Journal Articles
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884
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Item Numerical consideration of LTNE and darcy extended forchheimer models for the analysis of forced convection in a horizontal pipe in the presence of metal foam(American Society of Mechanical Engineers (ASME), 2021) Jadhav, P.H.; Gnanasekaran, N.; Arumuga Perumal, D.The intent of the current research work is to emphasize the computational modeling of forced convection heat dissipation in the presence of high porosity and thermal conductivity metallic foam in a horizontal pipe for different regimes of the fluid flow for a range of Reynolds number. A two-dimensional physical domain is considered in which Darcy extended Forchheimer (DEF) model is adopted in the aluminum metallic foam to predict the features of fluid flow and local thermal nonequilibrium (LTNE) model is employed for the analysis of heat transfer in a horizontal pipe for different flow regimes. The numerical results are initially matched with experimental and analytical results for the purpose of validation. The average Nusselt number for fully filled foam is found to be higher compared to other filling rate of metallic foams and the clear pipe at the cost of pressure drop. As an important finding, it has been observed that the laminar and transition flow gives higher heat transfer enhancement ratio and thermal performance factor compared to turbulent flow. This work resembles numerous industrial applications such as solar collectors, heat exchangers, electronic cooling, and microporous heat exchangers. The novelty of the work is the selection of suitable flow and thermal models in order to clearly assimilate the flow and heat transfer in metallic foam. The presence of aluminum metal foam is highlighted for the augmentation of heat dissipation in terms of PPI and porosity. The parametric study proposed in this work surrogates the complexity and cost involved in developing an expensive experimental setup. © 2021 American Society of Mechanical Engineers (ASME). All rights reserved.Item Flow Dynamics Of Lid-Driven Cavities With Obstacles Of Various Shapes And Configurations Using The Lattice Boltzmann Method(Yildiz Technical University, 2021) Rajan, I.; Arumuga Perumal, D.This work implements the emerging computational technique namely the Lattice Boltzmann Method (LBM) to a fluid flow problem of single sided lid-driven cavities with various shapes of obstacles placed in it. The numerical methodology employs the Single-Relaxation-Time (SRT) model applicable to low Mach number hydrodynamic problem for incompressible flow regime. Three geometrical shapes of the obstacles considered are circular, square, and elliptic. Cavity with obstacles exhibited remarkable circulation zones and structures in contrast to the classical lid driven cavity. The flow mechanics and the vortex dynamics are studied for various values of Reynolds Number (Re = 100, 400, and 1000). Due to the introduction of the obstacles, a strong induced vortex forms close to the obstacles and its size changes interestingly with the variation of Reynolds number, which is captured by LBM. Further the study is extended to examine the vortex phenomena induced by changing the position of the obstacles within the cavity. It is observed that the flow structures change dramatically with little change in the position of obstacle inside the cavity which helps to identify position with enhanced mixing characteristics. © 2021. Journal of Thermal Engineering. All rights reserved.Item Computational investigation on the effect of geometrical parameters on thermal energy storage systems(Begell House Inc., 2021) Chavan, S.; Gumtapure, V.; Arumuga Perumal, D.The present work is an attempt to understand the effect of geometry on the heating and cooling characteristics of thermal energy storage systems. Three different geometrical models (square, pentagon, and hexagon) were considered and the thermal storage material used was a composite of paraffin wax (98%) and Al2O3 nanoparticles (2%). The heating and cooling processes were analyzed by applying a constant heat flux. Among the three models, the square model showed a faster melting rate but the cooling rate was too steep. The hexagonal model showed optimum results in both the heating and cooling processes with uniform and smooth variations in the liquid fraction and temperature. Hence, for optimal thermal storage applications the hexagonal model (or its geometries), which is close to the circular model, can be considered. © 2021 by Begell House, Inc.Item Performance assessment of composite phase change materials for thermal energy storage-characterization and simulation studies(Bentham Science Publishers, 2021) Chavan, S.; Gumtapure, V.; Arumuga Perumal, D.Background: The present study mainly focuses on the development of new Thermal Storage Materials (TSM) and compare the performance for thermal energy storage capacity. Linear Low-Density Polyethylene (LLDPE) based Composite Phase Change Materials (CPCMs) is prepared, and its properties are analyzed using characterization, analytical calculations, and numerical simulation meth-ods. The composites are prepared by blending the functionalized graphene nanoparticles (1, 3 & 5%) with three different concentrations into LLDPE. All three CPCMs show enhanced thermal performance compared to the base material, but it is noticed that higher concentrations of nanoparticles increase the dynamic viscosity and produce an adverse effect on thermal performance. Thermal characterization shows improved latent heat capacity with nanoparticle concentration, analytical and numerical results also compared, which shown a difference of 10 to 25%. Objective: The purpose of this study is the development and evaluation of the thermal storage capacity of different thermal storage materials and enlighten the techniques used for characterizing the storage materials. Methods: Composite material preparation is carried out by using twin-screw extruders, characterization of developed material is done through FTIR, SEM, and DSC analysis. For complete analysis character-ization, analytical calculations and numerical simulation methods are used. Results: Linear low-density polyethylene-based composite materials can be successfully developed using a twin-screw extruder. This extrusion provided proper dispersion of nanoparticles into the base material, and it is validated by SEM analysis. DSC analysis confirmed the enhancement in the thermo-physical properties of composite materials. Conclusion: The latent heat capacity increased around 20% during the heating cycle and reduced ap-proximately 23% during the cooling cycle for base material and 5% addition of nanoparticle, respec-tively. The comprehensive study accomplishes that the optimum concentration of nanoparticle provides better thermal performance for thermal energy storage applications. © 2021 Bentham Science Publishers.Item Computational analysis of fluid immersed active cooling for battery thermal management using thermal lattice Boltzmann method(Springer Science and Business Media Deutschland GmbH, 2022) Joe, E.S.; Arumuga Perumal, D.A computational analysis of the thermal management system of a battery-pack, whereby the cells are actively cooled at their surfaces by being immersed in a nanofluid medium. Nanofluids used in the automotive and energy management systems are selected and modelled within this work. The present study is conducted by carefully observing the flow structures, thermal energy distribution, entropy generation and pumping power requirements within the battery-pack, to be able to present a resource helpful for designers in the preliminary stages of their thermal management system. This study throws light beyond the case of the battery-pack thermal management, to other applications that require to be maintained at a given temperature or require a certain quantity of heat to be removed from it. © 2022, The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature.Item Computational Modelling of Heat Transfer through Aluminium Metal Foams for LiFePO4 Battery Cooling(Bentham Science Publishers, 2024) Arjun, P.S.; Arumuga Perumal, D.Temperature is crucial for battery pack durability and power. Folded fin and serpentine channel cooling methods are mostly used to cool the pack. However, fluid absorption during cooling can reduce capacity and cause downstream temperatures to be higher than upstream. Consistent cooling is vital to prevent temperature variation and increase battery pack lifespan. This work is concerned with the computational study of heat dissipation from open-cell aluminium metal foam for cooling LiFePO4 battery packs. The battery module consists of six pieces of pouch cell and three pieces of the aluminium foam heat sink. In the present study, aluminium foams are positioned between the LiFePO4 battery modules that are arranged in a vertical manner. Thermal interaction between the battery module and aluminum foam was studied. The effect of pore density on heat dissipation performance at different mass flow rates was explored. It has been discovered that aluminium foam with suitable porosity and pore density can efficiently cool the LiFePO4 battery pack. This paper provides a theoretical framework for designing a thermal management system for lithium- ion batteries using aluminium foam. Background: Metal foam cooling is an established technique for thermal management of Lithiumion batteries in electric vehicles. Objective: The present study aims to analyze heat transfer through aluminium metal foams for vertically aligned LiFePO4 battery pack cooling. Methods: The Darcy extended Forchheimer (DEF) model examines fluid flow through metallic foams, using the local thermal non-equilibrium model to determine heat transfer. Results: The impact of the density of pores in the aluminium foam on the average wall temperature and temperature difference along the battery surface is determined. The variation of heat transfer of lithium-ion battery modules for different mass flow rates is also studied. Conclusion: The results indicate that utilizing aluminium foam as a heat transfer medium for battery modules significantly enhances their thermal management performance. © 2024 Bentham Science Publishers.Item Analyzing the impact of nanofluid flow rate and thermal conductivity on response time in a compact heat spreader-integrated microchannel heat sink(Springer Science and Business Media B.V., 2024) Narendran, G.; Gnanasekaran, N.; Arumuga Perumal, D.In microchannel-based cooling devices, the response time exhibits distinctive variations owing to the heterogeneous integration of the heat source and the heat sink. These variations accompanied by flow maldistribution attributes to local temperature gradients are often referred to as flow-induced high-temperature zones and develop an uneven temperature distribution in microchannel heat sinks. To explore this phenomenon, we have designed an experimental setup featuring an in-house rectangular microchannel with an integrated heat spreader. In this study, we use a nanofluid comprised of graphene oxide (GO) and water as the working fluid, aiming to understand the thermo-hydrodynamics of the heat sink for various channel aspect ratios. The experimental results show that the heat wave propagation in the heat spreader is highly directional and influenced by the nanofluids flow rate and thermal conductivity. The study demonstrated that bulk fluid diffusion of GO nanofluid increased the temperature of the heat spreader by 30%. In the case of working fluid temperature, it increased by 35% for water and 52% for GO-0.12%. © Akadémiai Kiadó Zrt 2024.Item A Computational Approach on Mitigation of Hotspots in a Microprocessor by Employing CNT Nanofluid in Bifurcated Microchannel(Institute for Ionics, 2024) Basha, S.M.M.; Ahammed, M.; Arumuga Perumal, D.; Yadav, A.The present study discusses the numerical analysis of mitigating hotspots in a microprocessor by employing nanofluid composed of carbon nanotubes (CNT) and water in a bifurcated microchannel. Fully developed laminar flow with water for different multi-stage bifurcated plate configurations is used for the computational study along with the conventional microchannel without bifurcation to determine the best possible configuration of bifurcated microchannel where further numerical investigation is carried out with CNT–water nanofluid. Numerical investigations are performed to evaluate the Nusselt number, temperature distribution, thermal resistance, pumping power, and streamline distribution for Reynolds Numbers varying from 70 to 560. Among all the bifurcated microchannels, the two-stage bifurcated microchannel shows the best thermal–hydraulic performance. So, the two-stage bifurcated microchannel is numerically studied with CNT–water nanofluid by varying the concentration from 1 to 5% where the bottom wall temperature significantly decreases along with desired uniform temperature distribution of the surface. It has been found that the average Nusselt number for a two-stage bifurcated microchannel with 5% CNT–water nanofluid is 43.54% higher than that of a two-stage bifurcated microchannel with water. There is a 9% decrement in thermal resistance against a 5% enhancement in pumping power using 1% CNT–water as coolant compared to that with only water in a two-stage bifurcated microchannel. Additionally, the influence of flow rate on multi-stage bifurcated microchannel combined with hotspots and studies involving varying intensities of hotspots along with their position in the microchannel are investigated. © King Fahd University of Petroleum & Minerals 2023.Item Deep dual domain joint discriminant feature framework for emotion based music player(Springer, 2024) Anbalagan, A.; Challa, R.T.; Saketh, S.; Chakka, S.; Arumuga Perumal, D.; Poornachari, P.Emotion based music player is an interdisciplinary study of computer vision and psychology. As music enhances the positive vibes it plays a significant role in soothing people’s emotion. Emotions can be predicted through facial expression analysis using vision-based methods. However, challenges like environment and expression complexity have become hindrance to attain a good recognition rate. Therefore, we put forward a deep dual domain joint feature framework based on linear discriminant analysis for facial emotion recognition. First, we detect the human face and learn the emotion pattern using the popular complementary deep domain networks called EfficientNet and ResNet50. The learned deep dual domain space is projected onto linear discriminant space to achieve a joint discriminant feature space. The recognition rate of the proposed joint discriminant feature framework is analyzed using support vector machine. To prove the efficacy of the proposed framework, we validated it on two Benchmarks namely FER2013 and CK48+ datasets. The proposed framework achieved a good recognition rate of 99% and 98.6% on FER2013 and CK48+ respectively. Experimental analysis on our EmDe dataset showed an accuracy of 99% and proves that the deep dual domain joint discriminant framework as a promising pipeline for emotion-based music player system. © The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2024.Item Infrared Perspectives: Computing laptop energy dissipation via thermal imaging and the Stefan-Boltzmann equation(Elsevier Ltd, 2024) Anbalagan, A.; Arumuga Perumal, D.; Persiya, J.Energy conservation is crucial for reducing greenhouse gas emissions and addressing climate change. Laptops contribute significantly to energy consumption, emphasizing the need for improved energy efficiency. This paper explores the application of thermal imaging technology to enhance energy conservation in laptops. Thermal imaging provides valuable insights into heat distribution on the laptop's surface, aiding in identifying areas of excessive energy consumption. By identifying areas of a laptop that generate excessive heat and implementing energy-efficient measures, energy consumption can be reduced, and the device's lifespan can be extended. The study leverages computer vision and artificial intelligence techniques to analyze thermal images. We collected the thermal images for the dataset using the FLIR E75 Thermal camera. Two methods of Region of Interest (ROI) extraction, contour-based thresholding, and Detectron2-based extraction are employed. Feature extraction includes statistical, texture, spatial, and energy features, and Principal Component Analysis (PCA) is used to reduce dimensionality. K-means clustering categorizes data points based on reduced features, and performance metrics validate the effectiveness of the clustering methods. The study also computes energy dissipation from thermal images using the Stefan-Boltzmann Law. Results indicate that thermal imaging, coupled with advanced analysis techniques, holds promise for improving energy conservation in laptops. © 2024 Elsevier Ltd