Carbon capture structured packing design and optimization method based on fluid topology optimization

Abstract

The present application relates to the technical field of carbon dioxide capture, and particularly relates to a carbon capture structured packing design and optimization method based on fluid topology optimization, comprising: constructing a carbon capture reaction design domain geometry unit, taking a packing basic unit as a core, setting a fluid inlet and outlet extension section, distinguishing a fluid domain, a solid domain and a transition state therebetween through a continuous material density field, and defining a gravity field and adiabatic no-slip boundary condition adapted to an actual absorption tower; establishing a polynomial modified topology optimization multi-physical field coupling equation group, introducing a polynomial improved Darcy interpolation function to optimize a fluid-solid interface characteristic, and combining a filtering method and a projection method to improve numerical stability; based on a modeling and solving platform, adopting a global convergence moving asymptote method to iteratively solve, and generating a carbon capture packing structure with a fine and complex flow channel; the present application can solve the problems of low design freedom and limited optimization efficiency of traditional packing design which relies on experience.

Description

Technical Field

[0001] This invention belongs to the field of carbon dioxide capture technology, specifically relating to a method for designing and optimizing structured packing materials for carbon capture based on fluid topology optimization. Background Technology

[0002] Post-combustion carbon capture based on chemical absorption is the most mature and widely used technology in industrial-scale decarbonization. Its core equipment consists of an absorber tower and a desorption tower filled with packing material. The carbon capture performance of the absorber tower depends not only on the performance of the absorbent itself but also on the hydrodynamic characteristics dominated by the packing structure. The packing structure provides a high specific surface area and sufficient turbulence effect by regulating the gas-liquid contact time, interfacial area, and mass transfer performance, thereby promoting the efficient CO2 absorption reaction. In the desorption tower, the regeneration efficiency and regeneration energy consumption of the absorbent depend crucially on the synergistic effect of fluid flow and heat transfer within the tower. The packing material, as the core carrier enhancing this synergistic process, directly affects the overall performance of the desorption process.

[0003] For decades, structured packing materials in the industrial carbon capture field have maintained similar configurations, a typical example being the corrugated plate design of Sulzer's Mellapak series. These geometrically regular, fixed-dimensional packing materials still have significant optimization potential. Furthermore, current packing structure optimization heavily relies on designer experience, often employing trial-and-error methods or limited screening of new structures. This results in low design freedom, poor optimization efficiency, over-reliance on initial geometric parameters, and strong randomness in implementation, ultimately achieving only limited performance improvements and failing to meet the demands of industrial decarbonization for efficient, low-consumption equipment.

[0004] In view of this, the present invention is hereby proposed. Summary of the Invention

[0005] To address the aforementioned technical problems in the prior art, this invention provides a method for designing and optimizing structured packing for carbon capture based on fluid topology optimization. By using given control equations, objective functions, and constraints, the topology, shape, and size of the design domain are simultaneously adjusted from a global optimization perspective to achieve optimal performance.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] A method for designing and optimizing structured packing materials for carbon capture based on fluid topology optimization, characterized by comprising:

[0008] S1. Define the geometric unit of the carbon capture reaction design domain. The geometric unit is based on the packing basic unit, includes fluid inlet and outlet extensions, and distinguishes between the fluid domain, solid domain and intermediate transition state.

[0009] S2. Establish a polynomial-modified topology optimization multiphysics coupling equation set, which includes fluid flow control equation, mass transfer reaction control equation and heat transfer control equation. Introduce a polynomial-modified Darcy interpolation function, and combine filtering method and projection method.

[0010] S3. Based on the geometric unit and the coupled equation set, the carbon trapping packing structure is generated by iteratively solving the problem using the global convergent moving asymptote method.

[0011] Furthermore, the geometric unit parameters of the carbon capture reaction design domain are as follows: the basic unit size of the packing is in the range of 4mm×4mm-16mm×16mm, with a preferred size of 8mm×8mm; the fluid inlet and outlet extension is 2mm×2mm, and this extension is a pseudo-design domain; a gravitational field is applied to the geometric unit along the x-axis; the solid wall boundary is set to an adiabatic no-slip condition, and the design domain is set with a symmetrical boundary along the x-axis.

[0012] Furthermore, the fluid flow control equations include:

[0013] The continuity equation and the Navier-Stokes equation, specifically the formulas are as follows:

[0014]

[0015]

[0016] in, For fluid density, For fluid velocity, For fluid design domain material density, For fluid pressure, Where g is the volume force, and g is the acceleration due to gravity in the fluid. For fluid viscosity;

[0017] The convection-diffusion equation and the mass flow rate equation are as follows:

[0018]

[0019]

[0020] in This refers to the concentration of reactants. This is the local reaction rate constant; The mass flow rate of the integral unit; This indicates the direction of reactant flow.

[0021] Furthermore, the polynomial-modified Darcy interpolation function satisfies:

[0022]

[0023] in, , The value is 0.3. To improve the polynomial function, the expression is:

[0024]

[0025]

[0026] Where b, c, d, e are user-defined constants, Da is the Darcy flow term, Lc is the characteristic length, and Re is the Reynolds number.

[0027] Furthermore, the governing equation for the mass transfer reaction includes:

[0028] The convection-diffusion equation and the local chemical reaction equation are as follows:

[0029]

[0030]

[0031] in, The concentration of reactants, This is the local reaction rate constant. The mass flow rate of the integral unit. This indicates the direction of reactant flow.

[0032] Furthermore, the heat transfer control equations include:

[0033] The energy balance equation, specifically the formula, is as follows:

[0034]

[0035] in, and These represent the heat capacity and thermal conductivity of the reactants, respectively. For the temperature field of the design domain, It serves as the heat source for the reaction.

[0036] Furthermore, the filtering method employs Helmholtz partial differential equation filtering, defined as:

[0037]

[0038] in, The filter radius is... Design variables for filter materials;

[0039] The projection method is hyperbolic tangent projection, defined as:

[0040]

[0041] in, For projection design variables, This is the projection steepness parameter. This is the projection threshold.

[0042] Furthermore, the iterative solution process is modeled using COMSOL Multiphysics 6.3 software, and the control equations are solved in steady state using the finite element method, combined with the SUPG method to stabilize the velocity field and the PSPG method to stabilize the pressure field.

[0043] The PARDISO solver was used to solve large sparse linear systems. The design variable sensitivity was extracted using the adjoint method, and the constraints were processed using Lagrange multipliers.

[0044] Furthermore, the carbon trapping packing structure has a dendritic multi-channel distribution in its flow channels;

[0045] When the absorbent viscosity is 1.02 × 10⁻⁶ -3 Pa s, 2.87×10 -3 Pa s, 1.02×10 -2 Pa At time s, the flow channel morphology of the carbon trapping packing structure is different, and the higher the absorbent viscosity, the wider the flow channel; the three-dimensional construction method of the carbon trapping packing structure is: formed by stretching and array combination operation based on the two-dimensional topology optimization result, or directly generated by topology optimization based on the three-dimensional design domain.

[0046] Furthermore, the carbon trapping packing structure can directly generate a three-dimensional internal flow channel distribution structure through topology optimization in the three-dimensional design domain. The three-dimensional structure can be spatially arranged by array or pattern replication operations in the X, Y, and Z dimensions to form a three-dimensional grid or spatial lattice structure.

[0047] Compared with existing technologies, the carbon capture structured packing design and optimization method based on fluid topology optimization provided by this invention includes: constructing geometric units for the carbon capture reaction design domain, with the basic packing unit as the core, setting fluid inlet and outlet extension sections, distinguishing the fluid domain, solid domain, and transition state between them through a continuous material density field, and defining boundary conditions such as gravity field and adiabatic no-slip adapted to the actual absorption tower; secondly, establishing a polynomial-modified topology optimization multiphysics coupling equation set, covering fluid flow, mass transfer reaction, and heat transfer control equations, introducing a polynomial-modified Darcy interpolation function to optimize fluid-solid interface characteristics, and combining filtering and projection methods to improve numerical stability; finally, based on a modeling and solving platform, using the global convergence moving asymptote method for iterative solution, generating a carbon capture packing structure with fine and complex flow channels. This structure can be constructed into a three-dimensional entity through stretching and array operations, and is suitable for carbon capture absorption towers and desorption towers. This invention can solve the problems of traditional packing design relying on experience, low design freedom, and limited optimization efficiency. Attached Figure Description

[0048] Figure 1 A flowchart illustrating the design and optimization method for carbon trapping structured packing provided in this embodiment of the invention;

[0049] Figure 2 A schematic diagram illustrating the design domain definition provided in an embodiment of the present invention;

[0050] Figure 3 Comparison diagrams showing the improved methods provided in embodiments of the present invention;

[0051] Figure 4 Structural diagrams of different absorbent fillers provided in embodiments of the present invention;

[0052] Figure 5 A schematic diagram of the numerical iteration process provided in an embodiment of the present invention;

[0053] Figure 6 A schematic diagram of the numerical iteration process provided in an embodiment of the present invention;

[0054] Figure 7 This is a mass transfer distribution diagram of different absorbents provided in an embodiment of the present invention.

[0055] Explanation of reference numerals in the attached figures:

[0056] 1. Structure generated by traditional topology optimization method; 2. Structure generated by polynomial improved topology optimization method; 3. Structure generated by polynomial improved coupled filtering projection technique topology optimization method; 4. Optimized structure of absorbent ①; 5. Optimized structure of absorbent ②; 6. Optimized structure of absorbent ③; 7. Mass transfer distribution of absorbent ①; 8. Mass transfer distribution of absorbent ②; 9. Mass transfer distribution of absorbent ③. Detailed Implementation

[0057] The technical solution of the present invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0058] It should be noted that, unless otherwise specifically stated, the relative arrangement and numerical expressions of the components and steps described in these embodiments should not be construed as limiting the scope of the invention.

[0059] The following description of exemplary embodiments is merely illustrative and is not intended to limit the invention or its application or use in any way. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail herein, but where applicable, such techniques, methods, and apparatus should be considered part of this specification.

[0060] Example 1

[0061] See Figure 1 , Figure 1 This is a flowchart illustrating the design and optimization method for carbon trapping structured packings based on fluid topology optimization proposed in this invention. The method involves the following steps:

[0062] S1. Define the geometric units of the carbon capture reaction design domain; specifically including:

[0063] Industrial applications of carbon capture packing typically consist of an array of several basic packing units. Therefore, the design starting point for this embodiment is the definition of the design domain for a single basic packing unit. The geometry of the basic packing unit must be adapted to the fluid flow and mass transfer requirements within the carbon capture tower. Its basic size range is set from 4mm×4mm to 16mm×16mm, and after performance verification, the optimal size was determined to be 8mm×8mm.

[0064] See Figure 2 As shown, the core size of the optimization unit is 8mm × 8mm. To ensure smooth fluid flow and avoid localized flow disturbances, extension sections with a uniform size of 2mm × 2mm are provided at the fluid inlet and outlet ends of the optimization unit. The above two-dimensional geometric model clearly defines the reaction space and flow path between the chemical absorbent and CO2. The two react in a counter-current contact manner within the design domain. The chemical absorbent inlet, chemical absorbent outlet, CO2 inlet, and CO2 outlet boundaries are defined at the corresponding ports of the model to achieve directional flow and sufficient contact between the gas and liquid phases. The following physical boundary conditions are applied to the design domain:

[0065] Apply along The gravity field along the axial direction is consistent with that of the packing material in a conventional vertical absorption tower. The solid wall boundary condition is set as adiabatic and no-slip. The symmetric boundary condition is designed to affect the entire design domain along... The axes are mirrored to save computational resources. Within the design domain, the fluid domain is characterized by defining a continuous material density field. and solid domain intermediate states between An interpolation model is used to map intermediate states to material permeability, and an optimization iteration process drives the design domain toward a clear structure. The fluid inlet and outlet are extended to create a pseudo-design domain. This area is a fluid channel and no additional design is required.

[0066] S2. Establish a polynomial-corrected set of topology optimization multiphysics coupling equations; specifically including:

[0067] S21. Definition of gas-liquid reaction process: The chemical absorbent and CO2 are injected into the packing unit by the pump under pressure, and the countercurrent convection diffusion occurs, which leads to full contact and an exothermic reaction. For the universal chemical absorbent A (such as organic amine), the reaction of the two-phase fluid is as shown in formula (1). The absorbent A reacts with CO2 to generate product B (such as carbamate) and generates heat.

[0068]

[0069] S22. Fluid Flow Governing Equations: Assuming the fluid flow inside the packing is an incompressible steady-state flow, the physical properties of the microchannel fluid flow are similar to those of the macroscopic fluid flow, satisfying the continuity assumption, mass conservation, and momentum conservation, and fulfilling the continuity equation and the Navier-Stokes (NS) equations:

[0070]

[0071]

[0072] in, For fluid density, For fluid velocity, For fluid design domain material density, For fluid pressure, Where g is the volume force, and g is the acceleration due to gravity in the fluid. This represents the fluid viscosity.

[0073] S23. Mass transfer and reaction kinetic equations: Mass transfer between the absorbent and CO2 mainly occurs within the packed bed through counter-convective flow, followed by capture reactions via convective diffusion. Solid disturbance units within the packed bed increase the fluid contact area and enhance disturbance, thereby improving reaction performance. Reaction kinetics are described by the convective diffusion equation (4) and the local chemical reaction equation (5):

[0074]

[0075]

[0076] in This refers to the concentration of reactants. This is the local reaction rate constant; The mass flow rate of the integral unit; The direction of reactant flow is indicated; based on the Maxwell-Stefan equation, the diffusion coefficient of the carbon capture reaction is taken. The CO2 capture rate is defined as 3×10⁻⁹ m² / s; the CO₂ capture rate is defined as:

[0077]

[0078] in, and These represent the integral values ​​of the reactant stream flow rates at the CO2 inlet and outlet boundaries, respectively. The design domain fluid dynamic boundary conditions are as follows:

[0079]

[0080] in, For surface forces, pressure or velocity boundary conditions are used at the fluid inlet and outlet boundaries; the absorbent and CO2 inlet concentrations are respectively... and .

[0081] S24. Temperature Field and Energy Balance Equations: The temperature field T(λ) is formed by the exothermic reaction, and the internal flow is non-isothermal. The heat of reaction is transferred and changes the fluid's viscosity and other properties, increasing the difficulty of convergence in topology optimization calculations. The energy balance equation for convective heat transfer inside the packing is as follows:

[0082]

[0083] in, and These represent the heat capacity and thermal conductivity of the reactants, respectively. For the temperature field of the design domain, The heat source in the packing material is the exothermic effect of the carbon capture reaction; the faster the reaction rate, the stronger the exothermic effect. With local reaction rate Defined as follows:

[0084]

[0085]

[0086] in, The enthalpy of the chemical reaction is defined; the thermal boundary conditions for the packing are defined as follows:

[0087]

[0088] in, T represents the temperature at the inlet of the counter-current fluid. e and These are ambient temperature and overall heat transfer coefficient, respectively.

[0089] S25. Darcy Interpolation and Polynomial Correction: For fluid topology optimization problems, fluid body forces are introduced as external forces in the form of frictional resistance, and the Darcy interpolation method is used to improve the design variables. It plays a corresponding role in the Navier-Stokes equations. It facilitates achieving zero velocity in the solid domain while eliminating additional frictional forces in the fluid domain. The fluid body forces in equation (3) and the Darcy interpolation function introduce... They are defined as follows:

[0090]

[0091]

[0092] in, For porous media reverse osmosis rate, subject to design variables Impact, when As the density approaches zero, the corresponding local material becomes more impermeable, thus reducing physical strength. When the volume is large, the local material is considered solid. Conversely, As the mass approaches 1, the physical force decreases, and the local material is treated as a fluid. The Darcy function penalty factor affects the clarity of the fluid-structure interface profile and controls... convexity. Values ​​that are too small will result in noticeable grayscale areas. If the value is too large, it will result in an unreasonable chessboard grid structure. When When the optimal fluid-solid interface profile can be obtained, it is possible to obtain the best configuration.

[0093] In the optimization model, The interpolation function is expressed as:

[0094]

[0095] Unlike traditional methods The linear relationship leads to poor local permeability. A polynomial improvement is used to increase Darcy friction and promote a clearer distribution of the flow channel profile. The improved polynomial formula is as follows:

[0096]

[0097] in, , , ,e is a user-defined constant, which can be taken as... =-1, =1, =1, e=0; the improved polynomial improves the convexity of the function, for The intermediate value approaching 1 has the most significant effect. The improved method significantly enhances channel flow and reduces the grayscale distribution at the fluid-solid interface while maintaining the local impermeability of the solid in the design domain. Furthermore, the modified method achieves good convergence.

[0098] In formula (14) This represents the impermeability of the solid, and theoretically should be set to an infinite value. However, in actual calculations, this can cause numerical oscillations, leading to non-convergence of the optimization. Therefore, In optimization problems, the value to be maximized is defined as:

[0099]

[0100] in, For the Darcy flow term, set to 10⁻⁴. For characteristic length, Let Reynolds number be the number of the Reynolds number, defined as follows:

[0101]

[0102]

[0103] in, The equation represents the ratio of inertial force to viscous force; The characteristic velocity of the design domain inlet.

[0104] S26. Filtering and Projection Methods: To address the checkerboard jagged edges and grid dependency issues in topology optimization methods, a Helmholtz partial differential equation (PDE) filtering method is introduced. This method implicitly applies minimum resolvable size constraints, enhancing the smoothness of design variables and ensuring numerical stability. The filter is defined as follows:

[0105]

[0106] in, It is the filter radius, defined as the minimum grid size; It is a design variable for filter materials.

[0107] After smoothing unreasonable fluid-structure interaction (FSI) boundary structures using PDE filtering, blurred gray-level boundary regions may appear. Combining this with hyperbolic tangent projection can significantly sharpen the intermediate density of these gray-level regions and clarify the boundary contours. The projection function is as follows:

[0108]

[0109] Where λp is the projection design variable; β is the projection steepness parameter; and λβ is the projection threshold, which is set to λβ=0.5. The projection function has a Sigmoid shape, and the value of the parameter β affects the steepness of the curve. If the value of β is too small, the gray-scale area is difficult to suppress, while if the value of β is too large, sensitivity overflow will occur and numerical oscillation will occur. Setting β=8 yields the best results.

[0110] See Figure 3 To illustrate the improved methods, the packing structures obtained by different topology optimization methods (traditional Darcy friction, improved Darcy friction, and improved Darcy friction combined with projection filtering) are compared. The different topology optimization methods include: structure 1 generated by the traditional topology optimization method, structure 2 generated by the polynomial improved topology optimization method, and structure 3 generated by the polynomial improved coupled-filter projection technique topology optimization method.

[0111] Compared to traditional optimization methods, improved Darcy friction exhibits better performance in improving the grayscale region of small channels and enhancing flow permeability, but the fuzziness of solid boundaries and the checkerboard zigzag structure still need improvement. The PDE filtering and projection method based on improved Darcy friction can obtain the smoothest fluid channel structure, eliminating the influence of fuzzy boundaries and unreasonable interface structures, and significantly improving fluid flowability.

[0112] S27. Objective Function and Optimization Constraints: Reactivity is a key performance parameter of the packing material. The microstructure of the packing unit enhances turbulence, thereby promoting the reaction. The global average reaction rate is the integral value of the local reaction rate over the design domain, mathematically defined as follows:

[0113]

[0114] While considering the objective of optimizing the reaction rate, the packing channel structure should also satisfy good flow properties to prevent clogging and other issues. Therefore, another objective function is introduced: flow energy dissipation, mainly including viscous losses and frictional losses. Strict constraint functions are adopted for the flow properties objective to ensure that the optimization results meet application requirements. The mathematical form of the constraints is as follows:

[0115]

[0116] Based on the multiphysics model description of the packing material described above, the mathematical form of the fluid topology optimization problem is established as follows:

[0117]

[0118]

[0119] S3. Based on the aforementioned geometric units and coupled equations, an optimized design is performed to obtain the carbon trapping packing structure. Specifically, this includes:

[0120] S31. To complete the topology optimization design of the high-efficiency carbon capture packing structure, COMSOL Multiphysics 6.3 software was used as the modeling and solution platform, and several key improvements were made based on its underlying finite element framework. Specific implementation included using the software to define the design domain, write custom calculation scripts, construct a multiphysics coupling model, and on this basis, develop a topology optimization process suitable for complex transport and reaction processes.

[0121] S32. The basic geometric dimensions of the packing unit are discretized by parameterization, and the boundary conditions of absorbent flow, CO2 component transport and chemical reaction, heat transfer process, and solid wall boundary conditions are clearly defined. The control equations (1)-(24) are used to fully describe the multi-physical coupling behavior of absorbent and CO2 flow, chemical reaction, mass transfer and heat transfer, and the steady-state numerical solution is performed by the finite element method (FEM).

[0122] To address the requirements of laminar flow characteristics and the numerical stability of the N-S equations, a bilinear isoparametric finite element method is used to fully couple and discretize the velocity, pressure, and temperature fields, reducing the solution complexity and suppressing spurious numerical oscillations that may be caused by higher-order elements.

[0123] S33. To satisfy the inf-sup condition and enhance the numerical stability of the convection-dominated case, a hybrid stabilization strategy is introduced: the streamline-upwind / Petrov–Galerkin (SUPG) method is used to stabilize the velocity field, and the pressure stabilization / Petrov–Galerkin (PSPG) method is used to stabilize the pressure field. By modifying the variational weak form, the numerical robustness of the physical field is improved, laying a reliable discrete foundation for topology optimization.

[0124] S34. Regarding the optimization algorithm, the gradient-based globally convergent moving asymptote method (GCMMA) is used to iteratively update the design variables. Sensitivity information of the objective function and constraints to the design variables is extracted uniformly using the efficient adjoint method. When solving large-scale sparse linear systems, the PARDISO solver is selected to ensure high computational efficiency and excellent numerical stability. Lagrange multipliers are introduced, and corresponding Lagrange functions are constructed to handle constraints during the optimization process.

[0125] S35. Targeting the unique porous, multiphase mass transfer and reaction characteristics of carbon trapping packings, this invention enhances the numerical description of the coupling between convection, reaction, and heat transfer. Specific optimization steps are as follows:

[0126] S351. Initialize the design parameters in the design domain and define the initial value of the variable λ;

[0127] S352. Solve the governing equations using the fully coupled finite element method;

[0128] S353. Calculate the objective function and constraints;

[0129] S354. Solve the adjoint equation and calculate and update the design sensitivity based on the high gradient information of the adjoint variable field.

[0130] S355. Update the design variable λ using the Global Convergence Method with Moving Asymptotes (GCMMA).

[0131] S356. Regularize the variable domain using the Helmholtz PDE filtering method and the hyperbolic tangent projection method;

[0132] S357. Determine if the convergence condition is met. If the condition is met, the optimal topology is obtained; if the condition is not met, continue iterative calculation until the objective function converges.

[0133] S36. The iterative convergence criterion is defined as the relative change of the objective function between adjacent iteration steps, as shown in the following formula:

[0134]

[0135] Where I is the number of iterations, and ε = 1 × 10 -6 When the results of adjacent iteration steps satisfy equation (25), the optimization is determined to be converged and the iteration is stopped.

[0136] Additionally, see Figure 4 The diagram shows the filler structure under three different viscosity absorbent conditions. From left to right, the absorbents are the optimized structure 4 (H2O viscosity) of absorbent ①, the optimized structure 5 (30% wt. MEA viscosity) of absorbent ②, and the optimized structure 6 (10 times H2O viscosity) of absorbent ③.

[0137] The viscosities of absorbents ①, ②, and ③ at a temperature of 293.15 K are 1.02 × 10⁻³ Pa·s, 2.87 × 10⁻³ Pa·s, and 1.02 × 10⁻² Pa·s, respectively. The inlet concentrations of the absorbents and CO₂ are defined as a₁ = 4978 mol / m³ and a₂ = 61.3 mol / m³, respectively. The inlet and outlet pressures of the absorbents and CO₂ gas are both defined as pin = 1 Pa and pout = 0 Pa.

[0138] Driven by the objective function, the packing material evolves into a complex multi-channel, multi-perturbation structure. The structure is distributed in a dendritic pattern to satisfy the countercurrent diffusion of the absorbent and CO2. Microchannels in different directions ensure sufficient fluid contact, maximizing specific surface area while satisfying flow properties and enhancing reactivity. As the absorbent viscosity increases, the viscous forces of the fluid strengthen. To maintain flow properties and avoid blockage, the channels gradually widen, demonstrating the universal adaptability of the topology optimization method to the objective function parameters. The numerical iterative solution process for topology optimization is as follows: Figure 5 and Figure 6 As shown, with the increase of the iteration step I, the permeable flow region is eliminated, the rough fluid-solid interface is smoothed, and the optimized structural profile is clear. Figure 7 The diagram shows the mass transfer distribution of the absorbent, including the mass transfer distribution of absorbent ① (7), absorbent ② (8), and absorbent ③ (9). The filler structure achieves good absorbent wettability.

[0139] Regarding the forming of the filler structure, the material distribution pattern determined by the two-dimensional topology optimization results can be used to construct a three-dimensional solid through a combination of stretching and arraying. Specifically, this includes:

[0140] First, based on the two-dimensional filler layout obtained by topology optimization, a certain thickness stretching operation is performed along the direction perpendicular to the two-dimensional design plane to generate a three-dimensional basic solid unit with uniform cross-sectional characteristics. The stretching process can adjust the stretching height according to the actual working conditions and performance requirements, and can be combined with gradient or variable thickness design to achieve better mechanical or functional performance.

[0141] Subsequently, the three-dimensional basic units obtained by stretching are arrayed in a specified plane, including but not limited to rectangular arrays, circular arrays or other custom path arrays; the spacing, number and arrangement of the arrays can be parametrically adjusted according to the actual application scenario, thereby realizing the orderly expansion and distribution of the filler structure over a large range, ensuring the realization of the continuity, periodicity or specific functional modes of the structure.

[0142] Furthermore, the design concept of this invention is also applicable to three-dimensional design domain models. In the three-dimensional design domain, topology optimization can directly generate the internal flow channel distribution structure of the three-dimensional packing without the need for two-dimensional to three-dimensional stretching conversion. However, the optimized three-dimensional packing unit structure can still be spatially arranged through array or pattern replication operations, thereby achieving efficient design and manufacturing of large-scale complex packing structures. The array in the three-dimensional design domain can be carried out in the X, Y, and Z dimensions, forming a three-dimensional mesh or spatial lattice structure. This design method greatly improves the flexibility and applicability of the design, while promoting the application of packing structures in advanced engineering fields such as porous materials, composite structures, and lightweight components.

[0143] In summary, this invention effectively transforms two-dimensional topology optimization results into practically usable three-dimensional solid structures through a combination of stretching and arraying operations, and possesses the versatility to naturally extend to full three-dimensional optimization design, significantly improving the efficiency and reliability of engineering optimization results.

[0144] The above specific embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for designing and optimizing structured packing materials for carbon capture based on fluid topology optimization, characterized in that, include: S1. Define the geometric unit of the carbon capture reaction design domain. The geometric unit is based on the packing basic unit, includes fluid inlet and outlet extensions, and distinguishes between the fluid domain, solid domain and intermediate transition state. S2. Establish a polynomial-modified topology optimization multiphysics coupling equation set, which includes fluid flow control equation, mass transfer reaction control equation and heat transfer control equation. Introduce a polynomial-modified Darcy interpolation function, and combine filtering method and projection method. The fluid flow control equations include: The continuity equation and the Navier-Stokes equation, specifically the formulas are as follows: in, For fluid density, For fluid velocity, For fluid design domain material density, For fluid pressure, Where g is the volume force, and g is the acceleration due to gravity in the fluid. For fluid viscosity; The convection-diffusion equation and the mass flow rate equation are as follows: in This refers to the concentration of reactants. This is the local reaction rate constant; The mass flow rate of the integral unit; The direction of reactant flow; The polynomial-modified Darcy interpolation function satisfies: in, , The value is 0.

3. To improve the polynomial function, the expression is: Where b, c, d, e are user-defined constants, Da is the Darcy flow term, Lc is the characteristic length, and Re is the Reynolds number; The mass transfer reaction governing equations include: The convection-diffusion equation and the local chemical reaction equation are as follows: in, The concentration of reactants, This is the local reaction rate constant. The mass flow rate of the integral unit. The direction of reactant flow; The heat transfer control equations include: The energy balance equation, specifically the formula, is as follows: in, and These represent the heat capacity and thermal conductivity of the reactants, respectively. For the temperature field of the design domain, As a heat source for the reaction; The filtering method employs Helmholtz partial differential equation filtering, defined as follows: in, The filter radius is... Design variables for filter materials; The projection method is hyperbolic tangent projection, defined as: in, For projection design variables, This is the projection steepness parameter. The projection threshold; S3. Based on the geometric unit and the coupled equation set, the carbon trapping packing structure is generated by iteratively solving the problem using the global convergent moving asymptote method.

2. The method for designing and optimizing carbon trapping structured packings based on fluid topology optimization according to claim 1, characterized in that, The geometric unit parameters of the carbon capture reaction design domain are as follows: the basic unit size of the packing is in the range of 4mm×4mm-16mm×16mm, and the size is 8mm×8mm; the fluid inlet and outlet extension is 2mm×2mm, and this extension is a pseudo-design domain; a gravitational field is applied to the geometric unit along the x-axis; the solid wall boundary is set to adiabatic no-slip condition, and the design domain is set with a symmetrical boundary along the x-axis.

3. The method for designing and optimizing carbon trapping structured packings based on fluid topology optimization according to claim 1, characterized in that, The iterative solution process uses COMSOL Multiphysics 6.3 software for modeling, and solves the control equations in steady state using the finite element method, combined with the SUPG method to stabilize the velocity field and the PSPG method to stabilize the pressure field. The PARDISO solver was used to solve large sparse linear systems. The design variable sensitivity was extracted using the adjoint method, and the constraints were processed using Lagrange multipliers.

4. The method for designing and optimizing carbon trapping structured packings based on fluid topology optimization according to claim 1, characterized in that, The carbon capture packing structure has a dendritic multi-channel distribution of its flow channels. When the absorbent viscosity is 1.02 × 10⁻⁶ - ³Pa s, 2.87×10 - ³Pa s, 1.02×10 - ²Pa At time s, the flow channel morphology of the carbon trapping packing structure is different, and the higher the absorbent viscosity, the wider the flow channel; the three-dimensional construction method of the carbon trapping packing structure is: formed by stretching and array combination operation based on the two-dimensional topology optimization result, or directly generated by topology optimization based on the three-dimensional design domain.

5. The method for designing and optimizing carbon trapping structured packings based on fluid topology optimization according to claim 4, characterized in that, The carbon capture packing structure can directly generate a three-dimensional internal flow channel distribution structure through topology optimization in the three-dimensional design domain. The three-dimensional internal flow channel distribution structure can be spatially arranged by array or pattern replication operations in the three dimensions of X, Y, and Z to form a three-dimensional grid or spatial lattice structure.

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