We explore the coupling of surface and subsurface flows on fully unstructured meshes that conform to complex soil structures. To accommodate the distorted meshes that inevitably result from explicit representation of complex soil structures, we leverage the structure of the Mimetic Finite Difference (MFD) spatial discretization scheme to couple surface and subsurface flows. The MFD method achieves second-order accuracy and maintains local mass conservation on distorted meshes. We couple the diffusion wave approximation for surface flows to the Richards equation for subsurface flow, ensuring continuity of both pressure and flux between the surface and subsurface. The MFD method is particularly convenient for this coupling because it uses face-based constraints in the subsurface system that can be expressed as face-pressure unknowns. Those unknowns are coincident with surface cell-based unknowns, thus allowing the discrete surface system to be directly substituted into the subsurface system and solved implicitly as a global system. Robust representation of the transition between wet and dry surface conditions requires upwinding of the relative permeability and is facilitated by globalization in the nonlinear solver. The approach and its implementation in the Advanced Terrestrial Simulator (ATS) are evaluated by comparison to previously published benchmarks. Using runoff from soils with patchy groundcover (duff) as an example, we show that the new method converges significantly faster in mesh convergence tests than the commonly used two-point flux approximation.

The efficient solution of sparse, linear systems that arise through the discretization of partial differential equations remains a key challenge for a range of high performance scientific simulations. One approach for reducing data movement and improving performance is by exposing and exploiting structure in a problem through the use of robust structured multilevel solvers. By choosing coarsening that preserves the structure of the problem, these methods maintain efficient structured computation and communication throughout the multigrid hierarchy. However, when coarsening is not permitted to be dependent on the operator, anisotropy must be addressed by the smoother - producing error compatible for coarse-grid correction with structured coarsening. In this paper, the components required in a scalable parallel structured solver are described with a focus on memory and communication efficiency of robust smoothers. While the implementation of communication and memory reduction techniques in smoothers integrated in a complete 3D solver present a significant engineering challenge, a novel approach is proposed that addresses these challenges systematically through a change to the solver's execution model. Enabled by user-level threading paired with a set of data and communication abstractions, this approach permits seamless aggregation of communication in plane smoothers - directly reusing code for a 2D distributed multilevel cycle. Results show an effective reduction in communication costs for coarse-grid problems, and result in a speedup of 8.7x in smoothing routines shown in Fig. 12 using this approach. This produces a significant improvement to strong scalability while maintaining favorable weak scaling behavior. Finally, a parallel scaling study using a series of refined meshes is included that demonstrates the effectiveness of this approach in an application of interest.

The current work presents experimental and computational investigations of fluid flow through a 37 element CANDU nuclear fuel bundle. Experiments based on Magnetic Resonance Velocimetry (MRV) permit three-dimensional, three-component fluid velocity measurements to be made within the bundle with sub-millimeter resolution that are non-intrusive, do not require tracer particles or optical access of the flow field. Computational fluid dynamic (CFD) simulations of the foregoing experiments were performed with the HYDRA-TH code using implicit large eddy simulation, which were in good agreement with experimental measurements of the fluid velocity. Greater understanding has been gained in the evolution of geometry-induced inter-subchannel mixing, the local effects of obstructed debris on the local flow field, and various turbulent effects, such as recirculation, swirl and separation. These capabilities are not available with conventional experimental techniques or thermal-hydraulic codes. The overall goal of this work is to continue developing experimental and computational capabilities for further investigations that reliably support nuclear reactor performance and safety. (C) 2017 Elsevier Inc. All rights reserved.

A variant of Anderson Mixing, namely the Nonlinear Krylov Acceleration (NKA), is presented and implemented in a reconstructed Discontinuous Galerkin (rDG) method to solve the compressible Euler and Navier–Stokes equations on hybrid grids. A nonlinear system of equations as a result of a fully implicit temporal discretization at each time step is solved using the NKA method with a lower-upper symmetric Gauss–Seidel (LU-SGS) preconditioner. The developed NKA method is used to compute a variety of flow problems and compared with a well-known Newton-GMRES method to demonstrate the performance of the NKA method. Our numerical experiments indicate that the NKA method outperforms its Newton-GMRES counterpart for transient flow problems, and is comparable to Newton-GMRES for steady cases, and thus provides an attractive alternative to solve the system of nonlinear equations arising from the rDG approximation.

The need to understand potential climate impacts and feedbacks in Arctic regions has prompted recent interest in modeling of permafrost dynamics in a warming climate. A new fine‐scale integrated surface/subsurface thermal hydrology modeling capability is described and demonstrated in proof‐of‐concept simulations. The new modeling capability combines a surface energy balance model with recently developed three‐dimensional subsurface thermal hydrology models and new models for nonisothermal surface water flows and snow distribution in the microtopography. Surface water flows are modeled using the diffusion wave equation extended to include energy transport and phase change of ponded water. Variation of snow depth in the microtopography, physically the result of wind scour, is modeled phenomenologically with a diffusion wave equation. The multiple surface and subsurface processes are implemented by leveraging highly parallel community software. Fully integrated thermal hydrology simulations on the tilted open book catchment, an important test case for integrated surface/subsurface flow modeling, are presented. Fine‐scale 100 year projections of the integrated permafrost thermal hydrological system on an ice wedge polygon at Barrow Alaska in a warming climate are also presented. These simulations demonstrate the feasibility of microtopography‐resolving, process‐rich simulations as a tool to help understand possible future evolution of the carbon‐rich Arctic tundra in a warming climate.

The grid-to-rod fretting (GTRF) problem in pressurized water reactors is a flow-induced vibration phenomenon that results in wear and failure of the cladding material on fuel rods. Grid-to-rod fretting is responsible for over 70% of the fuel leaks in pressurized water reactors in the U.S. The GTRFinduced wear process involves turbulent flow, mechanical vibration, tribology, and time-varying irradiated material properties in complex fuel assembly geometries. This paper presents a new approach for predicting GTRF induced fuel rod wear that uses high-resolution large-eddy simulation to drive nonlinear transient dynamics computations. The GTRF fluid-structure problem is separated into the simulation of the turbulent flow field in the complexgeometry fuel-rod bundles, calculation of statistics of the resulting fluctuating structural forces, and the nonlinear transient dynamics analysis of the fuel rod. Implicit large-eddy simulation is used to compute the time-dependent fluid forces downstream of a Westinghouse designed spacer-grid with mixing vanes: The turbulent flow simulation procedure is first validated using a 5×5 rod bundle configuration and comparing simulated and experimentallymeasured velocities immediately downstream of the mixing vanes. Next, ✩LA-UR-14-28497 ∗Corresponding author. Email addresses: christon@lanl.gov (Mark A. Christon), lur@westinghouse.com (Roger Lu), jbakosi@lanl.gov (Jozsef Bakosi), balu@lanl.gov (Balu Nadiga), karoutze@westinghouse.com (Zeses Karoutas), berndt@lanl.gov (Markus Berndt) Preprint submitted to Journal of Computational Physics April 13, 2016 highly-instrumented large-eddy simulations of the 3 × 3 rod bundle flow using a sequence of four meshes with increasing resolution is performed. The forces on the central fuel rod downstream of the mixing vanes are seen to fall in an asymptotic regime at the finer three resolutions, and this feature of the numerics is exploited to obtain the limiting values of the fuel rod forces using Richardson extrapolation. Furthermore, uncertainty in the fuel rod forces due to turbulent intermittency are estimated using time-series data from the one second turbulent computations. Finally, the simulated fluid dynamic forces on the fuel rod are used in nonlinear transient dynamics analyses of a full length fuel rod with spacer grids to obtain fuel rod acceleration, displacement and fuel rod wear. Robustness of the behavior of both the structural forces computed from the turbulent flow simulations and the results from the transient dynamics analyses highlight the progress made towards achieving a predictive simulation capability for the GTRF problem.

Regarding the Arctic Terrestrial Simulator (ATS), previous work solved integrated hydrology (coupled surface/subsurface flow) on multiple polygons, and surface flow over larger domains to guide landscape characterization. Solved thermal hydrology with freeze/thaw dynamics in three dimensions. Ongoing efforts apply state of the art thermal hydrology model to complex topography, and include mesh deformation processes.

The current work presents investigations of fluid flow through a 37-element CANDU nuclear fuel bundle residing within a deformed pressure tube. This scenario simulates the long-term effects of aging, whereby the pressure tube may experience up to 6% diametral creep, resulting in appreciable flow bypass and the concomitant increase in fuel temperature due to local undercooling. This work examines in high spatial detail the three-dimensional, three-component fluid velocity field through the fuel channel. A companion paper is dedicated to the experimental component of this work, which is based on Magnetic Resonance Velocimetry. In the present paper, computational fluid dynamic simulations have been performed with HYDRA-TH using an implicit large eddy simulation to predict turbulent flow behaviour. Together, an improved understanding has been gained in quantifying flow by-pass, the evolution of geometry-induced inter-subchannel mixing, the local effects of obstructing debris on the local flow field, and various turbulent effects, such as recirculation, swirl and separated flow. These capabilities are not possible with conventional experimental techniques or thermal-hydraulic codes. The overall goal of this work is to continue developing experimental and computational capabilities for continued investigations to support nuclear reactor performance and safety.

A new second-order accurate, hybrid, incremental projection method for time-dependent incompressible viscous flow is introduced in this paper. The hybrid finite-element/finite-volume discretization circumvents the well-known Ladyzhenskaya–Babuška–Brezzi conditions for stability, and does not require special treatment to filter pressure modes by either Rhie–Chow interpolation or by using a Petrov–Galerkin finite element formulation. The use of a co-velocity with a high-resolution advection method and a linearly consistent edge-based treatment of viscous/diffusive terms yields a robust algorithm for a broad spectrum of incompressible flows. The high-resolution advection method is shown to deliver second-order spatial convergence on mixed element topology meshes, and the implicit advective treatment significantly increases the stable time-step size. The algorithm is robust and extensible, permitting the incorporation of features such as porous media flow, RANS and LES turbulence models, and semi-/fully-implicit time stepping. A series of verification and validation problems are used to illustrate the convergence properties of the algorithm. The temporal stability properties are demonstrated on a range of problems with 2≤CFL≤100. The new flow solver is built using the Hydra multiphysics toolkit. The Hydra toolkit is written in C++ and provides a rich suite of extensible and fully-parallel components that permit rapid application development, supports multiple discretization techniques, provides I/O interfaces, dynamic run-time load balancing and data migration, and interfaces to scalable popular linear solvers, e.g., in open-source packages such as HYPRE, PETSc, and Trilinos.

Grid-to-rod fretting (GTRF) in pressurized water reactors is a flow-induced vibration phenomenon that results in wear and fretting of the cladding material on fuel rods. GTRF is responsible for over 70% of the fuel failures in pressurized water reactors in the United States. Predicting the GTRF wear and concomitant interval between failures is important because of the large costs associated with reactor shutdown and replacement of fuel rod assemblies. The GTRF-induced wear process involves turbulent flow, mechanical vibration, tribology, and time-varying irradiated material properties in complex fuel assembly geometries. This paper presents a new approach for predicting GTRF induced fuel rod wear that uses high-resolution implicit large-eddy simulation to drive nonlinear transient dynamics computations. The GTRF fluid–structure problem is separated into the simulation of the turbulent flow field in the complex-geometry fuel-rod bundles using implicit large-eddy simulation, the calculation of statistics of the resulting fluctuating structural forces, and the nonlinear transient dynamics analysis of the fuel rod. Ultimately, the methods developed here, can be used, in conjunction with operational management, to improve reactor core designs in which fuel rod failures are minimized or potentially eliminated. Robustness of the behavior of both the structural forces computed from the turbulent flow simulations and the results from the transient dynamics analyses highlight the progress made towards achieving a predictive simulation capability for the GTRF problem.

Advanced modeling and simulation has enabled the design of a variety of innovative products and the analysis of numerous complex phenomenon. However, significant barriers exist to widespread adoption of these tools. In particular, advanced modeling and simulation: (1) is considered complex to use, (2) needs in-house expertise, and (3) requires high capital costs. In this paper, we describe the development of an end-to-end, advanced modeling and simulation cloud platform that encapsulates best practices for scientific computing in the cloud, and demonstrate using Hydra-TH as a prototypical application. As an alternative to traditional advanced modeling and simulation workflows, our Web-based approach simplifies the processes, decreases the need for in-house computational science and engineering experts, and lowers the capital investments. In addition to providing significantly improved, intuitive software, the environment offers reproducible workflows where the full lifecycle of data from input to final analyzed results can be saved, shared, and even published.

We have developed a sophisticated mesh infrastructure capability to support large scale multiphysics simulations such as subsurface flow and reactive contaminant transport at storage sites as well as the analysis of the effects of a warming climate on the terrestrial arctic. These simulations involve a wide range of coupled processes including overland flow, subsurface flow, freezing and thawing of ice rich soil, accumulation, redistribution and melting of snow, biogeochemical processes involving plant matter and finally, microtopography evolution due to melting and degradation of ice wedges below the surface. In addition to supporting the usual topological and geometric queries about the mesh, the mesh infrastructure adds capabilities such as identifying columnar structures in the mesh, enabling deforming of the mesh subject to constraints and enabling the simultaneous use of meshes of different dimensionality for subsurface and surface processes. The generic mesh interface is capable of using three different open source mesh frameworks (MSTK, MOAB and STKmesh) under the hood allowing the developers to directly compare them and choose one that is best suited for the application's needs. We demonstrate the results of some simulations using these capabilities as well as present a comparison of the performance of the different mesh frameworks.

We have developed a sophisticated mesh infrastructure capability to support large scale multiphysics simulations such as subsurface flow and reactive contaminant transport at storage sites as well as the analysis of the effects of a warming climate on the terrestrial arctic. These simulations involve a wide range of coupled processes including overland flow, subsurface flow, freezing and thawing of ice rich soil, accumulation, redistribution and melting of snow, biogeochemical processes involving plant matter and finally, microtopography evolution due to melting and degradation of ice wedges below the surface. In addition to supporting the usual topological and geometric queries about the mesh, the mesh infrastructure adds capabilities such as identifying columnar structures in the mesh, enabling deforming of the mesh subject to constraints and enabling the simultaneous use of meshes of different dimensionality for subsurface and surface processes. The generic mesh interface is capable of using three different open source mesh frameworks (MSTK, MOAB and STKmesh) under the hood allowing the developers to directly compare them and choose one that is best suited for the application’s needs. We demonstrate the results of some simulations using these capabilities as well as present a comparison of the performance of the different mesh frameworks. c © 2014 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of organizing committee of the 23rd International Meshing Roundtable (IMR23).

We present a preliminary method to generate polyhedral meshes of general non-manifold domains. The method is based on computing the dual of a general tetrahedral mesh. The resulting mesh respects the topology of the domain to the same extent as the input mesh. If the input tetrahedral mesh is Delaunay and well-centered, the resulting mesh is a Voronoi mesh with planar faces. For general tetrahedral meshes, the resulting mesh is a polyhedral mesh with straight edges but possibly curved faces. The initial mesh generation phase is followed by a mesh untangling and quality improvement technique.We demonstrate the technique on some simple to moderately complex domains.

We compare a variant of Anderson Mixing with the Jacobian-Free Newton–Krylov and Broyden methods applied to an instance of the k-eigenvalue formulation of the linear Boltzmann transport equation. We present evidence that one variant of Anderson Mixing finds solutions in the fewest number of iterations. We examine and strengthen theoretical results of Anderson Mixing applied to linear problems.