Mass Morphing Process for Aircraft Weight Estimation
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Solution Overview
Problem
Conventional methods for estimating mass properties of aircraft designs are time-consuming and often result in sub-optimal design decisions due to inaccuracies, leading to costly engineering changes, reduced payload, and performance issues, as they rely on parametric data models and CAD/FEM representations.
Innovation Solution
A mass morphing process that uses geometrical information from a database to create linear transformations in four-dimensional homogeneous coordinates, allowing for the efficient transformation of mass properties from a source to a target design, eliminating the need for detailed CAD and FEM models, and enabling robust mass property distributions for quicker design iterations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional parametric data models and CAD/FEM representations are used to estimate mass properties, then design accuracy can be maintained, but the process requires tens of thousands of engineering hours and relatively long lead times
Solution Approach 1:
The patent creates simplified copy models that replicate essential mass property characteristics without requiring full CAD/FEM representations. These copy models capture the distributed mass property distributions needed for accurate estimation while eliminating the time-consuming detailed modeling process, resolving the contradiction between accuracy and time consumption
Solution Approach 2:
The patent segments the aircraft into discrete components and systems, applying parametric equations to each segment independently. This segmentation allows parallel processing of mass property estimates across multiple components, significantly reducing overall lead time while maintaining accuracy through component-level detail
2Productivity
If conventional parametric equations are used for weight estimation, then the process can be completed faster, but design nuances are overlooked resulting in sub-optimal design decisions
Solution Approach 1:
The patent applies local quality by using detailed parametric equations and distributed mass property models for specific critical components and systems where design nuances matter most, while using simplified approaches for less critical areas. This selective application of detail level maintains productivity while ensuring accuracy where it impacts design decisions
Solution Approach 2:
The patent implements an iterative process where mass property estimates are dynamically refined through multiple passes, allowing the model to adapt and improve accuracy as design details become available. This dynamic approach enables quick initial estimates followed by progressive refinement without requiring complete detail upfront
3Measurement precision
If detailed CAD and FEM models are created for each design iteration, then accurate mass properties can be obtained, but the process cannot meet requirements to quickly review design alternatives
Solution Approach 1:
The patent performs preliminary action by pre-defining parametric relationships, mass property distributions, and component models before design iterations begin. This preliminary setup creates a reusable framework that can quickly generate accurate mass properties for multiple design alternatives without requiring detailed CAD/FEM modeling for each iteration
Data Source
AI summary
Disclosed is a system and process for creating mass property models for new product designs. Engineers are able to use this robust model to perform various assessments. The system morphs legacy mass property values into new design project configurations. This is done by building linear transformations in four-dimensional homogeneous coordinates. The transformations capture source and target geometric characteristic shapes. Filtering techniques are used to retrieve relevant source mass properties from the database. These detailed mass properties are collected into bay wise functional groups and then converted to equivalent mass particulates. These point masses are transformed from the source domain to the target domain, and summed back together to generate target mass property data. The process outputs detailed mass property distributions used in engineering models and reports and is continually updated to accommodate detailed designs throughout project development.