Thermal performance of (organic and inorganic) multi PCM Encapsulated systems

The storing of energy is the imprisonment of energy at one time to use the similar for another time. This review paper treats with the approaches of thermal energy storage and its implementations in the neighborhood of solar water heating schemes in addition to scheme of solar air heating and the materials utilized to preserve that thermal energy efficiently. This paper delivers the theoretical information of appropriate and unwanted features of various phase change materials PCMs. The paper includes several approaches of thermal energy storage as, latent heat storage, sensible heat storage and thermo-chemical energy storage, concentrating mostly on (PCMs) as an arrangement of appropriate solution for usage of energy to fill the hole amid deliver and request to develop the effectiveness of energy of a scheme. Theoretical details have been shown in the paper. The numerical results show the temperature contour increases when the time of charging process increases, and the temperature contour decreases when the time of discharging process increases.

Classification of Grain Storage Inventory Modes Based on Temperature Contour Map of Grain Bulk Using Back Propagation Neural Network

Inventory modes classification can reduce the workload of grain depot management and it is time-saving, not labor-intensive. This paper proposed a method of using a temperature contour map converted from digital temperature data to classify stored grain inventory modes in a large bulk grain warehouse, which mainly included detection of inventory changes and routine operations performed (aeration). The back propagation (BP) neural network was used in this method to identify and classify grain storage inventory modes based on the temperature contour map for helping grain depot management work. The method extracted and combined color coherence vector (CCV), texture feature vector (TFV) and smoothness feature vector (SFV) of temperature contour maps as the input vector of the BP neural network, and used inventory modes as the output vector. The experimental results indicated that the accuracy of the BP neural network with vector (CCV and TFV and SFV) as the input vector was about 93.9%, and its training time and prediction time were 320 and 0.12 s, respectively.

THREE-DIMENSIONAL NUMERICAL SIMULATION OF A VERTICAL THERMAL TANK

In this study, the results obtained by the numerical simulation presented in this paper are compared with the results obtained experimentally by Oliveski (2000) for a vertical cylindrical thermal reservoir with internal diameter of 0.42m and internal height of 0.57m (79L). In the simulation using Ansys software, for the same parameters of the problem, a study to evaluate the degree of mesh refinement was performed based on the methodology used by Adolfo (2015). The boundary conditions adopted were: Flow: Transient; Buoyancy Model: Boussinesq Approximation; Step of time used: 1s; Wall Condition: Top Non slip / adiabatic; Base: h = 06 [Wm ^ 2 / K]; Lateral: h = 10 [Wm ^ 2 / K]; Initial tank conditions: Null velocity field and initial temperature of approximately 355.15 K. Total simulated flow time: 18,000 s. For the external temperature, contour condition used in the simulation, the ambient temperature was used as a function of time through the graph provided by Oliveski. Three meshes were compared based on the methodology used by Adolfo (2015) in his studies. These have 1,512,143 and 7,997,663, 851,837 and 4,379,079, 271,898 and 1,308,368, number of nodes and elements, respectively. For the turbulence model adopted, the SST (Shear Stress Transport) model was used. The simulations took approximately 58 days to complete. The residue sought in the iterations was at least 0.001, with a maximum of 100 iterations for each time step. For the behavior of the temperature field in the tank over time the formation of the stratified temperature profile was observed, as described in Oliveski's work, and also that the thermal stratification occurs only in the lower region and that in the upper region the water becomes temperature is almost constant. In terms of mean temperature in the tank, the simulation is very close to the results shown by Savicki (2007). However, in terms of temperature profile along the height of the tank, this behavior is shown to be different. Another fact is that the height of the thermocline found in this simulation was considerably higher than that shown in the Savicki simulation. Therefore, the results obtained were validated with the experimental results presented by Oliveski and the numerical results presented by Savicki. It has been confirmed that the mesh with the second refinement level is already sufficiently capable of generating satisfactory results.

Turbulent Flow Behavior of Mixing Process Inside a Pharmaceutical Stirred Tank

As mixing is an essential operation in many engineering fields a mixing system is designed using agitated vessels in which it is difficult to obtain accurate information on induced turbulence by the impeller where CFD can provide detailed understanding of such systems. Here the impeller is designed and tested in both single phase &multiphase. Here specifically incompressible flow is used and Multiple reference frame is used to model the motion of the impeller zone. Hence, we study the flow characteristics by comparing the velocity and temperature contour of three different rotating speed of the impeller and predict the percentage increase and decrease for varying boundary conditions.

Numerical Modeling on Fuel Cell Cooling using Water Based Aluminum Nitride Nanofluid

In the trendy research, CFD codes got developed and run with water-AlN nanofluid to predict the thermal concerns of fuel cell. The convective governing equalities of mass, force and drive are computed for predicting the thermal issues of fuel cell. The time step selected throughout the intact computation is 0.0001 s. The soundings affect CFD forecasts of temperature field, temperature contour plus fluid-solid boundary temperature of fuel cell. The fluid-solid boundary temperature of fuel cell is noticed as 320 K. This stands far less than the hazardous limit of 356 K temperature desired for the objective of beating thermal cataclysm of fuel cell. The temperature of water-AlN nanofluid stands peak contiguous to the fuel cell vicinity. Additionally, the temperature of water-AlN nanofluid gently drops with improvement in remoteness from fuel cell. Subsequently, this becomes surrounding temperature in the distant field zone. The corresponding tinted temperature contour stands accessible. In addition, the congruent plot of temperature against distance from fuel cell stays revealed. The development of CFD revelations stand together with the credentials of undertakings

Increased Melting Heat Transfer in the Latent Heat Energy Storage from the Tube-and-Shell Model to the Combine-and-Shell Model

The melting of paraffin in thermal storage tube-and-shell and combine-and-shell models was conducted with the numerical research aim of decreasing the charge time through changing the shape of the tube into combining form. The results discussed are temperature contour, liquid-solid interface contour, temperature distribution, liquid fraction, and the average Nusselt number. The results show that the charge time in the tube-and-shell model is 2000 s, while the combine-and-shell model is 1200 s, meaning an overall decrease in charge time in the combine-and-shell model by 40% when compared to that of the tube-and-shell model.

Numerical simulations to determine the influence of mould design on ice-templated scaffold structures

In recent years, there has been a shift from traditional cell culture on two-dimensional substrates towards the use of three-dimensional scaffolds for tissue engineering. Ice-templating is a versatile tool to create porous scaffolds from collagen. Here we discuss specific considerations for the design of moulds to produce freeze dried collagen scaffolds with pore sizes of around 100µm, a range that is relevant to tissue engineering. A numerical model of heat conduction, implemented in COMSOL Multiphysics® version 5.0, calculated the temperature contour lines and heat flow vectors during cooling for a variety of mould geometries and materials. We show how temperature distribution within moulds determines the resulting pore structure of the scaffolds by regulating ice growth, and we validate our simulation against experimental results. These simulations are especially useful when working with moulds that contain volumes of more than 1cm in each direction.

The Numerical Simulation and Experimental Research of Combustor in Micro Thermophotovoltaic Systems

With the establishment of the appropriate porous media model of the combustor, temperature contour map on combustor cross section were simulated under the condition of different flow rate and different porosity in the Fluent software, and experimented to verify the simulation. The results show that: Flame core position moves toward the export with the increase of flow rate, but when the flow increases to a certain amount, the outlet temperature rises significantly. temperature distribution is the best when flow rate is 120 mL/min; With the decrease of the porosity, the flame core position moves to the entrance. Wall average temperature of the combustor is the highest when porosity is 0.4.