A scene selection method for a spiral-wound membrane water inlet screen

Abstract

This invention discloses a scenario-based selection method for feed screens of spiral wound membrane systems, comprising: determining the dominant fouling type of the target system; obtaining core hydrodynamic characteristic parameters of the screen related to membrane fouling control; establishing scenario-based matching rules for different fouling types to achieve accurate selection of the feed screen; and applying the matched screen to the spiral wound membrane system. This invention solves the problem that existing general-purpose screens cannot accommodate different fouling conditions through bidirectional adaptation between fouling scenarios and screen configurations, effectively suppressing membrane fouling, delaying flux decay, and improving the long-term operational stability of spiral wound membrane systems.

Description

Technical Field

[0001] This invention relates to the field of spiral wound membrane separation water treatment technology, and in particular to a scenario-based selection method for spiral wound membrane inlet screens. Background Technology

[0002] Spiral wound membrane elements are the core components of nanofiltration and reverse osmosis water treatment systems, and the feed screen is a key component of spiral wound membrane elements, playing a crucial role in separating the membrane sheets, constructing the flow channels, and regulating the flow field. The geometric configuration of the feed screen directly determines the hydrodynamic conditions within the membrane flow channels, thus having a decisive impact on the inorganic scaling and biofouling processes on the membrane surface.

[0003] However, in existing technologies, the selection of inlet screens often adopts a universal approach of "one configuration adapting to all operating conditions," without considering the differentiated hydrodynamic requirements of different fouling formation mechanisms. The optimal screen configuration for inorganic scaling is often unsuitable for operating conditions dominated by biological fouling, and vice versa. This results in existing screen selection schemes failing to achieve an optimal balance between fouling control effectiveness and operating energy consumption, leading to problems such as rapid flux decline, short cleaning cycles, and high operating costs during long-term membrane system operation. Summary of the Invention

[0004] This invention provides a scenario-based selection method for spiral wound membrane inlet screens, comprising the following steps: S1. Based on the influent water quality parameters and operating condition characteristics of the target system, determine and identify the dominant pollution type, which includes inorganic scaling dominant condition and biological pollution dominant condition. S2, for the target inlet barrier, the core hydrodynamic characteristic parameters of the barrier are obtained by combining computational fluid dynamics (CFD) numerical simulation with experimental verification; S3. Based on the dominant pollution type of the target system and the hydrodynamic characteristics of the screen, establish a matching relationship between pollution scenarios and screen configurations: for inorganic scaling-dominated operating conditions, match an inlet screen with high shear and high mass transfer efficiency; for biological pollution-dominated operating conditions, match an inlet screen with the smallest proportion of low flow velocity area. S4, apply the selected mesh to the spiral wound membrane element and water treatment system.

[0005] Further, step S1 specifically includes: S11, Collect the basic operating parameters and feed water quality parameters of the target spiral wound membrane system. The basic operating parameters include, but are not limited to, system operating pressure, feed water crossflow rate, temperature, recovery rate, and membrane flux; the feed water quality parameters include, but are not limited to, scale-causing cation concentration, total hardness, total alkalinity, pH value, total organic carbon, total bacterial count, and turbidity. S12, based on the collected parameters, uses multivariate statistical analysis methods to quantify the contribution weights of different pollution factors and determine the dominant pollution type. The multivariate statistical analysis methods include, but are not limited to, principal component analysis, variance decomposition analysis, and redundancy analysis.

[0006] Further, step S2 specifically includes: S21, Determine the CFD numerical simulation computation domain and mesh generation scheme for the target mesh; S22, set fluid properties and boundary conditions to complete the numerical simulation of hydrodynamics and solute transport; S23, calculate and extract the core hydrodynamic characteristic parameters of the target mesh, including but not limited to channel porosity, low velocity region ratio, average wall shear stress of the membrane surface, average mass transfer coefficient, and concentration polarization index. S24. Experimentally verify the hydrodynamic parameters obtained from the simulation to ensure the accuracy of the parameters.

[0007] Further, in step S3, the high membrane shear stress refers to an average wall shear stress ≥ 3.8 Pa, and the high mass transfer efficiency refers to an average mass transfer coefficient ≥ 1.7 × 10⁻ 5 m / s, wherein the low concentration polarization refers to a concentration polarization index ≤ 1.85.

[0008] Furthermore, in step S3, the low velocity region percentage refers to the region whose flow velocity in the channel is less than 0.5 times the average inlet velocity, accounting for ≤10.0% of the total volume.

[0009] Furthermore, the spiral wound membrane element includes one or more of spiral wound reverse osmosis membrane elements, spiral wound nanofiltration membrane elements, and spiral wound ultrafiltration membrane elements.

[0010] This invention achieves precise adaptation of the membrane grid configuration to the pollution scenario by determining the dominant pollution type, obtaining hydrodynamic parameters, and selecting a configuration based on the specific scenario. This effectively suppresses membrane fouling, slows down flux decay, and improves the long-term operational stability of the spiral wound membrane system. Attached Figure Description

[0011] Figure 1 A schematic diagram of the overall process of the scenario-based selection method of the present invention is shown.

[0012] Figure 2 A schematic diagram of a sub-process for obtaining hydrodynamic parameters of the isolation net according to the present invention is shown.

[0013] Figure 3 The diagram shows a comparison of the normalized flux decay of embodiments of the present invention and comparative examples under inorganic scaling conditions.

[0014] Figure 4 A bar chart comparing the average mass transfer coefficients of embodiments of the present invention and comparative examples is shown. Detailed Implementation

[0015] This specific embodiment is merely an exemplary description of the technical solution of the present invention, used to clearly and completely describe the implementation ideas and operation process, and does not constitute a limitation on the scope of protection. The actual scope of protection of the present invention shall be determined by the claims.

[0016] To address the problem that existing universal selection schemes for inlet screens cannot adapt to different pollution conditions and are difficult to balance pollution control effects and operating energy consumption, the core concept of this invention is to establish a complete method for selecting screen configurations based on the differentiated hydraulic control paths of inorganic scaling and biological pollution, combining pollution characteristics and hydrodynamic parameters, so as to achieve precise adaptation of inlet screens to application scenarios.

[0017] The following is in conjunction with the appendix Figure 1 The technical solution of the present invention will be described in complete and clear detail, including the following steps: S1. Based on the influent water quality parameters and operating condition characteristics of the target system, determine and identify the dominant pollution type, which includes inorganic scaling dominant condition and biological pollution dominant condition. S2, for the target inlet barrier, the core hydrodynamic characteristic parameters of the barrier are obtained by combining CFD numerical simulation and experimental verification; S3. Based on the dominant pollution type of the target system and the hydrodynamic characteristics of the screen, establish a matching relationship between the pollution scenario and the screen configuration to complete the accurate selection of the inlet screen. S4, apply the selected mesh to the spiral wound membrane element and water treatment system.

[0018] Step S1 further includes the following sub-steps:

[0019] S11, Collect the basic operating parameters and feed water quality parameters of the target spiral wound membrane system. The basic operating parameters include, but are not limited to, system operating pressure, feed water crossflow velocity, operating temperature, operating recovery rate, and membrane flux design value; the feed water quality parameters include, but are not limited to, total concentration of scale-causing cations, as well as total hardness, total alkalinity, pH value, total organic carbon, total bacterial count, turbidity, and conductivity.

[0020] Among them, scale-causing cations include, but are not limited to, calcium ions, magnesium ions, barium ions, and strontium ions.

[0021] S12, based on the collected influent water quality and operating condition parameters, uses multivariate statistical analysis to quantify the contribution weight of different pollution factors to system pollution and determine the dominant pollution type.

[0022] In at least one possible implementation, inorganic pollution characteristic factors and biological pollution characteristic factors are extracted from the influent water quality parameters; the independent contribution and interactive contribution ratio of the two types of pollution characteristic factors to the overall pollution of the system are quantified, and the dominant pollution type of the system is determined by the pollution factor with the highest contribution weight.

[0023] The inorganic contamination characteristic factors include, but are not limited to, scale-causing cations, total hardness, and total alkalinity; the organic contamination characteristic factors include, but are not limited to, total organic carbon content and total number of microbial colonies.

[0024] The multivariate statistical analysis methods include, but are not limited to, principal component analysis, variance decomposition analysis, and redundancy analysis. Other equivalent pollution contribution quantification methods in this field may also be used.

[0025] Step S2, refer to Appendix Figure 2 Specifically, it also includes the following sub-steps:

[0026] S21, Determine the CFD numerical simulation computation domain and mesh generation scheme for the target mesh.

[0027] In at least one possible implementation, the mesh flow channel of the spiral wound membrane element is simplified to a flat flow channel structure, ignoring the influence of the membrane element curvature on the flow field.

[0028] In at least one possible implementation, the computational domain is selected with 3×5 repeating grid cells to balance simulation accuracy and computational cost. An unstructured grid is used to discretize the computational domain, and the grid near the partition wire is refined. Based on the above settings, grid independence is verified, using the average flow velocity in the flow channel and the pressure drop in the inlet channel as evaluation indicators. When the number of grid cells increases, the calculation deviation of these indicators should not exceed 5% to ensure simulation accuracy.

[0029] S22: Set fluid properties and boundary conditions to complete the numerical simulation of hydrodynamics and solute transport.

[0030] In at least one possible implementation, fluid flow is solved using the continuity equation and the Navier-Stokes equation, while solute transport is solved using the convection-diffusion equation. Since the membrane permeation rate is much lower than the crossflow rate in the system channels, a no-slip wall boundary is provided on the membrane surface.

[0031] S23, calculate and extract the core hydrodynamic characteristic parameters of the target mesh.

[0032] Based on the simulation results, core hydrodynamic characteristic parameters directly related to membrane fouling control are calculated and extracted, including but not limited to channel porosity, Reynolds number, average wall shear stress on the membrane surface, average mass transfer coefficient, concentration polarization index, and low velocity region ratio.

[0033] For example, for inorganic fouling conditions, the average wall shear stress, average mass transfer coefficient, and concentration polarization index of the membrane surface are extracted; for biofouling conditions, the proportion of low flow rate regions is extracted.

[0034] The expressions for the relevant indicators are as follows: ; ; ; ; ; ; ; ; ; in, The porosity of the flow channel. The total volume of the flow channel. The volume of the inlet mesh in the flow channel. The hydraulic diameter, This refers to the flow channel height (mesh thickness). This refers to the surface area of ​​the inlet mesh. The effective cross-sectional area of ​​the flow channel. For the flow channel width, It is the effective inlet flow rate. It's inbound traffic. It is the Reynolds number. It is fluid density. It is the dynamic viscosity of the fluid. It is the local mass transfer coefficient. It is the solute diffusion coefficient. It is the solute concentration at the membrane wall. It refers to the solute concentration in the bulk. It is the concentration gradient of the solute at the membrane wall along the direction perpendicular to the membrane surface (y direction). It is the average mass transfer coefficient. It is the surface area of ​​a single computational unit, and 𝐴 is the total membrane area. It is the concentration polarization index. It is the average solute concentration on the membrane surface. It is the average solute concentration in the bulk solution. It is the ratio of low-velocity regions. Represents a flow velocity less than The low-velocity region, below this threshold, corresponds to a region with sufficiently low shear stress that is conducive to initial scaling.

[0035] S24. Experimentally verify the hydrodynamic parameters obtained from the simulation to ensure the accuracy of the parameters.

[0036] In at least one possible implementation, a cross-flow filtration experimental device is used to conduct hydraulic performance tests, measuring the pressure drop (FCP) of the inlet channel under different meshes at a set flow rate. The results are then compared with simulation calculations to verify the accuracy of the numerical model. A threshold of no more than 10% relative deviation between experimental and simulated values ​​is used to verify the reliability of the numerical model and hydrodynamic parameters. Alternatively, based on engineering experience, a mature CFD simulation scheme validated by the industry can be directly adopted.

[0037] Step S3 further includes the following sub-steps:

[0038] S31 is designed for operating conditions dominated by inorganic scaling, and is preferentially matched with inlet water mesh with high shear and high mass transfer efficiency.

[0039] The core control mechanism of inorganic scaling is to reduce the concentration boundary layer by increasing membrane shear stress and solute mass transfer efficiency, thereby inhibiting concentration polarization and reducing the potential for inorganic salt crystallization and growth. Therefore, for operating conditions dominated by inorganic scaling, influent screens with high membrane shear stress, high mass transfer efficiency, and low concentration polarization should be prioritized.

[0040] Furthermore, the high membrane shear stress refers to an average wall shear stress ≥ 3.8 Pa, and the high mass transfer efficiency refers to an average mass transfer coefficient ≥ 1.7 × 10⁻ 5 m / s, wherein the low concentration polarization refers to a concentration polarization index ≤ 1.85.

[0041] S32, for operating conditions dominated by biological pollution, prioritizes matching the inlet mesh with the smallest proportion of low flow velocity areas.

[0042] The core control mechanism for biofouling is to eliminate hydraulic dead zones within the flow channel, reduce the proportion of low-velocity areas, and eliminate favorable environments for microbial attachment and colonization, thereby inhibiting the formation and development of biofilms. Therefore, for operating conditions dominated by biofouling, inlet screens with a small proportion of low-velocity areas and good flow field uniformity should be prioritized.

[0043] Furthermore, the low-velocity region is defined as the region within the flow channel where the flow velocity is less than 0.5 times the average inlet velocity, accounting for ≤10.0% of the total volume.

[0044] To further verify the effectiveness of the method of the present invention, the following examples and comparative examples were set up, and all experimental conditions and parameters were kept consistent with the aforementioned steps.

[0045] This embodiment uses an inorganic scaling-dominated operating scenario as the verification case. The influent is a mixed solution of 50 mmol / L Na₂SO₄ and 50 mmol / L CaCl₂. A cross-flow filtration device is used, employing a DF30 nanofiltration membrane. The operating pressure is constant at 5 bar, and the influent cross-flow velocity is controlled at 0.12 m / s. The single-group experimental cycle is 300 minutes. Membrane flux is measured and normalized flux is calculated every 10 minutes. Simultaneously, channel pressure drop is measured and calculated per unit length of channel. All candidate screens maintain consistent thickness, wire diameter, wire spacing, and node diameter.

[0046] According to the method of this invention, a triangular mesh is selected as an example for inorganic scaling conditions, wherein the mesh units of this configuration are arranged perpendicular to the water flow direction. Conventional double-layer interwoven meshes and hexagonal meshes are selected as comparative examples.

[0047] See attached document Figure 3 This allows for a comparison of the decrease in normalized membrane flux over time under fouling conditions using different separators. Normalized membrane flux refers to the ratio of membrane flux at a given operating moment to the initial membrane flux. A higher ratio and slower decay indicate better anti-fouling performance of the membrane module corresponding to the separator. When the operating time reaches 300 minutes, the normalized membrane flux corresponding to the embodiment of this application remains stable at 0.442, while the normalized membrane flux of the comparative examples has rapidly decreased to 0.385 and 0.323, significantly lower than that of the embodiment.

[0048] See attached document Figure 4 The differences in average mass transfer coefficients within the flow channel corresponding to different screens can be compared. The average mass transfer coefficient characterizes the mass transfer efficiency and concentration polarization suppression capability within the flow channel; a higher coefficient indicates a more effective delay in solute enrichment on the film surface and a reduction in fouling tendency. The average mass transfer coefficient corresponding to the embodiments of this application can reach [value missing]. The average mass transfer coefficient of each comparative example is only , The mass transfer efficiency is significantly lower than that of the embodiments in this application, which fully demonstrates that the embodiments in this application have significant advantages in mass transfer enhancement.

[0049] It should be understood that the mesh scheme, boundary conditions, and parameter extraction methods of the CFD numerical simulation are all exemplary implementations and can be replaced by conventional equivalent means in the field, all of which fall within the protection scope of this invention.

[0050] It should be understood that the triangular mesh, hexagonal mesh, and other mesh configurations described in this application are merely exemplary selection objects and are not a limitation on the mesh structure; the arrangement of the triangular mesh perpendicular to the water flow direction in the embodiments is only a preferred implementation method. This invention does not exclude the application of triangular mesh in other arrangements such as parallel to the flow direction or tilted at any angle in this selection method. All schemes that use the scenario-based matching logic described in this invention to implement mesh selection are covered within the protection scope of this invention.

[0051] It should be understood that the number of components, steps, and parameter values ​​not specifically limited in this application can be one or more, with "multiple" referring to two or more. Unless otherwise expressly stated or limited, the terms "determination," "matching," "simulation," "extraction," "verification," and "selection" used in this application should be interpreted broadly to cover equivalent technical means and implementation methods in the art, and do not constitute an undue limitation on the present invention.

[0052] Those skilled in the art should understand that, without departing from the core concept of this invention, all conventional optimizations, equivalent substitutions, and adaptive adjustments made to the implementation steps, parameter values, and configuration selections should be covered within the scope of protection of this invention.

Claims

1. A scenario-based selection method for spiral wound membrane inlet screens, characterized in that, include: S1. Based on the influent water quality parameters and operating condition characteristics of the target system, determine and identify the dominant pollution type, which includes inorganic scaling dominant condition and biological pollution dominant condition. S2, for the target inlet screen, obtain the core hydrodynamic characteristic parameters of the screen related to membrane fouling control by combining computational fluid dynamics (CFD) numerical simulation and experimental verification; S3. Based on the dominant pollution type of the target system and the hydrodynamic characteristics of the screen, establish a matching relationship between pollution scenarios and screen configurations: for inorganic scaling-dominated operating conditions, match an inlet screen with high shear and high mass transfer efficiency; for biological pollution-dominated operating conditions, match an inlet screen with the smallest proportion of low flow velocity area. S4, apply the selected mesh to the spiral wound membrane element and water treatment system.

2. The method according to claim 1, characterized in that, Step S1 specifically includes: S11, Collect the basic operating parameters and feed water quality parameters of the target spiral wound membrane system. The basic operating parameters include, but are not limited to, system operating pressure, feed water crossflow rate, temperature, recovery rate, and membrane flux; the feed water quality parameters include, but are not limited to, scale-causing cation concentration, total hardness, total alkalinity, pH value, total organic carbon, total bacterial count, and turbidity. S12, based on the collected parameters, the contribution weights of different pollution factors are quantified through multivariate statistical analysis methods to determine the dominant pollution type; the multivariate statistical analysis methods include, but are not limited to, principal component analysis, variance decomposition analysis, and redundancy analysis.

3. The method according to claim 1, characterized in that, Step S2 specifically includes: S21, Determine the CFD numerical simulation computation domain and mesh generation scheme for the target mesh; S22, Set fluid properties and boundary conditions to complete the numerical simulation; S23, calculate and extract the core hydrodynamic characteristic parameters of the target mesh, including but not limited to channel porosity, low velocity region ratio, average wall shear stress of the membrane surface, average mass transfer coefficient, and concentration polarization index. S24. Experimentally verify the hydrodynamic parameters obtained from the simulation to ensure their accuracy.

4. The method according to claim 1, characterized in that: For operating conditions dominated by inorganic fouling, the high membrane shear stress refers to an average wall shear stress ≥ 3.8 Pa, and the high mass transfer efficiency refers to an average mass transfer coefficient ≥ 1.7 × 10⁻ 5 m / s, wherein the low concentration polarization refers to a concentration polarization index ≤ 1.85; For operating conditions dominated by biological contamination, the term "low-velocity region" refers to the region within the flow channel where the flow velocity is less than 0.5 times the average inlet velocity, accounting for ≤10.0% of the total volume.

5. The method according to claim 1, characterized in that, In step S4, the spiral wound membrane element includes one or more of spiral wound reverse osmosis membrane elements, spiral wound nanofiltration membrane elements, and spiral wound ultrafiltration membrane elements.

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