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The agenda for the presentation is: introduction and overview; method description; Hydrodynamics problems; LED multi-physics problems; HED multi-physics problems; Kokkos port for ATS-1 and ATS-2; Summary and future work; and, Wrap-up.
Abstract not provided.
We present a novel machine learning CNN architecture that can learn from limited data combined appropriately with physics and statistical priors (e.g., forward models and noise models). To address the limited availability of training data we adopt a 3D patch-based approach for our models. Patch-based learning is central to several image reconstruction methods and demands fewer training data than DL approaches, as a single data volume can be broken into several millions of overlapping 3D sub-volumes or patches. This creates a very large number of training sub-volumes from a limited number of overall image volumes. A 3D Generative Adversarial Networks (GAN) is then trained to remove artifacts at the sub-volume level. The combination of a sub-volume-based approach with DL allows us to exploit the richness of the latter in extracting and representing image features, while avoiding risks associated with overfitting due to limited training data.
One challenge of using compartmental SEIR models for public health planning is the difficulty in manually tuning parameters to capture behavior reflected in the real-world data. This team conducted initial, exploratory analysis of a novel technique to use physics-informed machine learning tools to rapidly develop data-driven models for physical systems. This machine learning approach may be used to perform data assimilation of compartment models which account for unknown interactions between geospatial domains (i.e. diffusion processes coupling across neighborhoods/counties/states/etc.). Results presented here are early, proof-of-concept ideas that demonstrate initial success in using a physically informed neural network (PINN) model to assimilate data in a compartmental epidemiology model. The results demonstrate initial success and warrant further research and development.
The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.
The project developed new theoretical tools for analysis of nanodevices subjected to external optical and bias driving. Traditional theoretical techniques for molecular optoelectronics are either based on kinetic schemes or utilize quasiparticle description. The former fails to account for quantum mechanics of the system-bath interface and may fail qualitatively when used in open interacting systems. The latter is inconvenient in (usual for molecular optical spectroscopy) many body states description of the system. We developed a new technique - the Hubbard nonequilibrium Green's functions method - which allows to avoid shortcomings of standard theoretical approaches. The Hubbard NEGF was applied to analysis of experimental measurements of photoinduced current and bias-induced electroluminescence in STM molecular junctions. We also demonstrated practical usefulness of the Hubbard NEGF within newly proposed universal theory of current-induced forces for nonadiabatic molecular dynamics which generalizes celebrated Head-Gordon and Tully expression for electronic friction. Finally, following latest trends in laser techniques we studied local responses (local fluxes and local noise spectroscopy) of biased junctions as a source of information not accessible by total responses (total fluxes and noises) of the system.
Abstract not provided.
The CTH multiphysics hydrocode, which is used for a wide range of important calculations, has undertaken in recent years to overhaul its software quality and testing processes. A key part of this effort entailed building a new, robust V&V test suite made up of traditional hydrocode verification problems, such as those listed in the ASC Tri-Lab Test Suite and the Enhanced Tri-Lab Test Suite, as well as validation problems for some of CTHs most frequently used equations of state, materials models, and other key capabilities. Substantial progress towards this goal was made in FY19. In FY20, this test suite has been expanded to include verification and validation tests of the Sesame and JWL equation of state models as well as the Mader verification problem from the Tri-Lab Test Suite and the Blake verification problem - a linear elastic analog to the Hunter problem from the Enhanced Tri-Lab Test Suite. This report documents CTH performance on the new test suite problems. Verification test results are compared to analytic solutions and, for most tests, convergence results are presented. Validation test results are compared to experimental data and mesh refinement studies are included. CTH performs well overall on the new test problems. Convergence rates for the Blake and Mader problems are comparable to those for similar ASC codes. The JWL and Sesame verification tests show good agreement with analytic solutions. Likewise, CTH simulation results show good agreement with experimental validation data for the Sesame and JWL equations of state for the materials tested. Future V&V work will focus on adding tests for other key capabilities like fracture and high explosive models.
Abstract not provided.
Pagosa is a 3 dimensional, multi-material shock wave physics code that uses a structured cartesian mesh.
A summary of a Shaped Charge Assessment (SCA) of the TOW 2A shaped charge is shown here, modeled with the LANL PAGOSA hydrocode. Early, mid, and late time images show the jet formation and velocity
This presentation provides information on stability analysis and selection principles, formalizing organization, and nonequilibrium statistical mechanics of organization.
In support of Makani’s energy kite development program, Makani engaged with NREL to develop, verify, and document a multiphysics engineering model of a megawatt-scale tethered energy kite (named KiteFAST). After the original development of KiteFAST was completed, Makani further engaged NREL to develop a software enhancement of KiteFAST to enable the dynamics modeling of an energy kite tethered to a floating offshore platform (named KiteFAST-OS). Before this project, the capability to model the aero-hydro-servo-elastic dynamics of an airborne wind energy (AWE) system with electricity generation on the flying device (fly gen) and crosswind flight operation did not exist. Such physics-based modeling capability is needed for loads analysis, structural design, and certification of energy kites. Throughout the project, an exclusive license kept KiteFAST and KiteFAST-OS available only to Makani, NREL, and its counterparts. With the ending of Makani, the KiteFAST and KiteFAST-OS software were merged into a single code base (named KiteFAST), the exclusive license was terminated, and the source code, documentation, and example models were released publicly.
Most current flight systems are dependent on GPS for navigation. Recently, however, navigation in GPS-denied environments has become an area of intensive research. Additional navigation sensor data can be obtained from visual observations (stars or terrain), inertial measurement units, radar, measurements of the local magnetic field, or perhaps even gravity. Absolute and relative positioning via magnetic field measurements have been shown to be viable in many applications including ground navigation, low altitude aircraft flight, and spaceflight. There is greater variability in the magnetic field over shorter distances when flying at low altitude and in ground applications, leading to more accurate positioning. However, ground-based magnetic navigation is often heavily influenced by man-made structures, especially in urban environments. This is not the case for airborne magnetic navigation since the influence of buildings, roads, etc. is negligible for typical aircraft altitudes. For absolute magnetic navigation, the positioning accuracy decreases as altitude increases for a given vehicle velocity, but the observed time variability in the field can be reclaimed by traveling faster through the field. Thus, navigation accuracy becomes a balance of speed and altitude since the higher altitude can be counterbalanced by higher velocity. To understand these effects quantitatively, we explored various techniques to aid a simulated inertial measurement unit with magnetic information. Using a technique known as two-dimensional magnetic map matching, we simulated the performance of airborne magnetic navigation at fixed speed while varying the altitude, flight direction, magnetometer data collection time, reference magnetic map bias error, and type of trajectory (over land or over ocean).
The following assessment evaluates the efficacy of the control script for carrying out a linear signal to generate a linear mechanical response of the system: the TRUST nonlinear dynamics (TRUSTND) testbed. The hardware has three main components: the controller (NI PXIe 8861) embedded in the National Instruments chassis (NI PXIe 1092), the signal amplifier (The Modal Shop Linear Power Amplifier 2050E09) to amplify the output of a custom LabVIEW script, and a shaker (The Modal Shop Electrodynamic Exciter 2075E) where wave spring specimens live and are tested within the attached aluminum testbed (center mass). Different kinds of signals (single-tone, swept frequency and white noise) were sent through this hardware in the E-1 lab space at TA-53. First, the linearity of the setup was tested by specifying a sine wave in the control script and checking the quality of the oscillations in a wave spring (McMaster-Carr 9714K19 [1]). When passing a sine wave through the amplifier was succeeded, the frequency response of the wave spring was tested with white noise for comparison to finite-element model predictions. The testbed outputs a repeatable, linear response to the input excitation when used with the wave spring. These measurements reduce the uncertainty associated with the testbed and test procedure to better characterize uncertainty associated with material behavior (SX358 foam samples) in future tests
Abstract not provided.
The nodes, edges, faces, and blocks that define the connectivity of a multi-block mesh. This is equivalent to a coarse unstructured mesh with global numbering. The topology is approximate.
This report summarizes molecular and continuum simulation studies focused on developing physics - based predictive models for the evolution of polymer molecular order during the nonlinear processing flows of additive manufacturing. Our molecular simulations of polymer elongation flows identified novel mechanisms of fluid dissipation for various polymer architectures that might be harnessed to enhance material processability. In order to predict the complex thermal and flow history of polymer realistic additive manufacturing processes, we have developed and deployed a high - performance mesh - free hydrodynamics module in Sandia's LAMMPS software. This module called RHEO – short for Reproducing Hydrodynamics and Elastic Objects – hybridizes an updated - Lagrange reproducing - kernel method for complex fluids with a bonded particle method (BPM) to capture solidification and solid objects in multiphase flows. In combination, our two methods allow rapid, multiscale characterization of the hydrodynamics and molecular evolution of polymers in realistic processing geometries.