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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Science and Solutions for a Planet Under Pressure: Synthetic Research, Analytics, and Community Engagement on Five Priority Theme Areas

Support from the Department of Energy proved instrumental in supporting the work of Global Council for Science and the Environment (GCSE) on synthetic research, analysis, and community engagement, oriented around the themes and discussions from the GCSE Drawdown 2021 Conference — Research to Action: Science and Solutions for a Planet Under Pressure. These efforts helped inform and enhance the societal relevance of the knowledge that has been generated through the conference and, at the same time, advance the scientific insights acquired through synthesis and scientific translation efforts. The work centered on three main objectives: 1) documentation of findings from the completed GCSE 2021, culminating in the publication of a synthesis report; 2) development and vetting of integrated use cases that illustrate synthesis methods and enable scientific outreach, communications, and translational discussions among universities and the broader research community; and 3) strengthening the scientific basis for energy education research by sharing findings in university-educator fora.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Sierra/SolidMechanics 5.8 User's Manual

Sierra/SolidMechanics (Sierra/SM) is a Lagrangian, three-dimensional code for finite element analysis of solids and structures. It provides capabilities for explicit dynamic, implicit quasistatic and dynamic analyses. The explicit dynamics capabilities allow for the efficient and robust solution of models with extensive contact subjected to large, suddenly applied loads. For implicit problems, Sierra/SM uses a multi-level iterative solver, which enables it to effectively solve problems with large deformations, nonlinear material behavior, and contact. Sierra/SM has a versatile library of continuum and structural elements, and a large library of material models. The code is written for parallel computing environments enabling scalable solutions of extremely large problems for both implicit and explicit analyses. It is built on the SIERRA Framework, which facilitates coupling with other SIERRA mechanics codes. This document describes the functionality and input syntax for Sierra/SM.

42 ENGINEERING↗

DOE OSTI2022

Sierra/SolidMechanics 5.10 User's Guide

42 ENGINEERING↗

DOE OSTI2022

Sensitivity Analyses for Monte Carlo Sampling-Based Particle Simulations

Computational design-based optimization is a well-used tool in science and engineering. Our report documents the successful use of a particle sensitivity analysis for design-based optimization within Monte Carlo sampling-based particle simulation—a currently unavailable capability. Such a capability enables the particle simulation communities to go beyond forward simulation and promises to reduce the burden on overworked analysts by getting more done with less computation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Sierra/Solid Mechanics 5.16 User's Guide

36 MATERIALS SCIENCE↗

DOE OSTI2025

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women

Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditional topic modeling, such as Latent Dirichlet Allocation (LDA), faces limitations in capturing the semantic relationships in the text document although it has been widely applied in text mining. BERTopic, created in 2022, leveraged advances in deep learning and can capture the contextual relationships between words. In this work, we integrated Artificial Intelligence (AI) modules to LDA and BERTopic and provided a comprehensive comparison on the analysis of prescription opioid-related cardiovascular risks in women. Opioid use can increase the risk of cardiovascular problems in women such as arrhythmia, hypotension etc. 1,837 abstracts were retrieved and downloaded from PubMed as of April 2024 using three Medical Subject Headings (MeSH) words: “opioid,” “cardiovascular,” and “women.” Machine Learning of Language Toolkit (MALLET) was employed for the implementation of LDA. BioBERT was used for document embedding in BERTopic. Eighteen was selected as the optimal topic number for MALLET and 23 for BERTopic. ChatGPT-4-Turbo was integrated to interpret and compare the results. The short descriptions created by ChatGPT for each topic from LDA and BERTopic were highly correlated, and the performance accuracies of LDA and BERTopic were similar as determined by expert manual reviews of the abstracts grouped by their predominant topics. The results of the t-SNE (t-distributed Stochastic Neighbor Embedding) plots showed that the clusters created from BERTopic were more compact and well-separated, representing improved coherence and distinctiveness between the topics. Our findings indicated that AI algorithms could augment both traditional and contemporary topic modeling techniques. In addition, BERTopic has the connection port for ChatGPT-4-Turbo or other large language models in its algorithm for automatic interpretation, while with LDA interpretation must be manually, and needs special procedures for data pre-processing and stop words exclusion. Therefore, while LDA remains valuable for large-scale text analysis with resource constraints, AI-assisted BERTopic offers significant advantages in providing the enhanced interpretability and the improved semantic coherence for extracting valuable insights from textual data.

Research & Experimental Medicine↗

NASA NTRS1995

The Federal Role in Bringing Education into the National Information Infrastructure

One of the most important issues facing Congress is to work with business, education, and the states to enable the nation's shools to better prepare students for a technological work force and to ensure that education has a place on the National Information Infrastructure (NII). This document provides background and important information for national leaders concerned about education, the information infrastructure, and related issues for the Federal government.

Cradler, John↗

NASA NTRS2006

Flying the ST-5 Constellation with "Plug and Play" Autonomy Components and the GMSEC Bus

The Space Technology 5 (ST5) Project, part of NASA's New Millennium Program, will consist of a constellation of three micro-satellites. This viewgraph document presents the components that will allow it to operate in an autonomous mode. The ST-5 constellation will use the GSFC Mission Services Evolution Center (GMSEC) architecture to enable cost effective model based operations. The ST-5 mission will demonstrate several principles of self managing software components.

Shendock, Bob↗

DOE OSTI2022

A New Charged Lepton Flavor Violation Program at Fermilab

The muon has played a central role in establishing the Standard Model of particle physics, and continues to provide valuable information about the nature of new physics. A new complex at Fermilab, the Advanced Muon Facility, would provide the world's most intense positive and negative muon beams by exploiting the full potential of PIP-II and the Booster upgrade. This facility would enable a broad muon physics program, including studies of charged lepton flavor violation, muonium-antimuonium transitions, a storage ring muon EDM experiment, and muon spin rotation experiments. This document describes a staged realization of this complex, together with a series of next-generation experiments to search for charged lepton flavor violation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

PyCCE: A python package for custer correlation expansion simulations of spin qubit dynamics.

PyCCE, an open-source Python library for simulating the dynamics of spin qubits in a spin bath, is presented using the cluster-correlation expansion (CCE) method. PyCCE includes modules to generate realistic spin baths, employing coupling parameters computed from first principles with electronic structure codes, and enables the user to run simulations with either the conventional or generalized CCE method. Three use cases of the Python library are illustrated: the calculation of the Hahn-echo coherence time of the nitrogen-vacancy in diamond; the calculation of the coherence time of the basal divacancy in silicon carbide at avoided crossings; and the calculation for magnetic field orientation-dependent dynamics of a shallow donor in silicon. The complete documentation, downloadable tutorials, and installation instructions are available at https://pycce.readthedocs.io/en/latest/.

coherence↗

DOE OSTI2015

A Biochar Classification System and Associated Test Methods

In this chapter, a biochar classification system related to its use as soil amendment is proposed. This document builds upon previous work and constrains its scope to materials with properties that satisfy the criteria for biochar as defined by either the International Biochar Initiative (IBI) Biochar Standards or the European Biochar Community (EBC) Standards, and it is intended to minimise the need for testing in addition to those required according to the above-mentioned standards. The classification system envisions enabling stakeholders and commercial entities to (i) identify the most suitable biochar to fulfil the requirements for a particular soil and/or land-use, and (ii) distinguish the application of biochar for specific niches (e.g., soilless agriculture). It is based on the best current knowledge and the intention is to periodically review and update the document based on new data and knowledge that become available in the scientific literature. The main thrust of this classification system is based on the direct or indirect beneficial effects that biochar provides from its application to soil. We have classified the potential beneficial effects of biochar application to soils into five categories with their corresponding classes, where applicable: (i) carbon (C) storage value, (ii) fertiliser value, (iii) liming value, (iv) particle-size, and (v) use in soil-less agriculture. A summary of recommended test methods is provided at the end of the chapter.

Biochar↗

NASA NTRS2008

Stochastic Analysis of Orbital Lifetimes of Spacecraft

A document discusses (1) a Monte-Carlo-based methodology for probabilistic prediction and analysis of orbital lifetimes of spacecraft and (2) Orbital Lifetime Monte Carlo (OLMC)--a Fortran computer program, consisting of a previously developed long-term orbit-propagator integrated with a Monte Carlo engine. OLMC enables modeling of variances of key physical parameters that affect orbital lifetimes through the use of probability distributions. These parameters include altitude, speed, and flight-path angle at insertion into orbit; solar flux; and launch delays. The products of OLMC are predicted lifetimes (durations above specified minimum altitudes) for the number of user-specified cases. Histograms generated from such predictions can be used to determine the probabilities that spacecraft will satisfy lifetime requirements. The document discusses uncertainties that affect modeling of orbital lifetimes. Issues of repeatability, smoothness of distributions, and code run time are considered for the purpose of establishing values of code-specific parameters and number of Monte Carlo runs. Results from test cases are interpreted as demonstrating that solar-flux predictions are primary sources of variations in predicted lifetimes. Therefore, it is concluded, multiple sets of predictions should be utilized to fully characterize the lifetime range of a spacecraft.

Sasamoto, Washito↗

NASA NTRS1991

Space Electrochemical Research and Technology

This document contains the proceedings of NASA's third Space Electrochemical Research and Technology (SERT) Conference, held at the NASA Lewis Research Center on April 9-10, 1991. The objective of the conference was to assess the present status and general thrust of research and development in those areas of electrochemical technology required to enable NASA missions into the next century. The conference provided a forum for the exchange of ideas and opinions of those actively involved in the field, in order to define new opportunities for the application of electrochemical processes in future NASA missions. Papers were presented in three technical areas: the electrochemical interface, the next generation in aerospace batteries and fuel cells, and electrochemistry for nonenergy storage applications. This document contains the abstracts of the papers presented.

Electrochemistry↗

NASA NTRS2003

Using CFD as Rocket Injector Design Tool: Recent Progress at Marshall Space Flight Center

The choice of tools used for injector design is in a transitional phase between exclusive reliance on the empirically based correlations and extensive use of computational fluid dynamics (CFD). The Next Generation Launch Technology (NGLT) Program goals emphasizing lower costs and increased reliability have produced a need to enable CFD as an injector design tool in a shorter time frame. This is the primary objective of the Staged Combustor Injector Technology Task currently under way at Marshall Space Flight Center (MSFC). The documentation of this effort begins with a very brief status of current injector design tools. MSFC's vision for use of CFD as a tool for combustion devices design is stated and discussed with emphasis on the injector. The concept of the Simulation Readiness Level (SRL), comprised of solution fidelity, robustness and accuracy, is introduced and discussed. This quantitative measurement is used to establish the gap between the current state of demonstrated capability and that necessary for regular use in the design process. MSFC's view of the validation process is presented and issues associated with obtaining the necessary data are noted and discussed. Three current experimental efforts aimed at generating validation data are presented. The importance of uncertainty analysis to understand the data quality is also demonstrated. First, a brief status of current injector design tools is provided as context for the current effort. Next, the MSFC vision for using CFD as an injector design tool is stated. A generic CFD-based injector design methodology is also outlined and briefly discussed. Three areas where MSFC is using injector CFD analyses for program support will be discussed. These include the Integrated Powerhead Development (IPD) engine which uses hydrogen and oxygen propellants in a full flow staged combustion (FFSC) cycle and the TR-107 and the RS84 engine both of which use RP-1 and oxygen in an ORSC cycle. Finally, an attempt is made to objectively summarize what progress has been made at MSFC in enabling CFD as an injector design tool.

Tucker, Kevin↗

DOE OSTI2018

Tracking HIV-1 recombination to resolve its contribution to HIV-1 evolution in natural infection

Recombination in HIV-1 is well documented, but its importance in the low-diversity setting of within-host diversification is less understood. Here we develop a novel computational tool (RAPR (Recombination Analysis PRogram)) to enable a detailed view of in vivo viral recombination during early infection, and we apply it to near-full-length HIV-1 genome sequences from longitudinal samples. Recombinant genomes rapidly replace transmitted/founder (T/F) lineages, with a median half-time of 27 days, increasing the genetic complexity of the viral population. We identify recombination hot and cold spots that differ from those observed in inter-subtype recombinants. Furthermore, RAPR analysis of longitudinal samples from an individual with well-characterized neutralizing antibody responses shows that recombination helps carry forward resistance-conferring mutations in the diversifying quasispecies. These findings provide insight into molecular mechanisms by which viral recombination contributes to HIV-1 persistence and immunopathogenesis and have implications for studies of HIV transmission and evolution in vivo.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

FrESCO: Framework for Exploring Scalable Computational Oncology

The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information from electronic health records. This data is then used to create summary statistics about cancer incidence and mortality to facilitate population health monitoring. Extracting phenotypic information from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating the information extraction process from cancer pathology reports has the potential to improve data quality by extracting information in a consistent manner across registries. It can also improve patient outcomes by reducing the time from diagnosis, enabling rapid case ascertainment for clinical trials. Here we present FrESCO, a modular deep-learning natural language processing (NLP) library initially designed for extracting pathology information from clinical text documents. This repository is not solely limited to clinical medical text, but may also be used by researchers just getting started with NLP methods and those looking for a robust solution for their classification problems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Volume 1: Introduction to the HFIR Futures - Enhanced Capabilities Series

Since it began operating at full power in 1966, the High Flux Isotope Reactor (HFIR) has contributed unparalleled neutron science capabilities to research on neutron scattering, isotope production, materials and fuels irradiation, and neutron activation analysis. HFIR is a high-performance, multi-mission research reactor operated on behalf of the US Department of Energy (DOE) at the Oak Ridge National Laboratory (ORNL). In 2020, a DOE Basic Energy Sciences Advisory Committee Subcommittee (BESAC) published a report recommending that DOE make significant investments in HFIR to enable continued operations beyond the year 2100 while also enabling new research and isotope production capabilities. ORNL organized an initiative to investigate how to specifically address the report’s key recommendations, including enabling long-term operation, brainstorming future scientific research needs, and outlining the infrastructure required to realize these future research capabilities. A multivolume series of reports has been developed to document the nonscattering enhancements. This volume, the introductory report, provides an overview of HFIR and the initiative.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1980

Scale model studies for establishing the flow patterns of a low-speed tunnel

Experiments were conducted in a model tunnel scaled down in a ratio of 1:24 from the full size prototype V/STOL tunnel at NASA Langley Research Center. The flow characteristics around the tunnel were studied and the location and causes of local flow separation and local recirculation were documented. The study of the interaction between the various components from which the tunnel is built, an experimental setup similar to the sequence of tunnel circuit components was constructed which enabled the various components to be tested either individually or in combination. The components were tested by the simple technique of blowing air through them, then measuring the velocity distribution at relevant sections.

Barna, P. S.↗