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Digital Twin for Automated Flight Test Evaluation and Model Validation

Reference number
Coordinator Saab AB - SAAB Aktiebolag Aeronautics
Funding from Vinnova SEK 3 007 330
Project duration January 2020 - December 2022
Status Completed
Venture National Aeronautical Research Program 7
Call Research project in aviation technology - spring 2019

Purpose and goal

The overall project goal was to have an implemented and operational framework for automated model validation and anomaly detection in place in industry by the time the next large development project begins. This has been achieved and the Technology Readiness Level (TRL) of the framework is currently being increased at a rapid pace. The TRL of the framework at the time of writing is deduced as 7-9 as the framework is in use for a few of the subsystem models and simulators used in an actual development project

Expected results and effects

The developed framework will concretely enhance the model-based methods currently employed during preliminary and detailed design of aircraft at Saab. Particularly through an increased and communicated credibility, assessed in an objective fashion, of simulator applications such as the Total-System Rig used within the Gripen E project. Furthermore, various aspects of the framework show great promise in enhancing MBSE in other life-cycle phases. For example, the HPC cluster simulation capabilities enable rapid design space exploration in early concept phases.

Planned approach and implementation

The project has been conducted by means of implementing the Industry-as-laboratory methodology. Industry-as-laboratory highlights the relevance of industrial input to academic research in order to ensure focus on industrially relevant engineering methods. Industry supplies challenging problems rendering a state-of-the art analysis in academia. The state-of-the-art is expanded and tailored to address the problem at hand. The resulting hypothesis is then iteratively evaluated in both industry and academia

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 1 February 2023

Reference number 2019-02760

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