Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems.This study presents a new optimization method based on an unu...Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems.This study presents a new optimization method based on an unusual geological phenomenon in nature,named Geyser inspired Algorithm(GEA).The mathematical modeling of this geological phenomenon is carried out to have a better understanding of the optimization process.The efficiency and accuracy of GEA are verified using statistical examination and convergence rate comparison on numerous CEC 2005,CEC 2014,CEC 2017,and real-parameter benchmark functions.Moreover,GEA has been applied to several real-parameter engineering optimization problems to evaluate its effectiveness.In addition,to demonstrate the applicability and robustness of GEA,a comprehensive investigation is performed for a fair comparison with other standard optimization methods.The results demonstrate that GEA is noticeably prosperous in reaching the optimal solutions with a high convergence rate in comparison with other well-known nature-inspired algorithms,including ABC,BBO,PSO,and RCGA.Note that the source code of the GEA is publicly available at https://www.optim-app.com/projects/gea.展开更多
Electrolyte design strategies are closely related to the capacities, cycle life and safety of sodium–ion batteries. In this study, we aimed to optimize electrolyte with the focus on engineering aspects. The basic phy...Electrolyte design strategies are closely related to the capacities, cycle life and safety of sodium–ion batteries. In this study, we aimed to optimize electrolyte with the focus on engineering aspects. The basic physicochemical properties including ionic conductivity, viscosity,wettability and thermochemical stability of the electrolytes using Na PF6 as the solute and the mixed solvent with different components of EMC,DMC or DEC in PC or EC were systematically measured. Ah pouch cell with NaNi_(1/3)Fe_(1/3)Mn_(1/3)O_(2)/hard carbon electrodes was used to evaluate the performance of the prepared electrolytes. By using the Inductive Coupled Plasma Emission Spectrometer(ICP), X-ray photoelectron spectroscopy(XPS), Thermogravimetric-differential scanning calorimetry(TG-DSC) and Accelerating Rate Calorimeter(ARC), we show that an optimized electrolyte can effectively promote the formation of a protective interfacial layer on two electrodes, which not only retards parasitic reactions between the electrodes and electrolyte but also suppresses dissolution of metal ions from the cathode. With an optimized electrolyte, a NaNi_(1/3)Fe_(1/3)Mn_(1/3)O_(2)/hard carbon cell can attain 56.16% capacity retention under the low temperature of -40℃, and can be able to retain 80%capacity retention after more than 2500 cycles while presenting excellent thermal safety.展开更多
The particle swarm optimization(PSO)algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and sh.PSO is essentially an unconstrained algorithm...The particle swarm optimization(PSO)algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and sh.PSO is essentially an unconstrained algorithm and requires constraint handling techniques(CHTs)to solve constrained optimization problems(COPs).For this purpose,we integrate two CHTs,the superiority of feasibility(SF)and the violation constraint-handling(VCH),with a PSO.These CHTs distinguish feasible solutions from infeasible ones.Moreover,in SF,the selection of infeasible solutions is based on their degree of constraint violations,whereas in VCH,the number of constraint violations by an infeasible solution is of more importance.Therefore,a PSO is adapted for constrained optimization,yielding two constrained variants,denoted SF-PSO and VCH-PSO.Both SF-PSO and VCH-PSO are evaluated with respect to ve engineering problems:the Himmelblau’s nonlinear optimization,the welded beam design,the spring design,the pressure vessel design,and the three-bar truss design.The simulation results show that both algorithms are consistent in terms of their solutions to these problems,including their different available versions.Comparison of the SF-PSO and the VCHPSO with other existing algorithms on the tested problems shows that the proposed algorithms have lower computational cost in terms of the number of function evaluations used.We also report our disagreement with some unjust comparisons made by other researchers regarding the tested problems and their different variants.展开更多
Farmland Fertility Algorithm(FFA)is a recent nature-inspired metaheuristic algorithm for solving optimization problems.Nevertheless,FFA has some drawbacks:slow convergence and imbalance of diversification(exploration)...Farmland Fertility Algorithm(FFA)is a recent nature-inspired metaheuristic algorithm for solving optimization problems.Nevertheless,FFA has some drawbacks:slow convergence and imbalance of diversification(exploration)and intensification(exploitation).An adaptive mechanism in every algorithm can achieve a proper balance between exploration and exploitation.The literature shows that chaotic maps are incorporated into metaheuristic algorithms to eliminate these drawbacks.Therefore,in this paper,twelve chaotic maps have been embedded into FFA to find the best numbers of prospectors to increase the exploitation of the best promising solutions.Furthermore,the Quasi-Oppositional-Based Learning(QOBL)mechanism enhances the exploration speed and convergence rate;we name a CQFFA algorithm.The improvements have been made in line with the weaknesses of the FFA algorithm because the FFA algorithm has fallen into the optimal local trap in solving some complex problems or does not have sufficient ability in the intensification component.The results obtained show that the proposed CQFFA model has been significantly improved.It is applied to twenty-three widely-used test functions and compared with similar state-of-the-art algorithms statistically and visually.Also,the CQFFA algorithm has evaluated six real-world engineering problems.The experimental results showed that the CQFFA algorithm outperforms other competitor algorithms.展开更多
Due to the importance and role of systems engineering in space mission developments, optimization of Omid＇s systems engineering as a milestone to its current and future generations is focused. In this regard systems ...Due to the importance and role of systems engineering in space mission developments, optimization of Omid＇s systems engineering as a milestone to its current and future generations is focused. In this regard systems engineering management organization as the basis of optimization work flow in the conceptual design phase is proposed for improvement. To improve the systems engineering management, an agile enhanced organization chart is developed that defines various system duties. This is a type of concurrent engineering approach that promotes direct communication and data interchange between the team members. Due to the importance of decision making in the conceptual design phase, two design matrices are constructed that portray merits of various design options in terms of improved satellite life as well as specific choices of remote sensing capability for the Omid second generation（Omid-2）. Conceptual design optimization is explored considering several structural objectives as well as optimal solar energy absorption utilizing a multiple criteria decision making approach. The Eigenvector method is utilized to formulate the objective function via expert judgment. This approach is robust with respect to designer probable miss-judgment. The optimized version of Omid-2 turned out to be a passive Z-axis spin stabilized satellite made of hexagonal honeycomb configuration with carbon-epoxy side panels and Aluminum bottom plate.展开更多
The Bald Eagle Search algorithm(BES)is an emerging meta-heuristic algorithm.The algorithm simulates the hunting behavior of eagles,and obtains an optimal solution through three stages,namely selection stage,search sta...The Bald Eagle Search algorithm(BES)is an emerging meta-heuristic algorithm.The algorithm simulates the hunting behavior of eagles,and obtains an optimal solution through three stages,namely selection stage,search stage and swooping stage.However,BES tends to drop-in local optimization and the maximum value of search space needs to be improved.To fill this research gap,we propose an improved bald eagle algorithm(CABES)that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima.Firstly,CABES introduces the Cauchy mutation strategy to adjust the step size of the selection stage,to select a better search range.Secondly,in the search stage,CABES updates the search position update formula by an adaptive weight factor to further promote the local optimization capability of BES.To verify the performance of CABES,the benchmark function of CEC2017 is used to simulate the algorithm.The findings of the tests are compared to those of the Particle Swarm Optimization algorithm(PSO),Whale Optimization Algorithm(WOA)and Archimedes Algorithm(AOA).The experimental results show that CABES can provide good exploration and development capabilities,and it has strong competitiveness in testing algorithms.Finally,CABES is applied to four constrained engineering problems and a groundwater engineeringmodel,which further verifies the effectiveness and efficiency of CABES in practical engineering problems.展开更多
As optimization problems continue to grow in complexity,the need for effective metaheuristic algorithms becomes increasingly evident.However,the challenge lies in identifying the right parameters and strategies for th...As optimization problems continue to grow in complexity,the need for effective metaheuristic algorithms becomes increasingly evident.However,the challenge lies in identifying the right parameters and strategies for these algorithms.In this paper,we introduce the adaptive multi-strategy Rabbit Algorithm(RA).RA is inspired by the social interactions of rabbits,incorporating elements such as exploration,exploitation,and adaptation to address optimization challenges.It employs three distinct subgroups,comprising male,female,and child rabbits,to execute a multi-strategy search.Key parameters,including distance factor,balance factor,and learning factor,strike a balance between precision and computational efficiency.We offer practical recommendations for fine-tuning five essential RA parameters,making them versatile and independent.RA is capable of autonomously selecting adaptive parameter settings and mutation strategies,enabling it to successfully tackle a range of 17 CEC05 benchmark functions with dimensions scaling up to 5000.The results underscore RA’s superior performance in large-scale optimization tasks,surpassing other state-of-the-art metaheuristics in convergence speed,computational precision,and scalability.Finally,RA has demonstrated its proficiency in solving complicated optimization problems in real-world engineering by completing 10 problems in CEC2020.展开更多
The Bat algorithm,a metaheuristic optimization technique inspired by the foraging behaviour of bats,has been employed to tackle optimization problems.Known for its ease of implementation,parameter tunability,and stron...The Bat algorithm,a metaheuristic optimization technique inspired by the foraging behaviour of bats,has been employed to tackle optimization problems.Known for its ease of implementation,parameter tunability,and strong global search capabilities,this algorithm finds application across diverse optimization problem domains.However,in the face of increasingly complex optimization challenges,the Bat algorithm encounters certain limitations,such as slow convergence and sensitivity to initial solutions.In order to tackle these challenges,the present study incorporates a range of optimization compo-nents into the Bat algorithm,thereby proposing a variant called PKEBA.A projection screening strategy is implemented to mitigate its sensitivity to initial solutions,thereby enhancing the quality of the initial solution set.A kinetic adaptation strategy reforms exploration patterns,while an elite communication strategy enhances group interaction,to avoid algorithm from local optima.Subsequently,the effectiveness of the proposed PKEBA is rigorously evaluated.Testing encompasses 30 benchmark functions from IEEE CEC2014,featuring ablation experiments and comparative assessments against classical algorithms and their variants.Moreover,real-world engineering problems are employed as further validation.The results conclusively demonstrate that PKEBA ex-hibits superior convergence and precision compared to existing algorithms.展开更多
In recent years,with the increasing demand for social production,engineering design problems have gradually become more and more complex.Many novel and well-performing meta-heuristic algorithms have been studied and d...In recent years,with the increasing demand for social production,engineering design problems have gradually become more and more complex.Many novel and well-performing meta-heuristic algorithms have been studied and developed to cope with this problem.Among them,the Spherical Evolutionary Algorithm(SE)is one of the classical representative methods that proposed in recent years with admirable optimization performance.However,it tends to stagnate prematurely to local optima in solving some specific problems.Therefore,this paper proposes an SE variant integrating the Cross-search Mutation(CSM)and Gaussian Backbone Strategy(GBS),called CGSE.In this study,the CSM can enhance its social learning ability,which strengthens the utilization rate of SE on effective information;the GBS cooperates with the original rules of SE to further improve the convergence effect of SE.To objectively demonstrate the core advantages of CGSE,this paper designs a series of global optimization experiments based on IEEE CEC2017,and CGSE is used to solve six engineering design problems with constraints.The final experimental results fully showcase that,compared with the existing well-known methods,CGSE has a very significant competitive advantage in global tasks and has certain practical value in real applications.Therefore,the proposed CGSE is a promising and first-rate algorithm with good potential strength in the field of engineering design.展开更多
Completing the principal engineering components of a pumped storage power station spans between 50 and 60 months,from the inception of construction to the commencement of power generation by the first unit.The filling...Completing the principal engineering components of a pumped storage power station spans between 50 and 60 months,from the inception of construction to the commencement of power generation by the first unit.The filling of the penstock with water represents a critical phase preceding the production of electricity by the first unit.During this interval,the construction of the diversion shaft presents multiple challenges,including intricate construction procedures,considerable construction difficulty,elevated safety risks,and quality control issues.To address this issue,this study uses CFD software to analyze the flow field,pressure gradient,and head loss of shaft curved section with different curvature radius,and examines several key technologies by drawing on the practice of diversion shaft construction at the Meizhou pumped storage power station.These technologies include optimizing the curvature radius of the curved section of diversion shaft,reverse-well excavation for the shaft,and sliding-up for the lining concrete.It is found that as the curvature radius of shaft curved section reduces from 4 to 2 times the shaft diameter,the hydraulic characteristic index does not change much,and the increase of head loss accounts for about 0.18%of the total head loss of the water conveyance system.The result show that optimizing the curvature radius from 4 times to 2 times the shaft diameter is feasible and reasonable,and several improved technical measures have been proposed,such as stabilizing drill rods,mechanical scraper systems,and control technology of the relationship between concrete setting time and formwork sliding.Their implementation effectively mitigates difficulties and safety risks during shaft construction,expedites the project schedule,enhances engineering quality,and creates a 41-month timeline for the principal engineering schedule for the first power unit generation in China.展开更多
In recent years, with the development of technologies such as the Internet of Things(Io T), big data and cloud computing, digital twin technology has gradually been applied in marine research. The digital twin realize...In recent years, with the development of technologies such as the Internet of Things(Io T), big data and cloud computing, digital twin technology has gradually been applied in marine research. The digital twin realizes real-time monitoring, analysis and optimization of the state and behavior of a physical object or system by creating a virtual model. Research shows that digital twin technology has extensive application potential in ship design, marine resource development, marine equipment engineering design and optimization, marine ecological protection and early warning of disasters. Although digital twin technology has great potential in marine research, it also faces many challenges, including the complexity of data acquisition and processing, the accuracy and real-time performance of model construction, and the need for multidisciplinary cross-integration. An in-depth analysis of the technical bottlenecks and future development directions will provide an important reference for subsequent research and promote the further application and development of digital twin technology in marine research.展开更多
Purpose–The paper aims to clarify the operation rationality of high speed trains(HSTs)under tunnel condition with the speed of 400 km/h through representative aerodynamic factors including running drag,eardrum comfor...Purpose–The paper aims to clarify the operation rationality of high speed trains(HSTs)under tunnel condition with the speed of 400 km/h through representative aerodynamic factors including running drag,eardrum comfort,carriages noise,aerodynamic loads on tunnel ancillary facilities and HST,micro-pressure waves,and then put forward engineering suggestions for higher speed tunnel operation based on the analysis.Design/methodology/approach–Based on the field measurement data of CR400AF-C and CR400BF-J tunnel operation,correlations between each aerodynamic indicators with HST speed were established.By analyzing the safety reserve of aerodynamic indicators at 350 km/h and the sensitivity of each indicator to HST speed increasing and the indicators’formation mechanism,the coupling relationship between various indicators was obtained.Findings–The sensitivity of different aerodynamic indicators to speed variation differed.The aerodynamic indicators representing flow field around HST showed a linear relationship with HST speed including noise,eardrum comfort,aerodynamic load on HST body.The positive aerodynamic load on tunnel auxiliary facilities and the micro-pressure wave at the entrance of the tunnel have the same sensitivity to the 3th-power relation of HST speed.The over-limit proportion of micro-pressure wave was the highest among the indicators,and aerodynamic buffering measures were recommended for optimization.The open tunnel pressure relief structure is recommended,while allowing trains to pass through the tunnel at an unconditional speed of 380 km/h.Originality/value–Comprehensive evaluation of multiple aerodynamic indicators for HST tunnel operation with higher speeds was realized.The main engineering requirements to release aerodynamic effect were identified and the optimization scheme is proposed.展开更多
Chemical process optimization can be described as large-scale nonlinear constrained minimization. The modified augmented Lagrange multiplier methods (MALMM) for large-scale nonlinear constrained minimization are studi...Chemical process optimization can be described as large-scale nonlinear constrained minimization. The modified augmented Lagrange multiplier methods (MALMM) for large-scale nonlinear constrained minimization are studied in this paper. The Lagrange function contains the penalty terms on equality and inequality constraints and the methods can be applied to solve a series of bound constrained sub-problems instead of a series of unconstrained sub-problems. The steps of the methods are examined in full detail. Numerical experiments are made for a variety of problems, from small to very large-scale, which show the stability and effectiveness of the methods in large-scale problems.展开更多
Many engineering optimization problems frequently encounter continuous variables and discrete variables which adds considerably to the solution complexity. Very few of the existing methods can yield a globally optimal...Many engineering optimization problems frequently encounter continuous variables and discrete variables which adds considerably to the solution complexity. Very few of the existing methods can yield a globally optimal solution when the objective functions are non-convex and non-differentiable. This paper presents a hybrid swarm intelligence ap-proach (HSIA) for solving these nonlinear optimization problems which contain integer, discrete, zero-one and continuous variables. HSIA provides an improvement in global search reliability in a mixed-variable space and converges steadily to a good solution. An approach to handle various kinds of variables and constraints is discussed. Comparison testing of several examples of mixed-variable optimization problems in the literature showed that the proposed approach is superior to current methods for finding the best solution, in terms of both solution quality and algorithm robustness.展开更多
This paper introduces an optimization algorithm, the hummingbirds optimization algorithm(HOA), which is inspired by the foraging process of hummingbirds. The proposed algorithm includes two phases: a self-searching ph...This paper introduces an optimization algorithm, the hummingbirds optimization algorithm(HOA), which is inspired by the foraging process of hummingbirds. The proposed algorithm includes two phases: a self-searching phase and a guide-searching phase. With these two phases, the exploration and exploitation abilities of the algorithm can be balanced. Both the constrained and unconstrained benchmark functions are employed to test the performance of HOA. Ten classic benchmark functions are considered as unconstrained benchmark functions. Meanwhile, two engineering design optimization problems are employed as constrained benchmark functions. The results of these experiments demonstrate HOA is efficient and capable of global optimization.展开更多
Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsu...Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved.展开更多
Both the seat and cab system of truck play a vital role in ride comfort.The damping matching methods of the two systems are studied separately at present.However,the driver,seat,and cab system are one inseparable whol...Both the seat and cab system of truck play a vital role in ride comfort.The damping matching methods of the two systems are studied separately at present.However,the driver,seat,and cab system are one inseparable whole.In order to further improve ride comfort,the seat suspension is regarded as the fifth suspension of the cab,a new idea of ＂Five-suspensions＂ is proposed.Based on this idea,a 4 degree-of-freedom driver-seat-cab coupled system model is presented.Using the tested cab suspensions excitations as inputs and seat acceleration response as compared output,the simulation model is built.Taking optimal ride comfort as target,a new method of damping collaborative optimization for Five-suspensions is proposed.With a practical example of seat and cab system,the damping parameters are optimized and validated by simulation and bench test.The results show the seat vertical frequency-weighted RMS acceleration values tested for the un-optimized and optimized Five-suspensions are 0.50 m/s～2 and 0.39 m/s～2,respectively,with a decrease by 22.0%,which proves the model and method proposed are correct and reliable.The idea of ＂Five-suspensions＂ and the method proposed provide a reference for achieving global optimal damping matching of seat suspension and cab suspensions.展开更多
In underground mining by sublevel caving method, the deformation and damage of the surface induced by subsidence are the major challenging issues. The dynamic and soft backflling body increases the safety risks in the...In underground mining by sublevel caving method, the deformation and damage of the surface induced by subsidence are the major challenging issues. The dynamic and soft backflling body increases the safety risks in the subsiding area. In this paper, taking Zhangfushan iron mine as an example, the ore body and the general layout are focused on the safety of backflling of mined-out area. Then, we use the ANSYS software to construct a three-dimensional(3D) model for the mining area in the Zhangfushan iron mine. According to the simulation results of the initial mining stages, the ore body is stoped step by step as suggested in the design. The stability of the backflling is back analyzed based on the monitored displacements, considering the stress distribution to optimize the stoping sequence. The simulations show that a reasonable stoping sequence can minimize the concentration of high compressive stress and ensure the safety of stoping of the ore body.展开更多
Crude oil distillation is important in refining industry. Operating variables of distillation process have a critical effect on product output value and energy consumption. However, the objectives of minimum energy co...Crude oil distillation is important in refining industry. Operating variables of distillation process have a critical effect on product output value and energy consumption. However, the objectives of minimum energy consumption and maximum product output value do not coordinate with each other and do not lead to the maximum economic benefit of a refinery. In this paper, a systematic optimization approach is proposed for the maximum annual economic benefit of an existing crude oil distillation system, considering product output value and energy consumption simultaneously. A shortcut model in Aspen Plus is used to describe the crude oil distillation and the pinch analysis is adopted to identify the target of energy recovery. The optimization is a nonlinear programming problem and solved by stochastic algorithm of particle warm optimization.展开更多
In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective op...In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective optimization has been proposed as an efficient method for human-centered manufacturing. However, previous vast researches on optimization have been mainly focused on optimization theory and optimization techniques and paid little interests on the process of problem formulation itself. In this paper, therefore, the authors present a total framework for supporting multi-objective decision making. Then, the authors try to solve the formulated multi-objective optimization problem that involves both qualitative and quantitative performance measures as a general consequence from the above procedure. Taking especially quality as a qualitative measure, the authors gave a new idea to evaluate the quality quantitatively. Additionally, to facilitate the portability of the proposed method in multidisciplinary decision-making environments, the authors implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the approach through a case study.展开更多
文摘Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems.This study presents a new optimization method based on an unusual geological phenomenon in nature,named Geyser inspired Algorithm(GEA).The mathematical modeling of this geological phenomenon is carried out to have a better understanding of the optimization process.The efficiency and accuracy of GEA are verified using statistical examination and convergence rate comparison on numerous CEC 2005,CEC 2014,CEC 2017,and real-parameter benchmark functions.Moreover,GEA has been applied to several real-parameter engineering optimization problems to evaluate its effectiveness.In addition,to demonstrate the applicability and robustness of GEA,a comprehensive investigation is performed for a fair comparison with other standard optimization methods.The results demonstrate that GEA is noticeably prosperous in reaching the optimal solutions with a high convergence rate in comparison with other well-known nature-inspired algorithms,including ABC,BBO,PSO,and RCGA.Note that the source code of the GEA is publicly available at https://www.optim-app.com/projects/gea.
基金supported by Natural Science Foundation of China,China(21938005,21676165)Science&Technology Commission of Shanghai Municipality,China(19DZ1205500)+1 种基金Zhejiang Key Research and Development Program,China(2020C01128)National Key Research and Development Program,China(2016YFB0901500)。
文摘Electrolyte design strategies are closely related to the capacities, cycle life and safety of sodium–ion batteries. In this study, we aimed to optimize electrolyte with the focus on engineering aspects. The basic physicochemical properties including ionic conductivity, viscosity,wettability and thermochemical stability of the electrolytes using Na PF6 as the solute and the mixed solvent with different components of EMC,DMC or DEC in PC or EC were systematically measured. Ah pouch cell with NaNi_(1/3)Fe_(1/3)Mn_(1/3)O_(2)/hard carbon electrodes was used to evaluate the performance of the prepared electrolytes. By using the Inductive Coupled Plasma Emission Spectrometer(ICP), X-ray photoelectron spectroscopy(XPS), Thermogravimetric-differential scanning calorimetry(TG-DSC) and Accelerating Rate Calorimeter(ARC), we show that an optimized electrolyte can effectively promote the formation of a protective interfacial layer on two electrodes, which not only retards parasitic reactions between the electrodes and electrolyte but also suppresses dissolution of metal ions from the cathode. With an optimized electrolyte, a NaNi_(1/3)Fe_(1/3)Mn_(1/3)O_(2)/hard carbon cell can attain 56.16% capacity retention under the low temperature of -40℃, and can be able to retain 80%capacity retention after more than 2500 cycles while presenting excellent thermal safety.
基金The authors thank the Higher Education Commission,Pakistan,for supporting this research under the project NRPU-8925(M.A.J.and H.U.K.),https://www.hec.gowpk/。
文摘The particle swarm optimization(PSO)algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and sh.PSO is essentially an unconstrained algorithm and requires constraint handling techniques(CHTs)to solve constrained optimization problems(COPs).For this purpose,we integrate two CHTs,the superiority of feasibility(SF)and the violation constraint-handling(VCH),with a PSO.These CHTs distinguish feasible solutions from infeasible ones.Moreover,in SF,the selection of infeasible solutions is based on their degree of constraint violations,whereas in VCH,the number of constraint violations by an infeasible solution is of more importance.Therefore,a PSO is adapted for constrained optimization,yielding two constrained variants,denoted SF-PSO and VCH-PSO.Both SF-PSO and VCH-PSO are evaluated with respect to ve engineering problems:the Himmelblau’s nonlinear optimization,the welded beam design,the spring design,the pressure vessel design,and the three-bar truss design.The simulation results show that both algorithms are consistent in terms of their solutions to these problems,including their different available versions.Comparison of the SF-PSO and the VCHPSO with other existing algorithms on the tested problems shows that the proposed algorithms have lower computational cost in terms of the number of function evaluations used.We also report our disagreement with some unjust comparisons made by other researchers regarding the tested problems and their different variants.
文摘Farmland Fertility Algorithm(FFA)is a recent nature-inspired metaheuristic algorithm for solving optimization problems.Nevertheless,FFA has some drawbacks:slow convergence and imbalance of diversification(exploration)and intensification(exploitation).An adaptive mechanism in every algorithm can achieve a proper balance between exploration and exploitation.The literature shows that chaotic maps are incorporated into metaheuristic algorithms to eliminate these drawbacks.Therefore,in this paper,twelve chaotic maps have been embedded into FFA to find the best numbers of prospectors to increase the exploitation of the best promising solutions.Furthermore,the Quasi-Oppositional-Based Learning(QOBL)mechanism enhances the exploration speed and convergence rate;we name a CQFFA algorithm.The improvements have been made in line with the weaknesses of the FFA algorithm because the FFA algorithm has fallen into the optimal local trap in solving some complex problems or does not have sufficient ability in the intensification component.The results obtained show that the proposed CQFFA model has been significantly improved.It is applied to twenty-three widely-used test functions and compared with similar state-of-the-art algorithms statistically and visually.Also,the CQFFA algorithm has evaluated six real-world engineering problems.The experimental results showed that the CQFFA algorithm outperforms other competitor algorithms.
文摘Due to the importance and role of systems engineering in space mission developments, optimization of Omid＇s systems engineering as a milestone to its current and future generations is focused. In this regard systems engineering management organization as the basis of optimization work flow in the conceptual design phase is proposed for improvement. To improve the systems engineering management, an agile enhanced organization chart is developed that defines various system duties. This is a type of concurrent engineering approach that promotes direct communication and data interchange between the team members. Due to the importance of decision making in the conceptual design phase, two design matrices are constructed that portray merits of various design options in terms of improved satellite life as well as specific choices of remote sensing capability for the Omid second generation（Omid-2）. Conceptual design optimization is explored considering several structural objectives as well as optimal solar energy absorption utilizing a multiple criteria decision making approach. The Eigenvector method is utilized to formulate the objective function via expert judgment. This approach is robust with respect to designer probable miss-judgment. The optimized version of Omid-2 turned out to be a passive Z-axis spin stabilized satellite made of hexagonal honeycomb configuration with carbon-epoxy side panels and Aluminum bottom plate.
基金Project of Key Science and Technology of the Henan Province(No.202102310259)Henan Province University Scientific and Technological Innovation Team(No.18IRTSTHN009).
文摘The Bald Eagle Search algorithm(BES)is an emerging meta-heuristic algorithm.The algorithm simulates the hunting behavior of eagles,and obtains an optimal solution through three stages,namely selection stage,search stage and swooping stage.However,BES tends to drop-in local optimization and the maximum value of search space needs to be improved.To fill this research gap,we propose an improved bald eagle algorithm(CABES)that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima.Firstly,CABES introduces the Cauchy mutation strategy to adjust the step size of the selection stage,to select a better search range.Secondly,in the search stage,CABES updates the search position update formula by an adaptive weight factor to further promote the local optimization capability of BES.To verify the performance of CABES,the benchmark function of CEC2017 is used to simulate the algorithm.The findings of the tests are compared to those of the Particle Swarm Optimization algorithm(PSO),Whale Optimization Algorithm(WOA)and Archimedes Algorithm(AOA).The experimental results show that CABES can provide good exploration and development capabilities,and it has strong competitiveness in testing algorithms.Finally,CABES is applied to four constrained engineering problems and a groundwater engineeringmodel,which further verifies the effectiveness and efficiency of CABES in practical engineering problems.
文摘As optimization problems continue to grow in complexity,the need for effective metaheuristic algorithms becomes increasingly evident.However,the challenge lies in identifying the right parameters and strategies for these algorithms.In this paper,we introduce the adaptive multi-strategy Rabbit Algorithm(RA).RA is inspired by the social interactions of rabbits,incorporating elements such as exploration,exploitation,and adaptation to address optimization challenges.It employs three distinct subgroups,comprising male,female,and child rabbits,to execute a multi-strategy search.Key parameters,including distance factor,balance factor,and learning factor,strike a balance between precision and computational efficiency.We offer practical recommendations for fine-tuning five essential RA parameters,making them versatile and independent.RA is capable of autonomously selecting adaptive parameter settings and mutation strategies,enabling it to successfully tackle a range of 17 CEC05 benchmark functions with dimensions scaling up to 5000.The results underscore RA’s superior performance in large-scale optimization tasks,surpassing other state-of-the-art metaheuristics in convergence speed,computational precision,and scalability.Finally,RA has demonstrated its proficiency in solving complicated optimization problems in real-world engineering by completing 10 problems in CEC2020.
基金partially supported by MRC(MC_PC_17171)Royal Society(RP202G0230)+8 种基金BHF(AA/18/3/34220)Hope Foundation for Cancer Research(RM60G0680)GCRF(20P2PF11)Sino-UK Industrial Fund(RP202G0289)LIAS(20P2ED10,20P2RE969)Data Science Enhancement Fund(20P2RE237)Fight for Sight(24NN201)Sino-UK Education Fund(OP202006)BBSRC(RM32G0178B8).
文摘The Bat algorithm,a metaheuristic optimization technique inspired by the foraging behaviour of bats,has been employed to tackle optimization problems.Known for its ease of implementation,parameter tunability,and strong global search capabilities,this algorithm finds application across diverse optimization problem domains.However,in the face of increasingly complex optimization challenges,the Bat algorithm encounters certain limitations,such as slow convergence and sensitivity to initial solutions.In order to tackle these challenges,the present study incorporates a range of optimization compo-nents into the Bat algorithm,thereby proposing a variant called PKEBA.A projection screening strategy is implemented to mitigate its sensitivity to initial solutions,thereby enhancing the quality of the initial solution set.A kinetic adaptation strategy reforms exploration patterns,while an elite communication strategy enhances group interaction,to avoid algorithm from local optima.Subsequently,the effectiveness of the proposed PKEBA is rigorously evaluated.Testing encompasses 30 benchmark functions from IEEE CEC2014,featuring ablation experiments and comparative assessments against classical algorithms and their variants.Moreover,real-world engineering problems are employed as further validation.The results conclusively demonstrate that PKEBA ex-hibits superior convergence and precision compared to existing algorithms.
基金supported by MRC(MC_PC_17171)Royal Society(RP202G0230)+12 种基金BHF(AA/18/3/34220)Hope Foundation for Cancer Research(RM60G0680)GCRF(P202PF11)Sino-UK Industrial Fund(RP202G0289)LIAS(P202ED10,P202RE969)Data Science Enhancement Fund(P202RE237)Fight for Sight(24NN201)Sino-UK Education Fund(OP202006)BBSRC(RM32G0178B8)Natural Science Foundation of Zhejiang Province(LZ22F020005)National Natural Science Foundation of China(62076185)The 18th batch of innovative and entrepreneurial talent funding projects in Jilin Province(No.49)Natural Science Foundation of Jilin Province(YDZJ202201ZYTS567).
文摘In recent years,with the increasing demand for social production,engineering design problems have gradually become more and more complex.Many novel and well-performing meta-heuristic algorithms have been studied and developed to cope with this problem.Among them,the Spherical Evolutionary Algorithm(SE)is one of the classical representative methods that proposed in recent years with admirable optimization performance.However,it tends to stagnate prematurely to local optima in solving some specific problems.Therefore,this paper proposes an SE variant integrating the Cross-search Mutation(CSM)and Gaussian Backbone Strategy(GBS),called CGSE.In this study,the CSM can enhance its social learning ability,which strengthens the utilization rate of SE on effective information;the GBS cooperates with the original rules of SE to further improve the convergence effect of SE.To objectively demonstrate the core advantages of CGSE,this paper designs a series of global optimization experiments based on IEEE CEC2017,and CGSE is used to solve six engineering design problems with constraints.The final experimental results fully showcase that,compared with the existing well-known methods,CGSE has a very significant competitive advantage in global tasks and has certain practical value in real applications.Therefore,the proposed CGSE is a promising and first-rate algorithm with good potential strength in the field of engineering design.
文摘Completing the principal engineering components of a pumped storage power station spans between 50 and 60 months,from the inception of construction to the commencement of power generation by the first unit.The filling of the penstock with water represents a critical phase preceding the production of electricity by the first unit.During this interval,the construction of the diversion shaft presents multiple challenges,including intricate construction procedures,considerable construction difficulty,elevated safety risks,and quality control issues.To address this issue,this study uses CFD software to analyze the flow field,pressure gradient,and head loss of shaft curved section with different curvature radius,and examines several key technologies by drawing on the practice of diversion shaft construction at the Meizhou pumped storage power station.These technologies include optimizing the curvature radius of the curved section of diversion shaft,reverse-well excavation for the shaft,and sliding-up for the lining concrete.It is found that as the curvature radius of shaft curved section reduces from 4 to 2 times the shaft diameter,the hydraulic characteristic index does not change much,and the increase of head loss accounts for about 0.18%of the total head loss of the water conveyance system.The result show that optimizing the curvature radius from 4 times to 2 times the shaft diameter is feasible and reasonable,and several improved technical measures have been proposed,such as stabilizing drill rods,mechanical scraper systems,and control technology of the relationship between concrete setting time and formwork sliding.Their implementation effectively mitigates difficulties and safety risks during shaft construction,expedites the project schedule,enhances engineering quality,and creates a 41-month timeline for the principal engineering schedule for the first power unit generation in China.
基金financially supported by the Key R&D Program of Shandong Province,China (Grant No. 2023ZLYS01)the National Natural Science Foundation of China (Grant No. 42106172)+8 种基金the Natural Science Foundation of Shandong Province (Grant Nos.ZR2024MD003, ZR2023QD023, ZR2023QD066 and ZR2023QD018)the Consulting and Researching Project of the Chinese Academy of Engineering(Grant Nos. 2024-DFZD-29, 2022-DFZD-35, 2022-XY-21, and 2021-XBZD-13-31)Qingdao Marine Science and Technology Innovation Project (Grant No. 23-1-3-hygg-6-hy)the Natural Science Foundation of Qingdao (Grant Nos. 23-2-1-58-zyyd-jch and 23-2-1-72-zyyd-jch)Project Plan of Pilot Project of Integration of Science,Education and Industry of Qilu University of Technology (Shandong Academy of Sciences)(Grant No. 2023PX035)the Visiting and Training Program for Teachers from Ordinary Undergraduate Universities in Shandong Provincethe Open Fund of Shandong Key Laboratory of Marine Ecological Environment and Disaster Prevention and Mitigation (Grant No. 202302)Major Innovation Project for the Science Education Industry Integration Pilot Project of Qilu University of Technology (Shandong Academy of Sciences)(Grant Nos. 2023HYZX01, and2023JBZ03)University-Industry Collaborative Education Program (Grant No. 202102245036)。
文摘In recent years, with the development of technologies such as the Internet of Things(Io T), big data and cloud computing, digital twin technology has gradually been applied in marine research. The digital twin realizes real-time monitoring, analysis and optimization of the state and behavior of a physical object or system by creating a virtual model. Research shows that digital twin technology has extensive application potential in ship design, marine resource development, marine equipment engineering design and optimization, marine ecological protection and early warning of disasters. Although digital twin technology has great potential in marine research, it also faces many challenges, including the complexity of data acquisition and processing, the accuracy and real-time performance of model construction, and the need for multidisciplinary cross-integration. An in-depth analysis of the technical bottlenecks and future development directions will provide an important reference for subsequent research and promote the further application and development of digital twin technology in marine research.
文摘Purpose–The paper aims to clarify the operation rationality of high speed trains(HSTs)under tunnel condition with the speed of 400 km/h through representative aerodynamic factors including running drag,eardrum comfort,carriages noise,aerodynamic loads on tunnel ancillary facilities and HST,micro-pressure waves,and then put forward engineering suggestions for higher speed tunnel operation based on the analysis.Design/methodology/approach–Based on the field measurement data of CR400AF-C and CR400BF-J tunnel operation,correlations between each aerodynamic indicators with HST speed were established.By analyzing the safety reserve of aerodynamic indicators at 350 km/h and the sensitivity of each indicator to HST speed increasing and the indicators’formation mechanism,the coupling relationship between various indicators was obtained.Findings–The sensitivity of different aerodynamic indicators to speed variation differed.The aerodynamic indicators representing flow field around HST showed a linear relationship with HST speed including noise,eardrum comfort,aerodynamic load on HST body.The positive aerodynamic load on tunnel auxiliary facilities and the micro-pressure wave at the entrance of the tunnel have the same sensitivity to the 3th-power relation of HST speed.The over-limit proportion of micro-pressure wave was the highest among the indicators,and aerodynamic buffering measures were recommended for optimization.The open tunnel pressure relief structure is recommended,while allowing trains to pass through the tunnel at an unconditional speed of 380 km/h.Originality/value–Comprehensive evaluation of multiple aerodynamic indicators for HST tunnel operation with higher speeds was realized.The main engineering requirements to release aerodynamic effect were identified and the optimization scheme is proposed.
文摘Chemical process optimization can be described as large-scale nonlinear constrained minimization. The modified augmented Lagrange multiplier methods (MALMM) for large-scale nonlinear constrained minimization are studied in this paper. The Lagrange function contains the penalty terms on equality and inequality constraints and the methods can be applied to solve a series of bound constrained sub-problems instead of a series of unconstrained sub-problems. The steps of the methods are examined in full detail. Numerical experiments are made for a variety of problems, from small to very large-scale, which show the stability and effectiveness of the methods in large-scale problems.
基金Project supported by the National Natural Science Foundation ofChina (Nos. 60074040 6022506) and the Teaching and ResearchAward Program for Outstanding Young Teachers in Higher Edu-cation Institutions of China
文摘Many engineering optimization problems frequently encounter continuous variables and discrete variables which adds considerably to the solution complexity. Very few of the existing methods can yield a globally optimal solution when the objective functions are non-convex and non-differentiable. This paper presents a hybrid swarm intelligence ap-proach (HSIA) for solving these nonlinear optimization problems which contain integer, discrete, zero-one and continuous variables. HSIA provides an improvement in global search reliability in a mixed-variable space and converges steadily to a good solution. An approach to handle various kinds of variables and constraints is discussed. Comparison testing of several examples of mixed-variable optimization problems in the literature showed that the proposed approach is superior to current methods for finding the best solution, in terms of both solution quality and algorithm robustness.
基金supported by the National Natural Science Foundation of China(61601505)
文摘This paper introduces an optimization algorithm, the hummingbirds optimization algorithm(HOA), which is inspired by the foraging process of hummingbirds. The proposed algorithm includes two phases: a self-searching phase and a guide-searching phase. With these two phases, the exploration and exploitation abilities of the algorithm can be balanced. Both the constrained and unconstrained benchmark functions are employed to test the performance of HOA. Ten classic benchmark functions are considered as unconstrained benchmark functions. Meanwhile, two engineering design optimization problems are employed as constrained benchmark functions. The results of these experiments demonstrate HOA is efficient and capable of global optimization.
基金supported by the National Basic Research and Development Program of China (No. 2010CB732004)the joint funding of the National Natural Science Foundation and Shanghai Baosteel Group Corporation of China (No. 51074177)
文摘Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved.
基金Supported by National Natural Science Foundation of China(Grant No.51575325)Shandong Provincial Natural Science Foundation of China(Grant No.ZR2013EEM007)
文摘Both the seat and cab system of truck play a vital role in ride comfort.The damping matching methods of the two systems are studied separately at present.However,the driver,seat,and cab system are one inseparable whole.In order to further improve ride comfort,the seat suspension is regarded as the fifth suspension of the cab,a new idea of ＂Five-suspensions＂ is proposed.Based on this idea,a 4 degree-of-freedom driver-seat-cab coupled system model is presented.Using the tested cab suspensions excitations as inputs and seat acceleration response as compared output,the simulation model is built.Taking optimal ride comfort as target,a new method of damping collaborative optimization for Five-suspensions is proposed.With a practical example of seat and cab system,the damping parameters are optimized and validated by simulation and bench test.The results show the seat vertical frequency-weighted RMS acceleration values tested for the un-optimized and optimized Five-suspensions are 0.50 m/s～2 and 0.39 m/s～2,respectively,with a decrease by 22.0%,which proves the model and method proposed are correct and reliable.The idea of ＂Five-suspensions＂ and the method proposed provide a reference for achieving global optimal damping matching of seat suspension and cab suspensions.
文摘In underground mining by sublevel caving method, the deformation and damage of the surface induced by subsidence are the major challenging issues. The dynamic and soft backflling body increases the safety risks in the subsiding area. In this paper, taking Zhangfushan iron mine as an example, the ore body and the general layout are focused on the safety of backflling of mined-out area. Then, we use the ANSYS software to construct a three-dimensional(3D) model for the mining area in the Zhangfushan iron mine. According to the simulation results of the initial mining stages, the ore body is stoped step by step as suggested in the design. The stability of the backflling is back analyzed based on the monitored displacements, considering the stress distribution to optimize the stoping sequence. The simulations show that a reasonable stoping sequence can minimize the concentration of high compressive stress and ensure the safety of stoping of the ore body.
基金Supported by the National Natural Science Foundation of China(21176178)the State Key Laboratory of Chemical Engineering(SKL-Ch E-13B02)
文摘Crude oil distillation is important in refining industry. Operating variables of distillation process have a critical effect on product output value and energy consumption. However, the objectives of minimum energy consumption and maximum product output value do not coordinate with each other and do not lead to the maximum economic benefit of a refinery. In this paper, a systematic optimization approach is proposed for the maximum annual economic benefit of an existing crude oil distillation system, considering product output value and energy consumption simultaneously. A shortcut model in Aspen Plus is used to describe the crude oil distillation and the pinch analysis is adopted to identify the target of energy recovery. The optimization is a nonlinear programming problem and solved by stochastic algorithm of particle warm optimization.
文摘In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective optimization has been proposed as an efficient method for human-centered manufacturing. However, previous vast researches on optimization have been mainly focused on optimization theory and optimization techniques and paid little interests on the process of problem formulation itself. In this paper, therefore, the authors present a total framework for supporting multi-objective decision making. Then, the authors try to solve the formulated multi-objective optimization problem that involves both qualitative and quantitative performance measures as a general consequence from the above procedure. Taking especially quality as a qualitative measure, the authors gave a new idea to evaluate the quality quantitatively. Additionally, to facilitate the portability of the proposed method in multidisciplinary decision-making environments, the authors implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the approach through a case study.
