Venkatesh Kumar Kodur

Michigan State University

United States

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Research Interests

Solid Mechanics

Structural Engineering

Construction Materials Engineering

Computational Mechanics

Fire Science

Poroelasticity

Building Physics

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Articles16

Collaborators2

Srishti Banerji

Assistant Professor of Structural Engineering

Utah State University

UNITED STATES

Daud Abdoh

University of Twente

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Venkatesh Kumar Kodur

University Distinguished Professor and Director, SAFE-D Centre

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Articles16

Characterization of Plant-Based Natural Fiber Ropes for Potential Futuristic Application as Reinforcement in Concrete Structures

Performance of steel beams with endplate connections exposed to fire

Evaluating Shear Response of UHPC Bridge Girders Exposed to Fire

Modeling via peridynamics for crack propagation in laminated glass under fire

A coupled 3D thermo-mechanical peridynamic model for cracking analysis of homogeneous and heterogeneous materials

Factors influencing pore pressure measurements in concrete during heating and its influence on fire-induced spalling

Numerical model for tracing the response of Ultra‐High performance concrete beams exposed to fire

Temperature-dependent properties of high-strength steel for evaluating the fire resistance of structures

Comparative Fire Behavior of Reinforced Concrete Beams Made of Different Concrete Strengths

Experimental and Numerical Investigation of Blast Wave Attenuation by Using Barriers in Different Configurations and Shapes

Performance of clay masonry prisms with light weight plaster exposed to standard fire exposure

Modeling parameters for predicting the fire-induced progressive collapse in steel framed buildings

Performance evaluation of lightweight insulating plaster for enhancing the fire endurance of high strength structural concrete

Computationally efficient and effective peridynamic model for cracks and fractures in homogeneous and heterogeneous materials

Predicting Flexural Capacity of Ultrahigh-Performance Concrete Beams: Machine Learning–Based Approach

Explainable machine learning using real, synthetic and augmented fire tests to predict fire resistance and spalling of RC columns

Collaborators2

Srishti Banerji

Daud Abdoh

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