Cheng et al., 2023 - Google Patents
Robust aerodynamic optimization and design exploration of a wide-chord transonic fan under geometric and operational uncertaintiesCheng et al., 2023
- Document ID
- 5979922910955851886
- Author
- Cheng H
- Zhou C
- Lu X
- Zhao S
- Han G
- Yang C
- Publication year
- Publication venue
- Energy
External Links
Snippet
Axial compressors are inevitably affected by various uncertain factors in the process of manufacture and operation. These uncertainties obviously lead to reduced efficiency and large performance dispersion. However, researches on uncertainty quantification and robust …
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
- G06F17/5018—Computer-aided design using simulation using finite difference methods or finite element methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5086—Mechanical design, e.g. parametric or variational design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/16—Numerical modeling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/08—Multi-objective optimization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Ekradi et al. | Performance improvement of a transonic centrifugal compressor impeller with splitter blade by three-dimensional optimization | |
Wang et al. | Dual-convolutional neural network based aerodynamic prediction and multi-objective optimization of a compact turbine rotor | |
Li et al. | Review of design optimization methods for turbomachinery aerodynamics | |
Ju et al. | Aerodynamic analysis and design optimization of a centrifugal compressor impeller considering realistic manufacturing uncertainties | |
Cheng et al. | Robust aerodynamic optimization and design exploration of a wide-chord transonic fan under geometric and operational uncertainties | |
Pei et al. | Multiparameter optimization for the nonlinear performance improvement of centrifugal pumps using a multilayer neural network | |
Joly et al. | Machine learning enabled adaptive optimization of a transonic compressor rotor with precompression | |
Tang et al. | Aerodynamic robustness optimization and design exploration of centrifugal compressor impeller under uncertainties | |
Junying et al. | Compressor geometric uncertainty quantification under conditions from near choke to near stall | |
Kumar et al. | Robust design of compressor fan blades against erosion | |
Cheng et al. | Uncertainty quantification and sensitivity analysis on the aerodynamic performance of a micro transonic compressor | |
Hu et al. | Flow field modeling of airfoil based on convolutional neural networks from transform domain perspective | |
Hosseinimaab et al. | Optimizing the performance of a single-shaft micro gas turbine engine by modifying its centrifugal compressor design | |
Guo et al. | Aerodynamic evaluation of cascade flow with actual geometric uncertainties using an adaptive sparse arbitrary polynomial chaos expansion | |
Maral et al. | A genetic algorithm based multi-objective optimization of squealer tip geometry in axial flow turbines: a constant tip gap approach | |
Soulat et al. | Efficient optimisation procedure for design problems in fluid mechanics | |
Cheng et al. | Robust optimization and uncertainty quantification of a micro axial compressor for unmanned aerial vehicles | |
Li et al. | Uncertainty quantification and aerodynamic robust optimization of turbomachinery based on graph learning methods | |
Luo et al. | Aerodynamic optimization of a transonic fan rotor by blade sweeping using adaptive Gaussian process | |
Esfahanian et al. | Aerodynamic shape optimization of gas turbines: a deep learning surrogate model approach | |
Song et al. | Multidisciplinary robust optimization approach of fan rotors under structural constraints with blade curvature | |
Wang et al. | A Novel Multi-Fidelity Surrogate for Efficient Turbine Design Optimization | |
Tang et al. | An interval quantification-based optimization approach for wind turbine airfoil under uncertainties | |
Hu et al. | A dimension reduction-based multidisciplinary design optimization method for high pressure turbine blades | |
Pakatchian et al. | Applications of machine learning approaches in aerodynamic aspects of axial flow compressors: A review |