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The University of Southampton

Physics-based digital twins for enhanced vibro-acoustic sensing Seminar

16:00 - 17:00
24 January 2023
Building 13, room 3019

For more information regarding this seminar, please email Vanui Mardanyan at .

Event details

ISVR Research seminar

The current energy crisis in Europe shows the importance to accelerate the transition to a more sustainable society and industry. The ability to sustainably design and monitor vehicles and machines is important to establish this transition. Concretely, to improve sustainability a delicate balance between health, profitability and environment needs to be found. As the WHO indicates in recent publications, noise pollution is one of the biggest current health risks, thus is an important consideration towards sustainability.

The digital twin paradigm has the potential to find this difficult to obtain balance. A digital twin is a digital copy of a physical asset that behaves the same as the physical asset. Thus, by using sensor data from the physical asset, it can make design/control/maintenance decisions. From an acoustics standpoint this has two potential advantages. Firstly, products can be designed to be more silent, while still being sustainable. Alternatively, cheap non-intrusive acoustic measurements can be leveraged to obtain difficult to measure quantities, such as full sound (intensity) field estimates.

In this seminar, a physics-based digital twin approach for acoustic monitoring will be introduced that works by combining physics-based (reduced-order) models with sparse measurement data from the structure under investigation in a state estimator. The performance of the approach will be shown with several use cases related to vibro-acoustic identification and direct field acoustic testing.

Speaker information

Dr Sjoerd van Ophem , KU Leuven. Dr Sjoerd van Ophem is an FWO (Research foundation - Flanders) funded postdoctoral researcher working at the division Mecha(tro)nic system dynamics (LMSD) within the KU Leuven, Belgium. His main research interests are topics related to noise and vibration, specifically in combining physics-based models with measurement data to infer difficult to measure information from machines and vehicles. He is currently visiting the university of Oxford for a research stay on physics-based machine learning techniques for vibro-acoustics.

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