Refinement Indicator for Mesh Adaption in Shallow-Water Modeling

Tate, Jennifer N.; Berger, R. C.; Stockstill, Richard L.

doi:10.1061/(asce)0733-9429(2006)132:8(854)

Cited by 26 publications

(8 citation statements)

References 6 publications

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“…689443, via the GEOEssential project. The authors would also like to thank Corey Trahan for his valuable help in using the Adaptive Hydraulics suite (AdH) [59,88,89] for the high-fidelity numerical simulation of the 2D shallow water flow examples. Permission was granted by the Chief of Engineers to publish this information.…”

Section: Acknowledgmentsmentioning

confidence: 99%

A greedy non-intrusive reduced order model for shallow water equations

Dutta,

Farthing,

Perracchione

et al. 2020

Preprint

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In this work, we develop Non-Intrusive Reduced Order Models (NIROMs) that combine Proper Orthogonal Decomposition (POD) with a Radial Basis Function (RBF) interpolation method to construct efficient reduced order models for time-dependent problems arising in large scale environmental flow applications. The performance of the POD-RBF NIROM is compared with a traditional nonlinear POD (NPOD) model by evaluating the accuracy, robustness, and speed for test problems representative of riverine flows. Different greedy algorithms are studied in order to determine a near-optimal distribution of interpolation points for the RBF approximation. A new power-scaled residual greedy (psr-greedy) algorithm is proposed that overcomes the drawbacks of the existing greedy approaches to enhance the accuracy and efficiency of the RBF approximation. The relative performance of these greedy algorithms is studied with numerical experiments using realistic 2D shallow water flow applications involving coastal and riverine dynamics.

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Section: Acknowledgmentsmentioning

confidence: 99%

A greedy non-intrusive reduced order model for shallow water equations

Dutta,

Farthing,

Perracchione

et al. 2020

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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“…These models include the Adaptive Hydraulics Model (Täte et al 2006;Gambucci 2009;ADH 2010) and the Gridded Surface Subsurface Hydrologie Model (Downer & Ogden 2004;GSSHA 2010). The advantages for this data model are most realized when operating on a shared memory architecture or symmetric multi-processing machine.…”

Section: Application Programming Interfacementioning

confidence: 99%

Efficient application programming interface for multi-dimensional modeling data

Jones

Wallace

Jones

et al. 2011

Journal of Hydroinformatics

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This paper describes an Application Programming Interface (API) for managing multi-dimensional data produced for water resource computational modeling that is being developed by the US Army Engineer Research and Development Center (ERDC), in conjunction with Brigham Young University.This API, along with a corresponding data standard, is being implemented within ERDC computational models to facilitate rapid data access, enhanced data compression and data sharing, and cross-platform independence. The API and data standard are known as the eXtensible Model Data Format (XMDF), and version 1.3 is available for free download. This API is designed to manage geometric data associated with grids, meshes, riverine and coastal cross sections, and both static and transient array-based datasets. The inclusion of coordinate system data makes it possible to share data between models developed in different coordinate systems. XMDF is used to store the data-intensive components of a modeling study in a compressed binary format that is platformindependent. It also provides a standardized file format that enhances modeling linking and data sharing between models.

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Refinement Indicator for Mesh Adaption in Shallow-Water Modeling

Cited by 26 publications

References 6 publications

A greedy non-intrusive reduced order model for shallow water equations

A greedy non-intrusive reduced order model for shallow water equations

Validation of numerical modeling for flows near draghead in operation

Efficient application programming interface for multi-dimensional modeling data

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