CN-121980714-A - Design method of mixed-flow turbine

CN121980714ACN 121980714 ACN121980714 ACN 121980714ACN-121980714-A

Abstract

The invention relates to the technical field of turbomachinery design, in particular to a design method of a mixed flow turbine, which comprises the steps of setting up a collaborative parameterization model of rotor parameters and volute parameters, setting dynamic constraint to define a design space, acquiring efficiency and swallowing capacity parameters under a pulse peak working condition based on a CFD method, the prediction, search, verification and updating closed-loop optimization are realized through the Kriging agent model and the global search of the exclusion domain, meanwhile, the strength, the rigidity and the fatigue performance are checked by integrating the structural mechanics simulation, the form of key parts is optimized, the stress concentration is avoided, and the feasibility of the processing technology is fully considered. According to the invention, integrated collaborative optimization of the volute and the rotor is realized, the calculation cost is obviously reduced, the turbine efficiency is improved by more than 3% -4% under the constraint that the swallowing capacity deviation is not more than 2.5%, the energy absorption capacity is enhanced under the high loading condition, the blade load distribution is improved, the outlet rotational flow is reduced, the structure is stable and reliable, the processing difficulty is low, and the method is suitable for a turbocharging system in the fields of automobiles and the like.

Inventors

LIU ZHENG
Shi Yeqi
ZHANG TAO
ZHU CHUANG

Assignees

杭州玄材科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260408

Claims (10)

1. The design method of the mixed flow turbine is characterized by comprising the following design optimization steps of dynamic control: Establishing a mixed flow turbine cooperative parameterized model comprising a rotor and a volute, defining rotor geometry through a first parameter set, and defining volute geometry through a second parameter set; setting a numerical range for each design parameter in the first parameter set and the second parameter set, and establishing a geometric logic constraint and a pneumatic performance matching constraint to limit a design space allowing searching; Based on a computational fluid dynamics method, carrying out pneumatic simulation on different design candidates in a design space to obtain turbine efficiency and swallowing capacity parameters of the design candidates under a target working condition; Constructing and updating a proxy model to predict the performance of any point in a design space, calculating and excluding densely searched areas based on the distribution of the estimated design candidates, guiding the search to the areas which are not fully explored to find new high-performance design candidates, and estimating to realize iterative optimization loops; And repeating the iterative optimization loop until a preset convergence condition is met, and outputting an optimal mixed flow turbine geometry with improved turbine efficiency and meeting swallowing capacity constraint.
2. The method of designing a mixed-flow turbine according to claim 1, wherein establishing a mixed-flow turbine collaborative parameterization model includes the steps of: Dynamically defining a rotor geometry based on the first set of parameters including related parameters controlling blade cone angle, blade axial position, and blade camber line angle distribution; Dynamically defining a volute geometry based on the second parameter set, wherein the second parameter set comprises related parameters for controlling the radial distance between a volute tongue and an impeller, the volute section shape, the length of an induction section and the circumferential distribution of the section area; Integrating the first parameter set and the second parameter set into a complete turbine system input parameter set, associating the complete turbine system input parameter set with a three-dimensional computer aided design kernel through a computer program interface, and automatically generating a full three-dimensional flow channel geometric model comprising a volute, a vaneless nozzle and a rotor.
3. The method of designing a mixed-flow turbine according to claim 1, wherein the step of establishing geometric logic constraints and aerodynamic performance matching constraints comprises: Setting upper and lower limits of allowable variation values for each of the first and second parameter sets; setting a sequence rule and a minimum interval rule of geometric control points for control parameters used for defining blade camber line angle distribution in the first parameter group; Taking the swallowing capacity characteristic of the turbine as the dynamic constraint of the optimization process, and correspondingly adjusting the performance evaluation value of the turbine according to whether the deviation of the swallowing capacity parameter of the design candidate and the reference value exceeds a preset tolerance threshold.
4. The method of designing a mixed-flow turbine according to claim 1, wherein the step of directing a search to an insufficiently explored area to find new high performance design candidates includes: Generating initial design candidates in a design space by adopting a space filling sampling method, evaluating and storing the initial design candidates to form an initial design-performance database; training a machine learning agent model based on the database to predict performance of new design candidates and periodically updating the model as data increases; According to the distribution of design candidates in the database, calculating an exclusion domain according to a preset exclusion rule, and limiting a search range to an insufficient exploration area outside the exclusion domain; And in the insufficiently explored area, optimizing the agent model by utilizing an optimization algorithm, obtaining new design candidates with optimal prediction performance, verifying, and adding verification results into a database to trigger a new optimization cycle.
5. The method for designing a mixed-flow turbine according to claim 1, wherein the step of obtaining turbine efficiency and swallowing capacity parameters under target conditions by performing pneumatic simulation on different design candidates in a design space based on a computational fluid dynamics method comprises the steps of: automatically extracting a fluid calculation domain and discretizing grids based on a parameterized geometric model, and encrypting the grids of the key flow area; setting a physical model and boundary conditions corresponding to target working conditions; and extracting data from the simulation result, and calculating isentropic efficiency and mass flow parameters of the turbine.
6. The method of designing a mixed-flow turbine according to claim 1, further comprising a design knowledge mining step for identifying key design rules from the optimization process data, comprising: in the iterative search process, automatically recording all parameter values and performance results of each estimated design candidate to form a dynamically-increased data set; dynamically evaluating the influence degree of each design parameter on the turbine efficiency by adopting a sensitivity analysis method based on the data set; And carrying out importance ranking on each design parameter according to the influence degree, and dynamically identifying key influence parameters.
7. A system for designing a mixed-flow turbine, comprising: the system comprises a building module, a control module and a control module, wherein the building module is used for building a mixed flow turbine collaborative parameterization model comprising a rotor and a volute, defining the rotor geometry through a first parameter set and defining the volute geometry through a second parameter set; The constraint module is used for setting a numerical range for each design parameter in the first parameter set and the second parameter set, and establishing geometric logic constraint and pneumatic performance matching constraint so as to limit a design space allowing searching; the acquisition module is used for carrying out pneumatic simulation on different design candidates in the design space based on a computational fluid dynamics method, and acquiring turbine efficiency and swallowing capacity parameters of the design candidates under a target working condition; The optimization module is used for constructing and updating a proxy model to predict the performance of any point in the design space, calculating and eliminating the densely searched area based on the distribution of the estimated design candidates, guiding the search to the area which is not fully explored to find out new high-performance design candidates, and estimating to realize iterative optimization circulation; and the output module is used for repeating the iterative optimization loop until a preset convergence condition is met, and outputting an optimal mixed flow turbine geometry structure with improved turbine efficiency and meeting the swallowing capacity constraint.
8. The mixed flow turbine design system of claim 7, wherein the constraint module comprises: a setting unit configured to set a numerical upper limit and a numerical lower limit of allowable variation for each of the first parameter set and the second parameter set; A definition unit, configured to set a sequence rule and a minimum pitch rule of geometric control points for control parameters used for defining blade camber line angle distribution in the first parameter set; and the adjusting unit is used for taking the swallowing capacity characteristic of the turbine as the dynamic constraint of the optimization process, and correspondingly adjusting the performance evaluation value of the turbine according to whether the deviation between the swallowing capacity parameter of the design candidate and the reference value exceeds a preset tolerance threshold.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

Description

Design method of mixed-flow turbine Technical Field The invention relates to the technical field of turbine machinery design, in particular to a design method of a mixed flow turbine. Background The mixed flow turbine has the advantages of high axial flow coefficient and high radial flow acting capacity, compact structure and excellent pneumatic performance, and is widely applied to various power systems, and the design rationality directly determines the energy conversion efficiency and the running stability of the system. At present, mixed-flow turbine design depends on experience of personnel, an experience formula and a traditional CFD simulation check combined thought are adopted, an initial contour is determined by experience, and then simulation check iteration modification is carried out until performance requirements are met. The existing method has obvious defects, namely, firstly, strong dependence on experience, poor scheme consistency caused by experience differences of different designers, long design period, high research and development cost, difficulty in rapid and accurate design, secondly, lack of accurate theoretical support on initial profile, difficulty in radically treating losses such as flow separation and vortex of a runner in subsequent simulation iteration, low aerodynamic efficiency of a turbine, poor adaptability of complex working conditions, isolated consideration of aerodynamic performance, and failure in cooperative integration of structural strength and processing technology, and easiness in contradiction of pneumatic standard reaching, unreliable structure or reliable structure but pneumatic inefficiency. Therefore, a design method of a mixed-flow turbine is needed to solve the above problems. Disclosure of Invention The invention aims to provide a design method of a mixed-flow turbine, which comprises the following steps of: Establishing a mixed flow turbine cooperative parameterized model comprising a rotor and a volute, defining rotor geometry through a first parameter set, and defining volute geometry through a second parameter set; setting a numerical range for each design parameter in the first parameter set and the second parameter set, and establishing a geometric logic constraint and a pneumatic performance matching constraint to limit a design space allowing searching; Based on a computational fluid dynamics method, carrying out pneumatic simulation on different design candidates in a design space to obtain turbine efficiency and swallowing capacity parameters of the design candidates under a target working condition; Constructing and updating a proxy model to predict the performance of any point in a design space, calculating and excluding densely searched areas based on the distribution of the estimated design candidates, guiding the search to the areas which are not fully explored to find new high-performance design candidates, and estimating to realize iterative optimization loops; And repeating the iterative optimization loop until a preset convergence condition is met, and outputting an optimal mixed flow turbine geometry with improved turbine efficiency and meeting swallowing capacity constraint. Furthermore, the invention also discloses a design system of the mixed-flow turbine, which comprises: the system comprises a building module, a control module and a control module, wherein the building module is used for building a mixed flow turbine collaborative parameterization model comprising a rotor and a volute, defining the rotor geometry through a first parameter set and defining the volute geometry through a second parameter set; The constraint module is used for setting a numerical range for each design parameter in the first parameter set and the second parameter set, and establishing geometric logic constraint and pneumatic performance matching constraint so as to limit a design space allowing searching; the acquisition module is used for carrying out pneumatic simulation on different design candidates in the design space based on a computational fluid dynamics method, and acquiring turbine efficiency and swallowing capacity parameters of the design candidates under a target working condition; The optimization module is used for constructing and updating a proxy model to predict the performance of any point in the design space, calculating and eliminating the densely searched area based on the distribution of the estimated design candidates, guiding the search to the area which is not fully explored to find out new high-performance design candidates, and estimating to realize iterative optimization circulation; and the output module is used for repeating the iterative optimization loop until a preset convergence condition is met, and outputting an optimal mixed flow turbine geometry structure with improved turbine efficiency and meeting the swallowing capacity constraint. Further, the constraint module includes: a setting unit configured to set a num