Browsing by Author "Kumar, H."

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A Bayesian inference approach: estimation of heat flux from fin for perturbed temperature data
(Springer India, 2018) Kumar, H.; Gnanasekaran, N.
This paper reports the estimation of the unknown boundary heat flux from a fin using the Bayesian inference method. The setup consists of a rectangular mild steel fin of dimensions 250×150×6 mm3 and an aluminium base plate of dimensions 250×150×8 mm3. The fin is subjected to constant heat flux at the base and the fin setup is modelled using ANSYS14.5. The problem considered is a conjugate heat transfer from the fin, and the Navier–Stokes equation is solved to obtain the flow parameters. Grid independence study is carried out to fix the number of grids for the study considered. To reduce the computational cost, computational fluid dynamics (CFD) is replaced with artificial neural network (ANN) as the forward model. The Markov Chain Monte Carlo (MCMC) powered by Metropolis–Hastings sampling algorithm along with the Bayesian framework is used to explore the estimation space. The sensitivity analysis of the estimated temperature with respect to the unknown parameter is discussed to know the dependency of the temperature with the parameter. This paper signifies the effect of a prior model on the execution of the inverse algorithm at different noise levels. The unknown heat flux is estimated for the surrogated temperature and the estimates are reported as mean, Maximum a Posteriori (MAP) and standard deviation. The effect of a-priori information on the estimated parameter is also addressed. The standard deviation in the estimation process is referred to as the uncertainty associated with the estimated parameters. © 2018, Indian Academy of Sciences.
A Bottom-Up Optimization Approach for Friction Stir Welding Parameters of Dissimilar AA2024-T351 and AA7075-T651 Alloys
(Springer New York LLC barbara.b.bertram@gsk.com, 2017) Anil Kumar, K.S.; Murigendrappa, S.M.; Kumar, H.
In the present study, optimum friction stir weld parameters such as plunge depth, tool rotation speed and traverse speed for butt weld of dissimilar aluminum alloy plates, typically 2024-T351 and 7075-T651, are investigated using a bottom-up approach. In the approach, optimum FSW parameters are achieved by varying any one parameter for every trial while remaining parameters are kept constant. The specimens are extracted from the friction stir-welded plates for studying the tensile, hardness and microstructure properties. Optimum friction stir weld individual parameters are selected based on the highest ultimate tensile strength of the friction stir-welded butt joint specimens produced by varying in each case one parameter and keeping the other two constant. The microstructure samples were investigated for presence of defects, grain refinement at the weld nugget (WN), bonding between the two materials and interface of WN, TMAZ (thermomechanically affected zone) of both advancing and retreating sides of the dissimilar joints using optical microscopy and scanning electron microscopy analyses. In the experimental investigations, the optimum FSW parameters such as plunge depth, 6.2 mm, rotation speed, 650 rpm and traverse speed of 150 mm/min result in ultimate tensile strength, 435 MPa, yield strength, 290 MPa, weld joint efficiency, 92% and maximum elongation, 13%. The microstructure of optimized sample in the WN region revealed alternate lamellae material flow pattern with better metallurgical properties, defect free and very fine equiaxed grain size of about 3-5 µm. © 2017, ASM International.
A Comparative Study on Tree-Based Classifiers for Condition Monitoring of Face Milling Tool
(Springer, 2025) Viswanathan, P.C.; S, N.V.; Mahanta, T.K.; Kumaraswamy, M.C.; Kumar, H.; Sugumaran, S.
Background: This study delves into the significance of face milling tools in machining, emphasizing the need for timely fault diagnosis to enhance the efficiency of manufacturing processes. By examining defect scenarios such as flank wear, breakage and chipping, along with a reference for good tool condition, the research aims to improve diagnostic accuracy and optimize manufacturing performance. Methodology: Vibration signals generated during milling operations are analyzed to identify tool faults. A feature extraction process incorporating statistical, histogram, and ARMA features is employed to gain a nuanced understanding of tool behavior. Feature selection is performed using the J48 decision tree algorithm which helps identify the most relevant features. Subsequently, 13 tree-based classifiers are applied to classify tool faults effectively. Results: A comparative analysis of classification outcomes provides practical insights into the most effective features for fault diagnosis in milling tools. The study’s findings show that the combination of ARMA features with Extra trees achieved an impressive accuracy of 96.88% for milling tool fault diagnosis. The outcomes from the study contribute to real-world applications by enhancing diagnostic methodologies, ultimately advancing fault detection and classification in machining processes. © Springer Nature Singapore Pte Ltd. 2025.
A Markov Chain Monte Carlo-Metropolis Hastings Approach for the Simultaneous Estimation of Heat Generation and Heat Transfer Coefficient from a Teflon Cylinder
(Taylor and Francis Ltd. michael.wagreich@univie.ac.at, 2018) Kumar, H.; Kumar, S.; Gnanasekaran, N.; Balaji, C.
This paper reports the use of Markov Chain Monte Carlo (MCMC) and Metropolis Hastings (MH) approach, to solve an inverse heat transfer problem. Three-dimensional, steady state, conjugate heat transfer from a Teflon cylinder of dimensions 100 mm diameter and 100 mm length with uniform volumetric internal heat generation is considered. The goal is to estimate volumetric heat generation and heat transfer coefficient, given the temperature data at certain fixed location on the surface of the cylinder. The internal volumetric heat generation is specified as input and the temperature and heat transfer coefficient values are obtained by a numerical solution to the governing equation. The temperature values also depend on heat transfer coefficient which is obtained by solving Navier–Stokes equation to obtain flow information. In order to reduce the computational cost, a neural network is trained from the computational fluid dynamics simulations. This is posed as an inverse problem wherein volumetric heat generation and heat transfer coefficient are unknown but the temperature data is known by conducting experiments. The novelty of the paper is the simultaneous determination of volumetric heat generation and heat transfer coefficient for the experimentally measured steady-state temperatures from a Teflon cylinder using MCMC-MH as an inverse model in a Bayesian framework and finally, the estimates are reported in terms of mean, maximum a posteriori, and the standard deviation which is the uncertainty associated with the estimated parameters. © 2018 Taylor & Francis Group, LLC.
A neural network based method for estimation of heat generation from a teflon cylinder
(Global Digital Central, 2016) Kumar, S.; Kumar, H.; Gnanasekaran, N.
The paper reports the estimation of volumetric heat generation (qv) from a Teflon cylinder. An aluminum heater, which acts as a heat source, is placed at the center of the Teflon cylinder. The problem under consideration is modeled as a three dimensional steady state conjugate heat transfer from the Teflon cylinder. The model is created and simulations are performed using ANSYS FLUENT to obtain temperature data for the known heat generation qv. The numerical model developed using ANSYS acts as a forward model. The inverse model used in this work is Artificial Neural Network (ANN). Estimation of heat generation is carried out by minimizing the error between the simulated temperature and the experimental/surrogated temperature. The efficacy of the ANN method is explored for the estimation of unknown heat generation as both forward model and inverse model. The concept of Asymptotic Computational Fluid Dynamics (ACFD) is introduced as a fast forward model which is obtained by performing CFD simulations. The unknown heat generation is estimated for the surrogated data using ANN. In order to mimic experiments, noise is added to the surrogated data and estimation of heat generation is also carried out for the perturbed/noise added temperature data. © 2016, Global Digital Central. All rights reserved.
A New Forward Model Approach for a Mild Steel Fin under Natural Convection Heat Transfer
(Elsevier Ltd, 2015) Kulkarni, A.S.; Kumar, H.; Gnanasekaran, N.
This paper reports the correlation for temperature of the mild steel fin which is subjected to heat flux at its base. The study is performed on a two dimensional, steady state and laminar flow model. The numerical model is restricted to natural convection and the fluid under consideration is air. A rectangular mild steel fin (250 mm x 150 mm x 6 mm), aluminium base plate (250 mm x 150 mm x 8 mm) and an extended geometry representing the ambient air condition is modelled and simulated using ANSYS 14.5. Grid independence study is carried out to fix the number of grids in order to find the optimum number of nodes for carrying out simulations. The heat flux (q) at the bottom of the base plate is varied to study temperature distribution, surface heat transfer coefficient (h) and velocity profile of the flow in the boundary layer around the fin. All these parameters are studied by inclining the model at various angles. A multiple regression analysis is carried out to obtain correlation for the temperature in terms of angle of inclination and the heat flux. The main objective of the work is, proposing a model for the estimation of heat flux or heat transfer coefficient from the fin thereby reducing the computational cost of the forward model in the field of inverse heat transfer. Â© 2015 The Authors.
A PFC Hysteresis Current Controller for Totem-pole Bridgeless Bi-directional EV charger
(Institute of Electrical and Electronics Engineers Inc., 2022) Adiga, P.S.; Kumar, H.; Iyer, S.R.; Arjun, M.; Dsouza, R.C.; Balasubramanian, B.
The sheer increase in greenhouse gas emissions coupled with depleting fossil fuel reserves has created widespread interest in the design and development of Electric Vehicles; however, the design of reliable charging infrastructures for Electric Vehicles is posing challenges to engineers. Additionally, to enhance the efficiency of these Electric Vehicles, it is desirable for the chargers to have bidirectional power processing capabilities. Therefore, the development of bidirectional Battery chargers is one of the main areas of interest when it comes to EVs. In this regard, this paper presents a Hysteresis Controller for a Bridgeless bidirectional On-Board Battery Charger for Electric Vehicle applications. The AC power is fed from a grid via a totem pole-based AC-DC converter. However, the problem with such a power supply unit is that the design of inner current loop PID compensators is challenging due to the increase in complexity of the mathematical model. Therefore, in this paper, the conventional PID controller of the inner current loop is replaced with a Hysteresis controller. The control strategies have been developed to ensure that the power drawn by the grid is harmonic-free. The simulation study is carried out on a 1.5kW setup using MATLAB/SIMULINK. The proposed system is tested for bi-directional power flow. The simulation results are found to be in total agreement with the studied theory. Â© 2022 IEEE
A Suspended Polymeric Microfluidic Sensor for Liquid Condition Monitoring
(International Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII, 2022) Oseyemi, A.E.; Sedaghati, R.; Chandramohan, S.; Kumar, H.; Packirisamy, M.
The measurability of fluid properties like density and viscosity comes with a huge potential in numerous sensing applications, ranging from physical to biological to chemical. A vital quality of a lubricant is its viscosity. In general, liquids with high viscosity have molecules with higher cohesion capacity (higher flow resistance) while those with low viscosity have less cohesion ability, allowing for higher flow rates. This makes viscosity an essential indicator in condition monitoring programs, as information about the cohesive strength of the layers of a liquid can allow us to assess the liquid's ability to form a physical barrier between moving parts. This study proposes a microcantilever-based microfluidic platform that leverages the interaction between cal barrier flow and the bending characteristics of the beam for high sensitivity detection of changes in fluid properties, such as dynamic viscosity, density, and kinematic viscosity, from which valuable information about the health of structures engaging the liquid can be obtained. Â© 2022 International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII. All rights reserved.
A synergistic combination of Asymptotic Computational Fluid Dynamics and ANN for the estimation of unknown heat flux from fin heat transfer
(Elsevier B.V., 2018) Kumar, H.; Gnanasekaran, N.
This paper deals with conjugate heat transfer from a rectangular fin. The problem consists of mild steel (250 × 150 × 6 mm) fin placed vertically on aluminium base (250 × 150 × 4 mm). The aluminium plate is subjected to an unknown heat flux at the base. The fin set-up is modelled using ANSYS fluent 14.5. The fin geometry is surrounded by extended domain filled with air so as to account for natural convection conjugate heat transfer. Grid independence study is carried out to fix the number of grids. A simple correlation using Asymptotic Computational Fluid Dynamics (ACFD) is developed and the same is used as a forward model to obtain the temperature distribution considering heat flux as the input. The problem is treated as an inverse problem in which a non-iterative method, ANN is used as the inverse model to estimate the unknown heat flux from the information of temperature. The results of the forward model and the ANN predicted values are in close agreement with error less than 1%. Effect of noise on the unknown parameter is also studied extensively. © 2017 Faculty of Engineering, Alexandria University
An approach for characterizing twin-tube shear-mode magnetorheological damper through coupled FE and CFD analysis
(Springer Verlag service@springer.de, 2018) Gurubasavaraju, T.M.; Kumar, H.; Mahalingam, A.
The most promising technology in the field of semi-active suspension systems is the use of magnetorheological property of MR fluid, whose material behavior can be controlled through external magnetic field. Devices developed based on this principle are adaptive and controllable as desired for a specific application. It is important to understand the damping characteristics of these devices before employing them, using experimental or computational approaches. In the present work, both experimental and computational methods have been adopted for characterizing a twin-tube MR damper with an intention to develop a computational approach as an alternative to experimental test in the preliminary design stage. Initially, experimental characterization of MR damper was carried out at 1.5 and 2 Hz frequencies for damper stroke length of ± 5 mm under different DC currents ranging from 0.1 to 0.4 A. Later, coupled finite-element and computational fluid dynamic analysis has been carried out to estimate the damping force under same conditions as used in the experiment. The results of computation are in good agreement with experimental ones. Furthermore, using this computational approach, the damping force at different frequencies of 1.5, 2, 3, and 4 Hz has been estimated and its time histories are also plotted. The influence of fluid flow gap on the damping force has been determined and results revealed that damping force behaves inversely with fluid flow gap. © 2018, The Brazilian Society of Mechanical Sciences and Engineering.
An investigation on characteristics and free vibration analysis of laminated chopped glass fiber reinforced polyester resin composite
(Asian Research Publishing Network arpn@arpnjournals.com, 2016) Allien, V.; Kumar, H.; Desai, V.
In this paper material characterization and free vibration analysis of polyester resin based two, four and six layers chopped strand mat (CSM 450g/m2 specific weight) glass fiber reinforced with (CGRP) composite materials has been determined. In material characterization the tensile, flexural, impact, inter-laminar shear strength, fracture toughness has been evaluated. The results have revealed that, the four layer CGRP composite material has high impact, inter laminar shear strength and fracture toughness compared to two and six layers composite material. Free vibration analysis was carried out to determine the natural frequency of the CGRP composite materials theoretically and numerically (FEA). The result obtained from free vibration analysis indicated that natural frequency of six layers CGRP composite material is more than two and four layers CGRP composite material. © 2006-2016 Asian Research Publishing Network (ARPN).
Analysis of Magneto-rheological Fluid Damper and Linearization of Semi-active Quarter Car Model
(United Scientific Group, 2023) Puneet, N.P.; Kumbhar, S.; Kumar, H.; Gangadharan, K.V.
A vehicle with better suspension always provides extra satisfaction to the passengers. Active and semi-active suspension systems are meant to overcome the narrow comfort of passive suspension. Though active systems are superior in terms of performance, their cost makes it be used only in limited applications. Semi-active systems are the best compromise between active and passive systems. One procedure to achieve ‘semi-activeness’ is the use of magneto-rheological (MR) fluid in the system where the fluid property can be varied with a change in the magnetic field applied. The use of MR fluid in the damper for vehicular applications is presented in this study. The rheological characteristic of MR fluid prepared in-house is analyzed and the MR damper is characterized to understand the dynamic behavior of synthesized MR fluid. Then, the MR damper is represented mathematically using the modified algebraic model and is used in the quarter car model. Two road profiles are chosen for the analysis. Also, this study has attempted to address complexity arriving in the analysis of MR damper due to nonlinear hysteretic force characteristic using linearization toolbox in MATLAB Simulink. © 2023 Puneet et al.
Analyzing quarter car model with Magneto-Rheological (MR) damper using equivalent damping and Magic formula models
(Elsevier Ltd, 2019) Jamadar, M.-E.-H.; Desai, R.M.; Kumar, H.; Joladarashi, S.
Mathematical modelling of Magneto-Rheological (MR) damper has been an intriguing field of research ever since the invention of the device itself. An accurate model of MR damper results in development of an efficient controller for a semi-active system with MR damper. Hence, a number of models have been put forward to accurately predict the MR damper behavior. One of these models is Magic formula model. Based on the famous Magic formula used in tire force calculation, this model can be used for representing the peak damper force vs damper piston velocity amplitude graph. This model was later modified to capture the force displacement diagram of MR damper. The former model is denoted as Magic Formula Model-1 (MFM-1) and the latter one is denoted as Magic Formula Model-2 (MFM-2) here onwards. In the current study a commercial MR damper has been tested for various piston velocities and currents. The equivalent damping coefficient is then calculated for the tested conditions. The equivalent damping coefficients are used for analyzing a quarter car model. Two quarter car models with MR damper are simulated, one uses MFM-1 for MR damper and the other uses MFM-2. All the quarter car models are subjected to single pulse input and the sprung mass response is measured in terms of displacement. The RMS error between the response of quarter car model with equivalent damping and quarter car models with MR damper is used to determine the performance of each mathematical model. The study revealed that MFM-1 represents the MR damper behavior more accurate than that of MFM-2. Â© 2019 Elsevier Ltd.
Application of vibration analysis and data mining techniques for bearing fault diagnosis in two stroke IC engine gearbox
(American Institute of Physics Inc. subs@aip.org, 2020) Ravikumar, K.N.; Kumar, H.; Gangadharan, K.V.
This paper is about monitoring of ball bearing used in the IC engine gearbox using condition monitoring techniques. Experiments are conducted on two stroke IC engine which is driven by the 3HP DC motor. Vibration signals are acquired from the gearbox with triaxial accelerometer. Ball bearing with good and induced faulty (outer race fault, inner race fault, ball fault, inner and outer race fault) conditions were used in the analysis. Fault diagnosis of the ball bearing has been carried out using data mining (DM) techniques. In DM there are three stages viz.; feature extraction, feature selection and feature classification. For all the conditions of bearing, statistical and empirical mode decomposition (EMD) features are extracted from the vibration signals. Decision tree technique (J48 algorithm) is used in the analysis for selecting significant features from the feature vector. From the chosen features, ball-bearing conditions are classified using random forest algorithm. Results obtained from the different classifiers were compared, and a better classification algorithm with a decision tree will be suggested for condition monitoring of the rotating components. Â© 2020 Author(s).
Ball bearing fault diagnosis based on vibration signals of two stroke ic engine using continuous wavelet transform
(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2020) Ravikumar, K.N.; Madhusudana, C.K.; Kumar, H.; Gangadharan, K.V.
Ball bearings are used in the different critical fields of engineering applications such as IC engine, centrifugal pump and fans. In IC engine, the ball bearing is one of the critical components and it takes various types of dynamic loads and stresses. Condition monitoring of such ball bearing is very significant to avoid the catastrophic failure of rotating components in IC Engine. This article describes the fault detection of roller ball bearing of an IC engine gearbox with the use of signal processing technique such as spectrum analysis and Continuous Wavelet Transform (CWT) analysis. Vibration signals of IC engine are used to identify the fault in the ball bearing and to detect the healthy and fault bearing conditions. Â© Springer Nature Singapore Pte Ltd 2020.
Characterization and quarter car analysis with magnetorheological fluid damper using modified algebraic model (mAlg)
(Elsevier Ltd, 2022) Kumbhar, S.; Puneet, N.P.; Kumar, H.
Magnetorheological (MR) dampers have received the ever-increasing attention of many researchers considering their wide range of applications ranging from large seismic control of structures to prosthetics in the medical field. One such application is in semi-active vehicle suspension with MR damper. Modeling the dynamic behavior of MR damper is an intriguing challenge and many mathematical models are put forth to address this task. In this work, the MR damper is initially developed and characterized using in-house prepared MR fluid. This study aims at using a modified algebraic model (mAlg) for modeling the hysteretic behavior of the MR damper using experimental force data. Also, the study uses a Genetic algorithm toolbox to find optimal parameters for the mAlg model, and the accuracy of mAlg is visualized with various plots. The work also aims at analyzing the response of the quarter car model with MR damper to three kinds of road excitations using Simulink. © 2022
Characterization of an in-house prepared magnetorheological fluid and vibrational behavior of composite sandwich beam with magnetorheological fluid core
(Sharif University of Technology, 2023) Nagiredla, S.; Joladarashi, S.; Kumar, H.
In this research work, two different compositions of MR fluid samples with 24 and 30 percentage (%) volume fraction of carbonyl iron (CI) particles are prepared. Prepared MR fluid (MRF) samples contain carbonyl iron particles as a dispersive medium, silicone oil as a carrier fluid, and white lithium grease as an anti-settling agent. Influence of oscillating driving frequency, strain amplitude, magnetic field, and the percentage of CI particle on the rheological properties of the MR fluid samples are presented. Storage modulus and loss factor equations are estimated from the rheometry results using a linear regression method. The properties of MR fluid samples are taken to design and model the sandwich beams using ANSYS ACP software, where carbon epoxy composite material is used as the face layer and MR fluid as the core material. Modal, harmonic, and transient analysis studies have been conducted on all the modelled sandwich beams. Influence of MR fluid core material thickness, face layer thickness, CI particle volume percentage in the prepared MR fluid sample, and magnetic field on the vibrational response of the sandwich beams have been presented. Carbon-epoxy composites with an in-house made MRF sandwich beam has shown some significant results in the vibrational response. © 2023 Sharif University of Technology. All rights reserved.
Characterization of magnetorheological brake utilizing synthesized and commercial fluids
(Elsevier Ltd, 2019) Acharya, S.; Shyam Saini Tak, R.; Bhanu Singh, S.; Kumar, H.
Magnetorheological (MR) brakes produce braking torque due to variation in the magnetorheological properties of the MR fluid when external magnetic field is applied. In this study, MR fluids having 70% and 80% weight fractions of iron powder were prepared and MR brake characteristics were tested for prepared MR fluids and a commercial Lord MRF 132 DG fluid. It was found that there was an increase in braking torque with applied current to MR brake at all speeds indicating the MR effect. With increase in weight fraction, there is an increase in braking torque though the reduction in speed is not significant. However, in case of MRF 132 DG fluid, the decrease in rpm is significant especially at higher speeds. Though, the prepared fluids and commercial fluid produce closer braking torque values at higher currents, the increase in braking torque without magnetic field to that with magnetic field at maximum current of MR brake utilizing commercial fluid is very high due to its low viscous torque. Finally, analysis in finite element method magnetics software combined with analytical equations was used to compute torque and compared with experimental results of MR brake utilizing commercial fluid. Â© 2019 Elsevier Ltd.
Classification of gear faults in internal combustion (IC) engine gearbox using discrete wavelet transform features and K star algorithm
(Elsevier B.V., 2022) Ravikumar, K.N.; Madhusudana, C.K.; Kumar, H.; Gangadharan, K.V.
Vibration-based fault diagnosis is one of the widely used techniques for condition monitoring of the machines equipped with a gearbox. Severe operating conditions of gearbox result in gear tooth failure. To develop an effective fault diagnosis technique for the mechanical system, a machine learning approach is highly necessary and plays a vital role in the area of condition monitoring. This paper presents the vibration-based fault diagnosis of IC engine gearbox operating under actual running condition. An Eddy current dynamometer is used to apply the external load on the output shaft of the engine. Driving gear with healthy condition and progressive tooth defect conditions are considered for the analysis. The vibration signals of engine gearbox under various gear tooth conditions are measured. Discrete wavelet transform features are extracted from the vibration signals and more contributing features for classification are selected using decision tree algorithm. The Lazy based classifiers viz, k-nearest neighbour algorithm, K-star algorithm and locally weighted learning algorithm are used for classification. A comparative study of these classifiers is made using percentage of classification accuracy. The maximum classification accuracy of about 97.5% is achieved by the K-star algorithm. Based on the experimental results, K-star algorithm and discrete wavelet transform technique can be used for diagnosing the gear faults in IC engine gearbox using vibration signals. © 2021 Karabuk University
Combined Damping Effect of the Composite Material and Magnetorheological Fluid on Static and Dynamic Behavior of the Sandwich Beam
(Springer, 2023) Nagiredla, S.; Joladarashi, S.; Kumar, H.
Purpose: In the present study, the influence of combined damping due to composite facings and magnetorheological (MR) fluid on the static and dynamic response of the graphite/epoxy composite sandwich beam is investigated because the combined damping effect plays a crucial role in suppressing the high amplitudes of vibration for the structural applications. Methods: The sandwich beam element with 12 degrees of freedom is considered for the finite element (FE) formulation and the Lagrange’s approach is employed to obtain the equations of motion (EOM). The FE code is developed and validated with the available literature to examine the static, free and forced vibration response of the MR composite sandwich beam. Results: The influence of laminate angle, magnetic field, and thickness ratio on the static deflection, loss factor, natural frequency and forced vibration response are presented. Further, the influence of the applied magnetic field on the percentage of reduction in static deflection and the deviation in the first fundamental natural frequency and loss factor are evaluated. Conclusion: It is observed that the central static deflection of the sandwich beam is more for the composite facings at higher laminate angles. The percentage of deviation in the first fundamental natural frequency and loss factor significantly improved with the applied magnetic field. The damping considered in both the composite facings and MR fluid displayed a good attenuation in vibration amplitude. © 2022, Krishtel eMaging Solutions Private Limited.