Numerical and experimental study of flow over stages of an offset merger dune interaction
Section snippets
Background and problem
Sand dunes form and evolve in response to flow-induced mobilization of sediment [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13]. The morphology of aeolian desert sand dunes is shaped through aeolian process in response to aerodynamic loading from the aloft atmospheric surface layer (ASL) [1], [2], [12], [14], [15], [16], [17]. Similarly, the hydrodynamic loading associated with flows in rivers and channels mobilizes sediments and can promote formation of sediment dune fields
Cases and investigative techniques
In the following sub-sections, details of the topographic arrangements considered and investigative techniques are presented. We have used complementary numerical (LES) and experimental measurements to diversify the data sources, which provides an inherent validation. Salient details of the experiments and simulations are summarized in Table 2.
Instantaneous visualization
Results for the cases studied (“IB1” to “IB5” via LES, “Exp” via experiment; see Fig. 4 and Table 1) are presented throughout this section. For qualitative illustration of how the flow responds to the various dune configurations, we first show instantaneous flow fields. Fig. 5 shows instantaneous visualization of swirl strength, a commonly-used vortex identifier [71], [72], [73], [74], [75], signed by the out-of-plane component of the resolved vorticity unit vector,
Conclusion
Dune mobilization is sustained exclusively by imposed aero-/hydro-dynamic loading, but dune morphodynamics are influenced by sediment availability, vegetation (aeolian), flow direction, local topographic heterogeneity, seasonal effects, etc. Here, we have used experiments (Section 2.3) and numerical simulations (Section 2.2) to highlight the role of proximal dunes in altering dune morphology. Under the fully rough conditions typical of environmental flows in rivers (fluvial) or the atmospheric
Acknowledgments
This work was supported by the National Science Foundation, Grant # CBET-1603254. KTC also acknowledges NSF support via Grant # CBET-0923106. Scientific computing resources were provided by the Texas Advanced Computing Center at the University of Texas. We thank Gary Kocurek and David Mohrig, UT Austin for sharing insights about morphodynamic interpretations of this work. We thank anonymous reviewers for providing comprehensive, insightful comments that led to a much improved final manuscript.
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