Fire resistance design of Reinforced concrete wall is one of the important issues for structural safety. The sequentially coupled thermal-stress analysis method in ABAQUS software is used to calculate the fire resistance of walls. The results of a parametric study to examine the influences of parameters, such as axial load level, lateral load level, height-to-thickness ratio, wall thickness, material strengths, steel reinforcement ratio and concrete protection thickness to reinforcements on fire resistance of RC walls are presented.
Nowadays in automotive industry JIT production mode is an overwhelming trend. And it resulted in an unprecedented challenge to the traditional mode of production designing, operation and information transaction. To solve the problems mentioned above a novel method is proposed to establish planning system models with tree discrete view structure, to visualize control and optimization in designing production line based on processing work flow. This model gave attention to various paths to access and control the production line, and also to communications with other systems among enterprises. Finally, this paper proposed a prototype system and took a production line of 5V engine cylinder head for example to examine the planning method. The results show it helps a lot in improving the efficiency and accuracy of production line planning.
A finite element model for square reinforced concrete stub column under overall fire and axial compression is developed. The temperature of columns subjected to simulated heating and cooling standard fire and the maximal temperature field were determined. The creep of steel bars, bond slip between steel bars and concrete, transformation of material properties were considered in the force analysis. The deformation under overall fire and the load bearing capacity of the column with initial load after fire are provided.
In Insurance industry, data redundancy is an extremely common problem in the population statistics. As a result a satisfactory clustering quality can rarely be obtained with the traditional clustering method. To handle this kind of problems a clustering model based on attributes reduction and SOM neural network was proposed. Using attributes reduction rules redundant information can be easily distinguished and essential attributes effectively located. And therefore the clustering quality can also be improved evidently. Experiments conducted in the H life insurance company show the method can cope with the problems mentioned above effectively.
The mechanical properties of axial compression aluminium members under cyclic loading were studied and compared with those of steel columns. In order to proceed to theoretical study on hysteretic behavior of aluminium columns, a method by finite element analysis was proposed. The method was based on FEA software, ANSYS. The analysis methods considered the effects of material nonlinearity, geometrical nonlinearity and initial imperfection. On this basis, hysteretic curves, reversal skeleton curves and stiffness degradation curves of 6061-T6 aluminium columns, 6061-T4 aluminium columns and Q235 steel columns under axial cyclic loading were obtained and compared. Results show that the hysteretic behavior of the aluminium columns is similar with the low carbon steel columns and is significantly influenced by constitutive relationship.
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