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DOE OSTI2017

Preconditioned steepest descent methods for some nonlinear elliptic equations involving p-Laplacian terms

We describe and analyze preconditioned steepest descent (PSD) solvers for fourth and sixth-order nonlinear elliptic equations that include p-Laplacian terms on periodic domains in 2 and 3 dimensions. The highest and lowest order terms of the equations are constant-coefficient, positive linear operators, which suggests a natural preconditioning strategy. Such nonlinear elliptic equations often arise from time discretization of parabolic equations that model various biological and physical phenomena, in particular, liquid crystals, thin film epitaxial growth and phase transformations. The analyses of the schemes involve the characterization of the strictly convex energies associated with the equations. We first give a general framework for PSD in Hilbert spaces. Based on certain reasonable assumptions of the linear pre-conditioner, a geometric convergence rate is shown for the nonlinear PSD iteration. We then apply the general theory to the fourth and sixth-order problems of interest, making use of Sobolev embedding and regularity results to confirm the appropriateness of our pre-conditioners for the regularized p-Lapacian problems. Our results include a sharper theoretical convergence result for p-Laplacian systems compared to what may be found in existing works. We demonstrate rigorously how to apply the theory in the finite dimensional setting using finite difference discretization methods. Numerical simulations for some important physical application problems – including thin film epitaxy with slope selection and the square phase field crystal model – are carried out to verify the efficiency of the scheme.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Establishing mesh topology in multi-material cells: enabling technology for robust and accurate multi-material simulations

Real world problems are typically multi-material, combining materials such as gases, liquids and solids that have very different properties. The material interfaces may be fixed in time or can be a part of the solution, as in fluid-structure interactions or air-water dynamics, and therefore move and change shape. In such problems the computational mesh may be non-conformal to interfaces due to complexity of these interfaces, presence of small fractions of materials, or because the mesh does not move with the flow, as in the arbitrary Lagrangian–Eulerian (ALE) methods. In order to solve problems of interest on such meshes, interface reconstruction methods are usually used to recover an approximation of material regions within the cells. For a cell intersecting multiple material regions, these approximations of contained subregions can be considered as single-material subcells in a local mesh that we call a minimesh. In this paper, we discuss some of the requirements that discretization methods have on topological information in the resulting hierarchical meshes and present an approach that allows incorporating the buildup of sufficiently detailed topology into the nested dissections based PLIC-type reconstruction algorithms (e.g. Volume-of-Fluid, Moment-of-Fluid) in an efficient and robust manner. Specifically, we describe the X-MOF interface reconstruction algorithm in 2D, which extends the Moment-Of-Fluid (MOF) method to include the topology of minimeshes created inside of multi-material cells and parent-child relations between corresponding mesh entities on different hierarchy levels. X-MOF retains the property of being local to a cell and not requiring external communication, which makes it suitable for massively parallel applications. Here, we demonstrate some scaling results for the X-MOF implementation in Tangram, a modern interface reconstruction framework for exascale computing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Real-time control of connected vehicles in signalized corridors using pseudospectral convex optimization

Recent advances in Connected and Automated Vehicle (CAV) technologies have opened up new opportunities to enable safe, efficient, and sustainable transportation systems. However, developing reliable and rapid speed control algorithms in highly dynamic environments with complex inter-vehicle interactions and nonlinear vehicle dynamics is still a daunting task. In this paper, we develop a novel speed control method for CAVs to produce optimal speed profiles that minimize the fuel consumption and avoid idling at signalized intersections. To this end, an optimal control problem is formulated using the information of the upcoming traffic signal to adapt vehicles' speeds to avoid frequent stop-and-go driving patterns. Here, by applying the pseudospectral discretization method and the sequential convex programming method, the computational efficiency is greatly improved, enabling potential real-time on-vehicle applications. In addition, the algorithm is implemented under a model predictive control framework to ensure online control with instant response for collision avoidance and robust vehicle coordination. The proposed algorithm is verified through numerical simulations of three different traffic scenarios. The convergence and accuracy of the proposed approach are demonstrated by comparing with a popular nonlinear solver. Furthermore, the benefit of the proposed method in both traffic mobility and fuel efficiency is validated using the speed profile determined from a traffic following model in a simulation software as the baseline.

42 ENGINEERING↗

DOE OSTI2016

Finite Volume Method Based Neutronic Solvers for Steady and Transient Analysis of Molten Salt Reactors

In recent years, the coupled neutronics and thermal hydraulics analysis becomes more and more important, because it helps to identify the most relevant safety issues without conservative assumptions. In addition, such coupled simulations are essential for the generation IV advanced nuclear power systems such as molten salt reactor (MSR), because the presence of strong coupling between different phenomena, like the transport of delayed neutron precursors by the fluid flow?. Due to the different discretization methods used in reactor physics analysis and thermal-hydraulics analysis, it is hard to couple different kinds of codes. This work presents an attempt to solve the multigroup neutron diffusion equation with the finite volume method which is quite widely used for the numerical simulation of a variety of applications involving fluid flow and heat and mass transfer. The unstructured finite volume method (FVM) based on open source C++ library OpenFOAM was chosen as the development platform?. The objective of this paper is to concisely present the main features of the developed codes in terms of the theoretical background and numerical approach and as can be seen in the following sections, the calculation results obtained by the NDSFoam which solves the steady-state neutron diffusion equation and NDTFoam which solves the transient-state neutron diffusion equation are discussed and compared to the benchmark problems. In this paper, two new neutronic solvers using finite volume method have been developed to perform the neutron physics analysis. The solvers are based on OpenFOAM, and have been tested with several steady state and transient-state benchmark problems. By verifications of the codes, it is proved that the development of NDSFoam and NDTFoam are correct. In our future work, both of these two solvers will be coupled with the precompiled CFD solvers in OpenFOAM to analyze the molten salt fast reactors. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2018

Design, analysis and preliminary numerical results for the nonconforming VEM for parabolic problems

The virtual element method (VEM) is a numerical methodology for solving partial differential equations on unstructured polytopal meshes. In this work, we extend the nonconforming high-order formulation suitable to time-dependent diffusion problems with possibly nonlinear forcing terms. Coupling high-order virtual element formulations in space with time-marching schemes based on Backward Differention Formulas (BDFs) makes a fully discrete method with optimal order of convergence in the Method of Lines framework. We investigate and assess the performance of the method through theoretical analysis and a set of numerical experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

High-order methods for wind turbine simulations and moving to next-generation platforms

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. This milestone represents an effort to increase the fidelity of Nalu-Wind at a fixed resolution through the implementation of a tensor-product based, matrix-free high order scheme. High order finite element methods have increased local work per datum communicated and have the potential to provide significantly more accurate solutions at a fixed number of degrees of freedom. Previous to this milestone, Nalu-Wind had an arbitrary order Control Volume Finite Element Method discretization as a solver option, but it required too much memory and was too slow to be of practical use. The work in this milestone addresses these issues by first implementing an implicit, high order solver that only partially assembles the global system. This reduces the memory footprint of the high-order scheme by orders of magnitude for higher polynomial orders. Second, a faster, tensor-product based method for evaluating the action of the left-hand side was implemented. This reduces the amount of computational work required by the scheme and dramatically enhanced the time-to-solution on example problems. Finally, this milestone is an evaluation of the value of high order methods in the wind application space. With the enhancements to memory and computational cost, accuracy vs. time-to-solution was evaluated for several resolutions on an under-resolved Taylor Green vortex test case. Results show that the high order scheme is cost-competitive with the production low-order schemes in Nalu-Wind, being moderately more expensive than the production edge-based vertex centered finite volume scheme. The evaluation of accuracy on the test case shows a potential benefit to high order at the highest resolution while not deteriorating accuracy on the lowest tested resolution. More work is needed to show value in the wind application, but positive strides have been made.

17 WIND ENERGY↗

NASA NTRS1983

Convergence characteristics of nonlinear vortex-lattice methods for configuration aerodynamics

Nonlinear panel methods have no proof for the existence and uniqueness of their solutions. The convergence characteristics of an iterative, nonlinear vortex-lattice method are, therefore, carefully investigated. The effects of several parameters, including 1) the surface-paneling method, 2) the integration method of the trajectories of the wake vortices, 3) vortex-grid refinement , and 4) the initial conditions for the first iteration on the computed aerodynamic coefficients and on the flow field details are presented. The convergence of the iterative-solution procedure is usually rapid. The solution converges with grid refinement to a constant value, but the final value is not unique and varies with the wing surface-paneling and wake-discretization methods within some range in the vicinity of the experimental result.

Seginer, A.↗

NASA NTRS1983

Convergence characteristics of nonlinear vortex-lattice methods for configuration aerodynamics

Nonlinear panel methods have no proof for the existence and uniqueness of their solutions. The convergence characteristics of an iterative, nonlinear vortex-lattice method are, therefore, carefully investigated. The effects of several parameters, including (1) the surface-paneling method, (2) an integration method of the trajectories of the wake vortices, (3) vortex-grid refinement, and (4) the initial conditions for the first iteration on the computed aerodynamic coefficients and on the flow-field details are presented. The convergence of the iterative-solution procedure is usually rapid. The solution converges with grid refinement to a constant value, but the final value is not unique and varies with the wing surface-paneling and wake-discretization methods within some range in the vicinity of the experimental result.

Seginer, A.↗

NASA NTRS1974

Selection of sampling rate for digital control of aircrafts

The considerations in selecting the sample rates for digital control of aircrafts are identified and evaluated using the optimal discrete method. A high performance aircraft model which includes a bending mode and wind gusts was studied. The following factors which influence the selection of the sampling rates were identified: (1) the time and roughness response to control inputs; (2) the response to external disturbances; and (3) the sensitivity to variations of parameters. It was found that the time response to a control input and the response to external disturbances limit the selection of the sampling rate. The optimal discrete regulator, the steady state Kalman filter, and the mean response to external disturbances are calculated.

Katz, P.↗

DOE OSTI2018

Regularized Finite Element Formulations for Shear Band Instabilities in Metals

In my research I have addressed several fundamental issues of dynamic fracture: 1. established the role of heat conduction as a natural regularizing mechanism in shearband problems (i.e. using the correct physics for this problem), 2. developed a unified model to incorporate fracture through a modified phase field formulation, 3. developed stability analysis tools to determine the onset of localization, 4. developed discretization methods and solvers to solve this problem (on parallel computers) that lead to mesh insensitive results and fast convergence. For such difficult problems, the physics and numerics are strongly coupled. To accurately model the physics, one must develop reliable numerics but reliable numerics depends on correct description of the physics. To this end, we have already made significant progress in the field showing that a fully-coupled implicit solution with heat conduction is the key to obtain reliable results for shear bands (see the next sections for more details). This research fits well within the mission of DOE ASCR program on all aspects: from governing equations to discretization to solvers to parallel computers to applications problems. It also relies on the computational tools developed through the SciDAC institutes FASTMath and SDAV, such as PETSc (and SLEPc), ParaView, Trilinos and Masquite.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Advanced Fluid Reduced Order Models for Compressible Flow.

This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly the POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2018

Fourier amplitude sensitivity test applied to dynamic combined finite-discrete element methods-based simulations

Fracture propagation plays a key role for a number of applications of interest to the scientific community, from dynamic fracture processes like spallation and fragmentation in metals to failure of ceramics, airplane wings, etc. Simulations of material deformation and fracture propagation rely on accurate knowledge of material characteristics such as material strength and the amount of energy being dissipated during the fracture process. Within the combined finite-discrete element method (FDEM) framework material fracture behavior is typically described through a parametrized softening curve, which defines a stress-strain relationship unique to each material. We apply the Fourier amplitude sensitivity test to explore how each of these parameters influences the simulated damage processes and to determine the key input parameters that have the most impact on the model response. We present several sensitivity numerical experiments for the simulation of a split Hopkinson pressure bar (SHPB) test for weathered granite samples using different combinations of model parameters. We validate the obtained results against SHPB experimental data. The experiments show that the model is mostly sensitive to parameters related to tensile and shear strengths, even in the presence of other parameter perturbations. Lastly, the results suggest that the specification of tensile and shear strengths at the interfaces dominate the stress-time history of the FDEM simulation of SHPB test.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Generalization of a stability domain estimation method for nonlinear discrete systems

In this paper, we present a generalization approach of an algebraic existing method to estimate stability regions for discrete nonlinear polynomial systems of degree 3. The existing method is based on the enlargement of a guaranteed stability region by applying various steps of a proposed algorithm. Its main limitation is that the initial result has only been subsequently developed in a particular case of a single iteration. The stability domain obtained is consequently not the widest one. Our main contribution in this paper is to develop generalized functions that allow the enlargement of the guaranteed stability region after k iterations, for any value of k. A required fundamental tool is developed and consists in a general formula allowing to give the result of the Kronecker power calculation of two matrices sum. The advantages of this generalization are to reach a larger region of asymptotic stability and to improve the existing methods results. Two application examples illustrate the proposed method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Simulation of mineral dissolution at the pore scale with evolving fluid-solid interfaces: review of approaches and benchmark problem set

This manuscript presents a benchmark problem for the simulation of single-phase flow, reactive transport, and solid geometry evolution at the pore scale. The problem is organized in three parts that focus on specific aspects: flow and reactive transport (part I), dissolution-driven geometry evolution in two dimensions (part II), and an experimental validation of three-dimensional dissolution-driven geometry evolution (part III). Five codes are used to obtain the solution to this benchmark problem, including Chombo-Crunch, OpenFOAM-DBS, a lattice Boltzman code, Vortex, and dissolFoam. These codes cover a good portion of the wide range of approaches typically employed for solving pore-scale problems in the literature, including discretization methods, characterization of the fluid-solid interfaces, and methods to move these interfaces as a result of fluid-solid reactions. A short review of these approaches is given in relation to selected published studies. Results from the simulations performed by the five codes show remarkable agreement both quantitatively--based on upscaled parameters such as surface area, solid volume, and effective reaction rate--and qualitatively--based on comparisons of shape evolution. This outcome is especially notable given the disparity of approaches used by the codes. Therefore, these results establish a strong benchmark for the validation and testing of pore-scale codes developed for the simulation of flow and reactive transport with evolving geometries. They also underscore the significant advances seen in the last decade in tools and approaches for simulating this type of problem.

58 GEOSCIENCES↗

DOE OSTI2013

Multigrid solution of a distributed optimal control problem constrained by the Stokes equations

We construct multigrid preconditioners to accelerate the solution process of a linear-quadratic optimal control problem constrained by the Stokes system. The first order optimality conditions of the control problem form a linear system (the KKT system) connecting the state, adjoint, and control variables. Our approach is to eliminate the state and adjoint variables by essentially solving two Stokes systems, and to construct efficient multigrid preconditioners for the Schur-complement of the block associated with the state and adjoint variables. These multigrid preconditioners are shown to be of optimal order with respect to the convergence properties of the discrete methods used to solve the Stokes system. In particular, the number of conjugate gradient iterations is shown to decrease as the resolution increases, a feature shared by similar multigrid preconditioners for elliptic constrained optimal control problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A dynamic 2D Borehole Thermal Energy Storage (BTES) model for enhanced computational efficiency

Progressing toward a future increasingly reliant on renewable energy sources, the development of effective, durable energy storage solutions becomes essential to balance supply and demand fluctuations. Borehole Thermal Energy Storage (BTES) is a long-duration thermal energy storage technology that captures excess heat generated from renewable energy sources and stores it underground for later use, enabling the efficient utilization of sustainable energy. This approach is particularly valuable in district energy networks when integrated with Ground Source Heat Pumps (GSHP) to provide stable heating and cooling. However, traditional three-dimensional (3D) numerical models of BTES systems demand extensive computational resources, limiting their practicality for real-time and large-scale applications. This study introduces a novel two-dimensional (2D) modeling approach that reduces computational costs while maintaining high accuracy. By employing a radial ring-based discretization method, the model simulates heat injection, retention, and retrieval dynamics over seasonal cycles. A new thermal-mass weighted-average temperature parameter is introduced to evaluate the performance of BTES systems. Model validation against FEFLOW simulations demonstrates a 17-fold improvement in computational speed compared to traditional Computational Fluid Dynamics (CFD) models while achieving a mean absolute percentage error (MAPE) of 2 % during charging and 4 % during discharging. Additionally, a trade-off analysis between computational efficiency and accuracy is conducted, ensuring the model's applicability for real-world scenarios. The findings of this research contribute to the development of computationally efficient BTES models, facilitating better optimization, control, and integration into renewable energy systems. This work provides a foundation for further studies in techno-economic analysis, multi-year performance evaluation, and real-time operational strategies for BTES applications, supporting a more sustainable energy future.

2D modeling↗

DOE OSTI2013

Development of a coupled thermo-hydro-mechanical model in discontinuous media for carbon sequestration

Geomechanical alteration of porous media is generally ignored for most shallow subsurface applications, whereas CO 2 injection, migration, and trapping in deep saline aquifers will be controlled by coupled multifluid flow, energy transfer, and geomechanical processes. The accurate assessment of the risks associated with potential leakage of injected CO 2 and the design of effective injection systems requires that we represent these coupled processes within numerical simulators. The objectives of this study were to develop a coupled thermal-hydro-mechanical model into a single software, and to examine the coupling of thermal, hydrological, and geomechanical processes for simulation of CO 2 injection into the subsurface for carbon sequestration. A numerical model is developed to couple nonisothermal multiphase hydrological and geomechanical processes for prediction of multiple interconnected processes for carbon sequestration in deep saline aquifers. The geomechanics model was based on Rigid Body-Spring Model (RBSM), one of the discrete methods to model discontinuous rock system. Poisson’s effect that was often ignored by RBSM was considered in the model. The simulation of large-scale and long-term coupled processes in carbon capture and storage projects requires large memory and computational performance. Global Array Toolkit was used to build the model to permit the high performance simulations of the coupled processes. The model was used to simulate a case study with several scenarios to demonstrate the impacts of considering coupled processes and Poisson’s effect for the prediction of CO 2 sequestration.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Simulation of stochastic diffusion via first exit times

In molecular biology it is of interest to simulate diffusion stochastically. In the mesoscopic model we partition a biological cell into unstructured subvolumes. In each subvolume the number of molecules is recorded at each time step and molecules can jump between neighboring subvolumes to model diffusion. The jump rates can be computed by discretizing the diffusion equation on that unstructured mesh. If the mesh is of poor quality, due to a complicated cell geometry, standard discretization methods can generate negative jump coefficients, which no longer allows the interpretation as the probability to jump between the subvolumes. We propose a method based on the mean first exit time of a molecule from a subvolume, which guarantees positive jump coefficients. Two approaches to exit times, a global and a local one, are presented and tested in simulations on meshes of different quality in two and three dimensions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗