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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.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Representing the Sub-Grid Heterogeneity of Surface Precipitation in A General Circulation Model

Precipitation variability on spatial scales smaller than a typical general circulation model (GCM) grid box is often neglected, with the grid-mean precipitation rate being applied uniformly to underlying surface tiles. This reduces the extrema seen by the surface, with corresponding reductions in surface runoff and altered land-atmosphere fluxes. Here we present a novel approach to stochastically distribute precipitation across sub-grid surface tiles within a GCM. Based on 4 km Stage IV precipitation data, the scheme parameterizes the dry area fraction as a function of grid mean precipitation rate, and defines the relative distribution of intensities across non-dry surface tiles. To incorporate memory and mimic the persistence of precipitating storms, the relative intensity assigned to each sub-grid tile is determined by an autoregressive process. Using single column experiments, the scheme is shown to reproduce observed precipitation statistics at the scale of model surface tiles. We also document impacts on surface hydrology and energy partitioning, with notable increases in precipitation runoff, surface temperature variance, and the Bowen ratio.

GCM↗
DOE OSTI2021

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows

While in-situ workflow formulations have addressed some of the data-related challenges associated with extreme-scale scientific workflows, these workflows involve complex interactions and different modes of data exchange. In the context of increasing system complexity, such workflows present significant resource management challenges, requiring complex cost-performance tradeoffs. This paper presents RISE, an intelligent staging-based data management middleware, which builds on the DataSpaces framework and performs intelligent scheduling of data management operations to reduce I/O contention. In RISE, data are always written immediately to local buffers to reduce the effect of the transfer impact upon application performance. RISE identifies applications’ data access patterns and moves data towards data consumers only when the network is expected to be idle, reducing the impact of asynchronous background data movement upon critical data read/write requests. Here, we experimentally demonstrate that RISE can take advantage of staging nodes to offload data during writes without degrading application data movement performance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

International Satellite Cloud Climatology Project (ISCCP) Stage D1 3-Hourly Cloud Product - Revised Algorithm in Hierarchical Data Format (ISCCP_D1)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=TROPOSPHERE] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=280 Km; Longitude_Resolution=280 Km; Temporal_Resolution=3 Hourly].

CLOUD LIQUID WATER PATH↗
NASA NTRS1972

Skylab 2 space vehicle data evaluation guide

Vehicle telemetry measurements for all stages of Skylab 2 are presented. The data sources for the launch vehicle and command service module are identified. The data evaluation guide format is described. The system for designating the components of the spacecraft is defined. A list of abbreviations for technical terms used in the reporting documents is included.

Source record↗
NASA NTRS1977

Acoustic and aerodynamic performance of a variable-pitch 1.83-meter-(6-ft) diameter 1.20-pressure-ratio fan stage (QF-9)

Far field noise data and related aerodynamic performance are presented for a variable pitch fan stage having characteristics suitable for low noise, STOL engine application. However, no acoustic suppression material was used in the flow passages. The fan was externally driven by an electric motor. Tests were made at several forward thrust rotor blade pitch angles and one for reverse thrust. Fan speed was varied from 60 to 120 percent of takeoff (design) speed, and exhaust nozzles having areas 92 to 105 percent of design were tested. The fan noise level was at a minimum at the design rotor blade pitch angles of 64 deg for takeoff thrust and at 57 deg for approach (50 percent takeoff thrust). Perceived noise along a 152.4-m sideline reached 100.1 PNdb for the takeoff (design) configuration for a stage pressure ratio of 1.17 and thrust of 57,600 N. For reverse thrust the PNL values were 4 to 5 PNdb above the takeoff values at comparable fan speeds.

Glaser, F. W.↗
DOE OSTI2021

Fourier Neural Networks as Function Approximators and Differential Equation Solvers

We present a Fourier neural network (FNN) that can be mapped directly to the Fourier decomposition. The choice of activation and loss function yields results that replicate a Fourier series expansion closely while preserving a straightforward architecture with a single hidden layer. The simplicity of this network architecture facilitates the integration with any other higher-complexity networks, at a data pre- or postprocessing stage. We validate this FNN on naturally periodic smooth functions and on piecewise continuous periodic functions. We showcase the use of this FNN for modeling or solving partial differential equations with periodic boundary conditions. The main advantages of the current approach are the validity of the solution outside the training region, interpretability of the trained model, and simplicity of use.

Fourier decomposition↗
NASA NTRS1978

Fast processing of data from Sneg-2MP experiment

The following subjects are covered: Basic stages during computer processing of data from Sneg-2MP instrument, basic modes during separation and fast processing (separation of data during satellite flight, separation of burst data segments, sampling and analysis of initial burst data segment). Experimental results obtained on the basis of fast processed data are reported.

Dumer, I. I.↗
DOE OSTI2022

Adaptive elasticity policies for staging-based in situ visualization

In situ processing aims to alleviate the growing gap between computation and I/O capabilities by performing data processing close to the data source. In situ processing is widely used to process data generated by multiple data sources, including observation data from edge devices or scientific observational facilities and the simulation data generated by scientific computation on a high-performance computing (HPC) platform. For a scientific workflow that is run on an HPC platform and composed of a simulation program and an in situ data analytics or visualization (abbreviated as ana/vis) task, there is an implicit assumption that the computing resources assigned to the workflow keep static during the workflow execution. However, with the converging trend between the HPC and cloud computing platform, running the in situ ana/vis task in an elastic way is promising to decrease its overhead and improve its resource utilization rate. Resource elasticity represents the ability to change resource configurations such as the number of computing nodes/processes during workflow execution. An elastic job may dynamically adjust resource configurations; it may use a few resources at the beginning and more resources toward the end of the job when interesting data appear. However, it is hard to predict a priori how many computing nodes/processes need to be added/removed during the workflow execution to adapt to changing workflow needs. How to efficiently guide elasticity operations, such as growing or shrinking the number of processes used for in situ analysis during workflow execution, is an open-ended research question. In this article, we present adaptive elasticity policies that adopt workflow runtime information collected during workflow execution to predict how to trigger the addition/removal of processes in order to minimize in situ processing overhead. Taking in situ visualization tasks as an example, we integrate the presented elasticity policies into a staging-based elastic workflow and evaluate its efficiency in multiple elasticity scenarios. Compared with the situation without elasticity or with a static elasticity policy that uses a fixed number of processes for each rescaling operation, the adaptive elasticity policy can save overhead in finding a proper resource configuration and improve resource utilization efficiency. Furthermore, one experiment illustrates that the adaptive elasticity policy saves 41% of core-hours compared with the situation without the resource elasticity.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1977

Remote sensing of wetlands

The concept of using remote sensing to inventory wetlands and the related topics of proper inventory design and data collection are discussed. The material presented shows that aerial photography is the form of remote sensing from which the greatest amount of wetlands information can be derived. For extensive, general-purpose wetlands inventories, however, the use of LANDSAT data may be more cost-effective. Airborne multispectral scanners and radar are, in the main, too expensive to use - unless the information that these sensors alone can gather remotely is absolutely required. Multistage sampling employing space and high altitude remote sensing data in the initial stages appears to be an efficient survey strategy for gathering non-point specific wetlands inventory data over large areas. The operational role of remote sensing insupplying inventory data for application to several typical wetlands management problems is illustrated by summary descriptions of past ERIM projects.

Roller, N. E. G.↗
DOE OSTI2024

First test results of the HGCAL concentrator ASICs: ECON-T and ECON-D

With over 6 million channels, the High Granularity Calorimeter for the CMS HL-LHC upgrade presents a unique data transmission challenge. The ECON ASICs provide a critical stage of on-detector data compression and selection for the trigger path (ECON-T) and data acquisition path (ECON-D) of the HGCAL. The ASICs, fabricated in 65 nm CMOS, are radiation tolerant up to 200 Mrad and require low power consumption: < 2.5 mW/sensor-channel per chip. Here, we report on the first functionality and radiation tests for the ECON-D-P1 full-functionality prototype. We present a comparison of single event effect (SEE) cross sections measured for different methods of triple modular redundancy using test results from the ECON-T-P1 full-functionality prototype.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Enhancing NASA Earth Science Data Discovery from Scientific Publications

Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.

Irina V Gerasimov↗
DOE OSTI2023

High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Method to Segment Overlapping Plants

High-throughput plant phenotyping—the use of imaging and remote sensing to record plant growth dynamics—is becoming more widely used. The first step in this process is typically plant segmentation, which requires a well-labeled training dataset to enable accurate segmentation of overlapping plants. However, preparing such training data is both time and labor intensive. To solve this problem, we propose a plant image processing pipeline using a self-supervised sequential convolutional neural network method for in-field phenotyping systems. This first step uses plant pixels from greenhouse images to segment nonoverlapping in-field plants in an early growth stage and then applies the segmentation results from those early-stage images as training data for the separation of plants at later growth stages. The proposed pipeline is efficient and self-supervising in the sense that no human-labeled data are needed. We then combine this approach with functional principal components analysis to reveal the relationship between the growth dynamics of plants and genotypes. We show that the proposed pipeline can accurately separate the pixels of foreground plants and estimate their heights when foreground and background plants overlap and can thus be used to efficiently assess the impact of treatments and genotypes on plant growth in a field environment by computer vision techniques. This approach should be useful for answering important scientific questions in the area of high-throughput phenotyping.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Evaluation of D-1 tape and cassette characteristics: Moisture content of Sony and Ampex D-1 tapes when delivered

Commercial D-1 cassette tapes and their associated recorders were designed to operate in broadcast studios and record in accordance with the International Radio Consultative Committee (CCIR) 607 digital video standards. The D-1 recorder resulted in the Society of Motion Picture and Television Engineers (SMPTE) standards 224 to 228 and is the first digital video recorder to be standardized for the broadcast industry. The D-1 cassette and associated media are currently marketed for broadcast use. The recorder was redesigned for data applications and is in the early stages of being evaluated. The digital data formats used are specified in MIL-STD-2179 and the American National Standards Institute (ANSI) X3.175-190 standard. In early 1990, the National Media Laboratory (NML) was asked to study the effects of time, temperature, and relative humidity on commercial D-1 cassettes. The environmental range to be studied was the one selected for the Advanced Tactical Air Reconnaissance System (ATARS) program. Several discussions between NML personnel, ATARS representatives, recorder contractors, and other interested parties were held to decide upon the experimental plan to be implemented. Review meetings were held periodically during the course of the experiment. The experiments were designed to determine the dimensional stability of the media and cassette since this is one of the major limiting factors of helical recorders when the media or recorders are subjected to non-broadcasting environments. Measurements were also made to characterize each sample of cassettes to give preliminary information on which purchase specifications could be developed. The actual tests performed on the cassettes and media before and after aging fall into the general categories listed.

Ashton, Gary↗
NASA NTRSDate not supplied

A Study of the Swelling and Bursting of the High Pressure Coupling (HPC) of a Two-Stage Light Gas Gun

• Need for data at muzzle velocities of 7.0 km/s and above to simulate impacts of space debris and naturally occurring meteoroids • The two-stage light gas gun is a well known way of achieving these velocities • There is a danger of significant swelling and even bursting of the HPC (high pressure coupling). • A consistent picture of the swelling and bursting of the HPCs of two Ames two-stage light gas guns is developed, based on the following: 1. Experimental measurements of the swelling and bursting of the HPCs of two two-stage light gas guns. 2. Stress-strain calculations of the swelling and bursting of thick walled steel tubes. 3. Experimental measurements swelling and bursting of thick walled steel tubes. 4. CFD calculations of the maximum pressures in the HPC of a two-stage light gas gun using the code LGGUN. • It is shown that model developed predicts swelling and bursting that agrees reasonably well with measured data. • Hence, it is suggested that the model could be used in the design of a two-stage light gas guns to assess the risk of swelling and bursting and to give maximum suggested operating conditions for an existing gun.

Ballistic Range↗