Special Issue "Advanced Modelling Strategies for Hydraulic Engineering and River Research"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydraulics and Hydrodynamics".

Deadline for manuscript submissions: 30 September 2020.

Special Issue Editor

Dr. Michael Tritthart
Website
Guest Editor
BOKU—University of Natural Resources and Life Sciences Vienna,Department of Water, Atmosphere and Environment, Institute of Hydraulic Engineering and River Research,Muthgasse 107, 1190 Vienna, Austria
Interests: numerical modelling; hydrodynamics; sediment transport; hydraulic engineering

Special Issue Information

Dear Colleagues,

Our society, as a whole, and the work environment in particular, are currently undergoing large-scale digital transformation. This development is particularly beneficial for the field of water-related engineering. Advances in computer power have led to the evolvement of numerical methods, providing solutions to issues in hydraulic engineering and river research that were considered intractable in the past.

While 2D or 3D Reynolds-Averaged Navier–Stokes (RANS) methods are often the first choice for numerically tackling problems in applied hydraulics, high-resolution techniques such as Large Eddy Simulations (LES) have also been employed successfully for ever larger modelling domains. Advances in particle-based methods, such as Smoothed Particle Hydrodynamics (SPH) or Lattice Boltzmann Methods (LBM) could yield robust and highly accurate results. Also, strategies involving machine learning and artificial intelligence have matured in recent years. Further highly promising modelling strategies are the extension of numerical models to the physical domain by hybrid models, and the dissemination of results to a broader public audience by real-time virtual and augmented reality.

This Special Issue invites contributions related to the development or employment of advanced modelling strategies, such as (but not limited to) the aforementioned techniques, to solve applied issues involving hydraulic structures, rivers or reservoirs. This particularly applies to processes related to hydrodynamics, sediment transport (bedload, suspended load), sedimentation, erosion, morphodynamics, pollutant transport, density-driven currents, and flow–vegetation interactions, and potentially entails further ecological processes in an interdisciplinary view.

Dr. Michael Tritthart
Guest Editor

Manuscript Submission Information

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Keywords

  • numerical modelling
  • hydraulic engineering
  • rivers
  • reservoirs
  • hydrodynamics
  • sediment transport

Published Papers (5 papers)

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Research

Open AccessArticle
An Improved Meshless Divergence-Free PBF Framework for Ocean Wave Modeling in Marine Simulator
Water 2020, 12(7), 1873; https://doi.org/10.3390/w12071873 - 30 Jun 2020
Abstract
It is a challenging work to simulate wind and waves in virtual scenes of marine simulators. In this paper, a divergence-free position based fluid (DFPBF) framework is introduced for ocean wave modeling in marine simulators. We introduce a set of constant density constraints [...] Read more.
It is a challenging work to simulate wind and waves in virtual scenes of marine simulators. In this paper, a divergence-free position based fluid (DFPBF) framework is introduced for ocean wave modeling in marine simulators. We introduce a set of constant density constraints and divergence-free velocity constraints to enforce incompressibility. By adjusting the position distribution of fluid particles, the particle density is forced to be constant. Constraining the divergence-free velocity field can keep the density change rate at zero. When correcting the position and velocity of particles, we introduced a relaxation correction scheme to accelerate the convergence of the framework. The simulation results show that as the scene scale expands and the number of fluid particles increases, this acceleration effect will be more significant. Secondly, we propose a novel particle-based three-dimensional stochastic fluctuating wind field. The Perlin noise is introduced to disturb the constant horizontal wind field to form a stochastic wind field. On this basis, a stochastic fluctuating wind field simulation framework is proposed. By adjusting the pulse period and pulse width, users can flexibly control the fluid turnover under the action of the wind field. This wind field framework can be easily integrated into the DFPBF model. Based on this wind field model, we simulated some typical wind wave scenarios, including interaction scenarios with lighthouse and lifebuoy, and verified the effectiveness of the wind field model. Full article
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Open AccessArticle
CFD Modelling of Particle-Driven Gravity Currents in Reservoirs
Water 2020, 12(5), 1403; https://doi.org/10.3390/w12051403 - 15 May 2020
Abstract
Reservoir sedimentation results in ongoing loss of storage capacity all around the world. Thus, effective sediment management in reservoirs is becoming an increasingly important task requiring detailed process understanding. Computational fluid dynamics modelling can provide an efficient means to study relevant processes. An [...] Read more.
Reservoir sedimentation results in ongoing loss of storage capacity all around the world. Thus, effective sediment management in reservoirs is becoming an increasingly important task requiring detailed process understanding. Computational fluid dynamics modelling can provide an efficient means to study relevant processes. An existing in-house hydrodynamic code has been extended to model particle-driven gravity currents. This has been realised through a buoyancy term which was added as a source term to the momentum equation. The model was successfully verified and validated using literature data of lock exchange experiments. In addition, the capability of the model to optimize venting of turbidity currents as an efficient sediment management strategy for reservoirs was tested. The results show that the concentration field during venting agrees well with observations from laboratory experiments documented in literature. The relevance of particle-driven gravity currents for the flow field in reservoirs is shown by comparing results of simulations with and without buoyant forces included into the model. The accuracy of the model in the area of the bottom outlet can possibly be improved through the implementation of a non-upwind scheme for the advection of velocity. Full article
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Open AccessFeature PaperArticle
Comparison of Local and Global Optimization Methods for Calibration of a 3D Morphodynamic Model of a Curved Channel
Water 2020, 12(5), 1333; https://doi.org/10.3390/w12051333 - 08 May 2020
Abstract
In curved channels, the flow characteristics, sediment transport mechanisms, and bed evolution are more complex than in straight channels, owing to the interaction between the centrifugal force and the pressure gradient, which results in the formation of secondary currents. Therefore, using an appropriate [...] Read more.
In curved channels, the flow characteristics, sediment transport mechanisms, and bed evolution are more complex than in straight channels, owing to the interaction between the centrifugal force and the pressure gradient, which results in the formation of secondary currents. Therefore, using an appropriate numerical model that considers this fully three-dimensional effect, and subsequently, the model calibration are substantial tasks for achieving reliable simulation results. The calibration of numerical models as a subjective approach can become challenging and highly time-consuming, especially for inexperienced modelers, due to dealing with a large number of input parameters with respect to hydraulics and sediment transport. Using optimization methods can notably facilitate and expedite the calibration procedure by reducing the user intervention, which results in a more objective selection of parameters. This study focuses on the application of four different optimization algorithms for calibration of a 3D morphodynamic numerical model of a curved channel. The performance of a local gradient-based method is compared with three global optimization algorithms in terms of accuracy and computational time (model runs). The outputs of the optimization methods demonstrate similar sets of calibrated parameters and almost the same degree of accuracy according to the achieved minimum of the objective function. Accordingly, the most efficient method concerning the number of model runs (i.e., local optimization method) is selected for further investigation by setting up additional numerical models using different sediment transport formulae and various discharge rates. The comparisons of bed topography changes in several longitudinal and cross-sections between the measured data and the results of the calibrated numerical models are presented. The outcomes show an acceptable degree of accuracy for the automatically calibrated models. Full article
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Open AccessArticle
An Intuitionistic Fuzzy Based Decision-Making Method for River Operation Management: Practice from China
Water 2020, 12(5), 1322; https://doi.org/10.3390/w12051322 - 07 May 2020
Abstract
River course is the path of carrying river flow and the blood of modern economic and social development. River operation management has attracted great attention from governments and water conservancy circles all over the world. In China, the river operation management mode refers [...] Read more.
River course is the path of carrying river flow and the blood of modern economic and social development. River operation management has attracted great attention from governments and water conservancy circles all over the world. In China, the river operation management mode refers to the combination of two dimensions: The organization method of river operation management and the bearing and use method of river maintenance fund. Based on the practice of China, we used a two-dimensional matrix method to construct a feasible mode set, including 12 modes, according to the various organization methods of river operation management and the bearing and use methods of river maintenance fund over the years in China. We also compared and analyzed the advantages, disadvantages, and applicable conditions of these 12 river operation management modes. In particular, we investigated the main rivers of 19 provinces and municipalities in China, identified the main factors of the river operation management mode, further identified 5 key indexes, and constructed a decision-making index system for the river operation management mode. We used the intuitionistic fuzzy hybrid average (IFHA) and intuitionistic fuzzy weighted average (IFWA) operators to construct a set of river operation management mode selection method based on intuitionistic fuzzy decision-making. A case study was conducted to select the operation management mode for the Heilongjiang section of Songhua River, using the method put forward in this paper. This study can promote water resource management research and prepare for a possible future sustainability emergency. Full article
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Open AccessArticle
A Prediction–Correction Solver for Real-Time Simulation of Free-Surface Flows in River Networks
Water 2019, 11(12), 2525; https://doi.org/10.3390/w11122525 - 29 Nov 2019
Cited by 2
Abstract
A prediction–correction solver is presented here for rapid simulation of free-surface flows in dendritic and looped river networks. Rather than solving a large global algebraic system over the entire domain of river networks, the model solves subsystems for subdomains of branches in two [...] Read more.
A prediction–correction solver is presented here for rapid simulation of free-surface flows in dendritic and looped river networks. Rather than solving a large global algebraic system over the entire domain of river networks, the model solves subsystems for subdomains of branches in two steps: prediction and correction. With the help of the prediction–correction method (PCM), the partial linearization technique, the semi-implicit method, and the Eulerian–Lagrangian method (ELM), the model only needs to solve tridiagonal linear systems for branches and is free of any iteration. The new model was tested using a hypothetical looped river network with regular cross sections, the Three Gorges Reservoir (TGR) dendritic river network, and the Jing-south looped river system (with seasonally flooding branches). In the first test, a time-step sensitivity study was conducted and the model was revealed to produce accurate simulations at large time steps when the condition for application of the PCM to river networks was satisfied. In the TGR test, the PCM model provided almost the same histories of water levels and discharges as those simulated by the HEC-RAS model. In the Jing-south test, the mean absolute error in simulated water levels was 0.07–0.24 m, and the relative error in simulated cross-section water flux was 0.5–4.9% compared with field data; the conservation error was generally 2 × 10−4 to 3 × 10−4. The PCM model was revealed to be 2–4 times as fast as a reported model, which solves local nonlinear subsystems using two-layer iterations, and 1.2–1.4 times as fast as the HEC-RAS. Using a time step of 1200 s, it took the sequential code 26.8 and 23.1 s to complete a simulation of a one-year unsteady flow process, respectively, in the TGR river networks (with 588 cells) and the Jing-south river system (with 662 cells). Full article
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