dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Maas, Leo | |
dc.contributor.author | Soons, Jelle | |
dc.date.accessioned | 2022-09-09T02:01:02Z | |
dc.date.available | 2022-09-09T02:01:02Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/42512 | |
dc.description.abstract | Adding mass constraints to existing ADCP-data results in improved velocity estimates in various
transducer configurations. The problem of estimating vertical velocity with a conventional set-up
in horizontally dominant flow is that inhomogenities in the horizontal velocities can cause relatively
large errors in the vertical velocity estimate. A possible solution to obtain more accurate vertical
velocity estimates using mass constraints is introduced. The corrected data is compared to the original uncorrected data. Then a novel configuration of transducers that is a combination of multiple
transducer-receivers in a buckyball set up is discussed. Mass constraints are applied to synthetic data
of this set up, and this leads in various circumstances to improved estimates. Also discussed is a proof
of concept showing the ability of this set up to measure the shearing motion of internal waves. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | Here two novel methods to improve conventional ADCP measuring
techniques are introduced. Firstly a post-processing technique where mass conservation is added
as constraint to the velocity estimates is discussed. This reduces the inhomogeneity error. Secondly a hardware
addition is introduced: the buckyball concept. Here multiple transducer-receivers are combined into a buckyball
configuration allowing to estimate velocities in multiple directions. | |
dc.title | Applying Mass Conservation to ADCP-data | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | ADCP; mass conservation; turbulence anisotropy; internal waves | |
dc.subject.courseuu | Mathematical Sciences | |
dc.thesis.id | 9558 | |