The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment.This study reported a three-dimensional electrochemical treatment ...The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment.This study reported a three-dimensional electrochemical treatment process integrating graphite intercalation compound(GIC)adsorption,direct anodic oxidation,and·OH oxidation for decolourising Reactive Black 5(RB5)from aqueous solutions.The electrochemical process was optimised using the novel progressive central composite design-response surface methodology(CCD-NPRSM),hybrid artificial neural network-extreme gradient boosting(hybrid ANN-XGBoost),and classification and regression trees(CART).CCD-NPRSM and hybrid ANN-XGBoost were employed to minimise errors in evaluating the electrochemical process involving three manipulated operational parameters:current density,electrolysis(treatment)time,and initial dye concentration.The optimised decolourisation efficiencies were 99.30%,96.63%,and 99.14%for CCD-NPRSM,hybrid ANN-XGBoost,and CART,respectively,compared to the 98.46%RB5 removal rate observed experimentally under optimum conditions:approximately 20 mA/cm^(2) of current density,20 min of electrolysis time,and 65 mg/L of RB5.The optimised mineralisation efficiencies ranged between 89%and 92%for different models based on total organic carbon(TOC).Experimental studies confirmed that the predictive efficiency of optimised models ranked in the descending order of hybrid ANN-XGBoost,CCD-NPRSM,and CART.Model validation using analysis of variance(ANOVA)revealed that hybrid ANN-XGBoost had a mean squared error(MSE)and a coefficient of determination(R^(2))of approximately 0.014 and 0.998,respectively,for the RB5 removal efficiency,outperforming CCD-NPRSM with MSE and R^(2) of 0.518 and 0.998,respectively.Overall,the hybrid ANN-XGBoost approach is the most feasible technique for assessing the electrochemical treatment efficiency in RB5 dye wastewater decolourisation.展开更多
This article presents the design of a microfabricated bio-inspired flapping-wing Nnano Aaerial Vvehicle(NAV),driven by an electromagnetic system.Our approach is based on artificial wings composed of rigid bodies conne...This article presents the design of a microfabricated bio-inspired flapping-wing Nnano Aaerial Vvehicle(NAV),driven by an electromagnetic system.Our approach is based on artificial wings composed of rigid bodies connected by compliant links,which optimise aerodynamic forces though replicating the complex wing kinematics of insects.The originality of this article lies in a new design methodology based on a triple equivalence between a 3D model,a multibody model,and a mass/spring model(0D)which reduces the number of parameters in the problem.This approach facilitates NAV optimisation by using only the mass/spring model,thereby simplifying the design process while maintaining high accuracy.Two wing geometries are studied and optimised in this article to produce large-amplitude wing motions(approximately 40^\circ),and enabling flapping and twisting motion in quadrature.The results are validated thanks to experimental measurements for the large amplitude and through finite element simulations for the combined motion,confirming the effectiveness of this strategy for a NAV weighing less than 40 mg with a wingspan of under 3 cm.展开更多
This paper presents an investigation of the tribological performance of AA2024–B_(4)C composites,with a specific focus on the influence of reinforcement and processing parameters.In this study three input parameters ...This paper presents an investigation of the tribological performance of AA2024–B_(4)C composites,with a specific focus on the influence of reinforcement and processing parameters.In this study three input parameters were varied:B_(4)C weight percentage,milling time,and normal load,to evaluate their effects on two output parameters:wear loss and the coefficient of friction.AA2024 alloy was used as the matrix alloy,while B_(4)C particles were used as reinforcement.Due to the high hardness and wear resistance of B_(4)C,the optimized composite shows strong potential for use in aerospace structural elements and automotive brake components.The optimisation of tribological behaviour was conducted using a Taguchi-Grey Relational Analysis(Taguchi-GRA)and the Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS).A total of 27 combinations of input parameters were analysed,varying the B_(4)C content(0,10,and 15 wt.%),milling time(0,15,and 25 h),and normal load(1,5,and 10 N).Wear loss and the coefficient of friction were numerically evaluated and selected as criteria for optimisation.Artificial Neural Networks(ANNs)were also applied for two outputs simultaneously.TOPSIS identified Alternative 1 as the optimal solution,confirming the results obtained using the Taguchi Grey method.The optimal condition obtained(10 wt.%B_(4)C,25 h milling time,10 N load)resulted in a minimum wear loss of 1.7 mg and a coefficient of friction of 0.176,confirming significant enhancement in tribological behaviour.Based on the results,both the B_(4)C content and the applied processing conditions have a significant impact on wear loss and frictional properties.This approach demonstrates high reliability and confidence,enabling the design of future composite materials with optimal properties for specific applications.展开更多
The challenge of optimising multimodal functions within high-dimensional domains constitutes a notable difficulty in evolutionary computation research.Addressing this issue,this study introduces the Deep Backtracking ...The challenge of optimising multimodal functions within high-dimensional domains constitutes a notable difficulty in evolutionary computation research.Addressing this issue,this study introduces the Deep Backtracking Bare-Bones Particle Swarm Optimisation(DBPSO)algorithm,an innovative approach built upon the integration of the Deep Memory Storage Mechanism(DMSM)and the Dynamic Memory Activation Strategy(DMAS).The DMSM enhances the memory retention for the globally optimal particle,promoting interaction between standard particles and their historically optimal counterparts.In parallel,DMAS assures the updated position of the globally optimal particle is appropriately aligned with the deep memory repository.The efficacy of DBPSO was rigorously assessed through a series of simulations employing the CEC2017 benchmark suite.A comparative analysis juxtaposed DBPSO's performance against five contemporary evolutionary algorithms across two experimental conditions:Dimension-50 and Dimension-100.In the 50D trials,DBPSO attained an average ranking of 2.03,whereas in the 100D scenarios,it improved to an average ranking of 1.9.Further examination utilising the CEC2019 benchmark functions revealed DBPSO's robustness,securing four first-place finishes,three second-place standings,and three third-place positions,culminating in an unmatched average ranking of 1.9 across all algorithms.These empirical results corroborate DBPSO's proficiency in delivering precise solutions for complex,high-dimensional optimisation challenges.展开更多
A general and new explicit isogeometric topology optimisation approach with moving morphable voids(MMV)is proposed.In this approach,a novel multiresolution scheme with two distinct discretisation levels is developed t...A general and new explicit isogeometric topology optimisation approach with moving morphable voids(MMV)is proposed.In this approach,a novel multiresolution scheme with two distinct discretisation levels is developed to obtain high-resolution designs with a relatively low computational cost.Ersatz material model based on Greville abscissae collocation scheme is utilised to represent both the Young’s modulus of the material and the density field.Two benchmark examples are tested to illustrate the effectiveness of the proposed method.Numerical results show that high-resolution designs can be obtained with relatively low computational cost,and the optimisation can be significantly improved without introducing additional DOFs.展开更多
This paper presents an optimisatiombased verification process for obstacle avoidance systems of a unicycle-like mobile robot. It is a novel approach for the collision avoidance verification process. Local and global o...This paper presents an optimisatiombased verification process for obstacle avoidance systems of a unicycle-like mobile robot. It is a novel approach for the collision avoidance verification process. Local and global optimisation based verification processes are developed to find the worst-case parameters and the worst-case distance between the robot and an obstacle. The kinematic and dynamic model of the unicycle-like mobile robot is first introduced with force and torque as the inputs. The design of the control system is split into two parts. One is velocity and rotation using the robot dynamics, and the other is the incremental motion planning for robot kinematics. The artificial potential field method is chosen as a path planning and obstacle avoidance candidate technique for verification study as it is simple and widely used. Different optimisation algorithms are applied and compared for the purpose of verification. It is shown that even for a simple case study where only mass and inertia variations are considered, a local optimization based verification method may fail to identify the worst case. Two global optimisation methods have been investigated： genetic algorithms （GAs） and GLOBAL algorithms. Both of these methods successfully find the worst case. The verification process confirms that the obstacle avoidance algorithm functions correctly in the presence of all the possible parameter variations.展开更多
针对无线体域网(Wireless Body Area Network,WBAN)面临的能源供应限制和数据时效性不足问题,文中设计了一种基于无线供能体域网(Wireless-powered Body Area Network,WP-BAN)的传输优化策略。对WP-BAN进行系统建模,考虑了基于马尔可夫...针对无线体域网(Wireless Body Area Network,WBAN)面临的能源供应限制和数据时效性不足问题,文中设计了一种基于无线供能体域网(Wireless-powered Body Area Network,WP-BAN)的传输优化策略。对WP-BAN进行系统建模,考虑了基于马尔可夫的数据采集传输过程、能量供应与消耗过程以及信息年龄(Age-of-Information,AoI)增长过程,并在队列稳定性约束和链路容量约束下构建一个关于数据采样速率与数据丢弃率系统效用最大化的离散时间随机优化问题。运用Lyapunov优化理论将原问题转化为单时隙多序列的确定性优化问题,设计了效用最大化的传输调度和能量收集策略(Utility-maximization Transmission Scheduling and Energy Harvesting Strategy,UMTEHS)。在Lyapunov求解框架下使用BARON(Branch and Reduce Optimization Navigator)求解器求解转化后的优化问题,根据当前时刻的队列状态优化下一个时刻的数据传输调度和能量收集率。仿真实验验证了所提策略的有效性,其在保持系统能量中性运行的同时能够获得更大的系统效用和更小的AoI。展开更多
Self-piercing riveting(SPR)is a cold forming technique used to fasten together two or more sheets of materials with a rivet without the need to predrill a hole.The application of SPR in the automotive sector has becom...Self-piercing riveting(SPR)is a cold forming technique used to fasten together two or more sheets of materials with a rivet without the need to predrill a hole.The application of SPR in the automotive sector has become increasingly popular mainly due to the growing use of lightweight materials in transportation applications.However,SPR joining of these advanced light materials remains a challenge as these materials often lack a good combination of high strength and ductility to resist the large plastic deformation induced by the SPR process.In this paper,SPR joints of advanced materials and their corresponding failure mechanisms are discussed,aiming to provide the foundation for future improvement of SPR joint quality.This paper is divided into three major sections:1)joint failures focusing on joint defects originated from the SPR process and joint failure modes under different mechanical loading conditions,2)joint corrosion issues,and 3)joint optimisation via process parameters and advanced techniques.展开更多
In the present study, we developed a multi-component one-dimensional mathematical model for simulation and optimisation of a commercial catalytic slurry reactor for the direct synthesis of dimethyl ether （DME） from ...In the present study, we developed a multi-component one-dimensional mathematical model for simulation and optimisation of a commercial catalytic slurry reactor for the direct synthesis of dimethyl ether （DME） from syngas and CO2, operating in a churn-turbulent regime. DME productivity and CO conversion were optimised by tuning operating conditions, such as superficial gas velocity, catalyst concentration, catalyst mass over molar gas flow rate （W/F）, syngas composition, pressure and temperature. Reactor modelling was accomplished utilising mass balance, global kinetic models and heterogeneous hydrodynamics. In the heterogeneous flow regime, gas was distributed into two bubble phases： small and large. Simulation results were validated using data obtained from a pilot plant. The developed model is also applicable for the design of large-scale slurry reactors.展开更多
This paper presents the effect of mooring diameters, fairlead slopes and pretensions on the dynamic responses of a truss spar platform in intact and damaged line conditions. The platform is modelled as a rigid body wi...This paper presents the effect of mooring diameters, fairlead slopes and pretensions on the dynamic responses of a truss spar platform in intact and damaged line conditions. The platform is modelled as a rigid body with three degrees-of-freedom and its motions are analysed in time-domain using the implicit Newmark Beta technique. The mooring restoring force-excursion relationship is evaluated using quasi-static approach. MATLAB codes DATSpar and QSAML, are developed to compute the dynamic responses of truss spar platform and to determine the mooring system stiffness. To eliminate the conventional trial and error approach in the mooring system design, a numerical tool is also developed and described in this paper for optimising the mooring configuration. It has a graphical user interface and includes regrouping particle swarm optimisation technique combined with DATSpar and QSAML. A case study of truss spar platform with ten mooring lines is analysed using this numerical tool. The results show that optimum mooring system design benefits the oil and gas industry to economise the project cost in terms of material, weight, structural load onto the platform as well as manpower requirements. This tool is useful especially for the preliminary design of truss spar platforms and its mooring system.展开更多
Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electri...Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electricity market transactions.Therefore,the carbon trading market is introduced into the wind power market,and a new form of low-carbon economic dispatch model is developed.First,the economic dispatch goal of wind power is be considered.It is projected to save money and reduce the cost of power generation for the system.The model includes risk operating costs to account for the impact of wind power output variability on the system,as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment.The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions,and analyze the impact of different carbon trading prices on the system.A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals.Finally,the solution is optimised using the Ant-lion optimisation method,which combines Levi's flight mechanism and golden sine.The proposed model and algorithm's rationality is proven through the use of cases.展开更多
Creep strength enhanced ferritic(CSEF) steels are used in advanced power plant systems for high temperature applications. P92(Cr–W–Mo–V)steel, classified under CSEF steels, is a candidate material for piping, tubin...Creep strength enhanced ferritic(CSEF) steels are used in advanced power plant systems for high temperature applications. P92(Cr–W–Mo–V)steel, classified under CSEF steels, is a candidate material for piping, tubing, etc., in ultra-super critical and advanced ultra-super critical boiler applications. In the present work, laser welding process has been optimised for P92 material by using Taguchi based grey relational analysis(GRA).Bead on plate(BOP) trials were carried out using a 3.5 k W diffusion cooled slab CO_2 laser by varying laser power, welding speed and focal position. The optimum parameters have been derived by considering the responses such as depth of penetration, weld width and heat affected zone(HAZ) width. Analysis of variance(ANOVA) has been used to analyse the effect of different parameters on the responses. Based on ANOVA, laser power of 3 k W, welding speed of 1 m/min and focal plane at-4 mm have evolved as optimised set of parameters. The responses of the optimised parameters obtained using the GRA have been verified experimentally and found to closely correlate with the predicted value.? 2016 China Ordnance Society. Production and hosting by Elsevier B.V. All rights reserved.展开更多
Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to ...Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to two issues:Both the hyperparameter and ar-chitecture should be optimised and the optimisation process is computationally expen-sive.To tackle these two issues,this paper focusses on solving the hyperparameter and architecture optimization problem for the NN and proposes a novel light‐weight scale‐adaptive fitness evaluation‐based particle swarm optimisation(SAFE‐PSO)approach.Firstly,the SAFE‐PSO algorithm considers the hyperparameters and architectures together in the optimisation problem and therefore can find their optimal combination for the globally best NN.Secondly,the computational cost can be reduced by using multi‐scale accuracy evaluation methods to evaluate candidates.Thirdly,a stagnation‐based switch strategy is proposed to adaptively switch different evaluation methods to better balance the search performance and computational cost.The SAFE‐PSO algorithm is tested on two widely used datasets:The 10‐category(i.e.,CIFAR10)and the 100−cate-gory(i.e.,CIFAR100).The experimental results show that SAFE‐PSO is very effective and efficient,which can not only find a promising NN automatically but also find a better NN than compared algorithms at the same computational cost.展开更多
The paper studies stochastic dynamics of a two-degree-of-freedom system,where a primary linear system is connected to a nonlinear energy sink with cubic stiffness nonlinearity and viscous damping.While the primary mas...The paper studies stochastic dynamics of a two-degree-of-freedom system,where a primary linear system is connected to a nonlinear energy sink with cubic stiffness nonlinearity and viscous damping.While the primary mass is subjected to a zero-mean Gaussian white noise excitation,the main objective of this study is to maximise the efficiency of the targeted energy transfer in the system.A surrogate optimisation algorithm is proposed for this purpose and adopted for the stochastic framework.The optimisations are conducted separately for the nonlinear stiffness coefficient alone as well as for both the nonlinear stiffness and damping coefficients together.Three different optimisation cost functions,based on either energy of the system’s components or the dissipated energy,are considered.The results demonstrate some clear trends in values of the nonlinear energy sink coefficients and show the effect of different cost functions on the optimal values of the nonlinear system’s coefficients.展开更多
Computational fluid dynamics(CFD) simulation is an effective approach to develop and optimise gas drainage design for underground longwall coal mining. As part of the project supported by the Australian Government Coa...Computational fluid dynamics(CFD) simulation is an effective approach to develop and optimise gas drainage design for underground longwall coal mining. As part of the project supported by the Australian Government Coal Mining Abatement Technology Support Package(CMATSP), threedimensional CFD simulations were conducted to test and optimise a conceptual design which proposes using horizontal boreholes to replace vertical boreholes at an underground coal mine in Australia.Drainage performance between a vertical borehole and a horizontal borehole was first carried out to compare their capacity and effectiveness. Then a series of cases with different horizontal borehole designs were simulated to optimise borehole configuration parameters such as location, diameter, and number of boreholes. The study shows that the horizontal borehole is able to create low pressure sinks that protect the workings from goaf gas ingresses by changing goaf gas flow directions, and that it has the advantage to continuously maintain such low pressure sinks near the tailgate as the longwall advances. An example of optimising horizontal borehole locations in the longwall lateral direction is also given in this paper.展开更多
Two uncoupleable distributions, assigning missions to robots and allocating robots to home stations, accompany the use ofmobile service robots in hospitals.In the given problem, two workload-related objectives and fiv...Two uncoupleable distributions, assigning missions to robots and allocating robots to home stations, accompany the use ofmobile service robots in hospitals.In the given problem, two workload-related objectives and five groups of constraints areproposed.A bio-mimicked Binary Bees Algorithm (BBA) is introduced to solve this multiobjective multiconstraint combinatorialoptimisation problem, in which constraint handling technique (Multiobjective Transformation, MOT), multiobjectiveevaluation method (nondominance selection), global search strategy (stochastic search in the variable space), local searchstrategy (Hamming neighbourhood exploitation), and post-processing means (feasibility selection) are the main issues.TheBBA is then demonstrated with a case study, presenting the execution process of the algorithm, and also explaining the change ofelite number in evolutionary process.Its optimisation result provides a group of feasible nondominated two-level distributionschemes.展开更多
The optimisation of earthquake resistance of high buildings by multi-tuned mass dampers was investigated using bionic algorithms. In bionic or evolutionary optimisation studies the properties of parents are crossed an...The optimisation of earthquake resistance of high buildings by multi-tuned mass dampers was investigated using bionic algorithms. In bionic or evolutionary optimisation studies the properties of parents are crossed and mutated to produce a new generation with slightly different properties. The kids which best satisfy the object of the study, become the parents of the next generation. After a series of generations essential improvements of the object may be observed. Tuned mass dampers are widely used to reduce the impact of dynamic excitations on structures. A single mass system and multi-mass oscillators help to explain the mechanics of the dampers. To apply the bionic optimisation strategy to high buildings with passive tuned mass dampers subject to seismic loading a special beam element has been developed. In addition to the 6 degrees of freedom of a conventional beam element, it has 2 degrees of freedom for the displacements of the dampers. It allows for fast studies of many variants. As central result, efficient designs for damping systems along the height of an edifice are found. The impact on the structure may be reduced essentially by the use of such dampers designed to interact in an optimal way.展开更多
文摘The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment.This study reported a three-dimensional electrochemical treatment process integrating graphite intercalation compound(GIC)adsorption,direct anodic oxidation,and·OH oxidation for decolourising Reactive Black 5(RB5)from aqueous solutions.The electrochemical process was optimised using the novel progressive central composite design-response surface methodology(CCD-NPRSM),hybrid artificial neural network-extreme gradient boosting(hybrid ANN-XGBoost),and classification and regression trees(CART).CCD-NPRSM and hybrid ANN-XGBoost were employed to minimise errors in evaluating the electrochemical process involving three manipulated operational parameters:current density,electrolysis(treatment)time,and initial dye concentration.The optimised decolourisation efficiencies were 99.30%,96.63%,and 99.14%for CCD-NPRSM,hybrid ANN-XGBoost,and CART,respectively,compared to the 98.46%RB5 removal rate observed experimentally under optimum conditions:approximately 20 mA/cm^(2) of current density,20 min of electrolysis time,and 65 mg/L of RB5.The optimised mineralisation efficiencies ranged between 89%and 92%for different models based on total organic carbon(TOC).Experimental studies confirmed that the predictive efficiency of optimised models ranked in the descending order of hybrid ANN-XGBoost,CCD-NPRSM,and CART.Model validation using analysis of variance(ANOVA)revealed that hybrid ANN-XGBoost had a mean squared error(MSE)and a coefficient of determination(R^(2))of approximately 0.014 and 0.998,respectively,for the RB5 removal efficiency,outperforming CCD-NPRSM with MSE and R^(2) of 0.518 and 0.998,respectively.Overall,the hybrid ANN-XGBoost approach is the most feasible technique for assessing the electrochemical treatment efficiency in RB5 dye wastewater decolourisation.
基金supported by ANR-ASTRID NANOFLY(ANR-19-ASTR-0023)and French AID(Defense Innovation Agency).
文摘This article presents the design of a microfabricated bio-inspired flapping-wing Nnano Aaerial Vvehicle(NAV),driven by an electromagnetic system.Our approach is based on artificial wings composed of rigid bodies connected by compliant links,which optimise aerodynamic forces though replicating the complex wing kinematics of insects.The originality of this article lies in a new design methodology based on a triple equivalence between a 3D model,a multibody model,and a mass/spring model(0D)which reduces the number of parameters in the problem.This approach facilitates NAV optimisation by using only the mass/spring model,thereby simplifying the design process while maintaining high accuracy.Two wing geometries are studied and optimised in this article to produce large-amplitude wing motions(approximately 40^\circ),and enabling flapping and twisting motion in quadrature.The results are validated thanks to experimental measurements for the large amplitude and through finite element simulations for the combined motion,confirming the effectiveness of this strategy for a NAV weighing less than 40 mg with a wingspan of under 3 cm.
文摘This paper presents an investigation of the tribological performance of AA2024–B_(4)C composites,with a specific focus on the influence of reinforcement and processing parameters.In this study three input parameters were varied:B_(4)C weight percentage,milling time,and normal load,to evaluate their effects on two output parameters:wear loss and the coefficient of friction.AA2024 alloy was used as the matrix alloy,while B_(4)C particles were used as reinforcement.Due to the high hardness and wear resistance of B_(4)C,the optimized composite shows strong potential for use in aerospace structural elements and automotive brake components.The optimisation of tribological behaviour was conducted using a Taguchi-Grey Relational Analysis(Taguchi-GRA)and the Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS).A total of 27 combinations of input parameters were analysed,varying the B_(4)C content(0,10,and 15 wt.%),milling time(0,15,and 25 h),and normal load(1,5,and 10 N).Wear loss and the coefficient of friction were numerically evaluated and selected as criteria for optimisation.Artificial Neural Networks(ANNs)were also applied for two outputs simultaneously.TOPSIS identified Alternative 1 as the optimal solution,confirming the results obtained using the Taguchi Grey method.The optimal condition obtained(10 wt.%B_(4)C,25 h milling time,10 N load)resulted in a minimum wear loss of 1.7 mg and a coefficient of friction of 0.176,confirming significant enhancement in tribological behaviour.Based on the results,both the B_(4)C content and the applied processing conditions have a significant impact on wear loss and frictional properties.This approach demonstrates high reliability and confidence,enabling the design of future composite materials with optimal properties for specific applications.
基金supported by the Artificial Intelligence Innovation Project of Wuhan Science and Technology Bureau,2023010402040016the Natural Science Foundation of Hubei Province of China,2022CFB076,JSPS KAKENHI,JP25K15279,Natural Science Foundation of Hubei Province,2023AFB003+1 种基金the National Natural Science Foundation of China,52201363the Education Department Scientific Research Programme Project of Hubei Province of China,Q20222208.
文摘The challenge of optimising multimodal functions within high-dimensional domains constitutes a notable difficulty in evolutionary computation research.Addressing this issue,this study introduces the Deep Backtracking Bare-Bones Particle Swarm Optimisation(DBPSO)algorithm,an innovative approach built upon the integration of the Deep Memory Storage Mechanism(DMSM)and the Dynamic Memory Activation Strategy(DMAS).The DMSM enhances the memory retention for the globally optimal particle,promoting interaction between standard particles and their historically optimal counterparts.In parallel,DMAS assures the updated position of the globally optimal particle is appropriately aligned with the deep memory repository.The efficacy of DBPSO was rigorously assessed through a series of simulations employing the CEC2017 benchmark suite.A comparative analysis juxtaposed DBPSO's performance against five contemporary evolutionary algorithms across two experimental conditions:Dimension-50 and Dimension-100.In the 50D trials,DBPSO attained an average ranking of 2.03,whereas in the 100D scenarios,it improved to an average ranking of 1.9.Further examination utilising the CEC2019 benchmark functions revealed DBPSO's robustness,securing four first-place finishes,three second-place standings,and three third-place positions,culminating in an unmatched average ranking of 1.9 across all algorithms.These empirical results corroborate DBPSO's proficiency in delivering precise solutions for complex,high-dimensional optimisation challenges.
基金National Natural Science Foundation of China under Grant Nos.51675525 and 11725211.
文摘A general and new explicit isogeometric topology optimisation approach with moving morphable voids(MMV)is proposed.In this approach,a novel multiresolution scheme with two distinct discretisation levels is developed to obtain high-resolution designs with a relatively low computational cost.Ersatz material model based on Greville abscissae collocation scheme is utilised to represent both the Young’s modulus of the material and the density field.Two benchmark examples are tested to illustrate the effectiveness of the proposed method.Numerical results show that high-resolution designs can be obtained with relatively low computational cost,and the optimisation can be significantly improved without introducing additional DOFs.
文摘This paper presents an optimisatiombased verification process for obstacle avoidance systems of a unicycle-like mobile robot. It is a novel approach for the collision avoidance verification process. Local and global optimisation based verification processes are developed to find the worst-case parameters and the worst-case distance between the robot and an obstacle. The kinematic and dynamic model of the unicycle-like mobile robot is first introduced with force and torque as the inputs. The design of the control system is split into two parts. One is velocity and rotation using the robot dynamics, and the other is the incremental motion planning for robot kinematics. The artificial potential field method is chosen as a path planning and obstacle avoidance candidate technique for verification study as it is simple and widely used. Different optimisation algorithms are applied and compared for the purpose of verification. It is shown that even for a simple case study where only mass and inertia variations are considered, a local optimization based verification method may fail to identify the worst case. Two global optimisation methods have been investigated： genetic algorithms （GAs） and GLOBAL algorithms. Both of these methods successfully find the worst case. The verification process confirms that the obstacle avoidance algorithm functions correctly in the presence of all the possible parameter variations.
文摘针对无线体域网(Wireless Body Area Network,WBAN)面临的能源供应限制和数据时效性不足问题,文中设计了一种基于无线供能体域网(Wireless-powered Body Area Network,WP-BAN)的传输优化策略。对WP-BAN进行系统建模,考虑了基于马尔可夫的数据采集传输过程、能量供应与消耗过程以及信息年龄(Age-of-Information,AoI)增长过程,并在队列稳定性约束和链路容量约束下构建一个关于数据采样速率与数据丢弃率系统效用最大化的离散时间随机优化问题。运用Lyapunov优化理论将原问题转化为单时隙多序列的确定性优化问题,设计了效用最大化的传输调度和能量收集策略(Utility-maximization Transmission Scheduling and Energy Harvesting Strategy,UMTEHS)。在Lyapunov求解框架下使用BARON(Branch and Reduce Optimization Navigator)求解器求解转化后的优化问题,根据当前时刻的队列状态优化下一个时刻的数据传输调度和能量收集率。仿真实验验证了所提策略的有效性,其在保持系统能量中性运行的同时能够获得更大的系统效用和更小的AoI。
文摘Self-piercing riveting(SPR)is a cold forming technique used to fasten together two or more sheets of materials with a rivet without the need to predrill a hole.The application of SPR in the automotive sector has become increasingly popular mainly due to the growing use of lightweight materials in transportation applications.However,SPR joining of these advanced light materials remains a challenge as these materials often lack a good combination of high strength and ductility to resist the large plastic deformation induced by the SPR process.In this paper,SPR joints of advanced materials and their corresponding failure mechanisms are discussed,aiming to provide the foundation for future improvement of SPR joint quality.This paper is divided into three major sections:1)joint failures focusing on joint defects originated from the SPR process and joint failure modes under different mechanical loading conditions,2)joint corrosion issues,and 3)joint optimisation via process parameters and advanced techniques.
文摘In the present study, we developed a multi-component one-dimensional mathematical model for simulation and optimisation of a commercial catalytic slurry reactor for the direct synthesis of dimethyl ether （DME） from syngas and CO2, operating in a churn-turbulent regime. DME productivity and CO conversion were optimised by tuning operating conditions, such as superficial gas velocity, catalyst concentration, catalyst mass over molar gas flow rate （W/F）, syngas composition, pressure and temperature. Reactor modelling was accomplished utilising mass balance, global kinetic models and heterogeneous hydrodynamics. In the heterogeneous flow regime, gas was distributed into two bubble phases： small and large. Simulation results were validated using data obtained from a pilot plant. The developed model is also applicable for the design of large-scale slurry reactors.
基金partially supported by YUTP-FRG funded by PETRONAS
文摘This paper presents the effect of mooring diameters, fairlead slopes and pretensions on the dynamic responses of a truss spar platform in intact and damaged line conditions. The platform is modelled as a rigid body with three degrees-of-freedom and its motions are analysed in time-domain using the implicit Newmark Beta technique. The mooring restoring force-excursion relationship is evaluated using quasi-static approach. MATLAB codes DATSpar and QSAML, are developed to compute the dynamic responses of truss spar platform and to determine the mooring system stiffness. To eliminate the conventional trial and error approach in the mooring system design, a numerical tool is also developed and described in this paper for optimising the mooring configuration. It has a graphical user interface and includes regrouping particle swarm optimisation technique combined with DATSpar and QSAML. A case study of truss spar platform with ten mooring lines is analysed using this numerical tool. The results show that optimum mooring system design benefits the oil and gas industry to economise the project cost in terms of material, weight, structural load onto the platform as well as manpower requirements. This tool is useful especially for the preliminary design of truss spar platforms and its mooring system.
基金National Natural Science Foundation of China,Grant/Award Number:51677059。
文摘Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electricity market transactions.Therefore,the carbon trading market is introduced into the wind power market,and a new form of low-carbon economic dispatch model is developed.First,the economic dispatch goal of wind power is be considered.It is projected to save money and reduce the cost of power generation for the system.The model includes risk operating costs to account for the impact of wind power output variability on the system,as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment.The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions,and analyze the impact of different carbon trading prices on the system.A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals.Finally,the solution is optimised using the Ant-lion optimisation method,which combines Levi's flight mechanism and golden sine.The proposed model and algorithm's rationality is proven through the use of cases.
基金the management of Bharat Heavy Electricals Ltd., for funding this research programme
文摘Creep strength enhanced ferritic(CSEF) steels are used in advanced power plant systems for high temperature applications. P92(Cr–W–Mo–V)steel, classified under CSEF steels, is a candidate material for piping, tubing, etc., in ultra-super critical and advanced ultra-super critical boiler applications. In the present work, laser welding process has been optimised for P92 material by using Taguchi based grey relational analysis(GRA).Bead on plate(BOP) trials were carried out using a 3.5 k W diffusion cooled slab CO_2 laser by varying laser power, welding speed and focal position. The optimum parameters have been derived by considering the responses such as depth of penetration, weld width and heat affected zone(HAZ) width. Analysis of variance(ANOVA) has been used to analyse the effect of different parameters on the responses. Based on ANOVA, laser power of 3 k W, welding speed of 1 m/min and focal plane at-4 mm have evolved as optimised set of parameters. The responses of the optimised parameters obtained using the GRA have been verified experimentally and found to closely correlate with the predicted value.? 2016 China Ordnance Society. Production and hosting by Elsevier B.V. All rights reserved.
基金supported in part by the National Key Research and Development Program of China under Grant 2019YFB2102102in part by the National Natural Science Foundations of China under Grant 62176094 and Grant 61873097+2 种基金in part by the Key‐Area Research and Development of Guangdong Province under Grant 2020B010166002in part by the Guangdong Natural Science Foundation Research Team under Grant 2018B030312003in part by the Guangdong‐Hong Kong Joint Innovation Platform under Grant 2018B050502006.
文摘Research into automatically searching for an optimal neural network(NN)by optimi-sation algorithms is a significant research topic in deep learning and artificial intelligence.However,this is still challenging due to two issues:Both the hyperparameter and ar-chitecture should be optimised and the optimisation process is computationally expen-sive.To tackle these two issues,this paper focusses on solving the hyperparameter and architecture optimization problem for the NN and proposes a novel light‐weight scale‐adaptive fitness evaluation‐based particle swarm optimisation(SAFE‐PSO)approach.Firstly,the SAFE‐PSO algorithm considers the hyperparameters and architectures together in the optimisation problem and therefore can find their optimal combination for the globally best NN.Secondly,the computational cost can be reduced by using multi‐scale accuracy evaluation methods to evaluate candidates.Thirdly,a stagnation‐based switch strategy is proposed to adaptively switch different evaluation methods to better balance the search performance and computational cost.The SAFE‐PSO algorithm is tested on two widely used datasets:The 10‐category(i.e.,CIFAR10)and the 100−cate-gory(i.e.,CIFAR100).The experimental results show that SAFE‐PSO is very effective and efficient,which can not only find a promising NN automatically but also find a better NN than compared algorithms at the same computational cost.
基金funding for this work from NSF-CMMI 2009270 and EPSRC EP/V034391/1.
文摘The paper studies stochastic dynamics of a two-degree-of-freedom system,where a primary linear system is connected to a nonlinear energy sink with cubic stiffness nonlinearity and viscous damping.While the primary mass is subjected to a zero-mean Gaussian white noise excitation,the main objective of this study is to maximise the efficiency of the targeted energy transfer in the system.A surrogate optimisation algorithm is proposed for this purpose and adopted for the stochastic framework.The optimisations are conducted separately for the nonlinear stiffness coefficient alone as well as for both the nonlinear stiffness and damping coefficients together.Three different optimisation cost functions,based on either energy of the system’s components or the dissipated energy,are considered.The results demonstrate some clear trends in values of the nonlinear energy sink coefficients and show the effect of different cost functions on the optimal values of the nonlinear system’s coefficients.
基金the Department of Industry and Science,Australian Government for funding this researchthe management and staff of Glencore Bulga Underground Operations for their significant contributions in this project
文摘Computational fluid dynamics(CFD) simulation is an effective approach to develop and optimise gas drainage design for underground longwall coal mining. As part of the project supported by the Australian Government Coal Mining Abatement Technology Support Package(CMATSP), threedimensional CFD simulations were conducted to test and optimise a conceptual design which proposes using horizontal boreholes to replace vertical boreholes at an underground coal mine in Australia.Drainage performance between a vertical borehole and a horizontal borehole was first carried out to compare their capacity and effectiveness. Then a series of cases with different horizontal borehole designs were simulated to optimise borehole configuration parameters such as location, diameter, and number of boreholes. The study shows that the horizontal borehole is able to create low pressure sinks that protect the workings from goaf gas ingresses by changing goaf gas flow directions, and that it has the advantage to continuously maintain such low pressure sinks near the tailgate as the longwall advances. An example of optimising horizontal borehole locations in the longwall lateral direction is also given in this paper.
文摘Two uncoupleable distributions, assigning missions to robots and allocating robots to home stations, accompany the use ofmobile service robots in hospitals.In the given problem, two workload-related objectives and five groups of constraints areproposed.A bio-mimicked Binary Bees Algorithm (BBA) is introduced to solve this multiobjective multiconstraint combinatorialoptimisation problem, in which constraint handling technique (Multiobjective Transformation, MOT), multiobjectiveevaluation method (nondominance selection), global search strategy (stochastic search in the variable space), local searchstrategy (Hamming neighbourhood exploitation), and post-processing means (feasibility selection) are the main issues.TheBBA is then demonstrated with a case study, presenting the execution process of the algorithm, and also explaining the change ofelite number in evolutionary process.Its optimisation result provides a group of feasible nondominated two-level distributionschemes.
文摘The optimisation of earthquake resistance of high buildings by multi-tuned mass dampers was investigated using bionic algorithms. In bionic or evolutionary optimisation studies the properties of parents are crossed and mutated to produce a new generation with slightly different properties. The kids which best satisfy the object of the study, become the parents of the next generation. After a series of generations essential improvements of the object may be observed. Tuned mass dampers are widely used to reduce the impact of dynamic excitations on structures. A single mass system and multi-mass oscillators help to explain the mechanics of the dampers. To apply the bionic optimisation strategy to high buildings with passive tuned mass dampers subject to seismic loading a special beam element has been developed. In addition to the 6 degrees of freedom of a conventional beam element, it has 2 degrees of freedom for the displacements of the dampers. It allows for fast studies of many variants. As central result, efficient designs for damping systems along the height of an edifice are found. The impact on the structure may be reduced essentially by the use of such dampers designed to interact in an optimal way.
