The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu...The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.展开更多
Multi</span><span><span style="font-family:"">-</span></span><span><span style="font-family:"">goal and multi-objective optimizations are similar...Multi</span><span><span style="font-family:"">-</span></span><span><span style="font-family:"">goal and multi-objective optimizations are similar techniques to</span></span><span><span style="font-family:""> achieve <span>multiple conflicting goals/objectives simultaneously. There are several tech</span>niques <span>for solving multi-goal and multi-objective optimization problems. The</span> <span>present </span><span>study proposed the possibility of convertibility in solving multi-goal and mul</span>ti-objective optimization problems.展开更多
This article introduces a singleton type-1 fuzzy logic system(T1-SFLS) controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. T...This article introduces a singleton type-1 fuzzy logic system(T1-SFLS) controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. The WDO(Wind Driven Optimization) algorithm is used to optimize and tune the input/output membership function parameters of the fuzzy controller. The WDO algorithm is working based on the atmospheric motion of infinitesimal small air parcels navigates over an N-dimensional search domain. The performance of this proposed technique has compared through many computer simulations and real-time experiments by using Khepera-Ⅲ mobile robot. As compared to the T1-SFLS controller the Fuzzy-WDO algorithm is found good agreement for mobile robot navigation.展开更多
Landing gear lower drag stay is a key component which connects fuselage and landing gear and directly effects the safety and performance of aircraft takeoff and landing. To effectively design the lower drag stay and r...Landing gear lower drag stay is a key component which connects fuselage and landing gear and directly effects the safety and performance of aircraft takeoff and landing. To effectively design the lower drag stay and reduce the weight of landing gear, Global/local Linked Driven Optimization Strategy(GLDOS) was developed to conduct the overall process design of lower drag stay in respect of optimization thought. The whole-process optimization involves two stages of structural conceptual design and detailed design. In the structural conceptual design, the landing gear lower drag stay was globally topologically optimized by adopting multiple starting points algorithm. In the detailed design, the local size and shape of landing gear lower drag stay were globally optimized by the gradient optimization strategy. The GLDOS method adopts different optimization strategies for different optimization stages to acquire the optimum design effect. Through the experimental validation, the weight of the optimized lower dray stay with the developed GLDOS is reduced by 16.79% while keeping enough strength and stiffness, which satisfies the requirements of engineering design under the typical loading conditions. The proposed GLDOS is validated to be accurate and efficient in optimization scheme and design cycles. The efforts of this paper provide a whole-process optimization approach regarding different optimization technologies in different design phases, which is significant in reducing structural weight and enhance design tp wid 1 precision for complex structures in aircrafts.展开更多
This paper presents a Butterfly Optimization Algorithm(BOA)with a wind-driven mechanism for avoiding natural enemies known as WDBOA.To further balance the basic BOA algorithm's exploration and exploitation capabil...This paper presents a Butterfly Optimization Algorithm(BOA)with a wind-driven mechanism for avoiding natural enemies known as WDBOA.To further balance the basic BOA algorithm's exploration and exploitation capabilities,the butterfly actions were divided into downwind and upwind states.The algorithm of exploration ability was improved with the wind,while the algorithm of exploitation ability was improved against the wind.Also,a mechanism of avoiding natural enemies based on Lévy flight was introduced for the purpose of enhancing its global searching ability.Aiming at improving the explorative performance at the initial stages and later stages,the fragrance generation method was modified.To evaluate the effectiveness of the suggested algorithm,a comparative study was done with six classical metaheuristic algorithms and three BOA variant optimization techniques on 18 benchmark functions.Further,the performance of the suggested technique in addressing some complicated problems in various dimensions was evaluated using CEC 2017 and CEC 2020.Finally,the WDBOA algorithm is used proportional-integral-derivative(PID)controller parameter optimization.Experimental results demonstrate that the WDBOA based PID controller has better control performance in comparison with other PID controllers tuned by the Genetic Algorithm(GA),Flower Pollination Algorithm(FPA),Cuckoo Search(CS)and BOA.展开更多
This paper presents a multiscale design method for simultaneous topology optimization of both macrostructures and microstructures.Geometric features are extended as design primitives at both macro and micro scales and...This paper presents a multiscale design method for simultaneous topology optimization of both macrostructures and microstructures.Geometric features are extended as design primitives at both macro and micro scales and represented by Level Set Functions(LSFs).Parameters related to the locations,sizes,and orientations of macro and micro features are considered as design variables and optimized simultaneously.In the overlapping areas of different macro features,embedded microstructures are optimally figured out as the solution of the corresponding sub-optimization,problem.In this study,the eXtended Finite Element Method(XFEM)is implemented for structural and sensitivity analyses with respect to design variables.This method has the advantage of using a fixed grid independent of the topology optimization process.The homogenization procedure is applied to calculate the effective properties of considered microstructures in each macro feature.Numerical examples are presented to illustrate the effectiveness of the proposed method.Results depict that the multiscale design cannot obviously improve structural stiffness compared with a solid-material design under the linear elastic condition.展开更多
Additive Manufacturing(AM)has significantly impacted the development of high-performance materials and structures,offering new possibilities for industries ranging from aerospace to biomedicine.This special issue feat...Additive Manufacturing(AM)has significantly impacted the development of high-performance materials and structures,offering new possibilities for industries ranging from aerospace to biomedicine.This special issue features pioneering research that integrates AI-driven methods with AM,enabling the design and fabrication of complex,optimized structures with enhanced properties.展开更多
Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting deci...Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting decision models are constructed. Environmental policy formulation can prove additionally complicated because the various system components often contain considerable stochastic uncertainty and frequently numerous stakeholders exist that hold completely incompatible perspectives. Consequently, there are invariably unmodelled performance design issues, not apparent at the time of the problem formulation, which can greatly impact the acceptability of any proposed solutions. While a mathematically optimal solution might provide the best solution to a modelled problem, normally this will not be the best solution to the underlying real problem. Therefore, in public environmental policy formulation, it is generally preferable to be able to create several quantifiably good alternatives that provide very different approaches and perspectives to the problem. This study shows how a computationally efficient simulation-driven optimization approach that com- bines evolutionary optimization with simulation can be used to generate multiple policy alternatives that satisfy required system criteria and are maximally different in decision space. The efficacy of this modelling-to-generate-alternatives method is specifically demonstrated on a municipal solid waste management facility expansion case.展开更多
This paper aims to improve the performance of a class of distributed parameter systems for the optimal switching of actuators and controllers based on event-driven control. It is assumed that in the available multiple...This paper aims to improve the performance of a class of distributed parameter systems for the optimal switching of actuators and controllers based on event-driven control. It is assumed that in the available multiple actuators, only one actuator can receive the control signal and be activated over an unfixed time interval, and the other actuators keep dormant. After incorporating a state observer into the event generator, the event-driven control loop and the minimum inter-event time are ultimately bounded. Based on the event-driven state feedback control, the time intervals of unfixed length can be obtained. The optimal switching policy is based on finite horizon linear quadratic optimal control at the beginning of each time subinterval. A simulation example demonstrate the effectiveness of the proposed policy.展开更多
We focus on the friction loss measurement and reduction of the timing belt guide plates of a fourcylinder gasoline engine. To minimize the friction loss caused by the dynamic friction of the guide plates during timing...We focus on the friction loss measurement and reduction of the timing belt guide plates of a fourcylinder gasoline engine. To minimize the friction loss caused by the dynamic friction of the guide plates during timing belt motion and improve the efficiency of the internal combustion engine(ICE), we adopt four different plastic materials in fabricating the guide plates. With controlled engine boundary conditions and operational modes, an AVL electric dynamometer is used to measure the output of the engine. The results indicate that selecting polytetrafluoroethylene(PTFE) as the additive in fabricating the guide plates can effectively reduce the friction loss, so that the output torque and output power of the engine can be improved, thus reducing fuel consumptions. This work also has positive impact on the efficiency optimization of similar ICEs.展开更多
The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of th...The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of the tip-jet rotor composite power system, studying the effects of intake mode, inner cavity structure, propellant components, and injection amount on the characteristics of the composite power system. The results show that when a single high-temperature exhaust gas enters, the gas generator outlet fluid is uneven and asymmetric;when two-way high-temperature exhaust gas enters, the outlet temperature of the gas generator with a tilted inlet is more uniform than that with a vertical inlet;adding an inner cavity improves the temperature and velocity distribution of the gas generator's internal flow field;increasing the energy of the propellant is beneficial for improving the available moment.展开更多
Laser vision correction is a rapidly growing field for correcting nearsightedness, farsightedness as well as astigmatism with dominating laser-assisted in situ keratomileusis (LASIK) procedures. While the technique wo...Laser vision correction is a rapidly growing field for correcting nearsightedness, farsightedness as well as astigmatism with dominating laser-assisted in situ keratomileusis (LASIK) procedures. While the technique works well for correcting spherocylindrical aberrations, it does not fully correct high order aberrations (HOAs), in particular spherical aberration (SA), due to unexpected induction of HOAs post-surgery. Corneal epithelial remodeling was proposed as one source to account for such HOA induction process. This work proposes a dual-scale linear filtering kernel to model such a process. Several retrospective clinical data sets were used as training data sets to construct the model, with a downhill simplex algorithm to optimize the two free parameters of the kernel. The performance of the optimized kernel was testedon new clinical data sets that were not previously used for the optimization.展开更多
文摘The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.
文摘Multi</span><span><span style="font-family:"">-</span></span><span><span style="font-family:"">goal and multi-objective optimizations are similar techniques to</span></span><span><span style="font-family:""> achieve <span>multiple conflicting goals/objectives simultaneously. There are several tech</span>niques <span>for solving multi-goal and multi-objective optimization problems. The</span> <span>present </span><span>study proposed the possibility of convertibility in solving multi-goal and mul</span>ti-objective optimization problems.
文摘This article introduces a singleton type-1 fuzzy logic system(T1-SFLS) controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. The WDO(Wind Driven Optimization) algorithm is used to optimize and tune the input/output membership function parameters of the fuzzy controller. The WDO algorithm is working based on the atmospheric motion of infinitesimal small air parcels navigates over an N-dimensional search domain. The performance of this proposed technique has compared through many computer simulations and real-time experiments by using Khepera-Ⅲ mobile robot. As compared to the T1-SFLS controller the Fuzzy-WDO algorithm is found good agreement for mobile robot navigation.
基金co-supported by National Natural Science Foundation of China (Nos. 51975124 and 51675179)Aerospace Science and Technology Fund of China (No.AERO201937)Research Start-up Funding of Fudan University (No. FDU38341)。
文摘Landing gear lower drag stay is a key component which connects fuselage and landing gear and directly effects the safety and performance of aircraft takeoff and landing. To effectively design the lower drag stay and reduce the weight of landing gear, Global/local Linked Driven Optimization Strategy(GLDOS) was developed to conduct the overall process design of lower drag stay in respect of optimization thought. The whole-process optimization involves two stages of structural conceptual design and detailed design. In the structural conceptual design, the landing gear lower drag stay was globally topologically optimized by adopting multiple starting points algorithm. In the detailed design, the local size and shape of landing gear lower drag stay were globally optimized by the gradient optimization strategy. The GLDOS method adopts different optimization strategies for different optimization stages to acquire the optimum design effect. Through the experimental validation, the weight of the optimized lower dray stay with the developed GLDOS is reduced by 16.79% while keeping enough strength and stiffness, which satisfies the requirements of engineering design under the typical loading conditions. The proposed GLDOS is validated to be accurate and efficient in optimization scheme and design cycles. The efforts of this paper provide a whole-process optimization approach regarding different optimization technologies in different design phases, which is significant in reducing structural weight and enhance design tp wid 1 precision for complex structures in aircrafts.
基金This work was supported by National Natural Science Foundation of China under Grant U21A20464,62066005Project of the Guangxi Science and Technology under Grant No.ZL23014016.
文摘This paper presents a Butterfly Optimization Algorithm(BOA)with a wind-driven mechanism for avoiding natural enemies known as WDBOA.To further balance the basic BOA algorithm's exploration and exploitation capabilities,the butterfly actions were divided into downwind and upwind states.The algorithm of exploration ability was improved with the wind,while the algorithm of exploitation ability was improved against the wind.Also,a mechanism of avoiding natural enemies based on Lévy flight was introduced for the purpose of enhancing its global searching ability.Aiming at improving the explorative performance at the initial stages and later stages,the fragrance generation method was modified.To evaluate the effectiveness of the suggested algorithm,a comparative study was done with six classical metaheuristic algorithms and three BOA variant optimization techniques on 18 benchmark functions.Further,the performance of the suggested technique in addressing some complicated problems in various dimensions was evaluated using CEC 2017 and CEC 2020.Finally,the WDBOA algorithm is used proportional-integral-derivative(PID)controller parameter optimization.Experimental results demonstrate that the WDBOA based PID controller has better control performance in comparison with other PID controllers tuned by the Genetic Algorithm(GA),Flower Pollination Algorithm(FPA),Cuckoo Search(CS)and BOA.
基金supported by National Key Research and Development Program of China(No.2017YFB1102800)National Natural Science Foundation of China(Nos.11432011,11620101002,11722219).
文摘This paper presents a multiscale design method for simultaneous topology optimization of both macrostructures and microstructures.Geometric features are extended as design primitives at both macro and micro scales and represented by Level Set Functions(LSFs).Parameters related to the locations,sizes,and orientations of macro and micro features are considered as design variables and optimized simultaneously.In the overlapping areas of different macro features,embedded microstructures are optimally figured out as the solution of the corresponding sub-optimization,problem.In this study,the eXtended Finite Element Method(XFEM)is implemented for structural and sensitivity analyses with respect to design variables.This method has the advantage of using a fixed grid independent of the topology optimization process.The homogenization procedure is applied to calculate the effective properties of considered microstructures in each macro feature.Numerical examples are presented to illustrate the effectiveness of the proposed method.Results depict that the multiscale design cannot obviously improve structural stiffness compared with a solid-material design under the linear elastic condition.
文摘Additive Manufacturing(AM)has significantly impacted the development of high-performance materials and structures,offering new possibilities for industries ranging from aerospace to biomedicine.This special issue features pioneering research that integrates AI-driven methods with AM,enabling the design and fabrication of complex,optimized structures with enhanced properties.
文摘Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting decision models are constructed. Environmental policy formulation can prove additionally complicated because the various system components often contain considerable stochastic uncertainty and frequently numerous stakeholders exist that hold completely incompatible perspectives. Consequently, there are invariably unmodelled performance design issues, not apparent at the time of the problem formulation, which can greatly impact the acceptability of any proposed solutions. While a mathematically optimal solution might provide the best solution to a modelled problem, normally this will not be the best solution to the underlying real problem. Therefore, in public environmental policy formulation, it is generally preferable to be able to create several quantifiably good alternatives that provide very different approaches and perspectives to the problem. This study shows how a computationally efficient simulation-driven optimization approach that com- bines evolutionary optimization with simulation can be used to generate multiple policy alternatives that satisfy required system criteria and are maximally different in decision space. The efficacy of this modelling-to-generate-alternatives method is specifically demonstrated on a municipal solid waste management facility expansion case.
基金supported by the National Natural Science Foundation of China(Grant Nos.61174021 and 61104155)the Fundamental Research Funds for theCentral Universities,China(Grant Nos.JUDCF13037 and JUSRP51322B)+1 种基金the Programme of Introducing Talents of Discipline to Universities,China(GrantNo.B12018)the Jiangsu Innovation Program for Graduates,China(Grant No.CXZZ13-0740)
文摘This paper aims to improve the performance of a class of distributed parameter systems for the optimal switching of actuators and controllers based on event-driven control. It is assumed that in the available multiple actuators, only one actuator can receive the control signal and be activated over an unfixed time interval, and the other actuators keep dormant. After incorporating a state observer into the event generator, the event-driven control loop and the minimum inter-event time are ultimately bounded. Based on the event-driven state feedback control, the time intervals of unfixed length can be obtained. The optimal switching policy is based on finite horizon linear quadratic optimal control at the beginning of each time subinterval. A simulation example demonstrate the effectiveness of the proposed policy.
基金the Shanghai Automotive Industry Science and Technology Development Foundation(No.1614)
文摘We focus on the friction loss measurement and reduction of the timing belt guide plates of a fourcylinder gasoline engine. To minimize the friction loss caused by the dynamic friction of the guide plates during timing belt motion and improve the efficiency of the internal combustion engine(ICE), we adopt four different plastic materials in fabricating the guide plates. With controlled engine boundary conditions and operational modes, an AVL electric dynamometer is used to measure the output of the engine. The results indicate that selecting polytetrafluoroethylene(PTFE) as the additive in fabricating the guide plates can effectively reduce the friction loss, so that the output torque and output power of the engine can be improved, thus reducing fuel consumptions. This work also has positive impact on the efficiency optimization of similar ICEs.
文摘The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of the tip-jet rotor composite power system, studying the effects of intake mode, inner cavity structure, propellant components, and injection amount on the characteristics of the composite power system. The results show that when a single high-temperature exhaust gas enters, the gas generator outlet fluid is uneven and asymmetric;when two-way high-temperature exhaust gas enters, the outlet temperature of the gas generator with a tilted inlet is more uniform than that with a vertical inlet;adding an inner cavity improves the temperature and velocity distribution of the gas generator's internal flow field;increasing the energy of the propellant is beneficial for improving the available moment.
文摘Laser vision correction is a rapidly growing field for correcting nearsightedness, farsightedness as well as astigmatism with dominating laser-assisted in situ keratomileusis (LASIK) procedures. While the technique works well for correcting spherocylindrical aberrations, it does not fully correct high order aberrations (HOAs), in particular spherical aberration (SA), due to unexpected induction of HOAs post-surgery. Corneal epithelial remodeling was proposed as one source to account for such HOA induction process. This work proposes a dual-scale linear filtering kernel to model such a process. Several retrospective clinical data sets were used as training data sets to construct the model, with a downhill simplex algorithm to optimize the two free parameters of the kernel. The performance of the optimized kernel was testedon new clinical data sets that were not previously used for the optimization.
