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Aydin Shishegaran
Researcher at Iran University of Science and Technology
Publications - 30
Citations - 489
Aydin Shishegaran is an academic researcher from Iran University of Science and Technology. The author has contributed to research in topics: Compressive strength & Mean squared error. The author has an hindex of 9, co-authored 27 publications receiving 219 citations. Previous affiliations of Aydin Shishegaran include Bauhaus University, Weimar & Ton Duc Thang University.
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Computational predictions for estimating the maximum deflection of reinforced concrete panels subjected to the blast load
TL;DR: In this paper, the authors investigated the resistance of reinforced concrete panels (RCPs) due to explosive loading using nonlinear finite element analysis and surrogate models, and found that the key parameters are the panel thickness and compressive strength with respect to the explosive strength of RCPs, and the explosive weight and distance from the explosive have the most impact on the RCP failure.
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Prediction of air quality in Tehran by developing the nonlinear ensemble model
TL;DR: In this paper, four prediction models are utilized for predicting daily AQI, including Auto Regressive Integrate Moving Average (ARIMA), Principal Component Regression (PCR), and Gene Expression Programming (GEP) as the second ensemble model.
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Developing conductive concrete containing wire rope and steel powder wastes for route deicing
TL;DR: In this article, the use of steel wire rope and steel powder wastes in the concrete matrix to improve conductive and mechanical properties of the conductive concrete and solve environmental issues associated with recycling and reusing these type of wastes is discussed.
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Performance of a novel bent-up bars system not interacting with concrete
TL;DR: In this article, a new reinforcement bar system having bent-up bars, covered with rubber tubes, is proposed to increase the bending and shear capacities of reinforced concrete members, where the compressive force in the upper point of the reinforced bars is exerted to the end point of these bars located under neutral axis, and the tensile stress is decreased in reinforcements located under the neutral axis.
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Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes
Isa Ebtehaj,Hossein Bonakdari,Mir Jafar Sadegh Safari,Bahram Gharabaghi,Amir Hossein Zaji,Hossien Riahi Madavar,Zohreh Sheikh Khozani,Mohammad Sadegh Es-haghi,Aydin Shishegaran,Ali Danandeh Mehr +9 more
TL;DR: In this article, a combination of sensitivity and uncertainty analyses with a machine learning technique is proposed as a tool for selection of the best input combination for modeling process at non-deposition conditions of sediment transport.