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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Analysis and methodology for measuring oxygen concentration in liquid sodium with a plugging meter

Oxygen concentration in liquid sodium is a critical measurement in assessing the potential for corrosion damage in sodium-cooled fast reactors (SFRs). There has been little recent work on sodium reactors and oxygen detection. Thus, the technical expertise dealing with oxygen measurements within sodium is no longer readily available in the U.S. Two methods of oxygen detection that have been investigated are the plugging meter and the galvanic cell. One of the overall goals of the Univ. of Wisconsin's sodium research program is to develop an affordable, reliable galvanic cell oxygen sensor. Accordingly, attention must first be dedicated to a well-known standard known as a plugging meter. Therefore, a sodium loop has been constructed on campus in effort to develop the plugging meter technique and gain experience working with liquid metal. The loop contains both a galvanic cell test section and a plugging meter test section. Consistent plugging results have been achieved below 20 [wppm], and a detailed process for achieving effective plugging has been developed. This paper will focus both on an accurate methodology to obtain oxygen concentrations from a plugging meter, and on how to easily control the oxygen concentration of sodium in a test loop. Details of the design, materials, manufacturing, and operation will be presented. Data interpretation will also be discussed, since a modern discussion of plugging data interpretation does not currently exist. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Aging Infrastructure: Application of System Health Monitoring at the Defense Waste Processing Facility - 16069

The disposition of high level waste (HLW) into borosilicate glass canistered waste forms began at SRS in 1996. Since that time, the Defense Waste Processing Facility (DWPF) has produced nearly four thousand HLW canisters. The DWPF is now approaching 20 years of radioactive service and 25 years of operation since the commencement of nonradioactive testing in 1990. Many facility systems are challenged by equipment or component obsolescence, which places a premium on proper work planning, engineering, and maintenance resource allocation to ensure facility reliability. To this end, Savannah River Remediation (SRR) implements programs and procedures for performance monitoring of structures, systems, and components (SSCs) within all of its processing facilities. As these programs have matured, they have helped to identify vulnerabilities within facility systems and provided a framework for ranking system assets to ensure correct priority is established and maintained. This paper provides an overview of how SRR structures and implements system performance monitoring with specific focus on the recent replacement of the DWPF Safety Grade Purge Flowmeters. This case study will discuss: 1) How the performance monitoring process identified an availability risk due to the minimal vendor support for the in-use flow transmitters, 2) The design changes developed as part of the project to transition to a different measurement technology, which includes operational lessons learned from the original installation, 3) The execution of the replacement effort, which was complicated by the fact that the purge system is a Vital Safety System (VSS) and not easily taken out of service for extended maintenance, and 4) The need to consider future maintainability, particularly given that continued acceleration in technical innovation will likely increase the frequency of equipment obsolescence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Algorithmic Improvements for Portable Event-Based Monte Carlo Transport Using the Nvidia Thrust Library

High performance computing environments are progressively moving towards many-core computing architectures. The Los Alamos National Laboratory Trinity machine, available in late 2016, will use both Intel Xeon Haswell processors and Intel Xeon Phi Knights Landing many integrated core (MIC) coprocessors. The Lawrence Livermore National Laboratory Sierra machine, available in 2018, will use an IBM PowerPC architecture along with Nvidia graphics processing units (GPUs). Applications that must work in this supercomputing environment must continue to adapt in order to take advantage of the diverse hardware architectures that are coming. A significant consideration is not only the performance of the application on a given platform but also the portability of the application to other platforms. The algorithmic improvements presented in this paper build upon recently-reported work on event-based Monte Carlo transport in the ALPSMC code that models particle transport in one-dimensional binary stochastic media. That paper discussed the lack of available vectorization in the traditional history-based algorithm used for Monte Carlo transport and presented a data parallel event-based algorithm implemented using the Nvidia Thrust library for portability. The performance of the data parallel event-based algorithm implemented using Thrust was compared to a native CUDA implementation. The conclusions from that work were that the Thrust library abstraction technique caused too significant a loss in performance but that the event-based method was a viable option that should be further investigated. In this paper, we describe algorithmic improvements to the data parallel event-based algorithm previously presented. We made further algorithmic optimizations to the event-based CUDA implementation, most notably: data structure changes, a new conditional particle removal scheme in the event-based process, and the use of multiple GPUs. In addition to improvements to the algorithm, we re-implemented the Thrust version from the now further optimized CUDA version, giving a greater chance for success at a performant abstraction. Finally, we revisited our previous assumptions about the inability of the history-based method to achieve performance on vector style architectures such as the MICs and GPUs, with surprising and promising results. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

The energy level alignment at metal–molecule interfaces using Wannier–Koopmans method

We apply a recently developed Wannier-Koopmans method (WKM), based on density functional theory (DFT), to calculate the electronic energy level alignment at an interface between a molecule and metal substrate. We consider two systems: benzenediamine on Au (111), and a bipyridine-Au molecular junction. The WKM calculated level alignment agrees well with the experimental measurements where available, as well as previous GW and DFT + Σ results. These results suggest that the WKM is a general approach that can be used to correct DFT eigenvalue errors, not only in bulk semiconductors and isolated molecules, but also in hybrid interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Prediction of histone post-translational modifications using deep learning

Abstract Motivation Histone post-translational modifications (PTMs) are involved in a variety of essential regulatory processes in the cell, including transcription control. Recent studies have shown that histone PTMs can be accurately predicted from the knowledge of transcription factor binding or DNase hypersensitivity data. Similarly, it has been shown that one can predict PTMs from the underlying DNA primary sequence. Results In this study, we introduce a deep learning architecture called DeepPTM for predicting histone PTMs from transcription factor binding data and the primary DNA sequence. Extensive experimental results show that our deep learning model outperforms the prediction accuracy of the model proposed in Benveniste et al. (PNAS 2014) and DeepHistone (BMC Genomics 2019). The competitive advantage of our framework lies in the synergistic use of deep learning combined with an effective pre-processing step. Our classification framework has also enabled the discovery that the knowledge of a small subset of transcription factors (which are histone-PTM and cell-type-specific) can provide almost the same prediction accuracy that can be obtained using all the transcription factors data. Availabilityand implementation https://github.com/dDipankar/DeepPTM. Supplementary information Supplementary data are available at Bioinformatics online.

Baisya, Dipankar Ranjan (ORCID:0000000267847359)↗
DOE OSTI2012

Solid State Marx Modulators for Emerging Applications

Emerging linear accelerator applications increasingly push the boundaries of RF system performance and economics. The power modulator is an integral part of RF systems whose characteristics play a key role in the determining parameters such as efficiency, footprint, cost, stability, and availability. Particularly within the past decade, solid-state switch based modulators have become the standard in high-performance, high power modulators. One topology, the Marx modulator, has characteristics which make it particularly attractive for several emerging applications. This paper is an overview of the Marx topology, some recent developments, and a case study of how this architecture can be applied to a few proposed linear accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Evidence of a large-scale positive rotation–metallicity correlation in the Galactic thick disc

ABSTRACT This study is based on high quality astrometric and spectroscopic data from the most recent releases by Gaia and APOGEE. We select $58\, 882$ thin and thick disc red giants in the Galactocentric (cylindrical) distance range 5 < R < 13 kpc and within |$z$| < 3 kpc, for which full chemo-kinematical information is available. Radial chemical gradients, $\partial \rm {[M/H]} / \partial \rm {R}$, and rotational velocity–metallicity correlations, $\partial V_\phi / \partial \rm {[M/H]}$, are re-derived firmly uncovering that the thick disc velocity–metallicity correlation maintains its positiveness over the 8 kpc range explored. This observational result is important as it sets experimental constraints on recent theoretical studies on the formation and evolution of the Milky Way disc and on cosmological models of Galaxy formation.

Re Fiorentin, Paola↗
DOE OSTI2019

High-Performance Bi-2212 Round Wires Made With Recent Powders

Multifilamentary Bi 2 Sr 2 CaCu 2 O x (Bi-2212) wire made by the powder-in-tube technique is the only high-temperature superconductor made in the round shape preferred by magnet builders. The critical current density (J C ) of Bi-2212 round wire was improved significantly by the development of overpressure heat treatment in the past few years. Bi-2212 wire is commercially available in multiple architectures and kilometer-long pieces and is a very promising conductor for very high-field NMR and accelerator magnets. Here, we studied the effects of precursor powder and heat treatment conditions on the superconducting properties and microstructure of recent Bi-2212 wires. Short samples of recent wire with optimized overpressure processing showed J C (4.2 K, 15 T) = 6640 A/mm 2 and J C (4.2 K, 30 T) = 4670 A/mm 2 , which correspond to engineering critical current densities J E (4.2 K, 15 T) = 1320 A/mm 2 and J E (4.2 K, 30 T) = 930 A/mm 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2014

Proteogenomic strategies for identification of aberrant cancer peptides using large-scale Next Generation Sequencing data

Cancer is driven by the acquisition of somatic DNA lesions. Distinguishing the early driver mutations from subsequent passenger mutations is key to molecular sub-typing of cancers, and the discovery of novel biomarkers. The availability of genomics technologies (mainly wholegenome and exome sequencing, and transcript sampling via RNA-seq, collectively referred to as NGS) have fueled recent studies on somatic mutation discovery. However, the vision is challenged by the complexity, redundancy, and errors in genomic data, and the difficulty of investigating the proteome using only genomic approaches. Recently, combination of proteomic and genomic technologies are increasingly employed. However, the complexity and redundancy of NGS data remains a challenge for proteogenomics, and various trade-offs must be made to allow for the searches to take place. This paperprovides a discussion of two such trade-offs, relating to large database search, and FDR calculations, and their implication to cancer proteogenomics. Moreover, it extends and develops the idea of a unified genomic variant database that can be searched by any mass spectrometry sample. A total of 879 BAM files downloaded from TCGA repository were used to create a 4.34 GB unified FASTA database which contained 2,787,062 novel splice junctions, 38,464 deletions, 1105 insertions, and 182,302 substitutions. Proteomic data from a single ovarian carcinoma sample (439,858 spectra) was searched against the database. By applying the most conservative FDR measure, we have identified 524 novel peptides and 65,578 known peptides at 1% FDR threshold. The novel peptides include interesting examples of doubly mutated peptides, frame-shifts, and non-sample-recruited mutations, which emphasize the strength of our approach.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Investigation of the Mechanical Properties of GdBa{sub 2}Cu{sub 3}O{sub 7−δ} Added with Nanosized Ferrites ZnFe{sub 2}O{sub 4} and CoFe{sub 2}O{sub 4} Using Ultrasonic Measurement

Recently, there is much interest in studying the effect of nanosized ferrites addition on high- T{sub c} superconductors. However, little information is available on the mechanical properties. We have investigated the effect of (CoFe{sub 2}O{sub 4}){sub x} and (ZnFe{sub 2}O{sub 4}){sub x} nanosized ferrites with 0.01 ≤ x ≤ 0.40 on the mechanical properties of the high- T{sub c} superconducting compound GdBa{sub 2}Cu{sub 3}O{sub 7−δ} (Gd-123) prepared by the conventional solid-state reaction technique. Elastic parameters including shear modulus (G), bulk modulus (B), and Young’s modulus (E) of all samples were inspected using ultrasonic measurements and compared with Vickers microhardness results. Furthermore, the porosity of the samples was investigated and correlated to Young’s modulus, which was corrected to zero porosity using different models. The corrected values were correlated with Vickers microhardness. Moreover, the Debye temperature (θ{sub D}) and the electron-phonon coupling factor (λ) were also determined as a function of x. We observed that the different nanoparticles addition has influenced the Gd-123 compound differently. For (ZnFe{sub 2}O{sub 4}){sub x} added samples, the mechanical properties and Debye temperature improved up to x = 0.06, then deteriorated with further addition. However, (CoFe{sub 2}O{sub 4}){sub x} addition improved the mechanical properties for all samples with x up to 0.40. We found that the proportionality constant between the corrected values of E and H{sub v} and G and H{sub v} are strongly dependent on the porosity corrections and the kind of superconducting material. This indicates that the widely used formula E = 81.96 H{sub v} may not be valid for all types of superconducting materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Early season prediction of within-field crop yield variability by assimilating CubeSat data into a crop model

Accurate early season predictions of crop yield at the within-field scale can be used to address a range of crop production, management, and precision agricultural challenges. While the remote sensing of within-field insights has been a research goal for many years, it is only recently that observations with the required spatio-temporal resolutions, together with efficient assimilation methods to integrate these into modeling frameworks, have become available to advance yield prediction efforts. Here we explore a yield prediction approach that combines daily high-resolution CubeSat imagery with the APSIM crop model. The approach employs APSIM to train a linear regression that relates simulated yield to simulated leaf area index (LAI). That relationship is then used to identify the optimal regression date at which the LAI provides the best prediction of yield: in this case, approximately 14 weeks prior to harvest. Instead of applying the regression on satellite imagery that is coincident, or closest to, the regression date, our method implements a particle filter that integrates CubeSat-based LAI into APSIM to provide end-of-season high-resolution (3 m) yield maps weeks before the optimal regression date. The approach is demonstrated on a rainfed maize field located in Nebraska, USA, where suitable collections of both imagery and in-situ data were available for assessment. The procedure does not require in-field data to calibrate the regression model, with results showing that even with a single assimilation step, it is possible to provide yield estimates with good accuracy up to 21 days before the optimal regression date. Yield spatial variability was reproduced reasonably well, with a strong correlation to independently collected measurements (R 2 = 0.73 and rRMSE = 12%). When the field averaged yield was compared, our approach reduced yield prediction error from 1 Mg/ha (control case based on a calibrated APSIM model), to 0.5 Mg/ha (using satellite imagery alone), and then to 0.2 Mg/ha (results with assimilation up to three weeks prior to the optimal regression date). Such a capacity to provide spatially explicit yield predictions early in the season has considerable potential to enhance digital agricultural goals and improve end-of-season yield predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Thermodynamic Modeling and Experimental Study of the Fe-Cr-Zr System

Wide applications of zircaloys, stainless steels and their interactions in nuclear reactors require the knowledge on phase stability and thermodynamic property of the Fe-Cr-Zr system. This knowledge is also important to develop new Zr-contained Fe-Cr ferritic steels. This work aims at developing thermodynamic models for describing phase stability and thermodynamic property of the Fe-Cr-Zr system using the Calphad approach coupled with experimental study. Thermodynamic descriptions of the Fe-Cr and Cr-Zr systems were either directly adopted or slightly modified from literature. The Fe-Zr system has been remodeled to accommodate recent ab-initio calculation of formation enthalpies of various Fe-Zr compounds. Reliable ternary experimental data and thermodynamic models were mainly available in the Zr-rich region. Therefore, selected ternary alloys located in the vicinity of the eutectic valley of (Fe,Cr,Zr) and (Fe,Cr)2Zr laves phase in the Fe-rich region have been experimentally investigated in this study. Microstructure has been examined by using scanning electron microscope, energy-dispersive Xray spectroscopy and X-ray diffraction. These experimental results, along with the literature data were then used to develop thermodynamic models for phases in the Fe-Cr-Zr system. Calculated phase equilibria and thermodynamic properties of the ternary system yield satisfactory agreements with available experimental data, which gives the confidence to use these models as building blocks for developing a Zr, Fe and Cr contained multicomponent thermodynamic database for broader applications in nuclear reactors.

Yang, Ying↗
DOE OSTI2022

Constraining baryon annihilation in the hadronic phase of heavy-ion collisions via event-by-event fluctuations

We point out that the variance of net-baryon distribution normalized by the Skellam distribution baseline, κ 2 [$B-\overline{B}$]/$\langle B+\overline{B} \rangle$, is sensitive to the possible modification of (anti)baryon yields due to $B\overline{B}$ annihilation in the hadronic phase. The corresponding measurements can thus place stringent limits on the magnitude of the $B\overline{B}$ annihilation and its inverse reaction. We perform Monte Carlo simulations of the hadronic phase in Pb-Pb collisions at the LHC via the recently developed subensemble sampler + UrQMD afterburner and show that the effect survives in net-proton fluctuations, which are directly accessible experimentally. The available experimental data of the ALICE Collaboration on net-proton fluctuations disfavors a notable suppression of (anti)baryon yields in $B\overline{B}$ annihilations predicted by the present version of UrQMD if only global baryon conservation is incorporated. On the other hand, the annihilations improve the data description when local baryon conservation is imposed. The two effects can be disentangled by measuring κ 2 [$B-\overline{B}$]/$\langle B+\overline{B} \rangle$, which at the LHC is notably suppressed by annihilations but virtually unaffected by baryon number conservation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Toward the Minimal Floating Operation Count Cholesky Decomposition of Electron Repulsion Integrals

As quantum chemistry calculations deal with molecular systems of increasing size, the memory requirement to store electron-repulsion integrals (ERIs) greatly outpaces the physical memory available in computing hardware. Here, the Cholesky decomposition of ERIs provides a convenient yet accurate technique to reduce the storage requirement of integrals. Recent developments of a two-step algorithm have drastically reduced the memory operation (MOP) count, leaving the floating operation (FLOP) count as the last frontier of cost reduction in the Cholesky ERI algorithm. In this report, we introduce a dynamic integral tracking, reusing, and compression/elimination protocol embedded in the two-step Cholesky ERI method. Benchmark studies suggest that this technique becomes particularly advantageous when the basis set consists of many computationally expensive high-angular-momentum basis functions. With this dynamic ERI improvement, the Cholesky ERI approach proves to be a highly efficient algorithm with minimal FLOP and MOP count.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Development of a Thermophysical Properties Model for Flowsheet Simulation of Biomass Pyrolysis Processes

A properties model was developed for use in commercial process simulators to model pyrolysis of lignocellulosic biomass. The component list was chosen to enable process simulations based on a recently published lumped pyrolysis kinetics model. Since many of the compounds involved in pyrolysis are not found in simulator databanks, estimation based on available literature data was used to establish missing parameters. Standard solid enthalpy of formation, solid heat capacity, and solid density estimates calculated from the limited experimental data available were prepared for six biomass constituents and nine intermediate and end-products of their pyrolysis. Ideal gas enthalpy of formation and heat capacity, critical property, and vapor pressure estimates were prepared for another four pyrolysis end-products and one biomass component. The estimates were all validated against the closest available experimental data in the literature. The addition of these new components and properties allows thermodynamically rigorous simulation of lumped biomass pyrolysis reactions with accurate energy balances. Furthermore enthalpies of reaction calculated from the properties model were compared with reported reaction enthalpies for the same lumped biomass pyrolysis reactions and found to be in general agreement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Measurement of irradiation effects in precipitate hardened aluminum using nonlinear ultrasonic principles (in-situ)

Currently nuclear power plants are reaching the end of their initial design life. Yet, in order to meet the energy demands, twenty year extensions have been granted to many nuclear reactor facilities. These extensions will be ending by the year 2035, leaving a large gap in the available energy supply. In order to extend the life of these facilities it will imperative to develop techniques capable detecting damage in the aging nuclear facilities. However, the high temperature and high neutron flux environment limits the materials available for use in the nuclear reactor. Because of this limitation little NDE based inspection has been implemented in high radiation environments. Yet recent developments in the understanding of Aluminum Nitride (AlN) piezoelectric sensors high temperature and radiation dependent behavior have opened the door for in-situ experimentation. An experiment was designed to monitor the propagation of an ultrasonic wave in a precipitate hardened aluminum specimen while being subjected to radiation at the Pennsylvania State Universities Breazeale Reactor. Measurements of harmonic generation were made up to 1.85x10{sup 18} fluence with significant spectral difference between the pre-irradiated state and the post irradiated state. The connection between micro-structural material changes and harmonic measurements are addressed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Experimental analysis of a novel and low-cost pin photodiode dosimetry system for diagnostic radiology

Silicon PIN photodiode has recently found broad and exciting applications in the ionizing radiation dosimetry. In this study a compact and novel dosimetry system using a commercially available PIN photodiode (BPW34) has been experimentally tested for diagnostic radiology. The system was evaluated with clinical beams routinely used for diagnostic radiology and calibrated using a secondary reference standard. Measured dose with PIN photodiode (Air Kerma) varied from 10 to 430 μGy for tube voltages from 40 to 100 kVp and tube current from 0.4 to 40 mAs. The minimum detectable organ dose was estimated to be 10 μGy with 20% uncertainty. Results showed a linear correlation between the PIN photodiode readout and dose measured with standard dosimeters spanning doses received. The present dosimetry system having advantages of suitable sensitivity with immediate readout of dose values, low cost, and portability could be used as an alternative to passive dosimetry system such as thermoluminescent dosimeter for dose measurements in diagnostic radiology.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Crystallography of Reactive Intermediates

Metal–ligand (M–L) multiply bonded complexes hold a central place in inorganic chemistry and catalysis: From fundamental and historical perspectives, these species have played a critical role in the articulation of important bonding principles (i.e. the vanadyl ion in the development of molecular orbital theory); from a practical perspective, these species are critical intermediates in a variety of chemical reactions (i.e. N 2 and O 2 reduction, H 2 O oxidation, and C–H functionalization). For many high-valent, early metal complexes, overlap of ligand-based electrons with vacant π-symmetry orbitals leads to strong M–L multiple bonds. The stability of these species enables straightforward characterization with a suite of standard spectroscopic and diffraction-based experiments. Mid- and late-transition metal complexes, with attendant higher d-electron counts, often support more reactive M–L multiply bonded fragments. The reactivity of these species simultaneously renders them attractive intermediates for catalysis but challenging synthetic targets to observe and characterize. A number of important strategies have been advanced to enable experimental characterization of mid- to late-metal–ligand multiply bonded species. Synthetic manipulation of the coordination geometry and ligand donicity, as well as introduction of sterically encumbering ligands, have each emerged as powerful methods to tame the inherent reactivity of kinetically labile M–L multiple bonds. While these efforts have resulted in families of well-characterized complexes and provided critical insights regarding structure and bonding, the synthetic derivatization required to stabilize M–L fragments of interest often obviates the substrate functionalization activity relevant to catalysis. Photochemical synthesis of reactive species provides a conceptually attractive strategy to generate reactive M–L fragments under conditions compatible with time-resolved or cryogenic steady-state characterization, and photogeneration has enabled observation of a number of reactive M–L fragments. The suite of tools available to characterize photogenerated reactive species is often more limited than typical for kinetically stabilized complexes and structural characterization is typically not possible. Recently, photocrystallographic experiments, in which reactive M–L multiply bonded intermediates are generated within single-crystal matrices, have been advanced as a strategy to interrogate the structures of reactive intermediates in C–H functionalization. Lastly, this Comment describes the historical antecedents to these experiments, highlights examples of photocrystallographic characterization of reactive intermediates, and discusses future opportunities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗