The composition control of molten steel is one of the main functions in the ladle furnace(LF)refining process.In this study,a feasible model was established to predict the alloying element yield using principal compon...The composition control of molten steel is one of the main functions in the ladle furnace(LF)refining process.In this study,a feasible model was established to predict the alloying element yield using principal component analysis(PCA)and deep neural network(DNN).The PCA was used to eliminate collinearity and reduce the dimension of the input variables,and then the data processed by PCA were used to establish the DNN model.The prediction hit ratios for the Si element yield in the error ranges of±1%,±3%,and±5%are 54.0%,93.8%,and98.8%,respectively,whereas those of the Mn element yield in the error ranges of±1%,±2%,and±3%are 77.0%,96.3%,and 99.5%,respectively,in the PCA-DNN model.The results demonstrate that the PCA-DNN model performs better than the known models,such as the reference heat method,multiple linear regression,modified backpropagation,and DNN model.Meanwhile,the accurate prediction of the alloying element yield can greatly contribute to realizing a“narrow window”control of composition in molten steel.The construction of the prediction model for the element yield can also provide a reference for the development of an alloying control model in LF intelligent refining in the modern iron and steel industry.展开更多
The traditional prediction methods of element yield rate can be divided into experience method and data-driven method.But in practice,the experience formulae are found to work only under some specific conditions,and t...The traditional prediction methods of element yield rate can be divided into experience method and data-driven method.But in practice,the experience formulae are found to work only under some specific conditions,and the sample data that are used to establish data-driven models are always insufficient.Aiming at this problem,a combined method of genetic algorithm(GA) and adaptive neuro-fuzzy inference system(ANFIS) is proposed and applied to element yield rate prediction in ladle furnace(LF).In order to get rid of the over reliance upon data in data-driven method and act as a supplement of inadequate samples,smelting experience is integrated into prediction model as fuzzy empirical rules by using the improved ANFIS method.For facilitating the combination of fuzzy rules,feature construction method based on GA is used to reduce input dimension,and the selection operation in GA is improved to speed up the convergence rate and to avoid trapping into local optima.The experimental and practical testing results show that the proposed method is more accurate than other prediction methods.展开更多
The design procedure is made for a mine shaft where permanent underground facilities are interconnected. The highly faulted grounds were identified using empirical and semi-empirical theories. Furthermore, the behavio...The design procedure is made for a mine shaft where permanent underground facilities are interconnected. The highly faulted grounds were identified using empirical and semi-empirical theories. Furthermore, the behavior types are presented. This paper presents excavation and support methods in such ground conditions and the calculations results show that the installation of the yielding elements have an effect on support elements and prevent shotcrete damage during the curing stage. Different numerical analyses carried out showed that, with the yielding elements installed, the total displacements increase but the final axial force reduces, and therefore, the characteristic compressive strength of shotcrete is not exceeded. The calculation results of ground loads and displacements on the designed support system are presented with a 3D numerical geo-mechanical model adopted for highly faulted ground surrounding deeper complex underground structures.展开更多
Reverse shoulder arthroplasty (RSA) is an effective treatment for rotator cuff tears. Despite its advantages, complications occur at a high rate. Complications requiring revision include a high rate of base plate fail...Reverse shoulder arthroplasty (RSA) is an effective treatment for rotator cuff tears. Despite its advantages, complications occur at a high rate. Complications requiring revision include a high rate of base plate failure, 38% of which are due to instability. The primary stability the base plate ensures is a crucial factor and, thus, is the subject of much debate in clinical studies and biomechanical research. This study is aimed to provide data that will contribute to the base plate’s pri-mary stability and glenoid longevity by clarifying the stresses at the scapular fossa and base plate interface associated with elevation after RSA. A 3D finite element model was created from the DICOM data for the scapulohumeral joint and SMR shoulder system. For loading conditions, 30 N was applied for each posi-tion with abduction angles of 0, 45, 90, and 135 degrees. A three-dimensional fi-nite element analysis was performed using the static implicit method with LS-DYNA. The von Mises stresses in the scapular fossa were found not to exceed the yield stress on the bone even after elevation to an abduction angle of 135 de-grees after RSA. It is rough to uniformly compare the yield stress and the von Mises stress, but it was inferred that the possibility of fracture is low unless a large external force is applied. A maximum von Mises stress showed 0 degrees of abduction, suggesting that the lowered position is in a more severe condition than the elevated position. If better improvement is desired, it may be necessary to devise ways to reduce the stress on the upper screw. .展开更多
Soil amendment with fly ash（FA） and combined supplementation with N_2-fixing cyanobacteria masses as biofertilizer were done in field experiments with rice. Amendments with FA levels, 0, 0.5, 1.0, 2.0, 4.0, 8.0 and ...Soil amendment with fly ash（FA） and combined supplementation with N_2-fixing cyanobacteria masses as biofertilizer were done in field experiments with rice. Amendments with FA levels, 0, 0.5, 1.0, 2.0, 4.0, 8.0 and 10.0 kg/m2, caused increase in growth and yield of rice up to 8.0 kg/m2, monitored with several parameters. Pigment contents and enzyme activities of leaves were enhanced by FA, with the maximum level of FA at 10.0 kg/m2. Protein content of rice seeds was the highest in plants grown at FA level 4.0 kg/m2. Basic soil properties, p H value, percentage of silt, percentage of clay, water-holding capacity, electrical conductivity, cation exchange capacity, and organic carbon content increased due to the FA amendment. Parallel supplementation of FA amended plots with 1.0 kg/m2 N_2-fixing cyanobacteria mass caused further significant increments of the most soil properties, and rice growth and yield parameters. 1000-grain weight of rice plants grown at FA level 4.0 kg/m2 along with cyanobacteria supplementation was the maximum. Cyanobacteria supplementation caused increase of important basic properties of soil including the total N-content. Estimations of elemental content in soils and plant parts（root and seed） were done by the atomic absorption spectrophotometry. Accumulations of K, P, Fe and several plant micronutrients（Mn, Ni, Co, Zn and Cu） and toxic elements（Pb, Cr and Cd） increased in soils and plant parts as a function of the FA gradation, but Na content remained almost unchanged in soils and seeds. Supplementation of cyanobacteria had ameliorating effect on toxic metal contents of soils and plant parts. The FA level 4.0 kg/m2, with 1.0 kg/m2 cyanobacteria mass supplementation, could be taken ideal, since there would be recharging of the soil with essential micronutrients as well as toxic chemicals in comparative lesser proportions, and cyanobacteria mass would cause lessening toxic metal loads with usual N_2-fixation.展开更多
基金supported by the National Natural Science Foundation of China(No.51974023)State Key Laboratory of Advanced Metallurgy,University of Science and Technology Beijing(No.41621005)。
文摘The composition control of molten steel is one of the main functions in the ladle furnace(LF)refining process.In this study,a feasible model was established to predict the alloying element yield using principal component analysis(PCA)and deep neural network(DNN).The PCA was used to eliminate collinearity and reduce the dimension of the input variables,and then the data processed by PCA were used to establish the DNN model.The prediction hit ratios for the Si element yield in the error ranges of±1%,±3%,and±5%are 54.0%,93.8%,and98.8%,respectively,whereas those of the Mn element yield in the error ranges of±1%,±2%,and±3%are 77.0%,96.3%,and 99.5%,respectively,in the PCA-DNN model.The results demonstrate that the PCA-DNN model performs better than the known models,such as the reference heat method,multiple linear regression,modified backpropagation,and DNN model.Meanwhile,the accurate prediction of the alloying element yield can greatly contribute to realizing a“narrow window”control of composition in molten steel.The construction of the prediction model for the element yield can also provide a reference for the development of an alloying control model in LF intelligent refining in the modern iron and steel industry.
基金Projects(2007AA041401,2007AA04Z194) supported by the National High Technology Research and Development Program of China
文摘The traditional prediction methods of element yield rate can be divided into experience method and data-driven method.But in practice,the experience formulae are found to work only under some specific conditions,and the sample data that are used to establish data-driven models are always insufficient.Aiming at this problem,a combined method of genetic algorithm(GA) and adaptive neuro-fuzzy inference system(ANFIS) is proposed and applied to element yield rate prediction in ladle furnace(LF).In order to get rid of the over reliance upon data in data-driven method and act as a supplement of inadequate samples,smelting experience is integrated into prediction model as fuzzy empirical rules by using the improved ANFIS method.For facilitating the combination of fuzzy rules,feature construction method based on GA is used to reduce input dimension,and the selection operation in GA is improved to speed up the convergence rate and to avoid trapping into local optima.The experimental and practical testing results show that the proposed method is more accurate than other prediction methods.
文摘The design procedure is made for a mine shaft where permanent underground facilities are interconnected. The highly faulted grounds were identified using empirical and semi-empirical theories. Furthermore, the behavior types are presented. This paper presents excavation and support methods in such ground conditions and the calculations results show that the installation of the yielding elements have an effect on support elements and prevent shotcrete damage during the curing stage. Different numerical analyses carried out showed that, with the yielding elements installed, the total displacements increase but the final axial force reduces, and therefore, the characteristic compressive strength of shotcrete is not exceeded. The calculation results of ground loads and displacements on the designed support system are presented with a 3D numerical geo-mechanical model adopted for highly faulted ground surrounding deeper complex underground structures.
文摘Reverse shoulder arthroplasty (RSA) is an effective treatment for rotator cuff tears. Despite its advantages, complications occur at a high rate. Complications requiring revision include a high rate of base plate failure, 38% of which are due to instability. The primary stability the base plate ensures is a crucial factor and, thus, is the subject of much debate in clinical studies and biomechanical research. This study is aimed to provide data that will contribute to the base plate’s pri-mary stability and glenoid longevity by clarifying the stresses at the scapular fossa and base plate interface associated with elevation after RSA. A 3D finite element model was created from the DICOM data for the scapulohumeral joint and SMR shoulder system. For loading conditions, 30 N was applied for each posi-tion with abduction angles of 0, 45, 90, and 135 degrees. A three-dimensional fi-nite element analysis was performed using the static implicit method with LS-DYNA. The von Mises stresses in the scapular fossa were found not to exceed the yield stress on the bone even after elevation to an abduction angle of 135 de-grees after RSA. It is rough to uniformly compare the yield stress and the von Mises stress, but it was inferred that the possibility of fracture is low unless a large external force is applied. A maximum von Mises stress showed 0 degrees of abduction, suggesting that the lowered position is in a more severe condition than the elevated position. If better improvement is desired, it may be necessary to devise ways to reduce the stress on the upper screw. .
基金supported by the project from Council of Scientific and Industrial Research,New Delhi,India (Grant No.21 (0859)/11/EMR-Ⅱ)
文摘Soil amendment with fly ash（FA） and combined supplementation with N_2-fixing cyanobacteria masses as biofertilizer were done in field experiments with rice. Amendments with FA levels, 0, 0.5, 1.0, 2.0, 4.0, 8.0 and 10.0 kg/m2, caused increase in growth and yield of rice up to 8.0 kg/m2, monitored with several parameters. Pigment contents and enzyme activities of leaves were enhanced by FA, with the maximum level of FA at 10.0 kg/m2. Protein content of rice seeds was the highest in plants grown at FA level 4.0 kg/m2. Basic soil properties, p H value, percentage of silt, percentage of clay, water-holding capacity, electrical conductivity, cation exchange capacity, and organic carbon content increased due to the FA amendment. Parallel supplementation of FA amended plots with 1.0 kg/m2 N_2-fixing cyanobacteria mass caused further significant increments of the most soil properties, and rice growth and yield parameters. 1000-grain weight of rice plants grown at FA level 4.0 kg/m2 along with cyanobacteria supplementation was the maximum. Cyanobacteria supplementation caused increase of important basic properties of soil including the total N-content. Estimations of elemental content in soils and plant parts（root and seed） were done by the atomic absorption spectrophotometry. Accumulations of K, P, Fe and several plant micronutrients（Mn, Ni, Co, Zn and Cu） and toxic elements（Pb, Cr and Cd） increased in soils and plant parts as a function of the FA gradation, but Na content remained almost unchanged in soils and seeds. Supplementation of cyanobacteria had ameliorating effect on toxic metal contents of soils and plant parts. The FA level 4.0 kg/m2, with 1.0 kg/m2 cyanobacteria mass supplementation, could be taken ideal, since there would be recharging of the soil with essential micronutrients as well as toxic chemicals in comparative lesser proportions, and cyanobacteria mass would cause lessening toxic metal loads with usual N_2-fixation.
