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This software package can be used to build, train, and test a neural network machine learning model. The neural network architecture is specifically designed to embed tensor invariance properties by enforcing that the model predictions sit on an invariant tensor basis. This neural network architecture can be used in developing constitutive models for applications such as turbulence modeling, materials science, and electromagnetism.
Arrows is a software package that combines NWChem, SQL and NOSQL databases, email, and social networks (e.g. Twitter, Tumblr) that simplifies molecular and materials modeling and makes these modeling capabilities accessible to all scientists and engineers. EMSL Arrows is very simple to use. The user just emails chemical reactions to arrows@emsl.pnnl.gov and then an email is sent back with thermodynamic, reaction pathway (kinetic), spectroscopy, and other results. EMSL Arrows parses the email and then searches the database for the compounds in the reactions. If a compound isn't there, an NWChem calculation is setup and submitted to calculate it. Once the calculation is finished the results are entered into the database and then results are emailed back.
This package is a set of extensions to MOOSE (https://moose.inl.gov) adding anisotropic graphite material models for irradiation creep and swelling. The goal of the package is to provide a framework to model graphite components for use in future high temperature nuclear reactors.
Burst testing has long been a relied-on method for assessing fuel cladding materials in light-water reactoraccident scenarios. However, burst testing historically provided minimal in-situ observations beyond a few thermocouple readings, pressure from transducers, and post-test deformation measurements. Acquisition of full cladding thermomechanical data throughout a burst test would be invaluable to fuel system qualification, material model development and fuel performance code validation, such as the BISON fuel performance code. Recently, methodologies for simultaneously applying 2-dimensional digital image correlation and infrared thermography techniques to quantify the relationship between temperature, internal cladding pressure, and deformation during burst testing were developed. This work details results from the application of these techniques to burst testing of Zircaloy-4 cladding segments subjected to loss-of-coolant accident transients in an air environment. Two types of tests were performed with: (a) cladding segments connected to a fixed pressure reservoir as well as (b) closed systems where internal pressure increased during transients. In-situ thermomechanical measurements including strain and thermal gradient data are presented, demonstrating the effectiveness of applying combined surface measurement techniques to burst testing
The intent of this research effort is to prove the hypothesis that: Through the employment of controlled processing parameters which are based upon integrated advanced material characterization and multi-physics material modeling, bulk nanolayered composites can be designed to contain high densities of preferred interfaces that can serve as supersinks for the defects responsible for premature damage and failure.
The two primary purposes of LANL’s Computational Physics Student Summer Workshop are (1) To educate graduate and exceptional undergraduate students in the challenges and applications of computational physics of interest to LANL, and (2) Entice their interest toward those challenges. Computational physics is emerging as a discipline in its own right, combining expertise in mathematics, physics, and computer science. The mathematical aspects focus on numerical methods for solving equations on the computer as well as developing test problems with analytical solutions. The physics aspects are very broad, ranging from low-temperature material modeling to extremely high temperature plasma physics, radiation transport and neutron transport. The computer science issues are concerned with matching numerical algorithms to emerging architectures and maintaining the quality of extremely large codes built to perform multi-physics calculations. Although graduate programs associated with computational physics are emerging, it is apparent that the pool of U.S. citizens in this multi-disciplinary field is relatively small and is typically not focused on the aspects that are of primary interest to LANL. Furthermore, more structured foundations for LANL interaction with universities in computational physics is needed; historically interactions rely heavily on individuals’ personalities and personal contacts. Thus a tertiary purpose of the Summer Workshop is to build an educational network of LANL researchers, university professors, and emerging students to advance the field and LANL’s involvement in it.
The following table constitutes an initial assessment of feature coverage across the regression test suite used for DYNA3D and ParaDyn. It documents the regression test suite at the time of preliminary release 16.1 in September 2016. The columns of the table represent groupings of functionalities, e.g., material models. Each problem in the test suite is represented by a row in the table. All features exercised by the problem are denoted by a check mark (√) in the corresponding column. The definition of “feature” has not been subdivided to its smallest unit of user input, e.g., algorithmic parameters specific to a particular type of contact surface. This represents a judgment to provide code developers and users a reasonable impression of feature coverage without expanding the width of the table by several multiples. All regression testing is run in parallel, typically with eight processors, except problems involving features only available in serial mode. Many are strictly regression tests acting as a check that the codes continue to produce adequately repeatable results as development unfolds; compilers change and platforms are replaced. A subset of the tests represents true verification problems that have been checked against analytical or other benchmark solutions. Users are welcomed to submit documented problems for inclusion in the test suite, especially if they are heavily exercising, and dependent upon, features that are currently underrepresented.
Nonreactor nuclear facilities operating under the approval authority of the U.S. Department of Energy use unmitigated hazard evaluations to determine if potential radiological doses associated with design basis events challenge or exceed dose evaluation guidelines. Unmitigated design basis events that sufficiently challenge dose evaluation guidelines or exceed the guidelines for members of the public or workers, merit selection of safety structures, systems, or components or other controls to prevent or mitigate the hazard. Idaho State University, in collaboration with Idaho National Laboratory, has developed a portable and simple to use software application called SODA (Stochastic Objective Decision-Aide) that stochastically calculates the radiation dose distribution associated with hypothetical radiological material release scenarios. Rather than producing a point estimate of the dose, SODA produces a dose distribution result to allow a deeper understanding of the dose potential. SODA allows users to select the distribution type and parameter values for all of the input variables used to perform the dose calculation. Users can also specify custom distributions through a user defined distribution option. SODA then randomly samples each distribution input variable and calculates the overall resulting dose distribution. In cases where an input variable distribution is unknown, a traditional single point value can be used. SODA, developed using the MATLAB coding framework, has a graphical user interface and can be installed on both Windows and Mac computers. SODA is a standalone software application and does not require MATLAB to function. SODA provides improved risk understanding leading to better informed decision making associated with establishing nuclear facility material-at-risk limits and safety structure, system, or component selection. It is important to note that SODA does not replace or compete with codes such as MACCS or RSAC; rather it is viewed as an easy to use supplemental tool to help improve risk understanding and support better informed decisions. The SODA development project was funded through a grant from the DOE Nuclear Safety Research and Development Program.
Quantum computing (QC) is a promising early-stage technology with the potential to provide scientific computing capabilities far beyond what is possible with even an Exascale computer in specific problems of relevance to the Office of Science. These include (but are not limited to) materials modeling, molecular dynamics, and quantum chromodynamics. However, commercial QC systems are not yet available and the technical maturity of current QC hardware, software, algorithms, and systems integration is woefully incomplete. Thus, there is a significant opportunity for DOE to define the technology building blocks, and solve the system integration issues to enable a revolutionary tool. Once realized, QC will have world changing impact on economic competitiveness, the scientific enterprise, and citizen well-being. Prior to this workshop, DOE / Office of Advanced Scientific Computing Research (ASCR) hosted a workshop in 2015 to explore QC scientific applications. The goal of that workshop was to assess the viability of QC technologies to meet the computational requirements in support of DOE’s science and energy mission and to identify the potential impact of these technologies.
The purpose of the work presented in this memo was to calibrate the Sierra material model Multilinear Elastic-Plastic Hardening Model with Failure (MLEP-Fail) for 1/8 inch thick cast plate of 17-4 steel. The calibration approach is essentially the same as that recently used in a previous memo using data from smooth and notched tensile specimens. The notched specimens were manufactured with three notch radii R = 1=8, 1/32 and 1/64 inches. The dimensions of the smooth and notched specimens are given in the prints in Appendix A. Two cast plates, Plate 3 and Plate 4, with nominally identical properties were considered.
This is an addendum to the Sierra/SolidMechanics 4.48 User's Guide that documents additional capabilities available only in alternate versions of the Sierra/SolidMechanics (Sierra/SM) code. These alternate versions are enhanced to provide capabilities that are regulated under the U.S. Department of State's International Traffic in Arms Regulations (ITAR) export-control rules. The ITAR regulated codes are only distributed to entities that comply with the ITAR export-control requirements. The ITAR enhancements to Sierra/SM in- clude material models with an energy-dependent pressure response (appropriate for very large deformations and strain rates) and capabilities for blast modeling. Since this is an addendum to the standard Sierra/SM user's guide, please refer to that document first for general descriptions of code capability and use.
We investigate the use of implicit time integrators for finite element time domain approximations of Maxwell's equations in vacuum. We discretize Maxwell's equations in time using Crank-Nicolson and in 3D space using compatible finite elements. We solve the system by taking a single step of Newton's method and inverting the Eddy-Current Schur complement allowing for the use of standard preconditioning techniques. This approach also generalizes to more complex material models that can include the Unsplit PML. We present verification results and demonstrate performance at CFL numbers up to 1000.
Model materials consisting of metal nanoparticles loaded onto oxide supports were synthesized, characterized, and investigated in a number of catalytic chemical reactions. By varying the size, shape, and composition of nanoparticle, as well as the material used to support the nanoparticles, it was found that small changes to the catalyst can have enormous changes to the reaction activity and selectivity. Investigation of these carefully synthesized catalysts via in situ characterization, and reaction studies, leads to a deeper understanding of the molecular level parameters that govern catalysis. Through study of the properties of the nanoparticles it was discovered that nanoparticle size and shape have a dominant role in the chemoselective catalysis of furfural over platinum nanoparticles. When vapor phase furfural and hydrogen gas were passed over Pt nanoparticles ranging in size from 1.5 to 7.1 nm, the catalytic selectivity was found to be dominated by the size of the nanoparticle. Large nanoparticles promoted hydrogenation of furfural to furfuryl alcohol, while smaller nanoparticles favored decarbonylation to furan. The same size specific selectivity was found in the hydrogenative reforming (the transformation of hydrocarbons to branched isomers) of C6 hydrocarbons, in which Pt nanoparticle size controls isomerization selectivity. Methylcyclopentane was found to be extremely size dependent at lower temperatures (553 K). It was found that smaller sized nanoparticles favored isomer formation, while larger sizes catalyzed the aromatization reaction more efficiently. n-hexane was found to be much less dependent on particle size, but still showed an increase in isomerization with small particles over larger sized Pt nanoparticles. The composition of PtxRh1-x bimetallic nanoparticles was also studied. These catalysts were characterized under hexane reforming conditions with Ambient Pressure X-ray Photoelectron Spectroscopy (AP-XPS), in order to find the actual surface atomic composition under real catalytic working conditions. By using AP-XPS and catalytic data in tandem, it was found that an optimum Rh loading occurred when the surface ensemble statistically favored one Rh atom surrounded by Pt atoms. By utilizing different oxide materials for catalytic supports the flow of charge can play a role in the reaction at the surface or interface in a phenomenon known as the strong metal-support interaction (SMSI). When Pt nanoparticles were loaded onto mesoporous supports made of Co3O4, NiO, MnO2, Fe2O3, and CeO2 it was found that their activity for carbon monoxide oxidation was greatly enhanced relative to the support alone or Pt loaded onto inert mesoporous silica. This finding demonstrates that the interface of the metallic Pt nanoparticle and the oxide 2 support is able to produce turnovers that are orders of magnitude higher than the two materials separately. When the same type of experiments were investigated with n-hexane as the reactant and macroporous Al2O3, TiO2, Nb2O5, Ta2O5, and ZrO2 were utilized as supports, it was found that the reaction selectivity was greatly altered depending on the catalytic support material. TiO2, Nb2O5, and Ta2O5 (all of which are strong Lewis acids) were found to be much more selective for isomer production than the standard SiO2 mesoporous silica supported Pt nanoparticle catalyst. Finally, an acidified mesoporous silica material was utilized as the support. This material was synthesized by using AlCl3 to modify the surface of mesoporous silica. This support was found to have no activity for hexane isomerization alone. However, when Pt nanoparticles were supported on the material, the activity and isomer selectivity in hexane reforming was increased several orders of magnitude as compared to the same nanoparticles supported on unmodified mesoporous silica. This dissertation builds on the existing knowledge of known concepts in catalysis science such as structure sensitive reactions, the metal-support interaction, and acid-base chemistry. The results show how small changes in the active sites of a catalyst can create large changes in the catalytic chemistry. This research demonstrates how careful material control, characterization and reaction study can help to elucidate the molecular level components necessary to design efficient catalysts.
In October the team merged in updated ATDM/Trilinos configuration to include SPARC requirements. Assisted and worked on issues identified by the EMPIRE switchover to the ATDM/Trilinos configuration. Progress was made on automating dashboard triaging. Discovered and began addressing issues with mixed language calling with gcc-7.2 on Power8. Worked on new Python tool to filter CDASH reports to only show new issues. Completed ECP ST review. In October the team put an algorithm in place to prevent inverted elements in SPARC during refinement and worked on tests to morph mesher and should be ready for SGM integration soon. The team worked on solver rebalance and corrected issues. Complete SIMD work. Worked out next steps for solver improvements for EMPIRE. Adjusted some solver settings and to improve performance; strong scaling curves are flat instead of ascending etc. Worked on optimizing kernels for SPARC. Completed ECP ST reviews. The team worked on cleaning up branch for merge into SPARC master dev branch. Progress was made building scripts for catalyst builds on all HPC platforms of interest. Worked on adding TuckerMPl reader as plugin for catalyst. Completed ECP project review. Work has continued on NimbleSM, which now runs in a container and can be used modularly with an MPI code. The team also made progress on a qthreads version of NibleSM. Worked on build system issues within NimbleSM and Sierra for GPUs. Progressed on getting kookfied material models in NimbleSM. The team incorporated panel feedback form ECP project reviews into FY19 plans.
This report describes the outcome of the pilot SciDAC project jointly funded by the DOE Office of Nuclear Energy and the DOE Office of Science, Advanced Scientific Computing Research to advance understanding of fission gas behavior in nuclear fuel. The computational approach involved utilizing both a bottom up and top down multiscale materials modeling to evaluate the processes of xenon fission gas diffusion, xenon clustering and precipitation and the mechanisms of fission gas resolution by energetic fission fragments in uranium dioxide nuclear fuel. The computer science and applied mathematics research activities were focused on optimizing the uranium – oxygen – xenon interatomic potential implementation in the LAMMPS molecular dynamics code for large-scale simulations of fission gas resolution, in addition to improvements in visualization of accelerated molecular dynamics simulations and performance optimization of the Xolotl continuum cluster dynamics with a new grouping scheme to reduce the computational cost of modeling very large fission gas bubbles containing more than 10,000 xenon atoms. The most impactful result from this project stems from a systematic series of atomistic molecular dynamics to evaluate fission gas resolution from xenon bubbles that, combined with the fission product yields and consideration of electron-phonon coupling, informed a first principles model that predicts the magnitude of fission gas resolution in good agreement with empirical estimates.
Dynamic mode decomposition (DMD) is a method that has gained notoriety in the field of turbulent fluid flows as a method for decomposing the flow field into modes that could be further deconstructed to understand their influence on the overall dynamics of the system. Forays into solids and non-linear systems were considered, but not applied. In this work, DMD was applied for the first time to the heat-diffusion and reactive heat diffusion equations on a random particle pack of uniform solid spheres. A verification of a linear heat-diffusion test problem was successful, showing equality between the normal modes and Koopman modes obtained from DMD. Further application to a non-linear reactive system revealed stability limits of the underlying modes which are dependent on microstructure and chemical kinetics. This work will enable the development of reactive material models based on further analysis using DMD to quantify the statistical dependencies of transient response on microstructural characteristics.
This is an addendum to the Sierra/SolidMechanics 4.54 User's Guide that documents additional capabilities available only in alternate versions of the Sierra/SolidMechanics (Sierra/SM) code. These alternate versions are enhanced to provide capabilities that are regulated under the U.S. Department of State's International Traffic in Arms Regulations (ITAR) export control rules. The ITAR regulated codes are only distributed to entities that comply with the ITAR export control requirements. The ITAR enhancements to Sierra/SM include material models with an energy-dependent pressure response (appropriate for very large deformations and strain rates) and capabilities for blast modeling. This document is an addendum only; the standard Sierra/SolidMechanics 4.54 User's Guide should be referenced for most general descriptions of code capability and use.
Sierra/SolidMechanics (Sierra/SM) is a Lagrangian, three-dimensional finite element analysis code for solids and structures subjected to extensive contact and large deformations, encompassing explicit and implicit dynamic as well as quasistatic loading regimes. This document supplements the primary Sierra/SM 4.54 User's Guide, describing capabilities specific to Goodyear analysis use cases, including additional implicit solver options, material models, finite element formulations, and contact settings.