Refinement Indicator for Dynamic-Mesh Adaption in Three-Dimensional Shallow-Water Equation Modeling

Savant, Gaurav; Trahan, Corey J.; Berger, Charlie; McAlpin, Jennifer Tate; McAlpin, Tate O.

doi:10.1061/(asce)hy.1943-7900.0001394

Cited by 6 publications

(8 citation statements)

References 17 publications

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“…We use the numerical model, Adaptive Hydraulics (AdH), presented in Savant et al (2018) and Trahan et al (2018), to study the flushing times and water age in Mobile Bay.…”

Section: Numerical Modelmentioning

confidence: 99%

“…We, briefly, provide the basic model details in this section, and the interested reader is guided to Trahan et al (2018) and Savant et al (2018) for additional details.…”

Section: Numerical Modelmentioning

confidence: 99%

“…Mass conservation, to machine precision, in AdH was demonstrated in Berger and Howington (2002), and Savant et al (2018), and the interested user is referred to those publications for details.…”

Section: Numerical Modelmentioning

confidence: 99%

“…In this paper, we present the validation, and application of the 3D numerical model, Adaptive Hydraulics (AdH), presented in Trahan et al (2018) and Savant et al (2018), to the study of flushing times and water age in Mobile Bay, Alabama. The descriptions of techniques and methods presented herein will aid other researchers in the utilization of similar methods to study other strongly stratified microtidal estuarine systems with substantial freshwater river inflows.…”

Section: Introductionmentioning

confidence: 99%

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Numerical Modeling Investigation of Flushing Characteristics and Water Age in a Highly Stratified estuary: Mobile Bay, Alabama, U.S.A.

Savant

McAlpin²

2022

Preprint

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Abstract. The knowledge of timescales of flushing processes within an estuary is essential for the health, and productivity of the estuary, as well as for optimum estuarine management. The hydrodynamics, flushing times, and freshwater age within Mobile Bay were investigated using a three-dimensional (3D) numerical model, Adaptive Hydraulics. Bay flushing and freshwater times were analyzed for various freshwater flow conditions, wind conditions and investigated the influence of the Coriolis force. The flushing times were directly related to the magnitude of freshwater inputs to the system, with the bay exhibiting an average flushing time of 16.5 days for average river inflows. Freshwater age in the bay was closely associated with the freshwater inflows as well as with location in the Bay and varied from 2 days in the Upper Bay to 21 days in the Lower Bay for average river inflows. Northerly, Easterly, and Westerly winds play an enabling role in the flushing process, with lower depth-averaged flushing times compared to those without winds, with Northerly and Easterly winds being the most efficient. Southerly winds increase flushing times by changing the circulation patterns in the Bay.

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“…We use the numerical model, Adaptive Hydraulics (AdH), presented in Savant et al (2018) and Trahan et al (2018), to study the flushing times and water age in Mobile Bay.…”

Section: Numerical Modelmentioning

confidence: 99%

“…We, briefly, provide the basic model details in this section, and the interested reader is guided to Trahan et al (2018) and Savant et al (2018) for additional details.…”

Section: Numerical Modelmentioning

confidence: 99%

Section: Numerical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Numerical Modeling Investigation of Flushing Characteristics and Water Age in a Highly Stratified estuary: Mobile Bay, Alabama, U.S.A.

Savant

McAlpin²

2022

Preprint

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“…Currently, RANS-AdH captures the turbulent flow dissipation via a constant eddy viscosity subgrid closure scheme included in the molecular viscosity portion of the momentum equations. RANS-AdH has an automatic mesh adaption capability that is used to ensure a mesh independent flow solution (Tate, Berger, and Stockstill 2006;Savant et al 2018). Mesh adaption in RANS-AdH is controlled using the same method as in two-dimensional shallow water AdH by two user-specified parameters: a mesh refinement tolerance and a maximum number of adaption levels (ERDC 2019).…”

Section: Numerical Codementioning

confidence: 99%

Validation of numerical modeling for flows near draghead in operation

Johnston¹,

Hammack²,

Smith³

2019

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BACKGROUND: Fish and other aquatic species occasionally become entrained in dredges during operation. To better predict the likelihood of this entrainment occurring, the U.S. Army Corps of Engineers, San Francisco District, contacted the U.S. Army Engineer Research and Development Center (ERDC) to conduct a numerical model study to determine the flow behavior surrounding a draghead during operation. The validation data were taken from a previously completed 1:7-scale physical model study of a California draghead. 1 The numerical model study was completed by validating the numerical modeling process and then performing simulations at prototype scale to provide appropriate velocity measurements in the field. This report focuses on the numerical modeling process and validation portion of the numerical model.

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Formulation and application of the adaptive hydraulics three-dimensional shallow water and transport models

Trahan

Savant

Berger

et al. 2018

Journal of Computational Physics

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Refinement Indicator for Dynamic-Mesh Adaption in Three-Dimensional Shallow-Water Equation Modeling

Cited by 6 publications

References 17 publications

Numerical Modeling Investigation of Flushing Characteristics and Water Age in a Highly Stratified estuary: Mobile Bay, Alabama, U.S.A.

Numerical Modeling Investigation of Flushing Characteristics and Water Age in a Highly Stratified estuary: Mobile Bay, Alabama, U.S.A.

Validation of numerical modeling for flows near draghead in operation

Formulation and application of the adaptive hydraulics three-dimensional shallow water and transport models

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