Department of Applied Mechanics

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Soft materials are known for their plethora of biomedical applications, intricate structure–property correlation and nonlinear mechanical response. Multiple length–time scale phenomena and hierarchical structure results in their nonlinearity. Phenomenological and continuum mechanical models have been developed to predict their mechanics, which have mostly been very material-specific with inability to predict the mechanics of different types of soft materials simultaneously. This shortcoming has been addressed in the present work, wherein a generic nonlinear viscoelastic model has been proposed to predict the mechanical response of hydrogels, sponges, and xerogels. A fractal derivative viscoelastic model is proposed considering a fractal Maxwell model in parallel with a nonlinear spring. In particular, this model is chosen to qualitatively mimic the material nonlinearity inherent in soft materials. The fractal dashpot in combination with the nonlinear spring accounts for the power law time-dependent rheology of generic soft materials. These two different aspects in the form of nonlinear stiffness and non-Newtonian rheology account for mechanics of most soft materials. The present model is shown to fit well the existing literature results for mechanical response of a multitude of soft material classes with different test conditions and loading rates, which is one of the salient features of the model, apart from its simplistic mathematical framework. Further, a parametric study is reported on the mechanics of nanocellulose loaded poly(vinyl alcohol) xerogel. The model predictions are observed to be in conjunction with the experimental observations. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature.

World University root node

Mechanics of Time-Dependent Materials

Mechanics of soft polymeric materials using a fractal viscoelastic model

An energy harvesting dynamic vibration absorber (EHDVA) is studied to suppress undesirable vibrations in a host structure as well as to harvest electrical energy from vibrations using piezoelectric transduction. This work studies the feasibility of using vibration absorber for harvesting energy under random excitation and in presence of parametric uncertainties. A two degrees-of-freedom model is considered in the analytical formulation for the host along with the absorber. A separate equation is used for energy generation from piezoelectric material. Two studies are reported here: (i) with random excitation where the base input is considered to be Gaussian and (ii) parametric uncertainty is considered with harmonic excitation. Under random base excitation, the analytical results show that, with the proper selection of parameters, harvested electrical energy can be increased along with the reduction in vibration of the host structure. Graphs are reported showing tradeoff between harvested energy and vibration control. Whereas, Monte Carlo simulations are carried out to analyze the system with parametric uncertainty. This showed that the mean harvested power decreases with an increase in uncertainties in the natural frequency as well as damping ratio. In addition, optimal electrical parameters for obtaining maximum power for the case of uncertain parameters are also reported in this study. © 2021 by ASME.

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

Parametric Uncertainty and Random Excitation in Energy Harvesting Dynamic Vibration Absorber

This study focusses on the development of stochastic reduced order model for probabilistic characterisation of bladed disc systems with random spatial inhomogeneities. High fidelity finite element modelling is used to mathematically model the system. A two step reduction strategy is applied involving reduction in the state space dimension and reduction in the stochastic dimensions. Information of the spatial inhomogeneities are assumed to be available from limited in situ measurements across the spatial extent and are modelled as non-Gaussian random fields. The stochastic version of the finite element matrices are developed using a polynomial chaos based framework, which optimizes the stochastic dimensionality of the problem. The uncertainties in the input propagates through the system into the response, which are also random. Surrogate models for these response quantities are obtained as PCE and are constructed using the method of stochastic collocations. Challenges involved in application of PCE on complex geometrically irregular spatial domains are addressed. The efficacy of the proposed framework is demonstrated through two numerical examples -an academic bladed disc system and an industrial turbine rotor blade. © 2020 Elsevier Ltd

International Journal of Mechanical Sciences

Uncertainty quantification of bladed disc systems using data driven stochastic reduced order models

This study focusses on probabilistic modelling of the bladed disc system and numerical estimation of the distributions of the response quantities of the system. Stochastic finite element model of the system consisting of all the assemblies and the hub is developed and reported. The spatial inhomogeneity of mistuned structures is modelled as non-Gaussian random field. Experimentally, the system parameters can be measured at the specified locations of the bladed disk structure. In this analysis, a synthetic data is generated which represent this measured data set. Further, Nataf transformation is implemented to each component of the data set to get the polynomial chaos expansion framework of the system parameters. Since, the random field of the system parameter is approximated as correlated random variables, Spearman's rank correlation coefficient is used in this manuscript to obtain that correlation among the random parameters across the domain. The approximated probability density function obtained through the aforementioned methodology is compared with the target probability density function of the parameter using Kullback - Liebler (KL) entropy as a metric. Also, the same KL entropy is used as a metric to check the convergence of polynomial chaos terms in the expansion. Next, the proposed polynomial chaos method is integrated with commercial finite element software to quantify the propagation of randomness associated with system parameters into the response quantities. Subsequently, the statistical processing helps in estimating the probabilistic measure of the required response quantities. The results obtained through the conventional Monte Carlo (MC) simulations have been used as the benchmark to compare the response characteristics obtained through the proposed algorithm. Copyright © 2020 ASME

Proceedings of the ASME Turbo Expo

Stochastic modelling and analysis of rotating bladed discs

Flow separation over a two dimensional geometry such as aerofoil is defined as a point where shear stress goes to zero. For a three-dimensional boundary layer, separation is along a line and universally accepted definition of such lines do not exist for 3D geometry. Any flow leaves behind a wall signature on the surface which can be visualized by plotting velocity or skin-friction vector field over the surface. In our present work, critical point theory is used to explain the observations of vector fields over a finite wing surface and in particular, determine pattern in separation lines for 3D geometry. Oil flow experiments were carried out on a finite wing with NACA 0012 as cross-section for 0.085 and 0.1 million Reynolds number. Some of the results of wind tunnel experiments are discussed along with need for computational solution. Numerical simulations were carried out for sphere, spheroid, torus and 3D wing at different angles of attack at 1 million Re and separation lines are plotted over the surface. These lines are studied in pre-and post-stall angles of incidence to understand the nature of separation in three-dimensional boundary layer. © 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

AIAA Scitech 2021 Forum

Study of Separation of Three-Dimensional Boundary Layer using Critical Point Theory

This paper identifies the laminar separation bubble at the root or span-wise midsection of a rectangular wing using direct surface pressure measurements and analyses their behavior. The locations of separation, transition, and reattachment are identified from surface pressure measurements and oil flow visualizations. Surface oil flow visualization results also clarified the wing-tip and separation bubble interactions near the leading edge of the wing. The transition structure and turbulence characteristics in the separated shear layer locations are studied using Laser Doppler Velocimetry. Time series analysis is carried out to distinguish the flow patterns of transition and later transition locations along with chordwise locations of the root section of the wing. © 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

Time Series Behaviour of Laminar Separation Bubbles at Low Reynolds Number

Amorphous thin film metallic glasses (TFMGs) have given rise to a widespread research interest due to their technological promise for practical applications and scientific importance in the biomedical field. As a result of their disordered atomic structure (leading to amorphicity), these TFMGs symbolize a new class of structural and functional materials with extraordinary properties, including exciting strength along with superior mechanical properties and biological properties. TFMG top-coats have the potential to improve the strength, corrosion resistance, biocompatibility, and life span of potential biomaterials (metallic, ceramics, or polymers). This article reviews the mechanical properties and biological behavior of TFMGs as well as the current progress in Zr-based, Ti-based, Fe-based, and Mg-based TFMGs for biomedical applications. © 2021 Elsevier B.V.

Journal of Alloys and Compounds

Thin film metallic glasses for bioimplants and surgical tools: A review

A non-planar mixing layer observed between parallel Couette flows by Narasimhamurthy et al. (Phys Rev E 85:036,302, 2012) is considered. Direct numerical simulation is chosen, and simulations are run in order to determine the critical Reynolds number at which the interface between the co-flowing laminar and non-laminar flow becomes unstable exhibiting a meandering motion. The necessary conditions required to trigger the shear-layer instability were also discussed. Different combinations of Reynolds numbers are chosen keeping the Reynolds number ratio between the laminar and non-laminar flows as constant. Preliminary results indicate that the onset of instability occurs, and a meandering motion is observed at the interface when Reynolds number for the non-laminar flow corresponds to 650. © 2021, Springer Nature Singapore Pte Ltd.

Lecture Notes in Mechanical Engineering

DNS of an Oscillating Shear Layer Between Two Parallel Couette Flows

Study of separation of three-dimensional boundary layer using critical point theory

Tissue simulating optical multilayer phantoms that closely mimic optical properties of specific tissues are used to evaluate and calibrate spectral imaging studies in clinical diagnostics. Consistency in phantom layer thickness, fabricated through the spin coating method is crucial in using the methodology to create large datasets to facilitate artificial intelligence (AI) based optical diagnostic systems. These phantoms are usually imaged under a scanning electron microscope to verify layer dimensions, varying with the amount of used materials, changes in sample parameters, and spin speed. Imaging a considerable number of phantoms under SEM for different applications is challenging. This paper addresses the automated detection of layered skin phantom thickness acquired from light microscopy images. The thickness estimation reported in this work is also useful in optimizing the sample and spin coating parameters to achieve a predefined sample dimension during the fabrication procedure. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.