Steam generator primary side flow extraction method based on CFD simulation

Abstract

A steam generator primary side flow extraction method based on CFD simulation comprises the steps that a semicircular area where a steam generator heat transfer pipe is located is divided into a plurality of virtual areas, namely hot chamber fluid domains, and after numerical simulation based on a k-turbulence model is conducted on each hot chamber fluid domain to obtain a speed nephogram, the speed nephogram is calculated; and local flow velocity or mass flow at the inlet of each heat transfer pipe is obtained through position mapping and interpolation extraction. According to the method, the regional flow difference in the steam generator is accurately represented in the flow distribution process in a regional division mode, the problem that local regional differences cannot be distinguished by an average distribution method is effectively solved, and meanwhile, the limitation that a distribution method based on pressure drop is only suitable for different rows of pipelines is also overcome; the method has the characteristics of high automation degree and high processing efficiency, and is suitable for application scenes with high requirements on boundary condition precision in FIV and other single-tube modeling analysis.

Description

Technical Field

[0001] The present invention relates to a technology in the field of reactor control, in particular to a method for extracting the primary side flow of a steam generator based on CFD simulation. Background Art

[0002] Steam generators (SGs), core heat exchangers with high heat transfer efficiency and complex structures in pressurized water reactor (PWR) nuclear power plants, have a crucial influence on the accuracy of thermal-hydraulic calculations due to the coolant flow behavior on their primary side. Existing technologies for primary-side flow distribution in steam generator heat transfer tubes employ conventional average distribution methods that fail to account for the impact of structural factors such as tube density variations, support plate obstruction, and end effects on local flow distribution. Furthermore, average flow distribution is still employed for edge regions, disturbed areas, or areas affected by structural interference, failing to capture local deviations under real-world operating conditions. Furthermore, average boundary conditions cannot meet the precision requirements for subsequent analyses requiring precise boundary input, such as single-tube FIV response analysis and local wear prediction. Pressure drop-based distribution methods often rely on manual selection of pressure measurement points or analysis paths, making them inefficient for parallel analysis of large numbers of tubes and resulting in a high workload. Inlet flow distribution based on pressure drop is effective for heat transfer tubes of varying lengths (i.e., different rows), but ineffective for heat transfer tubes of the same length within the same row, thus failing to achieve global inlet flow distribution for heat transfer tubes. Summary of the Invention

[0003] In response to the above-mentioned deficiencies in the prior art, the present invention proposes a steam generator primary side flow extraction method based on CFD simulation. By dividing the regions, the regional flow differences inside the steam generator can be accurately characterized during the flow distribution process, effectively solving the problem that the average distribution method cannot distinguish local regional differences. At the same time, it also overcomes the limitation that the pressure drop-based distribution method is only applicable to different rows of pipes. The method has the characteristics of high degree of automation and high processing efficiency, and is suitable for application scenarios with high requirements on boundary condition accuracy in single-tube modeling analysis such as FIV.

[0004] The present invention is achieved through the following technical solutions:

[0005] The present invention relates to a method for extracting the primary side flow of a steam generator based on CFD simulation. The method divides the semicircular area where the heat transfer tubes of the steam generator are located into several virtual areas, namely, hot chamber fluid domains. After a numerical simulation based on the k-ɛ turbulence model is performed on each hot chamber fluid domain to obtain a velocity cloud map, the local flow velocity or mass flow at the inlet of each heat transfer tube is obtained through position mapping and interpolation extraction.

[0006] Technical Effects

[0007] This method distributes the inlet flow rates of heat transfer tubes from CFD numerical simulations of the steam generator's hot chamber, then uses a neighboring region algorithm and interpolation mathematical methods to determine the specific inlet flow rate for each heat transfer tube. Compared to existing technologies, this method accurately extracts and quantitatively distributes the inlet flow rates of all 10,025 heat transfer tubes within the steam generator. This effectively overcomes the limitations of traditional methods, which often lack observable flow rates and difficult to obtain boundary conditions in complex structures. This provides a highly accurate input foundation for subsequent thermal-hydraulic numerical simulations of multiple heat transfer tubes, analysis of local thermal behavior, and prediction of flow-induced vibrations. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 Flowchart of the present invention;

[0009] Figure 2 Schematic diagram of CFD numerical simulation results of the embodiment;

[0010] Figure 3 Schematic diagram of cloud map data extraction results in the embodiment. DETAILED DESCRIPTION

[0011] like Figure 1 As shown in FIG. 1 , this embodiment is directed to a thermal hydraulic numerical simulation problem of multiple heat transfer tubes of a steam generator, and a steam generator primary side flow rate extraction method based on CFD simulation is performed, including:

[0012] Step 1: Construct the hot chamber fluid domain. The thermal hydraulic numerical simulation problem of multiple heat transfer tubes of the steam generator is divided into several virtual areas, namely the hot chamber fluid domain. Specifically: Figure 2 In the semicircular area where the steam generator heat transfer tubes are located, a plurality of hot chamber fluid domains are arranged layer by layer at equal intervals by adjusting the radius.

[0013] The adjustment radius means: with the central vertical axis of the semicircular area where the heat transfer tube is located as the middle column, the center of the circle is placed one by one from bottom to top, and the row spacing is gradually adjusted to ensure that the top center of the circle is as close to the boundary of the semicircle as possible without crossing the boundary, thereby determining the maximum number of circles that can be accommodated and the corresponding optimal spacing.

[0014] The equal spacing arrangement layer by layer means: expanding to the left and right based on the height of the center of each layer, and dynamically adjusting the spacing according to the width of the semicircle at the current height when arranging horizontally, to ensure that all the centers of the circles are located inside the semicircle, and ultimately achieve symmetrical and non-overlapping coverage of the entire area, specifically including:

[0015] A) Equal spacing in the middle column: The middle column can be arranged at most A circle, then , then the inverse solution is , where: the height of the circle in the first row is r, is the optimal row spacing, and R is the radius of the semicircular tube sheet of the steam generator.

[0016] B) Equal spacing of each row: fixed height of each row Next, create as many circular areas as possible horizontally, and the outermost circle is still completely inside the semicircle. The height of the circle in the i-th row is ; At this height, the maximum lateral reach of the semicircle is: , each row is a cylindrical area arranged symmetrically according to the middle column. circles, the horizontal spacing is: ,in: is the maximum number of circles that can be accommodated in the i-th row, by setting the minimum spacing Judge, so the line spacing of the i-th row is: .

[0017] like Figure 2 As shown, there are 10025 heat transfer tube inlets of the hot chamber of the steam generator in this embodiment, and each line corresponds to a heat transfer tube.

[0018] Step 2: Perform independent CFD numerical simulations on each hot chamber fluid domain created in Step 1 using the k-ɛ turbulence model to obtain CFD simulation results, i.e., velocity contours, that characterize the flow characteristics of the primary-loop fluid in the hot chamber of the steam generator.

[0019] like Figure 2 As shown in the figure, the obvious non-uniform flow distribution of the primary loop fluid in the hot chamber and the deviation flow phenomenon under structural interference are shown, which intuitively shows the uniformity of the flow at the inlet of the primary loop of the heat transfer tube.

[0020] like Figure 3 As shown on the left, the velocity cloud map includes several thermal chamber fluid domains, and each thermal chamber fluid domain includes multiple random points and their corresponding simulation flow data.

[0021] Step 3: Extract cloud data: After exporting the CFD simulation results obtained in step 2 as a velocity cloud including several random points and their corresponding coordinates and flow data, the coordinates of the random points in the velocity cloud are converted to the coordinate system of the semicircular area where the heat transfer tube is located.

[0022] The export is preferably stored in a processable format (such as csv, xlsx).

[0023] Step 4: Position mapping. This involves using the nearest distance algorithm to determine the geometric center of the hot chamber fluid domain closest to each heat transfer tube in the velocity cloud. The plane coordinates of the heat transfer tube are then replaced with polar coordinates centered on this center. The polar diameters of all heat transfer tubes in their respective hot chamber fluid domains are then normalized to obtain a virtual point in the hot chamber fluid domain corresponding to each heat transfer tube in the velocity cloud.

[0024] like Figure 3 As shown in the figure, the blue font (1,101) represents the heat transfer tube located at the 1st row and 101th column. By searching in the adjacent area, the center of the fluid domain of the No. 14 hot chamber closest to it is obtained. After polar coordinate transformation and polar diameter normalization, it is mapped to a virtual point in the fluid domain of the No. 14 hot chamber, that is, the position of the five-pointed star mapped in the figure.

[0025] Step 5: interpolation extraction, that is, taking each virtual point as the center, the flow data of the random point in the fluid domain of the hot chamber in the velocity cloud map with the nearest distance are weighted averaged to obtain the flow data of each heat transfer tube.

[0026] The closest distance is preferably a random point that is in the first three to the first five distances from the virtual point.

[0027] The weighted average is obtained by weighted averaging the flow data of the random points, using the inverse of the distance between the random point and the virtual point as the weight.

[0028] As shown in Table 1, the primary side inlet flow data of multiple heat transfer tubes are shown. The first and second columns in the table represent the row and column values ​​of the heat transfer tubes, and the third column represents the primary circuit inlet flow value.

[0029] Table 1

[0030] Compared to existing technologies, this method uses the CFD method in step 2 to numerically simulate the fluid domain within the heat chamber, determining the fluid flow characteristics within the heat chamber and the non-uniformity of the inlet flow rates of 10,025 heat transfer tubes. Compared to existing methods that average the inlet flow rates of a single circuit, this method improves the simulation fidelity of multi-tube calculations. Subsequent steps ensure the accuracy of numerical extraction of the inlet flow rate for each heat transfer tube.

[0031] The above-mentioned specific implementation can be partially adjusted in different ways by those skilled in the art without departing from the principles and purpose of the present invention. The scope of protection of the present invention shall be based on the claims and shall not be limited by the above-mentioned specific implementation. All implementation schemes within its scope shall be subject to the constraints of the present invention.

Claims

1. A steam generator primary side flow extraction method based on CFD simulation, characterized in that: The semicircular area where the steam generator heat transfer tubes are located is divided into several virtual areas, namely the hot chamber fluid domains. A numerical simulation based on the k-ɛ turbulence model is performed for each hot chamber fluid domain to obtain a velocity contour map. The local flow velocity or mass flow rate at the inlet of each heat transfer tube is then obtained through position mapping and interpolation extraction.

2. The method for extracting the primary side flow of a steam generator based on CFD simulation according to claim 1 is characterized in that: include: Step 1: Construct a hot chamber fluid domain. The thermal hydraulic numerical simulation problem of multiple heat transfer tubes in a steam generator is divided into several virtual regions, namely, hot chamber fluid domains. Specifically, according to the semicircular area where the steam generator heat transfer tubes are located, several hot chamber fluid domains are arranged layer by layer with equal spacing by adjusting the radius. Step 2: Perform independent CFD numerical simulations on each hot chamber fluid domain created in Step 1 using the k-ɛ turbulence model to obtain CFD simulation results, i.e., velocity contours, that characterize the flow characteristics of the primary circuit fluid within the hot chamber of the steam generator. Step 3: Extracting cloud data: After exporting the CFD simulation results obtained in step 2 as a velocity cloud including several random points and their corresponding coordinates and flow data, the coordinates of the random points in the velocity cloud are converted to the coordinate system of the semicircular area where the heat transfer tube is located; Step 4: Position mapping. This involves using the nearest-distance algorithm to determine the geometric center of the hot chamber fluid domain closest to each heat transfer tube in the velocity cloud. The plane coordinates of the heat transfer tube are then replaced with polar coordinates centered on this center. The polar diameters of all heat transfer tubes in their respective hot chamber fluid domains are then normalized to obtain a virtual point within the hot chamber fluid domain in the velocity cloud corresponding to each heat transfer tube. Step 5: interpolation extraction, that is, taking each virtual point as the center, the flow data of the random point in the fluid domain of the hot chamber in the velocity cloud map with the nearest distance are weighted averaged to obtain the flow data of each heat transfer tube.

3. The method for extracting the primary side flow of a steam generator based on CFD simulation according to claim 2, wherein: The adjustment radius means: with the central vertical axis of the semicircular area where the heat transfer tube is located as the middle column, the center of the circle is placed one by one from bottom to top, and the row spacing is gradually adjusted to ensure that the top center of the circle is as close to the boundary of the semicircle as possible without crossing the boundary, thereby determining the maximum number of circles that can be accommodated and the corresponding optimal spacing.

4. The method for extracting the primary side flow of a steam generator based on CFD simulation according to claim 2 or 3, characterized in that: The described equal spacing arrangement means: expanding to the left and right based on the height of the center of each layer, and dynamically adjusting the spacing according to the semicircle width at the current height when arranging horizontally to ensure that all the centers of the circles are located inside the semicircle, ultimately achieving symmetrical and non-overlapping coverage of the entire area.

5. The method for extracting the primary side flow of a steam generator based on CFD simulation according to claim 2, wherein: The equal spacing arrangement layer by layer includes: A) Equal spacing in the middle column: The middle column has the most rows A circle, then , then the inverse solution is , where: the height of the circle in the first row is r, is the optimal row spacing, R is the radius of the semicircular tube sheet of the steam generator; B) Equal spacing of each row: fixed height of each row Next, create as many circular areas as possible horizontally, and the outermost circle is still completely inside the semicircle. The height of the circle in the i-th row is ; At this height, the maximum lateral reach of the semicircle is: , each row is a cylindrical area arranged symmetrically according to the middle column. circles, the horizontal spacing is: ,in: is the maximum number of circles that can be accommodated in the i-th row, by setting the minimum spacing Judge, so the line spacing of the i-th row is: .

6. The method for extracting the primary side flow of a steam generator based on CFD simulation according to claim 1 or 2, characterized in that: The velocity cloud map includes a plurality of thermal chamber fluid domains, and each thermal chamber fluid domain includes a plurality of random points and their corresponding simulation flow data.

7. The method for extracting the primary side flow of a steam generator based on CFD simulation according to claim 2, wherein: The closest distance is a random point that is three to five times closer to the virtual point.

8. The method for extracting the primary side flow of a steam generator based on CFD simulation according to claim 2, wherein: The weighted average is obtained by weighted averaging the flow data of the random points, using the inverse of the distance between the random point and the virtual point as the weight.

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