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At least 595 records · Page 33

Doppler Backscattering Data Analysis and Integrated Modeling with OMFIT

One Modeling Framework for Integrated Tasks (OMFIT) is a widely used software tool in the magnetic fusion research community. OMFIT provides magnetic fusion energy researchers with a framework for the development of special-purpose physics modules. This paper describes an OMFIT physics module pertaining to the Doppler Backscattering (DBS) fusion plasma diagnostic. DBS measures density fluctuations and flow velocity through plasma scattering of electromagnetic waves. The OMFIT DBS module was developed to analyze experimental DBS data and facilitate modeling of DBS systems installed on multiple tokamak devices. The OMFIT DBS module is designed to support several analysis workflows: detailed analysis of experimental data, experimental planning, and theory-based synthetic diagnostic modeling. The DBS module uses integrated modeling by leveraging other OMFIT physics modules to perform tasks related to DBS, e.g. ray/beam–tracing simulations, edge-localized mode–synchronized data analysis, magnetic equilibrium reconstruction, and fitting kinetic profile data. Furthermore, this paper describes several supported workflows and serves a reference for the OMFIT DBS module.

Doppler backscattering↗

Emulation Framework for Distributed Large-Scale Systems Integration

Recent trends in systems engineering include integration of very large-scale systems, which entails significant challenges when they are geographically dispersed. In these scenarios, intelligent integration of distributed large-scale systems requires significant coordination among hardware elements as well as all software components. The approach of integrated systems (both computing platform and experimental equipment) for end-to-end orchestration is called federation. Virtual frameworks can aid in the testing, assessment, and implementation of a functional system of interconnected resources. We present an emulation framework that replicates the software environments of multi-site federations of computing systems and instruments. Our emulation framework allows systems engineers to reduce developmentcost and avoid disruptions to production infrastructure. Our framework was effectively used to develop and test software modules for various tasks including container orchestration and instrument access. For performance assessment, however, the emulated framework is severely limited in providing accurate network and IO measurements at 10 Gbps and higher data rates. The data transfer performance profiles estimated using these emulated measurements are usually inaccurate for high bandwidth and high latency connections, since emulation does not accurately reflect the critical network transport dynamics.We utilize measurements from a physical testbed with hardware network emulators to obtain data transfer profiles that closely match the expected profiles for the emulated federations. We show the effectiveness of our approach by an illustrative example of integrated (federated) multi-site ultra large-scale systems that are connected via high speed wide area networks.

Imam, Neena↗

Configuring the Orion Guidance, Navigation, and Control Flight Software for Automated Sequencing

The Orion Crew Exploration Vehicle is being designed with greater automation capabilities than any other crewed spacecraft in NASA s history. The Guidance, Navigation, and Control (GN&C) flight software architecture is designed to provide a flexible and evolvable framework that accommodates increasing levels of automation over time. Within the GN&C flight software, a data-driven approach is used to configure software. This approach allows data reconfiguration and updates to automated sequences without requiring recompilation of the software. Because of the great dependency of the automation and the flight software on the configuration data, the data management is a vital component of the processes for software certification, mission design, and flight operations. To enable the automated sequencing and data configuration of the GN&C subsystem on Orion, a desktop database configuration tool has been developed. The database tool allows the specification of the GN&C activity sequences, the automated transitions in the software, and the corresponding parameter reconfigurations. These aspects of the GN&C automation on Orion are all coordinated via data management, and the database tool provides the ability to test the automation capabilities during the development of the GN&C software. In addition to providing the infrastructure to manage the GN&C automation, the database tool has been designed with capabilities to import and export artifacts for simulation analysis and documentation purposes. Furthermore, the database configuration tool, currently used to manage simulation data, is envisioned to evolve into a mission planning tool for generating and testing GN&C software sequences and configurations. A key enabler of the GN&C automation design, the database tool allows both the creation and maintenance of the data artifacts, as well as serving the critical role of helping to manage, visualize, and understand the data-driven parameters both during software development and throughout the life of the Orion project.

Odegard, Ryan G.↗

Materials genome innovation for computational software (magics) center

Functional layered material (LM) architectures will dominate nanomaterials science in this century. We have developed theory, modeling, simulation, and software and data tools that enhance understanding and AI guide synthesis, enable characterization of complex structures, and improve capabilities in the predictive design and growth of LMs. Research at the Center has focused on: Computational synthesis and characterization: AI guided synthesis and experimental synthesis of stacked LMs with tailored properties via optimized chemical vapor deposition (CVD) growth and liquid-phase exfoliation; study defects, edges, grain boundaries, wrinkling of atomic layers and their effects on chemical, mechanical, electrical, and optical properties. Far-from-equilibrium processes: Joint experimental and simulation based probe of electronic processes with NAQMD and ultrafast X-ray free-electron laser (XFEL) and ultrafast electron diffraction (UED) facilities at Stanford. Experimentally validate NAQMD by ultrafast electron diffraction and X-ray spectroscopy studies of structural and excited state dynamics, shape fluctuations, and phonon dynamics. Scalable software: Simulation engines for desktop-to-exascale platforms using low-overhead, linear-scaling QMD algorithms; divide-conquer-recombine NAQMD with electronic excitations; extended-Lagrangian reactive molecular dynamics (RMD), machine learning (ML) based neural-network quantum molecular dynamics (NNQMD), and super-state accelerated molecular dynamics (AMD) and kinetic Monte Carlo codes; thermal and electrical transport software; and design 3D architectures of LMs with desired functionality using scalable software. Distribution of software and data, and training: Software and simulation-experimental data generated within the Center are distributed to the materials science community via Berkeley Materials Project (MP) framework. We have also organized three workshops for software distribution and training at USC (Nov. 2017, Mar. 2018) and Gaithersburg, MD (Nov. 2018) to train researchers, with the last one in focused on underrepresented groups, in collaboration with Howard University which is one of the largest HBCUs. The Center supported a total of 46 personnel and 6 undergraduate students. These include 14 faculty, 11 postdoctoral research associates, 20 graduate research assistants, and mentored 6 undergraduate students. This resulted in the publications of 63 research papers that include 46 publications on Reactive and Quantum Dynamics Simulations, 13 publications on Machine Learning for Quantum Materials, and 4 publications on Quantum Computing.

2D Materials↗

Sterile neutrinos and the global reactor antineutrino dataset

We present results from global fits to the available reactor antineutrino dataset, as of Fall 2019, to determine the global preference for a fourth, sterile neutrino. We have separately considered experiments that measure the integrated inverse-beta decay (IBD) rate from those that measure the energy spectrum of IBD events at one or more locations. The evidence that we infer from rate measurements varies between ≲ 3σ and negligible depending on the reactor antineutrino flux model employed. Moreover, we find that spectral ratios ostensibly imply ≳ 3σ evidence, consistent with previous work, though these measurements are known to be plagued by issues related to statistical interpretation; these results should therefore be viewed cautiously. The software used is the newly developed GLoBESfit tool set which is based on the publicly available GLoBES framework and will be released as open-source software.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A new simulation model building process for use in dynamic systems integration research

A framework to build simulation models for aircraft dynamic systems integration is described. The objective of the framework is increased simulation model fidelity and reduced time required to develop and modify these models. The equations of motion for an elastic aircraft and their impact on the framework are discussed in broad terms. A software tool which automatically generates FORTRAN routines for tabular data lookups, the language used to develop a simulation model, and the structures for passing information into a simulation are discussed. A simulation variable nomenclature is presented. The framework has been applied to build an open-loop F/A-18 simulation model. This example model is used to illustrate model reduction issues. Current deficiencies in the framework are identified as areas for future research.

Arbuckle, P. Douglas↗

Engineering Software for Flight

This talk describes our efforts to improve the software engineering processes of the Copilot runtime verification framework so that the code generated can be used in UAS flights.

software engineering↗

EEL: A MOOSE-based Application for 3D Electro-Chemo-Thermo-Mechanical Modeling of Solid-State Batteries

This report describes a tool for three dimensional, high fidelity, coupled electro-chemo-thermo-mechanical modeling of solid-state batteries. A complete version of the tool is available as open source software at https://github.com/hugary1995/eel.git. The theoretical framework of the tool revolves around an inf-sup statement on a total potential, comprising the Helmholtz free energy, the electrical kinetic potential, the chemical potential, the Fourier potential, the chemical reaction potential, and the external power expenditure. The tool uses the finite element framework of Multiphysics Object-Oriented Simulation Environment (MOOSE) and a variational formulation to solve the boundary value problem for solid-state battery incorporating the full set of multiphysics couplings. The variational formulation also enables a modular software architecture for the tool so additional physics can be easily included by specifying the new contribution to the total potential. The report discusses several method of manufactured solutions that were used to verify the implementation of different physics and the Butler-Volmer reaction kinetics at the electrolyte-electrode interface. Finally, the report discusses results from complete charge/discharge simulations of a quasi-1D and a 3D solid-state battery.

25 ENERGY STORAGE↗

Software reliability: Additional investigations into modeling with replicated experiments

The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.

Nagel, P. M.↗

Uncertainty analysis of correlated parameters in automated reaction mechanism generation

Abstract Uncertainty analysis is a useful tool for inspecting and improving detailed kinetic mechanisms because it can identify the greatest sources of model output error. Owing to the very nonlinear relationship between kinetic and thermodynamic parameters and computed concentrations, model predictions can be extremely sensitive to uncertainties in some parameters while uncertainties in other parameters can be irrelevant. Error propagation becomes even more convoluted in automatically generated kinetic models, where input uncertainties are correlated through kinetic rate rules and thermodynamic group values. Local and global uncertainty analyses were implemented and used to analyze error propagation in Reaction Mechanism Generator (RMG), an open‐source software for generating kinetic models. A framework for automatically assigning parameter uncertainties to estimated thermodynamics and kinetics was created, enabling tracking of correlated uncertainties. Local first‐order uncertainty propagation was implemented using sensitivities computed natively within RMG. Global uncertainty analysis was implemented using adaptive Smolyak pseudospectral approximations as implemented in the MIT Uncertainty Quantification Library to efficiently compute and construct polynomial chaos expansions to approximate the dependence of outputs on a subset of uncertain inputs. Cantera was used as a backend for simulating the reactor system in the global analysis. Analyses were performed for a phenyldodecane pyrolysis model. Local and global methods demonstrated similar trends; however, many uncertainties were significantly overestimated by the local analysis. Both local and global analyses show that correlated uncertainties based on kinetic rate rules and thermochemical groups drastically reduce a model's degrees of freedom and have a large impact on the determination of the most influential input parameters. These results highlight the necessity of incorporating uncertainty analysis in the mechanism generation workflow.

Gao, Connie W.↗

An ERCOT test system for market design studies

An open source test system is developed that permits the dynamic modeling of centrally-managed wholesale power markets operating over highvoltage transmission grids. In default mode, the test system models basic operations in the Electric Reliability Council of Texas (ERCOT): namely, centrally-managed day-ahead and real-time markets operating over successive days, with congestion handled by locational marginal pricing. These basic operational features characterize all seven U.S. energy regions organized as centrally-managed wholesale power markets. Modeled participants include dispatchable generators, load-serving entities, and non-dispatchable generation such as unrmed wind and solar power. Users can congure a broad variety of parameters to study basic market and grid features under alternative system conditions. Users can also easily extend the test system's Java/Python software classes to study modied or newly envisioned market and grid features. Finally, the test system is integrated with a high-level simulation framework that permits it to function as a software component within larger systems, such as multi-country systems or integrated transmission and distribution systems. Finally, detailed test cases with 8-bus and 200-bus transmission grids are reported to illustrate these test system capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

Abstract The PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

Chemistry↗

The ATLAS Workflow Management System Evolution in the LHC Run3 and towards the High-Luminosity LHC era

The ATLAS experiment has 18+ years of experience using workload management systems to deploy and develop workflows to process and to simulate data on the distributed computing infrastructure. Simulation, processing and analysis of LHC experiment data require the coordinated work of heterogeneous computing resources. In particular, the ATLAS experiment utilizes the resources of 250 computing centers worldwide, the power of supercomputing centres, and national, academic and commercial cloud computing resources. In this contribution, we present new techniques for cost-effectively improving efficiency introduced in workflow management system software. The evolution from a mesh framework to new types of computing facilities such as cloud and HPCs is described, as well as new types of production and analysis workflows.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Topological background discrimination in the PandaX-III neutrinoless double beta decay experiment

The PandaX-III experiment plans to search for neutrinoless double beta decay (0ν ββ ) of 136 Xe in the China JinPing underground Laboratory (CJPL). The experiment will use a high pressure gaseous time projection chamber (TPC) to register both the energy and the electron track topology of an event. This article is devoted to demonstrate our particular detector setup capabilities for the identification of 0ν ββ and the consequent background reduction. As software tool we use REST, a framework developed for the reconstruction and simulation of TPC-based detector systems. We study the potential for background reduction by introducing appropriate parameters based on the properties of 0ν ββ events. We exploit for the first time not only the energy density of the electron track-ends, but also the electron scattering angles produced by an electron near the end of its trajectory. To implement this, we have added new algorithms for detector signal and track processing inside REST. Their assessment shows that background can be reduced by about 7 orders of magnitude while keeping 0ν ββ efficiency above 20% for the PandaX-III baseline readout scheme, a two-dimensional 3 mm pitch stripped readout. More generally, we use the potential of REST to handle 2D/3D data to assess the impact on signal-to-background significance at different detector granularities, and to validate the PandaX-III baseline choice. Finally, we demonstrate the additional potential to discriminate surface background events generated at the readout plane in the absence of to, by making use of event parameters related with the diffusion of electrons.

Majorana↗

Facile Integration of Robots into Experimental Orchestration at Scientific User Facilities

Integration of robots into scientific user facilities, such as the National Synchrotron Light Source II, improves their efficiency and capacity. Many such facilities use the opensource Bluesky project for experimental control and orchestration. However, there remains an open challenge in deploying robotic solutions at these facilities that are reconfigurable, extensible, and compatible with pre-existing software infrastructure. Herein, we introduce a framework that uses the Robotic Operating System 2 (ROS2) and Bluesky to provide extensible robotic applications, while working under the operational constraints of a large-scale user facility. We demonstrated this framework by integrating a robotic arm to pick and place a sample holder at a beamline, recording a 90% repeatability rate. This provides the groundwork for further new robotics applications at large-scale scientific user facilities that depend on Bluesky.

36 MATERIALS SCIENCE↗

A Benchmark Suite for Evaluating Scientific AI Workloads on GPUs

AI applications have been steadily increasing in the allocation portfolio among leadership computing facilities. These applications depend on deep learning frameworks with hardware acceleration and underlying software systems. With the rapid development of applications, software stacks, and hardware devices, it is essential to evaluate the performance of core operations in AI workloads for direction of optimizations and procurement of next-generation high-performance computing (HPC) infrastructures. Currently, most benchmarks lack scientific AI workloads. So, we present DeepKernelBench and the experimental results of evaluating the benchmark suite for early observations and performance comparisons on datacenter GPUs using representative workloads for scientific AI, including Attentions, General matrix multiplications, Geometrics and Fourier neural operations.

Jin, Zheming [Advanced Micro Devices (AMD)]↗

Benchmark Modeling and Simulation of the FFTF LOFWOS Test #13 Using SAM

The Fast Flux Test Facility (FFTF) was a 400 MW thermal powered, oxide-fueled, liquid sodium cooled test reactor, built to assist development and testing of advanced fuels and materials for fast breeder reactors. In July 1986, a series of unprotected Loss of Flow Without Scram (LOFWOS) transients were performed in FFTF as part of the Passive Safety Testing (PST) program. The LOFWOS Test #13, which was initiated at 50% power and 100% flow with the pump pony motors left off, has been chosen as a benchmark case by IAEA to support collaborative efforts within international partnerships on the validation of simulation tools and models in the area of sodium fast reactor passive safety in an IAEA Coordinated Research Project (CRP), launched in October 2018. The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR safety analysis. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. To participate the IAEA CRP and enhance the SAM validation base for advanced reactor transient safety analysis, benchmark simulations of the FFTF LOFWOS Test #13 are performed using the SAM code. In this first phase of the validation effort, the thermal-hydraulic behavior of the reactor system is the focus and the reactor kinetics is not considered in the SAM FFTF model. Instead, the results of Argonne’s neutronics calculations are directly used, including the power shape of the active core region and the power history during the transient. The simulation results of FFTF at steady state agreed well with the measured data from the test. During the transient, reasonably good agreement were also obtained. Future work to improve the model will focus on introducing the reactivity predictions into the model, as well as better understanding or resolving the current discrepancies with the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

FY20 SAM Code Developments and Validations for Transient Safety Analysis of Advanced non-LWRs

The System Analysis Module (SAM) is under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. This report summarizes major progress in SAM code development, capability enhancements, demonstration, and validation to support transient safety analysis of advanced non-LWRs. Rapid developments continued in fiscal year 2020 (FY20) to support various needs of the advanced reactor community, especially the NRC and industry on the licensing safety analysis of advanced reactor designs. Significant code changes were made to provide various capability enhancements, bug fixes, and user friendliness improvements. Major code updates are summarized in Section 1, while four important enhancements are detailed in Sections 2-5, including a multi-dimension flow model; reactivity feedback and decay heat models; control and trip system modeling, and additional fluid and solid thermophysical property models. Code validation activities in FY20 include using test data from the Fast Flux Test Facility (FFTF), the High Temperature Test Facility (HTTF), and several separate effects test facilities for pebble-bed modeling.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗