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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Molecular Rhodium Complexes Supported on the Metal-Oxide-Like Nodes of Metal Organic Frameworks and on Zeolite HY: Catalysts for Ethylene Hydrogenation and Dimerization

Metal–organic frameworks (MOFs) with nodes consisting of zirconium oxide clusters (Zr 6 ) offer new opportunities as supports for catalysts with well-defined, essentially molecular, structures. We used the precursor Rh(C 2 H 4 ) 2 (acac) (acac is acetylacetonate) to anchor Rh(I) complexes to the nodes of the MOF UiO-67 and, for comparison, to the zeolite dealuminated HY (DAY). These were characterized experimentally by measurement of catalytic activities and selectivities for ethylene hydrogenation and dimerization in a once-through flow reactor at 298 K and 1 bar. The catalyst performance data are complemented with structural information determined by infrared and extended X-ray absorption fine structure spectroscopies and by calculations at the level of density functional theory, the latter carried out also to extend the investigation to a related MOF, NU-1000. The agreement between the experimental and calculated structural metrics is good, and the calculations have led to predictions of reaction mechanisms and associated energetics. Finally, the data demonstrate a correlation between the catalytic activity and selectivity and the electron-donor tendency of the supported rhodium (as measured by the frequencies of CO ligands bonded as probes to the Rh(I) centers), which is itself a measure of the electron-donor tendency of the support.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Hydrostatic temperature calculations

Comparisons are made between hydrostatically computed temperatures and ambient temperatures associated with nine different data sources, including analyses, forecasts and conventional observations. Five-day averages and the day-to-day variations in the root-mean-square temperature differences are presented. Several different numerical and interpolation procedures are examined. Error correction and a constrained optimum procedure that minimizes ambient minus calculated hydrostatic temperature differences are introduced. Systematic differences between ambient and hydrostatic temperatures are found to be associated with the sinoptic situation. When compared with ambient temperatures, hydrostatic temperatures at 500 mb tend to be too warm at or in front of a trough and too cold behind the trough. In the vertical direction, for the eight-level configuration tested, the average hydrostatic temperatures are too cold at low levels (850, 700 mb) and too warm at upper levels, (300, 250 mb).

Raymond, William H.↗
DOE OSTI2020

NNSS Soils Monitoring: Plutonium Valley (CAU 366) FY2019

Desert Research Institute (DRI) conducted a field assessment of the potential for radionuclide-contaminated soil to be transported from the Plutonium Valley Dispersion Sites Contamination Area (CA) because of both wind and storm water runoff. This activity supported U.S. Department of Energy (DOE) Environmental Management Nevada Program (EM NV) efforts to establish post-closure monitoring plans for the Plutonium Valley Dispersion Sites Corrective Action Unit (CAU) 366. The DRI task was intended to identify the likely mechanism(s) of transport and determine the meteorological conditions that might cause the movement of radionuclide-contaminated soils. The emphasis of the work was on collecting sediment transported by channelized storm runoff and measuring airborne dust concentrations and associated wind conditions. These data will facilitate an appropriate post-closure monitoring program. In 2011, DRI installed meteorological monitoring stations north and south of the Plutonium Valley CA—known as Pu Valley North and Pu Valley South, respectively—as well as a fluvial sediment sampling station within the CA. Since installation, temperature, wind speed, wind direction, relative humidity, precipitation, solar radiation, barometric pressure, soil temperature, volumetric soil moisture content, and airborne particulate concentrations have been collected at both meteorological stations. The maximum, minimum, and average or total (as appropriate) for each of these parameters were recorded for each 10-minute interval. The sediment sampling station included an automatically activated sampling pump with collection bottles for suspended sediment, which was activated when sufficient flow was present in the channel, and passive traps for bedload material that was transported down the channel during runoff events. This report presents data collected from these stations during fiscal year (FY) 2019. During the FY2019 (October 1, 2018, through September 30, 2019) reporting period, the warmest month was July and the coldest month was February. Monthly total solar radiation was highest in June or July (depending on the station) and lowest in December. Monthly mean wind speeds were highest during February. At the Pu Valley North station, winds were commonly northerly, northwesterly, and southerly. At the Pu Valley South station, the wind direction was more variable and winds frequently came from most directions, excluding westerly and northwesterly winds. Winds above 15.0 miles per hour (mph) (24.1 kilometers per hour [km/hr]) were frequently southerly at both stations, and less-frequent strong winds were northerly (at the Pu Valley South station) or northwesterly (at the Pu Valley North station). Monthly average relative humidity ranged from 18 percent in August to 62 percent in January and February. Monthly total precipitation ranged from zero at both stations in September to 2.23 inches (in) (56.6 millimeters [mm]) during February at the Pu Valley South station and 2.09 in (53.1 mm) during March at the Pu Valley North station. From October 1, 2018, through September 30, 2019, the total precipitation was 8.23 in (209 mm) and 8.15 in (207 mm) at the Pu Valley South and Pu Valley North stations, respectively. The largest daily precipitation totals of 1.46 in (37.1 mm) and 1.14 in (29.0 mm) occurred at the Pu Valley South and Pu Valley North stations, respectively, on March 6, 2019. However, the ISCO autosampler was not activated during any storm event in FY2019 because the channel water depth measurements were insufficient for suspended sediment sample collection. Additionally, because no significant flow through the channel was indicated, no bedload samples were collected. Light breezes of 0.0 mph to 5.0 mph (0.0 km/hr to 8.0 km/hr) occurred most frequently (approximately 55 percent to 57 percent of the time). The frequency of occurrence diminished exponentially as the wind speed increased such that winds in excess of 25.0 mph (40.2 km/hr) occurred less than 0.01 percent of the time. Winds in excess of 15.0 mph (24.1 km/hr) were most commonly southerly, which is likely controlled by the topography of the valley because topographic highs define the east and west sides of the valley and converge toward the north.The concentrations of PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 micrometers [μm]) and PM10 (particulate matter with an aerodynamic diameter ≤10 μm) in the air generally increase as wind speed increases. However, the particle profiler at the Pu Valley South station regularly malfunctioned, which resulted in poor data quality and a limited period of record within FY2019. Therefore, discussion of the annual dust observations is mostly limited to the Pu Valley North station. At the Pu Valley North station, significant increases in windblown dust concentrations were observed when wind speeds exceeded 15.0 mph (24.1 km/hr), especially during southerly winds. When all wind speeds were considered, high dust concentrations at the Pu Valley North station were frequently associated with northerly, northwesterly, or southerly winds. The majority of PM10 transport at the Pu Valley North station occurred when winds were blowing northerly and northwesterly because of the high frequency of winds up to 15.0 mph (24.1 km/hr). The ratio of PM10 to PM2.5 is a qualitative indicator of the proximity of dust sources to the observation point and the values of the PM10 to PM2.5 ratio tend to be higher nearer to the source. The PM10 to PM2.5 ratio increased from 1.2 to 2.8 with higher wind speeds at the Pu Valley North station. This increase suggests that some locally sourced PM10 was present in the air when local winds exceeded 15.0 mph (24.1 km/hr). Local dust suspension is interpreted during major dust events when peaks in the PM10 to PM2.5 ratio occur simultaneously with the maximum wind speed and the peak PM10 concentration. Analysis of the five major dust events in FY2019 revealed that northerly winds were dominant in three events and southerly winds were dominant in two events. Local suspension of dust within Plutonium Valley is suspected to have occurred during two of the five major events (April 9, 2019, and September 28 to 29, 2019), and a nonlocal source of dust is presumed for the three other major dust events (October 14, 2018; May 16, 2019; and September 2, 2019). The three suspected regional dust transport events exhibited winds that typically did not exceed the 15.0 mph (24.1 km/hr) wind speed threshold for local dust transport and featured PM10 to PM2.5 ratios that indicate large-scale regional dust transport. Similar event characteristics (e.g., wind speed and PM10 concentration) were observed at air monitoring stations approximately 70 mi (113 km) to the northwest within the Tonopah Test Range (TTR). Therefore, these three regional events may not reflect transport from the Plutonium Valley CA. Routine monitoring of meteorological and hydrologic parameters at Plutonium Valley has been discontinued at the request of EM NV, effective at the conclusion of FY2019. Environmental data acquisition has been completed, and both Pu Valley North and Pu Valley South meteorological stations within Plutonium Valley as well as the ISCO autosampler station within the CA were removed on October 14, 2019.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Combining Dark Energy Survey Science Verification data with near-infrared data from the ESO VISTA Hemisphere Survey

We present the combination of optical data from the Science Verification phase of the Dark Energy Survey (DES) with near-infrared (NIR) data from the European Southern Observatory VISTA Hemisphere Survey (VHS). The deep optical detections from DES are used to extract fluxes and associated errors from the shallower VHS data. Joint seven-band ( grizYJK ) photometric catalogues are produced in a single 3 sq-deg dedicated camera field centred at 02h26m-04d36m where the availability of ancillary multiwavelength photometry and spectroscopy allows us to test the data quality. Dual photometry increases the number of DES galaxies with measured VHS fluxes by a factor of ~4.5 relative to a simple catalogue level matching and results in a ~1.5 mag increase in the 80 per cent completeness limit of the NIR data. Almost 70 per cent of DES sources have useful NIR flux measurements in this initial catalogue. Photometric redshifts are estimated for a subset of galaxies with spectroscopic redshifts and initial results, although currently limited by small number statistics, indicate that the VHS data can help reduce the photometric redshift scatter at both z < 0.5 and z > 1. We present example DES+VHS colour selection criteria for high-redshift luminous red galaxies (LRGs) at z ~ 0.7 as well as luminous quasars. Using spectroscopic observations in this field we show that the additional VHS fluxes enable a cleaner selection of both populations with <10 per cent contamination from galactic stars in the case of spectroscopically confirmed quasars and <0.5 per cent contamination from galactic stars in the case of spectroscopically confirmed LRGs. The combined DES+VHS data set, which will eventually cover almost 5000 sq-deg, will therefore enable a range of new science and be ideally suited for target selection for future wide-field spectroscopic surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Evaluating Energy Efficiency Opportunities from Connected and Automated Vehicle Deployments Coupled with Shared Mobility in California

Connected and Automated Vehicles (CAVs) can be considered to be a disruptive transportation technology, with the potential to significantly improve overall transportation system efficiency; however, CAVs may increase induce vehicle miles traveled (VMT) and bring on greater energy consumption. Further, shared mobility is another disruptive transportation event that is reshaping our travel patterns. The primary goal of this project was to extensively collect data from vehicles and associated infrastructure equipped with CAV technologies from both real-world experiments and simulation studies mainly deployed in California, and develop a comprehensive framework for evaluating energy efficiency opportunities from large-scale (e.g., statewide) introduction of CAVs and a wide deployment of shared mobility systems in a variety of scenarios. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance, and energy efficiency, a unique mesoscopic simulation-based model was developed for mobility and energy efficiency evaluation considering these disruptive transportation technologies. As a complement to existing studies on nationwide evaluation of CAVs’ energy impacts, this project was focused on data collection efforts and CAV applications under congested traffic environments that are frequently experienced on a massive scale across the major metropolitan areas in California. Extensive real-world data collection supplemented with simulation studies were conducted to cover a variety of CAV and shared mobility scenarios, particularly on scenarios less-explored in the existing research. Another key component of this project was to consider the interaction between different CAV technologies and shared mobility models, and the compound effect on energy efficiency. A comprehensive modeling suite was developed to quantify the impact of new mobility technologies on travel behavior and traffic performance. The developed modeling framework includes an energy intensity module, mode choice module and activity generation module that are integrated into an agent-based BEAM simulation platform to perform impact analysis based on a variety of scenarios. In addition, the RouteE model has been upgraded to incorporate the impact of CAVs on traffic flow, VMT and energy intensity, using micro-simulation data collected from both freeways and urban arterials. A novel fundamental influencing factor (FIF) mode choice model was developed to link CAV and shared mobility components with travel behaviors, and adapted into the BEAM-centered model framework. A statewide energy inventory was constructed under various CAV technology deployment scenarios by incorporating datasets and models for predicting vehicle market share and vehicle usage, which are tightly associated with the penetration of shared mobility systems. Based applying this modeling suite to a calibrated network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes. The statewide analysis based on the National Household Travel Survey (NHTS) sample data is consistent with the findings from the Riverside network and validate the developed clustering-prediction modeling methodology. The outcomes from this project will help close the knowledge gap on recognizing the potential performance and energy impacts of a broad deployment of CAV and shared mobility technologies across a wide range of roadway infrastructure with varying levels of congestion. Results from this project: 1) will support policymakers in steering CAV development and deployment towards an energy favorable direction; 2) reduce uncertainties in estimating energy saving opportunities from new mobility technologies and services; 3) increase the confidence of CAV technology investors both on the infrastructure side (i.e., transportation agencies) and on the vehicle side (i.e., OEMs); and 4) expedite the deployment of energy-efficient CAV and shared mobility applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

3-D decoupled inversion of complex conductivity data in the real number domain

Complex conductivity inversion, aslo called spectral induced polarization inversion, involves estimating the frequency dependent complex electrical conductivity distribution of the subsurface. The superior diagnostic capabilities provided by complex conductivity spectra have driven advancements in mechanistic understanding of complex conductivity as well as modelling and inversion appraoches over the past several decades. In this work, we demonstrate the theory and application for an approach to three-dimensional modeling and inversion of complex conductivity data in the real number domain. Beginning from first principles, we demonstrate how the equations for the real and imaginary components of the complex potential may be decoupled. This leads to a description of the real and imaginary source current terms, and a corresponding assessment of error arising from an assumption necessary complete the decoupled modeling. We show that for most earth materials, which exhibit relatively small phases (e.g. less than 0.2 radians) in complex conductivity, these errors become insignificant. For higher phase materials, the errors may be quantified and corrected through an iterative procedure. We demonstrate the accuracy of numerical forward solutions by direct comparison to corresponding analytic solutions. We demonstrate the inversion using both synthetic and field examples with data collected over a waste infiltration trench, at frequencies ranging from 0.5 to 7.5 Hz. In addition to insight provided by the decoupled equations, we see three primary advantages of the decoupled inversion in comparison to fully coupled inversion in complex number domain. First, memory requirements are reduced by a factor of two because it is unnecessary to simultaneously store both the real and complex components and associated Jacobian matrices. Second, data noise is specified separately for the real and imaginary components of potential (or magnitude and phase), which removes the ambiguity in data misfit residuals that exists in the complex number domain, thereby enabling the inversion to appropriately fit the data. Final, except for the source current terms, the modeling and inversion algorithms are equivalent to the direct current electrical resistivity tomography counterpart. In conclusion, this enables direct application of advancements and approaches developed originally for electrical resistivity tomography.

58 GEOSCIENCES↗
NASA NTRS2024

JWST Reveals CO Ice, Concentrated CO 2 Deposits, and Evidence for Carbonates Potentially Sourced From Ariel’s Interior

The Uranian moon Ariel exhibits a diversity of geologically young landforms, with a surface composition rich in CO 2 ice. The origin of CO 2 and other species, however, remains uncertain. We report observations of Ariel’s leading and trailing hemispheres, collected with NIRSpec (2.87–5.10 μm) on the James Webb Space Telescope. These data shed new light on Arielʼs spectral properties, revealing a double-lobed CO 2 ice scattering peak centered near 4.20 and 4.25 μm, with the 4.25 μm lobe possibly representing the largest CO 2 Fresnel peak yet observed in the solar system. A prominent 4.38 μm 13 CO 2 ice feature is also present, as is a 4.90 μm band that results from 12 CO 2 ice. The spectra reveal a 4.67 μm 12 CO ice band and a broad 4.02 μm band that might result from carbonate minerals. The data confirm that features associated with CO 2 and CO are notably stronger on Ariel’s trailing hemisphere compared to its leading hemisphere. We compared the detected CO 2 features to synthetic spectra of CO 2 ice and mixtures of CO 2 with CO, H 2 O, and amorphous carbon, finding that CO 2 could be concentrated in deposits thicker than ∼10 mm on Ariel’s trailing hemisphere. Comparison to laboratory data indicates that CO is likely mixed with CO 2 . The evidence for thick CO 2 ice deposits and the possible presence of carbonates on both hemispheres suggests that some carbon oxides could be sourced from Ariel’s interior, with their surface distributions modified by charged particle bombardment, sublimation, and seasonal migration of CO and CO 2 from high to low latitudes.

Uranian satellites↗
NASA NTRS1988

Strategies for concurrent processing of complex algorithms in data driven architectures

Research directed at developing a graph theoretical model for describing data and control flow associated with the execution of large grained algorithms in a special distributed computer environment is presented. This model is identified by the acronym ATAMM which represents Algorithms To Architecture Mapping Model. The purpose of such a model is to provide a basis for establishing rules for relating an algorithm to its execution in a multiprocessor environment. Specifications derived from the model lead directly to the description of a data flow architecture which is a consequence of the inherent behavior of the data and control flow described by the model. The purpose of the ATAMM based architecture is to provide an analytical basis for performance evaluation. The ATAMM model and architecture specifications are demonstrated on a prototype system for concept validation.

Stoughton, John W.↗
NASA NTRS1993

Identification and interpretation of patterns in rocket engine data

The goal of our research is to analyze ground test data, to identify patterns associated with the anomalous engine behavior. On the basis of this analysis, it is the task of our project to develop a Pattern Identification and Detection System which detects anomalous engine behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. Early detection of these anomalies is challenging because of the large amount of noise presence in the data. In the presence of this noise, early indication of anomalies becomes even more difficult to distinguish from fluctuations in normal steady state operation.

Lo, Ching F.↗
DOE OSTI2024

Geophysical and Environmental Monitoring Data, and Subsurface Flow Modelling Results for Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO

This dataset includes geoelectrical monitoring data acquired between October 2021 and November 2022, soil moisture and temperature data, groundwater data obtained from borehole SNIB covering the period from June 2021 to September 2022, and hydrological modelling results. The data were acquired to investigate how variations in bedrock type and topography, and vegetation cover control subsurface flow dynamics. To provide insights into the subsurface flow dynamics and their controls, a monitoring transect was installed at the Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO, measuring the spatio-temporal variations of soil moisture, soil and snow temperature, subsurface electrical resistivity variations, and groundwater dynamics. Field data are organized in a folder structure, with Electrical Resistivity Tomography (ERT) data being provided as one file per measurement, and data of the soil moisture and temperature sensors being provided as text files covering the entire monitoring period. The ‘Locations.csv’ file contains the location of all sensors, given in NAD83 – UTM Zone 13N. ERT monitoring data has been processed to filter data based on reciprocal errors (data with errors > 30% were removed), a linear error model was fitted to each survey, and to ensure a constant set of measurements for time-lapse inversion, filtered data were interpolated and assigned a 100% measurement error. Soil moisture and temperature data were acquired at 15 min intervals, and averaged to provide 1h data. Weather data and borehole data (groundwater depth, conductivity and temperature) were acquired at 30 min intervals, and are provided as daily measurements; all measurements are averaged, except of precipitation values, which are given as daily accumulation. The hydrological model was set up along the ERT monitoring transect, and net infiltration was used as surface boundary condition and derived from the weather data. Four different results are provided, (1) results for a parameterization using hydraulic permeability and porosity as derived from the ERT data through petrophysical relationships, and (2) three simplified model results, using 1 to 3 geological layers above the bedrock. Modelling was performed using PFLOTRAN, and for each model the PFLOTRAN input files are provided. The result files include weekly hydrological modelling results (e.g., saturation, velocities, pressures), as well as the model parameterization. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Dated soil C–N–P profiles, water quality, and chamber fluxes across Ohio and Michigan wetlands (2024–2025)

This dataset includes dated soil core chemistry (bulk density, phosphorus, nitrogen and carbon concentrations), water quality, and chamber flux measurements collected from wetlands in the Midwest United States—12 sites in Ohio, one site in Indiana, one site in Michigan—collected in the spring or summer of 2024 or 2025, all in (.csv) format. These data were generated to examine how wetland restoration, management activities, and time since restoration affect biogeochemical processes, carbon sequestration, nutrient accumulation, water quality, and greenhouse gas emissions. Specifically, these data aim to investigate how restored wetlands differ from natural wetlands in terms of carbon, nitrogen, phosphorus dynamics, as well as carbon dioxide and methane fluxes. Also included are surface and porewater quality parameters and chamber flux measurements across these different wetlands. Sampling was conducted at various sites representing a range of restoration stages, from about 4 years post-restoration up to 105 years post-restoration, and also includes a natural wetland used as a reference in Michigan. These data can be used to determine carbon sequestration rates, nutrient cycling, and to enhance our understanding of biogeochemical responses to wetland restoration in temperate ecosystems. This data package contains (1) a csv file (Water_Quality.csv) containing water quality data (dissolved organic carbon, total dissolved nitrogen, and temperature) organized by location; (2) a csv file (Soil_C_N_P_Seq.csv) containing carbon, nitrogen, and phosphorus concentrations at each soil level and time of each soil level, as well as their sequestration rates; (3) a csv file (CH4_CO2_Flux.csv) including methane and carbon dioxide fluxes that were measured with a chamber; (4) a file-level metadata (FLMD.csv) file that lists each file contained in the dataset with associated metadata; (5) a data dictionary (DD.csv) file that contains terms/column headers used throughout the files along with a definition, units, and data type; and (6) a locations metadata file (Location_metadata.csv).

Earth Science > Atmosphere > Atmospheric Chemistry↗
NASA NTRS1982

Remote sensing evidence for regolith water vapor sources on Mars

McCord et al. (1977) have presented earth-based photometric imaging data of an event associated with the 1973 dust storm on Mars. The initial dust cloud in Solis Lacus and two regions to the north and south appeared anomalously bright at blue wavelengths. Water frosts, hazes, and/or clouds were identified, and it was suggested that the water responsible for these findings may have originated from Solis Lacus. More recently, a more intensive review of the observational record of Mars was undertaken. Earth-based telescope observations and data from the Mariner and Viking missions have revealed that Solis Lacus has been a center of repeated activity. Persistent activity in the vicinity of Noachis-Hellespontus and in the border regions of Syrtis Major was also discovered. A review of the observations is provided and possible interpretations are discussed. The obtained results appear to support the original proposal that Solis Lacus may be a source of water vapor. Noachis-Hellespontus seems to be a similar vapor source

Huguenin, R. L.↗
NASA NTRS2012

Performance Considerations for the SIMPL Single Photon, Polarimetric, Two-Color Laser Altimeter as Applied to Measurements of Forest Canopy Structure and Composition

The Slope Imaging Multi-polarization Photon-counting Lidar (SIMPL) is a multi-beam, micropulse airborne laser altimeter that acquires active and passive polarimetric optical remote sensing measurements at visible and near-infrared wavelengths. SIMPL was developed to demonstrate advanced measurement approaches of potential benefit for improved, more efficient spaceflight laser altimeter missions. SIMPL data have been acquired for wide diversity of forest types in the summers of 2010 and 2011 in order to assess the potential of its novel capabilities for characterization of vegetation structure and composition. On each of its four beams SIMPL provides highly-resolved measurements of forest canopy structure by detecting single-photons with 15 cm ranging precision using a narrow-beam system operating at a laser repetition rate of 11 kHz. Associated with that ranging data SIMPL provides eight amplitude parameters per beam unlike the single amplitude provided by typical laser altimeters. Those eight parameters are received energy that is parallel and perpendicular to that of the plane-polarized transmit pulse at 532 nm (green) and 1064 nm (near IR), for both the active laser backscatter retro-reflectance and the passive solar bi-directional reflectance. This poster presentation will cover the instrument architecture and highlight the performance of the SIMPL instrument with examples taken from measurements for several sites with distinct canopy structures and compositions. Specific performance areas such as probability of detection, after pulsing, and dead time, will be highlighted and addressed, along with examples of their impact on the measurements and how they limit the ability to accurately model and recover the canopy properties. To assess the sensitivity of SIMPL's measurements to canopy properties an instrument model has been implemented in the FLIGHT radiative transfer code, based on Monte Carlo simulation of photon transport. SIMPL data collected in 2010 over the Smithsonian Environmental Research Center, MD are currently being modelled and compared to other remote sensing and in situ data sets. Results on the adaptation of FLIGHT to model micropulse, single'photon ranging measurements are presented elsewhere at this conference. NASA's ICESat-2 spaceflight mission, scheduled for launch in 2016, will utilize a multi-beam, micropulse, single-photon ranging measurement approach (although non-polarimetric and only at 532 nm). Insights gained from the analysis and modelling of SIMPL data will help guide preparations for that mission, including development of calibration/validation plans and algorithms for the estimation of forest biophysical parameters.

Dabney, Philip W.↗
DOE OSTI2021

Quality Control Methods for Advanced Metering Infrastructure Data

While urban-scale building energy modeling is becoming increasingly common, it currently lacks standards, guidelines, or empirical validation against measured data. Empirical validation necessary to enable best practices is becoming increasingly tractable. The growing prevalence of advanced metering infrastructure has led to significant data regarding the energy consumption within individual buildings, but is something utilities and countries are still struggling to analyze and use wisely. In partnership with the Electric Power Board of Chattanooga, Tennessee, a crude OpenStudio/EnergyPlus model of over 178,000 buildings has been created and used to compare simulated energy against actual, 15-min, whole-building electrical consumption of each building. In this study, classifying building type is treated as a use case for quantifying performance associated with smart meter data. This article attempts to provide guidance for working with advanced metering infrastructure for buildings related to: quality control, pathological data classifications, statistical metrics on performance, a methodology for classifying building types, and assess accuracy. Advanced metering infrastructure was used to collect whole-building electricity consumption for 178,333 buildings, define equations for common data issues (missing values, zeros, and spiking), propose a new method for assigning building type, and empirically validate gaps between real buildings and existing prototypes using industry-standard accuracy metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1979

False lock performance of quadriphase receivers

Quadriphase receivers, like biphase receivers, have the ability to false lock on a sideband on the data modulation. The theory associated with this phenomenon for receivers of binary phase-shift-keying (BPSK), using Costas loop demodulation, has recently been documented in the literature. This paper considers the corresponding theory for receivers of balanced quadriphase-shift-keying (QPSK) employing a quadriphase Costas loop (or equivalent fourth-power loop) for demodulation. Specific closed form expressions for false lock performance are developed and numerically evaluated for the particular case of single pole arm filters and an NRZ data format for each of the two statistically independent quadrature modulations.

Simon, M. K.↗
NASA NTRS2007

Reusable, Extensible High-Level Data-Distribution Concept

A framework for high-level specification of data distributions in data-parallel application programs has been conceived. [As used here, distributions signifies means to express locality (more specifically, locations of specified pieces of data) in a computing system composed of many processor and memory components connected by a network.] Inasmuch as distributions exert a great effect on the performances of application programs, it is important that a distribution strategy be flexible, so that distributions can be adapted to the requirements of those programs. At the same time, for the sake of productivity in programming and execution, it is desirable that users be shielded from such error-prone, tedious details as those of communication and synchronization. As desired, the present framework enables a user to refine a distribution type and adjust it to optimize the performance of an application program and conceals, from the user, the low-level details of communication and synchronization. The framework provides for a reusable, extensible, data-distribution design, denoted the design pattern, that is independent of a concrete implementation. The design pattern abstracts over coding patterns that have been found to be commonly encountered in both manually and automatically generated distributed parallel programs. The following description of the present framework is necessarily oversimplified to fit within the space available for this article. Distributions are among the elements of a conceptual data-distribution machinery, some of the other elements being denoted domains, index sets, and data collections (see figure). Associated with each domain is one index set and one distribution. A distribution class interface (where "class" is used in the object-oriented-programming sense) includes operations that enable specification of the mapping of an index to a unit of locality. Thus, "Map(Index)" specifies a unit, while "LocalLayout(Index)" specifies the local address within that unit. The distribution class can be extended to enable specification of commonly used distributions or novel user-defined distributions. A data collection can be defined over a domain. The term "data collection" in this context signifies, more specifically, an abstraction of mappings from index sets to variables. Since the index set is distributed, the addresses of the variables are also distributed.

James, Mark↗
DOE OSTI2018

Mission possible: Unify HPC and Big Data stacks towards application-defined blobs at the storage layer

HPC and Big Data stacks are completely separated today. The storage layer offers opportunities for convergence, as the challenges associated with HPC and Big Data storage are similar: trading versatility for performance. This motivates a global move towards dropping file-based, POSIX-IO compliance systems. However, on HPC platforms this is made difficult by the centralized storage architecture using file-based storage. In this paper we advocate that the growing trend of equipping HPC compute nodes with local storage redistributes the cards by enabling object storage to be deployed alongside the application on the compute nodes. Furthermore, such integration of application and storage not only allows fine-grained configuration of the storage system, but also improves application portability across platforms. In addition, the single-user nature of such application-specific storage obviates the need for resource-consuming storage features like permissions or file hierarchies offered by traditional file systems. In this article we propose and evaluate Blobs (Binary Large Objects) as an alternative to distributed file systems. Finally, we factually demonstrate that it offers drop-in compatibility with a variety of existing applications while improving storage throughput by up to 28%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Effective Padding of Multi-Dimensional Arrays to Avoid Cache Conflict Misses

Caches are used to significantly improve performance. Even with high degrees of set-associativity, the number of accessed data elements mapping to the same set in a cache can easily exceed the degree of associativity, causing conflict misses and lowered performance, even if the working set is much smaller than cache capacity. Array padding (increasing the size of array dimensions) is a well known optimization technique that can reduce conflict misses. In this paper, we develop the first algorithms for optimal padding of arrays for a set associative cache for arbitrary tile sizes, In addition, we develop the first solution to padding for nested tiles and multi-level caches. The techniques are in implemented in PAdvisor tool. Experimental results with multiple benchmarks demonstrate significant performance improvement from use of PAdvisor for padding.

array padding↗