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At least 73 records · Page 4

Southwest Wind Power R&D Test Site Development at the National Wind Technology Center (CRADA CRD-12-00472 Final Report)

Southwest Windpower, Inc. (SWWP) has been designing and distributing small wind turbines for more than 22 years and is the recognized global leader in the design, manufacturing and distribution of small wind systems (400-3000 watts). The company has been a pioneer in the development of wind technology and has built and shipped more than 170,000 wind turbines to over 120 countries worldwide. Headquartered in Flagstaff AZ, SWWP has sales representatives in over 88 countries. Applications for SWWP systems include residential homes, commercial properties, micro grids, remote cabins, telecom transmitters, offshore platforms, water pumping and sailboats. In addition, U.S. Department of Defense uses SWWP’s products in Forward Operating Bases (FOB’s), USGS uses them for remote monitoring of glacier movements and the CIA uses them to provide power seismic monitoring. Today, SWWP plans development of new technologies to address distributed energy market needs and become even more aggressive in international markets. This strategy includes extensive Research, Development, Demonstration & Deployment (RDD&D) activities to improve existing production line into more simple, reliable, and cost-effective wind turbine systems. Important part of such activities is the field testing of the new systems, which should provide: (i) validation of the reliable operation of hardware and software; (ii) validation of numerical models of the system and its components; (iii) field comparison of various control and optimization strategies; (iv) customized reliability testing; (v) customized monitoring and analysis testing; and (vi) IEC certification testing (vii) filed demonstration of system performance and reliability. Such field testing facility should encompass multiple towers and appropriate data acquisition systems. SWWP is exploring to move part of the engineering department to Colorado, and execute its RDD&D strategies in this new location. Partnership with NREL will provide great insights into SWWP’s RDD&D processes and more efficient commercialization by utilizing NWTC as the field testing site, and working close with NREL personnel. NWTC is ideally suited to strain the design. NREL is very experienced with customized and IEC testing. During this project, Southwest Windpower aims to improve the value proposition of distributed renewable energy, and make it a competitive choice in the energy markets. As of today, more then 170,000 small wind turbines, manufactured in the U.S., are installed in more then 180 countries. With the improved value proposition, Southwest Windpower wants to create and address new market needs, substantially increase its sales domestically and internationally, which should have positive impact on the creation of American jobs, competitiveness of U.S. economy, export or U.S. products, and the use of renewable energy.

17 WIND ENERGY↗

Meeting Expanding Needs to Collect Food Intake Specificity: The Nutrition Data System for Research (NDS-R)

Food and nutrient databases are populated with data obtained from a variety of sources including USDA Reference Tables, scientific journals, food manufacturers and foreign food tables. The food and nutrient database maintained by the Nutrition Coordinating Center (NCC) at the University of Minnesota is continually updated with current nutrient data and continues to be expanded with additional nutrient fields to meet diverse research endeavors. Data are strictly evaluated for reliability and relevance before incorporation into the database; however, the values are obtained from various sources and food samples rather than from direct chemical analysis of specific foods. Precise nutrient values for specific foods are essential to the nutrition program at the National Aeronautics and Space Administration (NASA). Specific foods to be included in the menus of astronauts are chemically analyzed at the Johnson Space Center for selected nutrients. A request from NASA for a method to enter the chemically analyzed nutrient values for these space flight food items into the Nutrition Data System for Research (NDS-R) software resulted in modification of the database and interview system for use by NASA, with further modification to extend the method for related uses by more typical research studies.

VanHeel, Nancy↗

On the Reprocessing and Reanalysis of Observations for Climate

The long observational record is critical to our understanding of the Earth s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. WCRP provides the means to bridge the different motivating objectives on which national efforts focus.

Bosilovich, Michael G.↗

COMMIT in 7-SEAS/BASELInE: Operation of and Observations from a Novel, Mobile Laboratory for Measuring In-Situ Properties of Aerosols and Gases

Trace gases and aerosols (particularly biomass-burning aerosols) have important implications for air quality and climate studies in Southeast Asia (SEA). This paper describes the purpose, operation, and datasets collected from NASA Goddard Space Flight Center's (NASA/GSFC) Chemical, Optical, and Microphysical Measurements of In-situ Troposphere (COMMIT) laboratory, a mobile platform designed to measure trace gases and optical/microphysical properties of naturally occurring and anthropogenic aerosols. More importantly, the laboratory houses a specialized humidification system to characterize hygroscopic growth/enhancement, a behavior that affects aerosol properties and cloud-aerosol interactions and is generally underrepresented in the current literature. A summary of the trace gas and optical/microphysical measurements is provided, along with additional detail and analysis of data collected from the hygroscopic system during the 2015 Seven South-East Asian Studies (7-SEAS) field campaign. The results suggest that data from the platform are reliable and will complement future studies of aerosols and air quality in SEA and other regions of interest.

aerosols↗

Interconnect fatigue design for terrestrial photovoltaic modules

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Mon, G. R.↗

On the Reprocessing and Reanalysis of Observations for Climate

The long observational record is critical to our understanding of the Earths climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and to summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide an climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

Uncertainty↗

Design and performance of an in-vacuum, magnetic field mapping system for the Muon g-2 experiment

The Muon g - 2 experiment at Fermilab (E989) aims to measure the anomalous magnetic moment, a μ , of the muon with a precision of 140 parts-per-billion. This requires a precise measurement of both the anomalous spin precession frequency, ω α , of muons stored in a magnetic field of 1.45 T, and a precise measurement of that magnetic field in terms of the shielded proton Larmor frequency, ω' ρ . The measurement of ω' ρ with a total systematic uncertainty of 70 parts-perbillion involves a combination of various nuclear magnetic resonance (NMR) probes. There are 378 probes mounted in fixed locations that constantly monitor field drifts. A water-based, cylindrical calibration probe provides the calibration in terms of the shielded proton Larmor frequency. A crucial element for the multi-step measurement of ω' ρ is the regular mapping of the magnetic field over the muon storage region. The former experiment at Brookhaven National Laboratory (BNL) employed an in-vacuum field mapping system equipped with 17 NMR probes, which was developed by the University of Heidelberg. We have refurbished and upgraded this system with new probes and electronics. The upgrades include the addition of 16-bit, 1 MSPS digitization of the NMR signals, which replaced the hardware-implemented zero-crossing counting of the system at Brookhaven. The digitized signals offer new capabilities in the NMR frequency analysis and its related systematic uncertainties. To sustain the higher data rates, a new communication scheme with time-division multiplexing was implemented to separate the important NMR reference clock from the data communication in order to reach the specifications for the accuracy and stability of the reference clock. A new barcode reader provides more precise azimuthal position determination during the measurement and calibration. While the mechanical systems that move the field mapper inside the storage ring have been mostly refurbished from BNL, the motion control system was completely replaced with a custom-built electronics centered around a commercial Galil motion controller. Both the field mapping NMR system and its motion control were successfully commissioned at Fermilab and have been in reliable operation during the first three data taking periods of the experiment at Fermilab. Finally, this article will provide the details of the upgrades of the field mapper and its performance.

47 OTHER INSTRUMENTATION↗

Estimation of Model Error Variances During Data Assimilation

Data assimilation is all about understanding the error characteristics of the data and models that are used in the assimilation process. Reliable error estimates are needed to implement observational quality control, bias correction of observations and model fields, and intelligent data selection. Meaningful covariance specifications are obviously required for the analysis as well, since the impact of any single observation strongly depends on the assumed structure of the background errors. Operational atmospheric data assimilation systems still rely primarily on climatological background error covariances. To obtain error estimates that reflect both the character of the flow and the current state of the observing system, it is necessary to solve three problems: (1) how to account for the short-term evolution of errors in the initial conditions; (2) how to estimate the additional component of error caused by model defects; and (3) how to compute the error reduction in the analysis due to observational information. Various approaches are now available that provide approximate solutions to the first and third of these problems. However, the useful accuracy of these solutions very much depends on the size and character of the model errors and the ability to account for them. Model errors represent the real-world forcing of the error evolution in a data assimilation system. Clearly, meaningful model error estimates and/or statistics must be based on information external to the model itself. The most obvious information source is observational, and since the volume of available geophysical data is growing rapidly, there is some hope that a purely statistical approach to model error estimation can be viable. This requires that the observation errors themselves are well understood and quantifiable. We will discuss some of these challenges and present a new sequential scheme for estimating model error variances from observations in the context of an atmospheric data assimilation system.

Dee, Dick↗

Automatic cloud tracking applied to GOES and Meteosat observations

An improved automatic processing method for the tracking of cloud motions as revealed by satellite imagery is presented and applications of the method to GOES observations of Hurricane Eloise and Meteosat water vapor and infrared data are presented. The method is shown to involve steps of picture smoothing, target selection and the calculation of cloud motion vectors by the matching of a group at a given time with its best likeness at a later time, or by a cross-correlation computation. Cloud motion computations can be made in as many as four separate layers simultaneously. For data of 4 and 8 km resolution in the eye of Hurricane Eloise, the automatic system is found to provide results comparable in accuracy and coverage to those obtained by NASA analysts using the Atmospheric and Oceanographic Information Processing System, with results obtained by the pattern recognition and cross correlation computations differing by only fractions of a pixel. For Meteosat water vapor data from the tropics and midlatitudes, the automatic motion computations are found to be reliable only in areas where the water vapor fields contained small-scale structure, although excellent results are obtained using Meteosat IR data in the same regions. The automatic method thus appears to be competitive in accuracy and coverage with motion determination by human analysts.

Endlich, R. M.↗

Inter-well connectivity detection in CO 2 WAG projects using statistical recurrent unit models

Routine well-wise injection and production measurements contain significant information on subsurface structure and properties. Data-driven technology that interprets surface data into subsurface structure or properties can assist operators in making informed decisions by providing a better understanding of field assets. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO 2 EOR projects utilizing the water-alternating-gas (WAG) process. SRU is a special type of recurrent neural network (RNN) that allows for better characterization of temporal trends, by learning various statistics of the input at different time scales. In our application, the complete states (injection rate, pressure and cumulative injection) at injectors and pressure states at producers are fed to SRU as the input and the phase rates at producers are treated as the output. Once the SRU is trained and validated, it is then used to assess the connectivity of each injector to any producer using permutation variable importance method, wherein inputs corresponding to an injector are shuffled and the increase in prediction error at a given producer is recorded as the importance (connectivity metric) of the injector to the producer. This method is tested in both synthetic and field-scale cases. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. This significantly improves confidence in our data-driven procedure. The novelty of this work is that it is purely data-driven method and can directly interpret routine surface measurements to intuitive subsurface knowledge. Furthermore, the streamline-based validation procedure provides physics-based backing to the results obtained from data analytics. This study results in a reliable and efficient data analytics framework that is well-suited for large field applications.

42 ENGINEERING↗

Use of the LANDSAT-2 data collection system in the Colorado River basin weather modification program

The author has identified the following significant results. Many types of environmental sensors can be interfaced to the LANDSAT DCP. The LANDSAT field installations proved to be remarkably reliable, weather resistant, and cost effective units able to relay high quality data in near real time. The wind averaging system demonstrated the feasibility of transmitting averaged wind data, stored over a period of several hours, from a remote site.

Kahan, A. M.↗

Ground testing at MSFC

The large-scale field collection of acoustic data and their analysis are described in this review. The entire sound-field program has the purpose of solving complex problems of excessive noise propagation associated with the static test firing of large space-booster powerplants. The site of data collection has been Mississippi Test Facility (MTF), where far-field sound-propagation and correlated meteorological measurements were initiated in 1962. The statistical evaluation of sound-measurement data shows that the polar distribution of sound in the springtime (at MTF) is determined mainly by the temperature field of the atmosphere. Greater deformation of sound-intensity polar distribution occurs in the autumn as a result of the influence of the wind field. The data on sound attenuation as a function of distance from its source revealed attenuation in excess of the expected magnitude. The excess was mainly between 1 and 10 kilometers from the source, with maximum attenuation (17 to 18 decibels) near 6 kilometers. Excess sound attenuation was compared with calculated sound dispersion. For all sound frequencies in all seasons the deviation between reference and empirical attenuation values formed a bell-shaped distribution on a semilogarithmic plot. The physical causes for the sound- attenuation behavior are considered to be atmospheric diffraction and scattering effects. Statistical analysis of sod-intensity extremes indicated amplification of the sound signals by focusing which could be expected along selected azimuths. Empirical amplification values showed the maximum occurring in winter (50 decibels at 22 kilometers). For the analysis of correlation between empirical sound data and local atmospheric sound- propagation conditions, #e concept of analytical classification of sound-velocity profiles has been developed. Examination of over a quarter-million individual sound-velocity profiles indicates that 33 profile types for heights up to 3 kilometers constitute the empirical possibilities of sound-propagation conditions in southeastern United States. Since the focusing qualities of each sound- velocity profile can be determined as a class characteristic, the overall probabilities of focusing occurrence can he obtained. The severity of focusing, as based upon lateral spread of focusing areas, has been determined. The data for MTF indicate focusing is most severe in winter, with the direction toward east being most affected. Sound propagation is a fluctuating phenomenon because atmospheric conditions vary continuously. A measuring system for analyzing the nonstationary sound-propagation phenomena has been established. The analysis of the acoustic fluctuation data is sup- posed to provide "dynamic” perturbation functions of sound, which are to be superimposed on the related characteristic sound-velocity-profile type. The ultimate result of the program will be the establishment of reliable contingency tables showing the relationship between atmospheric parameters and far-field sound intensities. These data will be the basis for more accurate sound-propagation forecasting for static firing tests.

STATIC TESTING↗

An evaluation of the ERTS data collection system as a potential operational tool

The Earth Resources Technology Satellite Data Collection System has been shown to be, from the users vantage point, a reliable and simple system for collecting data from U.S. Geological Survey operational field instrumentation. It is technically feasible to expand the ERTS system into an operational polar-orbiting data collection system to gather data from the Geological Survey's Hydrologic Data Network. This could permit more efficient internal management of the Network, and could enable the Geological Survey to make data available to cooperating agencies in near-real time. The Geological Survey is conducting an analysis of the costs and benefits of satellite data-relay systems.

Paulson, R. W.↗

A field study of wind over a simulated block building

A full-scale field study of the wind over a simulated two-dimensional building is reported. The study develops an experiment to investigate the structure and magnitude of the wind fields. A description of the experimental arrangement, the type and expected accuracy of the data, and the range of the data are given. The data are expected to provide a fundamental understanding of mean wind and turbulence structure of the wind field around the bluff body. Preliminary analysis of the data demonstrates the reliability and completeness of the data in this regard.

Frost, W.↗

Evolution of the total ozone field during the breakdown of the Antarctic circumpolar vortex

Nine years of total ozone measurements from the TOMS on Nimbus 7 are used to study the evolution of the Southern Hemisphere total ozone field during the breakdown of the Antarctic circumpolar vortex. The TOMS data provide detailed maps of the morphology of the ozone field and reliable estimates of the vertically integrated meridional transport of ozone during the springtime period when the breakdown occurs (September, October, November). In estimating the ozone transport, chemical effects, including those thought to be responsible for the Antarctic ozone hole, are neglected. This approximation appears to be valid for time scales of a few days to a week. On this time scale, local ozone changes are primarily due to transport. Planetary-scale waves, especially zonal wave numbers 1 and 2 dominate the eddy variance and ozone transport. Wave number 1 is quasistationary, while wave number 2 is eastward moving with a period of about 10 days.

Bowman, Kenneth P.↗

Containerless experiments in fluid physics in microgravity

The physical phenomena associated with the behavior of liquid samples freely suspended in low gravity must be thoroughly understood prior to undertaking detailed scientific studies of the materials under scrutiny. The characteristics of molten specimens under the action of containerless positioning stresses must be identified and separated from the specific phenomena relating to the absence of an overwhelming gravitational field. The strategy designed to optimize the scientific return of reliable experimental data from infrequent microgravity investigations should include the gradual and logical phasing of more sophisticated studies building on the accumulated results from previous flight experiments. Lower temperature fluid physics experiments using model materials can provide a great deal of information that can be useful in analyzing the behavior of high temperature melts. The phasing of the experimental capabilities should, therefore, also include a gradual build-up of more intricate and specialized diagnostic instrumentation and environmental control and monitoring capabilities. Basic physical investigations should also be distinguished from specific materials technology issues. The latter investigations require very specific high temperature (and high vacuum) devices that must be thoroughly mastered on the ground prior to implementing them in space.

Trinh, E. H.↗

GaAs Reliability Database

The database consists of two main sections, the data references and the device reliability records. The reference section contains 8 fields: reference number, date of publication, authors, article title, publisher, volume, and page numbers.

GaAs electric performance↗

Satellite magnetic modeling of north African hot spots

The primary objectives of the MAGSAT mission was to measure the intensity and direction of magnetization of the Earth's crust. A significant effort was directed to the large crustal anomalies first delineated by the POGO mission. The MAGSAT data are capable of spatial resolution of the crustal field to 250 km wavelength with reliability limits to less than 1 nT in the mean. The difficulties of dealing with less than the most robust of the MAGSAT anomalies is that often there is no more than the magnetic fields themselves to constrain geophysical models of the interior, and no independent means of assessing the quality of the crustal anomaly data in interpreting the subsurface are available.

Phillips, R. J.↗