Since bamboo has the advantages of straight grain, beautiful color, high strength and toughness, and excellent abrasion resistance, bamboo-based panels have been widely used in the fields of vehicle, construction, shi...Since bamboo has the advantages of straight grain, beautiful color, high strength and toughness, and excellent abrasion resistance, bamboo-based panels have been widely used in the fields of vehicle, construction, ship building, furniture, and decoration to partly take the place of wood, steel, plastic etc in China. This paper briefly described the basic component units, including strip, sliver, and particle, of bamboo-based panel and pointed out that to design the structure of bamboo-based panels should follow the principle of symmetric structure, surface forming method, and structuring principle of equalizing stress. According to the processing methods and formation of component units, the authors classified the bamboo-based panels in China into 13 types and presented the manufacturing technique and uses of the bamboo products, such as plybamboo, bamboo flooring, and bamboo-wood composite products in detail. In the last part of the paper, much information were offered on the output, market, and selling prospect of each type of bamboo-based panels.展开更多
The finite element artificial transmitting boundary method is employed here to treat the near field scattering of a cylindrical wave from an irregular cylinder. A comparison is made between this method and the analy...The finite element artificial transmitting boundary method is employed here to treat the near field scattering of a cylindrical wave from an irregular cylinder. A comparison is made between this method and the analytical one. And then examples are given to demonstrate the solution of several problems of the irregular object scattering. The method can not only produce clear physical pictures, but can efficiently handle many complicated scattering problems.展开更多
In the incremental sheet forming （ISF） process, springback is a very important factor that affects the quality of parts. Predicting and controlling springback accurately is essential for the design of the toolpath f...In the incremental sheet forming （ISF） process, springback is a very important factor that affects the quality of parts. Predicting and controlling springback accurately is essential for the design of the toolpath for ISF. A three-dimensional elasto-plastic finite element model （FEM） was developed to simulate the process and the simulated results were compared with those from the experiment. The springback angle was found to be in accordance with the experimental result, proving the FEM to be effective. A coupled artificial neural networks （ANN） and finite element method technique was developed to simulate and predict springback responses to changes in the processing parameters. A particle swarm optimization （PSO） algorithm was used to optimize the weights and thresholds of the neural network model. The neural network was trained using available FEM simulation data. The results showed that a more accurate prediction of s!oringback can be acquired using the FEM-PSONN model.展开更多
To solve the excessive huge scale problem of the traditional multi-bit digital artificial neural network（ANN） hardware implementation methods,a bit-stream ANN hardware implementation method based on sigma delta（Σ...To solve the excessive huge scale problem of the traditional multi-bit digital artificial neural network（ANN） hardware implementation methods,a bit-stream ANN hardware implementation method based on sigma delta（ΣΔ） modulation is presented.The bit-stream adder,multiplier,threshold function unit and fully digital ΣΔ modulator are implemented in a field programmable gate array（FPGA）,and these bit-stream arithmetical units are employed to build the bit-stream artificial neuron.The function of the bit-stream artificial neuron is verified through the realization of the logic function and a linear classifier.The bit-stream perceptron based on the bit-stream artificial neuron with the pre-processed structure is proved to have the ability of nonlinear classification.The FPGA resource utilization of the bit-stream artificial neuron shows that the bit-stream ANN hardware implementation method can significantly reduce the demand of the ANN hardware resources.展开更多
An artificial neural network model was developed to predict the oxidation of refractory gold concentrate （RGC） by ozone and ferric ions. The concentration of ozone and ferric ions, pulp density, oxygen amount, leach...An artificial neural network model was developed to predict the oxidation of refractory gold concentrate （RGC） by ozone and ferric ions. The concentration of ozone and ferric ions, pulp density, oxygen amount, leaching time and temperature were employed as inputs to the network; the output of the network was the percentage of the ferric extraction iron from RGC. The multilayered feed-forward networks were trained by 33 sets of input-output patterns using a back propagation algorithm; a three-layer network with 8 neurons in the hidden layer gave optimal results. The model gave good predictions of high correlation coefficient （R2=0.966）. The predictions by ANN are more accurate when compared with conventional multivariate regression analysis （MVRA）. In addition, calculation with ANN model indicates that temperature is the predominant parameter and ozone concentration is the lesser influential parameter in the pre-oxidation process of refractory gold ore. The ANN neural network model accurately estimates the ferric extraction during pretreatment process of RGC in gold smelter plants and can be used to optimize the process parameters.展开更多
基金This study was supported by National 9th-Five-Year Plan Project (No. 96-011-02-07-02).
文摘Since bamboo has the advantages of straight grain, beautiful color, high strength and toughness, and excellent abrasion resistance, bamboo-based panels have been widely used in the fields of vehicle, construction, ship building, furniture, and decoration to partly take the place of wood, steel, plastic etc in China. This paper briefly described the basic component units, including strip, sliver, and particle, of bamboo-based panel and pointed out that to design the structure of bamboo-based panels should follow the principle of symmetric structure, surface forming method, and structuring principle of equalizing stress. According to the processing methods and formation of component units, the authors classified the bamboo-based panels in China into 13 types and presented the manufacturing technique and uses of the bamboo products, such as plybamboo, bamboo flooring, and bamboo-wood composite products in detail. In the last part of the paper, much information were offered on the output, market, and selling prospect of each type of bamboo-based panels.
文摘The finite element artificial transmitting boundary method is employed here to treat the near field scattering of a cylindrical wave from an irregular cylinder. A comparison is made between this method and the analytical one. And then examples are given to demonstrate the solution of several problems of the irregular object scattering. The method can not only produce clear physical pictures, but can efficiently handle many complicated scattering problems.
基金Project(50175034) supported by the National Natural Science Foundation of China
文摘In the incremental sheet forming （ISF） process, springback is a very important factor that affects the quality of parts. Predicting and controlling springback accurately is essential for the design of the toolpath for ISF. A three-dimensional elasto-plastic finite element model （FEM） was developed to simulate the process and the simulated results were compared with those from the experiment. The springback angle was found to be in accordance with the experimental result, proving the FEM to be effective. A coupled artificial neural networks （ANN） and finite element method technique was developed to simulate and predict springback responses to changes in the processing parameters. A particle swarm optimization （PSO） algorithm was used to optimize the weights and thresholds of the neural network model. The neural network was trained using available FEM simulation data. The results showed that a more accurate prediction of s!oringback can be acquired using the FEM-PSONN model.
基金The National Natural Science Foundation of China (No.60576028)the Natural Science Foundation of Higher Education Institutions of Jiangsu Province(No.11KJB510004)
文摘To solve the excessive huge scale problem of the traditional multi-bit digital artificial neural network（ANN） hardware implementation methods,a bit-stream ANN hardware implementation method based on sigma delta（ΣΔ） modulation is presented.The bit-stream adder,multiplier,threshold function unit and fully digital ΣΔ modulator are implemented in a field programmable gate array（FPGA）,and these bit-stream arithmetical units are employed to build the bit-stream artificial neuron.The function of the bit-stream artificial neuron is verified through the realization of the logic function and a linear classifier.The bit-stream perceptron based on the bit-stream artificial neuron with the pre-processed structure is proved to have the ability of nonlinear classification.The FPGA resource utilization of the bit-stream artificial neuron shows that the bit-stream ANN hardware implementation method can significantly reduce the demand of the ANN hardware resources.
基金Project (2006AA06Z132) supported by High-tech Research and Development Program of ChinaProject (B604) supported by Leading Academic Discipline Project of Shanghai
文摘An artificial neural network model was developed to predict the oxidation of refractory gold concentrate （RGC） by ozone and ferric ions. The concentration of ozone and ferric ions, pulp density, oxygen amount, leaching time and temperature were employed as inputs to the network; the output of the network was the percentage of the ferric extraction iron from RGC. The multilayered feed-forward networks were trained by 33 sets of input-output patterns using a back propagation algorithm; a three-layer network with 8 neurons in the hidden layer gave optimal results. The model gave good predictions of high correlation coefficient （R2=0.966）. The predictions by ANN are more accurate when compared with conventional multivariate regression analysis （MVRA）. In addition, calculation with ANN model indicates that temperature is the predominant parameter and ozone concentration is the lesser influential parameter in the pre-oxidation process of refractory gold ore. The ANN neural network model accurately estimates the ferric extraction during pretreatment process of RGC in gold smelter plants and can be used to optimize the process parameters.
