Graduate Seminar in Fluid Mechanics

When:
October 13, 2017 @ 3:00 pm – 4:00 pm
2017-10-13T15:00:00-04:00
2017-10-13T16:00:00-04:00
Where:
316 Hodson Hall

3:00 pm Presentation

 “Structured Light Methods: A Brief Review and its Application in Measuring Deformation of Bat Wings

 Presented by SUBHRA SHANKHA KOLEY (Adviser: Prof. Katz)

Structured light method is a non-contact 3D surface measuring technique based on active stereo. In this method an arrangement of dots or stripes of varying intensity/color is projected on an object which is recorded on a camera. The geometric shape of the object distorts the projected pattern; this distortion is used to find the 3D surface shape of the object. In this talk, I would be reviewing the basic working principle of structured light along with the various types of structured light techniques. The structured light patterns are mainly divided in two categories where the patterns can either be coded temporally (i.e., over a sequence of images) or they can be coded spatially (single shot). I would also discuss the specific structured light pattern which would be used in my experiments to measure the deformation of bat wings.


3:25 pm Presentation

Scalar Source Reconstruction from Limited Remote Measurements

 Presented by VINCENT MONS (Adviser: Prof. Zaki)

Reconstructing the characteristics of a scalar source from limited remote measurements in a turbulent flow is a problem of great interest for environmental monitoring, and is challenging due to several aspects. Firstly, the numerical estimation of the scalar dispersion in a turbulent flow requires significant computational resources. Secondly, in actual practice, only a limited number of observations are available, which generally makes the corresponding inverse problem ill-posed. In this presentation, data assimilation approaches are considered to infer the scalar source localization in a turbulent channel flow at Reτ = 180. Non-intrusive ensemble-based variational techniques are employed, and their performance is compared with adjoint-based data assimilation. Strategies to decrease the number of numerical simulations performed in the assimilation process are discussed. The problem of optimal sensor placement in the framework of ensemble-based data assimilation is also investigated in order to enhance the quality and robustness of the source reconstruction from noisy measurements.

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