scholarly journals A Computationally Efficient Shallow Water Model for Mixed Cohesive and Non-Cohesive Sediment Transport in the Yangtze Estuary

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1435
Author(s):  
Peng Hu ◽  
Junyu Tao ◽  
Aofei Ji ◽  
Wei Li ◽  
Zhiguo He
Keyword(s):  
Sediment Transport ◽  
Yangtze Estuary ◽  
Water Model ◽  
Cohesive Sediments ◽  
Shallow Water Model ◽  
Computationally Efficient ◽  
Time Step ◽  
The Yangtze Estuary ◽  
Erosion Coefficient ◽  
Cohesive Sediment Transport

In this paper, a computationally efficient shallow water model is developed for sediment transport in the Yangtze estuary by considering mixed cohesive and non-cohesive sediment transport. It is firstly shown that the model is capable of reproducing tidal-hydrodynamics in the estuarine region. Secondly, it is demonstrated that the observed temporal variation of suspended sediment concentration (SSC) for mixed cohesive and non-cohesive sediments can be well-captured by the model with calibrated parameters (i.e., critical shear stresses for erosion/deposition, erosion coefficient). Numerical comparative studies indicate that: (1) consideration of multiple sediment fraction (both cohesive and non-cohesive sediments) is important for accurate modeling of SSC in the Yangtze Estuary; (2) the critical shear stress and the erosion coefficient is shown to be site-dependent, for which intensive calibration may be required; and (3) the Deepwater Navigation Channel (DNC) project may lead to enhanced current velocity and thus reduced sediment deposition in the North Passage of the Yangtze Estuary. Finally, the implementation of the hybrid local time step/global maximum time step (LTS/GMaTS) (using LTS to update the hydro-sediment module but using GMaTS to update the morphodynamic module) can lead to a reduction of as high as 90% in the computational cost for the Yangtze Estuary. This advantage, along with its well-demonstrated quantitative accuracy, indicates that the present model should find wide applications in estuarine regions.

scholarly journals Congested shallow water model: roof modeling in free surface flow

2018 ◽  
Vol 52 (5) ◽  
pp. 1679-1707 ◽  
Author(s):  
Edwige Godlewski ◽  
Martin Parisot ◽  
Jacques Sainte-Marie ◽  
Fabien Wahl
Keyword(s):  
Shallow Water ◽  
Numerical Solutions ◽  
Stokes Equations ◽  
Hyperbolic Equations ◽  
Mechanical Energy ◽  
Free Surface Flow ◽  
Surface Flow ◽  
Water Model ◽  
Shallow Water Model ◽  
Time Step

We are interested in the modeling and the numerical approximation of flows in the presence of a roof, for example flows in sewers or under an ice floe. A shallow water model with a supplementary congestion constraint describing the roof is derived from the Navier-Stokes equations. The congestion constraint is a challenging problem for the numerical resolution of hyperbolic equations. To overcome this difficulty, we follow a pseudo-compressibility relaxation approach. Eventually, a numerical scheme based on a finite volume method is proposed. The well-balanced property and the dissipation of the mechanical energy, acting as a mathematical entropy, are ensured under a non-restrictive condition on the time step in spite of the large celerity of the potential waves in the congested areas. Simulations in one dimension for transcritical steady flow are carried out and numerical solutions are compared to several analytical (stationary and non-stationary) solutions for validation.

scholarly journals MODELING ESTUARIAL COHESIVE SEDIMENT TRANSPORT

1984 ◽  
Vol 1 (19) ◽  
pp. 199
Author(s):  
E.J. Hayter ◽  
A.J. Mehta
Keyword(s):  
Sediment Transport ◽  
Transport Model ◽  
Cohesive Sediment ◽  
Transport Processes ◽  
Weighted Residual Method ◽  
Dispersive Transport ◽  
Time Step ◽  
Advection Dispersion ◽  
Cohesive Sediment Transport ◽  
Suspended Sediment Concentrations

Cohesive sediment related problems in estuaries include shoaling in navigable waterways and water pollution. A two-dimensional, depth averaged, finite element cohesive sediment transport model, CSTM-H, has been developed and may be used to assist in predicting the fate of sorbed pollutants and the frequency and quantity of dredging required to maintain navigable depths. Algorithms which describe the transport processes of redispersion, resuspenslon, dispersive transport, settling, deposition, bed formation and bed consolidation are incorporated in CSTM-H. The Galerkin weighted residual method is used to solve the advection-dispersion equation with appropriate source/sink terms at each time step for the nodal suspended sediment concentrations. The model yields stable and converging solutions. Verification was carried out against a series of erosion-deposition experiments in the laboratory using kaolinite and a natural mud as sediment. A model application under prototype conditions is described.

scholarly journals A PROCESS-BASED APPROACH TO SEDIMENT TRANSPORT

2011 ◽  
Vol 1 (32) ◽  
pp. 83 ◽  
Author(s):  
Ao Chu ◽  
Zhengbing Wang ◽  
Huib De Vriend ◽  
Marcel Stive
Keyword(s):  
Sediment Transport ◽  
Yangtze Estuary ◽  
Hangzhou Bay ◽  
Good Representation ◽  
The Yangtze Estuary ◽  
Proposed Model ◽  
Extensive Flow ◽  
Sediment Data ◽  
Mouth Bars ◽  
Insight Into

A process-based model for the Yangtze Estuary is constructed to study the sediment transport in the estuary. The proposed model covers the entire tidal region of the estuary, the Hangzhou Bay and a large part of the adjacent sea. The dominant processes, fluvial and tidal, are included in the model. The calibration of the model against extensive flow, water level, salinity and suspended sediment data shows a good representation of observed phenomena. With the present calibrated and validated model, the residual flow field and the residual sediment transport field are obtained. The residual sediment transport pattern gives insight into the morphological behaviour of the mouth bars.

scholarly journals Machine-Learned Preconditioners for Linear Solvers in Geophysical Fluid Flows

2021 ◽  
Author(s):  
Jan Ackmann ◽  
Peter Düben ◽  
Tim Palmer ◽  
Piotr Smolarkiewicz
Keyword(s):  
Machine Learning ◽  
Shallow Water ◽  
Water Model ◽  
Implicit Time ◽  
Learning Approaches ◽  
Shallow Water Model ◽  
Time Step ◽  
Linear Solvers ◽  
Linear Solver ◽  
Time Stepping

<p>Semi-implicit grid-point models for the atmosphere and the ocean require linear solvers that are working efficiently on modern supercomputers. The huge advantage of the semi-implicit time-stepping approach is that it enables large model time-steps. This however comes at the cost of having to solve a computationally demanding linear problem each model time-step to obtain an update to the model’s pressure/fluid-thickness field. In this study, we investigate whether machine learning approaches can be used to increase the efficiency of the linear solver.</p><p>Our machine learning approach aims at replacing a key component of the linear solver—the preconditioner. In the preconditioner an approximate matrix inversion is performed whose quality largely defines the linear solver’s performance. Embedding the machine-learning method within the framework of a linear solver circumvents potential robustness issues that machine learning approaches are often criticized for, as the linear solver ensures that a sufficient, pre-set level of accuracy is reached. The approach does not require prior availability of a conventional preconditioner and is highly flexible regarding complexity and machine learning design choices.</p><p>Several machine learning methods of different complexity from simple linear regression to deep feed-forward neural networks are used to learn the optimal preconditioner for a shallow-water model with semi-implicit time-stepping. The shallow-water model is specifically designed to be conceptually similar to more complex atmosphere models. The machine-learning preconditioner is competitive with a conventional preconditioner and provides good results even if it is used outside of the dynamical range of the training dataset.</p>

scholarly journals DEBRIS AND VESSEL TRANSPORT DUE TO TSUNAMI CURRENTS IN PORTS AND HARBORS

2018 ◽  
pp. 68
Author(s):  
Aykut Ayca ◽  
Patrick J. Lynett
Keyword(s):  
Water Model ◽  
Container Ship ◽  
Transport Capacity ◽  
Shallow Water Model ◽  
Computationally Efficient ◽  
Recovery Planning ◽  
The Past ◽  
Induced Currents ◽  
Floating Objects

The focus of the discussion will be on the debris and vessel transport capacity of the tsunami induced currents in ports and harbors. The tsunami events in the past 15 years proved that understanding these processes within the port/harbor basin has paramount importance in safety, recovery and the long-term resilience planning of the facilities; as all of these depend on the ability of structures or infrastructure to resist damage and the capability of harbors to become functional after the event. This endeavor requires an accurate representation of the flow field around the floating objects. Particularly, when the size of an average container ship is considered among with its’ fairly high draft to depth ratio, the interaction between flow and the vessels gets stronger. Therefore, in this study, the developed numerical tool, which is coupled with a 2HD nonlinear shallow water model, takes the interaction between the flow and the objects into account, and provides accurate results in a computationally efficient way. We will also present example simulation results of a numerical modelling study aimed at providing the quantitative guidance on maritime tsunami hazards in ports and harbors. This information can be used in pre-disaster recovery planning with the identification of the safe mooring spots or where the debris will likely accumulate after future tsunamis. Whilst the harbor’s ability to resist damage is a function of reducing the exposure to hazardous conditions as well as the maintaining/upgrading the structures/infrastructure within the harbors.

A 2D/3D hydrodynamic and sediment transport model for the Yangtze Estuary, China

2009 ◽  
Vol 77 (1-2) ◽  
pp. 114-136 ◽  
Author(s):  
Kelin Hu ◽  
Pingxing Ding ◽  
Zhengbing Wang ◽  
Shilun Yang
Keyword(s):  
Sediment Transport ◽  
Transport Model ◽  
Yangtze Estuary ◽  
The Yangtze Estuary ◽  
Sediment Transport Model

A Two-Stage Fourth-Order Multimoment Global Shallow-Water Model on the Cubed Sphere

2020 ◽  
Vol 148 (10) ◽  
pp. 4267-4279
Author(s):  
Yuzhang Che ◽  
Chungang Chen ◽  
Feng Xiao ◽  
Xingliang Li ◽  
Xueshun Shen
Keyword(s):  
Shallow Water ◽  
Fourth Order ◽  
Time Integration ◽  
Water Model ◽  
Shallow Water Model ◽  
Time Step ◽  
Two Stage ◽  
Order Scheme ◽  
Runge Kutta ◽  
Cubed Sphere

AbstractA new multimoment global shallow-water model on the cubed sphere is proposed by adopting a two-stage fourth-order Runge–Kutta time integration. Through calculating the values of predicted variables at half time step t = tn + (1/2)Δt by a second-order formulation, a fourth-order scheme can be derived using only two stages within one time step. This time integration method is implemented in our multimoment global shallow-water model to build and validate a new and more efficient numerical integration framework for dynamical cores. As the key task, the numerical formulation for evaluating the derivatives in time has been developed through the Cauchy–Kowalewski procedure and the spatial discretization of the multimoment finite-volume method, which ensures fourth-order accuracy in both time and space. Several major benchmark tests are used to verify the proposed numerical framework in comparison with the existing four-stage fourth-order Runge–Kutta method, which is based on the method of lines framework. The two-stage fourth-order scheme saves about 30% of the computational cost in comparison with the four-stage Runge–Kutta scheme for global advection and shallow-water models. The proposed two-stage fourth-order framework offers a new option to develop high-performance time marching strategy of practical significance in dynamical cores for atmospheric and oceanic models.

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