Balanced flowmeter structure optimization design method suitable for low-temperature medium

Abstract

The invention discloses a balance flowmeter structure optimization design method suitable for a low-temperature medium, relates to the technical field of balance flowmeter structure optimization, in particular to a balance flowmeter structure optimization design method suitable for the low-temperature medium, and provides a balance flowmeter structure optimization design method suitable for the low-temperature medium. The main technology involved in the invention comprises key technologies such as a low-temperature medium cavitation phase change refined flow simulation technology under a perforated plate throttling effect based on Fluent, a Fluent solver kernel calling technology based on Python, a parameter structure optimization technology based on a multi-target genetic algorithm and the like. According to the method, the internal flowing phase change condition of the balance flowmeter under the low-temperature medium is obtained through high-precision numerical simulation considering low-temperature medium phase change and two-phase flow, optimization iteration is conducted on multiple structure parameters of the balance flowmeter based on the multi-target genetic algorithm, and the design efficiency is greatly improved compared with a traditional single-factor structure optimization method.

Description

Technical Field

[0001] The invention relates to the technical field of structural optimization of balanced flowmeters, and in particular to a structural optimization design method of balanced flowmeters suitable for cryogenic media. Background Art

[0002] The balanced flowmeter is a differential pressure flow measuring instrument. It uses the throttling effect of the porous plate located in the straight tube to generate a pressure difference in the fluid passing through. The size of the pressure difference is related to the type of medium and the flow rate. After establishing the functional relationship between the pressure difference and the flow rate, the flow rate of the measured fluid can be obtained by measuring the pressure difference before and after the porous plate. The throttling element of the balanced flowmeter is a porous plate. The local pressure difference generated by throttling is the basis for the balanced flowmeter to measure the flow rate. At the same time, the throttling effect will also cause permanent pressure loss. Excessive local pressure drop will cause fluid cavitation, which is particularly obvious for low-temperature media. Permanent pressure loss will cause energy loss.

[0003] The core of the design of the balanced flowmeter lies in the design of the perforated plate throttling element, among which the main structural features include the distribution of the function holes (related to D0), the total opening area (related to the diameter of each circular hole), the number of holes, and the thickness of the orifice plate. The above features will affect the performance of the balanced flowmeter. Similar to the orifice plate flowmeter, the outflow coefficient C and the pressure loss coefficient ζ are usually used as its performance evaluation indicators.

[0004] The outflow coefficient C is the correction coefficient of the theoretical flow rate. The closer the value is to 1, the closer the measured flow rate is to the theoretical flow rate derived from the Bernoulli equation and the ideal fluid assumption. Its expression is:

[0005]

[0006] In the formula, q v is the volume flow rate, A is the pipe cross-sectional area, ρ is the fluid density, Δp is the pressure difference before and after the porous plate, and β is the equivalent diameter ratio:

[0007]

[0008] For non-standard porous plates, the flow coefficient C is difficult to obtain directly through theoretical methods and needs to be obtained indirectly through simulation calculation or actual measurement.

[0009] The pressure loss coefficient ζ reflects the permanent energy loss of the fluid through the porous balance plate, which is expressed by the permanent pressure loss coefficient between the far rear (the fluid is remixed after a certain distance after flowing through the porous plate) and the inlet. Its expression is:

[0010]

[0011] Where Δω is the pressure difference between the fully developed sections before and after the porous plate, which is taken as the static pressure difference between 2D upstream and 10D downstream of the porous plate, and u is the average flow velocity of the cross section 2D upstream of the porous plate.

[0012] When the Reynolds number is small, as the Reynolds number increases, the outflow coefficient of the balanced flowmeter shows a correlation with the Reynolds number; when the Reynolds number reaches the lower limit Re L After that, when the Reynolds number continues to increase, the outflow coefficient remains relatively constant; and when the Reynolds number continues to increase, there is an upper limit value Re U When the flow coefficient exceeds this value, cavitation occurs in the fluid. This self-similar region Re is independent of the Reynolds number. L ~Re U , which is the measurement range of the balanced flowmeter. For low-temperature media, compared with water, low-temperature fluids with low saturation temperature and small latent heat of vaporization are more prone to cavitation during throttling flow due to rapid velocity increase and large pressure drop. One of the goals of optimizing the structure of the balanced flowmeter is to widen the measurement range as much as possible, mainly to widen the upper limit of the Reynolds number Re U At the same time, for the purpose of economic energy saving, another goal of the balanced flowmeter structure optimization is to minimize the permanent pressure loss, that is, the pressure loss coefficient ζ is required to be as small as possible.

[0013] Compared with cavitation in room temperature fluids such as water, the physical mechanism behind low-temperature cavitation is more complicated. It is necessary to use high-precision numerical simulation considering gas-liquid phase change and two-phase flow to predict the flow conditions in the balanced flowmeter and obtain performance parameters.

[0014] The performance of balanced flowmeters is affected by multiple structural parameters, and the goal of structural optimization is not single. Traditional optimization design methods often use the control variable method in multiple simulation calculations to analyze and optimize a single structural parameter in turn, ignoring the coupling effect between multiple factors, and are time-consuming, labor-intensive, and inefficient. Therefore, there is an urgent need for a structural optimization design method for balanced flowmeters for cryogenic media. Summary of the invention

[0015] In view of the above problems, the present invention proposes a structural optimization design method for a balanced flowmeter suitable for cryogenic media. The main technologies involved in the present invention include key technologies such as the refined flow simulation technology of the cavitation phase change of cryogenic media under the throttling effect of the porous plate based on Fluent, the Fluent solver kernel calling technology based on Python, and the parameter structure optimization technology based on a multi-objective genetic algorithm. The present invention utilizes high-precision numerical simulation considering the phase change of cryogenic media and two-phase flow to obtain the internal flow phase change of the balanced flowmeter under cryogenic media, and optimizes and iterates multiple structural parameters of the balanced flowmeter based on a multi-objective genetic algorithm, which greatly improves the design efficiency compared to the traditional single-factor structural optimization method. The key process of the present invention is as follows:

[0016] 1. Extract the internal flow field of the balanced flowmeter, establish a three-dimensional parametric model, and control the parameters of the balanced flowmeter calculation domain geometry: D-flow channel inner diameter, PL1-orifice plate upstream pipe length, PL2-orifice plate downstream pipe length, n-number of holes (including 1 center hole and n-1 surrounding holes), d1-center hole diameter, d2-surrounding hole diameter, D0-circle diameter of the surrounding holes and h-orifice plate thickness. The above parameters can be fully controlled as shown in the attached manual Figure 1 The balanced flow meter structure shown in the figure generates the computational domain geometry for CFD calculation.

[0017] 2. The purpose of the initial simulation calculation is to set up the calculation model based on the prototype of the balanced flowmeter without structural optimization, and to establish a unified two-phase flow simulation model for the cryogenic medium. The simulation calculation is based on Fluent. Consider the high-precision numerical simulation of the phase change and two-phase flow of the cryogenic medium, including: grid division, turbulence model setting, two-phase flow model and cavitation model setting, phase change parameter setting according to the physical properties of the fluid (setting the corresponding curve of saturated vapor pressure and temperature), and boundary condition setting. For each geometric configuration, the internal flow characteristics at different Reynolds numbers are obtained through numerical calculation, where the Reynolds number upper limit Re of the stable range of the outflow coefficient C is U and pressure loss coefficient ζ are the key parameters that need to be obtained.

[0018] 3. Build an optimization design framework based on Python, and use the Python interface of CAD software and CFD software to realize the program's control of geometric models, generation of computational grids, adjustment of case parameters, and reading of result parameters. The optimization process involves the setting of constraint targets, the setting of objective functions, and iterative optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Attached Figure 1 The present invention is a flow chart of the structural optimization design method of a balanced flowmeter suitable for low-temperature media.

[0020] Attached Figure 2 It is a structural diagram of a balanced flow meter.

[0021] 1- Pipeline

[0022] 2-Multi-well plate

[0023] 3-Pressure hole 1

[0024] 4-Pressure hole 2

[0025] L1- The distance between pressure hole 1 and the center of the orifice plate

[0026] L2- The distance between pressure hole 2 and the center of the orifice plate

[0027] Attached Figure 3It is a structural diagram of the porous plate of the central throttling element of the balanced flowmeter.

[0028] D-Inner diameter of flow channel

[0029] d1-center hole diameter

[0030] d2-surrounding hole diameter

[0031] D0-The diameter of the distribution circle where the center of the surrounding holes is located

[0032] h-perforated plate thickness

[0033] n-number of holes (1 center hole and n-1 surrounding holes) DETAILED DESCRIPTION

[0034] A specific case is given below to illustrate the method for implementing the present invention.

[0035] 1. First, design a balanced flow meter prototype based on engineering experience (for example, n = 5, D0=0.6D,h=0.1D) is used as the initial value of the optimization design, and parameterized modeling is performed.

[0036] 2. Carry out high-precision numerical simulation considering phase change of cryogenic media and two-phase flow, including: fluid domain extraction, mesh division, turbulence model setting, two-phase flow model and cavitation model setting, phase change parameter setting according to fluid properties, boundary condition setting, calculation and analysis of results.

[0037] 3. Fully select a series of discrete points Re, re-set the boundary conditions in the previous step according to Re, and perform calculations to obtain the upper limit Re of the Reynolds number interval for the stable outflow coefficient C of the balanced flowmeter U and pressure loss coefficient ζ.

[0038] 4. Set constraints: Constrain the structural parameters (including the number of holes n, the center hole diameter d1, the surrounding hole diameter d2, the distribution circle diameter D0 of the surrounding holes, and the orifice plate thickness h) based on geometric conditions. The constraints are to ensure that the holes do not intersect or tangent to each other geometrically and that the edges of the distribution holes do not exceed the inner diameter of the pipe. Set upper and lower limits for each parameter based on engineering experience and actual processing.

[0039] 5. Set the objective function: to measure the upper limit of the Reynolds number Re U , pressure loss coefficient ζ are the objective functions, and the optimization goal is to make the former reach the maximum value and the latter reach the minimum value under the constraints.

[0040] 6. The multi-objective genetic algorithm NSGA-II and gradient optimization NLPQL are used in turn to perform global optimization and local gradient optimization on the optimization parameters, and iterative optimization is performed.

[0041] 7. During the iterative calculation process, the objective function is made to approach the expected value within the constraints. The calculation is stopped after the objective function is optimized or the set number of iterations is reached to obtain the optimized structural parameters.

Claims

1. A structural optimization design method for a balanced flowmeter suitable for cryogenic media is proposed. The main technologies involved in the present invention include the refined flow simulation technology of cavitation phase change of cryogenic media under the throttling effect of porous plates based on Fluent, the Fluent solver kernel calling technology based on Python, and the parameter structure optimization technology based on multi-objective genetic algorithm and other key technologies.

2. Build an optimization design framework based on Python, and use the Python interface of CAD software and CFD software to realize the program's control of geometric models, generation of computational grids, adjustment of case parameters, and reading of result parameters. The optimization process involves the setting of constraint targets, setting of objective functions, and iterative optimization.

3. In order to achieve the optimal design of the structural parameters of the balanced flowmeter, a three-dimensional parametric model needs to be established. The parameters that control the geometry of the balanced flowmeter calculation domain are: D-flow channel inner diameter, PL1-orifice plate upstream pipe length, PL2-orifice plate downstream pipe length, n-number of holes (including 1 center hole and n-1 surrounding holes), d1-center hole diameter, d2-surrounding hole diameter, D0-circle diameter of the surrounding holes and h-orifice plate thickness.

4. Carry out high-precision numerical simulation considering phase change of cryogenic medium and two-phase flow, including: Fluid domain extraction, meshing, turbulence model setting, two-phase flow model and cavitation model setting, phase change parameter setting according to fluid properties, boundary condition setting, calculation and analysis of results.

5. The internal flow characteristics at different Reynolds numbers are obtained through numerical calculation, where the upper limit of the Reynolds number Re of the stable range of the outflow coefficient C is U and the pressure loss coefficient ζ are the key parameters to be obtained. U , pressure loss coefficient ζ are the objective functions, and the optimization goal is to make the former reach the maximum value and the latter reach the minimum value under the constraints.

6. The multi-objective genetic algorithm NSGA-II and the gradient optimization NLPQL are used in turn to perform global optimization and local gradient optimization on the structural parameters of the balanced flowmeter. During the iterative calculation process, the objective function is made to approach the expectation within the constraints. The calculation is stopped after the objective function is optimized or the set number of iterations is reached to obtain the optimized structural parameters.

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