Test method of composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins

Abstract

The invention relates to the technical field of phase change heat storage, in particular to a test method of a composite nanoparticle latent heat system based on a Fibonacci fractal tree-shaped fin. The test method comprises the following steps: firstly, establishing a physical model of a nanoparticle three-sleeve vertical latent heat system based on the Fibonacci fractal tree-shaped fin; secondly, performing two-dimensional simulation analysis on the physical model by adopting a two-dimensional model, simulating the melting and solidification process of the PCM, analyzing the heat transfer performance and energy storage efficiency of the system, building an experimental device of a nano-particle three-sleeve vertical latent heat system based on the Fibonacci fractal tree-shaped fins, selecting proper PCM and nano-particles, simulating different working conditions, and establishing a three-sleeve vertical latent heat system based on the nano-particle three-sleeve vertical latent heat system based on the Fibonacci fractal tree-shaped fins. And finally, comparing a simulation result with an experimental result, adjusting parameters of a simulation model, improving the accuracy of the simulation result, analyzing the influence of different fin bifurcation angles, nanoparticle types, wall surface temperatures and fin materials on the heat transfer performance and energy storage efficiency of the system, and providing guidance for optimal design of the system.

Description

Technical Field

[0001] The invention relates to the technical field of phase-changing heat storage, and in particular to an experimental method for a composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins. Background Art

[0002] Phase change energy storage technology uses the latent heat absorbed and released by phase change materials (PCM) during the melting and solidification process to store and utilize the waste heat generated in human production and life. It is widely used in solar energy, building energy conservation, industrial waste heat recovery and battery thermal management systems. Among them, the casing latent heat system is one of the current research hotspots of phase change energy storage technology.

[0003] The latent heat system of tube-in-tube mainly consists of three parts: inner tube, outer tube and fin. The hot fluid flows in the inner tube and transfers the heat to the fin, which acts as a carrier to transfer the heat to the PCM, thereby achieving enhanced heat exchange. Generally, the use of many phase change materials requires wrapping containers, such as tubes, microcapsules, and porous media such as cement. The fin-in-tube latent heat system has broad application prospects in the fields of construction, thermal energy collection, thermal management of electronic devices, and efficient heat flux cooling of spacecraft. In the field of construction, it can be used to adjust the room temperature and improve energy utilization efficiency; in the field of solar energy, it can be used to store solar energy collected during the day for use at night. At present, in the field of medium and low temperature heat storage, paraffin, as a low-cost, non-toxic and odorless organic phase change material, has become the mainstream material in phase change thermal storage technology and is widely used in thermal management and waste heat recovery.

[0004] In addition, due to the low thermal conductivity of PCM, the optimization of fin structure has become one of the research hotspots. Many researchers have borrowed the characteristics of natural shapes, simplified them into TTES fins, and conducted thermal performance analysis. However, most of the existing research only stays on the thermal performance analysis of new fin structures, and has not optimized the specific size and shape according to the evaluation indicators. In addition, the existing research on latent heat systems based on Fibonacci fractal tree fins does not involve the effects of different fin bifurcation angles, different nanoparticle types, wall temperature, and fin materials on liquid phase distribution, temperature distribution, and heat release. Summary of the invention

[0005] The purpose of the present invention is to provide an experimental method for a composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins, aiming to solve the technical problem that the existing research on latent heat systems based on Fibonacci fractal tree-shaped fins does not involve the effects of different fin bifurcation angles, different nanoparticle types, wall temperatures and fin materials on liquid phase distribution, temperature distribution and heat release.

[0006] To achieve the above object, the present invention provides a test method for a composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins, comprising the following steps:

[0007] S1: Establish the physical model of nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins;

[0008] S2: Use a two-dimensional model to perform two-dimensional simulation analysis on the physical model, simulate the melting and solidification process of PCM, and analyze the heat transfer performance and energy storage efficiency of the system;

[0009] S3: Build an experimental device for a nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins, select appropriate PCM and nanoparticles for mixing, prepare composite phase change materials, and inject them into the system, adjust the parameters of the heat source and cooling system, simulate different working conditions, and record the melting and solidification process of PCM;

[0010] S4: Compare the simulation results with the experimental results, adjust the parameters of the simulation model to improve the accuracy of the simulation results, analyze the effects of different fin bifurcation angles, nanoparticle types, wall temperatures, and fin materials on the heat transfer performance and energy storage efficiency of the system, and provide guidance for the optimal design of the system.

[0011] Among them, in step S1, the inner tube diameter Ф1 of the three-tube vertical latent heat system is 20 mm, the outer tube diameter Ф2 is 60 mm, and the wall thickness is 1 mm. The fin structure of the three-tube vertical latent heat system adopts a golden ratio tree-shaped fin. The fin structure is provided with four inner and outer staggered fins. The lengths of the fins are composed of the Fibonacci sequence 8, 5, 3, 2, and 1 in sequence. The middle bifurcation angle θ is used as a control variable for fractal design.

[0012] Among them, in step S1, before establishing the physical model, the enthalpy porosity method is used to calculate the PCM phase change process in the TTES unit, and the control equation is as follows:

[0013] Energy equation:

[0014]

[0015] Where ρ is the PCM density, H is the PCM material enthalpy, is the vector differential operator, k is the thermal conductivity;

[0016] Continuity equation:

[0017]

[0018] In the formula, is the velocity vector;

[0019] Momentum equation:

[0020]

[0021] Where t is time; ρ is density; p is pressure; μ is dynamic viscosity; ξ is thermal expansion coefficient; T ref is the reference temperature, the source term The damping term of Darcy's law can be expressed as:

[0022]

[0023] The liquid phase rate at different times is expressed as follows:

[0024]

[0025] Where T solid Solid phase temperature, T liquid is the PCM liquid temperature;

[0026] The total enthalpy consists of sensible enthalpy and latent enthalpy:

[0027]

[0028] ΔH=λL

[0029] H=λL+h

[0030] Where ΔH is the latent heat enthalpy and h is the sensible heat enthalpy.

[0031] In step S1, the physical model established includes the physical property parameters of the composite phase change material, and the physical property parameters of the composite phase change material are calculated by the classical formula of nanoparticle mixture, and the physical property equation is as follows:

[0032] The density and specific heat of the composite phase change material are shown in the following formula:

[0033] ρ nf =(1-φ ns )ρ f +φ ns ρ ns

[0034] (ρc p ) nf =(1-φ ns )(ρc p ) f +φ ns (ρc p ) ns

[0035] The effective dynamic viscosity of the composite phase change material is expressed by the Brinkman equation:

[0036]

[0037] The thermal conductivity of the composite phase change material is expressed by the Brinkman equation:

[0038]

[0039] Where B is the Boltzmann constant (B = 1.3807 × 10-23 J / K), and γ is a variable representing the volume fraction of nanoparticles expressed as:

[0040] γ=8.4407(100φ ns ) -1.07304 (0.01<φ ns <0.1)

[0041] The empirical function f(T,φ) is as follows:

[0042]

[0043] The heat storage rate of the phase change material when melting while absorbing heat is expressed as:

[0044]

[0045] The heat storage density of the phase change material when it melts while absorbing heat is expressed as:

[0046]

[0047] Among them, in step S2, when the two-dimensional model is used to perform two-dimensional simulation analysis on the physical model, the HTF temperature is simplified to the pipe wall temperature, the PCM is melted by heat transfer between the inner pipe and the outer pipe, the initial state of the PCM is in a melting state at 363K, and the initial temperature of the PCM is:

[0048]

[0049] There is a coupled boundary condition between the fin and the PCM, there is no boundary velocity slip, and the thermal conditions are as follows:

[0050]

[0051] Among them, in step S2, the specific contents of using the two-dimensional model to perform two-dimensional simulation analysis on the physical model include: using MESH software to mesh the latent heat system, and using computational fluid dynamics software ANSYS Fluent to perform numerical calculations.

[0052] In step S2, in the process of numerical calculation using computational fluid dynamics software ANSYS Fluent, the Solidification / Melting model in the Fluent software is selected for solution, and the PISO algorithm is used to process the coupling problem of the pressure field and the velocity field, and the PRESTO! algorithm is used for pressure correction.

[0053] The invention discloses an experimental method for a composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins. First, a physical model of a nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins is established. Then, a two-dimensional model is used to perform two-dimensional simulation analysis on the physical model, the melting and solidification process of PCM is simulated, the heat transfer performance and energy storage efficiency of the system are analyzed, and an experimental device of the nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins is built. Appropriate PCM and nanoparticles are selected for mixing to prepare a composite phase change material, which is injected into the system. The parameters of a heat source and a cooling system are adjusted to simulate different working conditions. The melting and solidification process of PCM is recorded. Finally, the simulation results are compared with the experimental results, the parameters of the simulation model are adjusted, the accuracy of the simulation results is improved, the influence of different fin bifurcation angles, nanoparticle types, wall temperatures and fin materials on the heat transfer performance and energy storage efficiency of the system is analyzed, and guidance is provided for the optimal design of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 It is a flow chart of the steps of the test method of the composite nanoparticle latent heat system based on the Fibonacci fractal tree-shaped fins of the present invention.

[0056] Figure 2 It is a schematic diagram of a nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins provided by the present invention.

[0057] Figure 3 It is a verification diagram of four different grid numbers provided by the present invention.

[0058] Figure 4 It is a schematic diagram of the fitting results of the experiment and simulation of PCM melting and solidification provided by the present invention.

[0059] Figure 5 It is a comparative diagram of heat transfer characteristics analysis between the tree-shaped fins provided by the present invention and traditional fins.

[0060] Figure 6 It is a schematic diagram of the TTES liquid phase distribution and temperature distribution at different fin bifurcation angles provided by the present invention.

[0061] Figure 7 It is a schematic diagram of the change of the TTES liquid phase rate at different fin bifurcation angles provided by the present invention.

[0062] Figure 8 It is a schematic diagram of the average temperature change of PCM under TTES with different fin bifurcation angles provided by the present invention.

[0063] Fig. 9 It is a schematic diagram of the impact of different fin bifurcation angles on the comprehensive thermal performance of TTES provided by the present invention.

[0064] Fig.10 It is a schematic diagram of the change of TTES liquid phase rate under different nanoparticles provided by the present invention.

[0065] Fig.11 It is a schematic diagram of the average temperature change of PCM under TTES under different nanoparticles provided by the present invention.

[0066] Fig.12 It is a schematic diagram of the impact of the comprehensive thermal performance of TTES under different nanoparticles provided by the present invention.

[0067] Fig.13 It is a schematic diagram of the change of TTES liquid phase rate at different wall temperatures provided by the present invention.

[0068] Fig.14 It is a schematic diagram of the average temperature change of PCM under TTES at different wall temperatures provided by the present invention.

[0069] Fig.15 It is a schematic diagram of the solidification characteristics of TTES under different fin materials provided by the present invention. DETAILED DESCRIPTION

[0070] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0071] See also Figures 1 to 15 The present invention provides a test method for a composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins, comprising the following steps:

[0072] S1: Establish the physical model of nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins;

[0073] S2: Use a two-dimensional model to perform two-dimensional simulation analysis on the physical model, simulate the melting and solidification process of PCM, and analyze the heat transfer performance and energy storage efficiency of the system;

[0074] S3: Build an experimental device for a nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins, select appropriate PCM and nanoparticles for mixing, prepare composite phase change materials, and inject them into the system, adjust the parameters of the heat source and cooling system, simulate different working conditions, and record the melting and solidification process of PCM;

[0075] S4: Compare the simulation results with the experimental results, adjust the parameters of the simulation model to improve the accuracy of the simulation results, analyze the effects of different fin bifurcation angles, nanoparticle types, wall temperatures, and fin materials on the heat transfer performance and energy storage efficiency of the system, and provide guidance for the optimal design of the system.

[0076] In this embodiment, a physical model of a nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins is first established, and then a two-dimensional model is used to perform a two-dimensional simulation analysis on the physical model to simulate the melting and solidification process of the PCM, analyze the heat transfer performance and energy storage efficiency of the system, and build an experimental device for the nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins. Suitable PCM and nanoparticles are selected to prepare a composite phase change material, which is injected into the system. The parameters of the heat source and the cooling system are adjusted to simulate different working conditions, and the melting and solidification process of the PCM is recorded. Finally, the simulation results are compared with the experimental results, the parameters of the simulation model are adjusted, the accuracy of the simulation results is improved, and the effects of different fin bifurcation angles, nanoparticle types, wall temperatures, and fin materials on the heat transfer performance and energy storage efficiency of the system are analyzed to provide guidance for the optimal design of the system.

[0077] Among them, in step S1, the inner tube diameter Ф1 of the three-tube vertical latent heat system is 20 mm, the outer tube diameter Ф2 is 60 mm, and the wall thickness is 1 mm. The fin structure of the three-tube vertical latent heat system adopts a golden ratio tree-shaped fin. The fin structure is provided with four inner and outer staggered fins. The lengths of the fins are composed of the Fibonacci sequence 8, 5, 3, 2, and 1 in sequence. The middle bifurcation angle θ is used as a control variable for fractal design. The phase change materials involved in the three-tube vertical latent heat system in this technical solution are paraffin and nanoparticles. The physical properties of paraffin are shown in Table 1 below:

[0078] Table 1. Physical properties of paraffin wax

[0079] Physical properties PCM Main Ingredients RT55 Density / kg / m3 770 Specific heat / J / (kg·K) 2000 Thermal conductivity / W / (m·K) 70.2 Thermal conductivity (K-1) 4.5×10-4 Latent heat / kJ / (kg) 170 Dynamic viscosity / kg / (m·s) 3.408×10-4 Solid phase temperature / K 324 Liquidus temperature / K 330

[0080] The physical properties of the nanoparticles are shown in Table 2 below:

[0081] Table 2. Physical properties of nanoparticles

[0082]

[0083]

[0084] Furthermore, since the phase change process of PCM is relatively complex, it will present a porous structure when melted. Therefore, in step S1, before establishing the physical model, the enthalpy-porosity method is used to calculate the PCM phase change process in the TTES unit, and the following assumptions are made: (1) The liquid PCM is laminar and incompressible; (2) The thermal properties of PCM remain constant in the working temperature range, and the density adopts the Boussinesq assumption, which can be simplified to constant during cooling; (3) The heat loss between TTES and the external environment is ignored, and the thermal conductivity of the coupling wall is assumed to be the same as that of copper, and the thickness of the coupling wall is temporarily ignored; (4) The viscous dissipation coefficient is ignored. Based on the above assumptions, the enthalpy-porous medium model is used to establish a two-dimensional unsteady-state heat transfer model. The control equation is as follows:

[0085] Energy equation:

[0086]

[0087] Where ρ is the PCM density, H is the PCM material enthalpy, is the vector differential operator, k is the thermal conductivity;

[0088] Continuity equation:

[0089]

[0090] In the formula, is the velocity vector;

[0091] Momentum equation:

[0092]

[0093] Where t is time; ρ is density; p is pressure; μ is dynamic viscosity; ξ is thermal expansion coefficient; T re f is the reference temperature, the source term The damping term of Darcy's law can be expressed as:

[0094]

[0095] The liquid phase rate at different times is expressed as follows:

[0096]

[0097] Where T solid Solid phase temperature, Tliquid is the PCM liquid temperature;

[0098] The total enthalpy consists of sensible enthalpy and latent enthalpy:

[0099]

[0100] ΔH=λL

[0101] H=λL+h

[0102] Where ΔH is the latent heat enthalpy and h is the sensible heat enthalpy.

[0103] In step S1, the physical model established includes the physical property parameters of the composite phase change material. The physical property parameters of the composite phase change material are calculated by the classical formula of nanoparticle mixture, and the physical property equation is as follows:

[0104] The density and specific heat of the composite phase change material are shown in the following formula:

[0105] ρ nf =(1-φ ns )ρ f +φ ns ρ ns

[0106] (ρc p ) nf =(1-φ ns )(ρc p ) f +φ ns (ρc p ) ns

[0107] The effective dynamic viscosity of the composite phase change material is expressed by the Brinkman equation:

[0108]

[0109] The thermal conductivity of the composite phase change material is expressed by the Brinkman equation:

[0110]

[0111] Where B is the Boltzmann constant (B = 1.3807 × 10-23 J / K), and γ is a variable representing the volume fraction of nanoparticles expressed as:

[0112] γ=8.4407(100φ ns ) -1.07304 (0.01<φ ns <0.1)

[0113] The empirical function f(T,φ) is as follows:

[0114]

[0115] The heat storage rate of the phase change material when melting while absorbing heat is expressed as:

[0116]

[0117] The heat storage density of the phase change material when it melts while absorbing heat is expressed as:

[0118]

[0119] Furthermore, in step S2, the specific contents of using the two-dimensional model to perform two-dimensional simulation analysis on the physical model include: using MESH software to mesh the latent heat system, using computational fluid dynamics software ANSYS Fluent to perform numerical calculations, and in the process of using computational fluid dynamics software ANSYS Fluent to perform numerical calculations, selecting the Solidification / Melting model in the Fluent software for solving, and using the PISO algorithm to deal with the coupling problem of the pressure field and the velocity field, using the PRESTO! algorithm for pressure correction, and setting the relaxation factors of momentum, pressure term, energy term and liquid phase velocity to 0.7, 0.2, 1.0 and 0.9 respectively. The relative residuals of the energy equation and momentum equation are set to be less than 10 -6 , the relative residual of the continuity equation is set to be less than 10 -4 .

[0120] Furthermore, when using MESH software to mesh the latent heat system, Figure 3 As shown in Figure 2, grid independence and time step independence were verified for four different grid numbers (17685, 38297, 42051, and 66204) and four different time steps (0.005s, 0.01s, 0.05s, and 0.01s). Figure 3 (a) It can be found that when the number of grids increases from 38297 to 42051, the average temperature change of PCM decreases from 318.608K to 318.854K after 100 seconds, and the change is 0.078%. Figure 3 (b) shows that the relative deviation of the average PCM temperature within 100 seconds is very small (less than 0.03%) when the time step is between 0.01s and 0.005s. Therefore, it can be considered that the numerical simulation results have appropriate accuracy when the time step is 0.01s and the number of grids is 38297. Further increasing the number of grids or reducing the time step has little effect on the results.

[0121] Furthermore, in order to verify the accuracy of numerical simulation and improve work efficiency, the technical solution directly uses the experimental data in the prior art for comparative analysis with the numerical simulation results (the experimental data in the prior art here use the experimental data of Mat et al., specifically Sohif Mat, Abduljalil A. Al-Abidi, K. Sopian, MY Sulaiman, Abdulrahman Th Mohammad. Enhance heat transfer for PCM melting in triplex tube with internal–external fins [J]. Energy Conversion and Management, 2013; 74: 223–36.), sets the boundary conditions and initial conditions of the numerical model to be consistent with the parameters such as the fluid temperature and ambient temperature in the experiment, and uses a model of the same size, replacing the PCM material from RT55 to RT82 used in the experiment. Figure 4 (a) and (b) show the fitting results of PCM melting and solidification experiments and simulations, respectively. The simulation curves are highly consistent with the experimental curves, with a maximum deviation of only 1.42%. Since the insulation cotton used in the experiment cannot fully guarantee the heat exchange between the outer tube and the environment, the thermal boundary conditions of the tube wall are not completely insulated, resulting in some heat dissipation into the environment. Considering the limitations of the experimental conditions, the numerical model in this paper is reliable.

[0122] Furthermore, the mutual verification between simulation results and experimental results shows that:

[0123] 1. Comparative analysis between tree-shaped fins and traditional fins;

[0124] in, Figure 5 (a) shows the solidification cloud diagram of the traditional fin system and the tree-shaped fin system at different times. The left side is the liquid phase cloud diagram and the right side is the temperature cloud diagram. The area of ​​the traditional fin is the same as that of the tree-shaped fin, but due to the fractal structure of the tree-shaped fin, it has better heat transfer performance. The tree-shaped fin studied in this part uses a design with an angle θ of 90 degrees. Figure 5 (a) It can be observed that the tree-shaped fins show significant heat transfer effects at different time periods. At 400 seconds, most of the PCM in the tree-shaped fin system has solidified, while half of it in the traditional fin system has not yet completely solidified. The temperature cloud diagram also shows that at 400 seconds, the area of ​​the green area (high temperature area) in the traditional fin system is much larger than that in the tree-shaped fin system. In addition, from Figure 5From the PCM average temperature and liquid phase rate change curves in (b) and (c), it can be seen that the solidification rate of the tree-shaped fins is much greater than that of the traditional fins, and its complete solidification time is reduced by 37.96% compared with the traditional fins. Under the same fin volume fraction, the heat transfer capacity of the tree-shaped fins is significantly better than that of the traditional fins. At 500 seconds, the average temperature of the PCM under the tree-shaped fins is 10.22K lower than the average temperature under the traditional fins. The main reason for this phenomenon is that the tree-shaped fins have many branch fins in the fractal structure based on the Fibonacci sequence. These branch fins have good heat transfer capacity and can transfer more heat to areas that traditional fins cannot reach.

[0125] 2. The influence of different fin bifurcation angles on TTES heat transfer;

[0126] in, Figures 6 to 9 The figure shows the TTES liquid phase distribution cloud diagram and temperature distribution cloud diagram under different fin angles. This technical solution keeps the fin length and fin thickness unchanged, that is, the volume fraction remains unchanged, and only changes the fin angle θ to perform a single factor analysis on the TTES melting performance. The fin angles of 70°, 80°, 90°, 100° and 110° were selected for research. Figure 6 It can be seen that as the bifurcation angle of the fin increases, the solidification effect of the latent heat system becomes better. This is because as the bifurcation angle increases, the "dead zone" where the PCM is difficult to transfer heat can more effectively contact the fin. At 200 seconds, in the liquid phase cloud diagram with a bifurcation angle of 110 degrees, the solidified area is significantly larger than the fin with a bifurcation angle of 70 to 100 degrees, and the green high-temperature area is also smaller than the former. Figure 7 and Figure 8 From the liquid phase rate and PCM average temperature rate curves, it can be found that the rate of the fin with a bifurcation angle of 110 degrees is the fastest, and the cooling rate is obviously faster than that of the fins with other bifurcation angles. Fig. 9 It can be analyzed from the comprehensive heat transfer effect diagram that when the fin bifurcation angle increases from 70° to 110°, at 500 seconds, the average PCM temperature decreases by 2.97K, the complete solidification time decreases by 16.82%, the heat release increases by 28.09kJ, and the heat storage density and heat storage rate also increase steadily. These data further illustrate that the larger the fin bifurcation angle, the better the heat transfer effect. This is because the larger the bifurcation angle, the more obvious its fractal effect, but it cannot be greater than 110 degrees. After exceeding this value, the thickness of the system sub-fins will not be able to be manufactured, and its fins are too thin. Therefore, subsequent research will select a fin bifurcation angle of 110 degrees for in-depth analysis.

[0127] 3. Effects of different nanoparticles on TTES heat transfer;

[0128] Among them, metal nanoparticles have a high thermal conductivity, and mixing them with the working fluid can improve the thermal conductivity of PCM. Here, the focus is on the effect of four nanoparticles, copper, titanium dioxide, copper oxide and aluminum oxide, on the heat transfer performance of TTES at a bifurcation angle of 110 degrees and a volume fraction of 5%. Fig.10 and Fig.11 As shown in the figure, the new phase change material formed by mixing 5% volume fraction of aluminum oxide with PCM has the fastest liquid phase rate and PCM average temperature cooling rate. From Table 2, it can be found that although copper has the largest thermal conductivity and the thermal conductivity is also the largest after mixing with PCM, its specific heat capacity is the lowest, which will reduce the stored heat and temperature rise, indicating that there is a game relationship between specific heat capacity and thermal conductivity. Figure 7 It can be seen that the new modified phase change material formed by mixing 5% volume of aluminum oxide with PCM has the best heat transfer and heat storage effect. Fig.12 It can be found that compared with 5% copper, 5% alumina at 500 seconds, the average temperature of PCM decreased by 0.64K, the complete solidification time decreased by 21.25%, the heat release increased by 20.07kJ, and the heat storage density and heat storage rate also increased steadily. It can be seen that nanoparticles are not always effective in the heat storage of PCM. This is because although the addition of nanoparticles increases the heat transfer coefficient, it also reduces the volume of PCM, that is, it reduces the mass of PCM, thereby reducing the latent heat value and specific heat capacity, and ultimately affects the heat storage. Therefore, after selecting appropriate nanoparticles to add, it is necessary to further determine the game relationship between various heat storage characteristics.

[0129] 4. The influence of tube wall temperature on TTES heat transfer;

[0130] Among them, this part mainly analyzes the influence of different tube wall temperatures on the heat transfer performance of TTES under the conditions of a bifurcation angle of 110 degrees and a volume fraction of Al2O3 nanoparticles of 5%. Here, the temperature of HTF is simplified to the wall temperature, and five temperatures of 283K, 288K, 293K, 298K and 303K are set for research. The tube wall temperature refers to the temperature of the entire inner tube and the outer tube of the three-tube shell. It can be seen from the liquid phase ratio and PCM temperature change curves that with the increase of the tube wall temperature, the liquid phase ratio and the average PCM temperature also increase. This is because a higher temperature difference can improve the heat transfer efficiency, so that the fin temperature and wall temperature can be quickly transferred to the PCM, thereby realizing the temperature rise of the phase change material in a shorter time. Fig.13 It can be observed that when the temperature is lower than 293K, the liquid phase rate changes less and less when the HTF temperature is increased by 5K. This shows that when the wall temperature exceeds 293K, the effect of further increasing the wall temperature gradually weakens. Fig.14It can also be clearly seen that the average PCM temperature decreases significantly for every 5K decrease in HTF temperature. At 500 seconds, the HTF temperature drops from 303K to 283K, and the average PCM temperature drops from 309.39K to 288.95K, a decrease of 6.61%. This shows that the increase in wall temperature can effectively improve the heat transfer performance. The increase in the temperature difference between the wall temperature and the PCM is conducive to the improvement of the PCM heat release rate, increasing the heat release during the solidification process of the phase change material, thereby shortening the solidification time. Therefore, the recommended fluid temperature is around 293K.

[0131] 5. The influence of fin material on TTES heat transfer;

[0132] Among them, the bifurcation angle is 110 degrees, and the phase change material is a mixture of aluminum oxide and RT55 with a volume fraction of 5%. Since the fins are crucial to the heat transfer performance of TTES, three common metal materials, copper fins, iron fins and aluminum fins, are selected as the sleeve fin materials. The thermal conductivity of the three materials is shown in Table 3:

[0133] Table 3. Physical properties of various fin materials

[0134]

[0135] They are 16.27W / (m·K), 387.6W / (m·K) and 202.4W / (m·K) respectively. Fig.15 It can be seen that with the increase of thermal conductivity, the solidification rate of PCM is also faster. The PCM solidification rate of copper fins and aluminum fins is significantly higher than that of steel fins. This is because the thermal conductivity of copper fins and aluminum fins is similar, so their solidification effects are also similar, and their temperature rate and liquid fraction rate curves almost overlap. In addition, it can be found that the solidification time of copper fins is the shortest, which is 615 seconds, which is 56.26% less than that of iron fins; the average temperature of PCM at the solidification time of 500 seconds is 299.611K, which is 12.83K lower than that of iron fins. Therefore, the higher the thermal conductivity of the fins, the better the TTES heat storage effect, which proves the feasibility of copper materials as fins. In summary, this paper analyzes the solidification characteristics of the nanoparticle three-tube vertical latent heat system based on the Fibonacci sequence fractal tree fins, and mainly studies the effects of different fin bifurcation angles, different nanoparticle types, wall temperature and fin materials on liquid distribution, temperature distribution, solidification characteristics and heat release. The conclusions are as follows:

[0136] (1) Compared with traditional fins, the tree-shaped fractal fins designed based on the Fibonacci sequence can significantly enhance the heat transfer performance of TTES. At 500 seconds, the average temperature of the PCM under the tree-shaped fins was 10.22K lower than that of the traditional fins, and the complete solidification time was reduced by 37.96%.

[0137] (2) The larger the fin bifurcation angle, the better the heat transfer effect. When the fin bifurcation angle increases from 70° to 110°, at 500 seconds, the average PCM temperature decreases by 2.97K, the complete solidification time decreases by 16.82%, and the heat release increases by 28.09kJ. When the fin bifurcation angle is 110 degrees, the heat transfer performance is the best.

[0138] (3) By comparing the various nanoparticles, it was found that the mixture of Al2O3 and RT55 at a volume fraction of 5% had the best thermal performance as a phase change material. The increase in wall temperature can significantly enhance the heat transfer efficiency, and it is recommended that the wall temperature be around 293K to obtain better data results.

[0139] (4) The solidification time of copper fins is the shortest, which is 615 seconds, which is 56.26% shorter than that of iron fins. The higher the thermal conductivity of the fin material, the better the TTES heat storage effect.

[0140] What is disclosed above is only a preferred embodiment of the present invention, and it certainly cannot be used to limit the scope of rights of the present invention. Ordinary technicians in this field can understand that all or part of the processes of the above embodiment and equivalent changes made according to the claims of the present invention still fall within the scope of the invention.

Claims

1. An experimental method for a composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins, characterized in that: The steps include: S1: Establish the physical model of nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins; S2: Use a two-dimensional model to perform two-dimensional simulation analysis on the physical model, simulate the melting and solidification process of PCM, and analyze the heat transfer performance and energy storage efficiency of the system; S3: Build an experimental device for a nanoparticle three-tube vertical latent heat system based on Fibonacci fractal tree-shaped fins, select appropriate PCM and nanoparticles for mixing, prepare composite phase change materials, and inject them into the system, adjust the parameters of the heat source and cooling system, simulate different working conditions, and record the melting and solidification process of PCM; S4: Compare the simulation results with the experimental results, adjust the parameters of the simulation model to improve the accuracy of the simulation results, analyze the effects of different fin bifurcation angles, nanoparticle types, wall temperatures, and fin materials on the heat transfer performance and energy storage efficiency of the system, and provide guidance for the optimal design of the system.

2. The test method of composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins according to claim 1, characterized in that: In step S1, the inner tube diameter Ф1 of the three-tube vertical latent heat system is 20 mm, the outer tube diameter Ф2 is 60 mm, and the wall thickness is 1 mm. The fin structure of the three-tube vertical latent heat system adopts a golden ratio tree-shaped fin. The fin structure is provided with four inner and outer staggered fins. The lengths of the fins are composed of the Fibonacci sequence 8, 5, 3, 2, and 1 in sequence. The middle bifurcation angle θ is used as a control variable for fractal design.

3. The test method of composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins as claimed in claim 1, characterized in that: In step S1, before establishing the physical model, the enthalpy porosity method is used to calculate the PCM phase change process in the TTES unit, and the control equation is as follows: Energy equation: Where ρ is the PCM density, H is the PCM material enthalpy, is the vector differential operator, k is the thermal conductivity; Continuity equation: In the formula, is the velocity vector; Momentum equation: Where, t is time; ρ is density; p is pressure; μ is dynamic viscosity; ξ is thermal expansion coefficient; T ref is the reference temperature, the source term The damping term of Darcy's law can be expressed as: The liquid phase rate at different times is expressed as follows: Where T solid Solid phase temperature, T liquid is the PCM liquid temperature; The total enthalpy consists of sensible enthalpy and latent enthalpy: ΔH=λL H=λL+h Where ΔH is the latent heat enthalpy and h is the sensible heat enthalpy.

4. The test method of composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins as claimed in claim 3, characterized in that: In step S1, the physical model established includes the physical property parameters of the composite phase change material. The physical property parameters of the composite phase change material are calculated by the classical formula of nanoparticle mixture, and the physical property equation is as follows: The density and specific heat of the composite phase change material are shown in the following formula: r nf =(1-φ ns )r f +φ ns r ns (ρc p ) nf =(1-φ ns )(ρc p ) f +φ ns (ρc p ) ns The effective dynamic viscosity of the composite phase change material is expressed by the Brinkman equation: The thermal conductivity of the composite phase change material is expressed by the Brinkman equation: Where B is the Boltzmann constant (B = 1.3807 × 10-23 J / K), and γ is a variable representing the volume fraction of nanoparticles expressed as: γ=8.4407(100φ ns ) -1.07304 (0.01<φ ns <0.1) The empirical function f(T,φ) is as follows: The heat storage rate of the phase change material when melting while absorbing heat is expressed as: The heat storage density of the phase change material when it melts while absorbing heat is expressed as:

5. The test method of composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins as claimed in claim 1, characterized in that: In step S2, when the two-dimensional model is used to perform two-dimensional simulation analysis on the physical model, the HTF temperature is simplified to the pipe wall temperature, and the PCM is melted by heat transfer between the inner pipe and the outer pipe. The initial state of the PCM is in a melting state at 363K, and the initial temperature of the PCM is: There is a coupled boundary condition between the fin and the PCM, there is no boundary velocity slip, and the thermal conditions are as follows:

6. The test method of composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins as claimed in claim 5, characterized in that: In step S2, the specific contents of using the two-dimensional model to perform two-dimensional simulation analysis on the physical model include: using MESH software to perform mesh division on the latent heat system, and using computational fluid dynamics software ANSYS Fluent to perform numerical calculations.

7. The test method of composite nanoparticle latent heat system based on Fibonacci fractal tree-shaped fins as claimed in claim 6, characterized in that: In step S2, in the process of numerical calculation using computational fluid dynamics software ANSYS Fluent, the Solidification / Melting model in the Fluent software is selected for solution, and the PISO algorithm is used to process the coupling problem of the pressure field and the velocity field, and the PRESTO! algorithm is used for pressure correction.

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