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Devdas Menon

Researcher at Indian Institute of Technology Madras

Publications -  55
Citations -  486

Devdas Menon is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Slab & Engineering. The author has an hindex of 10, co-authored 50 publications receiving 388 citations. Previous affiliations of Devdas Menon include Indian Institutes of Technology.

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Vertical geometric irregularity in stepped building frames

TL;DR: In this paper, the authors proposed a regularity index to assess the degree of irregularities in a stepped building frame, and also proposed a modification of the code specified empirical formula for estimating fundamental period for regular frames, to estimate the fundamental time period of the stepped building.
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Dynamic studies of railtrack sleepers in a track structure system

TL;DR: In this paper, the dynamic response of a typical prestressed concrete railtrack sleeper due to wheel-track interaction dynamics, involving wheel and rail imperfections, under various parametric conditions is discussed.
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Multivariate Simulation and Multimodal Dependence Modeling of Vehicle Axle Weights with Copulas

TL;DR: A transformation invariant approach using copula functions is proposed for the multivariate simulation of dependent axle weights of different vehicle classes and is found to be in very good agreement with the observed data.
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Evaluation of dynamic load on railtrack sleepers based on vehicle-track modeling and analysis

TL;DR: In this paper, a dynamic interactive analysis is carried out between the vehicle and the track in the time domain using a finite element software, and the results of the interactive analysis give responses in the form of reaction time histories at the rail-seat locations during the passage of vehicle.
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Estimation of along-wind moments in RC chimneys

TL;DR: In this article, a comparative study reveals significant disparities among the various codal estimates of the design moments, given the same basic wind speed and terrain condition, and quantitatively assess the relative accuracy of these differing estimates with reference to rigorous stochastic dynamic analyses.