Desalination discharges are commonly in the form of inclined negatively buoyant jets (INBJs). Numerical predictions of INBJs remain a challenge. While accurate large eddy simulations (LES) of INBJs have become available very recently, they are substantially more resource intensive. Reynolds-averaged Navier–Stokes (RANS) modelling is potentially more efficient and can be more readily applied in practice. However, existing RANS simulations show substantial error when compared with experimental measurements. In this study, RANS simulations of 45° INBJs are performed with a dynamic turbulent Schmidt number (DTSN) approach. This new approach involves extracting turbulent Schmidt number ( Sc_t ) profiles in the INBJs from recently published LES data that have been validated by experiments. Detailed cross-sectional Sc_t profiles in INBJs are reported here for the first time. The relationship between Sc_t and a local mean flow parameter is also determined from the LES data. RANS simulations are then performed—with Sc_t being allowed to change dynamically during the simulation according to the pre-determined relationship. The results show that the DTSN approach improved the overall predictive capabilities of the RANS model to a limited extent. However, significant issues remain in terms of the models’ ability to predict dilutions in the descending portion of the flow. Importantly, the DTSN simulations demonstrate that the model predictions are sensitive to the determination of the relationship between Sc_t and the local flow parameter. Further improvements in the DTSN approach are therefore possible with refinement to the characterisation of this relationship. Based on a discussion of the present and recent literature describing RANS simulations of INBJs, the authors encourage a more cautious interpretation of the current predictive capabilities of RANS simulations in the context of INBJs.

The results of numerical simulations of inclined negatively buoyant jets are presented. These simulations address previously highlighted difficulties in capturing sufficient detail of critical flow processes to effectively predict the detailed flow behaviour. In particular, the new simulations are able to accurately capture the details of the buoyancy-induced instabilities, which are clearly evident in associated experimental investigations and that have significant impacts on the flow behaviour. This new information is captured for inclined negatively buoyant jets discharged at 45° above a horizontal reference plane. A Large Eddy Simulation (LES) approach is implemented that makes use of a Lagrangian Dynamic Sub-grid scale (SGS) model and a novel criterion for the adaptive meshing system. Comparisons with previously published simulation results and experimental data demonstrate that these new Adaptive LES simulations provide improved predictions of flow path, concentration and velocity fields, and associated mean and turbulent statistics. In addition, this study provides a set of methods for generating high-quality LES data sets for free shear flows, which are well beyond the level of detail that can be captured by current experimental systems.

AbstractEffectively forecasting and communicating flood hazards at national or continental scales is critical to reducing impacts of flooding. Yet, it remains a challenge due to the predominance of ungauged catchments in often complex and steep terrain. We present the development, communication, and evaluation of a national flood awareness system, the Aotearoa (New Zealand) Flood Awareness System, AFAS. Forecasts are produced with an uncalibrated, semi‐distributed hydrological model, driven by a high‐resolution convective‐scale atmospheric model with statistical perturbations in rainfall, soil moisture and baseflow to generate a 50‐member ensemble. We implement a relative flow and flood exceedance threshold framework to evaluate hourly forecasts across six categories from below normal to extremely high. Forecast performance is categorically assessed against observations, for a 2.5‐year reforecast, at 272 sites nationwide, up to 48 h ahead. Overall, AFAS produces skilful streamflow forecasts in catchments with complex topography, even with operational delays ingesting observations. We explore a novel approach to river forecast communication using daily videos. We suggest rethinking large‐scale streamflow forecast communication by balancing a depth with breadth approach (pointwise absolute flows versus distributed relative flows), to raise collective awareness before and during natural disasters. AFAS appears to be the first system producing public‐friendly videos to communicate streamflow forecasts in their topographical context. Future development of AFAS will benefit from a federated approach across national and regional agencies, including sharing of real‐time weather observations, forecasting tools and expertise.

A novel mesh refinement sensor is proposed for lattice Boltzmann methods (LBMs) applicable to either static or dynamic mesh refinement algorithms. The sensor exploits the kinetic nature of LBMs by evaluating the departure of distribution functions from their local equilibrium state. This sensor is first compared, in a qualitative manner, to three state-of-the-art sensors: (1) the vorticity norm, (2) the Q-criterion, and (3) spatial derivatives of the vorticity. This comparison shows that our kinetic sensor is the most adequate candidate to propose tailored mesh structures across a wide range of physical phenomena: incompressible, compressible subsonic/supersonic single phase, and weakly compressible multiphase flows. As a more quantitative validation, the sensor is then used to produce the computational mesh for two existing open-source LB solvers based on inhomogeneous, block-structured meshes with static and dynamic refinement algorithms, implemented in the Palabos and AMROC-LBM software, respectively. The sensor is first used to generate a static mesh to simulate the turbulent 3D lid-driven cavity flow using Palabos. AMROC-LBM is then adopted to confirm the ability of our sensor to dynamically adapt the mesh to reach the steady state of the 2D lid-driven cavity flow. Both configurations show that our sensor successfully produces meshes of high quality and allows to save computational time.

Introduction: This poster presents the computational workflow and results of the August 2020 version (v20.8) of probabilistic seismic hazard analysis (PSHA) in New Zealand (NZ) based on physics-based ground motion simulations (‘Cybershake NZ’). This version includes several notable advancements resulting from an improved NZ-wide Vs30 model, and revisions to the hybrid broadband ground motion simulation method of Graves and Pitarka (2010, 2015, 2016) based on simulation validation in Lee et al. (2019) which results in changes to the high-frequency method and the empirical site amplification factors around the transition frequency.

We present the scope, concepts, data structures and application programming models of the open-source Lattice Boltzmann library Palabos. Palabos is a C++ software platform developed since 2010 for Computational Fluid Dynamics simulations and Lattice Boltzmann modeling, which specifically targets applications with complex, coupled physics. The software proposes a very broad modeling framework, capable of addressing a large number of applications of interest in the Lattice Boltzmann community, yet exhibits solid computational performance. The article describes the philosophy of this programming framework and lists the models already implemented. Finally, benchmark simulations are provided which serve as a proof of quality of the implemented core functionalities.

As the cost of lifeline disruption rises with the size and complexity of urban communities, increasing efforts are put into enhancing infrastructure resilience to natural disasters. Aiming to improve the understanding of water supply network seismic resilience, this paper examines in detail the initial performance and restoration of the water supply network following the 22 February 2011 M w 6.2 Christchurch, New Zealand earthquake. In addition, a method to optimize the recovery of such systems is developed in two phases: the prioritization of pipe inspection and prioritization of pipe repairs. The results inferred from the observed pipe repairs suggest that the recovery was carried out efficiently; however, applying the proposed methodology would have substantially improved the recovery of the system with a 30% reduction in the number of buildings deprived of water in the first two days. Assumptions and limitations of the modeling are also discussed and practical solutions given to apply this framework in real-time for post-earthquake restoration.

This paper presents the computational components and results of the May 2018 version (v18.5) of probabilistic seismic hazard analysis (PSHA) in New Zealand based on physics-based ground motion simulations (`Cybershake NZ'). A total of 11,362 finite fault simulations are undertaken and seismic hazard results are computed on a spatiallyvariable grid of 27,481 stationswith distributed seismicity sources considered via conventional empirical ground motion models. In the current work completed to datethe Graves and Pitarka ( 20102015) hybrid broadband ground motion simulation approach is utilized considering a transition frequency of 0.25 Hza detailed crustal model with a grid spacing of 0.4 kmand an empirically-calibrated local site response model. A Monte Carlo scheme is used to sample variability in the seismic source parametrization (by varying the hypocenter location and slip distribution per each hypocenter realization)with the total number of ruptures for each fault being a function of the rupture magnitude. The generated uniform hazard maps across the country are presented. Treatment of uncertainty in the context of simulation-based PSHA and improvements for future versions of the ongoing effort are discussed.

Ground Motion (GM) Simulation involves complex calculations that produce a large collection of numerical data, which needs a good visual presentation to help better understanding of the complex dynamics of the earthquake. In this poster, we present a visualisation workflow that we developed to produce a 3D animation from the simulation data of the 2016 M7.8 Kaikoura earthquake as a case study, and discuss how it facilitated scientific discovery and communication.

Grid refinement has been addressed by different authors in the lattice Boltzmann method community. The information communication and reconstruction on grid transitions is of crucial importance from the accuracy and numerical stability point of view. While a decimation is performed when going from the fine to the coarse grid, a reconstruction must performed to pass form the coarse to the fine grid. In this context, we introduce a decimation technique for the copy from the fine to the coarse grid based on a filtering operation. We show this operation to be extremely important, because a simple copy of the information is not sufficient to guarantee the stability of the numerical scheme at high Reynolds numbers. Then we demonstrate that to reconstruct the information, a local cubic interpolation scheme is mandatory in order to get a precision compatible with the order of accuracy of the lattice Boltzmann method.These two fundamental extra-steps are validated on two classical 2D benchmarks, the 2D circular cylinder and the 2D dipole–wall collision. The latter is especially challenging from the numerical point of view since we allow strong gradients to cross the refinement interfaces at a relatively high Reynolds number of 5000. A very good agreement is found between the single grid and the refined grid cases.The proposed grid refinement strategy has been implemented in the parallel open-source library Palabos.

We present numerical simulations of bloodflow in cerebral aneurysms, obtained with the open source software Palabos which provides a flexible, highly parallelized and publicly available environment for the lattice Boltzmann (LB) method. LB models are promising tools for biomedical modeling that compares well with more traditional CFD techniques and can be easily augmented to include non-Newtonian rheology or biological processes. In this paper we shall discuss a LB model describing the formation of a thrombus in a cerebral aneurysmal cavity, whether spontaneous or induced by a flow diverter (stent).

We propose a inhomogeneous cellular automata (CA) model in which several species compete for their territory and can co-evolved in regions where several of them coexist. Our model has as few parameters as possible. Each cell represent an individual and the associated CA rule represents its genome. The state evolution of each cell is interpreted as a phenotype. The fitness is defined as the cell activity, i.e. the variability of the state over time. Individuals of low fitness evolves by copying part of the genomes of neighboring high fitness individuals. We then consider a computer experiment implementing the competition-evolution of two species (two rules) each populating initially half of cellular space.

Figure 2 shows the SeisFinder web interface for extraction at a single location of interest. Figure 3 shows the web interface for multiple locations of interest. Multiple location inputs can be uploaded in a CSV file. Figure 4 shows the output screen for multiple locations for a future Alpine Fault event (south to north scenario). The downloadable zip file contains the acceleration times series, intensity measures and the location metadata as shown in Figure 5. Figure 3: SeisFinder web interface for multiple locations of interest. Contains location metadata