In order to reduce the amount of global CO2 emissions, a new breed of aircraft and engine designs are needed. In this case, CAELESTIS has developed a novel, secure, end-to-end Interoperable Simulation Ecosystem (ISE) that performs multidirectional dataflow across the aircraft value chain linking product design and distributed engineering teams´ CAD-CAE tools, to accelerate the design and engineering optimization of disruptive aircraft and engine configurations, ensuring their manufacturability from the design conceptualization. This has been done by integrating a variety of state-of-the-art simulation tools, boosted by implementing HPC, and applying innovative high-fidelity surrogate models to support the multi-disciplinary design, optimization and uncertainty quantification and propagation.
The ecosystem was boosted by HPC infrastructures to massively execute predictions and delivered optimized design and engineering outputs at realistic-time scales. In this regard, high-fidelity model-based digital twins with unprecedented level of detail and covering several production stages and manufacturing deviations were developed and interconnected. Those were linked to machine learning tools adapted to HPC simulation outputs to improve detection of manufacturing flaws based on a probabilistic approach to quantify uncertainties and their propagation and influence on structural integrity, as well as identify design for manufacturing interdependencies to provide optimized product topologies.
From manufacturing point of view, HPC simulation were made available at manufacturing shopfloor as reduced order models in online monitoring edge computing devices, to support
i) product performance prediction based on detected defects on real time and
ii) informed corrective actions to minimize and compensate their effect.
Overall, CAELESTIS ISE will contribute to generate optimized and reliable aircraft design configurations, widen the design space and optimize the manufacturing process window and improve production efficiency and inline quality assurance.
