Presented in this document is a portion of the tests that exist in the Sierra Thermal/Fluids verification test suite. Each of these tests is run nightly with the Sierra/TF code suite and the results of the test checked under mesh refinement against the correct analytic result. For each of the tests presented in this document the test setup, derivation of the analytic solution, and comparison of the code results to the analytic solution is provided. This document can be used to confirm that a given code capability is verified or referenced as a compilation of example problems.
The study of heat transfer and ablation plays an important role in many problems of scientific and engineering interest. As with the computational simulation of any physical phenomenon, the first step towards establishing credibility in ablation simulations involves code verification. Code verification is typically performed using exact and manufactured solutions. However, manufactured solutions generally require the invasive introduction of an artificial forcing term within the source code, such that the code solves a modified problem for which the solution is known. In this paper, we present a nonintrusive method for manufacturing solutions for a non-decomposing ablation code, which does not require the addition of a source term.
The study of heat transfer and ablation plays an important role in many problems of scientific and engineering interest. As with the computational simulation of any physical phenomenon, the first step toward establishing credibility in ablation simulations involves code verification. Code verification is typically performed using exact and manufactured solutions. However, manufactured solutions generally require the invasive introduction of an artificial forcing term within the source code such that the code solves a modified problem for which the solution is known. In this paper, we present a nonintrusive method for manufacturing solutions for a non-decomposing ablation code, which does not require the addition of a source term.
The study of heat transfer and ablation plays an important role in many problems of scientific and engineering interest. As with the computational simulation of any physical phenomenon, the first step toward establishing credibility in ablation simulations involves code verification. Code verification is typically performed using exact and manufactured solutions. However, manufactured solutions generally require the invasive introduction of an artificial forcing term within the source code such that the code solves a modified problem for which the solution is known. In this paper, we present a nonintrusive method for manufacturing solutions for a non-decomposing ablation code, which does not require the addition of a source term.
The study of hypersonic flows and their underlying aerothermochemical reactions is particularly important in the design and analysis of vehicles exiting and reentering Earth's atmosphere. Computational physics codes can be employed to simulate these phenomena; however, code verification of these codes is necessary to certify their credibility. To date, few approaches have been presented for verifying codes that simulate hypersonic flows, especially flows reacting in thermochemical nonequilibrium. In this work, we present our code-verification techniques for verifying the spatial accuracy and thermochemical source term in hypersonic reacting flows in thermochemical nonequilibrium. Additionally, we demonstrate the effectiveness of these techniques on the Sandia Parallel Aerodynamics and Reentry Code (SPARC).
We propose a probabilistic framework for assessing the consistency of an experimental dataset, i.e., whether the stated experimental conditions are consistent with the measurements provided. In case the dataset is inconsistent, our framework allows one to hypothesize and test sources of inconsistencies. This is crucial in model validation efforts. The framework relies on statistical inference to estimate experimental settings deemed untrustworthy, from measurements deemed accurate. The quality of the inferred variables is gauged by its ability to reproduce held-out experimental measurements; if the new predictions are closer to measurements than before, the cause of the discrepancy is deemed to have been found. The framework brings together recent advances in the use of Bayesian inference and statistical emulators in fluid dynamics with similarity measures for random variables to construct the hypothesis testing approach. We test the framework on two double-cone experiments executed in the LENS-XX wind tunnel and one in the LENS-I tunnel; all three have encountered difficulties when used in model validation exercises. However, the cause behind the difficulties with the LENS-I experiment is known, and our inferential framework recovers it. We also detect an inconsistency with one of the LENS-XX experiments, and hypothesize three causes for it. We check two of the hypotheses using our framework, and we find evidence that rejects them. We end by proposing that uncertainty quantification methods be used more widely to understand experiments and characterize facilities, and we cite three different methods to do so, the third of which we present in this paper.
The study of hypersonic flows and their underlying aerothermochemical reactions is particularly important in the design and analysis of vehicles exiting and reentering Earth’s atmosphere. Computational physics codes can be employed to simulate these phenomena; however, code verification of these codes is necessary to certify their credibility. To date, few approaches have been presented for verifying codes that simulate hypersonic flows, especially flows reacting in thermochemical nonequilibrium. In this paper, we present our code-verification techniques for hypersonic reacting flows in thermochemical nonequilibrium, as well as their deployment in the Sandia Parallel Aerodynamics and Reentry Code (SPARC).
The SPARC (Sandia Parallel Aerodynamics and Reentry Code) will provide nuclear weapon qualification evidence for the random vibration and thermal environments created by re-entry of a warhead into the earth’s atmosphere. SPARC incorporates the innovative approaches of ATDM projects on several fronts including: effective harnessing of heterogeneous compute nodes using Kokkos, exascale-ready parallel scalability through asynchronous multi-tasking, uncertainty quantification through Sacado integration, implementation of state-of-the-art reentry physics and multiscale models, use of advanced verification and validation methods, and enabling of improved workflows for users. SPARC is being developed primarily for the Department of Energy nuclear weapon program, with additional development and use of the code is being supported by the Department of Defense for conventional weapons programs.
This document is the main user guide for the Sierra/Percept capabilities including the mesh_adapt and mesh_transfer tools. Basic capabilities for uniform mesh refinement (UMR) and mesh transfers are discussed. Examples are used to provide illustration. Future versions of this manual will include more advanced features such as geometry and mesh smoothing. Additionally, all the options for the mesh_adapt code will be described in detail. Capabilities for local adaptivity in the context of offline adaptivity will also be included. This page intentionally left blank.
The Encore software package is both a stand-alone application and a software library. This guide explains the syntax of Encore input, provides examples, and is a comprehensive catalog of the Encore commands. Acting as a stand-alone application, Encore provides utilities for reading solutions from files and enables solution verification, postprocessing, field transfers, and basic mesh refinement. Acting as a software library, Encore is a component of the fluid, thermal, and solid modeling applications in the Sierra Mechanics suite. As a library, Encore provides the enclosing modeling application a superset of the stand-alone capabilities—enabled by application specific information—including physics specific postprocessors and adaptive mesh refinement.
This document is the main user guide for the Sierra/Percept capabilities including the mesh_adapt and mesh_transfer tools. Basic capabilities for uniform mesh refinement (UMR) and mesh transfers are discussed. Examples are used to provide illustration. Future versions of this manual will include more advanced features such as geometry and mesh smoothing. Additionally, all the options for the mesh_adapt code will be described in detail. Capabilities for local adaptivity in the context of offline adaptivity will also be included.
We propose a new approach for the stabilization of linear tetrahedral finite elements in the case of nearly incompressible transient solid dynamics computations. Our method is based on a mixed formulation, in which the momentum equation is complemented by a rate equation for the evolution of the pressure field, approximated with piecewise linear, continuous finite element functions. The pressure equation is stabilized to prevent spurious pressure oscillations in computations. Incidentally, it is also shown that many stabilized methods previously developed for the static case do not generalize easily to transient dynamics. Extensive tests in the context of linear and nonlinear elasticity are used to corroborate the claim that the proposed method is robust, stable, and accurate.
The 2014 Sandia Verification & Validation Challenge Workshop was held at the 3rd ASME Verification & Validation Symposium in Las Vegas, on May 5-8, 2014. The workshop was built around a challenge problem, formulated as an engineering investigation that required integration of experimental data, modeling and simulation, and verification and validation. The challenge problem served as a common basis for the ASME Journal of Verification, Validation, and Uncertainty Quantification participants to both demonstrate methodology and explore a critical aspect of the field: the role of verification and validation in establishing credibility and supporting decision making. Ten groups presented responses to the challenge problem at the workshop, and the follow-on efforts are documented in this special edition of the ASME Journal of Verification, Validation, and Uncertainty Quantification.
Solution verification is the process of verifying the solution of a finite element analysis by performing a series of analyses on meshes of increasing mesh densities, to determine if the solution is converging. Solution verification has historically been too expensive, relying upon refinement templates resulting in an 8X multiplier in the number of elements. For even simple convergence studies, the 8X and 64X meshes must be solved, quickly exhausting computational resources. In this paper, we introduce Mesh Scaling, a new global mesh refinement technique for building series of all-hexahedral meshes for solution verification, without the 8X multiplier. Mesh Scaling reverse engineers the block decomposition of existing all-hexahedral meshes followed by remeshing the block decomposition using the original mesh as the sizing function multiplied by any positive floating number (e.g. 0.5X, 2X, 4X, 6X, etc.), enabling larger series of meshes to be constructed with fewer elements, making solution verification tractable.
Verification of tightly coupled multiphysics computational codes is generally significantly more difficult than verification of single-physics codes. The case of coupled heat conduction and thermal radiation in an enclosure is considered, and it is extended to a manufactured solution verification test for enclosure radiation to a fully two-dimensional coupled problem with conduction and thermal radiation. Convergence results are shown using a production thermal analysis code. Convergence rates are optimal with a pairwise view-factor calculation algorithm.
A new tool, called Mesh Scaling, for producing series of hexahedral meshes suitable for solution verification was enhanced and hardened by this milestone. In addition, solution verification using the meshes produced from Mesh Scaling was performed and documented. We conclude that Mesh Scaling now produces meshes suitable for solution verification, while offering a substantial decrease in the computational cost of solution verification.
