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Krishna Kumar

Krishna Kumar

Research Associate

Cambridge Center for Smart Infrastructure and Construction

ISG-80, Inglis Building
Department of Engineering
University of Cambridge
Trumpington Street

Cambridge , Cambridgeshire CB2 1PZ
Office Phone: 01223 748589


Krishna Kumar joined the Geotechnical Research Group at Cambridge University Engineering Department in October 2010 as a PhD student.  Krishna completed his PhD in January 2015 on  multi-scale multiphase modelling of granular flows. He was supervised by Professor Kenichi Soga. Krishna was funded by the Cambridge International Scholarship.  He is affiliated to the King’s College, Cambridge.


Krishna's work involves developing a large-scale big data framework that is capable of answering semantic queries on infrastructure monitoring using linked data model. He is working on adapting the Smart Cities standard to infrastructure monitoring. The big data framework will be able to provide real-time information and alerts (in case of a potential failure) on the behaviour of various structural elements in an infrastructure project. The linked data framework will enable engineers and researchers to understand the behaviour of infrastructure and its complex interactions with the environment during both construction and operation.

Krishna completed his PhD research at the University of Cambridge on multi-scale multiphase modelling of granular flows. His research was a part of a joint project with University of Montpellier II, France. Krishna is interested in understanding the mechanism of granular flow is of particular importance in predicting the run-out distances of debris flows and submarine landslides. A multi-scale approach is adopted to understand the fundamental microscopic parameters that control the complex macroscopic granular flow dynamics. A 2D/3D Material Point Method (MPM) code is extended to simulate granular flows as a continuum. A coupled GP-GPU compatible Discrete Element (DEM) – Lattice-Boltzmann Method (LBM) code with Large-scale Eddy Simulation (LES) technique is developed to study the underlying micro-mechanics of granular flows in fluid. Numerical simulations of granular flows under dry and submerged conditions were performed to understand the rheology of granular flows and the limitations continuum models have in simulating large deformation problems by investigating the mechanism of energy dissipation and flow kinematics.

Departments and Institutes

Department of Engineering:
PhD Research Student

Research Interests

Numerical modelling of granular flows

GPGPU computing

Big data & Linked data

Infrastructure monitoring

Key Publications

  • Soga, K., Kumar, K., Biscontin, G., and Kuo., M., (2014) “Geomechanics: from Micro to Macro”, IS-Cambridge 2014, Cambridge, UK. CRC Press.


  • Mutabaruka, P., Kumar, K., Delenne, J-Y., Radjai, F., and Soga, K., “Collapse and spread dynamics of granular piles: continuum versus discrete modelling”, EPJE
  • Soga, K., Alonso, E., Yerro, A., Kumar, K., and Bandara, S., (Under review) “Trends in large deformation analysis of landslide mass movement”, Geotechnique.
  • Kumar, K., Soga, K., and Delenne, J-Y., (2014) “Underwater granular flows down inclined plane”, IS-Cambridge 2014, UK, Paper No. 241.
  • Kumar, K., Soga, K., and Delenne, J-Y., (2013) “Multiscale Modelling of Granular Avalanches”, AIP Conf. Proc. 1542, 1250 (2013).
  • Kumar, K., Soga, K., and Delenne, J-Y., (2012) “Granular Flows in Fluid ”, in Discrete Element Modelling of Particulate Media, Royal Society of Chemistry, 59-66.