Conference Papers
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Item Numerical Studies for Charging and Discharging Characteristics of Composite Phase Change Material in A Deep and Shallow Rectangular Enclosure(Institute of Physics Publishing helen.craven@iop.org, 2018) Chavan, S.; Arumuga Perumal, D.A.; Gumtapure, V.In this study, a numerical analysis of the melting process with natural convection in a rectangular enclosure has been performed using enthalpy porosity model. A Composite phase change material (Paraffin wax (98%) is used as base material and copper nanoparticles (2%) as additives) is used. The enclosure is heated from one side and opposite side is isothermal at 300 K, and remaining walls are thermally insulated. Melting heat transfer in a rectangular enclosure with different orientations are investigated numerically. The flow field results in nonuniform melting of the composite phase change material (CPCM). The interface morphology is used to infer flow structure and the extent of two-dimensional energy transport. These flow patterns are found to be dependent on the orientation and the initial CPCM sub-cooling. The results reveal that the enclosure orientation has a significant effect on the formation of natural convection currents and consequently on the heat transfer rate and melting time of the CPCM. As the orientation changed from deep to shallow, the convection currents in the enclosure, increases and chaotic flow structure appear. Hence, it can be concluded that the heat transfer enhancement ratio for the deep enclosure is more than that of the shallow enclosure. © Published under licence by IOP Publishing Ltd.Item Effect of geometry on heating and cooling characteristics for thermal energy storage-A Computational Study(Toronto Metropolitan University, 2019) Chavan, S.; Gumtapure, V.; Arumuga Perumal, D.A.In the present work an attempt is made to understand the effect of geometry on heating and cooling characteristics for thermal energy storage applications. Three different geometrical models (square, pentagon and hexagon) are selected and thermal storage material used is composite of paraffin wax (98%) and Al2O3 nanoparticles (2%) [1-2]. The heating and cooling processes are analyzed by applying constant heat flux and the boundary conditions imposed are: Heating cycle (i) Constant heat flux is applied to left wall (for square) and upper left wall (for pentagon and hexagon). Cooling cycle (ii) Constant heat rejection through right wall (for square) and lower right wall (pentagon and hexagon). (iii) Remaining all other walls are Insulated for both the cases. The geometrical 2-D model is created by using ICEMCFD16.0 pre-processing software of ANSYS 16.0 version, in order to interpret the superior results good quality mesh is generated all over the computational domain. At the boundaries, the mesh size is reduced and made a uniform to response imposition of inputs and resolve the boundary layer conflicts. In order to reduce the computational time, relatively larger mesh is maintained at the center part of the domain. To investigate the problem Fluent 16.0 is used and concerned parameters are defined, boundary conditions are imposed and temperature dependent user-defined functions (UDF) are interpreted. The numerical investigation aims to understand the effect of geometry on heating and cooling characteristics using composite phase change material. The streamline patterns, liquid fractions and temperature distribution profiles are analyzed and among the models square and hexagonal model shown quicker melting (completed melting within 4000 sec). The liquid fraction variation is also similar and uniform, the temperature variation during complete melting process is least in square model followed by pentagonal model. However, liquid fraction variation is least in pentagonal model. Temperature variation during heating is maximum in case of hexagonal model (14%) increase in temperature. Liquid fraction variation is uniform and smooth in hexagonal model and consumed 50% less time than pentagonal model. The cooling cycle analysis also explored some interesting results, cooling rate is very quick in square model but for optimal thermal storage unit heat rejection process should not be too steep. Pentagonal model shown insignificant characteristics during both heating and cooling processes. The hexagonal model exhibited uniform and gradual variation in liquid fraction as well as temperature variation during the process. For ideal thermal storage device quicker heating is expected and heat rejection should be gradual and relatively slower (specially for long term storage applications). Among all the cases if only heating is required then square model will be the best selection but to achieve optimal heating and cooling hexagonal model will be the best option. © 2019, Toronto Metropolitan University. All rights reserved.Item Preparation and characterization of nanoparticle blended polymers for thermal energy storage applications(American Institute of Physics Inc. subs@aip.org, 2019) Chavan, S.; Gumtapure, V.; Arumuga Perumal, D.A.This paper is concerned with the comprehensive procedure of preparing, morphological characterization and thermal property evaluation of nanoparticle blended polymer composites. Polymer composites are intended to consecrate the thermal energy storage applications. Linear low-density polyethylene (LLDPE) is incorporated with functionalized graphene with different concentrations (1, 3 and 5%). The morphological study revealed compatibility of polymer composites, at lower concentrations (1-3%,) it shows homogenous dispersion, but above threshold limit the particle distribution is non-homogenous with coarse surface structures. Higher concentration (5%) of nanoparticles emulsifies the molecules and generates micelles between themselves. The thermal conductivity of the polymer composite is significantly enhanced with the reduction of specific heat. At lower concentrations polymer exhibits homogeneous dispersion and the interfacial interaction is comparatively higher, optimal concentration (3%,) of nanoparticle provides favorable results and hence polymer composites with ideal concentration can be utilized for thermal energy storage applications. © 2018 Author(s).Item Preparation of functionalized graphene-linear low-density polyethylene composites by melt mixing method(American Institute of Physics Inc. subs@aip.org, 2020) Chavan, S.; Gumtapure, V.; Arumuga Perumal, D.A.Graphene is attracting gigantic amount of scientific interest due to its excellent thermo-physical properties. Graphene integration improves the electrical and mechanical properties of polyethylene-based polymers. This paper is concerned with the comprehensive procedure of preparing, morphological characterization and thermal property evaluation of nanoparticle blended polymer composites. Polymer composites are intended to consecrate the thermal energy storage applications. Linear low-density polyethylene (LLDPE) is incorporated with functionalized graphene with different concentrations (1, 3 and 5%). The morphological study revealed compatibility of polymer composites, at lower concentrations (1-3%) it shows homogenous dispersion, but above threshold limit the particle distribution is non-homogenous with coarse surface structures. Higher concentration (5%) of nanoparticles emulsifies the molecules and generates micelles between themselves. The thermal conductivity of the polymer composite is significantly enhanced with the reduction of specific heat. At lower concentrations polymer exhibits homogeneous dispersion and the interfacial interaction is comparatively higher, optimal concentration (3%) of nanoparticle provides favorable results and hence polymer composites with ideal concentration can be utilized for thermal energy storage applications. © 2020 Author(s).Item Taskgraph Framework: A Competitive Alternative to the OpenMP Thread Model(Institute of Electrical and Electronics Engineers Inc., 2025) Chavan, S.; Nile, P.; Kumar, S.; Bhowmik, B.OpenMP is the predominant standard for shared memory systems in high-performance computing (HPC), offering a tasking paradigm for parallelism. However, existing OpenMP implementations, like GCC and LLVM, face computational limitations that hinder performance, especially for large-scale tasks. This paper presents the Taskgraph framework, a novel solution that overcomes the limitations of traditional task dependency graphs (TDGs). Unlike conventional TDGs, which require costly reconstruction for dynamic program structures, the Taskgraph framework uses a taskgraph clause with a list of variables, enabling real-time adaptation without complete reconstruction. This approach significantly reduces overhead, making the Task-graph model highly efficient for tasks with minimal dependencies, offering a competitive alternative to the OpenMP thread model, and enhancing efficiency and adaptability in dynamic HPC environments. © 2025 IEEE.