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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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This presentation discusses Diversity, Equity, and Inclusion (DEI) at the Center for Integrated Nanotechnologies (CINT). After defining diversity, equity, and inclusion, demographics are presented. DEI initiatives at other NSRCs are shared. The CINT DEI Committee Proposal is outlined, and opportunity for discussion is provided.
We certainly live in unusual and quite challenging times, and we hope everyone is healthy and doing well. For the first time in almost 30 years, because of the current COVID-19 crisis, the GEM Steering Committee decided to cancel the in-person GEM Summer Workshop and organize a virtual meeting in its place. The Virtual GEM will occur during the same week as the originally scheduled in-person workshop, July 20-23, with Monday July 20 as the student day. We will try to maintain the original format of GEM as much as possible, with plenary sessions in the morning, Focus Group breakout sessions in the afternoon, and poster sessions in the evening. Please provide your full support to the meeting organizers to help make this first VGEM a great success! As of now, we still plan to hold the GEM 2021 summer workshop in Hawaii from July 26-30, 2021, with a GEM student day on July 25. This workshop will be back-to-back with SHINE (to occur at the same hotel the week after GEM) - please consider attending both!
“ENDF/B-VIII.0 provides a major update to the ENDF thermal scattering library. Indeed, it is nearly a completely new sub-library. Only the legacy evaluations for Al, Fe, liquid and solid methane, ortho- and para- hydrogen and deuterium and benzene and the ENDF/B-VII.1 evaluations for SiO2 are unchanged.” Thirty-four (34) materials are provided in ENDF/B-VIII.0 with a total of two hundred and fifty-three (253) evaluations. LEAPR input files are also included for each of the materials as well as “readme” files for most of the materials. All of these 34 thermal scattering files have been re-processed with NJOY2016 (version 53) to produce 253 ACE files suitable for use in MCNP or other similar codes. Table 1 lists the 34 materials which are included in the ENDF/B-VIII.0 thermal scattering library and also notes where major changes have occurred in the re-release.
This presentation provides an overview of the lab, the organization, operations and mission, and the six key areas of science technology and engineering. Next, the presentation provides a picture of employment at LANL and gives advice for exploring opportunities for both collaboration and employment.
The employees at Los Alamos National Laboratory have always been the key to our mission success, dating all the way back to our inception in 1939 as Project Y. This was the secret Los Alamos Lab of the Manhattan Project charged with designing and producing the world’s first atomic weapons to help end World War II. Back then, prospective Lab employees received letters that directed them to an office at 109 E. Palace in Santa Fe, New Mexico. There, they were greeted by Dorothy McKibbin, secretary to Lab Director J. Robert Oppenheimer. Before anyone headed up the hill to begin work, Dorothy typed up the new employee’s personal information on what quickly became known as the McKibbin Card. Lab employees also had official badges, the black and white photos of which have become iconic over time. Today’s staff at the National Security Research Center, the Lab’s classified library, are just as vital as the Lab’s first workforce was. Our highly trained experts partner with researchers to solve global challenges.
The NMF k algorithm results in strong classification scores and informative basis functions to describe the spectra associated with pore formation.
What is the NSRC? It is: Los Alamos National Laboratory's classified library; World’s most-comprehensive collection of nuclear security materials; Supports our national security mission; and, is guided by Highly-trained, expert staff.
NSDS is the adept coordination of Los Alamos National Laboratory's nuclear science data, including the collection, integration, storage and access. The poster highlights historical milestones.
This report summarizes data completeness by tower and by instrument for 2019 and compares that data with the Los Alamos National Laboratory (LANL) and the ANSI/ANS-3.11-2015 standard. This report is designed to make data users aware of data completeness and any data quality issues. LANL meteorology monitoring goals include 95% completeness for all measurements. The ANS 2015 standard requires 90% completeness for all measurements. This report documents instrument/tower issues as they impact data completeness.
The SPOKE graph [2, 6] is a sparse decorated semantic graph representing a collection of knowledge collected in many scientific databases from the fields of healthcare, biochemistry, chemistry, biology, et cetera. This knowledge graph is stored as a relational dataset decorated with metadata on each constituent vertex and edge. Formally, the graph is G(V, E, D), where V is a set of n vertices V := {1, ..., n} and edges of the form (i, j) ϵ E for i, j ϵ V, and table D that for any item in V υ E stores unstructured data such as vertex/edge type, nature of a relationship, et cetera. D(i) = {data involving vertex i ϵ V}, and D(i, j) = {data involving edge (i, j) ϵ E}. Here, we treat the graph as undirected in the sense that a direct relationship for (i, j) causes a (possibly opposite) reverse direct relationship for (j, i). The SPOKE graph G(V, E, D) is formed by processing a collection of relational datasets from medicine, chemistry, and biology, connecting many entities. Here, we analyze an instance from 2019, Spoke-20190707, where a graph file contains 6.16M edges and associated metadata and a vertex file contains 2.15M vertices and the associated metadata. There are 12 different types of vertex entities; all edge types used are implicit (see §2). There is other metadata in D on edges and vertices, but we just use the topology and the vertex labels in this report. SPOKE is growing as more knowledge is gained and more datasets are added. SPOKE is likely to grow 10x during the next phase of this project, and we therefore would like to consider topoligical analysis techniques that are scalable to several orders of magnitude larger than the current dataset (say >1B edges).
A handout describing the Electronic Public Reading Room at Los Alamos National Laboratory is provided.
The Arctic Futures 2050 Conference was designed as a novel convening of Arctic scientists, Indigenous people, and decision makers, including policy makers at all levels of government. The conference was held 4–6 September 2019 in Washington, D.C. and gathered nearly 400 participants to explore six questions: What do we know, and what do we need to know about the Arctic—and why does it matter? What challenges confront policy makers in the rapidly changing Arctic? What basic research is needed to inform responses to Arctic change? What applied research is needed to inform responses to change? What tools can facilitate informing policy making with science and Indigenous knowledge? What opportunities exist for partnerships between policy makers and scientists? A conference report (see: https://www.searcharcticscience.org/arctic-2050/conference-2019/products) detailed all conference discussions. The main conference conclusion was that holistic understanding and useful adaptation to rapid Arctic change requires bringing together scientists, Indigenous Knowledge holders, and policy makers in all phases of defining the problems, conducting research, and sharing knowledge.
Abstract not provided.
In August, the Associate Laboratory Directorate of Weapons Production (ALDWP) hosted two virtual hiring events and welcomed the first cohort of a new college pipeline program. With hiring steadily on the increase in support of the national security mission, creative methods like these have been key to finding successful candidates.
Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP ® reference collection website at https://mcnp.lanl.gov. Whisper-1.0 was originally developed in 2014 and used to assist with nuclear criticality safety validation at Los Alamos National Laboratory. Whisper was upgraded in 2016 to Whisper-1.1 and prepared for release with MCNP6.2. Whisper contains a library of over 1100 critical experiment benchmarks and quantifies neutronic similarity of an application to benchmarks in the library. Using highest similarity benchmarks, Whisper computes a calculational margin (CM) encompassing of the worst-case bias and bias uncertainty at a 99% confidence level for each application. In addition, portions of the margin of subcriticality (MOS) for nuclear data uncertainty and potential code errors are computed. The baseline upper subcritical limit (USL) computed by Whisper is comprised of the CM, MOS nuclear data , and MOS code errors . The Whisper baseline USL is absent a portion of the MOS due to the area of application, which is applied based upon judgment by the criticality safety analyst. An objective of this paper is to present the baseline USL, CM and portions of the MOS as computed by Whisper for comparison with similar sensitivity/uncertainty tools, such as those used by IRSN and ORNL. The initial comparison involves four critical experiment benchmarks: HEU-MET-FAST-013-001, HEU-SOLTHERM-001-008, PU-MET-FAST-022-001, AND PU-SOL-THERM-001-001, which have been: 1. modeled independently by LANL, IRSN, and ORNL based upon information provided in the ICSBEP Handbook, 2. are common in S/U libraries for LANL, IRSN, and ORNL, 3. span a range of energy spectrum and fissile material, and 4. taken as applications for the purposes of this study and therefore excluded from use as a benchmark for calculating the upper subcritical limit. Results presented in this paper have been computed using covariance data for all isotopes in ENDF/BVII.0 using a 44-group energy structure. Benchmarks in the Whisper library were run in MCNP6.2 using 100,000 neutrons per cycle, skipping 100 cycles for 500 active cycles. Reference 10 also compares the results for baseline USL with an order of magnitude greater neutrons, using the same total number of cycles with 1,000,000 neutrons per cycle. Subsequent to the results presented in Reference 10 changes were made to the benchmark library, as discussed in Reference 11. Newer results using the revised benchmark library are presented herein.
This document covers the organization of the laboratory down to the group leader level from 1943 to 1984.
Recent years have seen a significantly increased focus in the areas of knowledge retention and mentoring of junior staff within the U.S. national laboratory complex. In order to involve the university community in this process, as well, an international safeguards mentoring program was established by Sandia National Laboratories (SNL) for early career university faculty. After a successful experience during 2019, the program continued into 2020 to include two new faculty members who were paired with SNL subject matter experts based on the topic of their individual projects: one to work on advanced laboratory work for physics, technology, and policy of nuclear safeguards and nonproliferation, and the other to look at machine learning applied to international safeguards and nonproliferation. There is a two-pronged purpose to the program: fostering the development of educational resources available for international safeguards and exploring new research topics stemming from the exchange of mentor and mentee. Further, the program as a whole allows for junior faculty members to establish and expand a relationship network within international safeguards. In addition, programs such as this build stronger connections between the academic and the national laboratory community. Thanks to the junior faculty members that now have new connections into the laboratory community and potential for collaboration projects with the laboratories in the future, safeguards knowledge can actually increase far beyond just individually engaging students using this new and efficient avenue.