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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Introduction to SINBAD - Tutorial - 25448

With the reduction of experimental activities in several countries accompanied by closing of many experimental facilities, the need to preserve the valuable information on the performed radiation shielding benchmarks became increasingly crucial. Since the early 1990's the Organization for Economic Cooperation and Development's Nuclear Energy Agency Data Bank (OECD/NEADB) and the Radiation Safety Information Computational Center (RSICC) are working together on the Shielding Integral Benchmark Archive and Database (SINBAD) project to preserve and make available the information on the past shielding benchmark experiments. The OECD NEA Working Party on Scientific Issues of Reactor Systems (WPRS) Expert Group on Radiation Transport and Shielding (EGRTS) was started in 2011 with the mandate among others, to monitor, steer and support the continued development of the SINBAD database. The database comprises now 102 shielding benchmarks, divided into three categories, covering both low and inter-mediate energy particles applications: fission reactor shielding (48 benchmarks), fusion blanket neutronics (31), and accelerator shielding (23) benchmarks. They are fundamental to ensure that modelling tools meet the requirements of nuclear industry and licensing needs. Validation of nuclear cross-section data, nuclear codes and models as well as nuclear design components are few examples of the use of the database. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

ANS MultiApps tutorial

The Multiphysics Object-Oriented Simulation Environment (MOOSE) [1] is an open-source, parallel finite element framework which provides the foundation formany advanced modeling and simulation tools developed under the Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program [2] for the analysis of advanced reactors. The MOOSE framework provides the common foundational capability on which many NEAMS codes for reactor analysis are built. The MOOSE framework also includes several systems to assemble unique workflows and coupling amongMOOSE-based applications. In particular, the MultiApp and Transfer systems are widely used to assemble different MOOSE-based or MOOSE- wrapped physics applications together to perform loosely or tightly coupled multiphysics simulations. The National Reactor Innovation Center’s (NRIC’s) Virtual Test Bed (VTB) [3] hosts publicly available nuclear reactor multiphysics simulation examples which leverage MOOSE’s MultiApp system to meet the modeling needs of different reactor types. The flexibility and robustness of coupling provided by MOOSE permits rapid development of coupled physics models for a wide range of reactor types and events.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

State preparation and evolution in quantum computing: a perspective from Hamiltonian moments

Quantum algorithms on the noisy intermediate-scale quantum (NISQ) devices are expected to simulate quan- tum systems that are classically intractable to demonstrate quantum advantages. However, the non-negligible gate error on the NISQ devices impedes the conventional quantum algorithms to be implemented. Practical strategies usually exploit hybrid quantum-classical quantum algorithms to demonstrate potentially useful ap- plications of quantum computing in the NISQ era. Among the numerous hybrid quantum-classical algorithms, recent efforts highlight the development of quantum algorithms based upon quantum computed Hamiltonian moments, ?f|Hˆn|f? (n = 1, 2, · · · ), with respect to quantum state |f?. In this tutorial, we will give a brief review of these quantum algorithms with focuses on the typical ways of computing Hamiltonian moments using quantum hardware and improving the accuracy of the estimated state energies based on the quantum computed moments. Furthermore, we will present a tutorial to show how we can measure and compute the Hamiltonian moments of a four-site Heisenberg model, and compute the energy and magnetization of the model utilizing the imaginary time evolution in the real IBM-Q NISQ hardware environment. Along this line, we will further discuss some practical issues associated with these algorithms. We will conclude this tutorial review by overviewing some possible developments and applications in this direction in the near future.

Aulicino, Joseph C.↗
DOE OSTI2020

Frequent Fulcrum Functions: The Basics of SCALE’s Graphical User Interface [Slides]

This tutorial introduces the Fulcrum graphical user interface and the basic functions that enhance the common activities of creating, editing, navigating, executing, and visualizing SCALE input files. This tutorial will help you become familiar with the Fulcrum input file text editor and the integrated input development environment features of autocompletion, automatic checking, cursor context, and input navigation. In addition, the Fulcrum and SCALE runtime environment will be reviewed to improve the understanding of job execution workflow. This tutorial does not cover data and geometry plotting. Please see the Advanced User Interface Capabilities tutorial for details regarding plotting data and geometry. No prior experience with SCALE is required. You can follow along using SCALE 6.2 or 6.3-beta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

High Performance Computing Innovation Center Open Source Developer Tools

The High Performance Computing Innovation Center (HPCIC) aims to ease the transition for developers to use open source software provided by the lab. HPCIC Developer Tools is a collection of software, containers, cloud configurations, and associated documentation that make it easy to deploy tutorials or small apps to demonstrate lab-developed software. For example, building a tutorial container that includes lab software and interactive interfaces; a command line or web-based tool that accepts user preferences for the tutorial; supporting tools and software development kits (SDKs) for developer interactions or productivity in different languages embraced by the larger developer community such as Go, Rust, and Python; and automation in version control to support continued update of software and associated resources. These tools are best developed in an open source environment such as GitHub, not only to champion the lab's open source software, but for purposes of branding and demonstrating the lab's leadership in open source. Such an effort that brings in more developers to use and contribute to lab software can further improve the quality of the software, and developer experience at the lab.

Beckingsale, DavidA↗
DOE OSTI2019

FY19Q3 LL17-GEOVIS-PD3SS

NFIX has been licensed to ORNL, LANL, SNL and LBNL for use on the MINOS venture. We continue to meet with the MINOS data team to receive feedback and suggestions for additional features. We are accommodating feature requests within our resources. • A new feature was added to NFIX that lists out sensor metadata files (json files) that NFIX is not able to ingest due to formatting errors. This feature has greatly eased the effort required by the MINOS team to identify errant json files. Our summer student used this new feature to determine the number of sensor data metafiles that NFIX was not ingesting (a small number) and found the root cause to be a particular set of formatting problems. The MINOS team is using this information to correct the mis-formatted files. Our summer student also developed a tutorial for the NFIX users. She was in a unique position to develop a tutorial as she had to come up to speed on the tool in order to use it for our data ingest study. The tutorial is planned to appear as an appendix in the project final report. A white paper on using GeoVisipedia technology for detecting changes at portals using satellite imagery was submitted to NA21. The technique uses GeoVisipedia’s model projection technology as a view-invariant segment technique thereby greatly enhancing the robustness of detecting changes. We demonstrated NFIX to our program manager and his technical advisor in April. Per headquarters direction we were not required to present at a DNN R&D Joint Program Review this year.

97 MATHEMATICS AND COMPUTING↗