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تسجيل مستخدم جديدCharacterizing flows with an instrumented particle measuring Lagrangian accelerations
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We present in this article a novel Lagrangian measurement technique: an instrumented particle which continuously transmits the force/acceleration acting on it as it is advected in a flow. We develop signal processing methods to extract information on the flow from the acceleration signal transmitted by the particle. Notably, we are able to characterize the force acting on the particle and to identify the presence of a permanent large-scale vortex structure. Our technique provides a fast, robust and efficient tool to characterize flows, and it is particularly suited to obtain Lagrangian statistics along long trajectories or in cases where optical measurement techniques are not or hardly applicable.
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Accessing and characterizing a flow impose a number of constraints on the employed measurement techniques; in particular optical methods require transparent fluids and windows in the vessel. Whereas one can adapt apparatus, fluid and methods in the l
ab to these constraints, this is hardly possible for industrial mixers. We present in this article a novel measurement technique which is suitable for opaque or granular flows: an instrumented particle, which continuously transmits the force/acceleration acting on it as it is advected in a flow. Its density is adjustable for a wide range of fluids and because of its small size and its wireless data transmission, the system can be used both in industrial and scientific mixers allowing a better understanding of the flow within. We demonstrate the capabilities and precision of the particle by comparing its transmitted acceleration to alternative measurements, in particular in the case of a turbulent von Karman flow. Our technique shows to be an efficient and fast tool to characterize flows.
The Lagrangian (LA) and Eulerian Acceleration (EA) properties of fluid particles in homogeneous turbulence with uniform shear and uniform stable stratification are studied using direct numerical simulations. The Richardson number is varied from $Ri=0
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