The Near-Surface Mounted(NSM)strengthening technique has emerged as a promising alternative to traditional strengthening methods in recent years.Over the past two decades,researchers have extensively studied its poten...The Near-Surface Mounted(NSM)strengthening technique has emerged as a promising alternative to traditional strengthening methods in recent years.Over the past two decades,researchers have extensively studied its potential,advantages,and applications,as well as related parameters,aiming at optimization of construction systems.However,there is still a need to explore further,both from a static perspective,which involves accounting for the nonconservation of the contact section resulting from the bond-slip effect between fiber-reinforced polymer(FRP)rods and resin and is typically neglected by existing analytical models,as well as from a dynamic standpoint,which involves studying the trends of vibration frequencies to understand the effects of various forms of damage and the efficiency of reinforcement.To address this gap in knowledge,this research involves static and dynamic tests on simply supported reinforced concrete(RC)beams using rods of NSM carbon fiber reinforced polymer(CFRP)and glass fiber reinforced polymer(GFRP).The main objective is to examine the effects of various strengthening methods.This research conducts bending tests with loading cycles until failure,and it helps to define the behavior of beam specimens under various damage degrees,including concrete cracking.Dynamic analysis by free vibration testing enables tracking of the effectiveness of the reinforcement at various damage levels at each stage of the loading process.In addition,application of Particle Swarm Optimization(PSO)and Genetic Algorithm(GA)is proposed to optimize Gradient Boosting(GB)training performance for concrete strain prediction in NSM-FRP RC.The GB using Particle Swarm Optimization(GBPSO)and GB using Genetic Algorithm(GBGA)systems were trained using an experimental data set,where the input data was a static applied load and the output data was the consequent strain.Hybrid models of GBPSO and GBGA have been shown to provide highly accurate results for predicting strain.These models combine the strengths of both optimization tec展开更多
As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weigh...As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weight under burst pressure con- straint. The actual burst pressure is calculated using the arc-length and restart analysis in finite element analysis (FEA). A penalty function in the fitness function is proposed to deal with the constrained problem. The effects of the population size and the number of generations in the GA on the weight and burst pressure of the vessel are explored. The optimization results using the proposed GA are also compared with those using the simple GA and the conventional Monte Carlo method.展开更多
A transient numerical model was applied to simulating the axial-directional crystallization purification(ADCP) process of gallium(Ga) raw material at different coolant temperatures(Tc), and the evolutions of melt/crys...A transient numerical model was applied to simulating the axial-directional crystallization purification(ADCP) process of gallium(Ga) raw material at different coolant temperatures(Tc), and the evolutions of melt/crystal(m/c) interface shape, temperature distribution and thermal stresses were simulated and analyzed. The results showed that the m/c interface shape, temperature distribution, and thermal stress in the Ga material were determined by the Tc in the crystallizer during the ADCP process. The temperature gradient and thermal stress in the grown Ga crystal increased with decreasing Tc. At Tc=15 ℃, the m/c interface shape was flat, and the temperature gradient was ideal. Therefore, the Ga materials with lower thermal stresses and suitable m/c interface shape, and an ideal efficiency of impurity removal were obtained. The purity of Ga reached 6 N standard by using ADCP process repeated 6 times at Tc of 15 ℃. The results of the simulation showed good agreement with the experimental results.展开更多
This letter investigates an efficient design procedure integrating the Genetic Algorithm (GA) with the Finite Difference Time Domain (FDTD) for the fast optimal design of Smart Antenna Arrays (SAA). The FDTD is used t...This letter investigates an efficient design procedure integrating the Genetic Algorithm (GA) with the Finite Difference Time Domain (FDTD) for the fast optimal design of Smart Antenna Arrays (SAA). The FDTD is used to analyze SAA with mutual coupling. Then,on the basis of the Maximal Signal to Noise Ratio (MSNR) criteria, the GA is applied to the optimization of weighting elements and structure of SAA. Finally, the effectiveness of the analysis is evaluated by experimental antenna arrays.展开更多
文摘The Near-Surface Mounted(NSM)strengthening technique has emerged as a promising alternative to traditional strengthening methods in recent years.Over the past two decades,researchers have extensively studied its potential,advantages,and applications,as well as related parameters,aiming at optimization of construction systems.However,there is still a need to explore further,both from a static perspective,which involves accounting for the nonconservation of the contact section resulting from the bond-slip effect between fiber-reinforced polymer(FRP)rods and resin and is typically neglected by existing analytical models,as well as from a dynamic standpoint,which involves studying the trends of vibration frequencies to understand the effects of various forms of damage and the efficiency of reinforcement.To address this gap in knowledge,this research involves static and dynamic tests on simply supported reinforced concrete(RC)beams using rods of NSM carbon fiber reinforced polymer(CFRP)and glass fiber reinforced polymer(GFRP).The main objective is to examine the effects of various strengthening methods.This research conducts bending tests with loading cycles until failure,and it helps to define the behavior of beam specimens under various damage degrees,including concrete cracking.Dynamic analysis by free vibration testing enables tracking of the effectiveness of the reinforcement at various damage levels at each stage of the loading process.In addition,application of Particle Swarm Optimization(PSO)and Genetic Algorithm(GA)is proposed to optimize Gradient Boosting(GB)training performance for concrete strain prediction in NSM-FRP RC.The GB using Particle Swarm Optimization(GBPSO)and GB using Genetic Algorithm(GBGA)systems were trained using an experimental data set,where the input data was a static applied load and the output data was the consequent strain.Hybrid models of GBPSO and GBGA have been shown to provide highly accurate results for predicting strain.These models combine the strengths of both optimization tec
基金Project (Nos. 2006BAK04A02-02 and 2006BAK02B02-08) sup-ported by the National Key Technology R&D Program, China
文摘As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weight under burst pressure con- straint. The actual burst pressure is calculated using the arc-length and restart analysis in finite element analysis (FEA). A penalty function in the fitness function is proposed to deal with the constrained problem. The effects of the population size and the number of generations in the GA on the weight and burst pressure of the vessel are explored. The optimization results using the proposed GA are also compared with those using the simple GA and the conventional Monte Carlo method.
基金Project(51465014)supported by the National Natural Science Foundation of ChinaProject(Guike AA17204021-7)supported by the Innovation Driven Development Special Foundation of Guangxi,China。
文摘A transient numerical model was applied to simulating the axial-directional crystallization purification(ADCP) process of gallium(Ga) raw material at different coolant temperatures(Tc), and the evolutions of melt/crystal(m/c) interface shape, temperature distribution and thermal stresses were simulated and analyzed. The results showed that the m/c interface shape, temperature distribution, and thermal stress in the Ga material were determined by the Tc in the crystallizer during the ADCP process. The temperature gradient and thermal stress in the grown Ga crystal increased with decreasing Tc. At Tc=15 ℃, the m/c interface shape was flat, and the temperature gradient was ideal. Therefore, the Ga materials with lower thermal stresses and suitable m/c interface shape, and an ideal efficiency of impurity removal were obtained. The purity of Ga reached 6 N standard by using ADCP process repeated 6 times at Tc of 15 ℃. The results of the simulation showed good agreement with the experimental results.
文摘This letter investigates an efficient design procedure integrating the Genetic Algorithm (GA) with the Finite Difference Time Domain (FDTD) for the fast optimal design of Smart Antenna Arrays (SAA). The FDTD is used to analyze SAA with mutual coupling. Then,on the basis of the Maximal Signal to Noise Ratio (MSNR) criteria, the GA is applied to the optimization of weighting elements and structure of SAA. Finally, the effectiveness of the analysis is evaluated by experimental antenna arrays.
