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Amlan K. Sengupta

Other affiliations: Indian Institutes of Technology
Bio: Amlan K. Sengupta is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Precast concrete & Girder. The author has an hindex of 5, co-authored 20 publications receiving 79 citations. Previous affiliations of Amlan K. Sengupta include Indian Institutes of Technology.

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Journal ArticleDOI
06 Jan 2021
TL;DR: In this article, an Artificial Neural Network (ANN) was used to predict the load bearing capacity and stiffness of perforated masonry walls subjected to in-plane loadings.
Abstract: Perforations adversely affect the structural response of unreinforced masonry walls (UMW) by reducing the wall’s load bearing capacity, which can cause serious structural damage. In the absence of a reliable procedure to accurately predict the load bearing capacity and stiffness of perforated masonry walls subjected to in-plane loadings, this study presents a novel approach to measure these parameters by developing simple but practical equations. In this regard, the Multi-Pier (MP) method as a numerical approach was employed along with the application of an Artificial Neural Network (ANN). The simulated responses of centrally perforated UMW by the MP method were validated utilizing full-scale experimental walls. The validated MP model was used to generate a simulated database. The simulated database includes results of analyses for 49 different configurations of perforated masonry walls and their corresponding solid masonry walls. The effect of the area and shape of the perforations on the UMW’s behavior was evaluated by the MP method. Following the outcomes of the verified MP method, the ANN is trained to develop empirical equations to accurately predict the reduction in the load bearing capacity and initial stiffness due to the perforation of UMW. The results of this study indicate that the perforations have a significant effect on the structural capacity of the UMW subjected to in-plane loadings.

27 citations

Journal ArticleDOI
TL;DR: In this paper, a multi-pier MP method was proposed to evaluate the behavior of masonrywalls under in-plane loads, which can be used in a commercial software and requires only truss elements with a nonlinear softening behavior.

18 citations

Journal ArticleDOI
TL;DR: In this article, the authors summarized and compared general conclusions of recent investigations on columns retrofitting using reinforced concrete jacketing, and their experimental, analytical, and numerical studies were reviewed and their findings collected and discussed.
Abstract: Seismic retrofitting and/or the strengthening of RC columns has been a popular area of research for decades. Currently, reinforced concrete jacketing is considered as the most common technique for repairing and strengthening of deficient and/or damaged RC columns. In general, this technique is a practical solution to recover and improve the load-carrying capacity and stiffness of reinforced concrete columns in earthquake-prone countries. It is a simple method that can be applied to any column cross section for rehabilitating structural elements by encasing the old member in a stiff jacket. The importance of this approach comes from its ability to improve the load-carrying capacity, strength, and stiffness of any column section significantly without the need for experienced labor or complicated installations process. This paper summarizes and compares general conclusions of recent investigations on columns retrofitting using reinforced concrete jacketing. As a part of this study, experimental, analytical, and numerical studies were reviewed and their findings were collected and discussed.

14 citations

Journal ArticleDOI
TL;DR: In this article, a Multi-pier (MP) method is used to determine the behavior of a wall under in-plane loads through the truss discretization method (TDM) along with several machine learning approaches such as Multilayer perceptron (MLP), Group of Method Data Handling (GMDH), and Radial basis function (RBF).

14 citations