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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Assembling an Effective Team for Renewable Generation and Storage Projects

On-site renewable generation and storage systems have piqued the interest of facility owners to substantially reduce their energy costs and environmental footprint. Assembling an effective team before the project begins can streamline the implementation of these systems and ensure that the design, installation, and operation of the system are well aligned with the needs of the facility owner. To inform this process, this resource will provide three specific guidelines: Guideline 1: Identify common skillsets in renewable energy and storage projects; Guideline 2: Decide who will fill these skillsets, internally and externally; and Guideline 3: Recognize additional project considerations to ensure cost-effectiveness, increased resiliency, and contribution to both electrification and decarbonization goals.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2025

Modeling Protein–Protein and Protein–Ligand Interactions by the ClusPro Team in CASP16

ABSTRACT In the CASP16 experiment, our team employed hybrid computational strategies to predict both protein–protein and protein–ligand complex structures. For protein–protein docking, we combined physics‐based sampling—using ClusPro FFT docking and molecular dynamics—with AlphaFold (AF)‐based sampling, followed by AF‐based refinement. Our method produced numerous high‐accuracy complex models, including cases where AF alone failed, underscoring the critical role of physics‐based sampling alongside deep learning‐based refinement. For protein–ligand docking, we integrated the ClusPro LigTBM template‐based approach with a machine learning‐based confidence model for rescoring. The method preserves conserved interaction fragments derived from homologous complexes, followed by local resampling using physics‐based sampling and a diffusion model. Our template‐based strategy achieved a mean lDDT‐PLI of 0.69 across 233 targets, which was highly competitive. These results demonstrate that combining physics‐based modeling with AI‐driven refinement can significantly enhance the accuracy of both protein–protein and protein–ligand structure predictions.

Ashizawa, Ryota [Department of Applied Mathematics↗
DOE OSTI2019

Sandia Fracture Challenge 3: detailing the Sandia Team Q failure prediction strategy

The third Sandia Fracture Challenge illustrated the geometric and material uncertainties presented by modern additive manufacturing techniques. Tasked with the challenge of predicting failure of a complex additively-manufactured geometry made of 316L stainless steel, we combined a rigorous material calibration scheme with a number of statistical assessments of problem uncertainties. Particularly, we used optimization techniques to calibrate a rate-dependent and anisotropic Hill plasticity model to represent material deformation coupled with a damage model driven by void growth and nucleation. Through targeted simulation studies we assessed the influence of internal voids and surface flaws on the specimens of interest in the challenge which guided our material modeling choices. Employing the Kolmogorov–Smirnov test statistic, we developed a representative suite of simulations to account for the geometric variability of test specimens and the variability introduced by material parameter uncertainty. This method allowed the team to successfully predict the failure mode of the experimental test population as well as the global response with a high degree of accuracy.

316L stainless steel↗
DOE OSTI2015

THE TEAM KECK REDSHIFT SURVEY 2: MOSFIRE SPECTROSCOPY OF THE GOODS-NORTH FIELD

We present the Team Keck Redshift Survey 2 (TKRS2), a near-infrared spectral observing program targeting selected galaxies within the CANDELS subsection of the GOODS-North Field. The TKRS2 program exploits the unique capabilities of the Multi-Object Spectrometer For Infra-Red Exploration (MOSFIRE), which entered service on the Keck I telescope in 2012 and contributes substantially to the study of galaxy spectral features at redshifts inaccessible to optical spectrographs. The TKRS2 project targets 97 galaxies drawn from samples that include z ≈ 2 emission-line galaxies with features observable in the JHK bands as well as lower-redshift targets with features in the Y band. We present a detailed measurement of MOSFIRE’s sensitivity as a function of wavelength, including the effects of telluric features across the YJHK filters. The largest utility of our survey is in providing rest-frame-optical emission lines for z > 1 galaxies, and we demonstrate that the ratios of strong, optical emission lines of z ≈ 2 galaxies suggest the presence of either higher N/O abundances than are found in z ≈ 0 galaxies or low-metallicity gas ionized by an active galactic nucleus. We have released all TKRS2 data products into the public domain to allow researchers access to representative raw and reduced MOSFIRE spectra.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Functional team selection as a framework for local adaptation in plants and their belowground microbiomes

Abstract Multicellular organisms are hosts to diverse communities of smaller organisms known as microbiomes. Plants have distinctive microbiomes that can provide important functions related to nutrition, defense, and stress tolerance. Empirical studies provide convincing evidence that in some—but not all—circumstances, belowground microbiomes help plants adapt to their local environment. The purpose of this review is to develop functional team selection (FTS) as a framework to help predict the conditions necessary for root microbiomes to generate local adaptation for their plant hosts. FTS envisions plants and their microbiomes as complex adaptive systems, and plant adaptations as emergent properties of these systems. If plants have the capacity to recognize and cultivate beneficial microbes and suppress pathogens, then it is possible for plants to evolve the capacity to gain adaptations by curating their microbiome. In resource-limited and stressful environments, the emergent functions of complex microbial systems may contribute to positive feedback linked to plant vigor, and ultimately, local adaptation. The key factors in this process are: (i) selective force, (ii) host constitution, (iii) microbial diversity, and (iv) time. There is increasing interest in harnessing beneficial microbial interactions in agriculture and many microbial growth-promoting products are commercially available, but their use is controversial because a large proportion of these products fail to consistently enhance plant growth. The FTS framework may help direct the development of durable plant-microbiome systems that enhance crop production and diminish pathogens. It may also provide valuable insights for understanding and managing other kinds of host-microbe systems.

Environmental Sciences & Ecology↗
DOE OSTI2020

An Approximation Algorithm for a Task Allocation, Sequencing and Scheduling Problem Involving a Human-Robot Team

Here we present an approximation algorithm for a Task Allocation, Sequencing and Scheduling Problem (TASSP) involving a team of human operators and robots. The robots have to travel to a given set of targets and collaboratively work on the tasks at the targets with the human operators. The problem aims to find a sequence of targets for each robot to visit and schedule the tasks at the targets with the human operators such that each target is visited exactly once by some robot, the scheduling constraints are satisfied and the maximum mission time of any robot is minimum. This problem is a generalization of the single Traveling Salesman Problem and is NP-Hard. Given k robots and m human operators, an algorithm is developed for solving the TASSP with an approximation ratio equal to 5/2- 1/k when m ≥ k and equal to 7/2 -1/k otherwise. Computational results are also presented to corroborate the performance of the proposed algorithm.

42 ENGINEERING↗
DOE OSTI2018

Tundra Trait Team: A database of plant traits spanning the tundra biome

Motivation: The Tundra Trait Team (TTT) database includes field-based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade-offs, trait-environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform earth system model parameters. Main types of variable contained: The database contains 81,537 measurements of 18 plant traits. The most frequently measured traits (>1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen content, leaf carbon content, leaf phosphorus content, seed mass, and stem specific density. Spatial location and grain: Measurements were collected in tundra habitats in both the northern and southern hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia, and Siberia and alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand). More than 99% of observations are georeferenced. Time period and grain: All data were collected between 1964 and 2016. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement: Trait measurements were made on 858 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (87%), while a small number represent plot or site means or maximums per species. Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

HUMAN-ARTIFICIAL INTELLIGENCE TEAMING FOR THE U.S. NAVY: DEVELOPING A HOLISTIC RESEARCH ROADMAP

With the ever-increasing deluge of data and demand for warfighters to make decisions upon its analysis, U.S. defense strategy has prioritized the development of artificial intelligence (AI)/machine learning (ML) systems that can analyze multi-source data streams and suggest courses of action. However, there is a history of systems that have failed to be adopted by the warfighter due not only to unsolved technical challenges, but also a lack of usability or contributions to mission effectiveness, perceived or otherwise. To avoid this, research into human-AI teaming shows promise for developing AI systems that work with frontline operators. A recent National Academies of Sciences, Engineering, and Medicine report (NASEM, 2022) presented 57 research objectives in this area; however, the U.S. Navy requires a more-focused set of priorities, as it is impossible to tackle every priority. A workshop involving 23 human factors scientists, computer scientists, and active-duty sailors was organized at the Naval Information Warfare Center Pacific, resulting in a set of five research priorities spanning near-, mid-, and far-term time frames. This panel will summarize the results of this workshop, with a focus on the big questions both going into this workshop and coming out of it. The panel participants come from government, academia, and industry, providing perspective from the different kinds of organizations required to accomplish these research goals.

Wong, Jason↗
DOE OSTI2014

The CMSN team working on computational-design-Fe-based-superconductors (Final Report)

This CMSN collaboration comprises four nodes. Rutgers (G. Kotliar K. Haule) , U Arizona(M. Van Schilfgaarde), UCDavis (S. Savrasov W. Pickett) and Ames National Labs-Iowa State University (J. Schmalian- K.M. Ho- V. Antropov). The goal of this CMSN was to develop an unified methodology for electronic structure calculations to estimate from first principles the physical properties of iron pnictides which should serve as a test of the methodologies and the codes. This goals requires the integration of methodologies to treat electron electron interactions ( which can be treated by DMFT GW and Gutzwiller methods ) and electron phonon interactions and magnetic interactions (to be treated in linear response) which were developed by the different members of this CMSN team. I summarize below the collaborative work carried out until now below stressing the difficult but all important task of joint code development. In this area significant advances have taken place during the last year. These include a) an integration of the DMFT code of the Rutgers group with the Gutzwiller codes developed in Iowa. The result is the best available code to carry out LDA+G and is having impact on correlated materials with f electrons. and b) A Wannier interface between the QP GW code developed in Arizona and the Rutgers DMFT codes. These developments will be continued and will open new capabilities to treat correlated materials in general, and will be applied to the iron pnictides in the final year of this CMSN.

Kotliar, Gabriel↗
DOE OSTI2014

SOLIDS PRECIPITATION EVENT IN MCU CAUSAL ANALYSIS AND RECOMMENDATIONS FROM SOLIDS RECOVERY TEAM

A process upset occurred in the Modular Caustic-Side Solvent Extraction Unit (MCU) facility on April 6th, 2014. During recovery efforts, a significant amount of solids were found in the Salt Solution Feed Tank (SSFT), Salt Solution Receipt Tanks (SSRTs), two extraction contactors, and scrub contactors. The solids were identified by Savannah River National Laboratory (SRNL) as primarily sodium oxalate and sodium alumina silicate (NAS) with the presence of some aluminum hydroxide. NAS solids have been present in the SSFT since simulant runs during cold chemical startup of MCU in 2007, and have not hindered operations since that time. During the process upset in April 2014, the oxalate solids partially blocked the aqueous outlet of the extraction contactors, causing salt solution to exit through the contactor organic outlet to the scrub contactors with the organic phase. This salt solution overwhelmed the scrub contactors and passed with the organic phase to the strip section of MCU. The partially reversed flow of salt solution resulted in a Strip Effluent (SE) stream that was high in Isopar™ L, pH and sodium. The primary cause of the excessive solids accumulation in the SSRTs and SSFT at MCU is attributed to an increase in the frequency of oxalic acid cleaning of the 512-S primary filter. Agitation in the SSRTs at MCU in response to cold weather likely provided the primary mechanism to transfer the solids to the contactors. Sources of the sodium oxalate solids are attributed to the oxalic acid cleaning solution used to clean the primary filter at the Actinide Removal Process (ARP) filtration at 512-S, as well as precipitation from the salt batch feed, which is at or near oxalate saturation. The Solids Recovery Team was formed to determine the cause of the solids formation and develop recommendations to prevent or mitigate this event in the future. A total of 53 recommendations were generated. These recommendations were organized into 4 focus areas: • Improve understanding of oxalate equilibrium and kinetics in salt solutions • Reduction/elimination of oxalic acid cleaning in 512-S • Flowsheet optimization • Improving diagnostic capability The recommendations implemented prior to resumption of MCU operations provide a risk mitigation or detection function through additional sampling and observation. The longer term recommendations provide a framework to increase the basic process knowledge of both oxalate chemistry and filtration behavior and then facilitate decisions that improve the salt flowsheet as a system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Statistical Analysis of the Worker Engagement Survey Administered at the Worker Safety and Security Team Festival

The Worker Safety and Security Team (WSST) at Los Alamos National Laboratory holds an annual festival, WSST-fest, to engage workers and inform them about safety- and securityrelated matters. As part of the 2015 WSST-fest, workers were given the opportunity to participate in a survey assessing their engagement in their organizations and work environments. A total of 789 workers participated in the 23-question survey where they were also invited, optionally, to identify themselves, their organization, and to give open-ended feedback. The survey consisted of 23 positive statements (i.e. “My organization is a good place to work.”) with which the respondent could express a level of agreement. The text of these statements are provided in Table 1. The level of agreement corresponds to a 5-level Likert scale ranging from “Strongly Disagree” to “Strongly Agree.” In addition to assessing the overall positivity or negativity of the scores, the results were partitioned into several cohorts based on the response meta-data (self-identification, comments, etc.) to explore trends. Survey respondents were presented with the options to identify themselves, their organizations and to provide comments. These options suggested the following questions about the data set.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2013

Materials Technical Team Roadmap

Roadmap identifying the efforts of the Materials Technical Team (MTT) to focus primarily on reducing the mass of structural systems such as the body and chassis in light-duty vehicles (including passenger cars and light trucks) which enables improved vehicle efficiency regardless of the vehicle size or propulsion system employed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Sigma Team for Advanced Actinide Recycle FY2015 Accomplishments and Directions

The Sigma Team for Minor Actinide Recycle (STAAR) has made notable progress in FY 2015 toward the overarching goal to develop more efficient separation methods for actinides in support of the United States Department of Energy (USDOE) objective of sustainable fuel cycles. Research in STAAR has been emphasizing the separation of americium and other minor actinides (MAs) to enable closed nuclear fuel recycle options, mainly within the paradigm of aqueous reprocessing of used oxide nuclear fuel dissolved in nitric acid. Its major scientific challenge concerns achieving selectivity for trivalent actinides vs lanthanides. Not only is this challenge yielding to research advances, but technology concepts such as ALSEP (Actinide Lanthanide Separation) are maturing toward demonstration readiness. Efforts are organized in five task areas: 1) combining bifunctional neutral extractants with an acidic extractant to form a single process solvent, developing a process flowsheet, and demonstrating it at bench scale; 2) oxidation of Am(III) to Am(VI) and subsequent separation with other multivalent actinides; 3) developing an effective soft-donor solvent system for An(III) selective extraction using mixed N,O-donor or all-N donor extractants such as triazinyl pyridine compounds; 4) testing of inorganic and hybrid-type ion exchange materials for MA separations; and 5) computer-aided molecular design to identify altogether new extractants and complexants and theory-based experimental data interpretation. Within these tasks, two strategies are employed, one involving oxidation of americium to its pentavalent or hexavalent state and one that seeks to selectively complex trivalent americium either in the aqueous phase or the solvent phase. Solvent extraction represents the primary separation method employed, though ion exchange and crystallization play an important role. Highlights of accomplishments include: Confirmation of the first-ever electrolytic oxidation of Am(III) in a noncomplexing aqueous solution and submission of this scientific breakthrough as a paper in Science; The first-ever co-crystallization of Am(VI) with UO 2 (NO 3 ) 2 ∙ 6H 2 O, opening the door to a new approach for separating hexavalent actinides as a group; Results showing that three potentially problematic metals will not present risk in ALSEP; Improvement in ALSEP contactor stripping kinetics to acceptable performance; A comparison of centrifugal contactors vs mixer-settlers showing the former performs better in ALSEP stripping; Synthesis of new mixed N,O-donor extractants with enhanced solubility and strength for selective trivalent actinide extraction; Development of computational methods showing promise in prediction of the selectivity of new extractants for trivalent actinides vs lanthanides; An order-of-magnitude improvement in aqueous Am/Eu complexation selectivity of an alternative macrocyclic stripping agent for ALSEP, potentially enabling an option for an Am product stream free from both Ln and Cm. An alternative aqueous combination of dipicolinate complexant and malonate buffer that may present options for ALSEP and TALSPEAK (Trivalent Actinide-Lanthanide Separations by Phosphorus-reagent Extraction from Aqueous Komplexes) type separations. The ALSEP concept is advancing toward a benchtop flowsheet demonstration planned for FY 2016, and a bench-scale test bed at Idaho National Laboratory (INL) will be employed to demonstrate at least one tandem Am oxidation and separation concept. This report outlines the goals of the STAAR, significance of achieving these goals, STAAR organization around the above aims and questions, recent highlights, and future directions. The report also includes a listing of publications, reports, patents, and dissertations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Learning Team Review 2016-0002 Parking Lot Event 2016

The purpose of a Learning Team is to transfer and communicate the information into operational feedback and improvement. We want to pay attention to the small things that go wrong because they are often early warning signals and may provide insight into the health of the whole system. The incident involved the collision of a van with a forklift having raised tines in rainy, overcast weather.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Carbon Capture Multidisciplinary Simulation Center Trilab Support Team (TST) Fall Meeting 2016 Report

The theme of this year’s meeting was “Predictivity: Now and in the Future”. After welcoming remarks, Erik Draeger gave a talk on the NNSA Labs’ history of predictive simulation and the new challenges faced by upcoming architecture changes. He described an example where the volume of analysis data produced by a set of inertial confinement fusion (ICF) simulations on the Trinity machine was too large to store or transfer, and the steps needed to reduce it to a manageable size. He also described the software re-engineering plan for LLNL’s suite of multiphysics codes and physics packages with a new push toward common components, making collaboration with teams like the CCMSC who already have experience trying to architect complex multiphysics code infrastructure on next-generation architectures all the more important. Phil Smith then gave an overview outlining the goals of the project, namely to accelerate development of new technology in the form of high efficiency carbon capture pulverized coal power generation as well as further optimize existing state of the art designs. He then presented a summary of the Center’s top-down uncertainty quantification approach, in which ultimate target predictivity informs uncertainty targets for lower-level components, and gave data on how close all the different components currently are to their targets. Most components still need an approximately two-fold reduction in uncertainty to hit the ultimate predictivity target, but the current accuracy is already rather impressive.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Team West Virginia/Rome Final Report

Overall, the team, West Virginia University (WVU) and University of Rome Tor Vergata (UTV), has a goal of building an attractive, low-cost, energy-efficient solar-powered home that represents both the West Virginian and Italian cultures.

14 SOLAR ENERGY↗
DOE OSTI2017

General Guidelines on Criteria for Adoption or Rejection of Evaluated Libraries and Data by the Nuclear Data Team

This memo contains general guidelines on what documentation and tools need to be in place as well as format and data testing requirements such that evaluated nuclear data sets or entire libraries can be adopted by the nuclear data team. Additional requirements beyond this memo might apply for specific nuclear data observables. These guidelines were established based on discussions between J.L. Conlin, M.G. Gray, A.P. McCartney, D. Neudecker, D.K. Parsons and M.C. White.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗