The layout of the buckets for tunnel boring machine(TBM)directly affects the muck removal efficiency of cutterhead during excavation.In order to improve the muck removal performance for TBM,the optimal design of bucke...The layout of the buckets for tunnel boring machine(TBM)directly affects the muck removal efficiency of cutterhead during excavation.In order to improve the muck removal performance for TBM,the optimal design of bucket layout was investigated.The whole muck transfer process was simulated by discrete-element method(DEM),including the muck falling,colliding,pilling up,shoveling and transferring into the hopper.The muck model was established based on size distribution analysis of muck samples from the water-supply tunnel project in Jilin Province,China.Then,the influence of the bucket number and the interval angle between buckets on muck removal performance was investigated.The results indicated that,as the number of buckets increased from four to eight,the removed muck increased by 29%and the residual volume decreased by 40.5%,and the process became steadier.Different interval angles between buckets were corresponding to different removed muck irregularly,but the residual muck number increased generally with the angles.The optimal layout of buckets for the cutterhead in this tunnel project was obtained based on the simulation results,and the muck removal performance of the TBM was verified by the actual data in the engineering construction.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
As a result of more and more serious energy risks, the study of national energy security zoning is not only the basic requirement of energy risk management but also the new demand of economic development for the energ...As a result of more and more serious energy risks, the study of national energy security zoning is not only the basic requirement of energy risk management but also the new demand of economic development for the energy industry. Firstly, this paper analyzes the basic situation of energy resources and production and consumption of primary. energy from 1996 to 2005 in China. Secondly; this paper founds an Energy Security Index System formed by six indices including the percentage of energy reserves, interlocal dependent degree, energy elasticity coefficient and so on. It subsequently calculates the weight of these indices with the factor analysis rating method Lastly, the paper evaluates and zones the abilities of energy security of 30 provinces in China with the grey chuster method According to their security; the 30 provinces are classified into three different levels： high, medium, and low levels. The regions at low energy security level include Beijing, Shanghai, Zhejiang, Fujian, Guangdong, Guangxi and Hainan. They are mainly littoral and short of primary energy production while mostly dependent on other provinces. Those at medium energy security level include 15 provinces （cities or districts）, such as Liaoning, Tianjin, Hebei, Shandong, Henan, Hunan and so on. These provinces are in the northeast, north, east of and central China. Those at high energy security level contain Shanxi. lnner Mongolia, Heilongjiang, Jilin, Chongqing, Sichuan, Shaanxi. Xinjiang. These provinces are the main primary energy production bases.展开更多
基金Project(51475478)supported by the National Natural Science Foundation of ChinaProject(2012AA041801)supported by the National High Technology Research and Development Program of China+1 种基金Project(2014FJ1002)supported by the Science and Technology Major Project of Hunan Province,ChinaProject(2013CB035401)supported by the National Basic Research Program of China。
文摘The layout of the buckets for tunnel boring machine(TBM)directly affects the muck removal efficiency of cutterhead during excavation.In order to improve the muck removal performance for TBM,the optimal design of bucket layout was investigated.The whole muck transfer process was simulated by discrete-element method(DEM),including the muck falling,colliding,pilling up,shoveling and transferring into the hopper.The muck model was established based on size distribution analysis of muck samples from the water-supply tunnel project in Jilin Province,China.Then,the influence of the bucket number and the interval angle between buckets on muck removal performance was investigated.The results indicated that,as the number of buckets increased from four to eight,the removed muck increased by 29%and the residual volume decreased by 40.5%,and the process became steadier.Different interval angles between buckets were corresponding to different removed muck irregularly,but the residual muck number increased generally with the angles.The optimal layout of buckets for the cutterhead in this tunnel project was obtained based on the simulation results,and the muck removal performance of the TBM was verified by the actual data in the engineering construction.
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the National Key Technology R&D Program of China – the Key Tech-nology and Demonstration for Integrated Governance of Energy and Water Resources Security Risk (Grant No. 2006BAD20B06)
文摘As a result of more and more serious energy risks, the study of national energy security zoning is not only the basic requirement of energy risk management but also the new demand of economic development for the energy industry. Firstly, this paper analyzes the basic situation of energy resources and production and consumption of primary. energy from 1996 to 2005 in China. Secondly; this paper founds an Energy Security Index System formed by six indices including the percentage of energy reserves, interlocal dependent degree, energy elasticity coefficient and so on. It subsequently calculates the weight of these indices with the factor analysis rating method Lastly, the paper evaluates and zones the abilities of energy security of 30 provinces in China with the grey chuster method According to their security; the 30 provinces are classified into three different levels： high, medium, and low levels. The regions at low energy security level include Beijing, Shanghai, Zhejiang, Fujian, Guangdong, Guangxi and Hainan. They are mainly littoral and short of primary energy production while mostly dependent on other provinces. Those at medium energy security level include 15 provinces （cities or districts）, such as Liaoning, Tianjin, Hebei, Shandong, Henan, Hunan and so on. These provinces are in the northeast, north, east of and central China. Those at high energy security level contain Shanxi. lnner Mongolia, Heilongjiang, Jilin, Chongqing, Sichuan, Shaanxi. Xinjiang. These provinces are the main primary energy production bases.
