Flue gas heat exchanger runner coupling optimization method considering ash deposition resistance and efficient heat transfer
By optimizing the flow channel design of the heat exchanger and combining CFD software and neural network algorithms, the problem of balancing heat transfer efficiency and anti-dust accumulation performance in traditional designs has been solved, achieving a comprehensive improvement in both high-efficiency heat transfer and anti-dust accumulation, while reducing costs and time.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUZHOU UNIVERSITY
- Filing Date
- 2026-02-03
- Publication Date
- 2026-05-26
AI Technical Summary
Existing heat exchanger designs fail to effectively combine heat transfer efficiency with anti-ash accumulation performance, making it difficult to balance heat transfer performance and flow performance, which affects the long-term stable operation and economy of waste heat recovery systems.
By combining CFD software and neural networks with genetic algorithms, a coupled optimization model for the high-temperature and low-temperature sides is constructed by optimizing design variables such as weld joint diameter, inner flow channel height, outer flow channel height, and pitch ratio, thereby achieving a comprehensive improvement in heat transfer performance, flow performance, and dust accumulation resistance.
It improves the heat transfer efficiency and dust accumulation resistance of heat exchangers, reduces manufacturing and operating costs, shortens the design cycle, and achieves efficient, low-consumption, and long-cycle operation.
Smart Images
Figure CN122088367A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of heat exchanger optimization technology, specifically to a flue gas heat exchanger flow channel coupling optimization method that balances anti-ash accumulation and efficient heat transfer. Background Technology
[0002] As the core energy transfer unit of a waste heat recovery system, the performance of the heat exchanger directly determines the system's energy utilization efficiency and operational economy, playing a crucial supporting role in energy conservation and emission reduction in the industrial sector and achieving the "dual carbon" target. However, existing heat exchanger design technologies still face two major technical bottlenecks that urgently need to be overcome: First, traditional design methods often focus on optimizing heat transfer efficiency and flow resistance in a single dimension, failing to consider the ash formation mechanism in conjunction with the heat exchanger's structural design, and neglecting the significant impact of wall ash deposition on heat transfer performance during actual operation. The accumulation of ash significantly increases thermal resistance and reduces the flow cross-sectional area, leading not only to a substantial decrease in the actual operating efficiency of the heat exchanger compared to the design value, but also increasing power consumption and maintenance costs, seriously affecting the long-term stable operation of the waste heat recovery system. Second, existing structural optimization strategies often adopt independent optimization modes for the high-temperature or low-temperature side flow channels, lacking comprehensive control over the synergistic performance of both flow channels and the establishment of a coupled correlation model for heat transfer characteristics, flow resistance, and anti-ash accumulation performance. This makes it difficult to reconcile the inherent contradiction between improving anti-ash accumulation performance and enhancing heat transfer and flow properties, severely limiting further breakthroughs in the overall performance of heat exchangers and failing to meet the urgent needs of industrial waste heat and flue gas recovery for efficient, low-consumption, and long-cycle operation equipment. Therefore, developing a flow channel synergistic optimization design method that can simultaneously improve anti-ash accumulation capability and overall heat transfer and flow performance is of great significance for the technological upgrading of industrial waste heat and flue gas recovery systems. Summary of the Invention
[0003] The purpose of this invention is to provide a flue gas heat exchanger flow channel coupling optimization method that balances anti-ash accumulation and high-efficiency heat transfer. While ensuring the heat transfer flow efficiency of the heat exchanger, it improves the anti-ash accumulation performance and balances the performance requirements of the high-temperature side and the low-temperature side.
[0004] In an embodiment of the present invention, a flue gas heat exchanger flow channel coupling optimization method that balances anti-ash accumulation and efficient heat transfer is provided, comprising:
[0005] Determine the performance indicators of the heat exchanger; select design variables based on the performance indicators; construct a sample space based on the design variables; obtain the basic performance indicator values based on the sample space;
[0006] Determine the optimization objective and design variables for the high-temperature side; obtain the set of optimization results for the high-temperature side based on the optimization objective and design variables.
[0007] The optimization objectives and design variables for the low-temperature side are determined based on the optimization results set for the high-temperature side; the optimization results set for the low-temperature side is obtained based on the optimization objectives and design variables for the low-temperature side.
[0008] The final optimization result set is obtained based on the high-temperature side optimization result set and the low-temperature side optimization result set; the optimized performance index value is obtained based on the final optimization result set.
[0009] The comprehensive performance value is obtained based on the basic performance index value and the optimized performance index value to verify the optimization results.
[0010] As a preferred embodiment of the present invention, obtaining the basic performance index value based on the sample space specifically involves: constructing a three-dimensional model of the basic heat exchanger based on the sample space, and using CFD software to perform numerical calculations of the performance index under multiple operating conditions on the three-dimensional model of the basic heat exchanger to obtain the basic performance index value.
[0011] The high-temperature side optimization result set is obtained based on the high-temperature side optimization objective and high-temperature side design variables as follows: the relationship between the high-temperature side optimization objective and the high-temperature side design variables is constructed based on the BP neural network, and the optimization problem is solved iteratively using a genetic algorithm to obtain the high-temperature side Pareto solution set; the high-temperature side optimization result set is obtained from the high-temperature side Pareto solution set using the TOPSIS method.
[0012] The specific steps for obtaining the low-temperature side optimization result set based on the low-temperature side optimization objective and low-temperature side design variables are as follows: A BP neural network is used to construct the relationship between the low-temperature side optimization objective and the low-temperature side design variables, and a genetic algorithm is used to iteratively solve the optimization problem to obtain the low-temperature side Pareto solution set; the TOPSIS method is then used to obtain the low-temperature side optimization result set from the low-temperature side Pareto solution set.
[0013] The optimized performance index values are obtained based on the final optimization result set as follows: a three-dimensional model of the optimized heat exchanger is constructed based on the final optimization result set, and CFD software is used to perform numerical calculations of the performance index values of the optimized heat exchanger under multiple operating conditions to obtain the optimized performance index values.
[0014] As a preferred embodiment of the present invention, the performance indicators of the heat exchanger determined include: Nusselt coefficient, friction resistance coefficient, and anti-ash accumulation factor;
[0015] The Nusselt coefficient is calculated using the following formula:
[0016]
[0017] in, For Nusselt coefficient, The surface heat transfer coefficient of the heat exchanger. For the hydraulic diameter of the computational domain, Thermal conductivity;
[0018] The friction resistance coefficient is calculated using the following formula:
[0019]
[0020] in, The coefficient of frictional resistance. For the hydraulic diameter of the computational domain, Pressure loss per unit length For the working fluid density, The average flow velocity of the working fluid. For the position of manager;
[0021] The anti-ash accumulation factor is calculated using the following formula:
[0022]
[0023] in, As an anti-ash accumulation factor, The critical thermal resistance for ash accumulation. This is the critical dust accumulation time.
[0024] As a preferred embodiment of the present invention, the selected design variables include: solder joint diameter, inner flow channel height, outer flow channel height, and pitch ratio.
[0025] As a preferred embodiment of the present invention, the sample space constructed based on design variables includes: a sample space of solder joint diameter of 3-12 mm; a sample space of inner flow channel height of 3-10 mm; a sample space of outer flow channel height of 10-25 mm; and a sample space of pitch ratio of 1-1.73.
[0026] As a preferred embodiment of the present invention, the determined high-temperature side optimization targets include: high-temperature side Nusselt coefficient, high-temperature side friction resistance coefficient, and anti-dust accumulation factor;
[0027] The determined high-temperature side design variables include: weld point diameter, inner flow channel height, outer flow channel height, and pitch ratio;
[0028] The relationship between the constructed high-temperature side optimization objective and the high-temperature side design variables is as follows:
[0029]
[0030] in, The high-temperature side Nusselt coefficient, The coefficient of friction resistance on the high-temperature side. As an anti-ash accumulation factor, The diameter of the solder joint. The height of the inner flow channel. The height of the outer flow channel. Pitch ratio;
[0031] The set of optimization results for the high-temperature side is represented by the following formula:
[0032]
[0033] in, This is a set of optimization results for the high-temperature side. The optimized value for the high-temperature side of the weld joint diameter. This represents the optimized value for the high-temperature side of the inner flow channel height. This represents the optimized value for the high-temperature side of the outer flow channel height. This represents the optimized value for the pitch ratio on the high-temperature side.
[0034] As a preferred embodiment of the present invention, the determined low-temperature side optimization targets include: the low-temperature side Nusselt coefficient and the low-temperature side friction resistance coefficient;
[0035] The determined low-temperature side design variables include: solder joint diameter, inner flow channel height, and pitch ratio;
[0036] The relationship between the constructed cryogenic side optimization objective and the cryogenic side design variables is as follows:
[0037]
[0038] in, The Nusselt coefficient is the low-temperature side. The coefficient of frictional resistance on the low-temperature side. The diameter of the solder joint. The height of the inner flow channel. Pitch ratio, Boundary adaptation factor and , The optimized value for the high-temperature side of the weld joint diameter. This represents the optimized value for the high-temperature side of the inner flow channel height. This represents the optimized value for the pitch ratio on the high-temperature side.
[0039] The set of optimization results for the low-temperature side is represented by the following formula:
[0040]
[0041] in, This is a set of optimization results for the low-temperature side. The optimized value for the low-temperature side of the solder joint diameter. This represents the optimized value for the low-temperature side of the inner flow channel height. This represents the optimized value for the pitch ratio on the low-temperature side.
[0042] As a preferred embodiment of the present invention, the final optimization result set obtained based on the high-temperature side optimization result set and the low-temperature side optimization result set is expressed by the following formula:
[0043]
[0044] in, For the final optimized result set, The optimized value for the low-temperature side of the solder joint diameter. This represents the optimized value for the low-temperature side of the inner flow channel height. This represents the optimized value for the high-temperature side of the outer flow channel height. This represents the optimized value for the pitch ratio on the low-temperature side.
[0045] As a preferred embodiment of the present invention, multiple operating conditions are achieved by changing the Reynolds number.
[0046] As a preferred embodiment of the present invention, obtaining the comprehensive performance value based on the basic performance index value and the optimized performance index value includes:
[0047] The comprehensive performance value on the high-temperature side is calculated using the following formula:
[0048]
[0049] in, This represents the comprehensive performance value on the high-temperature side. The optimized Nusselt coefficient for the high-temperature side, The basic Nusselt coefficient for the high-temperature side. The optimized friction resistance coefficient for the high-temperature side. The coefficient of frictional resistance on the high-temperature side of the foundation;
[0050] The overall performance value on the low-temperature side is calculated using the following formula:
[0051]
[0052] in, This represents the overall performance value on the low-temperature side. The optimized Nusselt coefficient for the low-temperature side, The basic Nusselt coefficient for the low-temperature side. The optimized friction resistance coefficient for the low-temperature side. The coefficient of friction resistance on the low-temperature side of the foundation.
[0053] In summary, the present invention has the following beneficial effects:
[0054] The method of this invention achieves coupled optimization of the high-temperature side and low-temperature side of the heat exchanger, which improves the core heat transfer performance, flow resistance characteristics and anti-dust accumulation ability of the heat exchanger. It solves the technical bottleneck that traditional heat exchangers cannot achieve both heat transfer efficiency and anti-dust accumulation performance. Moreover, it does not require the introduction of additional structures or systems, which greatly reduces manufacturing and operating costs and shortens the design cycle.
[0055] Further or more detailed beneficial effects will be described in conjunction with specific embodiments in the detailed implementation. Attached Figure Description
[0056] Figure 1 A flowchart of the flue gas heat exchanger flow channel coupling optimization method that balances anti-ash accumulation and efficient heat transfer according to an embodiment of the present invention is shown. Detailed Implementation
[0057] Embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. While some embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the invention. It should be understood that the accompanying drawings and embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the invention.
[0058] In the description of embodiments of the present invention, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.
[0059] like Figure 1 As shown, this invention proposes a flue gas heat exchanger flow channel coupling optimization method that balances anti-ash accumulation and efficient heat transfer, including:
[0060] Step 1. Determine the performance indicators of the heat exchanger; select design variables based on the performance indicators; construct a sample space based on the design variables; obtain the basic performance indicator values based on the sample space. Specifically, obtaining the basic performance indicator values based on the sample space involves constructing a basic three-dimensional model of the heat exchanger based on the sample space, and using CFD software to perform numerical calculations of the performance indicators of the basic heat exchanger three-dimensional model under multiple operating conditions to obtain the basic performance indicator values.
[0061] Pillow plate heat exchangers have become a common heat exchanger in the field of flue gas waste heat utilization due to their advantages such as high efficiency in heat transfer, compactness, design flexibility, and resistance to high temperature and pressure. Therefore, the optimized design of pillow plate heat exchangers is selected as the target heat exchanger in this embodiment of the invention.
[0062] In this step, the performance indicators of the heat exchanger determined include: Nusselt coefficient, friction resistance coefficient, and anti-ash accumulation factor.
[0063] In this step, the selected design variables include: solder joint diameter, inner flow channel height, outer flow channel height, and pitch ratio.
[0064] In this step, the sample space is constructed based on the design variables, including: a sample space for weld joint diameter of 3-12mm; a sample space for inner flow channel height of 3-10mm; a sample space for outer flow channel height of 10-25mm; and a sample space for pitch ratio of 1-1.73. This step will combine constraints such as processing technology and material properties to define the value range of each design variable in order to construct the sample space for the design variables.
[0065] After the sample space is determined, this step uses the Latin hypercube sampling method to extract design sample points with uniform spatial distribution characteristics. Each sample point corresponds to a unique combination of design variables. For example, in this embodiment, a certain design variable combination A could be: solder joint diameter of 13mm, inner channel height of 7mm, outer channel height of 12mm, and pitch ratio of 1.71.
[0066] Once the design variable combination is determined, a three-dimensional model of the basic heat exchanger can be constructed. After the three-dimensional model of the basic heat exchanger is constructed, CFD (Computational Fluid Dynamics) software can be used to perform numerical calculations on the performance indicators of the basic heat exchanger model to obtain the basic performance index values. The performance indicators are the Nusselt coefficient, the friction drag coefficient, and the anti-ash accumulation factor.
[0067] The Nusselt coefficient is calculated using the following formula:
[0068]
[0069] in, For Nusselt coefficient, The surface heat transfer coefficient of the heat exchanger. For the hydraulic diameter of the computational domain, Thermal conductivity;
[0070] The friction resistance coefficient is calculated using the following formula:
[0071]
[0072] in, The coefficient of frictional resistance. For the hydraulic diameter of the computational domain, Pressure loss per unit length For the working fluid density, The average flow velocity of the working fluid. For the position of manager;
[0073] The anti-ash accumulation factor is calculated using the following formula:
[0074]
[0075] in, As an anti-ash accumulation factor, The critical thermal resistance for ash accumulation. This is the critical ash accumulation time. The thermal resistance of ash accumulation on the heat exchanger surface has the characteristic of gradually increasing over time; when the critical ash accumulation time is reached... At this point, the increase in thermal resistance due to dust accumulation begins to slow down and eventually reaches a stable value. The critical ash accumulation thermal resistance and critical ash accumulation time can be obtained by fitting the results of numerical calculations of ash accumulation.
[0076] Furthermore, the calculated performance index values differ under different operating conditions. This step can change the operating conditions by altering the Reynolds number. The Reynolds number is determined by multiplying the average flow velocity of the working fluid by the hydraulic diameter of the calculation domain and dividing by the kinematic viscosity of the working fluid. For example, in this embodiment, the following operating conditions can be set: Condition 1: "High-temperature Reynolds number is 5000, low-temperature Reynolds number is 4000"; Condition 2: "High-temperature Reynolds number is 10000, low-temperature Reynolds number is 6000"; Condition 3: "High-temperature Reynolds number is 15000, low-temperature Reynolds number is 8000".
[0077] The basic performance indicators calculated under operating condition 1 for design variable combination A (i.e., weld diameter of 13mm, inner flow channel height of 7mm, outer flow channel height of 12mm, and pitch ratio of 1.71) are as follows: Nusselt coefficient of the high-temperature side foundation is 36; Nusselt coefficient of the low-temperature side foundation is 42; friction resistance coefficient of the high-temperature side foundation is 0.14; friction resistance coefficient of the low-temperature side foundation is 0.50; and anti-dust accumulation factor of the foundation is 16.7.
[0078] Step 2. Determine the high-temperature side optimization objective and high-temperature side design variables; obtain the high-temperature side optimization result set based on the high-temperature side optimization objective and high-temperature side design variables. Specifically, obtaining the high-temperature side optimization result set based on the high-temperature side optimization objective and high-temperature side design variables involves: constructing the correlation between the high-temperature side optimization objective and high-temperature side design variables using a BP neural network, and using a genetic algorithm to iteratively solve the optimization problem to obtain the high-temperature side Pareto solution set; then, using the TOPSIS method, obtaining the high-temperature side optimization result set from the high-temperature side Pareto solution set.
[0079] In this step, the determined optimization targets for the high-temperature side include: the high-temperature side Nusselt coefficient, the high-temperature side friction resistance coefficient, and the anti-ash accumulation factor. The high-temperature side optimization step aims to improve the heat transfer performance, flow performance, and anti-ash accumulation performance of the high-temperature side; therefore, the optimization targets for this step are the high-temperature side Nusselt coefficient, the high-temperature side friction resistance coefficient, and the anti-ash accumulation factor.
[0080] The determined high-temperature side design variables include: weld joint diameter, inner flow channel height, outer flow channel height, and pitch ratio. The optimization variables and their design range in this step correspond to the design variables and their sample space selected in step 102.
[0081] The relationship between the constructed high-temperature side optimization objective and the high-temperature side design variables (i.e., the description of the high-temperature side optimization problem) is as follows:
[0082]
[0083] in, The high-temperature side Nusselt coefficient, The coefficient of friction resistance on the high-temperature side. As an anti-ash accumulation factor, The diameter of the solder joint. The height of the inner flow channel. The height of the outer flow channel. This is the pitch ratio.
[0084] This step utilizes a BP neural network as a surrogate model to construct the relationship between the optimization objective and the design variables. A genetic algorithm is used to iteratively solve the optimization problem to obtain a Pareto solution set. The Technique for order preference by similarity to an ideal solution (TOPSIS) method is then used to obtain the optimization results for the high-temperature side from the Pareto solution set.
[0085] The set of optimization results for the high-temperature side is represented by the following formula:
[0086]
[0087] in, This is a set of optimization results for the high-temperature side. The optimized value for the high-temperature side of the weld joint diameter. This represents the optimized value for the high-temperature side of the inner flow channel height. This represents the optimized value for the high-temperature side of the outer flow channel height. This represents the optimized value for the pitch ratio on the high-temperature side.
[0088] Step 3. Determine the low-temperature side optimization objective and low-temperature side design variables based on the high-temperature side optimization result set; obtain the low-temperature side optimization result set based on the low-temperature side optimization objective and low-temperature side design variables. Specifically, obtaining the low-temperature side optimization result set based on the low-temperature side optimization objective and low-temperature side design variables involves: constructing the correlation between the low-temperature side optimization objective and low-temperature side design variables using a BP neural network, and using a genetic algorithm to iteratively solve the optimization problem to obtain the low-temperature side Pareto solution set; then, using the TOPSIS method, obtaining the low-temperature side optimization result set from the low-temperature side Pareto solution set.
[0089] In this step, the determined optimization targets for the low-temperature side include the low-temperature side Nusselt coefficient and the low-temperature side friction resistance coefficient. The low-temperature side optimization step aims to improve the heat transfer and flow performance of the low-temperature side; therefore, the optimization targets for this step are the low-temperature side Nusselt coefficient and the low-temperature side friction resistance coefficient.
[0090] The determined design variables for the cryogenic side include: solder joint diameter, inner channel height, and pitch ratio. Since the outer channel height does not affect the three-dimensional structure of the inner channel and therefore does not affect its performance, the optimization variables for the cryogenic side are solder joint diameter, inner channel height, and pitch ratio.
[0091] The design range of the low-temperature side optimization variables is based on the optimized configuration results of the high-temperature side optimization variables, and boundary adaptive adjustments are implemented; the magnitude of the boundary adjustment is quantitatively characterized by the boundary adaptation factor. In this step, the relationship between the constructed low-temperature side optimization objective and the low-temperature side design variables (i.e., the description of the low-temperature side optimization problem) is as follows:
[0092]
[0093] in, The Nusselt coefficient is the low-temperature side. The coefficient of frictional resistance on the low-temperature side. The diameter of the solder joint. The height of the inner flow channel. Pitch ratio, Boundary adaptation factor and , The optimized value for the high-temperature side of the weld joint diameter. This represents the optimized value for the high-temperature side of the inner flow channel height. This represents the optimized value for the pitch ratio on the high-temperature side.
[0094] This step uses a BP neural network as a surrogate model to build the relationship between the optimization objective and the design variables. A genetic algorithm is used to iteratively solve the optimization problem to obtain the Pareto solution set. The Technique for order preference by similarity to an ideal solution (TOPSIS) method is used to obtain the optimization results of the low-temperature side optimization from the Pareto solution set.
[0095] The set of optimization results for the low-temperature side is represented by the following formula:
[0096]
[0097] in, This is a set of optimization results for the low-temperature side. The optimized value for the low-temperature side of the solder joint diameter. This represents the optimized value for the low-temperature side of the inner flow channel height. This represents the optimized value for the pitch ratio on the low-temperature side.
[0098] Step 4. Obtain the final optimization result set based on the high-temperature side optimization result set and the low-temperature side optimization result set; obtain the optimized performance index values based on the final optimization result set. Specifically, obtaining the optimized performance index values based on the final optimization result set involves: constructing an optimized three-dimensional model of the heat exchanger based on the final optimization result set, and using CFD software to perform numerical calculations of the performance index values of the optimized three-dimensional model under multiple operating conditions to obtain the optimized performance index values.
[0099] In this step, the final set of optimization results obtained based on the high-temperature side optimization result set and the low-temperature side optimization result set is represented by the following formula:
[0100]
[0101] in, For the final optimized result set, The optimized value for the low-temperature side of the solder joint diameter. This represents the optimized value for the low-temperature side of the inner flow channel height. This represents the optimized value for the high-temperature side of the outer flow channel height. This represents the optimized value for the pitch ratio on the low-temperature side.
[0102] In step 1, the design variable combination A has a solder joint diameter of 13mm, an inner flow channel height of 7mm, an outer flow channel height of 12mm, and a pitch ratio of 1.71. Correspondingly, the final optimized result set in this step has a solder joint diameter of 24mm, an inner flow channel height of 7.2mm, an outer flow channel height of 10mm, and a pitch ratio of 1.45.
[0103] Once the final optimization result set is determined, a three-dimensional model of the optimized heat exchanger can be constructed. After the optimized three-dimensional model of the heat exchanger is constructed, CFD software can be used to perform numerical calculations on the performance indicators of the optimized heat exchanger to obtain the optimized performance index values. The performance indicators are the Nusselt coefficient, the friction resistance coefficient, and the anti-ash accumulation factor.
[0104] In this embodiment, the optimized performance index values calculated under operating condition 1 for the final optimized result set (i.e., weld diameter of 24mm, inner flow channel height of 7.2mm, outer flow channel height of 10mm, and pitch ratio of 1.45) are as follows: Nusselt coefficient after optimization on the high-temperature side is 73; Nusselt coefficient after optimization on the low-temperature side is 66; friction resistance coefficient after optimization on the high-temperature side is 0.07; friction resistance coefficient after optimization on the low-temperature side is 0.48; and the optimized anti-dust accumulation factor is 1.2.
[0105] Step 5. Obtain the comprehensive performance value based on the basic performance index value and the optimized performance index value to complete the verification of the optimization results.
[0106] In this step, obtaining the overall performance value based on the basic performance index value and the optimized performance index value includes:
[0107] The comprehensive performance value on the high-temperature side is calculated using the following formula:
[0108]
[0109] in, This represents the comprehensive performance value on the high-temperature side. The optimized Nusselt coefficient for the high-temperature side, The basic Nusselt coefficient for the high-temperature side. The optimized friction resistance coefficient for the high-temperature side. The coefficient of friction resistance on the high-temperature side of the foundation.
[0110] When the basic Nusselt coefficient for the high-temperature side is 36, the basic friction resistance coefficient for the high-temperature side is 0.14, the optimized Nusselt coefficient for the high-temperature side is 73, and the optimized friction resistance coefficient for the high-temperature side is 0.07, the calculated comprehensive performance value for the high-temperature side is 2.57. This is equivalent to a 157% improvement in the high-temperature side performance of the optimized heat exchanger.
[0111] The overall performance value on the low-temperature side is calculated using the following formula:
[0112]
[0113] in, This represents the overall performance value on the low-temperature side. The optimized Nusselt coefficient for the low-temperature side, The basic Nusselt coefficient for the low-temperature side. The optimized friction resistance coefficient for the low-temperature side. The coefficient of friction resistance on the low-temperature side of the foundation.
[0114] When the basic Nusselt coefficient on the low-temperature side is 42, the basic friction resistance coefficient on the low-temperature side is 0.50, the optimized Nusselt coefficient on the low-temperature side is 66, and the optimized friction resistance coefficient on the low-temperature side is 0.48, the calculated comprehensive performance value on the low-temperature side is 1.56. This is equivalent to a 56% improvement in the low-temperature side performance of the optimized heat exchanger.
[0115] In addition, the basic anti-ash accumulation factor was 16.7, and the optimized anti-ash accumulation factor was 1.2, which was 92.8% lower than the basic anti-ash accumulation factor.
[0116] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.
Claims
1. A method for optimizing the flow channel coupling of a flue gas heat exchanger that balances ash accumulation resistance and efficient heat transfer, characterized in that, include: Determine the performance specifications of the heat exchanger; Design variables are selected based on the aforementioned performance indicators; Construct a sample space based on the design variables; The basic performance index values are obtained based on the sample space; Determine the optimization objectives and design variables for the high-temperature side; The set of optimization results for the high-temperature side is obtained based on the high-temperature side optimization objective and the high-temperature side design variables; The optimization objectives and design variables for the low-temperature side are determined based on the set of optimization results from the high-temperature side. The set of optimization results for the low-temperature side is obtained based on the low-temperature side optimization objective and the low-temperature side design variables; The final optimization result set is obtained based on the high-temperature side optimization result set and the low-temperature side optimization result set; The optimized performance index values are obtained based on the final set of optimization results. The comprehensive performance value is obtained based on the basic performance index value and the optimized performance index value to verify the optimization results.
2. The method according to claim 1, characterized in that, The basic performance index values obtained based on the sample space are as follows: a three-dimensional model of the basic heat exchanger is constructed based on the sample space, and CFD software is used to perform numerical calculations of the performance index values of the three-dimensional model of the basic heat exchanger under multiple operating conditions to obtain the basic performance index values. The specific steps for obtaining the high-temperature side optimization result set based on the high-temperature side optimization objective and high-temperature side design variables are as follows: A BP neural network is used to construct the association between the high-temperature side optimization objective and the high-temperature side design variables; a genetic algorithm is used to iteratively solve the optimization problem to obtain the high-temperature side Pareto solution set; and the TOPSIS method is used to obtain the high-temperature side optimization result set from the high-temperature side Pareto solution set. The specific steps for obtaining the low-temperature side optimization result set based on the low-temperature side optimization objective and low-temperature side design variables are as follows: construct the association between the low-temperature side optimization objective and the low-temperature side design variables based on the BP neural network, and use the genetic algorithm to iteratively solve the optimization problem to obtain the low-temperature side Pareto solution set; The TOPSIS method is used to obtain the set of optimization results for the low-temperature side from the Pareto solution set on the low-temperature side; The optimized performance index values are obtained based on the final optimization result set as follows: a three-dimensional model of the optimized heat exchanger is constructed based on the final optimization result set, and CFD software is used to perform numerical calculations of the performance index values of the optimized heat exchanger under multiple operating conditions to obtain the optimized performance index values.
3. The method according to claim 2, characterized in that, The determined performance indicators of the heat exchanger include: Nusselt coefficient, friction resistance coefficient, and anti-ash accumulation factor; The Nusselt coefficient is calculated using the following formula: in, For Nusselt coefficient, The surface heat transfer coefficient of the heat exchanger. For the hydraulic diameter of the computational domain, Thermal conductivity; The frictional resistance coefficient is calculated using the following formula: in, The coefficient of frictional resistance. For the hydraulic diameter of the computational domain, Pressure loss per unit length For the working fluid density, The average flow velocity of the working fluid. For the position of manager; The anti-ash accumulation factor is calculated using the following formula: in, As an anti-ash accumulation factor, The critical thermal resistance for ash accumulation. This is the critical dust accumulation time.
4. The method according to claim 3, characterized in that, The selected design variables include: solder joint diameter, inner flow channel height, outer flow channel height, and pitch ratio.
5. The method according to claim 4, characterized in that, The sample space constructed based on the design variables includes: the sample space for the solder joint diameter is 3-12mm; the sample space for the inner flow channel height is 3-10mm; the sample space for the outer flow channel height is 10-25mm; and the sample space for the pitch ratio is 1-1.
73.
6. The method according to claim 5, characterized in that, The determined optimization targets for the high-temperature side include: the high-temperature side Nusselt coefficient, the high-temperature side friction resistance coefficient, and the anti-dust accumulation factor; The determined high-temperature side design variables include: weld point diameter, inner flow channel height, outer flow channel height, and pitch ratio; The relationship between the constructed high-temperature side optimization objective and the high-temperature side design variables is as follows: in, The high-temperature side Nusselt coefficient, The coefficient of friction resistance on the high-temperature side. As an anti-ash accumulation factor, The diameter of the solder joint. The height of the inner flow channel. The height of the outer flow channel. Pitch ratio; The set of optimization results for the high-temperature side is represented by the following formula: in, This is a set of optimization results for the high-temperature side. The optimized value for the high-temperature side of the weld joint diameter. This represents the optimized value for the high-temperature side of the inner flow channel height. This represents the optimized value for the high-temperature side of the outer flow channel height. This represents the optimized value for the pitch ratio on the high-temperature side.
7. The method according to claim 6, characterized in that, The determined optimization targets for the low-temperature side include: the low-temperature side Nusselt coefficient and the low-temperature side friction resistance coefficient; The determined low-temperature side design variables include: solder joint diameter, inner flow channel height, and pitch ratio; The relationship between the constructed cryogenic side optimization objective and the cryogenic side design variables is as follows: in, The Nusselt coefficient is the low-temperature side. The coefficient of frictional resistance on the low-temperature side. The diameter of the solder joint. The height of the inner flow channel. Pitch ratio, Boundary adaptation factor and , The optimized value for the high-temperature side of the weld joint diameter. This represents the optimized value for the high-temperature side of the inner flow channel height. This represents the optimized value for the pitch ratio on the high-temperature side. The set of optimization results for the low-temperature side is represented by the following formula: in, This is a set of optimization results for the low-temperature side. The optimized value for the low-temperature side of the solder joint diameter. This represents the optimized value for the low-temperature side of the inner flow channel height. This represents the optimized value for the pitch ratio on the low-temperature side.
8. The method according to claim 7, characterized in that, The final set of optimization results obtained based on the high-temperature side optimization result set and the low-temperature side optimization result set is expressed by the following formula: in, For the final optimized result set, The optimized value for the low-temperature side of the solder joint diameter. This represents the optimized value for the low-temperature side of the inner flow channel height. This represents the optimized value for the high-temperature side of the outer flow channel height. This represents the optimized value for the pitch ratio on the low-temperature side.
9. The method according to claim 2, characterized in that, Multiple operating conditions can be achieved by changing the Reynolds number.
10. The method according to claim 2, characterized in that, The overall performance value is obtained based on the basic performance index value and the optimized performance index value, including: The comprehensive performance value on the high-temperature side is calculated using the following formula: in, This represents the comprehensive performance value on the high-temperature side. The optimized Nusselt coefficient for the high-temperature side, The basic Nusselt coefficient for the high-temperature side. The optimized friction resistance coefficient for the high-temperature side. The coefficient of frictional resistance on the high-temperature side of the foundation; The overall performance value on the low-temperature side is calculated using the following formula: in, This represents the overall performance value on the low-temperature side. The optimized Nusselt coefficient for the low-temperature side, The basic Nusselt coefficient for the low-temperature side. The optimized friction resistance coefficient for the low-temperature side. The coefficient of friction resistance on the low-temperature side of the foundation.