Wireless sensors networks enable the chance to investigate with enhanced freedom physical phenomena, aiming to increase the informative content obtained by sensors measurements. In this work we will focus on a system allowing to experimentally measure pressure profiles obtained from sensor nodes deployed on a NACA0012 aircraft wing model. By exploiting measurements gathered from sensors, allowing to measure pressure fluctuations of ±600Pa with a resolution of 4Pa, together with results obtained by Computational Fluid Dynamics (CFD) models, the system enables extracting flow profile, thus obtaining information on flow separation and stall phenomenon. Wireless measures are delivered with an enhanced version of IEEE802.15.4e, allowing to decrease power consumption by a factor of 7. Packet routing, based on Routing Protocol for Low-Power and Lossy Networks (RPL), has been improved by means of a newly introduced Lifetime and Latency Aggregatable Metric (L2AM) leading to a 18% increased network lifetime.

Investigating Flow Dynamics with Wireless Pressure Sensors Network

Francioso Luca;De Pascali Chiara;
2014

Abstract

Wireless sensors networks enable the chance to investigate with enhanced freedom physical phenomena, aiming to increase the informative content obtained by sensors measurements. In this work we will focus on a system allowing to experimentally measure pressure profiles obtained from sensor nodes deployed on a NACA0012 aircraft wing model. By exploiting measurements gathered from sensors, allowing to measure pressure fluctuations of ±600Pa with a resolution of 4Pa, together with results obtained by Computational Fluid Dynamics (CFD) models, the system enables extracting flow profile, thus obtaining information on flow separation and stall phenomenon. Wireless measures are delivered with an enhanced version of IEEE802.15.4e, allowing to decrease power consumption by a factor of 7. Packet routing, based on Routing Protocol for Low-Power and Lossy Networks (RPL), has been improved by means of a newly introduced Lifetime and Latency Aggregatable Metric (L2AM) leading to a 18% increased network lifetime.
2014
9780769552491
Aerospace electronics
Aerospace simulation
Airborne WSN
Structural Health Monitoring
Wireless Sensor Networks
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/287900
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