In active noise control,the optimal deployment of secondary sources is a critical factor influencing the noise reduction performance due to the spatial inhomogeneity of the sound field.Traditional methods,which rely o...In active noise control,the optimal deployment of secondary sources is a critical factor influencing the noise reduction performance due to the spatial inhomogeneity of the sound field.Traditional methods,which rely on finite element analysis to model the sound field,are accurate but computationally intensive,leading to high costs in solving the deployment optimization problem.To address this issue,this paper proposes an expensive optimization method for secondary source deployment based on Interior Point Method-assisted Differential Evolution with Weibull distribution(IPMDEW).During the optimization process,a Kriging model is employed to construct a response surface,i.e.,a surrogate model,of the objective function.The surrogate model is used for the initial evaluation of the population,while the finite element model is utilized to verify promising individuals.A surrogate model update algorithm based on k-means clustering is designed to iteratively refine the model and enhance its accuracy.The IPMDEW algorithm utilizes the Weibull distribution-based weighted differential evolution for global exploration and switches to the gradient-based interior point method for refined local optimization when the population approaches convergence.The results demonstrate Kriging surrogate-assisted optimization method for secondary source deployment reduces the optimization time by 85.79%,i.e.,by 347.64 h,significantly improving optimization efficiency.Furthermore,the accuracy of the Kriging model continuously improves during the optimization process.The proposed method achieves a noise reduction of 58.32 dB,ensuring high optimization accuracy while substantially increasing efficiency.展开更多
Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon e...Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.展开更多
The properties of Mach stems in hypersonic corner flow induced by Mach interaction over 3D intersecting wedges were studied theoretically and numerically.A new method called ＂spatial dimension reduction＂ was used to...The properties of Mach stems in hypersonic corner flow induced by Mach interaction over 3D intersecting wedges were studied theoretically and numerically.A new method called ＂spatial dimension reduction＂ was used to analyze theoretically the location and Mach number behind Mach stems. By using this approach, the problem of 3D steady shock/shock interaction over 3D intersecting wedges was transformed into a 2D moving one on cross sections, which can be solved by shock-polar theory and shock dynamics theory. The properties of Mach interaction over 3D intersecting wedges can be analyzed with the new method,including pressure, temperature, density in the vicinity of triple points, location, and Mach number behind Mach stems.Theoretical results were compared with numerical results,and good agreement was obtained. Also, the influence of Mach number and wedge angle on the properties of a 3D Mach stem was studied.展开更多
An integrated method based on optical and digital image processing is presented to suppress speckle in digital holography. A spatial light modulator is adopted to introduce random phases to the illuminating beam. Mult...An integrated method based on optical and digital image processing is presented to suppress speckle in digital holography. A spatial light modulator is adopted to introduce random phases to the illuminating beam. Multiple holograms are reconstructed and superimposed, and the intensity is averaged to smooth the noise. The adaptive algorithm based on the nonlocal means is designed to further suppress the speckle. The presented method is compared with other methods reduction is improved, and the proposed method is effective The experimental results show that speckle and feasible.展开更多
For an optimal design of a surface-mounted permanent magnet synchronous motor(SPMSM),many objective functions should be considered.The classical optimization methods,which have been habitually designed based on magnet...For an optimal design of a surface-mounted permanent magnet synchronous motor(SPMSM),many objective functions should be considered.The classical optimization methods,which have been habitually designed based on magnetic circuit law or finite element analysis(FEA),have inaccuracy or calculation time problems when solving the multi-objective problems.To address these problems,the multi-independent-population genetic algorithm(MGA)combined with subdomain(SD)model are proposed to improve the performance of SPMSM such as magnetic field distribution,cost and efficiency.In order to analyze the flux density harmonics accurately,the accurate SD model is first established.Then,the MGA with time-saving SD model are employed to search for solutions which belong to the Pareto optimal set.Finally,for the purpose of validation,the electromagnetic performance of the new design motor are investigated by FEA,comparing with the initial design and conventional GA optimal design to demonstrate the advantage of MGA optimization method.展开更多
文摘In active noise control,the optimal deployment of secondary sources is a critical factor influencing the noise reduction performance due to the spatial inhomogeneity of the sound field.Traditional methods,which rely on finite element analysis to model the sound field,are accurate but computationally intensive,leading to high costs in solving the deployment optimization problem.To address this issue,this paper proposes an expensive optimization method for secondary source deployment based on Interior Point Method-assisted Differential Evolution with Weibull distribution(IPMDEW).During the optimization process,a Kriging model is employed to construct a response surface,i.e.,a surrogate model,of the objective function.The surrogate model is used for the initial evaluation of the population,while the finite element model is utilized to verify promising individuals.A surrogate model update algorithm based on k-means clustering is designed to iteratively refine the model and enhance its accuracy.The IPMDEW algorithm utilizes the Weibull distribution-based weighted differential evolution for global exploration and switches to the gradient-based interior point method for refined local optimization when the population approaches convergence.The results demonstrate Kriging surrogate-assisted optimization method for secondary source deployment reduces the optimization time by 85.79%,i.e.,by 347.64 h,significantly improving optimization efficiency.Furthermore,the accuracy of the Kriging model continuously improves during the optimization process.The proposed method achieves a noise reduction of 58.32 dB,ensuring high optimization accuracy while substantially increasing efficiency.
基金National Natural Science Foundation of China,No.41601151Guangdong Natural Science Foundation,No.2016A030310149
文摘Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.
基金supported by the National Natural Science Foundation of China (Grants 11372333, 90916028)
文摘The properties of Mach stems in hypersonic corner flow induced by Mach interaction over 3D intersecting wedges were studied theoretically and numerically.A new method called ＂spatial dimension reduction＂ was used to analyze theoretically the location and Mach number behind Mach stems. By using this approach, the problem of 3D steady shock/shock interaction over 3D intersecting wedges was transformed into a 2D moving one on cross sections, which can be solved by shock-polar theory and shock dynamics theory. The properties of Mach interaction over 3D intersecting wedges can be analyzed with the new method,including pressure, temperature, density in the vicinity of triple points, location, and Mach number behind Mach stems.Theoretical results were compared with numerical results,and good agreement was obtained. Also, the influence of Mach number and wedge angle on the properties of a 3D Mach stem was studied.
基金supported by the National Natural Science Foundation of China(No.61177018)the Program for New Century Excellent Talents in University(No.NECT-11-0596)+1 种基金the Key Program of Beijing Sci-ence and Technology Plan(No.D121100004812001)Beijing Nova Program(No.2011066)
文摘An integrated method based on optical and digital image processing is presented to suppress speckle in digital holography. A spatial light modulator is adopted to introduce random phases to the illuminating beam. Multiple holograms are reconstructed and superimposed, and the intensity is averaged to smooth the noise. The adaptive algorithm based on the nonlocal means is designed to further suppress the speckle. The presented method is compared with other methods reduction is improved, and the proposed method is effective The experimental results show that speckle and feasible.
基金This work was supported in part by the National Natural Science Foundation of China under Grant51507016。
文摘For an optimal design of a surface-mounted permanent magnet synchronous motor(SPMSM),many objective functions should be considered.The classical optimization methods,which have been habitually designed based on magnetic circuit law or finite element analysis(FEA),have inaccuracy or calculation time problems when solving the multi-objective problems.To address these problems,the multi-independent-population genetic algorithm(MGA)combined with subdomain(SD)model are proposed to improve the performance of SPMSM such as magnetic field distribution,cost and efficiency.In order to analyze the flux density harmonics accurately,the accurate SD model is first established.Then,the MGA with time-saving SD model are employed to search for solutions which belong to the Pareto optimal set.Finally,for the purpose of validation,the electromagnetic performance of the new design motor are investigated by FEA,comparing with the initial design and conventional GA optimal design to demonstrate the advantage of MGA optimization method.
