The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely,which poses a challenge to the study of the pantograph-catenary r...The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely,which poses a challenge to the study of the pantograph-catenary relationship and the design of highspeed pantographs.Good pantograph-catenary coupling quality is the essential condition to ensure safe and efficient operation of high-speed train,stable and reliable current collection,and reduction in the wear of contact wires and pantograph contact strips.Among them,the dynamic parameters of high-speed pantographs are crucial to pantograph-catenary coupling quality.With the reduction of the standard deviation of the pantograph-catenary contact force as the optimization goal,multi-parameter joint optimization designs for the high-speed pantograph with two contact strips at multiple running speeds are proposed.Moreover,combining the sensitivity analysis at the optimal solutions,with the parameters and characteristics of in-service DSA380 highspeed pantograph,the optimization proposal of DSA380 was given.展开更多
As a novel signaling technology,the power splitting receiver(PSR)simultaneously employs both the coherent and non-coherent signal processing.In order to improve its communication performance,an intelligent reflecting ...As a novel signaling technology,the power splitting receiver(PSR)simultaneously employs both the coherent and non-coherent signal processing.In order to improve its communication performance,an intelligent reflecting surface(IRS)is introduced into its signal propagation path.Consequently,an IRSaided PSR is concerned for a point-to-point(P2P)data link,where both the single-antenna and multiantenna deployments on the receiver are discussed.We aim at maximizing the capacity of the concerned P2P data-link by jointly optimizing the passive beamforming of IRS and the splitting ratio of PSR,either in single-antenna or multi-antenna case.However,owing to the coupling of multiple variables,the optimization problems are non-convex and challenging,especially in the later multi-antenna case.The proposed alternating-approximating algorithm(A-A),aided by semi-definite relaxation(SDR)and successive convex approximation(SCA)methods,etc.,successfully overcomes these challenges.We compare the IRS-aided PSR system that optimized by our proposed algorithm to the systems without IRS or PSR,and the systems without joint optimization.The simulation results show that our proposal has a better performance.展开更多
In this work,we consider an Unmanned Aerial Vehicle(UAV)aided covert edge computing architecture,where multiple sensors are scattered with a certain distance on the ground.The sensor can implement several computation ...In this work,we consider an Unmanned Aerial Vehicle(UAV)aided covert edge computing architecture,where multiple sensors are scattered with a certain distance on the ground.The sensor can implement several computation tasks.In an emergency scenario,the computational capabilities of sensors are often limited,as seen in vehicular networks or Internet of Things(IoT)networks.The UAV can be utilized to undertake parts of the computation tasks,i.e.,edge computing.While various studies have advanced the performance of UAV-based edge computing systems,the security of wireless transmission in future 6G networks is becoming increasingly crucial due to its inherent broadcast nature,yet it has not received adequate attention.In this paper,we improve the covert performance in a UAV aided edge computing system.Parts of the computation tasks of multiple ground sensors are offloaded to the UAV,where the sensors offload the computing tasks to the UAV,and Willie around detects the transmissions.The transmit power of sensors,the offloading proportions of sensors and the hovering height of the UAV affect the system covert performance,we propose a deep reinforcement learning framework to jointly optimize them.The proposed algorithm minimizes the system average task processing delay while guaranteeing that the transmissions of sensors are not detected by the Willie under the covertness constraint.Extensive simulations are conducted to verify the effectiveness of the proposed algorithm to decrease the average task processing delay with comparison with other algorithms.展开更多
Due to the extraordinary advantages,un-manned aerial vehicle(UAV)can be utilized as aerial base station(BS)to provide temporary and on-demand wireless connections for user equipments in the cover-age area.This article...Due to the extraordinary advantages,un-manned aerial vehicle(UAV)can be utilized as aerial base station(BS)to provide temporary and on-demand wireless connections for user equipments in the cover-age area.This article specifically considers the UAV-enabled orthogonal frequency division multiple access(OFDMA)wireless communication network.Consid-ering a practical scenario,a joint resource allocation and trajectory design optimization problem with the constraints on UAV mobility,limited total resource and backhaul link rate has been formulated,which aims to maximize the minimum achievable average rate of the users.To tackle the coupling and non-convexity of the proposed problem,an efficient opti-mization algorithm has been proposed based on alter-nating optimization,successive convex approximation and introducing slack variable techniques.Simulation results illustrate that the proposed optimization algo-rithm can effectively improve the system performance.Also,the numerical results unveil that joint optimiza-tion is superior to baseline schemes.展开更多
Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel.Existing experimental methods r...Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel.Existing experimental methods require lots of machining experiments and off-line tests, which may lead to high machining cost and low efficiency. This paper proposes a novel method of machining parameters optimization for an impeller based on the on-machine measuring technique. The absolute average error and standard deviation of the measured points are used to define the grey relational grade for reconstructing the objective function, and the complex problem of multi-objective optimization is simplified into a problem of single-objective optimization. Then, by comparing the values of the defined grey relational grade in a designed orthogonal experiment, the optimal combination of the machining parameters is obtained. The experiment-solving process of the objective function corresponds to the minimization of the used errors, which is advantageous to reducing the machining error. The proposed method is efficient and low-cost, since it does not require re-clamping the workpiece for off-line tests. Its effectiveness is verified by an on-machine inspection experiment of the impeller blade.展开更多
This paper presents an extended topology optimization approach considering joint load constraints with geo-metrical nonlinearity in design of assembled structures.The geometrical nonlinearity is firstly included to re...This paper presents an extended topology optimization approach considering joint load constraints with geo-metrical nonlinearity in design of assembled structures.The geometrical nonlinearity is firstly included to reflect the structural response and the joint load distribution under large deformation.To avoid a failure of fastener joints,topology optimization is then carried out to minimize the structural end compliance in the equilibrium state while controlling joint loads intensities over fasteners.During nonlinear analysis and optimization,a novel implementation of adjoint vector sensitivity analysis along with super element condensation is introduced to address numerical instability issues.The degrees of freedom of weak regions are condensed so that their influences are excluded from the iterative Newton-Raphson(NR)solution.Numerical examples are presented to validate the efficiency and robustness of the proposed method.The effects of joint load constraints and geometrical nonlinearity are highlighted by comparing numerical optimization results.展开更多
Despite significant improvements over the past several decades in diagnosis,treatment and prevention of periprosthetic joint infection(PJI),it still remains a major challenge following total joint arthroplasty.Given t...Despite significant improvements over the past several decades in diagnosis,treatment and prevention of periprosthetic joint infection(PJI),it still remains a major challenge following total joint arthroplasty.Given the devastating nature and accelerated incidence of PJI,prevention is the most important strategy to deal with this challenging problem and should start from identifying risk factors.Understanding and well-organized optimization of these risk factors in individuals before elective arthroplasty are essential to the ultimate success in reducing the incidence of PJI.Even though some risk factors such as demographic characteristics are seldom changeable,they allow more accurate expectation regarding individual risks of PJI and thus,make proper counseling for shared preoperative decision-making possible.Others that increase the risk of PJI,but are potentially modifiable should be optimized prior to elective arthroplasty.Although remarkable advances have been achieved in past decades,many questions regarding standardized practice to prevent this catastrophic complication remain unanswered.The current study provide a comprehensive knowledge regarding risk factors based on general principles to control surgical siteinfection by the review of current literature and also share own practice at our institution to provide practical and better understandings.展开更多
With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircr...With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy.Secondly, a combination of the genetic algorithm(GA) and the Monte Carol method is developed to minimize the total cost rate.Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management.展开更多
In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose ...In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.展开更多
To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.Howev...To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.However,the structural parameters of the shoulder joint will affect various performances of the mechanism.To obtain the optimal structure parameters,the particle swarm optimization(PSO) was used.Besides,the mathematical expressions of indexes of rotation ranges,maximum bearing torque,discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics.And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method.The normalization method and adaptive-weight method were used to determine each optimization index's weight coefficient;then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained.Compared with the average optimization generations and the optimal target values of many experiments,using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method,which validates superiority of the adaptive-weight method.展开更多
The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The tr...The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The transmitted waveforms and detection threshold are adaptively selected to enhance the tracking performance.The modified Riccati equation is adopted to predict the error covariance which is used as the criterion function,while the optimization problem is solved through the genetic algorithm(GA).The detection probability,false alarm probability and measurement noise covariance are all considered together,which significantly improves the tracking performance of the joint detection and tracking system.Simulation results show that the proposed adaptive waveform-detection threshold joint optimization method outperforms the adaptive threshold method and the fixed parameters method,which will reduce the tracking error.The average reduction of range error between the adaptive joint method and the fixed parameters method is about 0.6 m,while that between the adaptive joint method and the adaptive threshold only method is about 0.3 m.Similar error reduction occurs for the velocity error and acceleration error.展开更多
This work focuses on an unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) system based on device-to-device(D2D) communication. In this system, the UAV exhibits caching,computing and relaying capabilities...This work focuses on an unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) system based on device-to-device(D2D) communication. In this system, the UAV exhibits caching,computing and relaying capabilities to periodically provide specific service to cellular users and D2D receiver nodes in the appointed time slot. Besides, the D2D transmitter can provide additional caching services to D2D receiver to reduce the pressure of the UAV. Note that communication between multi-type nodes is mutually restricted and different links share spectrum resources. To achieve an improved balance between different types of node, we aim to maximize the overall energy efficiency while satisfying the quality-of-service requirements of the cellular nodes.To address this problem, we propose an alternating iteration algorithm to jointly optimize the scheduling strategies of the user, transmitting power of the UAV and D2D-TX nodes, and UAV trajectory. The successive convex approximation, penalty function, and Dinkelbach method are employed to transform the original problem into a group of solvable subproblems and the convergence of the method is proved. Simulation results show that the proposed scheme performs better than other benchmark algorithms, particularly in terms of balancing the tradeoff between minimizing UAV energy consumption and maximizing throughput.展开更多
In this paper,four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance.The deployable sola...In this paper,four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance.The deployable solar array model consists of a rigid main-body,two panels and four key mechanisms,containing torsion spring mechanism,closed cable loop mechanism,latch mechanism and attitude adjustment mechanism.Rigid and flexible components are established by Nodal Coordinate Formulation and Absolute Nodal Coordinate Formulation,respectively.The clearance joint model is described by nonlinear contact force model and amendatory Coulomb friction model.The latch time,stabilization time,maximum contact force and impulse sum of the contact force of the solar array system are selected as the four novel evaluation indices to represent the complex dynamic responses of a deployable solar array with clearance joints instead of the lock torque widely used in conventional works.To eliminate the gross errors caused by the nonlinear and nonsmooth mechanical properties,a hierarchical optimization strategy based on an adaptive simulated annealing algorithm and a nondominated sorting genetic algorithm is adopted for the solar array system with clearance joints.Results indicate that the effects of panel flexibility on the evaluation index responses and design optimization of the solar array system cannot be neglected.Besides,increasing the weight factor of the stabilization time index of the rigid system may compensate for the differences in optimal results of the rigid–flexible coupling system.That may provide some references for optimization design of deployable space mechanisms considering clearance joints.展开更多
Treatment of bone tumors in the mandible often involves extensive excavation of affected bone, followed by mandibular reconstruction. Prosthetic implants may be needed to restore jaw functionality. The challenges of m...Treatment of bone tumors in the mandible often involves extensive excavation of affected bone, followed by mandibular reconstruction. Prosthetic implants may be needed to restore jaw functionality. The challenges of making prosthetic bone implants include stress shielding and extending the mechanical life of the implant. We have developed a design algorithm to improve the efficiency of prosthesis design. A finite element model of the patient case is constructed from a computer tomography scan, and the computer implements topology optimization techniques to design the prosthesis with limited stress shielding affected by highly biomechanical compatibility. Topology optimization facilitates the design of low weight structures by automatically introducing holes into the structure. This is governed by engineering predetermined constraints to meet certain job specifications. Such a design will be tested for fatigue life before it is ready to be manufactured and used. Topology optimization can be performed as a design process to achieve a final design that takes stress shielding into consideration. The problem of stress shielding is solved by matching the stiffness of the orthopedic implant to the original bone that is being replaced. The material we used was titanium alloy (Ti-6Al-7Nb). Volume fraction of the orthodox implant was used (0.2872 for the studied case) as volume constraints. Compliance of the bulk bone was set as a further constraint to match the stiffness of the bone with the designed structure. Our results show a good life expectancy for the designed parts, with 12% higher life expectancy for stress-based topology optimization than for compliance-based topology optimization.展开更多
To minimize the mass and increase the bearing failure load of composite double-lap bolted joints,a three-step optimization strategy including feasible region reduction,optimization model decoupling and optimization wa...To minimize the mass and increase the bearing failure load of composite double-lap bolted joints,a three-step optimization strategy including feasible region reduction,optimization model decoupling and optimization was presented.In feasible region reduction,the dimensions of the feasible design region were reduced by selecting dominant design variables from numerous multilevel parameters by sensitivity analyses,and the feasible regions of variables were reduced by influence mechanism analyses.In model decoupling,the optimization model with a large number of variables was divided into various sub-models with fewer variables by variance analysis.In the third step,the optimization sub-models were solved one by one using a genetic algorithm,and the modified characteristic curve method was adopted as the failure prediction method.Based on the proposed optimization method,optimization of a double-lap single-bolt joint was performed using the ANSYS®code.The results show that the bearing failure load increased by 13.5%and that the mass decreased by 8.7%compared with those of the initial design of the joint,which validated the effectiveness of the three-step optimization strategy.展开更多
In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,th...In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,the user node only has a single antenna due to a limited price.Maximization of its downlink spectral efficiency is a joint optimization problem of three variables,namely phase-shift matrixΦof RIS,tilt angleθand beamforming vector w used in BS 3D beamforming.We solve this problem by employing the alternating optimization(AO)algorithm.But,in each iteration,a specific optimization order of firstlyΦ,secondlyθand finally w is proposed,which facilitates the search of optimalθin the way of narrowing its trust region and enabling unimodal property over the narrowed trust region.It finally results in a better combination of{Φ,θ,w}.展开更多
The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces ...The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces are simplified as the equivalent virtual material or linear spring damper element.The genetic algorithm for multi-objective optimization is then used to identify the mechanical properties of the equivalent joint by minimizing the error between the simulated dynamic characteristics and the experimental results,including the modal frequencies of the bolted joint beam and the frequency response functions(FRFs)of the rubber isolation system.The FRFs are divided into several subsections with frequency-varied dynamic properties of the joint to consider the nonlinear dynamic behaviors,and the effects of subsection number and excitation amplitudes on the FRFs are also investigated.The results show that the simulated dynamic characteristics of modal frequencies and FRFs agree well with the experimental results.With the increase in the subsection number,the simulated FRFs agree better with the experimental results,indicating a good performance of modeling the nonlinear dynamic behaviors of the joint interfaces forced by different excitation amplitudes.Larger excitation amplitudes will decrease the joint stiffness.展开更多
Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective...Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective implementation of massive MIMO challenging,due to the size and weight limits of the masssive MIMO that are located on each BS.Therefore,in order to miniaturize the massive MIMO,it is crucial to reduce the number of antenna elements via effective methods such as sparse array synthesis.In this paper,a multiple-pattern synthesis is considered towards convex optimization(CO).The joint convex optimization(JCO)based synthesis is proposed to construct a codebook for beamforming.Then,a criterion containing multiple constraints is developed,in which the sparse array is required to fullfill all constraints.Finally,extensive evaluations are performed under realistic simulation settings.The results show that with the same number of antenna elements,sparse array using the proposed JCO-based synthesis outperforms not only the uniform array,but also the sparse array with the existing CO-based synthesis method.Furthermore,with a half of the number of antenna elements that on the uniform array,the performance of the JCO-based sparse array approaches to that of the uniform array.展开更多
The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backsca...The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.展开更多
Based on a method combined artificial neural network (ANN) with particle swarm optimization (PSO) algorithm, the thermo-mechanical fatigue reliability of plastic ball grid array (PBGA) solder joints was studied. The s...Based on a method combined artificial neural network (ANN) with particle swarm optimization (PSO) algorithm, the thermo-mechanical fatigue reliability of plastic ball grid array (PBGA) solder joints was studied. The simulation experiments of accelerated thermal cycling test were performed by ANSYS software. Based on orthogonal array experiments, a back-propagation artificial neural network (BPNN) was used to establish the nonlinear multivariate relationship between thermo-mechanical fatigue reliability and control factors. Then, PSO was applied to obtaining the optimal levels of control factors by using the output of BPNN as the affinity measure. The results show that the control factors, such as print circuit board (PCB) size, PCB thickness, substrate size, substrate thickness, PCB coefficient of thermal expansion (CTE), substrate CTE, silicon die CTE, and solder joint CTE, have a great influence on thermo-mechanical fatigue reliability of PBGA solder joints. The ratio of signal to noise of ANN-PSO method is 51.77 dB and its error is 33.3% less than that of Taguchi method. Moreover, the running time of ANN-PSO method is only 2% of that of the BPNN. These conclusions are verified by the confirmative experiments.展开更多
基金the National Natural Science Foundation of China(Grant No.11672297)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB22020200).
文摘The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely,which poses a challenge to the study of the pantograph-catenary relationship and the design of highspeed pantographs.Good pantograph-catenary coupling quality is the essential condition to ensure safe and efficient operation of high-speed train,stable and reliable current collection,and reduction in the wear of contact wires and pantograph contact strips.Among them,the dynamic parameters of high-speed pantographs are crucial to pantograph-catenary coupling quality.With the reduction of the standard deviation of the pantograph-catenary contact force as the optimization goal,multi-parameter joint optimization designs for the high-speed pantograph with two contact strips at multiple running speeds are proposed.Moreover,combining the sensitivity analysis at the optimal solutions,with the parameters and characteristics of in-service DSA380 highspeed pantograph,the optimization proposal of DSA380 was given.
基金supported by National Key R&D Program of China with Grant number 2019YFB1803400in part by Sichuan Science and Technology Program under Grant 2024NSFSC0472。
文摘As a novel signaling technology,the power splitting receiver(PSR)simultaneously employs both the coherent and non-coherent signal processing.In order to improve its communication performance,an intelligent reflecting surface(IRS)is introduced into its signal propagation path.Consequently,an IRSaided PSR is concerned for a point-to-point(P2P)data link,where both the single-antenna and multiantenna deployments on the receiver are discussed.We aim at maximizing the capacity of the concerned P2P data-link by jointly optimizing the passive beamforming of IRS and the splitting ratio of PSR,either in single-antenna or multi-antenna case.However,owing to the coupling of multiple variables,the optimization problems are non-convex and challenging,especially in the later multi-antenna case.The proposed alternating-approximating algorithm(A-A),aided by semi-definite relaxation(SDR)and successive convex approximation(SCA)methods,etc.,successfully overcomes these challenges.We compare the IRS-aided PSR system that optimized by our proposed algorithm to the systems without IRS or PSR,and the systems without joint optimization.The simulation results show that our proposal has a better performance.
基金co-supported by the National Natural Science Foundation of China(No.62271093)the Natural Science Foundation of Chongqing,China(No.CSTB2023NSCQ-LZX0108)the Chongqing Graduate Research Innovation Project,China(No.CYS23093).
文摘In this work,we consider an Unmanned Aerial Vehicle(UAV)aided covert edge computing architecture,where multiple sensors are scattered with a certain distance on the ground.The sensor can implement several computation tasks.In an emergency scenario,the computational capabilities of sensors are often limited,as seen in vehicular networks or Internet of Things(IoT)networks.The UAV can be utilized to undertake parts of the computation tasks,i.e.,edge computing.While various studies have advanced the performance of UAV-based edge computing systems,the security of wireless transmission in future 6G networks is becoming increasingly crucial due to its inherent broadcast nature,yet it has not received adequate attention.In this paper,we improve the covert performance in a UAV aided edge computing system.Parts of the computation tasks of multiple ground sensors are offloaded to the UAV,where the sensors offload the computing tasks to the UAV,and Willie around detects the transmissions.The transmit power of sensors,the offloading proportions of sensors and the hovering height of the UAV affect the system covert performance,we propose a deep reinforcement learning framework to jointly optimize them.The proposed algorithm minimizes the system average task processing delay while guaranteeing that the transmissions of sensors are not detected by the Willie under the covertness constraint.Extensive simulations are conducted to verify the effectiveness of the proposed algorithm to decrease the average task processing delay with comparison with other algorithms.
基金supported by Project funded in part by China Postdoctoral Science Foundation(No.2021MD703980)in part by the National Natural Science Foundation of China(No.61901502).
文摘Due to the extraordinary advantages,un-manned aerial vehicle(UAV)can be utilized as aerial base station(BS)to provide temporary and on-demand wireless connections for user equipments in the cover-age area.This article specifically considers the UAV-enabled orthogonal frequency division multiple access(OFDMA)wireless communication network.Consid-ering a practical scenario,a joint resource allocation and trajectory design optimization problem with the constraints on UAV mobility,limited total resource and backhaul link rate has been formulated,which aims to maximize the minimum achievable average rate of the users.To tackle the coupling and non-convexity of the proposed problem,an efficient opti-mization algorithm has been proposed based on alter-nating optimization,successive convex approximation and introducing slack variable techniques.Simulation results illustrate that the proposed optimization algo-rithm can effectively improve the system performance.Also,the numerical results unveil that joint optimiza-tion is superior to baseline schemes.
基金co-supported by the National Basic Research Program of China(No.2015CB057304)the National Natural Science Foundation of China(Nos.51535004 and91648111)
文摘Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel.Existing experimental methods require lots of machining experiments and off-line tests, which may lead to high machining cost and low efficiency. This paper proposes a novel method of machining parameters optimization for an impeller based on the on-machine measuring technique. The absolute average error and standard deviation of the measured points are used to define the grey relational grade for reconstructing the objective function, and the complex problem of multi-objective optimization is simplified into a problem of single-objective optimization. Then, by comparing the values of the defined grey relational grade in a designed orthogonal experiment, the optimal combination of the machining parameters is obtained. The experiment-solving process of the objective function corresponds to the minimization of the used errors, which is advantageous to reducing the machining error. The proposed method is efficient and low-cost, since it does not require re-clamping the workpiece for off-line tests. Its effectiveness is verified by an on-machine inspection experiment of the impeller blade.
基金co-supported by National Key Research and Development Program(No.2017YFB1102800)NSFC for Excellent Young Scholars(No.11722219)Key Project of NSFC(Nos.51790171,5171101743,51735005,11620101002,and 11432011).
文摘This paper presents an extended topology optimization approach considering joint load constraints with geo-metrical nonlinearity in design of assembled structures.The geometrical nonlinearity is firstly included to reflect the structural response and the joint load distribution under large deformation.To avoid a failure of fastener joints,topology optimization is then carried out to minimize the structural end compliance in the equilibrium state while controlling joint loads intensities over fasteners.During nonlinear analysis and optimization,a novel implementation of adjoint vector sensitivity analysis along with super element condensation is introduced to address numerical instability issues.The degrees of freedom of weak regions are condensed so that their influences are excluded from the iterative Newton-Raphson(NR)solution.Numerical examples are presented to validate the efficiency and robustness of the proposed method.The effects of joint load constraints and geometrical nonlinearity are highlighted by comparing numerical optimization results.
基金Supported by The grant of Research Institute of Medical Science,Catholic University of Daegu(2011)
文摘Despite significant improvements over the past several decades in diagnosis,treatment and prevention of periprosthetic joint infection(PJI),it still remains a major challenge following total joint arthroplasty.Given the devastating nature and accelerated incidence of PJI,prevention is the most important strategy to deal with this challenging problem and should start from identifying risk factors.Understanding and well-organized optimization of these risk factors in individuals before elective arthroplasty are essential to the ultimate success in reducing the incidence of PJI.Even though some risk factors such as demographic characteristics are seldom changeable,they allow more accurate expectation regarding individual risks of PJI and thus,make proper counseling for shared preoperative decision-making possible.Others that increase the risk of PJI,but are potentially modifiable should be optimized prior to elective arthroplasty.Although remarkable advances have been achieved in past decades,many questions regarding standardized practice to prevent this catastrophic complication remain unanswered.The current study provide a comprehensive knowledge regarding risk factors based on general principles to control surgical siteinfection by the review of current literature and also share own practice at our institution to provide practical and better understandings.
基金supported by the Fundamental Research Funds for the Central Universities(NS2015072)
文摘With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy.Secondly, a combination of the genetic algorithm(GA) and the Monte Carol method is developed to minimize the total cost rate.Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management.
基金supported in part by the National Natural Science Foundation of China under Grants 61971126 and 61921004ZTE CorporationState Key Laboratory of Mobile Network and Mobile Multimedia Technology.
文摘In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.
基金the National Natural Science Foundation of China(NO.51405229)the Natural Science Foundation of Jiangsu Province of China(Nos.BK20151470 and BK20130796)
文摘To get the movement mode and driving mechanism similar to human shoulder joint,a six degrees of freedom(DOF) serial-parallel bionic shoulder joint mechanism driven by pneumatic muscle actuators(PMAs)was designed.However,the structural parameters of the shoulder joint will affect various performances of the mechanism.To obtain the optimal structure parameters,the particle swarm optimization(PSO) was used.Besides,the mathematical expressions of indexes of rotation ranges,maximum bearing torque,discrete dexterity and muscle shrinkage of the bionic shoulder joint were established respectively to represent its many-sided characteristics.And the multi-objective optimization problem was transformed into a single-objective optimization problem by using the weighted-sum method.The normalization method and adaptive-weight method were used to determine each optimization index's weight coefficient;then the particle swarm optimization was used to optimize the integrated objective function of the bionic shoulder joint and the optimal solution was obtained.Compared with the average optimization generations and the optimal target values of many experiments,using adaptive-weight method to adjust weights of integrated objective function is better than using normalization method,which validates superiority of the adaptive-weight method.
基金Project(61171133) supported by the National Natural Science Foundation of ChinaProject(11JJ1010) supported by the Natural Science Fund for Distinguished Young Scholars of Hunan Province,China
文摘The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The transmitted waveforms and detection threshold are adaptively selected to enhance the tracking performance.The modified Riccati equation is adopted to predict the error covariance which is used as the criterion function,while the optimization problem is solved through the genetic algorithm(GA).The detection probability,false alarm probability and measurement noise covariance are all considered together,which significantly improves the tracking performance of the joint detection and tracking system.Simulation results show that the proposed adaptive waveform-detection threshold joint optimization method outperforms the adaptive threshold method and the fixed parameters method,which will reduce the tracking error.The average reduction of range error between the adaptive joint method and the fixed parameters method is about 0.6 m,while that between the adaptive joint method and the adaptive threshold only method is about 0.3 m.Similar error reduction occurs for the velocity error and acceleration error.
基金the supports from the National Natural Science Foundation of China (61571156)Basic Research Project of Shenzhen (JCYJ20170413110004682 and JCYJ20150403161923521)。
文摘This work focuses on an unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) system based on device-to-device(D2D) communication. In this system, the UAV exhibits caching,computing and relaying capabilities to periodically provide specific service to cellular users and D2D receiver nodes in the appointed time slot. Besides, the D2D transmitter can provide additional caching services to D2D receiver to reduce the pressure of the UAV. Note that communication between multi-type nodes is mutually restricted and different links share spectrum resources. To achieve an improved balance between different types of node, we aim to maximize the overall energy efficiency while satisfying the quality-of-service requirements of the cellular nodes.To address this problem, we propose an alternating iteration algorithm to jointly optimize the scheduling strategies of the user, transmitting power of the UAV and D2D-TX nodes, and UAV trajectory. The successive convex approximation, penalty function, and Dinkelbach method are employed to transform the original problem into a group of solvable subproblems and the convergence of the method is proved. Simulation results show that the proposed scheme performs better than other benchmark algorithms, particularly in terms of balancing the tradeoff between minimizing UAV energy consumption and maximizing throughput.
基金supported by the National Natural Science Foundation of China(No.U1637207)Beijing Natural Science Foundation of China(No.1204040)。
文摘In this paper,four novel evaluation indices and corresponding hierarchical optimization strategies are proposed for a deployable solar array system considering panel flexibility and joint clearance.The deployable solar array model consists of a rigid main-body,two panels and four key mechanisms,containing torsion spring mechanism,closed cable loop mechanism,latch mechanism and attitude adjustment mechanism.Rigid and flexible components are established by Nodal Coordinate Formulation and Absolute Nodal Coordinate Formulation,respectively.The clearance joint model is described by nonlinear contact force model and amendatory Coulomb friction model.The latch time,stabilization time,maximum contact force and impulse sum of the contact force of the solar array system are selected as the four novel evaluation indices to represent the complex dynamic responses of a deployable solar array with clearance joints instead of the lock torque widely used in conventional works.To eliminate the gross errors caused by the nonlinear and nonsmooth mechanical properties,a hierarchical optimization strategy based on an adaptive simulated annealing algorithm and a nondominated sorting genetic algorithm is adopted for the solar array system with clearance joints.Results indicate that the effects of panel flexibility on the evaluation index responses and design optimization of the solar array system cannot be neglected.Besides,increasing the weight factor of the stabilization time index of the rigid system may compensate for the differences in optimal results of the rigid–flexible coupling system.That may provide some references for optimization design of deployable space mechanisms considering clearance joints.
文摘Treatment of bone tumors in the mandible often involves extensive excavation of affected bone, followed by mandibular reconstruction. Prosthetic implants may be needed to restore jaw functionality. The challenges of making prosthetic bone implants include stress shielding and extending the mechanical life of the implant. We have developed a design algorithm to improve the efficiency of prosthesis design. A finite element model of the patient case is constructed from a computer tomography scan, and the computer implements topology optimization techniques to design the prosthesis with limited stress shielding affected by highly biomechanical compatibility. Topology optimization facilitates the design of low weight structures by automatically introducing holes into the structure. This is governed by engineering predetermined constraints to meet certain job specifications. Such a design will be tested for fatigue life before it is ready to be manufactured and used. Topology optimization can be performed as a design process to achieve a final design that takes stress shielding into consideration. The problem of stress shielding is solved by matching the stiffness of the orthopedic implant to the original bone that is being replaced. The material we used was titanium alloy (Ti-6Al-7Nb). Volume fraction of the orthodox implant was used (0.2872 for the studied case) as volume constraints. Compliance of the bulk bone was set as a further constraint to match the stiffness of the bone with the designed structure. Our results show a good life expectancy for the designed parts, with 12% higher life expectancy for stress-based topology optimization than for compliance-based topology optimization.
基金This work was supported by the National Natural Science Foundation of China(11772028,11872131,11702012,U1864208,11572058 and 11372020).
文摘To minimize the mass and increase the bearing failure load of composite double-lap bolted joints,a three-step optimization strategy including feasible region reduction,optimization model decoupling and optimization was presented.In feasible region reduction,the dimensions of the feasible design region were reduced by selecting dominant design variables from numerous multilevel parameters by sensitivity analyses,and the feasible regions of variables were reduced by influence mechanism analyses.In model decoupling,the optimization model with a large number of variables was divided into various sub-models with fewer variables by variance analysis.In the third step,the optimization sub-models were solved one by one using a genetic algorithm,and the modified characteristic curve method was adopted as the failure prediction method.Based on the proposed optimization method,optimization of a double-lap single-bolt joint was performed using the ANSYS®code.The results show that the bearing failure load increased by 13.5%and that the mass decreased by 8.7%compared with those of the initial design of the joint,which validated the effectiveness of the three-step optimization strategy.
基金supported by the National Key R&D Program of China under Grant 2019YFB1803400partly by National Natural Science Foundation of China under Grant 62071394.
文摘In this paper,a three-node transmission model is conceived,where the base station(BS)node leverages 3D beamforming,the reconfigurable intelligent surface(RIS)node can constructively reconfigure the wireless channel,the user node only has a single antenna due to a limited price.Maximization of its downlink spectral efficiency is a joint optimization problem of three variables,namely phase-shift matrixΦof RIS,tilt angleθand beamforming vector w used in BS 3D beamforming.We solve this problem by employing the alternating optimization(AO)algorithm.But,in each iteration,a specific optimization order of firstlyΦ,secondlyθand finally w is proposed,which facilitates the search of optimalθin the way of narrowing its trust region and enabling unimodal property over the narrowed trust region.It finally results in a better combination of{Φ,θ,w}.
基金The work was supported by the Science Challenge Project(Grant No.TZ2018007)The authors also thank the National Natural Science Foundation of China(Grant Nos.11872059,11702279)National Defense Technology Foundation of China(Grant No.JSUS2018212C)for providing the financial support for this project.
文摘The nonlinear dynamic modeling by combining the equivalent linear mechanics with the multi-objective optimization algorithm is proposed to describe the nonlinear behaviors of the joint interfaces.The joint interfaces are simplified as the equivalent virtual material or linear spring damper element.The genetic algorithm for multi-objective optimization is then used to identify the mechanical properties of the equivalent joint by minimizing the error between the simulated dynamic characteristics and the experimental results,including the modal frequencies of the bolted joint beam and the frequency response functions(FRFs)of the rubber isolation system.The FRFs are divided into several subsections with frequency-varied dynamic properties of the joint to consider the nonlinear dynamic behaviors,and the effects of subsection number and excitation amplitudes on the FRFs are also investigated.The results show that the simulated dynamic characteristics of modal frequencies and FRFs agree well with the experimental results.With the increase in the subsection number,the simulated FRFs agree better with the experimental results,indicating a good performance of modeling the nonlinear dynamic behaviors of the joint interfaces forced by different excitation amplitudes.Larger excitation amplitudes will decrease the joint stiffness.
文摘Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile communications.However,exploiting a large number of antenna elements at base station(BS)makes effective implementation of massive MIMO challenging,due to the size and weight limits of the masssive MIMO that are located on each BS.Therefore,in order to miniaturize the massive MIMO,it is crucial to reduce the number of antenna elements via effective methods such as sparse array synthesis.In this paper,a multiple-pattern synthesis is considered towards convex optimization(CO).The joint convex optimization(JCO)based synthesis is proposed to construct a codebook for beamforming.Then,a criterion containing multiple constraints is developed,in which the sparse array is required to fullfill all constraints.Finally,extensive evaluations are performed under realistic simulation settings.The results show that with the same number of antenna elements,sparse array using the proposed JCO-based synthesis outperforms not only the uniform array,but also the sparse array with the existing CO-based synthesis method.Furthermore,with a half of the number of antenna elements that on the uniform array,the performance of the JCO-based sparse array approaches to that of the uniform array.
文摘The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.
基金Project(60371046) supported by the National Natural Science Foundation of ChinaProject(9140C0301060C03001) supported by the National Defense Science and Technology Foundation of Key Laboratory, China
文摘Based on a method combined artificial neural network (ANN) with particle swarm optimization (PSO) algorithm, the thermo-mechanical fatigue reliability of plastic ball grid array (PBGA) solder joints was studied. The simulation experiments of accelerated thermal cycling test were performed by ANSYS software. Based on orthogonal array experiments, a back-propagation artificial neural network (BPNN) was used to establish the nonlinear multivariate relationship between thermo-mechanical fatigue reliability and control factors. Then, PSO was applied to obtaining the optimal levels of control factors by using the output of BPNN as the affinity measure. The results show that the control factors, such as print circuit board (PCB) size, PCB thickness, substrate size, substrate thickness, PCB coefficient of thermal expansion (CTE), substrate CTE, silicon die CTE, and solder joint CTE, have a great influence on thermo-mechanical fatigue reliability of PBGA solder joints. The ratio of signal to noise of ANN-PSO method is 51.77 dB and its error is 33.3% less than that of Taguchi method. Moreover, the running time of ANN-PSO method is only 2% of that of the BPNN. These conclusions are verified by the confirmative experiments.
