By Er Ajay Gupta
Read or Download Study on Reinforced Concrete Frame with Solid Infill Masonry using Artificial Neural Network (ANN) RC Infill Wall Model in ANSYS (Ajay Gupta) PDF
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Additional resources for Study on Reinforced Concrete Frame with Solid Infill Masonry using Artificial Neural Network (ANN) RC Infill Wall Model in ANSYS (Ajay Gupta)
Example text
Lightweight mortar, designed mortar with a dry hardened density lower than 1500 kg/m3. 4. Pre-batched mortar, consisting of constituents batched in a plant, supplied to the building site and mixed there under factory specified proportions and conditions. 5. Site-made mortar, composed of primary constituents batched and mixed on the building site. The types of the mortar and their corresponding properties used here for modeling are stated as below. 5 Reinforced Concrete Concrete is a mixture of cement (usually Portland cement) and stone aggregate.
2 Modelling Strategy A parametric study is performed to obtain lateral stiffness of infill frames with varying aspect ratios. The FE model is prepared for the purpose. The FE model is first calibrated using published results of experimental specimens available in the literature. This calibrated model is used in the parametric study to determine the lateral stiffness of infill frames. The width of equivalent diagonal strut for the infill frame using other established relations is compared to that estimated from the FE method.
The validation of the predicted data sets was done in reference to those data sets from Ansys analysis. The predicted data and the desired data and their corresponding difference in percentage which indicates the accuracy of the predicted data are shown in the table below. 01%. Hence ANN can be taken as a powerful tool for the prediction of initial design parameters related to any field especially if the mass data regarding that field is available. For the data sets given above it can be noticed that error percentage is relatively high in stress and strain fields whereas the error percentage is almost negligible in reaction fields (displacements, shear and vertical reaction).
