Indoor heating heat source distribution optimization design method and layout

Abstract

This invention proposes an optimized design method and layout for indoor heating heat source distribution. The method first determines the optimal total number of heat sources, assuming that the length of each individual heat source is equal and the distances between adjacent heat sources are also equal. This results in the optimal length of each individual heat source. Then, while maintaining the obtained length of each individual heat source, the distances between adjacent heat sources are changed, and the total number of heat sources is adjusted accordingly. This further reduces costs and energy consumption, resulting in the best overall solution. This invention ensures that the indoor heating effect is essentially the same as that of a fully heated floor, while significantly reducing costs and energy consumption.

Description

Technical Field

[0001] This invention relates to the field of heating design, specifically to a method and layout for optimizing the distribution of indoor heating heat sources. Background Technology

[0002] Underfloor heating is a major method of indoor heating and can be used for heating residential buildings. Figure 1 It can also be used for aircraft cabin heating. Figure 2 Saving costs and reducing energy consumption while ensuring indoor heating requirements are met has always been the goal of optimizing the distribution of indoor heating heat sources. Summary of the Invention

[0003] To address the need for optimized design of indoor heating heat source distribution, this invention proposes an optimized design method for indoor heating heat source distribution based on theoretical analysis and numerical simulation of natural convection heat transfer, and obtains corresponding layout results. Under the premise of ensuring heating requirements, it significantly saves heat source costs and reduces energy consumption.

[0004] The technical solution of this invention is as follows:

[0005] A method for optimizing the distribution of indoor heating heat sources includes the following steps:

[0006] Step 1: Establish a simplified two-dimensional square cavity model for indoor heating; the bottom edge of the model adopts a discrete heat source distribution method; the design parameters are the length of a single heat source and the distance between two adjacent heat sources.

[0007] Step 2: Given that the length of each individual unit from the heat source is equal, and the distances between any two adjacent units from the heat source are also equal, with both length and distance being equal, adjust the total number of units from the heat source. For each number of heat sources, numerical simulations of natural convection heat transfer were used to obtain the heating effect within the cavity. Combining the heating effect with the corresponding heat source costs and energy consumption for each number of heat sources, the optimal number of heat sources for the preliminary overall solution was determined. and the corresponding length of a single distance from the heat source ;

[0008] Step 3: Maintain the single distance from the heat source obtained in Step 2. Without changing the distance between adjacent heat sources, the distance between adjacent heat sources is further increased, and the total number of heat sources is adjusted accordingly. For each case of adjacent distance from the heat source, numerical simulation of natural convection heat transfer is used to obtain the heating effect in the cavity. Combining the heating effect of each case of adjacent distance from the heat source with the corresponding heat source cost and energy consumption, the final optimal solution with the best overall effect is obtained.

[0009] Furthermore, in the aforementioned square cavity model, the side length is a dimensionless quantity, taking... The top and one side edges of the model are adiabatic boundaries, and the bottom is a heat source serving as a high-temperature boundary. The temperature of the constant-temperature heat source is set. The other side has a low-temperature boundary, with the temperature set to ambient or outdoor temperature. .

[0010] Furthermore, in steps 2 and 3, when comprehensively considering the heating effect and the corresponding heat source cost and energy consumption, a weighted method is adopted, assigning weights to the heating effect, heat source cost and energy consumption respectively, and taking the final weighted result.

[0011] Furthermore, in step 2, the number of heat sources corresponding to the preliminary optimal solution is obtained. and the corresponding dimensionless length of a single unit from the heat source .

[0012] Furthermore, in step 3, the dimensionless length of a single unit from the heat dissipation source corresponding to the final optimal solution with the best overall effect is obtained. dimensionless distance between adjacent heat sources .

[0013] Furthermore, the indoor heating adopts a bottom-mounted heating method, with the total length of the bottom surface of the heating space as the characteristic length. The bottom surface is 34 units away from the heat source, and the dimensionless distance between each unit and the heat source is... dimensionless distance from the heat source .

[0014] Beneficial effects

[0015] This invention, based on research into the flow and heat transfer of natural convection within indoor spaces or cabins, proposes an optimized design method and layout for indoor heating heat source distribution. The design method first determines the optimal total number of heat sources by ensuring that the length of each individual heat source is equal and that the distances between adjacent heat sources are also equidistant. Then, while maintaining the obtained length of each individual heat source, the distances between adjacent heat sources are changed, and the total number of heat sources is adjusted accordingly to further reduce costs and energy consumption, resulting in the optimal solution with the best overall effect. This invention ensures that the indoor heating effect is essentially the same as that of a fully heated floor, while significantly reducing costs and energy consumption.

[0016] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0017] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0018] Figure 1 Schematic diagram of a simplified model of residential indoor heating;

[0019] Figure 2 Schematic diagram of a simplified model of aircraft cabin heating;

[0020] Figure 3 Unoptimized heat source distribution;

[0021] Figure 4 Optimized heat dissipation distribution method;

[0022] Figure 5 Temperature distribution along different longitudinal axes ;

[0023] Figure 6 Nusselt numbers for different heat source distribution patterns ;

[0024] Figure 7 Isotherms for different heat source distribution patterns; ;

[0025] Figure 8 Temperature distribution along different longitudinal axes ;

[0026] Figure 9 Nusselt numbers for different heat source distribution patterns ;

[0027] Figure 10 Isotherms for different heat source distribution patterns; ; ; ; ; Partial comparison images;

[0028] Figure 11 Simplified model and boundary conditions of natural convection in a classic square cavity;

[0029] Figure 12 Simplified model and boundary conditions of natural convection in indoor heating with suspended heat source;

[0030] Figure 13 : The velocity component in the x-direction of the longitudinal centerline. Detailed Implementation

[0031] The embodiments of the present invention are described in detail below. These embodiments are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0032] like Figure 1 and Figure 2 As shown, underfloor heating is used for heating residential buildings and aircraft cabins. A simplified model can be established, in which the black line represents the adiabatic boundary, the red line represents the heat source, and the green line represents the low-temperature boundary of the environment in direct contact.

[0033] In order to optimize the heat source distribution strategy in indoor or cabin environments, this invention uses a simplified model and numerical simulation of natural convection heat transfer to optimize the design of indoor heating heat source distribution strategy. By using discrete heat source distribution, costs are saved and energy consumption is reduced while ensuring indoor heating requirements.

[0034] Natural convection is a classic problem in aerodynamics, and it has significant reference value and theoretical guidance for practical engineering applications in the electrical and electronics industry, aerospace industry, civil heating, and nuclear energy utilization. This invention equates the optimization of heat source distribution strategies within an indoor space or cabin to the study of natural convection heat transfer within a cavity, such as... Figure 3 and Figure 4 As shown, Figure 3 This demonstrates the heat source distribution before optimization, showing uniform heating across the entire bottom edge. Figure 4 The optimized discrete heat source distribution method is shown, in which and These are the constant temperature heat source temperature (high temperature boundary) and the ambient temperature or outdoor temperature (low temperature boundary), respectively. For Figure 4 The discrete heat source distribution shown in the diagram indicates that two main factors influence the flow heat transfer characteristics of this two-dimensional flow field: the length of each individual heat source from the heat source. and the distance between two adjacent heat sources .in This is the sequence number of the distance from the heat source. This represents the total number of points away from the heat source. In a three-dimensional case, these two factors can be expanded to the area of ​​each individual point away from the heat source. and the distance between the two heat sources , where 1 represents the unit span perpendicular to the paper.

[0035] Numerical simulations of heat transfer through natural convection flow were performed, using an unoptimized heat source distribution ( Figure 3 The heating effect (temperature distribution, Nusselt number, isotherms) of the heat source is the basic requirement for heating in this application. The heating effect after optimization (distribution method of heat source) is compared and analyzed to obtain the heat source distribution method that can reduce cost and energy consumption in this application.

[0036] The specific research process is as follows:

[0037] First, we define the total length of the heat source. If it corresponds to three-dimensional flow, then it is the total area of ​​the heat source. 1 represents the unit span perpendicular to the paper surface; obviously, The smaller the heat source, the lower the cost. The characteristic length, i.e., the side length of the square cavity, is used here as a dimensionless quantity for ease of study. It is not difficult to see that when the heat source distribution is not optimized, there are... (The heat source covers the entire bottom edge).

[0038] We first limit the length of a single distance from the heat source. They are of equal length, and the distances between two adjacent points from the heat source are... Given that all points are equidistant, find the optimal total number of points from the heat source. .

[0039] From an intuitive point of view, The larger the size, the closer the heating effect is to the unoptimized state where the entire bottom edge is heated. However, considering the overall heating effect, cost reduction, and energy consumption, Larger isn't always better. We specify the distance from the heat source. Numerical simulations of heat transfer during natural convection were performed, and the results are as follows: Figure 5 , Figure 6 , Figure 7 As shown, through analysis of the numerical simulation results, a conclusion can be obtained. The value corresponds to the best overall effect in terms of heating, cost reduction, and energy consumption. As can be seen from the graph, when... As the value gradually increases from 1 to 50, the indoor heating effect is essentially equivalent to the heating effect when the entire bottom edge is heated. And when... As the size increases further, the heating effect will improve further, becoming closer to the heating effect when the entire bottom edge is heated, but the change is small and can be ignored. For example, when... When the value is 100, the heating effect is improved by approximately 2%. Considering that... Considering the increasing processing and installation costs and difficulties associated with the heat source, it is generally determined that a total of 50 heat sources results in the best overall effect. This means the heating effect is essentially equivalent to heating the entire bottom edge, while reducing heat source costs and energy consumption by 50%, compared to an unoptimized heat source distribution strategy. Figure 3 ), total length of heat source ( ) is when not optimized ( The cost of heating is half of that of heat source, while the processing and installation costs and difficulty are moderate. Mathematically speaking, a comprehensive judgment can be made by weighting the factors of heating effect, heat source cost, and energy consumption, and then taking the final weighted result.

[0040] In the previous step, through numerical simulation and analysis, we obtained the total number of heat dissipation sources. The value is 50, at which point there is Next, while ensuring the dimensionless length of a single distance from the heat source... Without changing the distance from the heat source Gradually increase the number of heat sinks (corresponding to changes in the total number of heat sinks) to further reduce costs and energy consumption. This was considered separately. Then the corresponding distance from the total number of heat sources The corresponding dimensionless total lengths of the heat source are respectively It is obvious that when At this time, the heat source cost and energy consumption are the lowest, only one-fifth of the unoptimized one. ).like Figure 8 , Figure 9 and Figure 10 As shown, with Increase, although the Nusselt number is large ( Figure 9 The convective heat transfer is very intense. However, the heating effect at this time is relatively... It decreased by 14% ( Figure 8 and Figure 10 When the dimensionless spacing is... At that time, the heating effect decreased by only 6.7%, and the cost and energy consumption were 34% of the unoptimized result. Therefore, considering heating effect, cost, and energy consumption, this invention uses 34 heat dissipation sources, with a dimensionless length of [missing information - likely a unit of measurement]. The heat sources are evenly spaced. When the heating effect is approximately equivalent to heating the entire bottom edge, the cost and energy consumption are reduced by 66%. Alternatively, a weighted approach can be used, assigning weights to the heating effect, heat source cost, and energy consumption, and then taking the final weighted result.

[0041] Based on the above numerical simulation studies and analyses, this invention takes the natural convection of a simplified two-dimensional square cavity as the research object, and analyzes the flow and heat transfer characteristics under the influence of different total numbers of heat sources, the length of a single heat source, and the distance between heat sources. An optimal heat source distribution scheme for indoor or cabin environments is proposed: The results show that the optimal distribution scheme corresponds to the side length of the square cavity... When the total number of heat sources is 34, the dimensionless length of a single heat source is... dimensionless distance from the heat source At that time, the heating effect of the room or cabin is basically equivalent to the heating effect of heating the entire bottom edge (only reduced by 6.7%), but the cost and energy consumption are reduced by 66%.

[0042] The accuracy of the above analysis depends on the accuracy of the numerical simulation. The applicant's research group has long been engaged in the study of natural convection flow heat transfer, and has formed a complete research system that combines numerical simulation, theoretical analysis, and optimization design of heat source distribution strategies.

[0043] 1. Possesses high-efficiency and high-precision numerical simulation algorithms with independent intellectual property rights and ample computing equipment;

[0044] 2. A robust method for refining complex shape meshes (tree mesh);

[0045] 3. High-precision complex curve surface boundary processing format;

[0046] 4. A complete theoretical system for analyzing the heat transfer characteristics of natural convection has been established (Nusser number analysis method, isotherm and stream function display, velocity-type and temperature-type analysis methods, flow field topology analysis methods, etc.).

[0047] 5. Possesses reliable flow field visualization processing technology and analysis methods.

[0048] The applicant's research group has conducted extensive research on natural convection, such as the natural convection in a classic square cavity (e.g. Figure 11 As shown, the heat source is placed on the entire left boundary, while the right side is entirely a low-temperature boundary) and the indoor heating uses natural convection with a suspended heat source (such as...). Figure 12 As shown, the local heat source is placed on the left boundary, and the local low temperature boundary is placed on the right boundary. The computational grid and method used for the numerical simulation work in this application can guarantee the provision of reliable numerical calculation results for the numerical simulation work involved in this application.

[0049] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the present invention.

Claims

1. A method for optimizing the distribution of indoor heating heat sources, characterized in that: Includes the following steps: Step 1: Establish a simplified two-dimensional square cavity model for indoor heating; the bottom edge of the model adopts a discrete heat source distribution; the design parameters are the length of a single heat source and the distance between two adjacent heat sources; in the square cavity model, the side length is a dimensionless quantity, taken as... The top and one side edges of the model are adiabatic boundaries, and the bottom is a heat source serving as a high-temperature boundary. The temperature of the constant-temperature heat source is set. The other side has a low-temperature boundary, with the temperature set to ambient or outdoor temperature. ; Step 2: Given that the length of each individual unit from the heat source is equal, and the distances between any two adjacent units from the heat source are also equal, with both length and distance being equal, adjust the total number of units from the heat source. For each number of heat sources, numerical simulations of natural convection heat transfer were used to obtain the heating effect within the cavity. Combining the heating effect with the corresponding heat source costs and energy consumption for each number of heat sources, the optimal number of heat sources for the preliminary overall solution was determined. and the corresponding length of a single distance from the heat source ; Step 3: Maintain the single distance from the heat source obtained in Step 2. Without changing the distance between adjacent heat sources, the distance between adjacent heat sources is further increased, and the total number of heat sources is adjusted accordingly. For each case of adjacent distance from the heat source, numerical simulation of natural convection heat transfer is used to obtain the heating effect in the cavity. Combining the heating effect of each case of adjacent distance from the heat source with the corresponding heat source cost and energy consumption, the final optimal solution with the best overall effect is obtained.

2. The indoor heating heat source distribution optimization design method according to claim 1, characterized in that: In steps 2 and 3, when comprehensively considering the heating effect and the corresponding heat source cost and energy consumption, a weighted method is adopted, assigning weights to the heating effect, heat source cost and energy consumption respectively, and taking the final weighted result.

3. The indoor heating heat source distribution optimization design method according to claim 1, characterized in that: In step 2, the number of heat sources corresponding to the preliminary optimal solution is obtained. =50 and the corresponding dimensionless length of a single unit from the heat source =0.

01.

4. The indoor heating heat source distribution optimization design method according to claim 3, characterized in that: In step 3, the dimensionless length of a single unit from the heat source corresponding to the final optimal solution is obtained. =0.01, dimensionless distance between adjacent heat dissipation sources =0.

02.

5. An indoor heating heat source distribution layout designed using the method described in claim 1, characterized in that: The indoor heating system adopts a bottom-mounted heating method, with the total length of the bottom surface of the heated space as the characteristic length. The bottom surface is 34 units away from the heat source, and the dimensionless distance between each unit and the heat source is... dimensionless distance from the heat source .

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