Search NASA⌕ Search

SEARCH · Search NASA

Results for “map validation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57

Dark Energy Survey Year 1 Results: Photometric Data Set for Cosmology

Here, we describe the creation, content, and validation of the Dark Energy Survey (DES) internal year-one cosmology data set, Y1A1 GOLD, in support of upcoming cosmological analyses. The Y1A1 GOLD data set is assembled from multiple epochs of DES imaging and consists of calibrated photometric zeropoints, object catalogs, and ancillary data products -e.g., maps of survey depth and observing conditions, star-galaxy classification, and photometric redshift estimates|that are necessary for accurate cosmological analyses. The Y1A1 GOLD wide-area object catalog consists of 137 million objects detected in coadded images covering 1800 deg 2 in the DES grizY filters. The 10 limiting magnitude for galaxies is g = 23.4, r = 23.2, i = 22.5, z = 21.8, and Y = 20.1. We also performed photometric calibration of Y1A1 GOLD by combining nightly zeropoint solutions with stellar-locus regression, and the absolute calibration accuracy is better than 2% over the survey area. DES Y1A1 GOLD is the largest photometric data set at the achieved depth to date, enabling precise measurements of cosmic acceleration at z ≲1.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of a 5 MW reference gearbox for offshore wind turbines: 5 MW reference gearbox

This paper presents detailed descriptions, modeling parameters and technical data of a 5MW high-speed gearbox developed for the National Renewable Energy Laboratory offshore 5MW baseline wind turbine. The main aim of this paper is to support the concept studies and research for large offshore wind turbines by providing a baseline gearbox model with detailed modeling parameters. This baseline gearbox follows the most conventional design types of those used in wind turbines. It is based on the four-point supports: two main bearings and two torque arms. The gearbox consists of three stages: two planetary and one parallel stage gears. The gear ratios among the stages are calculated in a way to obtain the minimum gearbox weight. The gearbox components are designed and selected based on the offshore wind turbine design codes and validated by comparison to the data available from large offshore wind turbine prototypes. All parameters required to establish the dynamic model of the gearbox are then provided. Moreover, a maintenance map indicating components with high to low probability of failure is shown. The 5 MW reference gearbox can be used as a baseline for research on wind turbine gearboxes and comparison studies. It can also be employed in global analysis tools to represent a more realistic model of a gearbox in a coupled analysis.

17 WIND ENERGY↗

Processing ultrasonic inspection data from multiple scan patterns for turbine rotor weld build-up evaluations

The study presents a data processing methodology for weld build-up using multiple scan patterns. To achieve an overall high probability of detection for flaws with different orientations, an inspection procedure with three different scan patterns is proposed. The three scan patterns are radial-tangential longitude wave pattern, axial-radial longitude wave pattern, and tangential shear wave pattern. Scientific fusion of the inspection data is implemented using volume reconstruction techniques. The idea is to perform spatial domain forward data mapping for all sampling points. A conservative scheme is employed to handle the case that multiple sampling points are mapped to one grid location. The scheme assigns the maximum value for the grid location to retain the largest equivalent reflector size for the location. The methodology is demonstrated and validated using a realistic ring of weld build-up. Tungsten balls and bars are embedded to the weld build-up during manufacturing process to represent natural flaws. Flat bottomed holes and side drilled holes are installed as artificial flaws. Automatic flaw identification and extraction are demonstrated. Results indicate the inspection procedure with multiple scan patterns can identify all the artificial and natural flaws.

42 ENGINEERING↗

Root angle in maize influences nitrogen capture and is regulated by calcineurin B-like protein (CBL)-interacting serine/threonine-protein kinase 15 ( ZmCIPK15 )

Crops with reduced nutrient and water requirements are urgently needed in global agriculture. Root growth angle plays an important role in nutrient and water acquisition. A maize diversity panel of 481 genotypes was screened for variation in root angle employing a high-throughput field phenotyping platform. Genome-wide association mapping identified several single nucleotide polymorphisms (SNPs) associated with root angle, including one located in the root expressed CBL-interacting serine/threonine-protein kinase 15 (ZmCIPK15) gene (LOC100285495). Reverse genetic studies validated the functional importance of ZmCIPK15, causing a approximately 10° change in root angle in specific nodal positions. A steeper root growth angle improved nitrogen capture in silico and in the field. OpenSimRoot simulations predicted at 40 days of growth that this change in angle would improve nitrogen uptake by 11% and plant biomass by 4% in low nitrogen conditions. In field studies under suboptimal N availability, the cipk15 mutant with steeper growth angles had 18% greater shoot biomass and 29% greater shoot nitrogen accumulation compared to the wild type after 70 days of growth. We propose that a steeper root growth angle modulated by ZmCIPK15 will facilitate efforts to develop new crop varieties with optimal root architecture for improved performance under edaphic stress.

59 BASIC BIOLOGICAL SCIENCES↗

Automatic learning-based beam angle selection for thoracic IMRT

Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationally efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume coverage and organ at risk sparing and were superior over plans produced with fixed sets of common beam angles. The great majority of the automatic plans (93%) were approved as clinically acceptable by three radiation therapy specialists. Conclusions: The results demonstrated the feasibility of utilizing a learning-based approach for automatic selection of beam angles in thoracic IMRT planning. The proposed method may assist in reducing the manual planning workload, while sustaining plan quality.

60 APPLIED LIFE SCIENCES↗

Mutation Detection with Next-Generation Resequencing through a Mediator Genome

The affordability of next generation sequencing (NGS) is transforming the field of mutation analysis in bacteria. The genetic basis for phenotype alteration can be identified directly by sequencing the entire genome of the mutant and comparing it to the wild-type (WT) genome, thus identifying acquired mutations. A major limitation for this approach is the need for an a-priori sequenced reference genome for the WT organism, as the short reads of most current NGS approaches usually prohibit de-novo genome assembly. To overcome this limitation we propose a general framework that utilizes the genome of relative organisms as mediators for comparing WT and mutant bacteria. Under this framework, both mutant and WT genomes are sequenced with NGS, and the short sequencing reads are mapped to the mediator genome. Variations between the mutant and the mediator that recur in the WT are ignored, thus pinpointing the differences between the mutant and the WT. To validate this approach we sequenced the genome of Bdellovibrio bacteriovorus 109J, an obligatory bacterial predator, and its prey-independent mutant, and compared both to the mediator species Bdellovibrio bacteriovorus HD100. Although the mutant and the mediator sequences differed in more than 28,000 nucleotide positions, our approach enabled pinpointing the single causative mutation. Experimental validation in 53 additional mutants further established the implicated gene. Our approach extends the applicability of NGS-based mutant analyses beyond the domain of available reference genomes.

60 APPLIED LIFE SCIENCES↗

UNF-ST&DARDS Enhancements for RCCA Data in As-loaded Dual Purpose Cask Models

This report summarizes the work performed to enable detailed modeling of rod cluster control assembly (RCCAs) in dual purpose canisters (DPCs) in as-loaded configurations using the Used Nuclear Fuel – Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS). The goal of this project was to evaluate the reactivity impact that RCCAs have on k eff of DPCs with pressurized water reactor (PWR) fuel to potentially use the additional margin in future post-closure criticality safety analysis. This preliminary evaluation determined the number of DPCs that currently require compensatory actions prior to emplacement in a repository because of their high reactivity under post-closure criticality scenarios, which could be made acceptable by including the as-loaded RCCAs as specified in the Unified Database (UDB). This report briefly describes the modeling methods currently used within UNF-ST&DARDS and the modifications made to automate inclusion of the as-loaded RCCAs in the DPCs for post-closure criticality calculations for the loss of neutron absorber (NA) scenarios, or NA models. For the Zion site, the loss of basket scenarios, or degraded basket (DB) models, are also included. Discussion is also provided regarding the UDB data compared to available site-specific loading map data for the sites, which are specifically evaluated herein. This report compares the modifications to a similar evaluation for the Zion by site conducted by Walker as an initial validation. After the partial validation, all existing PWR sites with applicable NA models within the UDB were evaluated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Recent technology products from Space Human Factors research

The goals of the NASA Space Human Factors program and the research carried out concerning human factors are discussed with emphasis given to the development of human performance models, data, and tools. The major products from this program are described, which include the Laser Anthropometric Mapping System; a model of the human body for evaluating the kinematics and dynamics of human motion and strength in microgravity environment; an operational experience data base for verifying and validating the data repository of manned space flights; the Operational Experience Database Taxonomy; and a human-computer interaction laboratory whose products are the display softaware and requirements and the guideline documents and standards for applications on human-computer interaction. Special attention is given to the 'Convoltron', a prototype version of a signal processor for synthesizing the head-related transfer functions.

Jenkins, James P.↗

Global 3-D Ionospheric Electron Density Reanalysis Based on Multisource Data Assimilation

We report preliminary results of a global 3-D ionospheric electron density reanalysis demonstration study during 2002-2011 based on multisource data assimilation. The monthly global ionospheric electron density reanalysis has been done by assimilating the quiet days ionospheric data into a data assimilation model constructed using the International Reference Ionosphere (IRI) 2007 model and a Kalman filter technique. These data include global navigation satellite system (GNSS) observations of ionospheric total electron content (TEC) from ground-based stations, ionospheric radio occultations by CHAMP, GRACE, COSMIC, SAC-C, Metop-A, and the TerraSAR-X satellites, and Jason-1 and 2 altimeter TEC measurements. The output of the reanalysis are 3-D gridded ionospheric electron densities with temporal and spatial resolutions of 1 h in universal time, 5deg in latitude, 10deg in longitude, and approx.30 km in altitude. The climatological features of the reanalysis results, such as solar activity dependence, seasonal variations, and the global morphology of the ionosphere, agree well with those in the empirical models and observations. The global electron content derived from the international GNSS service global ionospheric maps, the observed electron density profiles from the Poker Flat Incoherent Scatter Radar during 2007-2010, and foF2 observed by the global ionosonde network during 2002-2011 are used to validate the reanalysis method. All comparisons show that the reanalysis have smaller deviations and biases than the IRI-2007 predictions. Especially after April 2006 when the six COSMIC satellites were launched, the reanalysis shows significant improvement over the IRI predictions. The obvious overestimation of the low-latitude ionospheric F region densities by the IRI model during the 23/24 solar minimum is corrected well by the reanalysis. The potential application and improvements of the reanalysis are also discussed.

Xinan Yue↗

Real-Time Prognostics of a Rotary Valve Actuator

Valves are used in many domains and often have system-critical functions. As such, it is important to monitor the health of valves and their actuators and predict remaining useful life. In this work, we develop a model-based prognostics approach for a rotary valve actuator. Due to limited observability of the component with multiple failure modes, a lumped damage approach is proposed for estimation and prediction of damage progression. In order to support the goal of real-time prognostics, an approach to prediction is developed that does not require online simulation to compute remaining life, rather, a function mapping the damage state to remaining useful life is found offline so that predictions can be made quickly online with a single function evaluation. Simulation results demonstrate the overall methodology, validating the lumped damage approach and demonstrating real-time prognostics.

actuator↗

Estimating Evaporative Fraction From Readily Obtainable Variables in Mangrove Forests of the Everglades, U.S.A.

A remote-sensing-based model to estimate evaporative fraction (EF) the ratio of latent heat (LE; energy equivalent of evapotranspiration -ET-) to total available energy from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micro-meteorological and flux tower observations, or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature [T(sub s)] normalized difference vegetation index (NDVI)and daily maximum air temperature [T(sub a)]. The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using T(sub s) and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the T(sub s) from Landsat relative to the T(sub s) from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

trapezoid↗

Weathering the Storm: Unmanned Aircraft Systems in the Maritime, Atmospheric and Polar Environments

Remotely piloted aircraft (RPA) have the potential to revolutionize local to regional data collection for geophysicists as platform and payload size decrease while aircraft capabilities increase. In particular, data from RPAs combine high-resolution imagery available from low flight elevations with comprehensive areal coverage, unattainable from ground investigations and difficult to acquire from manned aircraft due to budgetary and logistical costs. Low flight elevations are particularly important for detecting signals that decay exponentially with distance, such as electromagnetic fields. Onboard data processing coupled with high-bandwidth telemetry open up opportunities for real-time and near real-time data processing, producing more efficient flight plans through the use of payload-directed flight, machine learning and autonomous systems. Such applications not only strive to enhance data collection, but also enable novel sensing modalities and temporal resolution. NASAs Airborne Science Program has been refining the capabilities and applications of RPA in support of satellite calibration and data product validation for several decades. In this paper, we describe current platforms, payloads, and onboard data systems available to the research community. Case studies include Fluid Lensing for littoral zone 3D mapping, structure from motion for terrestrial 3D multispectral imaging, and airborne magnetometry on medium and small RPAs.

data collection↗

Using Remotely Piloted Aircraft and Onboard Processing to Optimize and Expand Data Collection

Remotely piloted aircraft (RPA) have the potential to revolutionize local to regional data collection for geophysicists as platform and payload size decrease while aircraft capabilities increase. In particular, data from RPAs combine high-resolution imagery available from low flight elevations with comprehensive areal coverage, unattainable from ground investigations and difficult to acquire from manned aircraft due to budgetary and logistical costs. Low flight elevations are particularly important for detecting signals that decay exponentially with distance, such as electromagnetic fields. Onboard data processing coupled with high-bandwidth telemetry open up opportunities for real-time and near real-time data processing, producing more efficient flight plans through the use of payload-directed flight, machine learning and autonomous systems. Such applications not only strive to enhance data collection, but also enable novel sensing modalities and temporal resolution. NASA’s Airborne Science Program has been refining the capabilities and applications of RPA in support of satellite calibration and data product validation for several decades. In this paper, we describe current platforms, payloads, and onboard data systems available to the research community. Case studies include Fluid Lensing for littoral zone 3D mapping, structure from motion for terrestrial 3D multispectral imaging, and airborne magnetometry on medium and small RPAs.

Fladeland, Matthew M.↗

The Mars 2020 lander vision system field test

The Mars 2020 Lander Vision System estimates position relative to a map and provides this information to the spacecraft so that large hazards can be avoided during landing. The LVS is a new mission critical sensor and as such requires extensive validation. A field test conducted in May 2019 was the primary means to prove that the LVS will operate as designed. During this test over 600 independent real-time runs on engineering model LVS hardware and software were executed and clearly showed that it could meet a 40m position estimation requirement over a wide operational envelope. This paper will describe the test approach, operations and results. Specific examples as well as aggregate performance will be discussed along with off-nominal testing and fault recovery.

Montgomery, J.↗

The Mars 2020 Lander Vision System Field Test

The Mars 2020 Lander Vision System estimates position relative to a map and provides this information to the spacecraft so that large hazards can be avoided during landing. The LVS is a new mission critical sensor and as such requires extensive validation. A field test conducted in May 2019 was the primary means to prove that the LVS will operate as designed. During this test over 600 independent real-time runs on engineering model LVS hardware and software were executed and clearly showed that it could meet a 40m position estimation requirement over a wide operational envelope. This paper will describe the test approach, operations and results. Specific examples as well as aggregate per-formance will be discussed along with off-nominal testing and fault recovery.

Johnson, A.↗

A MAPS based vertex detector for the STAR experiment at RHIC

The STAR experiment at RHIC is in the process of upgrading the inner detector region of the experiment to improve the vertex resolution. We describe the current design of a MAPS based vertex detector, which is the innermost and highest resolution detector of the set of three planned upgrade detectors. This detector will enable the identification of decay vertices displaced from the interaction vertex by 100-150 {micro}m and extend the capabilities of the STAR detector in the heavy flavor domain. We present selected detector design characteristics and prototyping results, which help to validate the design in preparation for the construction of the detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sun Grant/DOE Regional Feedstock Partnership: Final Technical Report

The U.S. Department of Energy (DOE) and the Sun Grant Initiative initiated the Regional Feedstock Partnership (referred to as the Partnership) in 2007 primarily to address information gaps associated with the likelihood for realization of the sustainable and reliable production of a billion-tons of biomass annually to support the U.S. bioenergy industry by the year 2030. Publication of The Technical Feasibility of a Billion-Ton Annual Supply (Perlack et al., 2005) in 2005, with its associated yield assumptions, led to the realization that the yield goals and assumptions utilized in that analysis required careful validation. To achieve the overall goal of validating key yield assumptions, the following objectives were developed: 1. Establishment of replicated field trials across regions to determine the impact of crop residue removal (primarily corn and small grains) on future grain yields and soil health. 2. Establishment of replicated field trials of some of the most promising dedicated energy crops (herbaceous annuals and perennials, as well as woody perennials) to demonstrate the potential performance of these feedstocks across the U.S. 3. Assessment of feedstock resources to be used to estimate a sustainable national supply potential. Teams composed of representatives from Land Grant Universities, USDA ARS, DOE National Laboratories, industry, and other federal agencies were identified and assembled to address each of these objectives. For Objective 1, members of the USDA ARS’ Resilient Economic Agricultural Practices (REAP) team combined with university personnel to leverage on-going work and established new trials to determine sustainable corn residue removal rates. In addition, universities across the continental U.S. conducted surveys of published past research to define parameters for the use of cereal grain residue (primarily wheat) as a biomass feedstock. For Objective 2, and based on input from DOE, USDA, Land Grant university scientists, and others, several herbaceous and woody energy crop species were selected for new or further evaluation across wide geographic areas as cellulosic feedstock sources. Species teams were organized to assess the yield potential of candidate herbaceous feedstocks including sorghum, energycane, Miscanthus x giganteus (hereafter referred to as miscanthus), switchgrass, and mixed perennial species (primarily grasses and some legumes) on Conservation Reserve Program (CRP) land. Woody species will be critical components of the bioenergy sector; therefore, species teams were also organized for shrub willow and hybrid poplar (Populus spp.). Field trials of each species were utilized to determine yield potential across the U.S. For Objective 3, a GIS resource team was organized with representatives from each of the five Sun Grant regions. While some regional assessments were made, the multi-institutional team decided that the group from Oregon State University would utilize their PRISM ELM model to estimate national yield potential of the various species evaluated. The following are key outcomes and impacts • The Partnership demonstrated the production potential of diverse herbaceous and woody feedstocks across much of the U.S. for 5-7 consecutive growing seasons. Long-term studies such as this are not commonly possible due to limitations in funding cycles. • Long-term field trials were valuable in demonstrating the importance of agronomic management practices and genetic resources to yield of sorghum, switchgrass, miscanthus, energycane, CRP mixed perennial grasses, poplar, and willow. • National yield potential maps were developed for all species evaluated in the Partnership. • Sustainable corn stover removal rates were quantified for use by producers, harvesters, and commercial lignocellulosic biorefineries. • Data from the Partnership field trials not only validated initial Billion Ton estimates, but were instrumental in developing both the Billion Ton Update in 2011, and especially the 2016 Billion Ton Report. • The Partnership provided the opportunity to assemble and conserve a poplar germplasm collection that contains more than 20,000 clones for use in breeding programs. New clones resulting from crosses made using this germplasm collection have resulted in significantly improved cultivars that could be scaled up and deployed. • Further validation of improved yields of new varieties/cultivars of biomass sorghum, energycane, hybrid poplars, and shrub willows was produced by the Partnership. • The Partnership demonstrated the potential of energycane in northern parts of the southeastern U.S., particularly in relation to sugarcane varieties. • For certain feedstocks (e.g., CRP mixed grasses, switchgrass, willow, and poplar), production economics were ascertained through Partnership field trials. • Biomass samples collected as part of the Partnership are also being used to populate Idaho National Laboratory’s Bioenergy Feedstock Library. • Because of the size and scope of the Partnership, workforce development was a key component and outcome. Numerous undergraduate students (25), graduate students (15 MS and 8 PhD), and postdoctoral researchers (7) were trained by Partnership participants. This will help to prepare individuals for careers in the emerging fields of plant breeding, biomass production, feedstock supply logistics, and biomass conversion processes. • More than 130 scientific publications have been authored by Partnership team members. Numerous other presentations, outreach publications, book chapters, and websites have also been developed to further the continued development of the bioeconomy.

09 BIOMASS FUELS↗

Reactant conversion in homogeneous turbulence - Mathematical modeling, computational validations, and practical applications

The presently obtained closed-form analytical expressions, which predict the limiting rate of mean reactant conversion in homogeneous turbulent flows under the influence of a binary reaction, are derived via the single-point pdf method based on amplitude mapping closure. With this model, the maximum rate of the mean reactant's decay can be conveniently expressed in terms of definite integrals of the parabolic cylinder functions. The results obtained are shown to be in good agreement with data generated by direct numerical simulations.

Madnia, C. K.↗