Shear Resistance Prediction of post-fire reinforced concrete beams using artificial neural network

In this paper, a prediction method based on artificial neural network was developed to rapidly determine the residual shear resistance of reinforced concrete (RC) beams after fire. Firstly, the temperature distribution along the beam section was determined through finite element analysis using software ABAQUS. A residual shear strength calculation model was developed and validated using the test data. Using this model, 384 data entries were derived for training and testing. The input layer of neural network involved parameters of beam height, beam width, fire exposure time, cross-sectional area of stirrup, stirrup spacing, concrete strength, and concrete cover thickness. The output was the shear resistance of RC beams. It was found that use of BP neural network could precisely predict the post-fire shear resistance of RC beams. The predicted data were highly consistent with the target data. Thus, this is a novel method for computing post-fire shear resistance of RC beams. Using this new method, further investigation was also made on the effects of different parameters on the shear resistance of the beams

The Precise Formula in a Sine Function Form of the norm of the Amplitude and the Necessary and Sufficient Phase Condition for Any Quantum Algorithm with Arbitrary Phase Rotations

In this paper we derived the precise formula in a sine function form of the norm of the amplitude in the desired state, and by means of he precise formula we presented the necessary and sufficient phase condition for any quantum algorithm with arbitrary phase rotations. We also showed that the phase condition: identical rotation angles, is a sufficient but not a necessary phase condition.Comment: 16 pages. Modified some English sentences and some proofs. Removed a table. Corrected the formula for kol on page 10. No figure

THE MIXED MODE CRACK PROBLEM IN A FGM LAYER

ABSTRACT Functionally graded materials (FGMs) are multiphase composites whose composition, microstructure and properties vary gradually. They can be tailored to meet the requirements encountered in practice through the design of their constituents. In this paper, analytical expressions for stress intensity factors of mixed-mode cracks in a FGM strip have been derived for the first time. A parametric study, by varying both the geometric and material parameters, is conducted to determine their effects on the stress intensity factors

Effect of policy incentives on the uptake of electric vehicles in China

© 2019 by the authors. In the backdrop of growing public concerns about climate change and air pollution, and the contribution of petroleum combustion in the transport sector to these issues, China has introduced a range of policy incentives for promoting the uptake of electric vehicles (EVs). These incentives have resulted in a rapid increase in EV stocks since the early 2010s, and this trend is expected to continue, or even accelerate, in the years to come, which would, in turn, lead to a policy-oriented EV market. The primary objective of the project is to develop an understanding of the effect of various policy incentives on EV uptake based on annual data of 43 cities from 2011 to 2017, and these policies mainly refer to those that focus on EV purchasing, registering, driving, and charging stages. The novelty of this paper is that we focused on policy effect on EV adoption behavior, rather than adoption intention which has widely been analyzed in previous studies. Results showed that the abolishment of purchasing and driving restriction, government subsidies, purchase tax exemption, and dedicated license plates significantly promote EV diffusion, and the effect of the two restrictions are more powerful. Thus, this study suggested that abolishment of purchasing and driving restrictions can be insisted to drive EV market share, meanwhile improving policies that can guide consumers through various motivations are also necessary

High temperature constitutive model of 6005A aluminum alloy

Use Gleeble-3800 thermal simulation test machine to conduct thermal tensile test on 6005A aluminum alloy at 623~723 K and 0,01~1 s-1 strain rate. Using the obtained true stress-strain curve, the modified Zerilli-Armstrong (m- Z-A) model considering strain compensation was used to construct the constitutive model of the alloy. The results show that the correlation coefficient and average absolute error of the m-Z-A model are 0,97311 and 4,1779 %, respectively. The experimental data is in good agreement with the predicted curve obtained by calculating the model, which verifies the feasibility of the model

High temperature constitutive model of 6005A aluminum alloy

Use Gleeble-3800 thermal simulation test machine to conduct thermal tensile test on 6005A aluminum alloy at 623~723 K and 0,01~1 s-1 strain rate. Using the obtained true stress-strain curve, the modified Zerilli-Armstrong (m- Z-A) model considering strain compensation was used to construct the constitutive model of the alloy. The results show that the correlation coefficient and average absolute error of the m-Z-A model are 0,97311 and 4,1779 %, respectively. The experimental data is in good agreement with the predicted curve obtained by calculating the model, which verifies the feasibility of the model