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At least 991 records · Page 55

Data for Application of Time-Domain 1H NMR for Investigating Dynamics of Vegetative Lipids in Bioenergy Crops at Different Developmental Stages

Sweet sorghum is typically cultivated for the food and fodder market. Recently, sweet sorghum varieties are being metabolically transitioned to enhance energy density by accumulating oil droplets in their vegetative tissues for bioenergy applications. Owing to the high biomass yield of sorghum, the transgenic lines can compete with oil-seed crops for biodiesel yield per unit area. In the initial phase of transgenic development, a high-throughput phenotyping method can bridge the gap between the production pipeline and analysis to improve the efficiency of the process. To meet the requirement, the present study extends the application of time-domain 1H-NMR spectroscopy for rapid quantification and characterization of the total in-situ lipids of sweet sorghum ‘ramada’ to lay the groundwork for analyzing the upcoming large quantity of transgenic samples. NMR technology has been successfully established for analyzing lipid contents of vegetative tissues of non-transgenic variety. The multiexponential analysis of spin-lattice (T1) relaxation spectra obtained from TD-NMR aided the investigation of the dynamics of the free and bound lipid fraction with plant development. The total lipid concentration of bagasse and leaves of non-transgenic sweet sorghum remained unchanged throughout the plant development. Leaves displayed a higher percentage of bound lipids as compared to bagasse. A significant variation in the lipid concentration of juice was observed at the different growth stages with a maximum lipid accumulation of 1.21 ± 0.04% w/w at the boot stage that decreased with further maturity of the plant.

Biomass Analytics↗

HL-LHC Analysis With ROOT: ROOT Project Input to the HL-LHC Computing Review (Stage 2)

ROOT is high energy physics' software for storing and mining data in a statistically sound way, to publish results with scientific graphics. It is evolving since 25 years, now providing the storage format for more than one exabyte of data; virtually all high energy physics experiments use ROOT. With another significant increase in the amount of data to be handled scheduled to arrive in 2027, ROOT is preparing for a massive upgrade of its core ingredients. As part of a review of crucial software for high energy physics, the ROOT team has documented its R&D plans for the coming years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Aerodynamic performance of axial-flow fan stage operated at nine inlet guide vane angles

The overall performance of a fan stage with nine inlet guide vane angle settings is presented. These data were obtained over the stable flow range at speeds from 60 to 120 percent of design for vane setting angles from -25 to 42.5 degrees. At design speed and design inlet guide vane angle, the stage has a peak efficiency of 0.892 at a pressure ratio of 1.322 and a flow of 25.31 kg/s. The stall margin based on peak efficiency and stall was 20 percent. Based on an operating line passing through the peak efficiency point at the design setting angle, the useful operating range of the stage at design speed is limited by stall at the positive setting angles and by choke at the negative angles. At design the calculated static thrust along the operating line varied from 68 to 114 percent of that obtained at design setting angle.

Moore, R. D.↗

Learning-Based Real-Time Event Identification Using Rich Real PMU Data

A large-scale deployment of phasor measurement units (PMUs) that reveal the inherent physical laws of power systems from a data perspective enables an enhanced awareness of power system operation. However, the high-granularity and non-stationary nature of PMU data and imperfect data quality could bring great technical challenges for real-time system event identification. To address these challenges, this paper proposes a two-stage learning-based framework. In the first stage, a Markov transition field (MTF) algorithm is exploited to extract the latent data features by encoding temporal dependency and transition statistics of PMU data in graphs. Then, a spatial pyramid pooling (SPP)-aided convolutional neural network (CNN) is established to efficiently and accurately identify power events. The proposed method fully builds on and is also tested on a large real-world dataset from several tens of PMU sources (and the corresponding event logs), located across the U.S., with a time span of two consecutive years. We report the numerical results validate that our method has high identification accuracy while showing good robustness against poor data quality.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Space-Based Range

Space-Based Range (SBR), previously known as Space-Based Telemetry and Range Safety (STARS), is a multicenter NASA proof-of-concept project to determine if space-based communications using NASA's Tracking and Data Relay Satellite System (TDRSS) can support the Range Safety functions of acquiring tracking data and generating flight termination signals, while also providing broadband Range User data such as voice, video, and vehicle/payload data. There was a successful test of the Range Safety system at Wallops Flight Facility (WFF) on December 20, 2005, on a two-stage Terrier-Orion spin-stabilized sounding rocket. SBR transmitted GPS tracking data and maintained links with two TDRSS satellites simultaneously during the 10-min flight. The payload section deployed a parachute, landed in the Atlantic Ocean about 90 miles downrange from the launch site, and was successfully recovered. During the Terrier-Orion tests flights, more than 99 percent of all forward commands and more than 95 percent of all return frames were successfully received and processed. The time latency necessary for a command to travel from WFF over landlines to White Sands Complex and then to the vehicle via TDRSS, be processed onboard, and then be sent back to WFF was between 1.0 s and 1.1 s. The forward-link margins for TDRS-10 (TDRS East [TDE]) were 11 dB to 12 dB plus or minus 2 dB, and for TDRS-4 (TDRS Spare [TDS]) were 9 dB to 10 dB plus or minus 1.5 dB. The return-link margins for both TDE and TDS were 6 dB to 8 dB plus or minus 3 dB. There were 11 flights on an F-15B at Dryden Flight Research Center (DFRC) between November 2006 and February 2007. The Range User system tested a 184-element TDRSS Ku-band (15 GHz) phased-array antenna with data rates of 5 Mbps and 10 Mbps. This data was a combination of black-and-white cockpit video, Range Safety tracking and transceiver data, and aircraft and antenna controller data streams. IP data formatting was used.

Source record↗

Influence of Data Acquisition Algorithms on X-ray Phase Contrast Imaging Computed Tomography

X-ray phase contrast imaging (XPCI) is a non-destructive evaluation technique that enables high-contrast detection of low-attenuation materials that are largely transparent in traditional radiography. Extending a grating based Talbot-Lau XPCI system to three- dimensional imaging with computed tomography (CT) imposes two motion requirements: the analyzer grating must translate transverse to the optical axis to capture image sets for XPCI reconstruction, and the sample must rotate to capture angular data for CT reconstruction. The acquisition algorithm choice determines the order of movement and positioning of the two stages. The choice of image acquisition algorithm for XPCI CT is instrumental to collecting high fidelity data for reconstruction. We investigate how data acquisition influences XPCI CT by comparing two simple data acquisition algorithms and determine that capturing a full phase-stepping image set for a CT projection before rotating the sample results in higher quality data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An Integral Study of Galactic Black Hole States

XTE 51550-564 was clearly detected with INTEGRAL out to 600 keV with the SPI, and is one of only two sources detected with IBISPICSIT. Software difficulties in analyzing the data prevented us from progressing with the analysis past the most elementary stages (see last year's report). The support from the INTEGRAL help desk has been very disappointing. People affiliated with INTEGRAL published a paper on the results of our data before we could master the reduction and analysis software. We are not the only group that got stuck with the analysis without adequate support from the INTEGRAL help desk. This was a rather disappointing experience as we lost many months of valuable time and efforts.

Source record↗

Combining Multi-Faceted Laboratory Studies of 74001-2 and Regional Remote Sensing to Address How Pyroclastic Eruptions Record and Affect the Lunar Volatile Budget

Basaltic magmatism is an efficient process for bringing volatiles from a planetary interior to its surface, with the possibility of generation of a transient lunar atmosphere as abundant volcanic materials de-gassed. However, pyroclastic deposits are locations where trapped gases may be studied [e.g., 2,3]. Volatile-rich pyroclastic deposits occur over a wide surface area of the Moon, indicating that the transport of volatiles and associated pyroclastic materials from the Moon’s mantle to the surface was a wide-spread phenomenon. Numerous studies analyzing remotely sensed data and using empirical modeling have demonstrated that various stages of pyroclastic eruptions significantly influence gas release patterns, morphology, and mineralogy of the deposit. Many observations based on mare basalts and pyroclastic deposits have identified potential histories of gas release [e.g., 2-10] and their influence on volatiles and their stable isotopes [e.g., 11-13]. The best representation of these pyroclastic deposits in the sample collection is core sample 74001-74002 that was collected during the Apollo 17 mission to the Taurus-Littrow Valley (TLV). The double drive tube penetrated a part of a regional-scale pyroclastic deposit and sampled approximately 68.1 cm of that deposit in the TLV. Remnants of this and other pyroclastic depos-its are represented throughout and beyond the TLV [e.g., 14-16]. The stratigraphy of this core has been investigated and defined by numerous studies. The CASA Moon SSERVI research team is conducting a multi-faceted analytical study of this deposit. Data generated from revisiting the stratigraphy of 74001-74002 will be used to place stable isotopes (H, B, Cl, S, Zn, Cu, Rb, Ga, Pb), Ar-Ar and U-Pb chronology, geochemistry, nanometer-scale observations of mineral surfaces, orbital observations, and experiments and modeling within a stratigraphic, eruptive, and geologic context. It is important to place these data into such a context. For example, recent S isotope measurements reported by Dottin et al. show differences within this core that may be related to either changes in source or eruptive process over the course of the eruption (vs. multiple eruptions). A fuller understanding of the stratigraphy is fundamental to resolving this interpretation. This comprehensive approach can only be achieved within the context of a program such as SSERVI. In addition, imaging produced in this project will be incorporated into a citizen scientist program to further identify many of the textural features of this double drive tube.

SSERVI↗

HydroGEN and H2NEW Data Hub

HydroGEN is a multi-lab consortium focused on early-stage R&D in H2 production, supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), Hydrogen and Fuel Cell Technologies Office (HFTO). The consortium advances research and development (R&D) of innovative materials for advanced water splitting (AWS) technologies to enable clean, sustainable and low-cost ($1/kg H2) hydrogen production and fosters cross-cutting innovation using theory-guided applied materials R&D to advance all emerging water-splitting pathways for hydrogen production. Hydrogen from Next-generation Electrolyzers of Water (H2NEW) is a consortium of nine U.S. Department of Energy (DOE) national laboratories focused on making large-scale electrolyzers, which produce hydrogen from electricity and water, more durable, efficient, and affordable. The presentation introduces the HydroGEN data hub to the H2NEW consortium and encourages H2NEW members to use it to store and share data with team members and eventually the public. The two consortia share this data hub.

advanced water splitting technologies↗

A Scalable PDC Placement Technique for Fast and Resilient Monitoring of Large Power Grids

The wide-area measurement system (WAMS) is a key enabler of real-time monitoring of power grids. The essential goals of WAMS design are fast and resilient data transfer from phasor measurement units (PMU) to phasor data concentrators (PDC). We propose a scalable two-stage PDC placement technique for minimizing the end-to-end delay while maintaining resiliency. In the prescreening stage, the plausible candidates of PDC configurations are identified based on a graph theory-based multi-median function (MMF). Here, in this article, a computationally efficient meta-heuristic algorithm is used to address scalability. In the candidate selection stage, two different algorithms, namely, Suurballe's and Dijkstra's, are employed to identify the best of those plausible PDC configurations as the final design. This technique not only minimizes the hop paths between PMUs and PDCs, but also ensures network resiliency against single PMU, PDC, or communication link failure by incorporating the roles of PMUs in power grid observability into routing policy. Simulation results on the IEEE 57-bus test power system and the 2000-bus test power system demonstrate the effectiveness and scalability of the proposed technique.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Trapped Waves and Screech Tones With Various Rectangular Nozzles

This report documents experimental observations made on ‘trapped waves’ occurring with various convergent, rectangular nozzles. Most of the data pertain to three nozzles of aspect ratios (AR) 2, 4 and 8, each having an equivalent diameter of 2.12 in. The trapped waves, manifesting as a series of peaks in the near field pressure fluctuation spectra, are seen with all three nozzles. The number of spectral peaks detected on the major axis is larger than that detected on the minor axis by a factor approximately equal to the AR. These spectral peaks occur in high subsonic conditions and persist into the supersonic regime. Screech tones seem to appear as a continuation of these spectral peaks, i.e., with increasing Mach number it is as if one of these peaks gets amplified and turns into the screech tone. This trend is clearer at smaller AR and gets somewhat obscured at higher AR. Screech frequency variation with Mach number is documented for these and other rectangular nozzles, covering an AR range of 1-16. For larger AR (≥ 3), screech frequency is found to scale on the narrow dimension of the nozzle. Screech staging behavior is more pronounced for smaller AR cases. The screech frequency data for the AR=1 (square) case involves multiple stages similar to that of a round nozzle.

nozzles↗

Multistage Turbomachinery Flows Simulated Numerically

At the NASA Lewis Research Center, a comprehensive assessment was made of the predictive capability of the average passage flow model as applied to multistage axial-flow compressors. This model, which describes the time-averaged flow field within a typical passage of a blade row embedded in a multistage configuration, is being widely used throughout U.S. aircraft industry as an integral part of their design systems. Rotor flow-angle deviation. In this work, detailed data taken within a four and one-half stage large low-speed compressor were used to assess the weaknesses and strengths of the predictive capabilities of the average passage flow model. The low-speed compressor blading is of modern design and employs stator end-bends. Measurements were made with slow- and high response instrumentation. The high-response measurements revealed the velocity components of both the rotor and stator wakes. From the measured wake profiles, we found that the flow exiting the rotors deviated from the rotor exit metal angle to a lesser degree than was predicted by the average passage flow model. This was found to be due to blade boundary layer transition, which recently has been shown to exist on multistage axial compressor rotor and stator blades, but was not accounted for in the average passage model. Consequently, a model that mimics the effects of blade boundary layer transition, Shih k-epsilon model, was incorporated into the average passage model. Simulations that incorporated this transition model showed a dramatic improvement in agreement with data. The altered model thus improved predictive capability for multistage axial-flow compressors, and this was verified by detailed experimental measurement.

Hathaway, Michael D.↗

Mechanism of Microseismic Generation During Hydraulic Fracturing - With Evidence From HFTS 2 Observations

The objective of this study is to understand how microseismic events are generated during hydraulic fracturing, as well as the role of geomechanical conditions (i.e., stress and mechanical stratigraphy) in this process. In the industry, microseismic event clouds have been generally used as an “outer-boundary” of the “stimulated reservoir volume” (SRV). However, by comparing with other surveillance data (Low frequency Distributed Acoustic Sensing, or LF-DAS strain) in the Hydraulic Fracturing Test Site (HFTS) 2 experiment, we show that this assumption is fundamentally flawed. The HFTS 2 data has three unique observations that have not been commonly observed in other datasets: 1. Due to influence of offset pad depletion, microseismic data shows that hydraulic fractures from the child well can propagate over 3000 feet into the depleted low stress zone. 2. By comparing microseismic and horizontal fiber LF-DAS strain data, we observe that microseismic event cloud does not necessarily reflect the created hydraulic fracture volume. Particularly, the extent of microseismic event clouds near heel stages are much shorter than what is shown with LF-DAS strain data. 3. Microseismic event magnitudes are larger in the depleted regions. Through geomechanical analysis, we demonstrate that the “bedding-plane-slip” model is likely the mechanism for microseismic generation during hydraulic fracturing. Furthermore, this model successfully explains the above field observations from HFTS 2 experiment. We also provide a quantitative relationship connecting the microseismic event magnitude with fracture width increment and layer mechanical property contrast.

58 GEOSCIENCES↗

A High-Throughput Computing Infrastructure to Generate Custom, Open Community Geothermal Datasets

The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.

15 GEOTHERMAL ENERGY↗

Incremental Parallelization of Non-Data-Parallel Programs Using the Charon Message-Passing Library

Message passing is among the most popular techniques for parallelizing scientific programs on distributed-memory architectures. The reasons for its success are wide availability (MPI), efficiency, and full tuning control provided to the programmer. A major drawback, however, is that incremental parallelization, as offered by compiler directives, is not generally possible, because all data structures have to be changed throughout the program simultaneously. Charon remedies this situation through mappings between distributed and non-distributed data. It allows breaking up the parallelization into small steps, guaranteeing correctness at every stage. Several tools are available to help convert legacy codes into high-performance message-passing programs. They usually target data-parallel applications, whose loops carrying most of the work can be distributed among all processors without much dependency analysis. Others do a full dependency analysis and then convert the code virtually automatically. Even more toolkits are available that aid construction from scratch of message passing programs. None, however, allows piecemeal translation of codes with complex data dependencies (i.e. non-data-parallel programs) into message passing codes. The Charon library (available in both C and Fortran) provides incremental parallelization capabilities by linking legacy code arrays with distributed arrays. During the conversion process, non-distributed and distributed arrays exist side by side, and simple mapping functions allow the programmer to switch between the two in any location in the program. Charon also provides wrapper functions that leave the structure of the legacy code intact, but that allow execution on truly distributed data. Finally, the library provides a rich set of communication functions that support virtually all patterns of remote data demands in realistic structured grid scientific programs, including transposition, nearest-neighbor communication, pipelining, gather/scatter, and redistribution. At the end of the conversion process most intermediate Charon function calls will have been removed, the non-distributed arrays will have been deleted, and virtually the only remaining Charon functions calls are the high-level, highly optimized communications. Distribution of the data is under complete control of the programmer, although a wide range of useful distributions is easily available through predefined functions. A crucial aspect of the library is that it does not allocate space for distributed arrays, but accepts programmer-specified memory. This has two major consequences. First, codes parallelized using Charon do not suffer from encapsulation; user data is always directly accessible. This provides high efficiency, and also retains the possibility of using message passing directly for highly irregular communications. Second, non-distributed arrays can be interpreted as (trivial) distributions in the Charon sense, which allows them to be mapped to truly distributed arrays, and vice versa. This is the mechanism that enables incremental parallelization. In this paper we provide a brief introduction of the library and then focus on the actual steps in the parallelization process, using some representative examples from, among others, the NAS Parallel Benchmarks. We show how a complicated two-dimensional pipeline-the prototypical non-data-parallel algorithm- can be constructed with ease. To demonstrate the flexibility of the library, we give examples of the stepwise, efficient parallel implementation of nonlocal boundary conditions common in aircraft simulations, as well as the construction of the sequence of grids required for multigrid.

VanderWijngaart, Rob F.↗

Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations: China 2004-2013

Three decades of rapid economic development is causing severe and widespread PM2.5(particulate matter (is) less than 2.5 ) pollution in China. However, research on the health impacts of PM2.5 exposure has been hindered by limited historical PM2.5 concentration data. We estimated ambient PM2.5 concentrations from 2004 to 2013 in China at 0.1 deg resolution using the most recent satellite data and evaluated model performance with available ground observations. We developed a two-stage spatial statistical model using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) and assimilated meteorology, land use data, and PM2.5 concentrations from China's recently established ground monitoring network. An inverse variance weighting (IVW) approach was developed to combine MODIS Dark Target and Deep Blue AOD to optimize data coverage. We evaluated model predicted PM2.5 concentrations from 2004 to early 2014 using ground observations. The overall model cross-validation R(sup 2) and relative prediction error were 0.79 and 35.6%, respectively. Validation beyond the model year (2013) indicated that it accurately predicted PM(sub 2.5) concentrations with little bias at the monthly (R(sup 2) = 0.73), regression slope = 0.91) and seasonal (R(sup 2) = 0.79), regression slope = 0.92) levels. Seasonal variations revealed that winter was the most polluted season and that summer was the cleanest season. Analysis of predicted PM2.5 levels showed a mean annual increase of 1.97 micro-g/cu cm between 2004 and 2007 and a decrease of 0.46 micro-g/cu cm between 2008 and 2013. Our satellite-driven model can provide reliable historical PM2.5 estimates in China at a resolution comparable to those used in epidemiologic studies on the health effects of long-term PM2.5 exposure in North America. This data source can potentially advance research on PM2.5 health effects in China.

satellite remote sensing↗

Modeling performance of data collection systems for high-energy physics

Exponential increases in scientific experimental data are outpacing silicon technology progress, necessitating heterogeneous computing systems—particularly those utilizing machine learning (ML)—to meet future scientific computing demands. The growing importance and complexity of heterogeneous computing systems require systematic modeling to understand and predict the effective roles for ML. We present a model that addresses this need by framing the key aspects of data collection pipelines and constraints and combining them with the important vectors of technology that shape alternatives, computing metrics that allow complex alternatives to be compared. For instance, a data collection pipeline may be characterized by parameters such as sensor sampling rates and the overall relevancy of retrieved samples. Alternatives to this pipeline are enabled by development vectors including ML, parallelization, advancing CMOS, and neuromorphic computing. By calculating metrics for each alternative such as overall F1 score, power, hardware cost, and energy expended per relevant sample, our model allows alternative data collection systems to be rigorously compared. We apply this model to the Compact Muon Solenoid experiment and its planned high luminosity-large hadron collider upgrade, evaluating novel technologies for the data acquisition system (DAQ), including ML-based filtering and parallelized software. The results demonstrate that improvements to early DAQ stages significantly reduce resources required later, with a power reduction of 60% and increased relevant data retrieval per unit power (from 0.065 to 0.31 samples/kJ). However, we predict that further advances will be required in order to meet overall power and cost constraints for the DAQ.

Olin-Ammentorp, Wilkie (ORCID:0000000224729862)↗