CFD-based constructed wetland hydraulic optimization method and waveform subsurface flow constructed wetland system

Abstract

The invention discloses a CFD-based constructed wetland hydraulic optimization method and a waveform subsurface flow constructed wetland system, and the optimization method comprises the steps: constructing a three-dimensional geometric model, carrying out grid division, building a multi-physical field model, setting a boundary condition and a discrete method, carrying out numerical solution, carrying out post-processing, and carrying out configuration iterative optimization. Quantizing a water flow path length and a wetland system hydraulic performance evaluation index as optimization criteria; the wetland system is of a cuboid structure, comprises a water inlet area, a waveform underflow reaction area and a water outlet area, and is provided with three filler layers and functional filler columns; according to the scheme, through CFD multi-model coupling and iterative optimization, the problem that a traditional wetland is poor in hydraulic condition is solved, the hydraulic effects of few dead zones and uniform water flow are achieved, and the method is suitable for low-carbon-nitrogen-ratio sewage treatment.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment technology, specifically to a hydraulic optimization method for constructed wetlands based on CFD technology and a waveform subsurface flow constructed wetland system. Background Technology

[0002] Constructed wetland systems are considered a promising wastewater treatment technology due to their green, low-carbon, and low-cost nature. However, in practical applications, their denitrification efficiency is often limited by unsatisfactory internal hydraulic conditions and the resulting inefficient biochemical reaction processes. Traditional subsurface flow constructed wetlands rely on empirically designed configurations. The porous structure formed by the internal packing material leads to an inertial flow state, easily causing hydraulic short-circuiting and dead zones. These problems result in uneven distribution of hydraulic retention time, low mass transfer efficiency between wastewater and packing material / microbial film, and an inability to stably construct the aerobic-anoxic alternating environment required for nitrification-denitrification. Existing technologies do not systematically incorporate CFD numerical simulation for refined quantitative assessment of the flow field, making it difficult to fundamentally optimize the hydraulic flow pattern, thus limiting denitrification efficiency. This is especially true in the treatment of low C / N ratio wastewater, where the combination of carbon source scarcity and poor hydraulic conditions further restricts the improvement of treatment effects.

[0003] Based on the above problems, there is an urgent need for a technical solution that can accurately optimize the hydraulic configuration. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a CFD-based hydraulic optimization method for constructed wetlands, comprising: S1. Construct a three-dimensional geometric model based on the actual structural characteristics of the constructed wetland and extract the computational fluid domain; S2. Perform structured mesh generation on the computational fluid domain; S3. Establish the steady-state laminar flow control equations, porous media model and discrete phase model based on pressure solution. The porous media model is associated with the wetland matrix resistance characteristics, and the discrete phase model is used to obtain the residence time distribution of fluid particles. S4. Set the velocity boundary, free outflow boundary, and wall boundary, and configure the discretization method; S5. Perform numerical solutions and monitor the convergence and divergence of the equations; S6. Post-process the simulation results to extract and calculate hydraulic performance evaluation indicators, including dead zone ratio, effective volume ratio, and water flow divergence. S7. When the dead zone ratio and hydraulic performance do not meet the design specifications, adjust the number of wetland guide plates, the packing gradation sequence, or the matrix layer thickness ratio, and repeat steps S1-S6 until the design specifications are met.

[0005] Preferably, the continuity equation involved in the porous media model is: In the formula, , , These represent the velocity components in the x, y, and z directions, respectively, in m / s; t is time, in seconds; and ρ is the fluid density, in kg / m³. 3 ; The momentum conservation equations involved in the porous medium model are: ; In the formula, P is the static pressure, with units of Pa, and ρ g This is a gravitational volume force, with units of N / m. 3 , ij For stress tensor, The additional momentum loss source is the momentum source phase in the i-direction (x,y,z), which includes viscous drag and inertial drag loss source terms; the viscous drag and inertial drag loss source terms satisfy: In the formula, D ij and C ij These are the loss coefficient matrices for viscous drag and inertial drag, respectively. The energy conservation equations involved in the porous media model are: , In the formula, the subscripts f and s refer to fluid and solid, respectively; ε represents the porosity of the medium; h represents enthalpy; J j S is the diffusion flux of component j; S is the volumetric heat source term; k eff The effective thermal conductivity of the medium is denoted by ; the governing equation is . In the formula, k f and k s Thermal conductivity of fluids and solid media.

[0006] Furthermore, the discrete phase model adopts the Eulerian-Lagrange description method, and the particles are set as massless inert particles with a particle size of 10⁻. 6 m is injected into the fluid domain in a surface source manner, and a unidirectional coupling solution strategy is adopted. Particle trajectory tracking adopts a steady-state tracking mode, and the maximum number of tracking steps is set to 50,000. The number of injected particle flows is large enough to ensure statistical representativeness.

[0007] Further optimized, the boundary conditions are specifically configured as follows: the left inlet surface of the physical model is set as a velocity boundary, and the liquid phase velocity is set according to the hydraulic residence time; the right outlet surface of the physical model is set as a free outflow boundary, and the outlet pressure is set to 101.3 kPa; the porous media interface region adopts a shared topological boundary form; all other boundaries are set as wall boundaries; the inlet and outlet particle tracking attributes are set to Escape, and the wall tracking attributes are set to Reflect.

[0008] In a further preferred embodiment, the discretization method is configured as follows: a pressure-based coupled solver is used, the spatial discretization scheme is a second-order upwind difference scheme, the pressure-velocity coupling uses the SIMPLE algorithm, and the momentum equation, turbulent kinetic energy and dissipation rate equations are all discretized using a first-order upwind scheme; the numerical solution is executed through a CFD solver, the number of calculation steps is set after standard initialization, and the solution stops when the residuals of all equations are lower than the set threshold.

[0009] In a further preferred embodiment, the mesh is divided using regular hexahedral mesh units, with the basic size of the volume mesh controlled within the range of 8mm to 12mm. For areas with significant flow characteristics, such as the wall surface, the edge of the internal baffle, and the interface layer of the filler, boundary layers are set and local mesh densification is performed. The total number of mesh units needs to be determined after verification of mesh independence.

[0010] Further preferred, after the solution is completed, the calculation results are post-processed using Tecplot and EXCEL. The specific steps include: S7.1 Based on the solution results of AnsysFluent, Tecplot is used for flow field visualization analysis. First, isosurfaces are created, and liquid phase velocity distribution cloud maps and velocity vector maps are drawn on the surfaces; S7.2 After particle tracking is completed, the discrete phase particle data is captured at the outlet boundary, and the .dpm file containing particle motion trajectory and residence time information is exported and imported into Excel for the calculation of hydraulic performance indicators.

[0011] Further optimization involves comprehensively analyzing the numerical simulation results of the wetland system flow regime, evaluating the influence of different numbers of compartments, different substrate filling sequences, and different substrate layer thickness ratios on the system's hydraulic performance, and finally determining the configuration scheme with the optimal system hydraulic performance.

[0012] A waveform subsurface flow constructed wetland system, applied to the development of any of the above-mentioned CFD-based constructed wetland hydraulic optimization methods, is characterized in that the system has a cuboid structure, 0.9m long, 0.3m wide, and 0.35m high, including an inlet zone, a waveform subsurface flow reaction zone, and an outlet zone; the inlet zone is provided with an inlet, which enters the waveform subsurface flow reaction zone from the top through an overflow weir; the waveform subsurface flow reaction zone is divided into four reaction functional compartments by three guide plates, each filled with three layers of packing material, and the second reaction compartment is provided with a functional packing column; the outlet zone is provided with an overflow plate and an outlet.

[0013] In a further preferred embodiment, the three-layer packing structure consists of a pebble support layer, a quartz sand main functional layer, and a gravel plant layer, arranged from bottom to top. Functional packing columns are installed in between, and carbon source packing is configured according to the effluent water quality requirements. The main body of the packing support device can be a hollow tubular component made of polyvinyl chloride, with 5mm diameter through holes evenly distributed on the tube wall, and the inner surface covered with a nylon filter screen. The system integrates clearly defined anaerobic, anoxic, and aerobic zones through spatial configuration zoning and packing gradation optimization.

[0014] Technical effects: The core inventive technology of this invention is to couple a porous media model with a discrete phase (DPM) model, and to achieve iterative configuration optimization by using quantified indicators such as dead zone ratio and water flow path length as optimization criteria. This technology precisely solves the problem of poor hydraulic conditions caused by traditional wetland design relying on experience, controlling the dead zone ratio to within 5%, ensuring that the water flow path meets design requirements, providing a stable environment for nitrification-denitrification, and adapting to the needs of low C / N ratio wastewater treatment. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating a method for developing a hydraulically optimized constructed wetland system based on fluid mechanics principles and CFD numerical simulation technology, as exemplified by the present invention. Figure 2 A schematic diagram of a waveform subsurface flow constructed wetland device as an example of the present invention includes a front view of the device, a side view of the device, a top view of the device, and a three-dimensional geometric model diagram. Figure 3 This is a fluid calculation region diagram of a waveform undercurrent constructed wetland device as an example of the present invention; Figure 4 This is a grid partition diagram of a waveform undercurrent constructed wetland device as an example of the present invention; Figure 5 The following are schematic diagrams illustrating different setting conditions for examples of the present invention: (a) schematic diagrams of wetland system structures with different numbers of compartments, (b) schematic diagrams of wetland system structures with different substrate filling sequences, and (c) schematic diagrams of wetland system structures with different substrate layer thickness ratios. Figure 6 A flow field distribution diagram of a waveform subsurface flow constructed wetland device as an example of the present invention. Figure 7 This is a schematic diagram of a waveform undercurrent constructed wetland device as an example of the present invention; Figure 8 The schematic diagram of the packing support device for example of the present invention includes: an isometric view of the packing support device and a side view of the packing support device. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0017] Traditional subsurface flow constructed wetland configuration design often relies on empirical design or tracer experiments, which is time-consuming and labor-intensive and cannot visualize the details of the internal flow field. This leads to short-circuiting and dead zones in the water flow, uneven distribution of hydraulic residence time, and low contact mass transfer efficiency between wastewater and packing materials and microbial films.

[0018] Based on this, please refer to Figure 1-8 This embodiment provides a CFD-based hydraulic optimization method for constructed wetlands, including the following steps: S1. Construct a three-dimensional geometric model based on the actual structural characteristics of the constructed wetland and extract the computational fluid domain; S2. Perform structured mesh generation on the computational fluid domain; S3. Establish the steady-state laminar flow control equations, porous media model and discrete phase model based on pressure solution. The porous media model is associated with the wetland matrix resistance characteristics, and the discrete phase model is used to obtain the residence time distribution of fluid particles. S4. Set the velocity boundary, free outflow boundary, and wall boundary, and configure the discretization method; S5. Perform numerical solutions and monitor the convergence and divergence of the equations; S6. Post-process the simulation results to extract and calculate hydraulic performance evaluation indicators, including dead zone ratio, effective volume ratio, and water flow divergence. S7. When the dead zone ratio and hydraulic performance do not meet the design specifications, adjust the number of wetland guide plates, the packing gradation sequence, or the matrix layer thickness ratio, and repeat steps S1-S6 until the design specifications are met.

[0019] This scheme systematically addresses the blindness of traditional wetland hydraulic configuration design by combining CFD technology with iterative optimization mechanisms, achieving precise control of hydraulic conditions. In specific implementation, step S1 requires constructing a geometric model using 3D modeling software based on the actual size, filler layout, and flow guiding structure of the constructed wetland. During construction, key structures affecting water flow, such as the flow guides and filler layer interfaces, must be retained, while factors with minimal impact on fluid flow, such as reaction heating and small components, must be ignored. Subsequently, the software extracts only the computational fluid domain containing the fluid-flowable area to ensure the accuracy of the simulation. In step S2, structured mesh generation requires the use of a professional meshing tool adapted to fluid computation. First, the overall mesh size range is determined. Then, for areas with drastic flow changes, such as the wall surface, the edge of the flow guide, and the interface of the filler layer, boundary layers are set and local mesh refinement is performed. The mesh size in the refined area should be 1 / 3 to 1 / 2 of the overall mesh size to ensure accurate capture of complex flow field details. The total number of mesh cells must be determined after verifying mesh independence. In step S3, the steady-state laminar flow control equations need to be determined based on the actual flow velocity range of the wetland to ensure their applicability. The porous media model requires experimental determination of parameters such as particle size and porosity of the wetland packing material, and based on this, the viscous drag and inertial drag coefficients are calculated to ensure the model accurately reflects the obstruction effect of the packing material on the flow. The discrete phase model requires the selection of massless inert particles as tracer particles, and the particle injection location must cover the entire inlet cross-section to ensure a comprehensive characterization of the flow field. In step S4, the boundary conditions must be set to fit the actual operating conditions of the wetland. The velocity boundary velocity must be calculated based on the design hydraulic residence time and the effective wetland volume. The pressure of the free outflow boundary is set to standard atmospheric pressure, and the wall boundary must be set to a no-slip condition. In step S5, the numerical solution requires the use of a professional CFD solver. After initialization, a reasonable number of calculation steps and convergence criteria are set. During the solution process, the residual curves of each control equation are monitored in real time. If residual oscillations or divergence occur, the time step, mesh quality, or convergence threshold must be adjusted promptly to ensure stable solutions. The post-processing in step S6 requires the use of flow field visualization software and data processing tools. Velocity contour maps and vector maps are used to visually represent the flow field distribution. Key parameters such as dead zone ratio, effective volume ratio, and water divergence are calculated by statistically analyzing the residence time data of discrete phase particles. The iterative optimization in step S7 requires simulations for different combinations of structural parameters. Each adjustment is followed by re-execution of the preceding steps until the hydraulic performance indicators meet the set requirements, resulting in the optimal configuration. The technical effect achieved by the above implementation method is that dead zones within the wetland are effectively controlled, and water flow distribution is uniform, providing a good hydraulic foundation for pollutant removal.

[0020] Traditional constructed wetland technology configuration optimization lacks refined design and control methods based on the combination of hydraulic efficiency and pollutant removal characteristics, making it difficult to accurately reflect the correlation mechanism between the fluid movement law and efficiency within the wetland.

[0021] Based on this, the core function of the continuity equation involved in the porous media model is to describe the mass conservation of the fluid during the flow process, that is, the change in mass of the fluid element per unit time is equal to the net mass flowing into that element. Here, ux, uy, and uz represent the fluid velocity in the xyz directions of the three-dimensional coordinate system, respectively. Their values ​​are obtained through a CFD solver and directly reflect the speed of water flow at different locations. In practical applications, it is necessary to combine the design flow rate and effective volume of the wetland and reasonably set the velocity boundary conditions to ensure that the simulation results are consistent with the actual water flow state. t is the time parameter, used to describe the time evolution of the fluid motion. In steady-state simulations, the ∂ρ / ∂t term is 0, meaning the fluid density does not change with time, suitable for continuous and stable operation of wetlands. ρ is the fluid density; for wastewater in wastewater treatment scenarios, its density is approximately 1000 kg / m³, similar to the density of water. 3 If the wastewater contains high concentrations of pollutants, the actual density value must be experimentally determined and substituted into the equation to avoid affecting the calculation results due to density setting deviations. Solving the equation requires combining the computational fluid domain grid of the wetland. A CFD solver is used to solve the partial differential equations using a discretization method to obtain the velocity components at each grid node, thereby analyzing the flow trajectory and distribution patterns of the fluid within the wetland. The technical advantages achieved by the above implementation method are clear definition of equation parameters, rigorous calculation process, and accurate reflection of the mass conservation characteristics of the fluid within the wetland, providing accurate data support for subsequent flow field analysis and hydraulic performance evaluation.

[0022] Compared with traditional methods that rely on empirical design or tracer experiments, this method can more accurately quantify the resistance of baffle settings and packing configuration to fluid flow and clarify their relationship with hydraulic efficiency, thereby significantly improving the realism and reliability of flow field simulation.

[0023] Based on this, the momentum conservation equation involved in the porous media model describes the momentum change law of the fluid during motion, that is, the momentum change of a fluid element per unit time is equal to the sum of all external forces acting on that element. P is the static pressure, reflecting the pressure distribution inside the fluid, and its value is obtained by a solver. In the wetland simulation, the static pressure is higher in the inlet region and closer to atmospheric pressure in the outlet region. ρg is the gravitational volume force, obtained by multiplying the fluid density and gravitational acceleration, with the gravitational acceleration taken as 9.81 m / s². 2This force causes the fluid to tend to flow under gravity, especially significantly affecting the flow velocity in the vertical direction. τij is the stress tensor, reflecting the viscous shear effect inside the fluid. For laminar flow, the stress tensor is proportional to the velocity gradient, and its value is determined by the dynamic viscosity and velocity distribution of the fluid. Si is the additional momentum loss source, a key term in simulating the resistance of the packing material to water flow. It includes viscous resistance and inertial resistance. Viscous resistance is proportional to the flow velocity and mainly affects the flow state in low-velocity regions, while inertial resistance is proportional to the square of the flow velocity and mainly affects the flow state in high-velocity regions. Dij and Cij are the viscous resistance and inertial resistance loss coefficient matrices, respectively. Their values ​​need to be determined based on the physical properties of the wetland packing material. For isotropic packing materials with uniform particle size, parameters such as particle size and porosity can be experimentally determined and then calculated using empirical formulas. For example, the viscous resistance coefficient can be obtained by... The inertial drag coefficient can be calculated through... Calculation, where The average particle size of the filler is The porosity of the packing material is used. The energy conservation equation further refines the thermodynamic description of the porous media model. By considering the enthalpy change of the fluid and solid, heat conduction, and various heat source terms, it ensures that the model can comprehensively reflect the energy transfer process within the wetland. Solving the equation requires coupling with the continuity equation. A pressure-velocity coupled algorithm is used through a CFD solver to iteratively solve for the velocity and pressure distribution at each grid node, accurately reflecting the momentum change and drag loss of the water flow within the packing layer. The technical effects achieved by the above implementation method are: accurate calculation of the momentum change and energy transfer of the fluid within the wetland; realistic simulation of the resistance effect of the packing material on the water flow; and a high degree of consistency between the flow field simulation results and the actual flow state, providing a reliable basis for optimizing the hydraulic performance of wetlands.

[0024] The parameters involved in the porous media model were obtained through matrix porosity measurement experiments, and the viscous drag coefficient and inertial drag coefficient were calculated based on the above governing equations. The specific calculated values ​​are shown in the table below: Traditional tracer experiments offer limited data acquisition dimensions, making it difficult to accurately capture the internal flow characteristics of the system and lacking detailed and clear information on key hydraulic parameters such as gas-liquid two-phase distribution and velocity vectors. In contrast, the CFD discrete phase model approach provides an intuitive basis for configuration optimization, and through statistical analysis of the trajectories of numerous massless tracer particles, it allows for more accurate calculation of residence time distribution curves, resulting in more precise quantification of hydraulic parameters.

[0025] Based on this, the discrete phase model adopts the Eulerian-Lagrange method, treating the fluid as a continuous phase and using the Eulerian method to describe its motion. Discrete phase particles are treated as tracer particles, and the Lagrange method is used to track their trajectories. This approach balances computational efficiency and simulation accuracy, accurately reflecting the overall flow characteristics of the continuous phase fluid while also obtaining microscopic residence time information through particle trajectories. The setting of massless inert particles means that the particles' own gravity and inertia have no effect on the fluid flow; they only follow the fluid's motion, ensuring that the particle trajectories accurately reflect the motion paths of fluid particles. The particle size is set to 1×10⁻⁻⁻⁶. 6 The size of the particle stream (m) is much smaller than the mesh size of the fluid computational domain, avoiding interference from particles with the fluid flow field. The surface source injection method involves uniformly distributing particle injection points at the wetland inlet cross-section. The number of injection points is determined by the inlet cross-section size and mesh density, ensuring that particles uniformly cover the entire inlet area and comprehensively characterize the motion of fluid particles at different locations. The simulation process employs continuous-phase steady-state calculation and selects a unidirectional coupling solution strategy, ignoring the reverse effect of discrete-phase particles on the continuous-phase flow field. After particle release, its motion is entirely dominated by the predetermined flow field; in this case, the discrete phase is "flow-following" in the traditional sense. The steady-state tracking mode is suitable for continuous and stable wetland operation. After particle injection, its trajectory is continuously tracked until the particle reaches the outlet or reaches the maximum tracking step count. The maximum tracking step count is set to 50,000, calculated based on the maximum possible water flow path length and average velocity of the wetland, ensuring that the particle can move completely to the outlet and avoiding trajectory interruption due to insufficient tracking steps. The number of injected particle streams is sufficiently large to ensure statistical representativeness and reduce the impact of random errors on the results. In actual simulations, the aforementioned parameters of the discrete phase model need to be precisely set in the CFD solver. After tracking is complete, the residence time data of all particles at the outlet are extracted. Statistical analysis is then used to obtain key parameters such as the residence time distribution curve, average residence time, and standard deviation of residence time, thereby evaluating the hydraulic efficiency and flow field uniformity of the wetland. The technical effect achieved by the above implementation method is that it can accurately obtain the residence time distribution data of fluid particles. The data has good accuracy and statistical representativeness, providing a reliable basis for the calculation and evaluation of wetland hydraulic performance indicators.

[0026] The unclear boundary condition configuration in traditional technical solutions leads to unreasonable boundary constraints in numerical solutions, affecting the accuracy of flow field simulation results. Therefore, the specific configuration of boundary conditions must be tailored to actual operating conditions and clearly defined: the velocity boundary setting at the left inlet face of the physical model needs to be calculated in conjunction with the effective volume of the wetland and the design hydraulic retention time to ensure that the wastewater has sufficient time to react with the packing material and microorganisms within the wetland. The formula for calculating the inlet velocity is u=Q / A, where Q is the design flow rate and A is the inlet cross-sectional area. The calculated velocity needs to be input into the CFD solver as the inlet boundary condition to ensure that the inlet flow rate meets the design requirements. The free outflow boundary at the right outlet face of the physical model is set at 101.3 kPa, which is standard atmospheric pressure and conforms to the environmental pressure conditions of actual wetland operation. The free outflow boundary means that the pressure at the outlet is fixed, and the fluid can flow freely without additional constraints, accurately reflecting the flow state at the wetland outlet. The shared topological boundary form in the porous media interface region refers to the connection between different packing layers using shared nodes. This ensures continuous fluid flow between different packing layers without pressure abrupt changes or flow interruptions. This boundary form can accurately simulate the transitional flow of fluid between packing layers with different resistance characteristics. The remaining boundaries are set as wall boundaries, with a no-slip condition, meaning the fluid velocity at the wall is 0. This realistically simulates the obstruction effect of the wetland pool wall on the water flow, preventing fluid penetration or slippage. The inlet and outlet particle tracking attribute is set to Escape, meaning particles leave the computational domain directly upon reaching the inlet or outlet boundary without further tracking. The wall particle tracking attribute is set to Reflect, meaning particles reflect upon impact with the wall, following the specular reflection law. This setting realistically reflects the interaction between fluid particles and the wall, ensuring the authenticity of particle trajectories. In practice, the above configurations must be precisely set in the boundary condition setting module of the CFD solver to ensure reasonable boundary constraints that conform to actual working conditions, providing reliable boundary condition support for numerical solutions. The technical effects achieved by the above implementation method are that the boundary constraints are highly consistent with the actual operating conditions of the wetland, the numerical solution process is stable, and the flow field simulation results can accurately reflect the actual flow state.

[0027] Traditional techniques often suffer from unclear discretization methods and termination conditions, leading to insufficient accuracy or low computational efficiency, failing to achieve a balance between accuracy and efficiency. Therefore, the discretization method configuration must consider both accuracy and efficiency: a pressure-based coupled solver is employed, suitable for simulating incompressible fluid flows. This solver can simultaneously resolve the continuity and momentum equations, avoiding convergence difficulties that may occur with separate solvers, and is particularly suitable for simulating low-velocity, incompressible wastewater flows in wetlands. A second-order upwind difference scheme is chosen for spatial discretization. This scheme offers higher computational accuracy than the first-order upwind difference scheme, more accurately capturing gradient changes in the flow field, reducing numerical dispersion and oscillations, and improving the accuracy of flow field simulation. Its core principle is to obtain the discrete value of the current node through quadratic interpolation of the function values ​​of adjacent grid nodes. The pressure-velocity coupling algorithm employs the SIMPLE algorithm, a classic pressure-velocity coupling algorithm in computational fluid dynamics. It achieves coupled pressure and velocity solutions through an iterative process of guessing the pressure field, solving the momentum equation, calculating the pressure correction equation, and correcting the pressure and velocity fields. This ensures that both the continuity and momentum equations are satisfied simultaneously, making it suitable for steady-state simulations of wetland flow fields. The momentum, turbulent kinetic energy, and dissipation rate equations are all discretized using a first-order upwind scheme. This scheme has good stability, avoids numerical oscillations, and ensures convergence of the solution process, making it particularly suitable for regions with complex flow states. Numerical solutions are executed using a professional CFD solver. Standard initialization involves setting the velocity, pressure, and other physical quantities in the computational domain to default initial values. For steady-state simulations, initial values ​​have a relatively small impact on the final results, but reasonable initial values ​​can accelerate convergence. Setting a calculation step count prevents the calculation from getting stuck in infinite iterations. A maximum calculation step count is typically set based on past simulation experience. If the convergence condition is not met even after reaching the maximum calculation step count, the model settings or parameters need to be checked or adjusted. The solution process stops when the residuals of all equations fall below a set threshold. Residuals are a key indicator of the solution error; smaller residuals result in higher accuracy. Setting the threshold requires a comprehensive consideration of simulation accuracy and computational efficiency, ensuring accuracy while avoiding inefficiency caused by over-computation. In practice, the discretization method and termination conditions must be precisely configured in the CFD solver's solution settings module. The residual curve's trend should be monitored in real-time during the solution process until the residuals meet the requirements or the maximum number of computation steps is reached. The technical effect achieved by this implementation method is that the numerical solution accuracy meets engineering requirements, computational efficiency is high, unnecessary computational waste is avoided, and accurate flow field simulation results can be obtained quickly.

[0028] In traditional techniques, unreasonable parameter settings in mesh generation lead to poor mesh quality, affecting the stability and accuracy of numerical solutions. Therefore, mesh generation needs to optimize core parameters: using hexahedral mesh elements offers good geometric symmetry and computational accuracy. Compared to tetrahedral mesh elements, it has smaller numerical discretization errors and higher solution stability, making it particularly suitable for structured mesh generation and significantly improving the accuracy of wetland flow field simulation. The basic size of the volume mesh is controlled within the range of 8mm to 12mm, determined based on the wetland's geometry and flow characteristics. Too small a size results in an excessive number of mesh elements, drastically increasing computational load and reducing efficiency; too large a size leads to insufficient discretization accuracy, failing to capture detailed changes in the flow field. This range strikes a balance between accuracy and efficiency. The wall surface, the edge of the internal baffle, and the interface layer of the packing are areas of drastic flow changes, prone to complex flow phenomena such as large velocity gradients and flow separation. Setting a boundary layer and performing local mesh refinement can effectively improve the discretization accuracy of these key areas. The number of boundary layer layers is set to 3 to 5, with the height of the first layer being 0.5 mm to 1 mm, and the height of each subsequent layer increasing proportionally. The mesh size in the refined area is 1 / 3 to 1 / 2 of the overall mesh size, ensuring accurate capture of complex flow field details. In practice, professional meshing software is required. First, import the 3D geometric model and the computational fluid dynamics domain, set the meshing parameters, and generate a structured hexahedral mesh. Then, local refinement is performed on the key areas. After generating the mesh, the mesh quality needs to be checked, mainly evaluating the mesh distortion and aspect ratio, ensuring that the mesh distortion is below 0.8 and the aspect ratio is less than 5. For poor-quality meshes, optimization and adjustment are required until the requirements are met before importing them into the CFD solver for numerical solution. The technical effects achieved by the above implementation method are excellent mesh quality, satisfactory discretization accuracy, stable numerical solution process, and accurate and reliable flow field simulation results.

[0029] Traditional technical solutions often fail to effectively incorporate hydraulic efficiency considerations when determining the overall size, structural composition, and layout of key components of wetland systems. This can easily lead to uneven flow distribution within the system, inducing short-circuiting and dead zones. This not only results in insufficient contact efficiency between wastewater and the packing material but also causes disordered dissolved oxygen distribution, ultimately adversely affecting the stability of treatment effects and operational efficiency.

[0030] Based on this, this embodiment provides a wave-shaped subsurface flow constructed wetland system, employing any of the aforementioned CFD-based hydraulic optimization methods for constructed wetlands. The system has a cuboid structure, 0.9m long, 0.3m wide, and 0.35m high, and includes an inlet zone, a wave-shaped subsurface flow reaction zone, and an outlet zone. The partitioning of the inlet, wave-shaped subsurface flow reaction, and outlet zones ensures a clear flow path for wastewater within the wetland and defines the function of each zone. The main function of the inlet zone is uniform water distribution and preliminary oxygenation. The wave-shaped subsurface flow reaction zone is the core area for pollutant removal, and the outlet zone is used to collect and discharge treated wastewater. The inlet of the inlet zone is located at the bottom. Wastewater enters from the bottom and flows upwards, passing through an overflow weir into the wave-shaped subsurface flow reaction zone. The height of the overflow weir is determined according to the design water level to ensure a stable water level in the inlet zone, achieving uniform water distribution. Simultaneously, the wastewater forms a cascade as it crosses the overflow weir, increasing the contact area between the wastewater and air, achieving preliminary oxygenation, and increasing the dissolved oxygen content in the inlet water. Three vertically positioned guide vanes in the corrugated subsurface flow reaction zone divide the zone into four independent functional compartments. The guide vanes are positioned below the wetland's design water level, allowing wastewater to flow alternately up and down between compartments, creating a corrugated flow path and extending the actual residence time. The guide vanes are made of corrosion-resistant, high-strength plastic or stainless steel, with a thickness of 5mm to 10mm, ensuring structural stability. Three layers of packing fill each functional compartment, forming a three-dimensional reaction space. Functional packing columns are located in the second compartment, a critical area for water flow, ensuring full contact between the packing and wastewater and maximizing its carbon source release. An overflow plate in the effluent zone is positioned near the corrugated subsurface flow reaction zone, at the same height as the overflow weir in the influent zone, ensuring a stable water level in the wetland. Treated wastewater enters the effluent zone through the overflow plate and is discharged through the outlet, located at the bottom of the effluent zone for rapid wastewater removal and to prevent water accumulation. In actual construction, the wetland pool body needs to be constructed according to the design dimensions, using corrosion-resistant and aging-resistant materials such as fiberglass and concrete. Then, the inlet, overflow weir, guide plate, packing layer, functional packing column, overflow plate, and outlet are installed sequentially, ensuring that each component is firmly installed and well-sealed to prevent leakage or short-circuiting of wastewater. The technical effect achieved by the above implementation method is that the wetland system has a reasonable structure, uniform hydraulic flow, few dead zones, and sufficient contact between wastewater and the packing material, creating favorable conditions for pollutant removal.

[0031] In traditional technical solutions, the material, particle size, thickness, and formulation design of the packing layer are not clearly defined, resulting in poor microbial attachment of the packing and failing to meet the denitrification requirements of wastewater with low carbon-to-nitrogen ratios.

[0032] Based on this, the three-layer packing material, from bottom to top, consists of a pebble support layer, a quartz sand main functional layer, and a gravel plant layer. The material selection, particle size, and thickness design of each layer are determined based on the functional positioning of the packing material and CFD optimization results. The pebble support layer, located at the bottom, primarily supports the upper packing material and ensures smooth water flow. Its particle size is 30mm to 50mm, possessing high porosity and mechanical strength, effectively preventing the loss of upper packing material. Its 50mm thickness ensures stable support. The quartz sand main functional layer, located in the middle, is the core area for pollutant removal. Its quartz sand particle size is 1.5mm to 3mm, with a large specific surface area, providing ample attachment sites for microorganisms. Its 200mm thickness ensures sufficient contact time between wastewater and the packing material, improving pollutant removal efficiency. The gravel plant layer, located at the top, has a particle size of 8mm to 13mm and moderate porosity, providing support for the root growth of wetland plants without hindering water flow. Its 50mm thickness facilitates plant planting and growth. The functional packing column consists of a solid-phase novel biomass packing material and a packing support device. The solid-phase novel biomass packing material uses alkali-pretreated calamus and β-hydroxybutyric acid-β-hydroxyvalerate copolymer as the main carbon-releasing raw materials. The alkali-pretreated calamus is obtained by soaking in sodium hydroxide solution; this pretreatment disrupts the cell wall structure of the calamus, improving carbon source release efficiency. β-hydroxybutyric acid-β-hydroxyvalerate copolymer is a biodegradable polymer material that can slowly release carbon. The two are mixed in a certain proportion as the main carbon-releasing raw materials to meet the carbon source requirements of the denitrification process. Polyvinyl alcohol-sodium alginate hydrogel serves as the cross-linking framework, possessing good biocompatibility and a porous structure. It can fix the carbon-releasing raw materials and provide attachment sites for microorganisms. The freeze-crosslinking process involves freezing the mixture and then performing a crosslinking reaction to form a stable porous structure. The particle size is controlled at 20 mm to ensure that the packing particles are evenly distributed in the wastewater and in full contact with the wastewater. In actual preparation, it is necessary to strictly mix the raw materials according to the formula ratio, control the freezing temperature and cross-linking time, and ensure the stability of the functional filler's performance. When filling the filler layer, it is necessary to lay it evenly in layers with moderate compaction to avoid uneven porosity. When filling the functional filler column, the prepared solid-phase novel biomass filler must be evenly loaded into the support device to ensure the permeability of the filler column. The technical effect achieved by the above implementation method is that the filler layer has excellent microbial attachment performance and the carbon source matrix release characteristics are continuously stable, which can meet the denitrification requirements of low carbon-to-nitrogen ratio wastewater.

[0033] In traditional technical solutions, the material and structural design of the filler support device are unreasonable, and the plant planting parameters and functional zoning configurations are unclear, resulting in inconvenient filler replacement, poor plant growth, and the inability to form clearly defined anaerobic, hypoxic, and aerobic zones.

[0034] Based on this, the main body of the packing support device is a hollow tubular component made of polyvinyl chloride (PVC). PVC is corrosion-resistant, lightweight, and high-strength, making it suitable for wastewater treatment environments. The inner diameter of the hollow tubular component is determined according to the particle size of the functional packing material, ensuring smooth filling and replacement. The tube wall is evenly distributed with 5mm diameter through-holes. The number and density of these through-holes are determined based on the water flow velocity and the carbon source release requirements of the packing material, ensuring that wastewater can smoothly enter the device and contact the functional packing material, while also ensuring that the carbon source is evenly released into the wastewater. The inner surface is covered with a 30-50 mesh nylon filter screen, which prevents the loss of functional packing particles without affecting the flow of wastewater and carbon source. The mesh size of the filter screen must balance filtration efficiency and permeability.

[0035] The three-layer packing structure consists of a pebble support layer, a quartz sand main functional layer, and a gravel plant layer, arranged from bottom to top. The pebble support layer has a particle size of 30mm to 50mm and a thickness of 50mm. The quartz sand main functional layer has a particle size of 1.5mm to 3mm and a thickness of 200mm. The gravel plant layer has a particle size of 8mm to 13mm and a thickness of 50mm. The functional packing column is composed of a solid-phase novel biomass packing material and a packing support device. The solid-phase novel biomass packing material uses alkali-pretreated calamus and β-hydroxybutyric acid-β-hydroxyvalerate copolymer as the main carbon-releasing raw material, and polyvinyl alcohol-sodium alginate hydrogel as the cross-linking skeleton. It is prepared into a granular material with a controllable porous structure through a freeze cross-linking process, with a particle size controlled at 20mm.

[0036] The main body of the packing support device is a hollow tubular component made of polyvinyl chloride. The tube wall is evenly distributed with 5mm diameter through-holes, and the inner surface is covered with a 30-50 mesh nylon filter. Both ends are equipped with removable sealing end caps. Sweet flag is planted within the gravel plant layer at a density of 2 plants per reaction compartment. The system's internal structure is optimized through spatial partitioning and packing material gradation, integrating clearly defined anaerobic, anoxic, and aerobic zones. The removable sealing end caps at both ends are connected by threads or snaps, facilitating the filling, replacement, and maintenance of the packing material. The end caps are made of the same material as the tubular components, ensuring the structure's corrosion resistance and sealing performance. Sweet flag (Acorus calamus) is a common wetland plant with good pollution tolerance and root oxygen secretion capacity, supplementing dissolved oxygen in wetland systems and promoting nitrification. The planting density of 2 plants per reaction compartment is determined based on the area of ​​the reaction compartment and the plant's growth needs, ensuring sufficient growing space while fully utilizing its ecological functions. The anaerobic, anoxic, and aerobic zones within the system are formed through spatial configuration zoning and optimized packing material gradation. Different compartments in the wave-shaped subsurface flow reaction zone create different oxygen environments due to variations in water flow velocity and dissolved oxygen content. Differences in the particle size and porosity of the packing material layers further reinforce this zoning. The cobblestone support layer and the quartz sand main functional layer have relatively low porosity and slow water flow velocity, easily forming anaerobic and anoxic zones. The gravel plant layer has higher porosity, and oxygen secretion from plant roots creates an aerobic zone. This zoning of different oxygen environments provides a stable microenvironment for the nitrification-denitrification nitrogen removal process. During actual installation, the packing material support device must be vertically fixed in the second reaction compartment, ensuring the orifices are oriented correctly and aligned with the water flow direction. When planting calamus, healthy seedlings should be selected, planted at a depth of 10mm to 15mm, ensuring close contact between the roots and the gravel plant layer. During system operation, the sealing of the packing material support device and the integrity of the filter screen must be checked regularly, and any failed functional packing material should be replaced promptly to maintain plant growth. The technical effects achieved by the above implementation method are convenient system maintenance, good plant growth, clear and stable functional zoning, providing a suitable microenvironment for denitrification reaction, and improving the stability of wastewater treatment effect.

[0037] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A CFD-based hydraulic optimization method for constructed wetlands, characterized in that, include: S1. Construct a three-dimensional geometric model based on the actual structural characteristics of the constructed wetland and extract the computational fluid domain; S2. Perform structured mesh generation on the computational fluid domain; S3. Establish the steady-state laminar flow control equations, porous media model and discrete phase model based on pressure solution. The porous media model is associated with the wetland matrix resistance characteristics, and the discrete phase model is used to obtain the residence time distribution of fluid particles. S4. Set the velocity boundary, free outflow boundary, and wall boundary, and configure the discretization method; S5. Perform numerical solutions and monitor the convergence and divergence of the equations; S6. Post-process the simulation results to extract and calculate hydraulic performance evaluation indicators, including dead zone ratio, effective volume ratio, and water flow divergence. S7. When the dead zone ratio and hydraulic performance do not meet the design specifications, adjust the number of wetland guide plates, the packing gradation sequence, or the matrix layer thickness ratio, and repeat steps S1-S6 until the design specifications are met.

2. The CFD-based hydraulic optimization method for constructed wetlands according to claim 1, characterized in that, The continuity equation involved in the porous media model is: In the formula, , , These represent the velocity components in the x, y, and z directions, respectively, in m / s; t is time, in seconds; and ρ is the fluid density, in kg / m³. 3 ; The momentum conservation equations involved in the porous medium model are: ; In the formula, P is the static pressure, with units of Pa, and ρ g This is a gravitational volume force, with units of N / m. 3 , ij For stress tensor, The additional momentum loss source is the momentum source phase in the i-direction (x,y,z), which includes viscous drag and inertial drag loss source terms; the viscous drag and inertial drag loss source terms satisfy: In the formula, D ij and C ij These are the loss coefficient matrices for viscous drag and inertial drag, respectively. The energy conservation equations involved in the porous media model are: ， In the formula, the subscripts f and s refer to fluid and solid, respectively; ε represents the porosity of the medium; h represents enthalpy; J j S is the diffusion flux of component j; S is the volumetric heat source term; k eff The effective thermal conductivity of the medium is denoted by ; the governing equation is . In the formula, k f and k s Thermal conductivity of fluids and solid media.

3. The CFD-based hydraulic optimization method for constructed wetlands according to claim 1, characterized in that, The discrete phase model uses an Eulerian-Lagrange description, assuming the particles are massless inert particles with a diameter of 10⁻⁻⁶. 6 m is injected into the fluid domain in a surface source manner, and a unidirectional coupling solution strategy is adopted. Particle trajectory tracking adopts a steady-state tracking mode, and the maximum number of tracking steps is set to 50,000. The number of injected particle flows is large enough to ensure statistical representativeness.

4. The CFD-based hydraulic optimization method for constructed wetlands according to claim 1, characterized in that, The specific boundary conditions are configured as follows: the inlet surface at the left end of the physical model is set as a velocity boundary, and the liquid phase velocity is set according to the hydraulic residence time; the outlet surface at the right end of the physical model is set as a free outflow boundary, and the outlet pressure is set to 101.3 kPa; the porous media interface region adopts a shared topological boundary form; all other boundaries are set as wall boundaries; the inlet and outlet particle tracking attributes are set to Escape, and the wall tracking attributes are set to Reflect.

5. The CFD-based hydraulic optimization method for constructed wetlands according to claim 1, characterized in that, The discretization method is configured as follows: a pressure-based coupled solver is used, the spatial discretization scheme is a second-order upwind difference scheme, the pressure-velocity coupling uses the SIMPLE algorithm, and the momentum equation, turbulent kinetic energy and dissipation rate equations are all discretized using a first-order upwind scheme; the numerical solution is executed through a CFD solver, the number of calculation steps is set after standard initialization, and the solution stops when the residuals of all equations are lower than the set threshold.

6. The CFD-based hydraulic optimization method for constructed wetlands according to claim 1, characterized in that, The mesh generation adopts regular hexahedral mesh units, and the basic size of the volume mesh is controlled within the range of 8mm to 12mm. For areas with significant flow characteristics such as the wall surface, the edge of the internal baffle, and the interface layer of the filler, boundary layers are set and local mesh refinement is performed. The total number of mesh units needs to be determined after the mesh independence is verified.

7. The CFD-based hydraulic optimization method for constructed wetlands according to claim 1, characterized in that, After the solution is completed, the calculation results are post-processed using Tecplot and EXCEL. The specific steps include: S7.1 Based on the solution results of AnsysFluent, Tecplot is used to perform flow field visualization analysis. First, isosurfaces are created, and liquid phase velocity distribution cloud maps and velocity vector maps are drawn on the surfaces; S7.2 After particle tracking is completed, the discrete phase particle data is captured by selecting the outlet boundary, and the .dpm file containing particle motion trajectory and residence time information is exported and imported into Excel for the calculation of hydraulic performance indicators.

8. The CFD-based hydraulic optimization method for constructed wetlands according to claim 1, characterized in that, A comprehensive analysis of the numerical simulation results of the wetland system flow regime was conducted to evaluate the influence of different numbers of compartments, different substrate filling sequences, and different substrate layer thickness ratios on the hydraulic performance of the system, and finally the configuration scheme with the optimal hydraulic performance of the system was determined.

9. A waveform subsurface flow constructed wetland system, applied to the development of the CFD-based constructed wetland hydraulic optimization method as described in any one of claims 1 to 8, characterized in that, The system has a cuboid structure, 0.9m long, 0.3m wide, and 0.35m high, and includes an inlet zone, a wave-shaped subsurface flow reaction zone, and an outlet zone. The inlet zone has an inlet, which allows water to enter the wave-shaped subsurface flow reaction zone from the top through an overflow weir. The wave-shaped subsurface flow reaction zone is divided into four reaction functional compartments by three guide plates, each filled with three layers of packing material. The second reaction compartment contains a functional packing column. The outlet zone has an overflow plate and an outlet.

10. The waveform subsurface flow constructed wetland system according to claim 9, characterized in that, The three-layer packing system consists of a pebble support layer, a quartz sand main functional layer, and a gravel plant layer, arranged from bottom to top. Functional packing columns are installed in between, and carbon source packing is configured according to the effluent quality requirements. The main body of the packing support device can be a hollow tubular component made of polyvinyl chloride, with 5mm diameter through holes evenly distributed on the tube wall, and the inner surface covered with a nylon filter screen. The system integrates clearly defined anaerobic, anoxic, and aerobic zones through spatial configuration zoning and packing gradation optimization.

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