Segmental Bridges under Combined Torsion, Bending and Shear

Segmental bridges with unbonded prestressed tendons have some advantages, such as the weather independence and the corrosion protection of prestressing tendons. This paper analyzed the behavior of a prestressed segmental bridge with unbonded tendons under combined loading of torsion, bending and shear. According to the experiment research, a modified skew bending model was developed to calculate the bearing capacity of segmental bridges subjected to combined bending, shear and torsion. The finite element method was used to investigate the deflection behaviors of such structure, also to check the theoretical model. The theoretical and FEM research results were compared favorably with the test results from Technical University of Braunschweig, Germany. Finally, suggestion for the design and construction of segmental bridges with external prestressing was made.

Estimating the Properties of Ground-Waste-Brick Mortars Using DNN and ANN

In this study,deep-neural-network(DNN)-and artificial-neural-network(ANN)-based models along with regression models have been developed to estimate the pressure,bending and elongation values of ground-brick(GB)-added mortar samples.This study is aimed at utilizing GB as a mineral additive in concrete in the ratios 0.0%,2.5%,5.0%,7.5%,10.0%,12.5%and 15.0%.In this study,756 mortar samples were produced for 84 different series and were cured in tap water(W),5%sodium sulphate solution(SS5)and 5%ammonium nitrate solution(AN5)for 7 days,28 days,90 days and 180 days.The developed DNN models have three inputs and two hidden layers with 20 neurons and one output,whereas the ANN models have three inputs,one output and one hidden layer with 15 neurons.Twenty-five previously obtained experimental sample datasets were used to train these developed models and to generate the regression equation.Fifty-nine non-training-attributed datasets were used to test the models.When these test values were attributed to the trained DNN,ANN and regression models,the brick-dust pressure as well as the bending and elongation values have been observed to be very close to the experimental values.Although only a small fraction(30%)of the experimental data were used for training,both the models performed the estimation process at a level that was in accordance with the opinions of experts.The fact that this success has been achieved using very little training data shows that the models have been appropriately designed.In addition,the DNN models exhibited better performance as compared with that exhibited by the ANN models.The regression model is a model whose performance is worst and unacceptable;further,the prediction error is observed to be considerably high.In conclusion,ANN-and DNN-based models are practical and effective to estimate these values.

MEASUREMENT OF INTERNAL STRESSES OF METAL MULTILAYER COMPOSITE COATINGS

The principle, formula and determination of internal stresses of metal multilayer composite coatings by means of the bending strip method were studied. Using this method, internal stresses of ion-plated metal multilayer composite coatings and thick monolayer coating of aluminium bronze, stainless steel and nickel-iron alloy were determined. The reason of decrement in internal stresses of multilayer composite coatings was discussed.