Segmented modeling simulation method suitable for PCHE under supercritical CO2 working condition

Abstract

The application is suitable for a segmented modeling simulation method of PCHE under supercritical CO2 working condition: S1, PCHE structure division: the PCHE is divided into a bundle tube segment and a core heat exchange segment; S2, bundle tube segment direct simulation: a three-dimensional geometric model of the bundle tube segment is established, a three-dimensional grid model is obtained by grid division on the three-dimensional geometric model, a full three-dimensional direct numerical simulation method is used for fine simulation on the three-dimensional grid model until convergence, and flow distribution data of each microchannel inlet of the core heat exchange segment are obtained; S3, core heat exchange segment simplified modeling: based on the fine simulation result of the single channel, a physical reduced-order model of the flow resistance of the microchannel representing the core heat exchange segment is established, and the model is a resistance network composed of multiple parallel resistance elements; S4, coupled solution: the flow distribution data are applied to the resistance network model as boundary conditions, and the resistance network model is calculated in a coupled manner, and overall performance parameters of the PCHE are output.

Description

Technical Field

[0001] This invention belongs to the technical field of printed circuit heat exchanger (PCHE) simulation and computational fluid dynamics (CFD), specifically involving a segmented modeling efficient simulation method suitable for supercritical CO2 conditions, which directly solves the bundled tube section of the PCHE and simplifies the modeling and solving of the core heat exchange section. Background Technology

[0002] Printed circuit board heat exchangers (PCHEs) are a new type of compact heat exchanger with advantages such as large specific surface area, high heat exchange efficiency, resistance to high temperature and pressure, and small device size. They are the most widely used and most promising type of heat exchanger in supercritical CO2 power generation systems. As the advantages of PCHEs become increasingly apparent, they are also gradually being applied in industrial fields such as offshore oil and gas processing, floating liquefied natural gas systems, helium heat exchange in high-temperature gas-cooled reactors, and electronic devices.

[0003] The PCHE (Potentially Variable Energy Flow) system consists of thousands of micro-flow channels, which inherently leads to large mesh sizes and high computational costs in its numerical simulation. However, the problem becomes even more complex and severe when PCHEs are applied to supercritical CO2 conditions. Although CO2 does not undergo a phase transition in the supercritical region, its physical properties (such as density, viscosity, specific heat capacity, and thermal conductivity) change drastically, especially in the near-critical region, where even slight changes in temperature and pressure can cause significant alterations in these properties. This presents a significant challenge to accurate numerical simulation. Currently, the simulation of PCHEs under supercritical CO2 conditions faces several difficulties, and existing simulation methods and tools have significant limitations. The primary problem is the high cost of full 3D high-resolution simulation: to capture the complex flow and heat transfer details inside the PCHE under supercritical CO2 conditions, especially the flow separation and secondary flow phenomena in the core section of non-linear channels (such as Z-shaped and S-shaped channels), a full 3D computational fluid dynamics model with very fine mesh generation is typically required. For a linear PCHE model of moderate complexity (e.g., 7×11 channels), the number of grids has reached nearly 20 million, resulting in huge consumption of computing resources and long simulation cycles, which greatly increases the difficulty of PCHE engineering design and optimization iteration. Summary of the Invention

[0004] This invention addresses the problems and shortcomings of existing technologies by providing a segmented modeling and simulation method for PCHE under supercritical CO2 conditions. This method creatively proposes a simulation strategy of "partitioning and hybrid solution" to address the structural and functional differences between the bundled tube section and the core heat exchange section in PCHE. This achieves a significant improvement in overall computational efficiency while ensuring the simulation accuracy of key areas.

[0005] The present invention solves the above-mentioned technical problems through the following technical solution:

[0006] This invention provides a segmented modeling and simulation method for PCHE (Potentially High-Pressure Chemistry) under supercritical CO2 conditions, characterized by the following steps:

[0007] S1, PCHE structure division: The PCHE is divided into a bundled tube section for fluid distribution and collection, and a core heat exchange section consisting of multiple microchannels for the main heat exchange.

[0008] S2. Direct simulation of bundled tube sections: Establish a three-dimensional geometric model of the bundled tube section, mesh the three-dimensional geometric model to obtain a three-dimensional mesh model, and use the full three-dimensional direct numerical simulation method to perform fine simulation of the three-dimensional mesh model until convergence, so as to obtain the flow distribution data of each microchannel inlet of the core heat exchange section.

[0009] S3. Simplified modeling of the core heat exchange section: Based on the detailed simulation results of a single channel, a physical reduced-order model is established to characterize the flow resistance of the microchannel in the core heat exchange section. This model is a resistance network composed of multiple parallel resistance elements, each resistance element representing a microchannel.

[0010] S4. Coupled Solution: Apply the flow distribution data as boundary conditions to the inlet of each resistance element in the resistance network model to determine the flow resistance characteristics of each resistance element. Perform coupled calculations on the resistance network model to output the overall performance parameters of PCHE.

[0011] Preferably, S3 specifically includes the following steps:

[0012] S31. Establishment of a single-channel flow model: Establish an independent and complete three-dimensional fine model of a single channel. The channel geometry and wall conditions of the single-channel three-dimensional fine model are completely consistent with the actual microchannels in the core heat exchange section.

[0013] S32. Verify the mesh independence of the single-channel three-dimensional fine model: Generate a series of meshes from sparse to dense to form multiple sets of meshes with different densities. Under the same boundary conditions, when the difference in the pressure drop calculation results of the two densest sets of meshes is less than 1%, the results are considered to have converged. The mesh with the best computational efficiency is selected and applied to the single-channel three-dimensional fine model for subsequent calibration calculations.

[0014] S33. Pressure Drop-Flow Rate Relationship Acquisition: The computationally efficient mesh is applied to a single-channel 3D fine-grained model, and the SIMPLEC algorithm is used to calculate the pressure drop of this single channel under a series of different inlet flow velocities. The calibration curve of the single-channel pressure drop-flow relationship was obtained;

[0015] S34. Flow resistance model construction: Based on the relationship between the flow resistance characteristics of a single channel and the inlet flow rate, a flow resistance model is constructed.

[0016]

[0017] in, This represents the quadratic coefficient of the resistance term. This represents the first-order coefficient of the resistance term. This indicates the fluid density in a single channel. Indicates the fluid velocity in a single channel;

[0018] S35. Equivalent flow resistance coefficient obtained: Pressure drops of each group obtained using calibration curves. ,density and flow rate Substituting these values ​​into the flow resistance model, the corresponding equivalent flow resistance coefficient K is calculated, thereby generating a flow rate-flow resistance coefficient table. The equivalent flow resistance coefficient K includes... and ;

[0019] S36. The core heat exchange section is modeled as a resistance network model. The flow resistance characteristics of each resistance element in the resistance network model are determined by the generated flow rate-flow resistance coefficient table.

[0020] Preferably, in S4, the flow distribution data is used as a boundary condition and applied to the inlet of each resistance element in the resistance network model. Based on the flow distribution data of each resistance element, the flow resistance characteristics are determined by querying the flow-resistance coefficient table. Coupled calculations are performed on the resistance network model to output the overall performance parameters of PCHE.

[0021] Preferably, in S4, the overall performance parameters include the total voltage drop and the flow distribution of each channel;

[0022] Verify overall performance parameters: Compare the flow distribution of each channel of PCHE obtained by coupled solution with the existing full 3D fine simulation results of PCHE. When the error of the flow of each microchannel relative to the flow of each microchannel in the existing full 3D fine simulation results is less than the predetermined threshold, the segmented modeling simulation method is deemed effective.

[0023] Preferably, in S4, the uniformity of flow distribution in the core heat exchange section is quantified by calculating the flow non-uniformity factor.

[0024] Preferably, in S2, a k-ε turbulence model is adopted, and the Prandtl number of turbulence is dynamically corrected to adapt to the variable physical properties and heat transfer characteristics of supercritical CO2 in the quasi-critical region; the NIST REFPROP database is coupled, and the variable physical properties of supercritical CO2 are handled by interpolation method; the SIMPLEC algorithm is used for pressure-velocity coupled solution; wherein, the dynamic correction is based on the ratio of the instantaneous specific heat capacity of supercritical CO2 to the reference specific heat capacity.

[0025] Preferably, in S2, when the PCHE structure is symmetric, a symmetric simplified model is established and symmetric boundary conditions are set for calculation.

[0026] Preferably, in S2, the standard computational fluid dynamics process is first used to verify mesh independence: a series of meshes from sparse to dense are generated to form multiple sets of meshes with different densities. The calculation is performed under the same boundary conditions, and the total pressure drop of the bundled pipe section and the flow rate of the key channel are monitored. When the difference in total pressure drop between two consecutive sets of dense meshes is stable within 1%, the result is considered to have converged, and the mesh that achieves the best balance between computational resources and computational accuracy is selected as the three-dimensional mesh model for formal simulation calculation.

[0027] The present invention also provides an electronic device, characterized in that it includes: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory to execute the above-described segmented modeling and simulation method.

[0028] The present invention also provides a computer-readable storage medium storing computer program instructions thereon, characterized in that the computer program instructions, when executed by a processor, implement the above-described segmented modeling and simulation method.

[0029] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of the present invention.

[0030] The positive and progressive effects of this invention are as follows:

[0031] 1. A highly efficient simulation method of "partitioned approach and hybrid solution" was proposed: For the first time in PCHE simulation, a differentiated simulation method was creatively proposed based on the differences in the physical structure and function of PCHE, rather than the traditional "one-size-fits-all" full 3D or fully simplified simulation method. This fundamentally solves the contradiction between "simulation accuracy" and "simulation efficiency". Direct simulation is used in the bundled tube section, which requires high precision, to ensure the accuracy of the key physical process of flow distribution; in the core heat exchange section, which has high computational costs, a physical reduction model is used, sacrificing unnecessary flow details in exchange for an order-of-magnitude improvement in computational efficiency.

[0032] 2. While ensuring computational accuracy, in-depth efficiency optimizations were performed at multiple levels, including geometry, modeling, and solution. First, a symmetry simplification technique was employed, creating 1 / 2 or 1 / 4 models for symmetric structures, directly reducing mesh size and computation time by 50%-75%. Second, physical order reduction was performed on the model, simplifying the tens of thousands of core 3D microchannels into a network of "resistance elements" defined by "flow resistance coefficients," achieved by adding distributed resistance source terms to the model. This is the core of the order-of-magnitude improvement in computational efficiency. Finally, through the aforementioned hybrid strategies and optimization techniques, the time required for full 3D simulation, which originally took days or even weeks, was reduced to hours, perfectly supporting rapid iteration in engineering design. Attached Figure Description

[0033] Figure 1 This is the overall flowchart of the segmented modeling and simulation method of the present invention.

[0034] Figure 2 This is a schematic diagram of the PCHE structure partitioning; in the diagram, 1—bundled tube section, 2—core heat exchange section.

[0035] Figure 3 This is a 3D geometric model diagram of PCHE.

[0036] Figure 4 This is a schematic diagram of data transfer during the coupled solution process.

[0037] Figure 5 is a geometric model diagram of the 7x11 channel PCHE in the embodiment; Figure 5a In the diagram, 11—supercritical carbon dioxide inlet, 12—water inlet, 13—supercritical carbon dioxide outlet, and 14—water outlet; Figure 5b In the middle, 3—partial detail of the PCHE bundled tube section, 4—partial detail of the PCHE core heat exchange section; Figure 5c In the middle, 5 is the cold aisle and 6 is the hot aisle.

[0038] Figure 6 shows the pressure drop-flow rate relationship curve for a single channel. Figure 6a The working fluid is water; Figure 6b The working fluid is SCO2 (supercritical CO2).

[0039] Figure 7 This is a flow distribution diagram of the 7×11 channels in a preferred embodiment of the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] To address the different simulation requirements of the bundled tube section and the core heat exchange section: The PCHE structure can be divided into the bundled tube section and the core heat exchange section. (I) The bundled tube section, as the "traffic hub" of the PCHE, is responsible for uniformly distributing and efficiently collecting fluids. Its performance directly determines the efficiency and safety of the entire PCHE. The bundled tube section is usually a three-dimensional structure with cavities or guide vanes. The complex three-dimensional flow (such as eddies and flow separation) inside plays a decisive role in the flow distribution and cannot be simplified. Therefore, it must be solved by three-dimensional direct numerical simulation. (II) The core heat exchange section, as the "main office area" of the PCHE, is responsible for efficiently and compactly completing the core heat transfer task. The core heat exchange section is usually composed of a large number of regular and repetitive microchannels. If all of them are solved directly, the aforementioned problems of mesh volume and computational cost will arise. However, its regular and repetitive structural characteristics allow us to use physical reduction modeling. By simplifying the microchannels into a network of "resistance elements", we can capture their macroscopic pressure drop and heat transfer effect while sacrificing unnecessary flow details, thereby achieving an order-of-magnitude improvement in computational efficiency.

[0042] Therefore, it is extremely important to propose a segmented modeling and efficient simulation method suitable for supercritical CO2 conditions, which involves direct solution of PCHE bundled tube sections and simplified modeling and solution of core heat exchange sections.

[0043] like Figure 1 As shown, this segmented modeling and simulation method includes the following steps:

[0044] S1, PCHE structure division: The PCHE is divided into a bundled tube section for fluid distribution and collection, and a core heat exchange section consisting of multiple microchannels for the main heat exchange.

[0045] S2. Direct simulation of bundled tube sections: A three-dimensional geometric model of the bundled tube section is established. The three-dimensional geometric model is meshed to obtain a three-dimensional mesh model. The three-dimensional mesh model is then finely simulated using a full three-dimensional direct numerical simulation method until convergence, thereby obtaining the flow distribution data of each microchannel inlet in the core heat exchange section.

[0046] In S2, a k-ε turbulence model is adopted, and the Prandtl number of turbulence is dynamically corrected to adapt to the variable physical properties and heat transfer characteristics of supercritical CO2 in the quasi-critical region. The NIST REFPROP database is coupled, and the variable physical properties of supercritical CO2 are handled by interpolation method. The SIMPLEC algorithm is used for pressure-velocity coupled solution. Among them, the dynamic correction is based on the ratio of the instantaneous specific heat capacity of supercritical CO2 to the reference specific heat capacity.

[0047] In S2, when the PCHE structure is symmetric, a symmetric simplified model is established and symmetric boundary conditions are set for calculation.

[0048] In S2, the standard computational fluid dynamics process is first used to verify mesh independence: a series of meshes from sparse to dense are generated to form multiple sets of meshes with different densities. The calculation is performed under the same boundary conditions, and the total pressure drop of the bundled pipe section and the flow rate of the key channels are monitored. When the difference in total pressure drop between two consecutive sets of dense meshes is stable within 1%, the result is considered to have converged. The mesh that achieves the best balance between computational resources and computational accuracy is selected as the three-dimensional mesh model for formal simulation calculation.

[0049] S3. Simplified modeling of the core heat exchange section: Based on the detailed simulation results of a single channel, a physical reduced-order model is established to characterize the flow resistance of the microchannel in the core heat exchange section. This model is a resistance network composed of multiple parallel resistance elements, each of which represents a microchannel.

[0050] S3 specifically includes the following steps:

[0051] S31. Establishment of a single-channel flow model: Establish an independent and complete three-dimensional fine model of a single channel. The channel geometry and wall conditions of the single-channel three-dimensional fine model are completely consistent with the actual microchannels in the core heat exchange section.

[0052] S32. Verify the mesh independence of the single-channel 3D fine model: Generate a series of meshes from sparse to dense to form multiple sets of meshes with different densities. Under the same boundary conditions, when the difference in the pressure drop calculation results of the two densest sets of meshes is less than 1%, the results are considered to have converged. The mesh with the best computational efficiency is selected and applied to the single-channel 3D fine model for subsequent calibration calculations.

[0053] S33. Pressure Drop-Flow Rate Relationship Acquisition: The computationally efficient mesh is applied to a single-channel 3D fine-grained model, and the SIMPLEC algorithm is used to calculate the pressure drop of this single channel under a series of different inlet flow velocities. The calibration curve of the single-channel pressure drop-flow relationship was obtained.

[0054] S34. Flow resistance model construction: Based on the relationship between the flow resistance characteristics of a single channel and the inlet flow rate, a flow resistance model is constructed.

[0055]

[0056] in, This represents the quadratic coefficient of the resistance term. This represents the first-order coefficient of the resistance term. This indicates the fluid density in a single channel. This indicates the fluid velocity in a single channel.

[0057] S35. Equivalent flow resistance coefficient obtained: Pressure drops of each group obtained using calibration curves. ,density and flow rate Substituting these values ​​into the flow resistance model, the corresponding equivalent flow resistance coefficient K is calculated, thereby generating a flow rate-flow resistance coefficient table. The equivalent flow resistance coefficient K includes... and .

[0058] S36. The core heat exchange section is modeled as a resistance network model. The flow resistance characteristics of each resistance element in the resistance network model are determined by the generated flow rate-flow resistance coefficient table.

[0059] S4. Coupled Solution: Apply the flow distribution data as boundary conditions to the inlet of each resistance element in the resistance network model to determine the flow resistance characteristics of each resistance element. Specifically, based on the flow distribution data of each resistance element, consult the flow-resistance coefficient table to determine the flow resistance characteristics. Perform coupled calculations on the resistance network model to output the overall performance parameters of PCHE.

[0060] In S4, the uniformity of flow distribution in the core heat exchange section is quantified by calculating the flow non-uniformity factor.

[0061] In S4, the overall performance parameters include the total pressure drop and the flow distribution of each channel. To verify the overall performance parameters, the flow distribution of each channel of the PCHE obtained by the coupled solution is compared with the existing full three-dimensional fine simulation results of the PCHE. When the error of the flow of each microchannel relative to the flow of each microchannel in the existing full three-dimensional fine simulation results is less than the predetermined threshold, the segmented modeling simulation method is deemed to be effective.

[0062] The following section, in conjunction with the accompanying drawings and VirtualFlow simulation software, details the efficient segmented modeling simulation method applicable to supercritical CO2 conditions, which directly solves the PCHE bundled tube section and simplifies the modeling of the core heat exchange section.

[0063] As shown in Figure 5, the core heat exchange section in this embodiment is 640 mm long and consists of 7 stacked plates. Each layer contains 11 parallel microchannels, forming a 7 (row) × 11 (column) microchannel array. The hot-side working fluid is supercritical CO2, with an inlet pressure of 7.5 MPa and a temperature of 343.15 K; the cold-side working fluid is water, with an inlet pressure of 0.1 MPa and a temperature of 309.15 K. Under these conditions, the properties of supercritical CO2 change drastically, and its flow and heat transfer characteristics differ significantly from those of water, thus validating the robustness of the simulation method.

[0064] (I) Overall Process

[0065] This embodiment follows Figure 1 The execution logic of the flowchart shown is based on the idea of ​​"partitioning and hybrid solution". It sequentially executes the following steps: (S1) PCHE structure partitioning, (S2) direct simulation of bundled tube sections, (S3) simplified modeling of core heat exchange section and (S4) coupled solution, and finally outputs and verifies the overall performance parameters.

[0066] (II) Implementation in stages

[0067] Step S1, PCHE structure partitioning:

[0068] like Figure 2 As shown, this step is completed in the preprocessing module of VirtualFlow software. Based on the differences in the physical structure and function of PCHE, it is divided into two computational parts: bundled tube section 1 and core heat exchange section 2. Bundled tube section 1 includes the distribution / collection chambers for the fluid inlet and outlet. This region has a complex structure and significant three-dimensional flow effects (such as eddies and flow separation), playing a decisive role in flow distribution, and must be simulated directly numerically. Core heat exchange section 2 is the region composed of the aforementioned 7×11 channel array. This region has a regular and repetitive structure and is the area where the main heat exchange occurs, making it suitable for simplified physical modeling.

[0069] Step S2, Direct simulation of the bundled tube segment:

[0070] The goal is to obtain the inlet flow distribution of each channel with high accuracy. The geometric and mesh models used are as follows: Figure 3 As shown. In VirtualFlow software, a system is built... Figure 3The three-dimensional geometric model of the bundled pipe section shown is used to generate a three-dimensional mesh model. To ensure the accuracy of the calculation results, mesh independence verification is first performed according to the standard procedure of computational fluid dynamics (CFD): a series of meshes from sparse to dense (three sets of meshes with different densities) are generated. Calculations are performed under the same boundary conditions, monitoring the total pressure drop of the bundled pipe section and the flow rate of key channels. When the difference between the calculation results (such as the total pressure drop) of two consecutive sets of refined meshes stabilizes within 1%, the results are considered to have converged, and the mesh that achieves the best balance between computational resources and computational accuracy is selected for formal calculation.

[0071] Physical model and solver settings:

[0072] 1. Property Processing: Enables the VirtualFlow software to process the variable properties of supercritical fluids. The NIST REFPROP database is specified for the supercritical CO2 domain, and the software processes variable properties through real-time interpolation.

[0073] 2. Turbulence Model: Select the k-ε turbulence model and enable the dynamic correction function for the Prandtl number of turbulence.

[0074] 3. Multi-domain setting: Different system operating pressures are set for the supercritical CO2 side and the water side (7.5 MPa and 0.1 MPa, respectively).

[0075] 4. Solver: The pressure-velocity coupling uses the SIMPLEC algorithm.

[0076] Execution and output:

[0077] Run the model to simulate until convergence. After the simulation is complete, output the mass flow rate data of the 77 channel inlet sections of the core heat exchange section, forming a flow distribution list. Figure 7 As shown, the distribution results of this data are compared with the direct simulation results.

[0078] Step S3: Simplified modeling of the core heat exchange section:

[0079] Single-channel characteristic calibration: Using the above steps S31-S35, the calibration curve of the single-channel pressure drop-flow relationship is shown in Figure 6.

[0080] In the VirtualFlow software's modeling environment, the entire core heat exchange section (7×11 microchannel array) is modeled as a resistance network model consisting of 77 parallel "resistance elements". The flow resistance characteristics of each resistance element are determined by the table of the rigorously calibrated flow resistance coefficient K mentioned above.

[0081] Step S4, Coupled Solution:

[0082] Its detailed data transmission process is as follows: Figure 4(A schematic diagram of data transfer in the coupled solution process is shown.)

[0083] Data coupling: The inlet mass flow data of the 77 channels obtained in step S2 are used as boundary conditions and applied one-to-one to the inlet of each element of the resistance network model established in step S3.

[0084] System Solution: Run this resistance network model in the system solver of the VirtualFlow software.

[0085] Performance Output: The software quickly outputs the overall performance parameters of the PCHE, including the total voltage drop (ΔP). total (and the flow distribution and pressure drop characteristics of each channel.)

[0086] Model Validation and Results

[0087] To fully verify the effectiveness of this method, a comparative verification was conducted from two aspects: intermediate results and key overall performance.

[0088] Flow distribution accuracy verification: The flow distribution calculated by this method is compared with the results of full 3D direct simulation. The results are as follows: Figure 7 As shown in the comparison chart of flow distribution results, the relative error between the flow distribution of each channel obtained by this method and the direct simulation results is less than 3%, which proves the accuracy of the present invention in capturing the key physical process of flow distribution.

[0089] Key overall performance verification: The total voltage drop (ΔP) calculated by this method is verified. total Compared with a high-precision full three-dimensional benchmark solution, the total pressure drop predicted by the method of this invention is in high agreement with the benchmark value. Given the accuracy of flow distribution and the high-fidelity calibration of the core section resistance characteristics, this method is also suitable for accurately predicting the total heat transfer (Q). total It provides a reliable foundation, and its overall performance prediction error fully meets the accuracy requirements of engineering design.

[0090] Efficiency Improvement: The overall simulation calculation time and computational resource consumption are reduced by orders of magnitude compared to direct full 3D simulation, achieving a perfect balance between accuracy and efficiency.

[0091] In summary, by referring to Figure 1 The process involves sequentially executing each step of the present invention in the VirtualFlow software. Through rigorous verification, it has been confirmed that the method described in this invention can achieve an order-of-magnitude improvement in computational efficiency in the simulation of PCHE under supercritical CO2 conditions, while ensuring the accuracy of predictions for key physical processes and overall performance. This provides core technical support for the rapid design and optimization of PCHE.

[0092] This invention also provides an electronic device, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory to execute the aforementioned method.

[0093] This invention also provides a computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the aforementioned method.

[0094] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0095] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A segmented modeling and simulation method for PCHE (Programmable Chromatography-Enhanced Chemistry) under supercritical CO2 conditions, characterized in that, Includes the following steps: S1, PCHE structure division: The PCHE is divided into a bundled tube section for fluid distribution and collection, and a core heat exchange section consisting of multiple microchannels for the main heat exchange. S2. Direct simulation of bundled tube sections: Establish a three-dimensional geometric model of the bundled tube section, mesh the three-dimensional geometric model to obtain a three-dimensional mesh model, and use the full three-dimensional direct numerical simulation method to perform fine simulation of the three-dimensional mesh model until convergence, so as to obtain the flow distribution data of each microchannel inlet of the core heat exchange section. S3. Simplified modeling of the core heat exchange section: Based on the detailed simulation results of a single channel, a physical reduced-order model is established to characterize the flow resistance of the microchannel in the core heat exchange section. This model is a resistance network composed of multiple parallel resistance elements, each resistance element representing a microchannel. S4. Coupled Solution: Apply the flow distribution data as boundary conditions to the inlet of each resistance element in the resistance network model to determine the flow resistance characteristics of each resistance element. Perform coupled calculations on the resistance network model and output the overall performance parameters of PCHE. S3 specifically includes the following steps: S31. Establishment of a single-channel flow model: Establish an independent and complete three-dimensional fine model of a single channel. The channel geometry and wall conditions of the single-channel three-dimensional fine model are completely consistent with the actual microchannels in the core heat exchange section. S32. Verify the mesh independence of the single-channel three-dimensional fine model: Generate a series of meshes from sparse to dense to form multiple sets of meshes with different densities. Under the same boundary conditions, when the difference in the pressure drop calculation results of the two densest sets of meshes is less than 1%, the results are considered to have converged. The mesh with the best computational efficiency is selected and applied to the single-channel three-dimensional fine model for subsequent calibration calculations. S33. Pressure Drop-Flow Rate Relationship Acquisition: The computationally efficient mesh is applied to a single-channel 3D fine-grained model, and the SIMPLEC algorithm is used to calculate the pressure drop of this single channel under a series of different inlet flow velocities. The calibration curve of the single-channel pressure drop-flow relationship was obtained; S34. Flow resistance model construction: Based on the relationship between the flow resistance characteristics of a single channel and the inlet flow rate, a flow resistance model is constructed. ； in, This represents the quadratic coefficient of the resistance term. This represents the first-order coefficient of the resistance term. This indicates the fluid density in a single channel. Indicates the fluid velocity in a single channel; S35. Equivalent flow resistance coefficient obtained: Pressure drops of each group obtained using calibration curves. ,density and flow rate Substituting these values ​​into the flow resistance model, the corresponding equivalent flow resistance coefficient K is calculated, thereby generating a flow rate-flow resistance coefficient table. The equivalent flow resistance coefficient K includes... and ; S36. The core heat exchange section is modeled as a resistance network model. The flow resistance characteristics of each resistance element in the resistance network model are determined by the generated flow rate-flow resistance coefficient table.

2. The segmented modeling and simulation method for PCHE under supercritical CO2 conditions as described in claim 1, characterized in that, In S4, the flow distribution data is used as a boundary condition and applied to the inlet of each resistance element in the resistance network model. Based on the flow distribution data of each resistance element, the flow resistance characteristics are determined by querying the flow-resistance coefficient table. Coupled calculations are performed on the resistance network model to output the overall performance parameters of PCHE.

3. The segmented modeling and simulation method for PCHE under supercritical CO2 conditions as described in claim 1, characterized in that, In S4, the overall performance parameters include the total pressure drop and the flow distribution of each channel; Verify overall performance parameters: Compare the flow distribution of each channel of PCHE obtained by coupled solution with the existing full 3D fine simulation results of PCHE. When the error of the flow of each microchannel relative to the flow of each microchannel in the existing full 3D fine simulation results is less than the predetermined threshold, the segmented modeling simulation method is deemed effective.

4. The segmented modeling and simulation method for PCHE under supercritical CO2 conditions as described in claim 1, characterized in that, In S4, the uniformity of flow distribution in the core heat exchange section is quantified by calculating the flow non-uniformity factor.

5. The segmented modeling and simulation method for PCHE under supercritical CO2 conditions as described in claim 1, characterized in that, In S2, a k-ε turbulence model is adopted, and the Prandtl number of turbulence is dynamically corrected to adapt to the variable physical properties and heat transfer characteristics of supercritical CO2 in the quasi-critical region; the NIST REFPROP database is coupled, and the variable physical properties of supercritical CO2 are handled by interpolation method; the SIMPLEC algorithm is used for pressure-velocity coupled solution. The dynamic correction is based on the ratio of the instantaneous specific heat capacity of supercritical CO2 to the reference specific heat capacity.

6. The segmented modeling and simulation method for PCHE under supercritical CO2 conditions as described in claim 1, characterized in that, In S2, when the PCHE structure is symmetric, a symmetric simplified model is established and symmetric boundary conditions are set for calculation.

7. The segmented modeling and simulation method for PCHE under supercritical CO2 conditions as described in claim 1, characterized in that, In S2, the standard computational fluid dynamics process is first used to verify mesh independence: a series of meshes from sparse to dense are generated to form multiple sets of meshes with different densities. The calculation is performed under the same boundary conditions, and the total pressure drop of the bundled pipe section and the flow rate of the key channels are monitored. When the difference in total pressure drop between two consecutive sets of dense meshes is stable within 1%, the result is considered to have converged. The mesh that achieves the best balance between computational resources and computational accuracy is selected as the three-dimensional mesh model for formal simulation calculation.

8. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in memory to execute the segmented modeling and simulation method according to any one of claims 1-7.

9. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the segmented modeling and simulation method as described in any one of claims 1-7.

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