Department of Mechanical Engineering

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

The continuous Non-Destructive Evaluation of assets for long-term assurance of performance has led to several developments over the deployment of a Real-Time Structural Health Monitoring (SHM) system. Considering the challenges involved under the implementation of an SHM system for the applications working under harsh environmental conditions with limited access to power sources this work is aimed to contribute towards overcoming those challenges by using the noise from the structure's machinery or any ambient source as an alternative energy source and employing Fiber Optics based sensing, for its applicability under harsh environments. The required SHM system is realized with the cross-correlation of a fully diffused noise field, sensed using the Fiber Bragg Grating (FBG) sensors at two random locations. With no control on the input received as noise, to this end, a method is developed based on a Deep Learning framework, which is aimed towards a Universal Deployment of the passive SHM system. The methodology is designed to perform the health monitoring of the system, independent of the input perturbations. The validation performed on simulation data has demonstrated the feasibility of the developed technique towards the required kind of passive SHM system. © 2021 by ASME

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Proceedings of 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation, QNDE 2021

DEVELOPMENT OF A CONVOLUTIONAL NEURAL NETWORK ASSSITED FIBER OPTICS BASED PASSIVE STRUCTURAL HEALTH MONITORING SYSTEM

In this paper, it is aimed to identify flaws in glass fiber reinforced polymer composites by smart skin graphene nano platelet (GNP) spray coating in infrared thermography technique. The initial resistance of GNP was made to 1 kΩ. Characterization of sensor and beam was done with scanning electron microscopy and computed tomography (CT) respectively. The thermo-elastic behaviour was evaluated in uniaxial test. The surface temperature was studied with IR camera and it was observed that the surface coated GNP sensor upon a damage and without the damage specimen retains heat than without coating the sensor. Hereafter testing with 0.1 mm/min, 0.5 mm/min and 1 mm/min, it was found that without damage specimen, the temperature increased to 112.5%, 13.3% and 40% respectively. And temperature increased to 93.2%, 36.7% and 76.4% in the specimen with the damage. Specimen were also tested for spectrum fatigue cyclic load at 0.1 Hz and 1 Hz. Failure peak of laminates has been analyzed with optical microscopy and CT which was correlated with temperature rise. For 0.1 Hz spectrum loading, the specimen with the damage, with and without GNP coated, temperature rose to 2040% after first laminate failure. Similarly, for 0.1 Hz specimen temperature rose to 15,637.5% in case of without damage specimen, with GNP coated than without GNP coated. And in case of 1 Hz spectrum loading with damage specimen, the temperature rose to 105.73% after GNP coated. Similarly, at 1 Hz loading, the temperature rose to 143.07% in case of without damage specimen after GNP coated. GNP skin coated nano-sensor helps in early detection of temperature signals. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Journal of Nondestructive Evaluation

Improved Thermal Signature of Composite Beams with GNP Smart Skin for Defect Investigation

Nonlinear ultrasonic guided waves are among the most promising new tools for early stage damage detection owing to their high sensitivity and long-range propagation features. However, signatures from instrumentation, transducers, and couplant effects create false positives mixing with the material- or defect-induced nonlinearities, leading to inaccurate measurements. Here, we propose a novel technique using a waveguide metamaterial rod, which acts as a mechanical acoustic filter for suppression of higher harmonic components in the measured signal. The proposed waveguide metamaterial consists of an array of flat axisymmetric ridges arranged periodically on the surface of the rod. It is experimentally demonstrated that the higher harmonic components are filtered when the proposed metamaterial rod is placed at the transmission side, thus removing unwanted nonlinearities from the received signal in a pitch-catch configuration. Furthermore, the application of this method is demonstrated by detecting a discontinuity in the workpiece through its nonlinear response enhanced using the metamaterial. This technique is attractive for early stage material diagnosis in engineering, biomedicine, and health monitoring of critical engineering assets. © 2021 Author(s).

APL Materials

Waveguide metamaterial rod as mechanical acoustic filter for enhancing nonlinear ultrasonic detection

This paper describes a technique for measurement of temperatures at multiple locations using the multiple waveguide configurations. A single transducer has been used for transmitting and receiving the torsional wave T(0,1) mode in the waveguides. Here, a single transducer is attached to multiple waveguides of different lengths (each waveguide is designed with a single bend). This method improves upon the earlier reported studies using straight waveguides, where the non-consideration of the temperature gradient issues. The temperature measurement range is from room temperature to the maximum utility temperature of the waveguide material. The time of flight difference (δTOF) of reflected ultrasonic torsional guided wave modes (T(0,1)) from the bend, which is the reference signal, and another signal from the end of the waveguide is utilized to measure the corresponding temperature of the surrounding media. The T(0,1) wave mode is less dispersive as compared to L(0,1) mode in the same material from the early reported work. The wavelength of the T(0,1) mode is significantly smaller than that of L(0,1) mode due to torsional velocity is less than the longitudinal velocity of ultrasonic sensor. Hence, it can be improved the sensitivity of the temperature measurements. This temperature measurement technique is more interest in several industrial applications, where using the furnaces and melters. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lecture Notes in Mechanical Engineering

Ultrasonic Waveguide Technique for Temperature Measurement Using T(0,1) Wave Mode

Heat sinks and heat exchangers based on flow boiling in mini/microchannels are expected to be more compact and efficient. One of the major challenges while using copper material for phase-change heat transfer application is the change in surface characteristics after prolonged usage due to the thermal oxidation of surface over time. This study involves the repeated experimental runs of flow boiling of water in a 1 mm hydraulic diameter end-milled copper channel to verify the influence of ageing on the thermal and hydraulic performance. As it is difficult to measure the surface wettability in a mini/microchannel, this work makes use of the ageing and surface characterization study conducted on the dummy copper samples to infer the influence of ageing on mini/microchannel surface characteristics and consequently its boiling performance. The test involves measuring over a period of time the wetting behaviors of the end-milled copper samples left in water at three different conditions: one in a constant temperature bath maintained at 60 ℃ and 1 atm and the remaining two in a pool of boiling water at 110 ℃ and 120 ℃. The study compares the fresh sample and the aged sample for the surface oxidation, surface chemical composition and surface morphology, and discusses the changes in the contact angle and surface morphology caused by copper ageing. Copyright © 2021 by ASME

Journal of Heat Transfer

Experimental Investigation on the Change in Flow Boiling Characteristics Due to Boiling-Induced Copper Ageing

Pumpless transport of droplets on open surfaces has gained significant attention because of its applications starting from vapor condensation to Lab-on-a-Chip systems. Mixing two droplets on open surfaces can be carried out quickly by using wettability patterning. However, it is quite challenging to split a droplet in the absence of external stimuli because of the interfacial energy of the droplet. Here, we demonstrate a standalone power-free technique for transport and splitting of droplets on open surfaces using continuous wettability gradients. A droplet moves continuously from a low to a high wettability region on the wettability-gradient surface. A Y-shaped wettability-gradient track - laid on a superhydrophobic background - is used to investigate the dynamics of the splitting process. A three-dimensional phase-field Cahn-Hilliard model for interfaces and the Navier-Stokes equations for transport are employed and solved numerically using the finite element method. Numerical results are used to decipher the motion and splitting of droplet at the Y junction using the principle of energy conservation. It is observed that droplet splitting depends on the configuration of the Y junction; droplets split faster for the superhydrophobic wedge angle of 90∘ and the splitting ratio (ratio of the sizes of daughter droplets) depends on the widths of the Y branches. A critical branch-width ratio (w2w1=0.79) is identified below which the droplet does not split and moves towards the branch of higher width and settles there. The present study provides the required theoretical underpinnings to achieve autonomous transport and splitting of droplets on open surfaces, which has clear potential for applications in Lab-on-a-Chip devices. © 2021 American Physical Society.

Fulltext

Physical Review Fluids

Autonomous transport and splitting of a droplet on an open surface

The study reports on the characterization of interfacial disbonds in an elastic-viscoelastic (steel-rubber) adhesively bonded bilayer structure where the elastic material (steel) has a significantly higher impedance than the viscoelastic material (rubber). The study uses the A0 mode guided wave at a low frequency of 100 kHz, which was generated and detected using non-contact air-coupled ultrasound. The A0 mode could be generated and detected from both steel and rubber sides, despite the high viscoelasticity of the rubber layer. However, the A0 mode guided wave propagation is sustained only in the steel layer and not in the rubber layer. The mode travelling along the steel layer leaks into the rubber layer and hence can be detected from the rubber side in the bonded region. When the disbond is below either the transmitter or the receiver, a better sensitivity in the disbond detection was achieved from the rubber side rather than the steel side. Using the experimental and 2D frequency-domain finite element simulation results, a linear correlation between the extent of disbond and the amplitude, time-of-flight (ToF) difference of the A0 mode arrival in the disbond region on the steel side was also established. The results show the potential to characterize interfacial disbonds regardless of the position with respect to the transmitter or receiver in elastic-viscoelastic multilayered structures using air-coupled guided wave inspection from single-side access. © 2021 Elsevier Ltd

NDT and E International

Guided A0 wave mode interaction with interfacial disbonds in an elastic-viscoelastic bilayer structure

A method is presented to evaluate the interfacial weakness of aluminium-based honeycomb sandwich structure (HSS) using Shear Horizontal (SH) guided wave. SH guided waves are sensitive to the interfacial properties since the wave particles vibration is oriented parallel to the adhesive-adherent joints. Periodic permanent magnet (PPM) electromagnetic acoustic transducers (EMATs) are used to excite and detect SH-guided waves. A semi-analytical finite element method is developed to simulate the SH wave propagation in HSS. The boundary stiffness approach is used to model the adhesive-adherent interface. The excitation parameters are chosen such that only SH0 mode is generated in the structure. The interaction of the fundamental SH0 wave mode with various defects and the different interface stiffness is analyzed. The frequency-wavenumber analysis is used to study the effect of interface stiffness on SH wave propagation. The analysis reveals that in a perfect bond, SH0 and S0 guided modes are present. The interaction of SH0 mode with the honeycomb core results in the genesis of S0 mode. Thus, the presence or absence of the S0 mode can be used as an indicator of bond quality. The findings from the FE simulation are validated against the experiment. The analysis shows a reliable non-destructive evaluation of the interface joint and classifying them as good or bad bonds. © 2021 by ASME

EVALUATION OF ADHESIVE INTERFACE PROPERTIES IN HONEYCOMB SANDWICH STRUCTURE USING GUIDED WAVES

Ultrasonic non-Destructive evaluation (NDE) techniques are widely used to ensure the integrity and strength of structures. Guided ultrasonic waves are typically used for inspecting inaccessible and hidden locations of complex structures. For rapid inspection, non-contact transduction methods such as air-coupled ultrasonic transducers and electromagnetic acoustic transducers (EMAT) are preferred. However, the major downside of these techniques is the high-power requirement. To overcome this challenge, a pulse compression-based signal processing technique called coded excitation is proposed. By using temporally long low-power transmission signals, results comparable in signal-to-noise ratio (SNR) to high-power transmissions are achieved. The pulse compression-based coded excitation technique for low-power operation and enhanced SNR results for guided ultrasonic wave NDE is presented. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Coded Excitation for Low-Power Operation in Guided Ultrasonic Wave Non-destructive Evaluation

We conceptualize Distributed Learning Machines (DLMs) – a novel machine learning approach that integrates existing machine learning algorithms with traditional mesh-based numerical methods for solving forward and inverse problems in nonlinear partial differential equations (PDEs). In conventional numerical methods such as finite element method (FEM), the discretization of the computational domain is a standard technique to reduce the representation load of basis functions. Along the same lines, we propose a distributed neural network architecture that facilitates the simultaneous deployment of several localized neural networks to solve PDEs in a unified manner. The most critical requirement of the DLMs is the synchronization of the distributed neural networks. For this, we introduce a new physics-based interface regularization term to the cost function of the existing learning machines like the Physics Informed Neural Network (PINN) and the Physics Informed Extreme Learning Machine (PIELM). To evaluate the efficacy of this approach, we develop three distinct variants of DLM namely, time-marching Distributed PIELM (DPIELM), Distributed PINN (DPINN) and time-marching DPINN. We show that ideas of linearization and time-marching allow DPIELM to be able to solve nonlinear PDEs to some extent. Next, we show that DPINNs have potential advantages over existing PINNs to solve the inverse problems in heterogeneous media. Finally, we propose a rapid, time-marching version of DPINN which leverages the ideas of transfer learning to accelerate the training. Collectively, this framework leads towards the promise of hybrid Neural Network-FVM or Neural Network-FEM schemes in the future. © 2020 Elsevier B.V.