A simulation analysis method for dynamic visualization of particle deposition on heat exchange surface

Abstract

The application discloses a kind of heat exchange surface particle deposition dynamic visualization simulation analysis method, belong to heat exchange surface particle deposition simulation field, this method includes to the grid division of heat exchange surface cold surface physical model, and determines depositable area;Based on simulation condition, set the inlet particle mass concentration and environmental parameter of flow field area;Set simulation duration, at each time step, the following operations are carried out: based on control equation calculation local flow field parameter, output particle deposition rate and particle denudation rate;According to particle deposition rate and particle denudation rate, obtain particle net deposition rate;According to particle net deposition rate, determine volume source term;According to volume source term, update dirt layer parameter, flow field parameter, depositable area and deposition dense area.The application solves the problem that existing method cannot truly reflect the dynamic influence of deposition layer on airflow flow characteristics.

Description

Technical Field

[0001] This invention belongs to the field of heat exchange surface particle deposition simulation, and particularly relates to a simulation analysis method for dynamic visualization of heat exchange surface particle deposition. Background Technology

[0002] Particle deposition is a common physical phenomenon in heat exchange equipment in industries such as power, chemical, and metallurgy. When an airflow containing solid particles flows through a heat exchange surface, if the particles adhere to and accumulate on the wall, a porous deposition layer will gradually form. Studies have shown that the deposition layer has limited impact on heat transfer in the early stages of formation, but as the operating time increases, the deposition layer thickens, and the pores inside are filled with air with extremely low thermal conductivity. Therefore, the effective thermal conductivity is much lower than that of the metal wall, ultimately leading to a significant increase in the overall thermal resistance of the deposition layer. An excessively thick deposition layer not only significantly reduces heat transfer efficiency but also narrows the flow channel, increases system pressure drop and energy consumption, and in severe cases, can even lead to performance degradation or forced shutdown of the heat exchange equipment.

[0003] Existing data indicates that particulate deposition can reduce heat exchanger efficiency by more than 30%, and increase system pressure drop by several times compared to clean conditions. In various industrial systems, energy efficiency losses due to deposition account for approximately 2.5% of global energy consumption, and over 50% of heat exchanger performance degradation is directly related to particulate deposition. Furthermore, the maintenance costs and downtime losses resulting from deposit cleaning are significant, accounting for approximately 0.25% of total plant operating costs. Therefore, accurate prediction and effective control of particulate deposition behavior are crucial for improving the energy efficiency and economic viability of industrial systems.

[0004] Currently, some models can predict particle deposition processes, but most treat the particle deposition layer as a "virtual layer," only estimating its thickness, thermal resistance, or some simple physical properties, failing to truly reflect the dynamic impact of the deposition layer on airflow characteristics. Although some improved methods attempt to introduce additional models or complex algorithms to address this issue, they often significantly increase model complexity and computational burden, limiting their practical application in multi-condition engineering scenarios. Summary of the Invention

[0005] In view of the above-mentioned shortcomings in the prior art, the present invention provides a simulation analysis method for dynamic visualization of particle deposition on heat exchange surfaces, which solves the problem that the existing methods cannot truly reflect the dynamic influence of the deposition layer on the airflow characteristics.

[0006] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is: a simulation analysis method for dynamic visualization of particle deposition on a heat exchange surface, comprising: constructing a cold surface physical model of the heat exchange surface; Determine the number of meshes required to meet the simulation accuracy, and mesh the physical model of the cold surface. Based on the simulated operating conditions, the inlet particulate matter mass concentration and environmental parameters of the flow field region were set. Initialize the depositable region and set the simulation duration. At each time step, perform the following operations on each grid: Local flow field parameters are calculated based on the governing equations, and particle deposition rate and particle erosion rate are output. The net particle deposition rate is obtained based on the particle deposition rate and particle erosion rate. Update the volume source term based on the net particle deposition rate; Determine whether UDMI_0 = 1 and UDMI_1 ≠ 0; UDMI_0 is a binary parameter used to determine whether the mesh is depositable, where 1 indicates depositable and 0 indicates non-depositable; UDMI_1 is a binary parameter used to determine whether the mesh is densely deposited, where 1 indicates non-dense deposition and 0 indicates dense deposition. If satisfied, update the deposition layer parameters and flow field parameters based on the volume source term, and determine whether the conditions are met. ≥ If so, update the depositable and densely deposited regions and proceed to the next time step simulation; otherwise, directly proceed to the next time step simulation. The volume fraction of the sedimentary particle phase; This represents the critical threshold for the volume fraction of sedimentary particles. If the conditions are not met, update the flow field parameters and determine whether the simulation duration has been reached. If yes, end the simulation; otherwise, proceed to the next time step.

[0007] Furthermore, the number of grids required to achieve the required simulation accuracy is the minimum value that satisfies the condition that the total mass of the deposition layer no longer changes when the number of grids is increased.

[0008] Furthermore, during the mesh generation, the near-wall surface is densified while satisfying the requirement of y+; where y+ is the dimensionless distance to the wall surface.

[0009] Furthermore, the expression for the governing equation is:

[0010]

[0011] in, The sign of the partial derivative; It is the volume fraction; For fluid density; For generalized variables; For time; For divergence operators; For velocity components; The generalized diffusion coefficient; Spatial coordinates; For volume source terms; For phase identification; It is a gas phase; It is a suspended particulate phase; It is a sedimentary granular phase; This refers to the volume fraction of the gas phase. This represents the volume fraction of the suspended particulate phase. This represents the volume fraction of the sedimentary particle phase.

[0012] Furthermore, the expression for the particle deposition rate is:

[0013]

[0014]

[0015]

[0016]

[0017]

[0018]

[0019]

[0020] in, The particle deposition rate; This represents the adhesion probability. The dimensionless deposition rate of the particles; The friction speed; This represents the mainstream concentration of particles; The surface adhesion coefficient; It is an exponential function with the natural constant as its base; It is the surface activation energy; It is the gas constant; Surface temperature; The velocity of the particles; The dimensionless depositional velocity under Brownian and vortex diffusion deposition mechanisms; The dimensionless depositional velocity under the turbulent swimming sedimentation deposition mechanism; The particle concentration is expressed in dimensionless form. is the dimensionless depositional velocity under gravity sedimentation deposition mechanism; The dimensionless depositional velocity under the thermophoretic sedimentation mechanism; The Brownian diffusion coefficient is used. The vortex diffusion coefficient is denoted as . Kinematic viscosity; The dimensionless distance to the wall; For the dimensionless relaxation time of the particles; The mean square velocity of the particles; Dynamic viscosity; Stokes-Cunningham slip correction factor; The particle diameter; air density; Particle density; It is the acceleration due to gravity; The angle between the direction of particle motion and the direction of gravity; The cosine sign; Thermophoretic diffusion coefficient; Air temperature; This is the distance from the heat exchange surface; This represents the local concentration of the particles.

[0021] Furthermore, the expression for the particle erosion rate is:

[0022] in, The particle erosion rate; The erosion constant is denoted by . The intensity factor of the sedimentary layer; This refers to the wall shear force. The thickness of the deposited layer.

[0023] Furthermore, the expression for the net particle deposition rate is:

[0024] in, This represents the net deposition rate of the particles. The particle deposition rate; The particle erosion rate is represented by .

[0025] Furthermore, the expression for the volume source term is:

[0026] in, This is the volumetric source term, which is the mass of particles transferred from the suspended particulate phase to the sedimentary phase per unit volume and per unit time. This represents the net deposition rate of the particles. The surface area of ​​the control volume, specifically referring to a mesh; To control the volume of the body.

[0027] Furthermore, the updated deposition layer parameters specifically refer to the total mass of the updated deposition layer and the thickness of the already deposited deposition layer:

[0028]

[0029] in, The total mass of the sedimentary layer; for( , The volume fraction of the deposited phase at ( ); for( , The density of the deposited phase at ( ); for( , The volume of the deposited phase at that location; The upper limit of the horizontal axis; The x-axis is the horizontal axis. The upper limit of the ordinate; The vertical axis is used as the coordinate. The thickness of the deposited layer; This represents the total volume of the deposited phase; The area of ​​the deposition surface.

[0030] Furthermore, the source phase formulas used when updating the flow field parameters include:

[0031]

[0032]

[0033]

[0034]

[0035] in, It is the mass source phase for the suspended particulate phase; This is the volumetric source term, which is the mass of particles transferred from the suspended particulate phase to the sedimentary phase per unit volume and per unit time. It is the mass source phase of the deposited granular phase; The momentum source phase in the x-direction of the suspended particulate phase; Let be the velocity component of the suspended particle phase in the x-direction; The y-direction momentum source phase is the suspended particulate phase; Let be the velocity component of the suspended particle phase in the y-direction; This is the momentum source term for the already deposited particles.

[0036] The beneficial effects of this invention are as follows: By studying the layer-by-layer accumulation and growth characteristics of sediment layers, which have been neglected in previous models, this invention proposes a dynamic visualization model that can accurately describe the spatiotemporal evolution of sediment layers. Based on the Eulerian multiphase flow framework, this method realizes the particle deposition process by adding source terms, eliminating the need for dynamic meshes or additional mathematical models, significantly reducing computational complexity and improving numerical stability. The calculation results show good agreement with experimental data in terms of sediment layer thickness and quality, providing a new and effective means for optimizing and controlling the antifouling structure of heat exchange surfaces from the perspective of particle deposition mechanism and structural evolution. Attached Figure Description

[0037] Figure 1 This is a flowchart of the method of the present invention.

[0038] Figure 2 This is a schematic diagram of the layer-by-layer growth mechanism of sedimentary layers.

[0039] Figure 3 This is a comparison chart of the calculated values ​​and experimental thickness data of this invention.

[0040] Figure 4 This is a graph showing the comparison between the calculated values ​​and experimental quality data of this invention.

[0041] Figure 5 This is a diagram showing the influence of the sediment layer on the flow field calculated by this invention.

[0042] Figure 6 This is a diagram showing the influence of the virtual sedimentary layer on the flow field, calculated using a traditional model. Detailed Implementation

[0043] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0044] like Figure 1 As shown, in one embodiment of the present invention, a simulation analysis method for dynamic visualization of particle deposition on a heat exchange surface includes: constructing a cold surface physical model of the heat exchange surface; Determine the number of meshes required to meet the simulation accuracy, and mesh the physical model of the cold surface. Based on the simulated operating conditions, the inlet particulate matter mass concentration and environmental parameters of the flow field region were set. Initialize the depositable region and set the simulation duration. At each time step, perform the following operations on each grid: Local flow field parameters are calculated based on the governing equations, and particle deposition rate and particle erosion rate are output. The net particle deposition rate is obtained based on the particle deposition rate and particle erosion rate. Update the volume source term based on the net particle deposition rate; Determine whether UDMI_0 = 1 and UDMI_1 ≠ 0; UDMI_0 is a binary parameter used to determine whether the mesh is depositable, where 1 indicates depositable and 0 indicates non-depositable; UDMI_1 is a binary parameter used to determine whether the mesh is densely deposited, where 1 indicates non-dense deposition and 0 indicates dense deposition. If satisfied, update the deposition layer parameters and flow field parameters based on the volume source term, and determine whether the conditions are met. ≥ If so, update the depositable and densely deposited regions and proceed to the next time step simulation; otherwise, directly proceed to the next time step simulation. The volume fraction of the sedimentary particle phase; This represents the critical threshold for the volume fraction of sedimentary particles. If the conditions are not met, update the flow field parameters and determine whether the simulation duration has been reached. If yes, end the simulation; otherwise, proceed to the next time step.

[0045] The number of grids required to achieve the required simulation accuracy is the minimum value that satisfies the following condition: the total mass of the sediment layer no longer changes when the number of grids is increased.

[0046] In this embodiment, the grid independence of the divided grid is verified, and several different numbers of grids are divided for comparative verification. When the total mass of the sediment layer no longer changes and the difference gradually stabilizes as the number of grids increases, the number of grids that meets the simulation accuracy can be obtained.

[0047] During the mesh generation, the near-wall surface is densified while satisfying the requirement of y+, where y+ is the dimensionless distance to the wall surface.

[0048] In this embodiment, a two-dimensional physical model is established using ICEM software. A quadrilateral structured mesh is used to divide the computational domain mesh, and the mesh near the wall is refined while satisfying the y+ requirement.

[0049] The expression for the governing equation is:

[0050]

[0051] in, The sign of the partial derivative; It is the volume fraction; For fluid density; For generalized variables; For time; For divergence operators; For velocity components; The generalized diffusion coefficient; Spatial coordinates; For volume source terms; For phase identification; It is a gas phase; It is a suspended particulate phase; It is a sedimentary granular phase; This refers to the volume fraction of the gas phase. This represents the volume fraction of the suspended particulate phase. This represents the volume fraction of the sedimentary particle phase.

[0052] In this embodiment, the entire flow field region is simulated and calculated using the continuity, momentum, and energy equations in FLUENT software. The general form of each governing equation is as follows:

[0053] The governing equations describe the generalized variables from left to right. The time-varying factors (transient term), convective transport caused by fluid flow (convective term), diffusion due to physical quantity gradients (diffusion term), and generation or consumption within the system (source term). By... By assigning different physical meanings, this general equation can be transformed into the mass equation, momentum equation, and energy equation, respectively, and then used to calculate the change in mass per unit volume, the change in fluid momentum (thus analyzing the velocity field and pressure field), and the distribution and evolution of energy (or temperature) within the system.

[0054] when When = 1, the equation is the mass conservation equation; when When the components are u, v, and w, which are the velocity components, the equation becomes the momentum equation; when... When the temperature is T, the equation is the energy conservation equation.

[0055] The expression for the particle deposition rate is:

[0056]

[0057]

[0058]

[0059]

[0060]

[0061]

[0062]

[0063] in, The particle deposition rate; This represents the adhesion probability. The dimensionless deposition rate of the particles; The friction speed; This represents the mainstream concentration of particles; The surface adhesion coefficient; It is an exponential function with the natural constant as its base; It is the surface activation energy; It is the gas constant; Surface temperature; The velocity of the particles; The dimensionless depositional velocity under Brownian and vortex diffusion deposition mechanisms; The dimensionless depositional velocity under the turbulent swimming sedimentation deposition mechanism; The particle concentration is expressed in dimensionless form. is the dimensionless depositional velocity under gravity sedimentation deposition mechanism; The dimensionless depositional velocity under the thermophoretic sedimentation mechanism; The Brownian diffusion coefficient is used. The vortex diffusion coefficient is denoted as . Kinematic viscosity; The dimensionless distance to the wall; For the dimensionless relaxation time of the particles; The mean square velocity of the particles; Dynamic viscosity; Stokes-Cunningham slip correction factor; The particle diameter; air density; Particle density; It is the acceleration due to gravity; The angle between the direction of particle motion and the direction of gravity; The cosine sign; Thermophoretic diffusion coefficient; Air temperature; This is the distance from the heat exchange surface; This represents the local concentration of the particles.

[0064] In this embodiment, the dimensionless deposition rate of particles is a key evaluation parameter characterizing particle deposition behavior on the wall surface. This parameter provides a unified and quantifiable basis for the deposition prediction model. Using this parameter, the total particle deposition rate at the wall surface can be comprehensively predicted under different operating conditions (such as flow rate, temperature, particle size, etc.), thereby effectively assessing deposition risk and providing theoretical support for the anti-deposition or deposition-promoting design of equipment structures. The particle deposition mechanism on the wall surface mainly consists of four types: Brownian and vortex diffusion, turbulent sedimentation, gravity sedimentation, and thermophoretic sedimentation.

[0065] The expression for the particle erosion rate is:

[0066] in, The particle erosion rate; The erosion constant is denoted by . The intensity factor of the sedimentary layer; This refers to the wall shear force. The thickness of the deposited layer.

[0067] In addition to deposition, particles already attached to the wall surface may also be carried away from the surface by airflow, a process known as particle ablation.

[0068] The expression for the net particle deposition rate is:

[0069] in, This represents the net deposition rate of the particles. The particle deposition rate; The particle erosion rate is represented by .

[0070] By combining the two processes of deposition and erosion, the net deposition rate per unit time and per unit area can be calculated.

[0071] The expression for the volume source term is:

[0072] in, This is the volumetric source term, which is the mass of particles transferred from the suspended particulate phase to the sedimentary phase per unit volume and per unit time. This represents the net deposition rate of the particles. The surface area of ​​the control volume, specifically referring to a mesh; To control the volume of the body.

[0073] In this embodiment, to couple the net deposition flux in the Eulerian multiphase flow model, this wall flux needs to be converted into a mass source term acting on the fluid element. That is, the area flux needs to be converted into the rate of change of mass per unit volume. Therefore, the corresponding volume source term is in the form of: .

[0074] The parameters for the updated sedimentary layer specifically refer to the total mass of the updated sedimentary layer and the thickness of the already deposited sedimentary layer:

[0075]

[0076] in, The total mass of the sedimentary layer; for( , The volume fraction of the deposited phase at ( ); for( , The density of the deposited phase at ( ); for( , The volume of the deposited phase at that location; The upper limit of the horizontal axis; The x-axis is the horizontal axis. The upper limit of the ordinate; The vertical axis is used as the coordinate. The thickness of the deposited layer; This represents the total volume of the deposited phase; The area of ​​the deposition surface.

[0077] In this embodiment, the quality and thickness of the deposited layer can be calculated using a user-defined function (UDF) and stored in user-defined memory (UDM). In this invention, a volume fraction greater than 10... -6 The region is defined as the sedimentary layer region.

[0078] When updating the flow field parameters, the source phase formulas used include:

[0079]

[0080]

[0081]

[0082]

[0083] in, It is the mass source phase for the suspended particulate phase; This is the volumetric source term, which is the mass of particles transferred from the suspended particulate phase to the sedimentary phase per unit volume and per unit time. It is the mass source phase of the deposited granular phase; The momentum source phase in the x-direction of the suspended particulate phase; Let be the velocity component of the suspended particle phase in the x-direction; The y-direction momentum source phase is the suspended particulate phase; Let be the velocity component of the suspended particle phase in the y-direction; This is the momentum source term for the already deposited particles.

[0084] In this embodiment, during the particle deposition process, there is a mass per unit volume and per unit time. kg of material is transferred from the suspended particulate phase to the sedimentary phase. This process can be analogized to interphase mass transfer. The four source phase formulas involved in the calculation are as follows: Mass source phase of suspended particulate phase ; Mass source phase of sedimentary granular phase ; Momentum source phase in the x-direction of suspended particulate phase ; The momentum source phase in the y-direction of the suspended particulate phase ; Assuming the deposited particles are in a static state, i.e. =0, therefore its momentum source term can be ignored: .

[0085] In this embodiment, the accumulation process of the ash layer is mainly constrained by two core physical mechanisms. First, the growth of the ash layer exhibits a typical layer-by-layer depositional characteristic. Since particles cannot achieve self-suspension in the gas phase, new deposits must rely on the support provided by the ash layer already formed below. Therefore, the deposition process is characterized by bottom-up, step-by-step stacking, rather than isolated floating depositional behavior. Second, during the formation and evolution of the ash layer, the depositional mode tends to stabilize, and the geometric filling characteristics between particles no longer change significantly after a certain thickness. Therefore, its macroscopic porosity can be approximated as constant, meaning that the structure of the sedimentary layer does not undergo significant compaction or loosening changes during growth. Accordingly, when the sediment volume fraction of a local unit exceeds a threshold, the excess particles will generate a new sedimentary layer upwards, thereby driving a continuous increase in the overall thickness.

[0086] This invention proposes the concept of "layer-by-layer growth" to describe the accumulation pattern of ash layers. This method can effectively reveal the dynamic evolution mechanism of particle deposition. Figure 2 As shown, the generation of the gray layer can be divided into four stages: the initial stage ( When the dust concentration is 0, the dust-laden airflow passes over the surface without any deposition; during the dust accumulation time... A sparse sedimentary layer begins to form on the wall surface. < ); until time +1, the lower layer gradually densifies, and the volume fraction of local sediments reaches a threshold, triggering the formation of a new layer; as time evolves to... +2, the sedimentary layer continues to densify, and a new layer is formed on top until the maximum particle deposition time is reached.

[0087] In the specific numerical implementation, there is no particle deposition in the initial stage (corresponding to...). Figure 2 In (a) of the model, the near-wall mesh is marked with DEFINE_INIT (UDMI_0=1) to define the depositable region and establish the initial conditions for the deposition calculation. Subsequently, the DEFINE_ADJUST macro is executed iteratively at each time step, calculating local flow field parameters (velocity, temperature, turbulence, energy, etc.) to output the deposition rate and erosion rate, and further obtaining the net deposition rate and volumetric source term, thus achieving dynamic updates of the particle deposition rate. When UDMI_0=1 and UDMI_1≠0 is satisfied, it indicates that the element is still in a depositable state and the pores are not completely filled, allowing new particles to continue to accumulate; at this time, the model updates the deposition layer parameters and flow field parameters, iteratively correcting the deposition layer thickness and porosity. If the conditions are not met, the current deposition layer parameters remain unchanged, only the flow field is updated and the time step is advanced. This continues until the maximum computation time is reached. During the time evolution process, critical criteria are used... ≥ The model determines the stacking state of local cells. When the volume fraction exceeds a threshold, it triggers a UDMI update to distinguish between "deposited areas" and "depositable areas," thereby promoting the generation of new layers above and achieving the layer-by-layer accumulation and continuous evolution of the ash layer (corresponding to...). Figure 2 (c) and Figure 2 In (d) of this embodiment, =1- .

[0088] To verify the accuracy of the model, this invention used a self-built experimental platform to conduct comparative verification of the established model, focusing on analyzing the variation of the thickness and mass of the particle deposition layer in the horizontal wind channel over time.

[0089] The experimental section is 1000 mm long and has a cross-sectional dimension of 120 mm × 120 mm. The bottom heating zone is 100 mm long, and the surface temperature is kept constant. Typical experimental conditions include four parameter combinations: Condition 1: Inlet particulate matter mass concentration (… The concentration of heat exchanger is 0.1 g / m³, and the temperature of the heated wall surface is ( Condition 1 is 20℃; Condition 2 is =0.2g / m³, =30℃; Operating condition 3 is =0.3g / m³, =40℃; Operating condition 4 is =0.4g / m³, =50℃. All operating conditions were conducted under the following conditions: inlet air velocity 0.5 m / s, inlet temperature 20℃, and humidity 50%. The average particle diameter was 8.83 μm, and the density was 2346 kg / m³. 3 .

[0090] In the numerical simulation, the boundary conditions were consistent with the experimental setup: a velocity inlet on the left, a free outflow on the right, a constant-temperature heating section in the central region of the lower wall, and adiabatic conditions on the remaining wall surfaces. The calculation time step was 1 second, and the total simulation duration was 10 hours. The simulation was successful when the residuals of the continuity, momentum, and energy equations were all less than 10. -6 When the calculation is complete, it is determined that the calculation has converged.

[0091] Figure 3 and Figure 4 The model-predicted ash accumulation thickness is shown below. ) and quality ( A comparison with experimental measurements shows that the simulation results generally agree well with the experimental data, and the model accurately captures the dynamic process of the sedimentary layer transitioning from initial rapid growth to slow accumulation in the later stages. Especially in the middle and later stages of deposition, the model successfully reflects the inhibition of thickness growth caused by particle erosion, verifying the reliability of the deposition-erosion coupling model. Under different working conditions, the model can reasonably describe the dynamic evolution of the ash layer and correctly reflect the competitive relationship and dominant effect among various physical mechanisms. Overall, the simulation results are consistent with the experimental trends. Within a 10-hour ash accumulation period, the model's predicted sedimentary layer thickness error is controlled within ±10%, and the mass error is within 18%, indicating that the model has high prediction accuracy and stability during long-term deposition and is suitable for quantitative assessment and mechanism analysis of actual particle deposition processes.

[0092] The constructed particle deposition model was applied in practice to analyze the impact of particle deposition on the flow field on the heat exchange surface. The results are as follows: like Figure 5 As shown, based on the method proposed in this invention, the calculated deposition layer actually exists. The deposition of particles impedes the flow field, forcing streamlines to deflect along the surface of the deposition layer. And as... Figure 6 The results shown are from traditional models. Because these models typically treat the sedimentary layer as virtual, neglecting its structural evolution during actual deposition, they fail to capture the feedback effects of particle deposition on flow and heat transfer. The comparative results more fully demonstrate that the calculation method of this invention is closer to the actual situation of particle deposition.

[0093] This invention proposes a "layer-by-layer growth" concept, which can realistically reflect the dynamic evolution of sedimentary layers on heat-transferring surfaces. Traditional models typically treat sedimentary layers as virtual, ignoring their structural evolution characteristics during actual accumulation and failing to capture the feedback effects of sedimentary layers on flow and heat transfer. This invention introduces a sedimentary phase volume fraction threshold as a judgment condition. When the volume fraction of local sedimentary particles exceeds the critical value, a new layer is automatically triggered, thereby achieving physical modeling of the bottom-up, layer-by-layer accumulation behavior of sedimentary layers. This method not only restores the support mechanism in sedimentary layer formation but also dynamically captures the deposition inhibition phenomenon caused by erosion, significantly improving the physical realism and predictive ability of the model.

[0094] This invention couples the deposition and erosion processes within the Eulerian multiphase flow framework using source terms, eliminating the need for dynamic meshes or additional complex sub-models. This significantly reduces computational complexity and solution burden while maintaining accuracy. Compared to existing highly complex models, this method exhibits good numerical stability and engineering applicability. Experimental data validates that the model's prediction error for deposition layer thickness is controlled within ±10% over a 10-hour deposition period, with a quality error below 18%. It accurately reflects the dynamic process of deposition layer transitioning from rapid accumulation to slow growth under various operating conditions, making it suitable for the quantitative assessment of long-term deposition behavior in real-world industrial environments.

[0095] The dynamic visualization model constructed in this invention can output key parameters such as deposition layer thickness, quality, and porosity in real time through user-defined functions (UDFs) and user-defined memory (UDMs), enabling visualized tracking of the deposition process and structural evolution analysis. This method provides a reliable numerical analysis tool for optimizing the antifouling structure of heat exchange surfaces and formulating operational control strategies. It helps guide the design and energy-saving operation and maintenance of heat exchange equipment from a mechanistic perspective, effectively mitigating the energy efficiency degradation and operational risks caused by particle accumulation, and possesses significant engineering application value.

Claims

1. A simulation analysis method for dynamic visualization of particle deposition on a heat exchange surface, characterized in that, include: Construct a physical model of the cold surface of the heat exchange surface; Determine the number of meshes required to meet the simulation accuracy, and mesh the physical model of the cold surface. Based on the simulated operating conditions, the inlet particulate matter mass concentration and environmental parameters of the flow field region were set. Initialize the depositable region and set the simulation duration. At each time step, perform the following operations on each grid: Local flow field parameters are calculated based on the governing equations, and particle deposition rate and particle erosion rate are output. The net particle deposition rate is obtained based on the particle deposition rate and particle erosion rate. Update the volume source term based on the net particle deposition rate; Determine whether UDMI_0 = 1 and UDMI_1 ≠ 0; UDMI_0 is a binary parameter used to determine whether the mesh is depositable, where 1 indicates depositable and 0 indicates non-depositable; UDMI_1 is a binary parameter used to determine whether the mesh is densely deposited, where 1 indicates non-dense deposition and 0 indicates dense deposition. If satisfied, update the deposition layer parameters and flow field parameters based on the volume source term, and determine whether the conditions are met. ≥ If so, update the depositable and densely deposited regions and proceed to the next time step simulation; otherwise, directly proceed to the next time step simulation. The volume fraction of the sedimentary particle phase; This represents the critical threshold for the volume fraction of sedimentary particles. If the conditions are not met, update the flow field parameters and determine whether the simulation duration has been reached. If yes, end the simulation; otherwise, proceed to the next time step.

2. The simulation analysis method for dynamic visualization of particle deposition on heat exchange surfaces according to claim 1, characterized in that, The number of grids required to achieve the required simulation accuracy is the minimum value that satisfies the following condition: when the number of grids is increased, the total mass of the sediment layer no longer changes.

3. The simulation analysis method for dynamic visualization of particle deposition on heat exchange surfaces according to claim 1, characterized in that, During the mesh generation, the near-wall surface is densified while satisfying the requirement of y+, where y+ is the dimensionless distance to the wall surface.

4. The simulation analysis method for dynamic visualization of particle deposition on a heat exchange surface according to claim 1, characterized in that, The expression for the governing equation is: in, The sign of the partial derivative; It is the volume fraction; For fluid density; For generalized variables; For time; For divergence operators; For velocity components; The generalized diffusion coefficient; Spatial coordinates; For volume source terms; For phase identification; It is a gas phase; It is a suspended particulate phase; It is a sedimentary granular phase; This refers to the volume fraction of the gas phase. This represents the volume fraction of the suspended particulate phase. This represents the volume fraction of the sedimentary particle phase.

5. The simulation analysis method for dynamic visualization of particle deposition on heat exchange surfaces according to claim 1, characterized in that, The expression for the particle deposition rate is: in, The particle deposition rate; This represents the adhesion probability. The dimensionless deposition rate of the particles; The friction speed; This represents the mainstream concentration of particles; The surface adhesion coefficient; It is an exponential function with the natural constant as its base; It is the surface activation energy; It is the gas constant; Surface temperature; The velocity of the particles; The dimensionless depositional velocity under Brownian and vortex diffusion deposition mechanisms; The dimensionless depositional velocity under the turbulent swimming sedimentation deposition mechanism; The particle concentration is expressed in dimensionless form. is the dimensionless depositional velocity under gravity sedimentation deposition mechanism; The dimensionless depositional velocity under the thermophoretic sedimentation mechanism; The Brownian diffusion coefficient is used. The vortex diffusion coefficient is denoted as . Kinematic viscosity; The dimensionless distance to the wall; For the dimensionless relaxation time of the particles; The mean square velocity of the particles; Dynamic viscosity; Stokes-Cunningham slip correction factor; The particle diameter; air density; Particle density; It is the acceleration due to gravity; The angle between the direction of particle motion and the direction of gravity; The cosine sign; Thermophoretic diffusion coefficient; Air temperature; This is the distance from the heat exchange surface; This represents the local concentration of the particles.

6. The simulation analysis method for dynamic visualization of particle deposition on a heat exchange surface according to claim 1, characterized in that, The expression for the particle erosion rate is: in, The particle erosion rate; The erosion constant is denoted by . The intensity factor of the sedimentary layer; This refers to the wall shear force. The thickness of the deposited layer.

7. The simulation analysis method for dynamic visualization of particle deposition on a heat exchange surface according to claim 1, characterized in that, The expression for the net particle deposition rate is: in, This represents the net deposition rate of the particles. The particle deposition rate; The particle erosion rate is represented by .

8. The simulation analysis method for dynamic visualization of particle deposition on a heat exchange surface according to claim 1, characterized in that, The expression for the volume source term is: in, This is the volumetric source term, which is the mass of particles transferred from the suspended particulate phase to the sedimentary phase per unit volume and per unit time. This represents the net deposition rate of the particles. The surface area of ​​the control volume, specifically referring to a mesh; To control the volume of the body.

9. The simulation analysis method for dynamic visualization of particle deposition on a heat exchange surface according to claim 1, characterized in that, The parameters for the updated sedimentary layer specifically refer to the total mass of the updated sedimentary layer and the thickness of the already deposited sedimentary layer: in, The total mass of the sedimentary layer; for( , The volume fraction of the deposited phase at ( ); for( , The density of the deposited phase at ( ); for( , The volume of the deposited phase at that location; The upper limit of the horizontal axis; The x-axis is used for coordinates. The upper limit of the ordinate; The vertical axis is used as the coordinate. The thickness of the deposited layer; This represents the total volume of the deposited phase; The area of ​​the deposition surface.

10. The simulation analysis method for dynamic visualization of particle deposition on a heat exchange surface according to claim 1, characterized in that, When updating the flow field parameters, the source phase formulas used include: in, It is the mass source phase for the suspended particulate phase; This is the volumetric source term, which is the mass of particles transferred from the suspended particulate phase to the sedimentary phase per unit volume and per unit time. It is the mass source phase of the deposited granular phase; The momentum source phase in the x-direction of the suspended particulate phase; Let be the velocity component of the suspended particle phase in the x-direction; The y-direction momentum source phase is the suspended particulate phase; Let be the velocity component of the suspended particle phase in the y-direction; This is the momentum source term for the already deposited particles.

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