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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

UPR/Mayaguez High Energy Physics

This year the University of Puerto Rico at Mayaguez (UPRM) High Energy Physics (HEP) group continued with the ongoing research program outlined in the grant proposal. The program is centered on the Compact Muon Solenoid (CMS) experiment at the proton-proton (pp) collisions at the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland. The main research focus is on data analysis and on the preparation for the High Luminosity (HL) LHC or experiment detector upgrade. The physics data analysis included Higgs Doublet Search and measurement of the (1) Λ 0 b branching fraction, (2) B meson mass, and (3) hyperon θ - b lifetime. The detector upgrade included work on the preparations for the Forward Pixel (FPIX) detector Silicon Sensor Testing in a production run at Fermilab. In addition, the group has taken responsibilities on the Software Release through our former research associate Dr. Eric Brownson who acted until last December as a Level Two Offline Manager for the CMS Upgrade. In support of the CMS data analysis activities carried out locally, the UPRM group has built and maintains an excellent Tier3 analysis center in Mayaguez. This allowed us to analyze large data samples and to continue the development of algorithms for the upgrade tracking robustness we started several years ago, and we plan to resume in the near future. This project involves computer simulation of the radiation damage to be suffered at the higher luminosities of the upgraded LHC. This year we continued to serve as a source of outstanding students for the field of high energy physics. Three of our graduate students finished their MS work in May, 2014, Their theses research were on data analysis of heavy quark b-physics. All of them are currently enrolled at Ph.D. physics program across the nation. One of them (Hector Moreno) at New Mexico University (Hector Moreno), one at University of New Hampshire (Sandra Santiesteban) and one at University of Puerto Rico-Rio Piedras (Carlos Malca). The students H. Moreno and C. Malca has been directly supervised by Dr. Mendez and S. Santiesteban supervised by Dr. Ramirez. During the last 13 years, our group have graduated 23 MS students on experimental High Energy Physics data analysis and applied hardware techniques. Most of the students have been supported by DOE grants, included this grant. Since 2001, Dr. Mendez have directly supervised eleven students, Dr. Ramirez three students and the former PI (Dr. Lopez) nine students. These theses work are fully documented in the group web page (http://charma.uprm.edu). The High Energy Physics group at Mayaguez is small and presently consists of three Physics faculty members, the Senior Investigators Dr. Hector Mendez (Professor) and Dr. Juan Eduardo Ramirez (Professor), and Dr. Sudhir Malik who was just hired in July 2014. Dr. Ramirez is in charge of the UPRM Tier-3 computing and will be building the network bandwidth infrastructure for the campus, while Dr. Mendez will continues his effort in finishing the heavy quark physics data analysis and moving to work on SUSY analysis for the 2015 data. Our last grant application in 2012 was awarded only for 2013-2014. As a result our postdoc position was lost last month of March. Since then, we have hired Dr. Malik as a new faculty in order to reinforce the group and to continue our efforts with the CMS experiment. Our plan is to hire another junior faculty in the next two years to strengthen the HEP group even further. Dr. Mendez continues with QuarkNet activities involving an ever larger group of high school physics teachers from all around Puerto Rico.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Processing data communications events by awakening threads in parallel active messaging interface of a parallel computer

Processing data communications events in a parallel active messaging interface (`PAMI`) of a parallel computer that includes compute nodes that execute a parallel application, with the PAMI including data communications endpoints, and the endpoints are coupled for data communications through the PAMI and through other data communications resources, including determining by an advance function that there are no actionable data communications events pending for its context, placing by the advance function its thread of execution into a wait state, waiting for a subsequent data communications event for the context; responsive to occurrence of a subsequent data communications event for the context, awakening by the thread from the wait state; and processing by the advance function the subsequent data communications event now pending for the context.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Spatial Access Priority Mapping (SAPM) with Fishers: A Quantitative GIS Method for Participatory Planning

Spatial management tools, such as marine spatial planning and marine protected areas, are playing an increasingly important role in attempts to improve marine management and accommodate conflicting needs. Robust data are needed to inform decisions among different planning options, and early inclusion of stakeholder involvement is widely regarded as vital for success. One of the biggest stakeholder groups, and the most likely to be adversely impacted by spatial restrictions is the fishing community. In order to take their priorities into account, planners need to understand spatial variation in their perceived value of the sea. Here, a readily accessible, novel method for quantitatively mapping fishers’ spatial access priorities is presented. Spatial access priority mapping, or SAPM, uses only basic functions of standard spreadsheet and GIS software. Unlike the use of remote-sensing data, SAPM actively engages fishers in participatory mapping, documenting rather than inferring their priorities. By so doing, SAPM also facilitates the gathering of other useful data, such as local ecological knowledge. The method was tested and validated in Northern Ireland, where over 100 fishers participated in a semi-structured questionnaire and mapping exercise. The response rate was excellent, 97%, demonstrating fishers’ willingness to be involved. The resultant maps are easily accessible and instantly informative, providing a very clear visual indication of which areas are most important for the fishers. The maps also provide quantitative data, which can be used to analyse the relative impact of different management options on the fishing industry and can be incorporated into planning software, such as MARXAN, to ensure that conservation goals can be met at minimum negative impact to the industry. This research shows how spatial access priority mapping can facilitate the early engagement of fishers and the ready incorporation of their priorities into the decision-making process in a transparent, quantitative way.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

FY25 Report on Water NSTF Testing: Parametric and Accident Testing with Lower Tank Inlet

The Natural Convection Shutdown Heat Removal Test Facility (NSTF) at Argonne National Laboratory has continued to generate empirical validation data on the performance of water-based reactor cavity cooling system (RCCS) for seven years. This data is actively being used to support the development of passive decay heat removal systems for advanced reactors. Distinguishing this facility are 1) the large, ½ scale of the facility and 2) its governance under an NQA-1 qualified program for producing data of the highest pedigree for advanced reactor designers and regulators. In addition to the experimental activities discussed in this report, a computational modeling program continues to support the experimental program and further accuracy and understanding of the computational models. Together, the experimental and computational work create a mutually beneficial relationship integral to the overall program objective of advancing the understanding of the RCCS technology.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Delegated Regressor, A Robust Approach for Automated Anomaly Detection in the Soil Radon Time Series Data

We propose a new method based on the idea of delegating regressors for predicting the soil radon gas concentration (SRGC) and anomalies in radon or any other time series data. The proposed method is compared to different traditional boosting e.g., Extreme Gradient Boosting (EGB) and simple regression methods e.g., support vector regressors with linear kernel and radial kernel in terms of accurate predictions. R language has been used for the statistical analysis of radon time series (RTS) data. The results obtained show that the proposed methodology predicts SRGC more accurately when compared to different traditional boosting and regression methods. The best correlation is found between the actual and predicted radon concentration for window size of 2 i.e., two days before and after the start of seismic activities. RTS data was collected from 05 February 2017 to 16 February 2018, including 7 seismic events recorded during the study period. Findings of study show that the proposed methodology predicts the SRGC with more precision, for all the window sizes, by overlapping predicted with the actual radon time series concentrations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Developing a New Model to Estimate the Costs to Decommission DOE's Active Facilities - 16368

The Active Facilities Data Collection System (AFDCS) is a major means the U.S. Department of Energy (DOE or Department) uses to estimate its out-year environmental liability for the active and surplus facilities across the Department. The previous AFDCS cost model was based on cost assumptions that date back to the mid-1990s. The model is being replaced with a model that reflects more recent facility disposition experience and costs. DOE's Office of Environmental Management's (DOE-EM) historical cost collection database provides the basis for the new AFDCS cost model. This paper describes the process that was used to update the AFDCS facility data inputs, analyze this data, and formulate historical costs and parameters. This process created a robust and reliable cost model that will provide DOE with a valid estimate of the facilities' disposition costs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

XRootD popularity on hadoop clusters

Performance data and metadata of the computing operations at the CMS experiment are collected through a distributed monitoring infrastructure, currently relying on a traditional Oracle database system. This paper shows how to harness Big Data architectures in order to improve the throughput and the efficiency of such monitoring. A large set of operational data - user activities, job submissions, resources, file transfers, site efficiencies, software releases, network traffic, machine logs - is being injected into a readily available Hadoop cluster, via several data streamers. The collected metadata is further organized running fast arbitrary queries; this offers the ability to test several Map&Reduce-based frameworks and measure the system speed-up when compared to the original database infrastructure. By leveraging a quality Hadoop data store and enabling an analytics framework on top, it is possible to design a mining platform to predict dataset popularity and discover patterns and correlations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

New Science, New Media: An Assessment of the Online Education and Public Outreach Initiatives of The Dark Energy Survey

As large-scale international collaborations become the standard for astronomy research, a wealth of opportunities have emerged to create innovative education and public outreach (EPO) programming. In the past two decades, large collaborations have focused EPO strategies around published data products. Newer collaborations have begun to explore other avenues of public engagement before and after data are made available. We present a case study of the online EPO program of The Dark Energy Survey, currently one of the largest international astronomy collaborations actively taking data. DES EPO is unique at this scale in astronomy, as far as we are aware, as it evolved organically from scientists' passion for EPO and is entirely organized and implemented by the volunteer efforts of collaboration scientists. We summarize the strategy and implementation of eight EPO initiatives. For content distributed via social media, we present reach and user statistics over the 2016 calendar year. DES EPO online products reached ~2,500 users per post, and 94% of these users indicate a predisposition to science-related interests. We find no obvious correlation between post type and post reach, with the most popular posts featuring the intersections of science and art and/or popular culture. We conclude that one key issue of the online DES EPO program was designing material which would inspire new interest in science. The greatest difficulty of the online DES EPO program was sustaining scientist participation and collaboration support; the most successful programs are those which capitalized on the hobbies of participating scientists. We present statistics and recommendations, along with observations from individual experience, as a potentially instructive resource for scientists or EPO professionals interested in organizing EPO programs and partnerships for large science collaborations or organizations.

Wolf, R. C.↗
DOE OSTI2023

A multiscale recurrent neural network model for predicting energy production from geothermal reservoirs

Optimization of energy production from geothermal reservoirs requires reliable prediction of energy production performance under alternative operation and development scenarios. Traditionally, reservoir simulation models are used for the evaluation and screening of alternative production and development plans. However, simulation models require extensive data collection and modeling efforts and are time-consuming to build, run, and update. Data-driven predictive models, on the other hand, can serve as efficient prediction tools that can be used for decision support and management of daily operations and surveillance activities. Data-driven models become particularly attractive when a reservoir simulation model for a field does not exist and/or is difficult to build. Machine learning (ML)-based data-driven models that have recently become popular in several fields exploit statistical patterns and relations in training data to generate predictions. As such, they tend to perform better in interpolation problems (that is, prediction within the training data range) than when they are used to extrapolate beyond the training data. Production data from geothermal reservoirs tend to exhibit short-term variabilities as well as long-term trends, such as monotonically declining production temperatures. Capturing both short-term features and long-term trends with ML-based models is not trivial. We evaluate the use of recurrent neural networks (RNN) for the prediction of energy production from geothermal reservoirs. RNN is a class of ML architectures that are used to represent and predict sequential/dynamic data. Thus, it can be challenging to apply RNN to problems where long-term trends must be captured and extrapolation beyond the training data range is needed. We introduce the multiscale RNN architecture to extend the application of RNN to detect and predict both short-term variabilities and long-term trends in geothermal data. The developed architecture consists of a long-term component to only capture low-frequency data patterns, and a short-term component to detect features with higher frequency and more nonlinearity. The final prediction is obtained by combining the long-term and short-term predictions. Both synthetic and field data are used to evaluate the presented multiscale RNN model. The prediction performance of the multiscale RNN is compared against those obtained from the regular RNN and the autoregressive (AR) model. The results suggest that the multiscale architecture improves the long-term prediction performance of the regular RNN and enhances its robustness against noise.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Changing-look Active Galactic Nuclei from the Dark Energy Spectroscopic Instrument. I. Sample from the Early Data

Changing-look active galactic nuclei (CL AGNs) can be generally confirmed by the emergence (turn-on) or disappearance (turn-off) of broad emission lines (BELs), associated with a transient timescale (about 100 ~ 5000 days) that is much shorter than predicted by traditional accretion disk models. We carry out a systematic CL AGN search by crossmatching the spectra coming from the Dark Energy Spectroscopic Instrument and the Sloan Digital Sky Survey. Following previous studies, we identify CL AGNs based on Hα, Hβ, and Mg ii at z ≤ 0.75 and Mg ii, C iii], and C iv at z > 0.75. We present 56 CL AGNs based on visual inspection and three selection criteria, including 2 Hα, 34 Hβ, 9 Mg ii, 18 C iii], and 1 C iv CL AGN. Eight cases show simultaneous appearances/disappearances of two BELs. We also present 44 CL AGN candidates with significant flux variation of BELs, but remaining strong broad components. In the confirmed CL AGNs, 10 cases show additional CL candidate features for different lines. In this paper, we find: (1) a 24:32 ratio of turn-on to turn-off CL AGNs; (2) an upper-limit transition timescale ranging from 330 to 5762 days in the rest frame; and (3) the majority of CL AGNs follow the bluer-when-brighter trend. Our results greatly increase the current CL census (~30%) and would be conducive to exploring the underlying physical mechanism.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Replication Data for: Tuning reactivity layer-by-layer: formic acid activation on Ag/Pd(111)

The data underlying this published work have been made publicly available in this repository as part of the IMASC Data Management Plan. This work was supported as part of the Integrated Mesoscale Architectures for Sustainable Catalysis (IMASC), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award # DE-SC0012573.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Single-cell measurement of plasmid copy number and promoter activity

Abstract Accurate measurements of promoter activities are crucial for predictably building genetic systems. Here we report a method to simultaneously count plasmid DNA, RNA transcripts, and protein expression in single living bacteria. From these data, the activity of a promoter in units of RNAP/s can be inferred. This work facilitates the reporting of promoters in absolute units, the variability in their activity across a population, and their quantitative toll on cellular resources, all of which provide critical insights for cellular engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

CD206 + Trem2 + macrophage accumulation in the murine knee joint after injury is associated with protection against post-traumatic osteoarthritis in MRL/MpJ mice

Post-traumatic osteoarthritis (PTOA) is a painful joint disease characterized by the degradation of bone, cartilage, and other connective tissues in the joint. PTOA is initiated by trauma to joint-stabilizing tissues, such as the anterior cruciate ligament, medial meniscus, or by intra-articular fractures. In humans, ~50% of joint injuries progress to PTOA, while the rest spontaneously resolve. To better understand molecular programs contributing to PTOA development or resolution, we examined injury-induced fluctuations in immune cell populations and transcriptional shifts by single-cell RNA sequencing of synovial joints in PTOA-susceptible C57BL/6J (B6) and PTOA-resistant MRL/MpJ (MRL) mice. We identified significant differences in monocyte and macrophage subpopulations between MRL and B6 joints. A potent myeloid-driven anti-inflammatory response was observed in MRL injured joints that significantly contrasted the pro-inflammatory signaling seen in B6 joints. Multiple CD206 + macrophage populations classically described as M2 were found enriched in MRL injured joints. These CD206 + macrophages also robustly expressed Trem2 , a receptor involved in inflammation and myeloid cell activation. These data suggest that the PTOA resistant MRL mouse strain displays an enhanced capacity of clearing debris and apoptotic cells induced by inflammation after injury due to an increase in activated M2 macrophages within the synovial tissue and joint space.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

U.S. Industry Opportunities for Advanced Nuclear Technology Development Phase II (Final Report)

This limited scope study aims at preserving the results of experimental programs for the safety of light water cooled and advanced reactors by locating and documenting, to the extent possible, where the experimental test information for these programs has been archived. The Light Water Reactor Data Preservation Activity Team initially identified seven (7) experimental programs, exceeding the required five (5) in the scope of work, which were determined to be “at risk” of potentially losing valuable data. The seven (7) experimental programs/subject areas identified are (descriptions of each experiment/experience are provided in Section 3.0): 1. FERMI-1 Reactor Accident 2. Fission Product Behavior During the In-Pile Severe Fuel Damage Test SFD I-4 3. Containment Iodine Computer Code Exercise Based on Radioiodine Test Facility (RTF) Experiment 4. Wide Range Piping Integrity Demonstration (WIND) Project 5. Iodine Chemical Research in Canada 6. High Temperature Fission Product Chemistry and Transport in Steam 7. Anything related to radioactive Methyl Iodide.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Muons and seismic: a dynamic duo for the shallow subsurface?

This paper explores, at a preliminary level, the possibility of merging seismic data, both active and passive, with density constraints inferred from muon measurements. We focus on a theoretical analysis but note that muon experiments are ongoing to test model predictions with experimental data.

58 GEOSCIENCES↗
DOE OSTI2017

Altona Well Field 222Rn Data

Field data and 222Rn activities from the Altona well field. 222Rn, the most stable isotope of radon, was tested for during well extraction experiments. Tracers were also tracked to monitor the well. Data include 222Rn activities and complimentary geochemical data for multiple field experiments as part of an EGS project.

222Rn↗
DOE OSTI2018

A Probe-Enabled Approach for the Selective Isolation and Characterization of Functionally Active Subpopulations in the Gut Microbiome

Increasing evidence has shown that microorganisms present in the mammalian gut have a major impact on the metabolism of xenobiotics – chemicals foreign to the body including drugs and environmental contaminants – either by modulating host metabolism or by transforming xenobiotics or their metabolites directly. Being able to predict these interactions will be critical to develop precision medicine strategies utilizing the gut microbiota. However, current knowledge of which microbes are responsible for a given activity is severely limited and is further complicated by the sheer diversity of gut microbes between individuals. Current approaches including metagenomic and metatranscriptomic analyses can only identify enzymes and organisms that have the potential to catalyze a specific reaction, but cannot determine if an enzyme is truly active within the gut. To identify the microorganisms that are directly responsible for an activity in the gut of an individual, new functional approaches are needed. Here, we present an activity-based probe (ABP) approach to define the microbial populations responsible for a specific xenobiotic metabolizing activity. We developed an ABP for β-glucuronidases, enzymes capable of reversing a major pathway in phase II metabolism that is responsible for xenobiotic elimination. Using this ABP, we covalently labelled active β-glucuronidases both in vitro and in bacterial cells in the mouse gut microbiota. Cells possessing β-glucuronidase activity were then fluorescently labeled, isolated using fluorescence-activated cell sorting (FACS), and identified by sequencing. We found that glucuronidase active bacteria in the murine gut are taxonomically diverse, and even within phyla the taxa displaying function are highly disparate. Perturbation of the gut microbiota with vancomycin decreased but did not eliminate β-glucuronidase activity, which corresponded to a shift in the β-glucuronidase active population. These data demonstrate that the metabolic activity of the gut microbiota can be plastic and that during perturbation, functional capacity may be maintained by phylogenetically disparate populations. This work highlights the utility of ABPs to identify currently unknown functional microbial subpopulations responsible for a specific activity of interest within the gut of an individual.

Whidbey, Christopher↗
DOE OSTI2014

DISENTANGLING PLANETS AND STELLAR ACTIVITY FOR GLIESE 667C

Gliese 667C is an M1.5V star with a multi-planet system, including planet candidates in the habitable zone. The exact number of planets in the system is unclear, because the existing radial velocity (RV) measurements are known to contain contributions from stellar magnetic activity. Following our analysis of Gliese 581, we have analyzed the effect of stellar activity on the HARPS/HARPS-TERRA RVs of GJ 667C, finding a significant RV-activity correlation when using the width (FWHM) of the HARPS cross-correlation function to trace the magnetic activity. When we correct for this correlation, we confirm the detections of the previously observed planets b and c in the system, while simultaneously ascribing the RV signal near 90 days ({sup p}lanet d{sup )} to an artifact of the stellar rotation. We are unable to confirm the existence of the additional RV periodicities described in Anglada-Escudé et al. in our activity-corrected data.

79 ASTRONOMY AND ASTROPHYSICS↗