The Uncertainty Laboratory
Location: MSB 108
Mechanical Science Block
Department of Applied Mechanics
Indian Institute of Technology Madras
Email: uncertaintylab.iitm@gmail.com
Twitter: @UncertaintyLab
Phone: +91 44 2257 5071
Location: MSB 108
Mechanical Science Block
Department of Applied Mechanics
Indian Institute of Technology Madras
Email: uncertaintylab.iitm@gmail.com
Twitter: @UncertaintyLab
Phone: +91 44 2257 5071
Please visit our FaceBook page
for more information and photographs.
Dr Somnath Roy
(PhD in Physics, Jadavpur University)
Nonlinear Dynamics and control
Rahul Das
PhD Student
Targeted energy transfer in nonlinear dynamical systems
Co-guide: Prof Anil K Bajaj, Purdue University
Short video
Rajanya Chatterjee
PhD Student
Bladeless wind energy harvesters
Co-guide: Prof Sunetra Sarkar, Aerospace Engg
Short video
Samana P
PhD Student
Dynamics of complex networked systems
Prabhat Karmakar
PhD Student
Reduced order modeling in mechanics of materials
Co-guide: Prof Ilaksh Adlakha, Applied Mechanics
Nurani Rajagopal Rohan
Chaotic associative memory models
Co-guide: Prof V Srinivasa Chakravarthy, Dept of Biotechnology
Prasad Sashikant Kokitkar
Machine learning in complex dynamical systems
Ujwal Vishwanath
Mechanical Engineering
IDDD in Complex Systems & Dynamics
Nonlinear Dynamics and control
Anushree KS
Mechanical Engineering
IDDD in Computational Engineering
Kunjeti Dharanidhar Gupta
IDDD in Complex Systems & Dynamics
Class of 2025
B.Tech: Engineering Physics
FPGA implementation of chaotic associative memory
Dr. Mahashweta Patra
PhD (IISER, Kolkata, 2019)
Postdoc 2019-2020
Smooth discontinuous maps
Subsequent position: Post-doc at Indiana University, USA
Dr. Jithin Jith
PhD (IIT Madras, 2018)
Post-doctoral Researcher (2018-2019)
Stochastic modelling of buffeting in fin structures
Co-guide: Prof Sunetra Sarkar, Aerospace Engg
Subsequent position: Schlumberger
Dr. Dheelibun W Remigius
PhD (IIT Madras, 2018)
Post-doctoral Researcher (2018)
Intermittency in rotating discs in compresisble bounded fluid medium
Co-guide: Prof Sunetra Sarkar, Aerospace Engg
Subsequent Position: Post-doctoral Researcher, Technical University of Denmark
Dhrubajyoti Biswas
PhD (2024)
BSc Physics, St Xaviers Kolkata
Emergent dynamics of large ordered complex systems Download
This thesis explores emergent phenomena in large coupled dynamical systems. It examines the Kuramoto model with unidirectional interlayer, generalized adaptive, and higher order interactions, revealing various types of transitions to synchrony. It also investigates ageing in a network of Rulkov neurons, highlighting the interplay of connectivity, coupling strength, and noise. Finally, computational benefits of utilizing GPUs for large-scale dynamical system simulations are also presented.
Examiners
Prof Sudeshna Sinha
Physics
IISER Mohali
Personal website
Co-guide: Prof Vaibhav Madhok, Physics
Short video
Saranya Biswas
PhD (2024)
BE Mechanical Engineering, Jadavpur University
Characterization of noisy dynamical systems Download
The thesis investigates characterization of attractors and the stability of noisy dynamical systems. A joint probability density function based definition of stochastic fixed points and limit cycles have been proposed. The local stability of such attractors have been quantified by developing a Hamiltonian based metric, which enables identifying the most likely locations in the attractor for trajectories to escape. A Shannon entropy based global stability measure has been proposed for the stability of coexisting attractors in multistable systems. Finally, a stochastic basin stability based method has been proposed that predicts the onset of multiplicative noise induced intermittency in a computationally efficient manner for higher order systems.
Examiners:
Prof Anirban Chakraborti
School of Computational and Integrative Sciences
Jawaharlal Nehru University
Prof Manish Shrimali
Department of Physics
Central University of Rajasthan
Short video
Vineeth Reddy
PhD (2024)
Dual Degree, Civil & Applied Mechanics, IIT Madras
Reduced order models to predict mesoscale mechanical behavior of polycrystalline materials Download
Co-guide: Prof Ilaksh Adlakha, Applied Mechanics
The fatigue behavior of polycrystalline materials is dictated by the mesoscale spatial material heterogeneity. This thesis focusses on developing reduced order models that efficiently represent the material microstructure and predict the mesoscale mechanical behavior of polycrystalline materials in a computationally efficient manner. The first part of the thesis explores low dimensional representations, such as Voronoi tesselation and principal component analysis. Subsequently, fatigue hot spots at the mesoscale have been identified using methods based on low rank tensor decomposition techniques and transfer learning based neural networks. The developments have been shown to lead to predictions that compare favourably with results using crystal plasticity simulations for polycrystalline aggregates subjected to axial deformations.
Examiners
Prof Alankar
Mechanical Engineering
IIT Bombay
Prof Ravi Shastri Ayyagiri
Mechanical Engineering
IIT Gandhinagar
Prof Kanjarla Anand Krishna
Metallurgical and Materials Engineering
IIT Madras
Short video
Present: GKN Aerospace Bangalore
Dr. Aasifa Rounak
PhD (2022)
B.Tech Mechanical Engineering, VSSUT Burla.
Noise in multistable nonsmooth dynamical systems Download
The thesis focuses on the effects of additive noise on the behaviour of nonsmooth dynamical systems where multiple stable attractors co-exist. The trajectories in the state space of such systems are piecewise continuous and exhibit discontinuities at the switching boundaries. The interplay between the trajectories and the switching boundaries induces strong nonlinear behaviour leading to rich dynamics with the system exhibiting stability and bifurcation characteristics that are not observed in smooth nonlinear dynamical systems. The presence of additive noise in the system creates additional complexities resulting in dynamical behaviour that are difficult to interpret. This study investigates the physics associated with the behaviour of such nonsmooth systems in the presence of additive noise and develops measures for characterising dynamical features such as the attractor space, basins, stability of attractors and noise-induced phenomena. More specifically, the study focuses on noise-induced transitions in systems that possess coexisting attractors and developing quantitative measures that can be used for predicting these transitions.
Publications
Examiners:
Prof Rachel Kuske
Department of Mathematics
Georgia Institute of Technology USA
Prof Marian Wiercigroch
School of Engineering
Unievrsity of Aberdeen
Post PhD: Post-doc, School of Mechanical and Materials Engineering, University College Dublin, Ireland
Present: Assistant Professor, University of College Dublin, Ireland
Short video
Personal website
Dr. Rahul Kumar
PhD (2022)
Analysis of bladed discs with spatial random inhomogeneities Download
Co-guide: Prof S Faruque Ali, Applied Mechanics
A computationally efficient finite element (FE) based method is developed for the probabilistic analysis of bladed discs with random spatial inhomogeneities. The spatial inhomogeneities arise on account of manufacturing tolerances despite the most stringent quality controls and are modelled as non-Gaussian random fields. A high fidelity FE model for the designed system, free from any uncertainties, is assumed to be available. A key challenge lies in developing a weak form representation for the non-Gaussian fields defined over irregular and complex domains like the blades, and integrating with existing FE models. Polynomial chaos (PC) based frameworks are developed for weak form representation of the random fields, that directly use the limited available measurements. The response quantities are expressed in the same PC basis and which serve as surrogate models for computationally efficient probabilistic analyses. The computational bottleneck in developing these surrogate models is overcome by adopting stochastic reduced order modelling, that involves integrating methods such as static condensation and system equivalent reduction expansion process (SEREP), with PC based FE formalisms. The efficacy of the proposed frameworks is demonstrated through numerical examples involving both academic rotors as well as industrial rotor blades.
Publications
Examiners
Prof Hamed Haddad Khodaparast
Aerospace Engineering
Swansea University
Prof Arunasis Chakraborti
Civil Engineering
IIT Guwahati
Awards
Institute Research Award (2022)
Post PhD: Visiting Assistant Professor, Department of Mathematics, Georgia Tech, USA
Short video
Dr. S Krishnakumar
PhD (2020)
Multiplicative noise induced intermittency in fluid-elastic dynamical systems Download
This thesis studies the phenomenon of mul- tiplicative noise induced intermittency (mNII) arising due to the streamwise flow velocity fluctuations, which appear in the governing equations of motion as parametric or multi- plicative noise. The conditions for the onset and disappearance for mNII are developed analytically. The role of correlation in the flow fluctuations is investigated. The theoretical developments proposed in this thesis are investigated numerically through a set of progressively complex mathematical models. The importance of mNII is demonstrated through experimental investigations on a flow induced oscillations based energy harvester.
Publications
Examiners
Dr. James Heagy
Institute for Defence Analysis
Virginia USA
Prof Kartik Venkatraman
Aerospace Engineering
IISc Bangalore
Post PhD: Post-doc at Divecha Center for Climate Change, Indian Institute of Science Bangalore
Dr. Chandan Bose
PhD (2019)
Dynamical analysis of unsteady flow phenomena around flapping wings Download
Co-guide: Prof Sunetra Sarkar, Aerospace Engineering
The primary aim of this dissertation is to investigate the transitional wake dynamics and nonlinear fluid-structure interaction (FSI) behavior of flapping wings in low Reynolds number (Re) regime through high-fidelity numerical simulations. The study focusses on identifying the dynamical transition routes to chaos in the unsteady flow-field of rigid and flexible flapping wings and on examining the underlying flow-physics behind the chaotic transition.
Publications
Examiners
Prof. Amit Agarwal
Mechanical Engineering
IIT Bombay
Prof Bernd Noack
TU Berlin
Germany
Awards
V Ramamurthy Best Thesis Award in Applied Mechanics Department, IIT Madras, 2020
Indian National Academy in Engineering (INAE) Innovative Students Projects Award, 2020
Institute Research Award (2020).
Post PhD: Post-doc at University of Liége, Belgium
Present: Assistant Professor,
Aerospace Engineering
University of Birmingham
Website
Short video
Dr. Jithin Jith
PhD (2018)
Acousto-elastic interactions in high pressure centrifugal compressors Download
The study develops a computationally efficient numerical framework for accurate acousto-elastic eigenanalysis of high-pressure centrifugal compressors. CO2 is chosen as the working fluid because of its various applications in the oil and gas industry. Under high-pressure conditions, CO2 transitions into a supercritical fluid and brings about large changes in its thermophysical properties. The first part of the thesis studies the effect of these changes on the eigenfrequencies and eigenmodes of an idealised centrifugal compressor.
Following this, the acousto-elastic computational framework is augmented to account for viscous and thermal dissipative phenomena in the acoustic boundary layers of the working fluid. Conventional acousto- elastic analyses of centrifugal compressors do not consider the visco-thermal effects, and therefore fail to capture the impact of these losses on the frequency response of the compressor. A novel computationally efficient numerical framework, using the Boundary Layer Impedance (BLI) model, is proposed to account for the visco-thermal effects.
Publications
Co-guide: Prof Sunetra Sarkar, Aerospace Engineering
Examiners
Prof CS Manohar
Civil Engineering
IISc Bangalore
Post PhD: Schlumberger
Dr. Hridya P
PhD (2018)
Reduced order modelling in stochastically parametered vibrating fluid structure interaction systems Download
This study focuses on the development of reduced order models that enable enhancing the computational efficiency of the solution of stochastically parametered large ordered linear dynamical systems. The finite element (FE) discretized equations of motion are assumed to be the starting point of the analysis with the distributed parameter uncertainties being assumed to be represented in the weak form as a vector of random variables with specified probability density function (pdf). A two step procedure is adopted to develop the reduced order models for these systems. A reduction in the state space dimension is first achieved by adopting modal truncation along with the system equivalent reduction expansion process (SEREP). These developments are extended to the stochastic case by applying Polynomial Chaos Expansion (PCE) to bring about further reduction in the stochastic dimensions by retaining only the dominant stochastic modes in the basis space. The proposed developments enable building surrogate models for complex large ordered stochastically parametered fluid-structure interaction (FSI) systems which lead to accurate predictions at significantly reduced computational costs.
Publications
Co-guide: Prof Sunetra Sarkar, Aerospace Engg
Examiners:
Prof Kartik Venkatraman
Aerospace Engineering
IISc Bangalore
Prof Ioannis Kougloumtzoglou
Civil and Environmental Engineering
Columbia University, New Yoirk
Post PhD: Post doctoral researcher, Civil Engineering, Indian Institute of Science
Present: Assistant Professor
Civil Engineering,
Cochin University of Science and Technology
Dr. J Venkatramani
PhD (2018)
Intermittency in pitch-plunge aeroleastic systems Download
This thesis focuses on investigating the phenomenon of intermittency in the dynam- ical behavior of aeroelastic systems. Wind tunnel experiments on a NACA 0012 profile reveal the rpesence of fluctuations in the flow lead to an earlier onset of flutter. Stochastic bifurcation analysis is carried out to estimate the dynamical stability boundaries. The physical mechanisms for the intermittent oscillations that presage loss of stability have been investigated. A set of precursor measures based on recurrence quantification analysis, Hurst exponents, statsitical entropy and complexity based measures have been developed to predict the onset of flutter.
Publications
Co-guide: Prof Sunetra Sarkar, Aerospace Engineering
Examiners
Prof Dewey Hodges
Aerospace Engineering
Georgia Tech, USA
Prof Kartik Venkatraman
Aerospace Engineering
IISc Bangalore
Awards
V Ramamurthy Best Thesis Award in Applied Mechanics Department, IIT Madras
Post PhD: Assistant Professor,
Mechanical Engg, Shiv Nadar University, Noida.
website
Dr. Pankaj Kumar
PhD (2017)
Investigations into the bifurcation of stochastically excited nonlinear oscillators Download
The focus of the study undertaken in this dissertation has been on the development of numerical techniques for the dynamical stability analysis of nonlinear oscillators sub- jected to random excitations, and to gain an understanding on the dynamical behaviour of such systems at different parameter regimes. Essentially, the study builds on the established ideas of dynamic stability analysis of deterministic systems and extends these concepts in interpreting the behaviour of stochastically excited nonlinear oscillators. The crux in this approach lies in writing the corresponding Fokker-Planck (FP) equation for these nonlinear oscillators and developing numerical techniques for their solution. Inferences about the stochastic stability are made based on the topological changes in the structure of the joint probability density function (pdf) of the associated state variables, at different parameter regimes as well as the topological changes associated with the phase plane trajectories. The use of various non-smooth coordinate transformations has been investigated for analysing problems involving discontinuities in the vector field, for developing the corresponding Fokker-Planck-Kolmogorov equations.
Publications
Co-guide: Prof S Narayanan, Mechanical Engg
Examiners:
Prof CS Manohar
Civil Engineering
IISc Bangalore
Prof Arvid Naess
Department of Mathematics
Norwegian University of Science and Technology, Trondheim
Post PhD: Senior Scientist
Bharat Heavy Electrical Limited, India (External Registrant)
Dr. Y Appalanaidu
PhD (2016)
Stochastic damage growth in circular pipes carrying high temperature fluids Download thesis
The work reported in this thesis investigated the problem of predicting the damage growth in structural components in industrial installations that carry liquids at high tem- peratures, and estimating the risk of failure. The investigations were limited to the damage growth mechanisms due to thermal creep and fatigue only. The damage processes and the material properties were modelled as random inhomgeneities in space and time. Stochastic finite element frameworks have been used for developing a weak formulation of the problem. Probabilistic analsyes have been carried out to estimate the risk of failures in these components.
Publications
Examiners
Prof Debraj Ghosh
Civil Engineering
IISc Bangalore
Prof Achintya Haldar
Civil Engineering
University of Arizona, USA
Post PhD: Associate Professor
Mechanical Engg, Vellore Institute of Technology
Website
Dr. P Sasikumar
PhD (2015)
Uncertainty quantification and reliability analysis of laminated composite structures with spatial random inhomogeneities Download
The work reported in this thesis is aimed towards the development of methodologies for quantification of the uncertainties associated with laminated CFRP composite structures and estimating their failure probability. Most of the studies available in composite literature have focussed on developing models for the structural system that ignore the effects of spatial random inhomogeneities in the material properties. This is primarily due to the complexities involved in modelling the spatially random inhomogeneities in the material properties of composite structural systems and their subsequent analysis. The present study has focussed on the development of a stochastic finite element methodology that enables incorporating non-Gaussian models for the spatial random inhomogeneities in the material properties in laminated CFRP composites.
Examiners
Prof Marios Chryssanthopoulos
Structural Engineering
University of Surrey, UK
Prof CS Manohar
Civil Engineering
IISc Bangalore
Awards
Innovative Thesis Award by Indian National Academy of Engineering (INAE)
Post PhD: Scientist
Vikram Sarabhai Space Center
Trivandrum, India (External Registrant)
Avisha Ghorpade
MS S
Stochastic Modelling and analysis of fin buffeting Download
This study aims to model buffeting in tail fin of delta-wing combat aircraft for estimation of premature failure due to fatigue damage. Buffeting occurs when the tail fin is subjected to irregular oscillations due to the flow from aircraft wings striking its surface. This phenomenon impacts the aerodynamic performance of the aircraft and may also affect the fatigue life of the fin. The separated flow from a delta wing is stochastic in nature and is known to be Gaussian. The present study quantifies the forces on the tail fin from CFD analyses with random boundary conditions and its response have been obtained from FE analyses. A solver that couples Navier-Stokes solver with Finite Element structural solver has been developed to find the response of the fin using a one-way fluid-structure interaction approach. Further, random vibration analysis was done to estimate the random stresses developed in the fin due to buffeting. The rainflow fatigue damage and the expected life of the fin were calculated based on analytico-computational algorithms. The predictions have been validated using Monte Carlo simulations.
Co-guide: Prof Sunetra Sarkar, Aerospace Engg
Placement: Eaton
Short video
N Ganesh
MS (2013)
A spectral approach to time variant reliability analysis of randomly excited nonlinear vibrating systems Download
The focus of this study is on the development of a methodology by which one can derive analytical/numerical approximations for the crossing statistics of the response of nonlinear structures subjected to random vibrations. This involves transforming the problem into a mathematical subspace spanned by the basis vectors obtained from the projections of the spectral content of the input process. The present study investigates the use of a special class of stochastic collocation technique- the sparse grid approach based on Smolyak’s algorithm, for computing these multi-dimensional inte- grals. The usefulness of this method lies in its computational efficiency in comparison to other existing techniques.
Placement: Design Engineer
TVS Motors, Bangalore
Present: GE Renewable Energy, Bangalore
Rangaraj Pandurangan
MS (2013)
Polynomial chaos in bootstrap particle filtering for system identification Downalod
This study focuses on the use of particle filters, more specifically the bootstrap particle filter, for identification of the system parameters of dynamical systems from measurement data. The underlying principle of the bootstrap particle filters is based on Bayesian framework. The implementation of the bootstrap particle filter involves solving the forward problem a large number of times using Monte Carlo simulations. This is computationally intensive, especially in dealing with com- plex systems where the solution of a single forward problem requires significant com- putational time. The present study focuses on the development of a new approach of coupling the bootstrap particle filter with Polynomial Chaos Expansion to reduce the computational effort. Polynomial Chaos based methods are spectral uncertainty quantification tools based on projecting the uncertain parameters along random basis functions, which are in the form of polynomials. The central idea of the proposed method lies in projecting the forward problem into a space spanned by orthogonal functions and performing filtering in this space. This ensures an accelerated solution of the forward problem, requiring significantly less computational efforts. Moreover, performing the filtering in the random space bypasses the requirement of constructing the polyno- mial chaos expansion at later time steps in the identification algorithm. This further reduces the required computational effort.
Co-guide: Prof Abhijit Chaudhuri, Applied Mechanics
Placement: General Electric, Bangalore.
Present: Benz, Bangalore
Bharat Pokale
MS (2013)
An experimental study on system identification in beams for vibration measurements Download
A particle filter based methodology is developed for damage identification from ambient vibration measurements obtained from physical experiments. The focus of the study has been primarily on identifying vibration induced fatigue cracks. To demonstrate the applicability of the proposed method, small scale laboratory experiments have been conducted and the time history of the response obtained from accelerometer readings has been assumed to be the inputs to the particle filter algorithm. It has been demon- strated that the method is useful not only for identifying the presence of damage but also for estimating the severity and the approximate location of what are essentially localized damages.
Placement: Assistant Professor
Hindustan Univeristy, Chennai.
R Rangaraj
MS (2012)
Identification of fatigue cracks in vibrating beams using particle filtering algorithm Download
The focus of this study is on the development of a methodology for identifying fatigue cracks in beams from vibration measurements. This constitutes an inverse problem. A particle filter based methodology is developed to address the problem. This method is built on the principles of dynamic state estimating within a Bayesian frame work. The beam is modeled using finite elements with crack parameters to be identified be- ing modeled as random variables with assumed probability density function. As more measurements become available, the probability density functions of these variables are updated following Bayesian framework. Thus the variability associated with these variables decrease with time as more measurements are assimilated. This leads to iden- tification of the fatigue cracks with reasonable accuracy levels. The performance of the proposed method is demonstrated through numerical case studies.
Co-guide: Prof Anuradha Banerjee, Applied Mechanics
Placement: Senior Engineer
Asok Leyland Motors, Chennai. (External Registrant)
Swarnakshi Kailash
IDDD in Complex Systems & Dynamics
Class of 2024
B.Tech: Bioscience
Advanced computational framework for epidemic simulation in large scale networks
Placement: Cleammax
Guru Viknesh S
IDDD in Complex Systems & Dynamics
Class of 2023
B.Tech: Metallurgy
Prediction of chaotic responses using Koopman theory
Placement: Inito
Adithya Narayanan
IDDD in Complex Systems & Dynamics
Class of 2023
B.Tech: Aerospace Engineering
Sindy based prediction in chaotic systems
Placement: Indus Insights
Devarkonda Chandrasekhar Yashwant
M.Tech Student (2019) Applied Mechanics
Numerical investigations into fluid-structure interactions
Placement: K12 Techno Service Private Limited, Bangalore
Siddhesh Godbole
Dual Degree (2015): Civil & Applid Mechanics
Parallelization in uncertainty quantification analysis in large order dynamical systems Download
Placement: PhD Student,
University of Melbourne, Australia
Vighnesh Ambetkar
Dual Degree (2015): Naval Architecture & Applied Mechanics
A saddlepoint approach to estimating crossing statistics for random processes Download
Placement: Indian Register for Shipping
At present: DNV GL
Jainendra Dubey
M.Tech (2015): Applied Mechanics
Interfacing comercial softwares for uncertainty quantification in fluid structure interaction problems
Placement: Scientist F,
Indira Gandhi Center for Atomic Research, Kalpakkam (External Registrant)
Anindya Roy
M. Tech (2014): Applied Mechanics
Development of stochastic FEM based methodlogy for uncertainty quantification in structures with non-Gaussian inhomogenieties
Placement: PhD Student,
Technical University of Delft, The Netherlands.
T Sravan Kumar
Dual Degree (2014): Civil Engg & Applied Mechanics
Numerical studies on noisy Lorentz attractor
Placement: Risk Analyst,
Nomura Services India Pvt Ltd
Abhishek Ghiya
M. Tech (2013): Applied Mechanics
Energy harvesting from wind vibrations
Placement: Scientist,
Defence Research Development Organization, Pune (External Registrant)
Kaushik Mohan
Dual Degree (2013): Naval Architecture & Applied Mechanics
Multivariate extreme value distributions for vector LMA processes
Placement: Deutsche Bank
Later: New York University
Abhishek Venketesweran
Dual Degree (2013): Aerospace Engineering
Polynomial chaos in multiscale modelling of uncertainties in composite structures Download
Placement: PhD Student,
State Univeristy of New York, Buffalo
Jithin Jith
Dual Degree (2012): Naval Architecture & Applied Mechanics
Crossing statistics of second order response of structures subjected to LMA loadings Download
Placement: PhD Student, IIT Madras
Yash Vyas
Dual Degree (2012): Civil Engg & Applied Mechanics
Modelling of uncertainties and analysis os stochastic damage growth in structural systems Download
Placement: Wipro Technologies,
Financial and banking sector
Later: Stanford University
Lokeshwar Rao M
M.Tech (2011): Applied Mechanics
Parameter estimation in vibrating structures using particle filtering algorithm
Placement: General Electric, Bangalore
Radhika Nair
M.Tech (2010): Applied Mechanics
Damage detection in aging vibrating structures using a probabilistic method.
Placement: PhD Student, IISc Bangalore
At present: Faculty at LBS Institute of Technology for Women, Trivandrum
Rajasekhar Reddy
Dual Degree (2009): Mechanical Engineering
Stochastic Hopf bifurcation of a 2-dimensional turbine blade in randomly fluctuating flow
Placement: Headstrong, Hyderabad
At present: HealthLucid, Bangalore
Manoj Kattaminchi
M. Tech (2009): Applied Mechanics
Uncertainty quantification of natural frequencies of jointed segments of aerospace vehicles
Placement: Scientist,
Defence Research Development Organization, Hyderabad (External Registrant)
Naajein Cherat
M. Tech (2009): Applied Mechanics
Stochastic fatigue crack growth in randomly vibrating structures
Placement: General Electric, Bangalore
Royyuru Sai Prasanna Gangadhar
IDDD in Data Science
Class of 2024
B.Tech: Mechanical Engineering
Dynamics of fake news
Co-advisor: Prof Ponnurangam Kumaraguru
IIIT Hyderbad
Ashwad Raaj
2021-2023
Networks in climate science
Mohit Kumar
B.Tech Mechanical Engineering
2018-2022
Awards: Presidents Gold Medal 2022, IIT Madras
Website
Post graduation: PhD in Purdue University
Siddharth Gupta
Data driven approach to reduced order modelling in nonlinear dynamical systems
Placement: National Thermal Power Corporation
Ramakrishna Kuppa
2011-2019
Crossing statistics of non-Gaussian random processes
Affiliation: Sreenidhi Institute of Technology, Hyderabad (External Registrant)
Bidhayak Goswami
2017-2018
Placement: PhD Student, IIT Kanpur
Indranil Hazra
2016-2017
Placement: PhD Student, University of Waterloo, Canada
Currently Assistant Professor, IIT Jodhpur
Sreelekha Etikyala
2015-2017
Placement: PhD Student, Chalmers University, Sweden
At present, working in Volvo, Sweden
V Srinivasan
2008-2010
Placement: Eaton
At present: Aptiv Technical Center India
Design a web page with Mobirise
