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At least 1,009 records · Page 56

CFD Validation with LDV Test Data for Payload/Fairing Internal Flow

Flowfield testing of a 1/5th scale model of a payload/fairing configuration, typical of an expendable launch vehicle, has been performed. Two-dimensional (planar) velocity measurements were carried out in four planes with the aid of Laser Doppler Velocimetry (LDV). Computational Fluid Dynamics (CFD) analysis results for the scale model flowfleld are compared with the test data. The CFD results are in general agreement with the test data. The ability of the CFD methodology in identifying the global flow features (including critical points such as vortex, saddle point, etc.) has been demonstrated. Practical problems and difficulties associated with the LDV method applied to the complex geometry under consideration have been summarized.

Kandula, max↗

Implementation of a Transition Model in a NASA Code and Validation Using Heat Transfer Data on a Turbine Blade

The purpose of this report is to summarize and document the work done to enable a NASA CFD code to model laminar-turbulent transition process on an isolated turbine blade. The ultimate purpose of the present work is to down-select a transition model that would allow the flow simulation of a variable speed power turbine to be accurately performed. The flow modeling in its final form will account for the blade row interactions and their effects on transition which would lead to accurate accounting for losses. The present work only concerns itself with steady flows of variable inlet turbulence. The low Reynolds number k- model of Wilcox and a modified version of the same model will be used for modeling of transition on experimentally measured blade pressure and heat transfer. It will be shown that the k- model and its modified variant fail to simulate the transition with any degree of accuracy. A case is thus made for the adoption of more accurate transition models. Three-equation models based on the work of Mayle on Laminar Kinetic Energy were explored. The three-equation model of Walters and Leylek was thought to be in a relatively mature state of development and was implemented in the Glenn-HT code. Two-dimensional heat transfer predictions of flat plate flow and two-dimensional and three-dimensional heat transfer predictions on a turbine blade were performed and reported herein. Surface heat transfer rate serves as sensitive indicator of transition. With the newly implemented model, it was shown that the simulation of transition process is much improved over the baseline k- model for the single Reynolds number and pressure ratio attempted; while agreement with heat transfer data became more satisfactory. Armed with the new transition model, total-pressure losses of computed three-dimensional flow of E3 tip section cascade were compared to the experimental data for a range of incidence angles. The results obtained, form a partial loss bucket for the chosen blade. In time the loss bucket will be populated with losses at additional incidences. Results obtained thus far will be discussed herein.

Ameri, Ali A.↗

A Global End-Member Approach to Derive aCDOM(440) from Near-Surface Optical Measurements

This study establishes an optical inversion scheme for deriving the absorption coefficient of colored (or chromophoric, depending on the literature) dissolved organic material (CDOM) at the 440 nm wavelength, which can be applied to global water masses with near-equal efficacy. The approach uses a ratio of diffuse attenuation coefficient spectral end members, i.e., a short and long wavelength pair. The global perspective is established by sampling "extremely" clear water plus a generalized extent in turbidity and optical properties that each span three decades of dynamic range. A unique data set was collected in oceanic, coastal, and inland waters (as shallow as 0.6 m) from the North Pacific Ocean, the Arctic Ocean, Hawaii, Japan, Puerto Rico, and the east and west coasts of the United States. The data were partitioned using subjective categorizations to define a validation quality subset of conservative water masses, i.e., the inflow and outflow of properties constrain the range in the gradient of a constituent, plus 15 subcategories of water masses that were not evolving conservatively. The dependence on subcategories was confirmed with an objective methodology based on cluster analysis techniques. The latter defined five distinct classes with validation quality data present in all classes, but which also decreased in percent composition as a function of increasing class number and optical complexity. Four different algorithms based on different validation quality end members were validated with accuracies of 1.–6.2 %, wherein pairs with the largest spectral span were most accurate. Although algorithm accuracy decreased with the inclusion of more subcategories containing non-conservative water masses, changes to the algorithm fit were small when a preponderance of subcategories were included. The high accuracy for all end-member algorithms was the result of data acquisition and data processing improvements, e.g., increased vertical sampling resolution to less than 1mm and a boundary constraint to mitigate wave focusing effects, respectively. An independent evaluation with a historical database confirmed the consistency of the algorithmic approach and its application to quality assurance, e.g., to flag data outside expected ranges, identify suspect spectra, and objectively determine the in-water extrapolation interval by converging agreement for all applicable end-member algorithms. The legacy data exhibit degraded performance (as 44 % uncertainty) due to a lack of high-quality near-surface observations, especially for clear waters wherein wave-focusing effects are problematic. The novel optical approach allows the in situ estimation of an in-water constituent in keeping with the accuracy obtained in the laboratory.

Stanford B Hooker↗

Technical Report Series on Global Modeling and Data Assimilation: Soil Moisture Active Passive (SMAP) Project Calibration and Validation for the L4_C Beta-Release Data Product - Volume 42

During the post-launch Cal/Val Phase of SMAP there are two objectives for each science product team: 1) calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the L1 science requirements according to the Cal/Val timeline. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product specifically for the beta release. The beta-release version of the SMAP L4_C algorithms utilizes a terrestrial carbon flux model informed by SMAP soil moisture inputs along with optical remote sensing (e.g. MODIS) vegetation indices and other ancillary biophysical data to estimate global daily NEE and component carbon fluxes, particularly vegetation gross primary production (GPP) and ecosystem respiration (Reco). Other L4_C product elements include surface (<10 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture and landscape FT controls on GPP and Reco (Kimball et al. 2012). The L4_C product encapsulates SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and underlying freeze/thaw and soil moisture constraints to these processes, 2) documenting primary connections between terrestrial water, energy and carbon cycles, and 3) improving understanding of terrestrial carbon sink activity in northern ecosystems.

Cal/Val↗

Global Summary MGS TES Data and Mars-Gram Validation

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many Mars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Arizona Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topograph$ from Mars Global Surveyor Mars Orbiting Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with a global summary data set of Mars Global Surveyor Thermal Emission Spectrometer (TES) data. TES averages and standard deviations were assembled from binned TES data which covered surface to approx. 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of a Mars global dust storm). TES data were binned in 10-by-10 degree latitude-longitude bins (i.e. 36 longitude bins by 19 latitude bins), 12 seasonal bins (based on 30 degree increments of Ls angle). Bin averages and standard deviations were assembled at 23 data levels (temperature at 21 pressure levels, plus surface temperature and surface pressure). Two time-of day bins were used: local time near 2 or 14 hours local time). Two dust optical depth bins wereused: infrared optical depth either less than or greater than 0.25 (which corresponds to visible optical depth either less than or greater than about 0.5). For interests in aerocapture and precision entry and landing, comparisons focused on atmospheric density. TES densities versus height were computed from TES temperature versus pressure, using assumptions of perfect gas law and hydrostatics. Mars-GRAM validation studies used density ratio (TES/Mars-GRAM) evaluated at data bin center points in space and time. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (> 45 deg N), or at most altitudes in the southern hemisphere at Ls approx. 90 and 180deg). Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approx. 65-10.5% (varying with height) for all data, or approx. 5-12%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for local time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about the same as the standard deviation of TES data about the TES mean value at a given position and season.

Justus, C.↗

TPSAS-NF1676L-35283-DND

In this talk, we present a long-term burned area database that has been developed using Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) data from 1979-2000. Burned area has been verified using Total Ozone Mapping Spectrometer data and validated using available Landsat imagery (160 scenes thus far representing 5.6 Mha of burned area, 219 fire events, and 11% of the total burned area in the AVHRR database). Visually the burned scar data compare well. Validation is in ongoing, though initial analyses show an intersection of 42% with commission and omission errors of 31% and 25%, respectively. Most commission and omission errors are related to spatial inconsistencies using imagery with significantly different spatial resolutions. Of the fire events missed by AVHRR (omissions), 86% are related to fires <10,000 ha (6 GAC pixels) and 44% are related to fires <3,000ha (2 GAC pixels). Total burned area compares well, with the AVHRR database under-representing burned area by 10% compared to the Landsat data analyzed. Correlation in burned scar area between the AVHRR and Landsat data is 0.98 for all fires and 0.68 for fires that are < 0.1 Mha.

Amber Soja↗

Generating Synthetic Time Series Photovoltaic Data with Real-World Physical Challenges and Noise for Use in Algorithm Test and Validation

The PV Fleet Data Initiative and other projects seek the develop algorithms for automated analysis of PV time series data for extraction of statistical information and other parameters of the data such as degradation rates, soiling loss information, tracker performance, clipping or curtailment, system availability and other valuable information. While there is a vast body of PV data available for application of said extraction algorithms it is difficult to validate these algorithms because the true parameters to be extracted are not known. There has been a wide use of synthetic data in the literature for algorithm validation but this synthetic data is typically very bounded by the problem or topic at hand. The PV Fleet Data Initiative project has demonstrated that real time series PV data almost always includes a host of data quality and physical problems that, in reality, any automated PV abstraction algorithm must handle appropriately. For this reason, this work describes the development of a complex synthetic PV times series data set that includes data quality and physical problems that have been experienced in real world PV data. The various quality and physical problems are documented in the synthetic data so that users can test the validity of various PV extraction algorithms as well as develop new algorithms to solve problems this data set can support.

14 SOLAR ENERGY↗

A general software reliability process simulation technique

The structure and rationale of the generalized software reliability process, together with the design and implementation of a computer program that simulates this process are described. Given assumed parameters of a particular project, the users of this program are able to generate simulated status timelines of work products, numbers of injected anomalies, and the progress of testing, fault isolation, repair, validation, and retest. Such timelines are useful in comparison with actual timeline data, for validating the project input parameters, and for providing data for researchers in reliability prediction modeling.

Tausworthe, Robert C.↗