In the present research, artificial artificial networks hare be applied to establish the constitutive rela- tionship model of Ti - 5Al - 2Sn - 2Zr - 4Mo - 4Cr (wt - % ) alloy. In the first stage of the re- search...In the present research, artificial artificial networks hare be applied to establish the constitutive rela- tionship model of Ti - 5Al - 2Sn - 2Zr - 4Mo - 4Cr (wt - % ) alloy. In the first stage of the re- search, an isothermal compressive experiment using Thermecmastor - Z hot simulator is studied to ac- quire the flow stress at different deformation temperature,equivalent strain and equivalent strain rate. Then,a feed - forward neural network is trained by using the experimental data.After the training process is finished, the neural networks become a knowledge-based constitutive relationship system. Comparison of the predicted and experimental results results shows that the neural network model has good le- arning precision and good generalization.The neural neural network methods are found to show much better agreement than existing methods with the experiment data, and have the advantage of being able to deal with noisy for or data with strong non - linear reationships. At last, this model can be aused to simulate the flow behavior of Ti - 5Al - 2Sn - 2Zr - 4Mo - 4Ca alloy.展开更多
In order to ensure the reliability of network-on-chip （NoC） under faulty circumstance, a dynamic fault tolerant routing algorithm is proposed. This algorithm can implement detour routing when there are both static a...In order to ensure the reliability of network-on-chip （NoC） under faulty circumstance, a dynamic fault tolerant routing algorithm is proposed. This algorithm can implement detour routing when there are both static and dynamic permanent faults in the network. That means the packet is able to move around the fanlts to the destination with a non-minimum path. In addition, the multi-level congestion control mechanism gives the algorithm the ability to distribute the load over the whole network and to avoid hotspots around the faults. Simulation results demonstrate the advantage of the proposed routing algorithm in terms of average packet latency and packet loss rate compared with negative-first routing algo- rithm and DyAD routing algorithm in the presence of permanent faults. For the proposed algorithm, it can get much less average packet latency and lead to less than 20% packet loss rate.展开更多
Considering multiplicative Schwarz algorithm for solving algebraic obstacle problems, we show the geometric convergence of the algorithm by the use of discrete maximum principle. We also get a decay rate bound indepen...Considering multiplicative Schwarz algorithm for solving algebraic obstacle problems, we show the geometric convergence of the algorithm by the use of discrete maximum principle. We also get a decay rate bound independent of the meshsize for the iterative error and illustrate the method by some numerical experiments.展开更多
This paper presents a new interconnection net work topology ,called The twisted-cube connected network is a variant of the hypercube, and it has a better recursive structure . The regularity, connectivities, subgraphs...This paper presents a new interconnection net work topology ,called The twisted-cube connected network is a variant of the hypercube, and it has a better recursive structure . The regularity, connectivities, subgraphs of the twisted- cube conaected aetwork are studied . The twisted-cube connected network is proved to be a 3-cube-free network, which is the essential difference from the hypercube and variants of the hypercube. An efficient routing algorithm is proposed, and the diameter of n-dimensional twisted-cube connected network is proved to be just which is less than that of the hypercube.展开更多
This work deals with the numerical localization of small electromagnetic inhomogeneities. The underlying inverse problem considers, in a three-dimensional bounded domain, the time-harmonic Maxwell equations formulated...This work deals with the numerical localization of small electromagnetic inhomogeneities. The underlying inverse problem considers, in a three-dimensional bounded domain, the time-harmonic Maxwell equations formulated in electric field. Typically, the domain contains a finite number of unknown inhomogeneities of small volume and the inverse problem attempts to localize these inhomogeneities from a finite number of boundary measurements. Our localization approach is based on a recent framework that uses an asymptotic expansion for the perturbations in the tangential boundary trace of the curl of the electric field. We present three numerical localization procedures resulting from the combination of this asymptotic expansion with each of the following inversion algorithms： the Current Projection method, the MUltiple Signal Classification （MUSIC） algorithm, and an Inverse Fourier method. We perform a numerical study of the asymptotic expansion and compare the numerical results obtained from the three localization procedures in different settings.展开更多
Energy efficiency, which consists of using less energy or improving the level of service to energy consumers, refers to an effective way to provide overall energy. But its increasing pressure on the energy sector to c...Energy efficiency, which consists of using less energy or improving the level of service to energy consumers, refers to an effective way to provide overall energy. But its increasing pressure on the energy sector to control greenhouse gases and to reduce CO2 emissions forced the power system operators to consider the emission problem as a consequential matter besides the economic problems. The economic power dispatch problem has, therefore, become a multi-objective optimization problem. Fuel cost, pollutant emissions, and system loss should be minimized simultaneously while satisfying certain system constraints. To achieve a good design with different solutions in a multi-objective optimization problem, fuel cost and pollutant emissions are converted into single optimization problem by introducing penalty factor. Now the power dispatch is formulated into a hi-objective optimization problem, two objectives with two algorithms, firefly algorithm for optimization the fuel cost, pollutant emissions and the real genetic algorithm for minimization of the transmission losses. In this paper the new approach （firefly algorithm-real genetic algorithm, FFA-RGA） has been applied to the standard IEEE 30-bus 6-generator. The effectiveness of the proposed approach is demonstrated by comparing its performance with other evolutionary multi- objective optimization algorithms. Simulation results show the validity and feasibility of the proposed method.展开更多
文摘In the present research, artificial artificial networks hare be applied to establish the constitutive rela- tionship model of Ti - 5Al - 2Sn - 2Zr - 4Mo - 4Cr (wt - % ) alloy. In the first stage of the re- search, an isothermal compressive experiment using Thermecmastor - Z hot simulator is studied to ac- quire the flow stress at different deformation temperature,equivalent strain and equivalent strain rate. Then,a feed - forward neural network is trained by using the experimental data.After the training process is finished, the neural networks become a knowledge-based constitutive relationship system. Comparison of the predicted and experimental results results shows that the neural network model has good le- arning precision and good generalization.The neural neural network methods are found to show much better agreement than existing methods with the experiment data, and have the advantage of being able to deal with noisy for or data with strong non - linear reationships. At last, this model can be aused to simulate the flow behavior of Ti - 5Al - 2Sn - 2Zr - 4Mo - 4Ca alloy.
基金Supported by the National High Technology Research and Development Program of China (863 Program) (2002AA1Z149)
文摘In order to ensure the reliability of network-on-chip （NoC） under faulty circumstance, a dynamic fault tolerant routing algorithm is proposed. This algorithm can implement detour routing when there are both static and dynamic permanent faults in the network. That means the packet is able to move around the fanlts to the destination with a non-minimum path. In addition, the multi-level congestion control mechanism gives the algorithm the ability to distribute the load over the whole network and to avoid hotspots around the faults. Simulation results demonstrate the advantage of the proposed routing algorithm in terms of average packet latency and packet loss rate compared with negative-first routing algo- rithm and DyAD routing algorithm in the presence of permanent faults. For the proposed algorithm, it can get much less average packet latency and lead to less than 20% packet loss rate.
基金This research is supported by the National Natural Science Foundation of China and LSEC.
文摘Considering multiplicative Schwarz algorithm for solving algebraic obstacle problems, we show the geometric convergence of the algorithm by the use of discrete maximum principle. We also get a decay rate bound independent of the meshsize for the iterative error and illustrate the method by some numerical experiments.
文摘This paper presents a new interconnection net work topology ,called The twisted-cube connected network is a variant of the hypercube, and it has a better recursive structure . The regularity, connectivities, subgraphs of the twisted- cube conaected aetwork are studied . The twisted-cube connected network is proved to be a 3-cube-free network, which is the essential difference from the hypercube and variants of the hypercube. An efficient routing algorithm is proposed, and the diameter of n-dimensional twisted-cube connected network is proved to be just which is less than that of the hypercube.
基金supported by ACI NIM (171) from the French Ministry of Education and Scientific Research
文摘This work deals with the numerical localization of small electromagnetic inhomogeneities. The underlying inverse problem considers, in a three-dimensional bounded domain, the time-harmonic Maxwell equations formulated in electric field. Typically, the domain contains a finite number of unknown inhomogeneities of small volume and the inverse problem attempts to localize these inhomogeneities from a finite number of boundary measurements. Our localization approach is based on a recent framework that uses an asymptotic expansion for the perturbations in the tangential boundary trace of the curl of the electric field. We present three numerical localization procedures resulting from the combination of this asymptotic expansion with each of the following inversion algorithms： the Current Projection method, the MUltiple Signal Classification （MUSIC） algorithm, and an Inverse Fourier method. We perform a numerical study of the asymptotic expansion and compare the numerical results obtained from the three localization procedures in different settings.
文摘Energy efficiency, which consists of using less energy or improving the level of service to energy consumers, refers to an effective way to provide overall energy. But its increasing pressure on the energy sector to control greenhouse gases and to reduce CO2 emissions forced the power system operators to consider the emission problem as a consequential matter besides the economic problems. The economic power dispatch problem has, therefore, become a multi-objective optimization problem. Fuel cost, pollutant emissions, and system loss should be minimized simultaneously while satisfying certain system constraints. To achieve a good design with different solutions in a multi-objective optimization problem, fuel cost and pollutant emissions are converted into single optimization problem by introducing penalty factor. Now the power dispatch is formulated into a hi-objective optimization problem, two objectives with two algorithms, firefly algorithm for optimization the fuel cost, pollutant emissions and the real genetic algorithm for minimization of the transmission losses. In this paper the new approach （firefly algorithm-real genetic algorithm, FFA-RGA） has been applied to the standard IEEE 30-bus 6-generator. The effectiveness of the proposed approach is demonstrated by comparing its performance with other evolutionary multi- objective optimization algorithms. Simulation results show the validity and feasibility of the proposed method.
