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Rolls-Royce Finds New-Engine Benefits in Old Test Data

๐Ÿ“… Date:

โœ๏ธ Author: Jim Camillo

๐Ÿ”– Topics: generative design, failure analysis

๐Ÿข Organizations: Rolls-Royce, Altair

The goal, according to Peter Wehle, head of innovation, research and testing at RRD, is to use this information to reduce new-engine weight and mass, while maintaining structural integrity.

Both parties are hopeful that using ML and AI will significantly reduce the number of sensors needed to obtain present and future data, thereby saving RRD millions of euros annually. According to Mahalingam, the software lets engineers choose the data they want from a data silo, select the algorithms they want to employ and decide whether or not they want to use a neural network to train an ML model.

Wehle notes that the disruptive tool is based on the interaction between a communication endpoint of the engine simulation and neighboring points. It carefully analyzes the effects of loads on physical structures.

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