The objective of this activity is to develop technology and methods to enable the digital representation of spacecraft from the thermal perspective in order to better support the design, development, testing and operation of the spacecraft thermal control system.

 

The term Digital Twin is a hot topic in the simulation industry. Examples of digital twins in other comparable domains are for health monitoring of vehicles or gas turbines. The proposed activity aims to apply the ideas of digital twins, with a specific focus on spacecraft thermal control systems (TCS). A set of possible use cases is provided below with expected benefits:

• Testing: A real time digital representation of the article under test. Benefit: support monitoring and understanding of thermal test execution - data display, safety of test article, and near real time thermal model correlation. Improving the capture of the as-tested configuration.

• Operations: A real time thermal mathematical model of an operating S/C fed by telemetry and used for planning or what if studies. Benefit: allows informed decisions to be made by operators or optimisation of (for example) science operations.

• Health Monitoring: A health monitoring system for the TCS, possibly as part of a wider S/C level twin. Benefit: Early detection or prediction of anomalies, for example on constellations where human monitoring of telemetry is limited.

• Data Fusion: A repository of all the models and data pertinent to the TCS over the full lifecycle of the S/C. Benefit: more efficient access to data ensuring traceability.

 

Thus, in order to enable the digital twins it is necessary to develop a number of technologies; for example, the following topics may need to be addressed in the activity:

 

• Data modelling activities to make a formal link between S/C parameters (e.g. telemetry) and thermal engineering quantities (dissipations, current environment heat fluxes, etc.).

• Optimised thermal and radiative solvers for faster than real time simulations, enabling the operations use case above.

• Co-simulation with other disciplines (e.g. power) or an overall S/C simulator

• Use of ?big data? to exploit large thermal data sets coming from analysis, test and operations.

• Modern 3D visualisation and linked data techniques, for example to overlay data from the digital twin onto S/C geometry (e.g. augmented reality).

 

It is important to note that these technologies need to be available to users at the time of generation of the data or models. An approach that relies on assembling a digital twin after the fact is unlikely to gain acceptance, the necessary links to the digital twin need to be embedded in the industrial processes.

 

Finally, the main tasks to be executed in this activity include:

• State of the art, requirements capture and selection of industrial validation cases

• Architectural design and identification of needed building blocks

• Developments

• Demonstration of developments on industrial validation cases