Gas Turbine Engine Modelling Automation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modelling a gas turbine engine is a time-consuming process requiring significant human resources due to its complex structure, especially when precise re-positioning of components is necessary.
Innovation Solution
A method involving determining match feature data entities to satisfy matching criteria within a data structure, allowing for relative movement and association of physical features in a model, utilizing a tree structure and user input for moveable or modifiable components, to automate the positioning and coupling of components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional CAD package is used to model gas turbine engine by assembling components, then the model can be generated with proper structure, but the process becomes time-consuming and requires significant human resources
Solution Approach 1:
The patent applies preliminary action by pre-defining match features and association rules for engine components before the actual assembly process. The system pre-processes component data to identify coupling features, clearance requirements, and positional relationships, so that during model generation, components can be automatically positioned and associated without time-consuming manual intervention. This resolves the contradiction by maintaining model accuracy through pre-established association rules while dramatically improving productivity through automated assembly.
2Manufacturing precision
If components are manually re-positioned within the model, then precise positioning can be achieved, but the operation becomes time-consuming and requires high level of precision
Solution Approach 1:
The patent implements self-service by enabling components to automatically determine their own positions and associations based on predefined match features. Each component contains metadata about its coupling features, clearance requirements, and positional relationships with other components. During assembly, the system queries these self-describing features and automatically positions components without requiring manual intervention or high-precision manual re-positioning operations. This resolves the contradiction by achieving precise positioning through automated self-association while eliminating time-consuming manual operations.
3Device complexity
If complex structure of gas turbine engine is modelled using traditional methods, then complete model can be generated, but significant human resources are required
Solution Approach 1:
The patent applies segmentation by breaking down the complex gas turbine engine model into discrete components with standardized data structures. Each component (compressor, turbine, combustion chamber, etc.) is represented as a separate entity with defined match features and association rules. This segmentation allows the system to process and assemble components independently through automated queries and operations, rather than requiring manual handling of the entire complex structure at once. This resolves the contradiction by maintaining complete engine structure while improving productivity through divided, automated processing.
Solution Approach 2:
The patent implements universality by creating a standardized data structure and association mechanism that can handle all types of engine components uniformly. The match feature system provides universal functionality for defining positional relationships, couplings, and clearances across different component types. This universal approach allows the same automated process to handle the entire complex engine structure without requiring specialized manual procedures for each component, thereby resolving the contradiction between handling device complexity and maintaining productivity.
Data Source
AI summary
A method of modelling at least a part of a gas turbine engine, method including: determining whether a first match feature data entity, defining a first location where a first physical feature may associate with another physical feature of a data structure, and a second match feature data entity, defining a second location where the second physical feature may associate with another physical feature of the data structure, satisfy a first matching criterion, the data structure including: a first data entity representing a geometrical shape of the first physical feature, the first data entity being associated with the first match feature data entity; and a second data entity representing a geometrical shape of the second physical feature, the second data entity being associated with the second match feature data entity; and performing relative movement between the first physical feature and the second physical feature within a model using the determination.