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

Process industries rely on effective decision-making by human operators to ensure safety. Control room operators acquire various inputs from the DCS, interpret them, make a prognosis, and respond through appropriate control actions. In order to perform these effectively, the operator needs to have appropriate mental models of the process. Poor mental models would increase the operator's cognitive workload and make them prone to errors. Traditionally, operator training systems are used to help operators learn appropriate mental models. However, performance assessment metrics used during training do not explicitly account for their cognitive workload while performing a task. In this work, we demonstrate that this leads to an incorrect assessment of operators’ abilities. We propose an Electroencephalography (EEG) power spectral density-based metric that can quantify the cognitive workload and provide detailed insight into the evolution of the operator's mental models during training. To demonstrate its utility, we have conducted training experiments with ten participants performing 438 tasks. Statistical studies reveal that the proposed metric can quantify the cognitive workload and therefore be used to assess operator training accurately. © 2021 Institution of Chemical Engineers

World University root node

Department Of Chemical Engineering

Process Safety and Environmental Protection

Electroencephalography (EEG) based cognitive measures for evaluating the effectiveness of operator training

Process plant operators rely on their knowledge of process cause-and-effect relationships during abnormal situation management. Novice operators develop such process knowledge during training. Hence, holistic assessment of operators’ training is essential to ensure process safety. Currently, during training, operators’ process understanding is evaluated using criteria such as successful completion, task based measures, and operator actions that ignore their cognitive behavior. In this work, we propose an eye-tracking-based approach that uses the operator's attention allocation during different pre-specified training scenarios along with process data, alarm information, and operator actions. Our approach is based on the precept that an operator would focus their attention on those variables on the human-machine interface that they believe have a direct causal relationship to the situation at hand. Also, expert operators seek time-based information for proactive monitoring. Accordingly, to quantify the progress of a novice operator's learning, we develop two metrics — association metric and salience metric — using correspondence analysis of operators' eye gaze. To evaluate the applicability of the metrics, we conducted experiments with ten participants who performed 486 tasks. Statistical studies reveal that the proposed metrics can quantify operators’ learning and thus can be used to objectively evaluate training effectiveness. © 2021 The Institution of Chemical Engineers

Metrics for objectively assessing operator training using eye gaze patterns

Analysis of fluctuations of uterine contractions under varied gestational ages is clinically significant. In this work, fluctuations associated with Preterm pregnancies are analyzed. For this, uterine electromyography (uEMG) signals in Preterm condition with varied gestational ages are considered. The signals are subjected to Adaptive Fractal Analysis (AFA) where a global trend is identified using overlapping windows of varying orders. The signal is detrended and fluctuation function is estimated. Hurst exponent features are extracted and analyzed statistically. Results show that AFA is able to characterize the variations in the fluctuations of Preterm uEMG signals. The feature values are distinct and vary with gestational age. Coefficient of variation is observed to be low, indicating that these features could handle inter-subject variability of Preterm signals. As early diagnosis of premature delivery is imperative for timely medical intervention and treatment, it appears that the proposed features could aid in determining the changes in uterine muscle contractions in Preterm condition. © 2021 World Scientific Publishing Company.

Fluctuation and Noise Letters

Analysis of Fluctuations of Uterine Contractions in Preterm Pregnancies using Adaptive Fractal Features of Electromyography Signals

Accurate prediction of preterm birth is a global, public health priority. This necessitates the need for an efficient technique that aids in early diagnosis. The objective of this study is to develop an automated system for an effective detection of preterm (weeks of gestation < 37) condition using Electrohysterography (EHG) and topological features associated with the frequency components of signals. The EHG signals recorded prior to gestational age of 26 weeks are considered. The pre-processed signals are subjected to discrete Fourier transform to obtain the Fourier coefficients. The envelope is computed from the boundary of the complex Fourier coefficients identified using the α-shape method. Topological features namely, area, perimeter, circularity, convexity, ellipse variance and bending energy are extracted from the envelope. Classifications based on threshold-determination method and machine learning algorithms namely, naïve Bayes, decision tree and random forest are employed to differentiate the term and preterm conditions. The results show that the Fourier coefficients of EHG signals exhibit different shapes in the term and preterm conditions. The regularity of signals is found to increase in preterm condition. All the features are found to have significant differences between these two conditions. Bending energy as a single biomarker achieves a maximum accuracy of 80.7%. The random forest model based on the topological features detects the conditions with the maximum accuracy and positive predictive value of about 98.6%. Therefore, the proposed automated system seems to be effective and could be used for the accurate detection of term and preterm conditions. © 2021 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences

Biocybernetics and Biomedical Engineering

Automated detection of preterm condition using uterine electromyography based topological features

Molecular Dynamic simulations and experiments have been performed to investigate the evaporative behavior of a liquid droplet in the presence of nanoparticles on a smooth, heated flat plate. Nanofluids of different volume fractions with CuO and Al2O3 nanoparticles were prepared to obtain liquid droplets. Experiments were conducted for droplets of both nanofluids and base fluid (DI water). The results showed that in the pinned region of evaporation, droplets of nanofluids with higher volume fractions of dense nanoparticles evaporated by keeping their base pinned at the triple point contact line. It is also observed that the evaporation rate of nanofluid droplets with nanoparticles having higher density is slower and promoted a typical pattern formation. Molecular Dynamic simulations were further performed to analyse the influence of various nanoparticle-liquid interaction strengths (εnp−l) on evaporative behavior. The simulation results suggest that in the pinned evaporation stage, for higher values of εnp−l, the droplet undergoes a delay on evaporation while subjected to higher heat flux on the substrate. © 2021 Elsevier B.V.

Department of Metallurgical and Materials Engineering

Colloids and Surfaces A: Physicochemical and Engineering Aspects

Influence of Nanoparticles on the Evaporation of a Nanodroplet from Solid Substrates: An Experimental and Molecular Dynamics Investigation

We study the generation of vorticity at a water–air interface due to the spreading of ethanol–water droplets for ethanol concentrations in the drop ranging from 20% ≤ Ce≤ 100% on the surface of a 50 mm deep water layer. On deposition onto the water layer, the lighter, miscible ethanol droplet spreads as a film on the water surface due to the ethanol–water surface tension difference. Simultaneous to the film spreading, an expanding vortex ring is found below the tip of the spreading film front. The phenomenon in the water layer is visualized using particles, and 2D PIV is used to obtain the velocity field. Vortex regions are identified using the λ2 method for various time instants. The average vorticity generation in between the time instants is calculated. A scaling law is proposed for the dimensionless vorticity at a given instant based on the experimental observations. © 2021, Springer Nature Singapore Pte Ltd.

Lecture Notes in Mechanical Engineering

Vorticity Generation Due to Surface Tension-Driven Spreading

Nowadays, adequate and accurate representation of the microvascular flow resistance constitutes one of the major challenges in computational haemodynamic studies. In this work, a theoretical, porous media framework, ultimately designed for representing downstream resistance, is presented and compared against an in vitro experimental results. The resistor consists of a poro-elastic tube, with either a constant or variable porosity profile in space. The underlying physics, characterizing the fluid flow through the porous media, is analysed by considering flow variables at different network locations. Backward reflections, originated in the reservoir of the in vitro model, are accounted for through a reflection coefficient imposed as an outflow network condition. The simulation results are in good agreement with the measurements for both the homogenous and heterogeneous porosity conditions. In addition, the comparison allows identification of the range of values representing experimental reservoir reflection coefficients. The pressure drops across the heterogeneous porous media increases with respect to the simpler configuration, whilst flow remains almost unchanged. The effect of some fluid network features, such as tube Young's modulus and fluid viscosity, on the theoretical results is also elucidated, providing a reference for the invitro and insilico simulation of different microvascular conditions. © 2021 Elsevier Ltd

Journal of Biomechanics

On the poro-elastic models for microvascular blood flow resistance: An in vitro validation

A non-planar or a bilateral mixing-layer is studied by means of a series of direct numerical simulations (DNSs). This mixing-layer forms at the interface of two co-current plane Couette flows of different Reynolds numbers. The current DNS study determined the conditions for the onset of shear-layer instability at the interface. The influence of different Reynolds number (of the co-current plane Couette flows) and their Reynolds number ratio on the mixing-layer is studied. A critical Reynolds number of about 500 (or more particularly one of the co-current plane Couette flows must be turbulent) and a Reynolds number ratio greater than 2 is required for the genesis of this bilateral shear-layer instability. Independent of the Reynolds number and the Reynolds number ratio, the temporal evolution of the shear-layer instability followed the same pattern. In addition, the oscillation frequency of the instability was found to increase with increasing Reynolds number and increasing Reynolds number ratio. Further, influence of instability on the local skin friction and the two-point correlation is elaborated on. © 2021 Elsevier Inc.

International Journal of Heat and Fluid Flow

Onset of shear-layer instability at the interface of parallel Couette flows

Electrotactile displays provide tactile feedback using electrical currents. However, prolonged usage of them causes skin irritation and burns. This study presents a novel method to use the electrotactile display at a lower threshold by applying two subthreshold electrotactile stimuli placed nearby. This method is tested on fourteen subjects over a frequency range from 20 to 1280 Hz in the tuning curve. Two Psychophysical experiments have been conducted to measure their thresholds for individual stimuli and presented together. In the first experiment, the frequencies of both the stimuli were the same, and it showed 36% to 18% reduction in EPT of the second stimulus when the first stimulus was at 10% to 50% of its threshold. In the second experiment, Meissner and Pacinian were selectively stimulated by applying stimuli at their resonant frequencies (30 and 250 Hz, respectively), results showed slightly more reduction in the case of 250 Hz compared to 30 Hz. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Advances in Intelligent Systems and Computing

Spatial Summation of Electro-Tactile Displays at Subthreshold

A three-dimensional molecular dynamics simulation of a rarefied gas flow confined between two parallel solid walls has been carried out to study the gas transport behavior in nanoscale pressure-driven flows. To simulate the effects of pressure-driven flows in nanoscale systems; a reservoir is created at the beginning of the channel. A force, in the form of gravity, is applied to every gas molecule occupying a specific region in the reservoir thereby facilitating to establish a streamwise inhomogeneous flow in a finite length nanochannel. Further, the model is tested for its structural stability and steady-state characteristics. The flow characteristics are evaluated at various bins (A, B, C, and D) along the length of the channel. The presence of a pressure drop established along the length of the channel results in a significant variation of flow properties in the channel. The characteristics of the system are further studied using the spatial distribution of flow properties. To investigate the streamwise variation, thermal accommodation coefficients (TACs) at various sections of the channel are calculated. The results indicate that the TACs vary along the length. Further, the effect of pressure drop on TACs is also analysed. The effect of confinement is also studied with velocity autocorrelation function (VACF) and mean squared displacement (MSD). The effect of confinement is evident in the fluid region away from the wall too. © 2021