelligence characteristics effectively overcome the local optimal trap.The numerical simulation results show that the proposed method exhibits high accuracy in both single-and multi-inclusion models(the error with the commercial software MARC is less than 5%),and in the complex model with 100 inclusions,the maximum Mises stress is reduced by 32.6%after optimization.The synergistic effect of the two breaks through the trade-off between efficiency and accuracy in traditional optimization,and provides the ability of both computational efficiency and global optimization for multi-scale composite material design. 展开更多
关键词 Particle-reinforced composites Artificial fish swarm algorithm Voronoi cell finite element method Optimization algorithms
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Sintering bed state optimization model constructed by finite element and intelligent algorithms 认领 引用
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作者 Ran Liu Huan Jin +4 位作者 Song Liu Xiao-Jie Liu Jian-Hai Hao Jun Zhao Qing Lv 《Journal of Iron and Steel Research International》 SCIE EI CSCD 2026年第4期134-152,共19页
To ensure the uniformity of the gas flow in the sintering material layer,improve the sintering efficiency,and reduce the production energy consumption,it is of great significance to predict the permeability index of t... To ensure the uniformity of the gas flow in the sintering material layer,improve the sintering efficiency,and reduce the production energy consumption,it is of great significance to predict the permeability index of the original material layer in advance.However,how to achieve accurate prediction in line with the actual production environment has always been a challenge.Based on this,deep learning was combined with finite element numerical simulation,and an integrated prediction method with high interpretability and controllability was proposed.This method used the wavelet threshold denoising technology jointly improved based on complete ensemble empirical mode decomposition with adaptive noise(CEEN)to process the original data,so as to improve the data quality.Subsequently,a temporal convolutional network-long short-term memory(TCN-LSTM)model was constructed and trained for permeability prediction.Comparative analysis showed that the proposed model has a higher prediction accuracy than other comparative models,with the coefficient of determination R2 as high as 95%.In the experimental simulation stage,taking a 360 m2 sintering machine of a certain steel plant as the research object,the COMSOL finite element software was used to establish a physical model for process simulation.The results showed that the variation curve of the permeability of the material layer along the depth direction is highly consistent with the measured results,with a relative error of approximately 3.90 and the R2 of 92.38%.In addition,based on the results of finite element numerical simulation,when using the TCN-LSTM model for prediction,the difference between the predicted value and the simulated value is small,with an average relative error of only 4.92%and the R2 of 97.29%,showing a high degree of fitting and matching.Therefore,the method of combining finite element numerical simulation with CEEN-TCN-LSTM can accurately predict the permeability index of the material layer,effectively meeting the dual needs of predicting the permeability in advance and monitoring the change process of the material layer in actual production and providing technical support for the optimization of the sintering process and the production of high-quality sinter. 展开更多
关键词 Permeability index Deep learning Finite element numerical simulation CEEN-TCN-LSTM COMSOL Sintering bed state
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Experience-guided optimization of jacket foundations for offshore wind turbines in varying water depths based on finite element analysis and the genetic algorithm 认领 引用
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作者 Jiajia HUANG Tao JIN +6 位作者 Jianwu HUANG Shasha SONG Wei DAI Chaoqun ZUO Lizhong WANG Lilin WANG Zhen GUO 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2026年第3期183-199,共17页
Structural optimization plays a crucial role in reducing the cost of offshore wind power,particularly in deep-water regions where the weight of jacket foundations increases substantially.However,there is ongoing debat... Structural optimization plays a crucial role in reducing the cost of offshore wind power,particularly in deep-water regions where the weight of jacket foundations increases substantially.However,there is ongoing debate regarding the water-depth range that is suitable for jacket foundations,and the threshold where floating foundations become more viable.Existing studies have not quantitatively analyzed how water depth affects jacket foundation mass,and have often struggled to handle the high dimensionality and stringent constraints inherent in jacket foundation optimization problems.In this study,we propose an optimization framework that couples parametric finite element analysis with a genetic algorithm to minimize the mass of jacket foundations based on three actual engineering projects at varying water depths.A novel population initialization strategy incorporating engineering experience-based solutions is introduced to improve convergence efficiency and solution quality.Comparative analysis against preliminary designs and existing offshore wind projects demonstrates the model’s ability to achieve cost-effective solutions,specifically reducing required jacket masses by 18.66%,20.98%,and 17.22%at depths of 30.06,60.23,and 89.81 m,respectively.The results reveal a 122.94%increase in jacket mass—from 1431.28 to 3190.90 t—as water depth increases from 30.06 to 89.81 m.The jacket foundation demonstrates superior cost effectiveness in shallow to moderate water depths,as the unit weight per megawatt(MW)of floating foundations is 97.51%and 35.74%higher at water depths of 60.23 and 89.81 m,respectively.Accordingly,the applicable water-depth threshold between the jacket and floating foundations is estimated to be approximately 100 m.The proposed optimization model offers a novel methodology and practical insights for the optimal design of offshore wind turbine support structures in varying marine environments. 展开更多
关键词 Structural optimization Jacket foundation Genetic algorithm Offshore wind power Population initialization Parametric modeling
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Topological optimization design and biomechanical analysis of a novel titanium-PEEK multilayer cage in ACDF surgery:a finite element study 认领 引用
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作者 Yusheng Jin Qianqian Zhang +4 位作者 Chenjia Zhang Liming He Haoyu Feng Lingfeng Chen Weiyi Chen 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第6期565-574,共10页
Anterior cervical discectomy and fusion is the gold standard for the treatment of cervical spondylosis,with the cage playing a crucial role in maintaining intervertebral height and promoting bone fusion.However,cages ... Anterior cervical discectomy and fusion is the gold standard for the treatment of cervical spondylosis,with the cage playing a crucial role in maintaining intervertebral height and promoting bone fusion.However,cages made from single materials,such as polyetheretherketone(PEEK)or titanium alloys,often suffer from limitations like low fusion rates and high risks of subsidence.This study aims to design a multilayer cervical cage optimized through topological optimization,featuring a titanium alloy outer layer and a PEEK inner layer,combining the advantages of both materials to improve fusion rates and reduce the risk of subsidence.A finite element model of the C3-C7 cervical spine was developed,with a simplified ROI-C cage implanted at the C5-C6 segment for topological optimization.The multilayer cage was then redesigned based on the topological optimization result,and its biomechanical performance was compared with that of PEEK and titanium alloy cages.The results showed that there were no significant differences in postoperative cervical range of motion among the three types of cages.The facet joint force of the surgical segment significantly decreased in all models,with the titanium alloy cage model showing the greatest decrease and the PEEK cage model showing the least.The stress distribution at the contact interface between the titanium alloy cage and the vertebral body was the most concentrated,while it was the most uniform in the PEEK cage.In conclusion,the multilayer cage combines the advantages of both titanium alloy and PEEK,ensuring postoperative vertebral stability while reducing stress concentration at the contact interface with the vertebral body.This novel multilayer cage offers a new perspective on the selection of cages in clinical practice. 展开更多
关键词 Anterior cervical discectomy and fusion,Cage Topology optimize Subsidence Vertebral stability Finite element analysis
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SEMI-INFINITE INTERVAL-VALUED OPTIMIZATION PROBLEMS WITH ROBUST CONSTRAINTS 认领 引用
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作者 Anurag JAYSWAL Ajeet KUMAR 《Acta Mathematica Scientia》 SCIE CSCD 2026年第1期383-406,共24页
In this paper,we consider a robust semi-infinite interval-valued optimization problem with inequality constraints having an uncertain parameter.The parametric representation of the aforesaid problem is also considered... In this paper,we consider a robust semi-infinite interval-valued optimization problem with inequality constraints having an uncertain parameter.The parametric representation of the aforesaid problem is also considered in order to derive the necessary and sufficient optimality conditions.Furthermore,we formulate a mixed-type dual problem and derive duality results which associate the robust weak efficient solution of the primal and its dual problems.Several examples are given to illustrate the results in the manuscript. 展开更多
关键词 semi-infinite programming interval-valued programming robust weak efficient solution optimality conditions duality
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Finite element analysis and optimization of the rubber diaphragms in type-120 relief valves 认领 引用
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作者 Ming Gao Dongkai Li +5 位作者 Kun Liu Lijun Liu Ben Guo Anhui Pan Xiao Xie Huanre Han 《Railway Sciences》 2025年第5期598-612,共15页
Purpose–Type-120 relief valves are critical components of locomotive braking systems,and they rapidly discharge the air pressure during brake release to enable swift pressure relief.In order to develop type-120 relie... Purpose–Type-120 relief valves are critical components of locomotive braking systems,and they rapidly discharge the air pressure during brake release to enable swift pressure relief.In order to develop type-120 relief valve rubber diaphragms with long life and high performance,the damaged faulty samples were analyzed and studied.Design/methodology/approach–Finite element analysis(FEA)was used to investigate the stress distribution and failure mechanism of the rubber diaphragms within the type-120 relief valves under dynamic loading conditions.The Ogden hyperelastic constitutive model was used to fit the diaphragm data obtained from the uniaxial tensile tests,and its suitability for the modeling of large deformations was confirmed.Findings–The FEA results indicated that,when the rubber diaphragms reached their maximum deformation,the peak stress on their upper surfaces was 5.44 MPa.Thus,this region is highly susceptible to fatigue damage.The service life of the rubber diaphragms could be extended by using rubber compounds with high tensile moduli or a fabric-reinforced rubber diaphragm.Originality/value–This study provides valuable data and experience for the development of the rubber diaphragms in the type-120 valves and other long-life rubber products in the railway field. 展开更多
关键词 Type-120 relief valve Rubber diaphragm Damage failure Finite element analysis
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Optimal Linear Phase Finite Impulse Response Band Pass Filter Design Using Craziness Based Particle Swarm Optimization Algorithm 认领 引用
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作者 SANGEETA Mandal SAKTI Prasad Ghoshal +1 位作者 RAJIB Kar DURBADAL Mandal 《Journal of Shanghai Jiaotong university(Science)》 EI 2011年第6期696-703,共8页
An efficient method is proposed for the design of finite impulse response(FIR) filter with arbitrary pass band edge,stop band edge frequencies and transition width.The proposed FIR band stop filter is designed using c... An efficient method is proposed for the design of finite impulse response(FIR) filter with arbitrary pass band edge,stop band edge frequencies and transition width.The proposed FIR band stop filter is designed using craziness based particle swarm optimization(CRPSO) approach.Given the filter specifications to be realized,the CRPSO algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristics.In this paper,for the given problem,the realizations of the optimal FIR band pass filters of different orders have been performed.The simulation results have been compared with those obtained by the well accepted evolutionary algorithms,such as Parks and McClellan algorithm(PMA),genetic algorithm(GA) and classical particle swarm optimization(PSO).Several numerical design examples justify that the proposed optimal filter design approach using CRPSO outperforms PMA and PSO,not only in the accuracy of the designed filter but also in the convergence speed and solution quality. 展开更多
关键词 finite impulse response(FIR) filter particle swarm optimization(PSO) craziness based particle swarm optimization(CRPSO) Parks and McClellan algorithm(PMA) genetic algorithm(GA) optimization
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A Cell-Based Linear Smoothed Finite Element Method for Polygonal Topology Optimization 认领 引用 被引量：2
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作者 Changkye Lee Sundararajan Natarajan +1 位作者 Seong-Hoon Kee Jurng-Jae Yee 《Computer Modeling in Engineering & Sciences》 SCIE EI 2022年第6期1615-1634,共20页
The aim of this work is to employ a modified cell-based smoothed finite element method(S-FEM)for topology optimization with the domain discretized with arbitrary polygons.In the present work,the linear polynomial basi... The aim of this work is to employ a modified cell-based smoothed finite element method(S-FEM)for topology optimization with the domain discretized with arbitrary polygons.In the present work,the linear polynomial basis function is used as the weight function instead of the constant weight function used in the standard S-FEM.This improves the accuracy and yields an optimal convergence rate.The gradients are smoothed over each smoothing domain,then used to compute the stiffness matrix.Within the proposed scheme,an optimum topology procedure is conducted over the smoothing domains.Structural materials are distributed over each smoothing domain and the filtering scheme relies on the smoothing domain.Numerical tests are carried out to pursue the performance of the proposed optimization by comparing convergence,efficiency and accuracy. 展开更多
关键词 Smoothed finite element method linear smoothing function topology optimization solid isotropic material with penalization(SIMP) polygonal finite element cell
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A Finite Difference Method and Effective Modification of Gradient Descent Optimization Algorithm for MHD Fluid Flow Over a Linearly Stretching Surface 认领 引用 被引量：2
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作者 Yasir Nawaz Muhammad Shoaib Arif +3 位作者 Mairaj Bibi Javeria Nawaz Abbasi Umer Javed Amna Nazeer 《Computers, Materials & Continua》 SCIE EI 2020年第2期657-677,共21页
Present contribution is concerned with the construction and application of a numerical method for the fluid flow problem over a linearly stretching surface with the modification of standard Gradient descent Algorithm ... Present contribution is concerned with the construction and application of a numerical method for the fluid flow problem over a linearly stretching surface with the modification of standard Gradient descent Algorithm to solve the resulted difference equation.The flow problem is constructed using continuity,and Navier Stoke equations and these PDEs are further converted into boundary value problem by applying suitable similarity transformations.A central finite difference method is proposed that gives third-order accuracy using three grid points.The stability conditions of the present proposed method using a Gauss-Seidel iterative procedure is found using Von-Neumann stability criteria and order of the finite difference method is proved by applying the Taylor series on the discretised equation.The comparison of the presently modified optimisation algorithm with the Gauss-Seidel iterative method and standard Newton’s method in optimisation is also made.It can be concluded that the presently modified optimisation Algorithm takes a few iterations to converge with a small value of the parameter contained in it compared with the standard descent algorithm that may take millions of iterations to converge.The present modification of the steepest descent method converges faster than Gauss-Seidel method and standard steepest descent method,and it may also overcome the deficiency of singular hessian arise in Newton’s method for some of the cases that may arise in optimisation problem(s). 展开更多
关键词 Magnetohydrodynamic exact finite difference scheme optimization algorithm stability&convergence
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Shape optimization of axisymmetric solids with the finite cell method using a fixed grid 认领 引用 被引量：3
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作者 Liang Meng Wei-Hong Zhang +2 位作者 Ji-Hong Zhu Zhao Xu Shou-Hu Cai 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2016年第3期510-524,共15页
In this work, a design procedure extending the B-spline based finite cell method into shape optimization is developed for axisymmetric solids involving the centrifugal force effect. We first replace the traditional co... In this work, a design procedure extending the B-spline based finite cell method into shape optimization is developed for axisymmetric solids involving the centrifugal force effect. We first replace the traditional conforming mesh in the finite element method with structured cells that are fixed during the whole design process with a view to avoid the sophisticated re-meshing and eventual mesh distortion.Then, B-spline shape functions are further implemented to yield a high-order continuity field along the cell boundary in stress analysis. By means of the implicit description of the shape boundary, stress sensitivity is analytically derived with respect to shape design variables. Finally, we illustrate the efficiency and accuracy of the proposed protocol by several numerical test cases as well as a whole design procedure carried out on an aeronautic turbine disk. 展开更多
关键词 Finite cell method（FCM） Shape optimization B-spline Sensitivity analysis Axisymmetric solids
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In silico optimization of actuation performance in dielectric elastomercomposites via integrated finite element modeling and deep learning 认领 引用 被引量：1
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作者 Jiaxuan Ma Sheng Sun 《Theoretical & Applied Mechanics Letters》 CAS CSCD 2024年第1期48-56,共9页
Dielectric elastomers(DEs)require balanced electric actuation performance and mechanical integrity under applied voltages.Incorporating high dielectric particles as fillers provides extensive design space to optimize ... Dielectric elastomers(DEs)require balanced electric actuation performance and mechanical integrity under applied voltages.Incorporating high dielectric particles as fillers provides extensive design space to optimize concentration,morphology,and distribution for improved actuation performance and material modulus.This study presents an integrated framework combining finite element modeling(FEM)and deep learning to optimize the microstructure of DE composites.FEM first calculates actuation performance and the effective modulus across varied filler combinations,with these data used to train a convolutional neural network(CNN).Integrating the CNN into a multi-objective genetic algorithm generates designs with enhanced actuation performance and material modulus compared to the conventional optimization approach based on FEM approach within the same time.This framework harnesses artificial intelligence to navigate vast design possibilities,enabling optimized microstructures for high-performance DE composites. 展开更多
关键词 Dielectric elastomer composites Multi-objective optimization Finite element modeling Convolutional neural network
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A Full-Newton Step Feasible IPM for Semidefinite Optimization Based on a Kernel Function with Linear Growth Term 认领 引用 被引量：2
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作者 GENG Jie ZHANG Mingwang PANG Jinjuan 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2020年第6期501-509,共9页
In this paper,we propose and analyze a full-Newton step feasible interior-point algorithm for semidefinite optimization based on a kernel function with linear growth term.The kernel function is used both for determini... In this paper,we propose and analyze a full-Newton step feasible interior-point algorithm for semidefinite optimization based on a kernel function with linear growth term.The kernel function is used both for determining the search directions and for measuring the distance between the given iterate and theμ-center for the algorithm.By developing a new norm-based proximity measure and some technical results,we derive the iteration bound that coincides with the currently best known iteration bound for the algorithm with small-update method.In our knowledge,this result is the first instance of full-Newton step feasible interior-point method for SDO which involving the kernel function. 展开更多
关键词 semidefinite optimization interior-point algorithm kernel function iteration complexity
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Structural Optimization of Lap Link Based on Elastoplastic Finite Element Analysis 认领 引用 被引量：1
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作者 耿冬寒 郑炜 阎祥安 《Transactions of Tianjin University》 EI CAS 2007年第1期23-27,共5页
Based on finite-deformation elastoplastic theory, a scheme to solve the structural problems of the lap link by using ANSYS is proposed. The analysis results show that the maximum deformation exists at the loading spot... Based on finite-deformation elastoplastic theory, a scheme to solve the structural problems of the lap link by using ANSYS is proposed. The analysis results show that the maximum deformation exists at the loading spot of the lateral pin and the stiffness of this area needs to be enhanced; the maximum stresses occur at the two sides adjacent to the loading spot and the intensity around this region should be strengthened;the materials at the pole and pinhole with relatively low stress are redundant and removing excessive weight is possible. Based on the analysis, corresponding improvements are tentatively made, and the simulation results prove that, the stiffness and intensity of the new structure are improved. Furthermore, the reliability and validity of this design are verified by tensile tests of two types of structure. 展开更多
关键词 lap link finite element method finite-deformation elastoplastic
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Reliability Prediction of Wrought Carbon Steel Castings under Fatigue Loading Using Coupled Mold Optimization and Finite Element Simulation 认领 引用
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作者 Muhammad Azhar Ali Khan Syed Sohail Akhtar +2 位作者 Abba AAbubakar Muhammad Asad Khaled S.Al-Athel 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第12期2325-2350,共26页
The fatigue life and reliability of wrought carbon steel castings produced with an optimized mold design are predicted using a finite element method integrated with reliability calculations.The optimization of the mol... The fatigue life and reliability of wrought carbon steel castings produced with an optimized mold design are predicted using a finite element method integrated with reliability calculations.The optimization of the mold is carried out using MAGMASoft mainly based on porosity reduction as a response.After validating the initial mold design with experimental data,a spring flap,a common component of an automotive suspension system is designed and optimized followed by fatigue life prediction based on simulation using Fe-safe.By taking into consideration the variation in both stress and strength,the stress-strength model is used to predict the reliability of the component under fatigue loading.Under typical loading conditions of 70 kN,the analysis showed that 95%of the steel spring flaps achieve infinite life.However,under maximum loading conditions of 90 kN,reliability declined significantly,with only 65%of the spring flaps expected to withstand the stress without failure.The study also identified a safe load-induced stress of 95 MPa on the spring flap.The findings suggest that transitioning from forged to cast spring flaps is a promising option,particularly if further improvements in casting design reduce porosity to negligible levels,potentially achieving 100%reliability under typical loading conditions.This integrated approach of mold optimization coupled with reliability estimation under realistic service loading conditions offers significant potential for the casting industry to produce robust,cost-effective products. 展开更多
关键词 Casting optimization simulation finite element reliability automotive suspension
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A class of polynomial primal-dual interior-point algorithms for semidefinite optimization 认领 引用 被引量：6
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作者 王国强 白延琴 《Journal of Shanghai University(English Edition)》 2006年第3期198-207,共10页
In the present paper we present a class of polynomial primal-dual interior-point algorithms for semidefmite optimization based on a kernel function. This kernel function is not a so-called self-regular function due to... In the present paper we present a class of polynomial primal-dual interior-point algorithms for semidefmite optimization based on a kernel function. This kernel function is not a so-called self-regular function due to its growth term increasing linearly. Some new analysis tools were developed which can be used to deal with complexity ＂analysis of the algorithms which use analogous strategy in [5] to design the search directions for the Newton system. The complexity bounds for the algorithms with large- and small-update methodswere obtained, namely,O（qn^（p＋q/q（P＋1）log n/ε and O（q^2√n）log n/ε,respectlvely. 展开更多
关键词 semidefinite optimization （SDO） primal-dual interior-point methods large- and small-update methods polynomial complexity
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Improved Artificial Rabbit Optimization Algorithm Fused with Particle Swarm Optimization for Wireless Sensor Network Coverage Optimization 认领 引用 被引量：1
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作者 WU Jin SU Zhengdong 《Journal of Shanghai Jiaotong university(Science)》 EI 2026年第2期375-389,共15页
Aiming at the problem of low node coverage during node deployment in wireless sensor network(WSN),an improved artificial rabbit optimization algorithm incorporating particle swarm optimization(ARO-PSO)is proposed for ... Aiming at the problem of low node coverage during node deployment in wireless sensor network(WSN),an improved artificial rabbit optimization algorithm incorporating particle swarm optimization(ARO-PSO)is proposed for network coverage optimization.ARO-PSO successfully combines the stochastic characteristics of ARO and the global characteristics of PSO.Firstly,to optimize the quality of the initial population,Sine chaos mapping is introduced to initialize the population;secondly,to better balance the exploration and exploitation,adaptive settings are made;finally,combined with the characteristics of the ARO energy factor,a population decreasing strategy is introduced to further accelerate the convergence speed of the algorithm.Experimental and analytical comparisons are made with ARO and PSO and 6 other excellent optimizers on 13 benchmark functions.The results show that ARO-PSO largely outperforms the original algorithm.Finally,ARO-PSO is applied to WSN coverage optimization experiments in 2D and 3D environments,and the proposed algorithm exhibits higher network coverage and improves the monitoring quality of the network compared to standard ARO and PSO and other state-of-the-art algorithms.The experimental results fully demonstrate the superiority of the ARO-PSO-based WSN node deployment optimization method. 展开更多
关键词 wireless sensor network(WSN) swarm intelligence optimization artificial rabbits optimization(ARO) particle swarm optimization(PSO) coverage optimization
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NONCOMPACT INFINITE OPTIMIZATION AND EQUILIBRIA OF CONSTRAINED GAMES IN GENERALIZED CONVEX SPACES 认领 引用
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作者 丁协平 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2000年第9期1002-1007,共6页
By applying a new existence theorem of quasi-equilibrium problems due to the author, some existence theorems of solutions for noncompact infinite optimization problems and noncompact constrained game problems are prov... By applying a new existence theorem of quasi-equilibrium problems due to the author, some existence theorems of solutions for noncompact infinite optimization problems and noncompact constrained game problems are proved in generalized convex spaces without linear structure. These theorems improve and generalize a number of important results in recent literature. 展开更多
关键词 noncompace infinite optimization noncompact constrained game quasiequilibrium generalized convex space
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An adaptive machine learning-based optimization method in the aerodynamic analysis of a finite wing under various cruise conditions 认领 引用 被引量：1
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作者 Zilan Zhang Yu Ao +1 位作者 Shaofan Li Grace X.Gu 《Theoretical & Applied Mechanics Letters》 CAS CSCD 2024年第1期27-34,共8页
Conventional wing aerodynamic optimization processes can be time-consuming and imprecise due to the complexity of versatile flight missions.Plenty of existing literature has considered two-dimensional infinite airfoil... Conventional wing aerodynamic optimization processes can be time-consuming and imprecise due to the complexity of versatile flight missions.Plenty of existing literature has considered two-dimensional infinite airfoil optimization,while three-dimensional finite wing optimizations are subject to limited study because of high computational costs.Here we create an adaptive optimization methodology built upon digitized wing shape deformation and deep learning algorithms,which enable the rapid formulation of finite wing designs for specific aerodynamic performance demands under different cruise conditions.This methodology unfolds in three stages:radial basis function interpolated wing generation,collection of inputs from computational fluid dynamics simulations,and deep neural network that constructs the surrogate model for the optimal wing configuration.It has been demonstrated that the proposed methodology can significantly reduce the computational cost of numerical simulations.It also has the potential to optimize various aerial vehicles undergoing different mission environments,loading conditions,and safety requirements. 展开更多
关键词 Aerodynamic optimization Computational fluid dynamics Radial basis function Finite wing Deep learning neural network
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Convergence of shape optimization calculations of mechanical components using adaptive biological growth and iterative finite element methods 认领 引用 被引量：1
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作者 Mohammad Zehsaz Kaveh E.Torkanpouri Amin Paykani 《Journal of Central South University》 SCIE EI CAS 2013年第1期76-82,共7页
Shape optimization of mechanical components is one of the issues that have been considered in recent years. Different methods were presented such as adaptive biological for reducing costs and increasing accuracy. The ... Shape optimization of mechanical components is one of the issues that have been considered in recent years. Different methods were presented such as adaptive biological for reducing costs and increasing accuracy. The effects of step factor, the number of control points and the definition way of control points coordinates in convergence rate were studied. A code was written using ANSYS Parametric Design Language (APDL) which receives the studied parameters as input and obtains the optimum shape for the components. The results show that for achieving successful optimization, step factor should be in a specific range. It is found that the use of any coordinate system in defining control points coordinates and selection of any direction for stimulus vector of algorithm will also result in optimum shape. Furthermore, by increasing the number of control points, some non-uniformities are created in the studied boundary. Achieving acceptable accuracy seems impossible due to the creation of saw form at the studied boundary which is called "saw position". 展开更多
关键词 shape optimization adaptive biological growth control points step factor optimization rate
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