CN-121980665-A - Automatic simulation prediction system and method for aerodynamic characteristics of standard airflow temperature sensor

CN121980665ACN 121980665 ACN121980665 ACN 121980665ACN-121980665-A

Abstract

The automatic simulation prediction system and method for the aerodynamic characteristics of the standard airflow temperature sensor are suitable for measuring high-temperature gases of an aeroengine, a gas turbine and the like, and belong to the field of measurement and test. The system comprises a user input module, an input checking module, an automatic grid dividing module, an automatic loading boundary module, an automatic solving module and an automatic result analyzing module, wherein a full-flow automatic simulation framework from parameter input to result analysis is constructed based on PyFluent API and ANSYS Fluent deep integration, a simulation flow is decomposed into a plurality of independent functional modules, and the integrated simulation of the aerodynamic characteristic simulation of a standard airflow temperature sensor and the automatic extraction of key performance indexes, namely the integrated simulation of geometric introduction, intelligent grid division, dynamic boundary condition loading, self-adaptive solving and key performance indexes, is realized. The invention can improve the simulation efficiency and accuracy of the standard air flow temperature sensor and is beneficial to optimizing the standard air flow temperature sensor.

Inventors

WANG YUFANG
ZHANG XUETAO
CUI JIAHUI

Assignees

中国航空工业集团公司北京长城计量测试技术研究所

Dates

Publication Date: 20260505
Application Date: 20251128

Claims (8)

1. The automatic simulation prediction system for the aerodynamic characteristics of the standard airflow temperature sensor is characterized by comprising a user input module, an input check module, an automatic grid dividing module, an automatic loading boundary module, an automatic solving module and an automatic result analyzing module, wherein the modules realize seamless data transmission and intelligent flow coupling through PyFluent API to form closed-loop automatic simulation; The user input module is used for providing a Graphical User Interface (GUI) and a Command Line Interface (CLI), supporting parameterized input and batch task configuration, and is suitable for multi-working-condition simulation and optimization design; The input checking module automatically checks geometric models, material physical properties and working condition parameters input by a user based on a preset rationality threshold, and triggers a feedback mechanism to prompt the user to correct when the check is not passed; The automatic meshing module adopts a self-adaptive network meshing strategy based on characteristic dimensions and combines a network quality feedback mechanism to realize dynamic encryption and reconstruction; the automatic loading boundary module dynamically generates a boundary condition expression according to working condition parameters input by a user, and realizes real-time loading and updating of the boundary condition through PyFluent API; the automatic solving module is internally provided with a self-adaptive solving strategy, and automatically adjusts solving parameters and convergence criteria according to flow field characteristics; The automatic result analysis module integrates the automatic extraction of key performance indexes and the visual report generation function.
2. The automated simulation prediction system of aerodynamic characteristics of a standard airflow temperature sensor as set forth in claim 1, wherein the key performance indicators comprise flow field, temperature field data about the standard airflow temperature sensor.
3. The automated simulation prediction system of the aerodynamic characteristics of the standard airflow temperature sensor according to claim 2, wherein the user input module is used for providing a graphical user interface GUI and a command line interface CLI, inputting a geometric model, physical properties of materials, an incoming flow speed, an incoming flow total temperature and simulation setting of the standard airflow temperature sensor by a user, storing the geometric model, the physical properties of materials, the incoming flow speed, the incoming flow total temperature and the simulation setting by files for simulation; The input checking module performs rationality checking on parameters such as a geometric model, materials, physical properties of materials, incoming flow speed, total incoming flow temperature, simulation setting and the like input by the user input module item by item, wherein the checking of the geometric model is realized by adopting the secondary development of python on SPACECLAIM and is mainly used for checking whether a small face, an overlapped face, a closed face and a loophole exist in the model, and triggering a feedback mechanism when the checking is not passed, so as to prompt a user to correct; the automatic grid division module is used for realizing intelligent grid division of the geometric model of the standard airflow temperature sensor by calling an automatic function of ANSYS Fluent Meshing to generate a simulation grid; the automated loading boundary module interacts with Fluent software through PyFluent API to realize geometric import, grid division, boundary condition setting, solver configuration and solving calculation; The automatic solving module realizes the automatic operation of ANSYS Fluent by calling Pyfluent libraries, and ensures the smooth running of the simulation process; the automatic result analysis module is used for reading and processing result data output by ANSYS Fluent, and analyzing and visually displaying the data by utilizing Python calculation and visualization tools, and generating various charts and animations, so that users are assisted to intuitively understand simulation results.
4. The automated simulation prediction system of aerodynamic characteristics of a standard airflow temperature sensor according to claim 3, wherein the physical properties of the material comprise density, specific heat ratio, thermal conductivity and surface emissivity, the simulation setting comprises grid density and solver type, the physical properties of the material comprise density, specific heat ratio, thermal conductivity and surface emissivity, and the simulation setting comprises grid density and solver type.
5. The automated simulation prediction system of the aerodynamic characteristics of a standard airflow temperature sensor as set forth in claim 3, wherein the visualization tool comprises Pandas, matplotlib.
6. The automatic simulation prediction method for the aerodynamic characteristics of the standard airflow temperature sensor is realized based on the automatic simulation prediction system for the aerodynamic characteristics of the standard airflow temperature sensor as set forth in claim 1, 2, 3, 4 or 5, and is characterized by comprising the following steps: S1, inputting information including a geometric model, materials, physical properties, incoming flow speed and total incoming flow temperature of a standard air flow temperature sensor through a user input module, and realizing the user input of the geometric model, the physical properties, the incoming flow speed and the total incoming flow temperature of the standard air flow temperature sensor and simulation setting through the user input module, wherein the geometric model establishes the geometric model of the standard air flow temperature sensor by utilizing three-dimensional modeling software, comprises ball welding, even wires, shielding cases, vertical rods and cooling pipeline models of the standard air flow temperature sensor, and exports the established geometric model into a ANSYS SPACECLAIM compatible format, and stores the geometric model for simulation use; S2, an input checking module automatically checks parameters input by a user based on a preset rationality threshold, and specifically comprises a geometric model checking mechanism, a material physical property checking mechanism, a working condition parameter checking mechanism and a feedback mechanism; S3, calling Pyfluent a library through a Python script, starting ANSYS Fluent Meshing, loading a geometric model of a standard airflow temperature sensor, and carrying out grid division on a model surface of the standard airflow temperature sensor at the same time, wherein the grid size is set according to the characteristic size of the model of the standard airflow temperature sensor, and the characteristic size of the model of the standard airflow temperature sensor is the ball welding diameter of the standard airflow temperature sensor; S4, boundary condition generation and loading, wherein the boundary condition generation module constructs a dynamic boundary condition function based on working condition parameters input by a user; total press-in conditions: Wherein P 0 is the total inlet pressure, P ∞ is the incoming static pressure, gamma is the specific heat ratio, and Ma is the incoming Mach number; Radiation boundary conditions: q r ＝εσ(T 4 -T ∞ 4 ) wherein q r is radiant heat flux, ε is surface emissivity, σ is Stefan-Boltzmann constant; The dynamic loading mechanism loads the Expression into Fluent in real time through a PyFluent Named Expression function, so that dynamic updating of boundary conditions is realized; S5, calling Pyfluent a library through a Python script, starting ANSYS Fluent, loading a standard airflow temperature sensor grid model, setting physical parameters required by simulation, including density, viscosity and material and radiation coefficient of a standard airflow temperature sensor of fluid, setting parameters of a calculation solver, including iteration step number and convergence criteria, setting initial conditions, including an initial speed field and a pressure field, running the Python script, realizing automatic operation of the ANSYS Fluent through Pyfluent, performing simulation calculation of the standard airflow temperature sensor, monitoring simulation progress in real time in the calculation process, and outputting intermediate results according to requirements; S6, automatically extracting key performance indexes including a flow field, a pressure field and a speed field of a standard air flow temperature sensor by a result analysis module, integrating NumPy, matplotlib and Pandas, performing post-processing and analysis on result data, generating a multi-dimensional simulation report containing the key indexes, cloud pictures and curves, and displaying the flow field characteristics and the temperature field characteristics of the standard air flow temperature sensor; s7, based on an automatic simulation method, multiple-station simulation is performed by changing simulation parameters, simulation results under different working conditions are compared, and influences of the parameters on temperature measurement characteristics of the standard airflow temperature sensor are analyzed.
7. The method for automated simulation prediction of aerodynamic characteristics of a standard airflow temperature sensor according to claim 6, wherein in step S2, The geometric model check is used for calling ANSYS SPACECLAIM to carry out geometric integrity check and identifying whether facets, overlapped surfaces and non-closed bodies exist or not; The material physical property check is used for verifying whether the density, specific heat capacity and heat conductivity coefficient are within a reasonable range according to a material database; The working condition parameter check comprises whether the Mach number of the incoming flow is in a compressible flow range or not, and whether the total temperature is below the material tolerance temperature or not; The feedback mechanism is that if the check is not passed, the system automatically prompts the user to correct the non-conforming item and gives out a suggested value range.
8. The method for automated simulation prediction of aerodynamic characteristics of a standard airflow temperature sensor according to claim 7, wherein in step S7, The simulation parameters include incoming flow conditions, cooling water conditions and structural parameters.

Description

Automatic simulation prediction system and method for aerodynamic characteristics of standard airflow temperature sensor Technical Field The invention relates to an automatic simulation prediction system and method for aerodynamic characteristics of a standard airflow temperature sensor, which are suitable for measuring high-temperature gases of an aeroengine, a gas turbine and the like, and belong to the technical field of measurement and test. Background Standard airflow temperature sensors are a key component in aircraft engine testing for measuring the total temperature of the airflow. Its performance directly affects the accuracy of the engine performance assessment. The traditional standard air flow temperature sensor testing method relies on an experimental wind tunnel, and is high in cost and long in period. In recent years, with the development of Computational Fluid Dynamics (CFD) technology, numerical simulation has become a viable alternative. However, the existing simulation flow is mainly based on a Graphical User Interface (GUI), and when complex working condition simulation and parameter optimization are performed, the operation is complex, the efficiency is low, human errors are easily introduced, and the high-efficiency simulation requirement under the complex working condition is difficult to meet. PyFluent is a Python API of ANSYS Fluent that allows a user to interact with Fluent through a Python script to automate the simulation process. PyFluent brings higher flexibility and scalability to the field of CFD simulation, especially in scenarios requiring repetitive operations or complex task batching. However, existing PyFluent applications still have the following limitations: 1. functional limitations existing PyFluent scripts are generally limited to simple operations such as model importation, meshing, solver setup, and the like, and lack targeted support for complex operating conditions. 2. The automation degree is insufficient, and part of operation can be automatically realized by PyFluent, but the whole simulation flow still needs more manual intervention, especially in the aspects of boundary condition setting, motion simulation, result analysis and the like. 3. The existing PyFluent application is mostly scattered scripts, the systematic framework and the modularized design are lacked, and the requirements of complex simulation tasks are difficult to meet. 4. The learning cost is high, pyFluent needs to be deeply understood on Fluent software and Python programming, and the learning and application difficulty is high for non-professional users. Disclosure of Invention In order to solve the problems of the traditional simulation method of the standard air flow temperature sensor, the invention aims to provide an automatic simulation prediction system and method for the aerodynamic characteristics of the standard air flow temperature sensor, which are realized through systematic frame design and modularization function, improve the simulation efficiency and accuracy of the standard air flow temperature sensor and are beneficial to the design and optimization of the standard air flow temperature sensor. The invention aims at realizing the following technical scheme: The invention discloses a standard air flow temperature sensor pneumatic characteristic automatic simulation prediction system which comprises a user input module, an input check module, an automatic grid dividing module, an automatic loading boundary module, an automatic solving module and an automatic result analyzing module, wherein data seamless transmission and flow intelligent coupling are realized between the modules through PyFluent API, and a closed-loop automatic simulation assembly line is formed. The user input module is used for providing a Graphical User Interface (GUI) and a Command Line Interface (CLI), supporting parameterized input and batch task configuration, and is suitable for multi-working-condition simulation and optimization design. The input checking module automatically checks geometric models, material physical properties and working condition parameters input by a user based on a preset rationality threshold, and triggers a feedback mechanism to prompt the user to correct when the check is not passed. The automatic meshing module adopts a self-adaptive network meshing strategy based on characteristic dimensions and combines a network quality feedback mechanism to realize dynamic encryption and reconstruction. And the automatic loading boundary module dynamically generates a boundary condition expression according to the working condition parameters input by the user, and realizes real-time loading and updating of the boundary condition through PyFluent API. The automatic solving module is internally provided with a self-adaptive solving strategy, and can automatically adjust solving parameters and convergence criteria according to flow field characteristics, so that the computing efficiency