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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

GPS Global Tracking Network Operations At JPL During the 1992 IGS Experiment and Beyond

The GPS Network Operations center at JPL Provides resources for the collection, distribution and maintenance of GPS data from global network of GPS receivers. This includes the ability to remotely diagnosis receiver problems, communicate with receivers and operators of receivers, to automatically collect, process and distribute data for 14 stations in the IGS network. This amounts to 35 megabytes of raw, finished data and products daily.

GPS receiver Global Network↗
DOE OSTI2025

Comprehensive Analysis of the Relative Dispersion of Droplet-Size Distributions and Their Relationships to Key Physical Fog Processes Under Different Aerosol Conditions and Evolutionary Stages

The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects, radiative transfer, and microphysical processes. However, previous studies have been mostly concerned with clouds, with limited studies on fog, particularly those that examine the combined influences of all key physical processes and their roles during fog evolution. As such, this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables, as well as the underlying microphysical and dynamic processes, based on field fog campaigns in polluted and clean conditions. In polluted fog, droplet concentrations are higher, leading to smaller droplets and increased dispersion. The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog, but shifts to negative in clean fog. Here, we attribute the difference to various microphysical processes like aerosol activation, condensation, collision-coalescence, and entrainment-mixing. In polluted fog, high aerosol concentrations, low supersaturations, and strong turbulence (entrainment-mixing) provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation, resulting in a positive correlation between dispersion and volume-mean radius, especially during the fog formation stage. In contrast, during the mature stage in clean fog, condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius. The collision-coalescence process is more active in the mature stage, increasing radii and leading to the negative correlation between dispersion and volume-mean radius. This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Life-Cycle Analysis of Shale Gas and Natural Gas

The technologies and practices that have enabled the recent boom in shale gas production have also brought attention to the environmental impacts of its use. Using the current state of knowledge of the recovery, processing, and distribution of shale gas and conventional natural gas, we have estimated up-to-date, life-cycle greenhouse gas emissions. In addition, we have developed distribution functions for key parameters in each pathway to examine uncertainty and identify data gaps - such as methane emissions from shale gas well completions and conventional natural gas liquid unloadings - that need to be addressed further. Our base case results show that shale gas life-cycle emissions are 6% lower than those of conventional natural gas. However, the range in values for shale and conventional gas overlap, so there is a statistical uncertainty regarding whether shale gas emissions are indeed lower than conventional gas emissions. This life-cycle analysis provides insight into the critical stages in the natural gas industry where emissions occur and where opportunities exist to reduce the greenhouse gas footprint of natural gas.

03 NATURAL GAS↗
NASA NTRS2014

VARED: Verification and Analysis of Requirements and Early Designs

Requirements are a part of every project life cycle; everything going forward in a project depends on them. Good requirements are hard to write, there are few useful tools to test, verify, or check them, and it is difficult to properly marry them to the subsequent design, especially if the requirements are written in natural language. In fact, the inconsistencies and errors in the requirements along with the difficulty in finding these errors contribute greatly to the cost of the testing and verification stage of flight software projects [1]. Large projects tend to have several thousand requirements written at various levels by different groups of people. The design process is distributed and a lack of widely accepted standards for requirements often results in a product that varies widely in style and quality. A simple way to improve this would be to standardize the design process using a set of tools and widely accepted requirements design constraints. The difficulty with this approach is finding the appropriate constraints and tools. Common complaints against the tools available include ease of use, functionality, and available features. Also, although preferable, it is rare that these tools are capable of testing the quality of the requirements.

Badger, Julia↗
NASA NTRS1972

Solution of the Boltzmann kinetic equation for the relaxation of a gas mixture

The temporal behavior is considered of a quiescent mixture of gases of different temperatures with spatially uniform distribution. The process of heating a cold gas by a hot gas is treated on the basis of the Boltzmann kinetic equation. The mixture is assumed to be composed of absolutely hard smooth spheres, and the initial distribution functions for each gas is taken to the Maxwellian. With such a choice of initial distribution functions, it is shown that the solution of the Boltzmann kinetic equation depends only on the velocity modulus and the time.

Rykov, V. A.↗
DOE OSTI2024

Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data

The paper presents the development of algorithms for mass and energy constrained neural network models that can exactly conserve the overall mass and energy of distributed chemical process systems, even though the noisy transient data used for optimal model training violate the same. In contrast to approximately satisfying mass and energy balance constraints of a system by soft penalization of objective function, algorithms have been developed for solving equality-constrained nonlinear optimization problems, thus providing the guarantee of exactly satisfying the system mass and energy conservation laws. For developing dynamic mass-energy constrained network models for distributed systems, hybrid series and parallel dynamic-static neural networks have been leveraged. The developed algorithms for solving both the training and forward problems are validated using both steady-state and dynamic data in the presence of various noise characteristics. The developed data-driven algorithms are flexible to exactly satisfy mass and energy balance constraints for dynamic chemical processes if the system holdup information is available. The proposed network structures and algorithms are applied to the development of data-driven lumped and distributed models of an adiabatic superheater/reheater system, a nonisothermal continuous stirred tank reactor, as well as an electrically heated plug-flow reactor system where one form of energy gets transformed to another. It has been observed that the mass-energy constrained neural networks yield a root mean squared error of <1% with respect to the system truth for the case studies evaluated in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Estimation of the processes controlling variability in phytoplankton pigment distributions on the southeastern U.S. continental shelf

Five coastal-zone-color-scanner images from the southeastern U.S. continental shelf are combined with concurrent moored current meter measurements to assess the processes controlling the variability in chlorophyll concentration and distribution in this region. An equation governing the space and time distribution of a nonconservative quantity such as chlorophyll is used in the calculations. The terms of the equation, estimated from observations, show that advective, diffusive, and local processes contribute to the plankton distributions and vary with time and location. The results from this calculation are compared with similar results obtained using a numerical physical-biological model with circulation fields derived from an optimal interpolation of the current meter observations and it is concluded that the two approaches produce different estimates of the processes controlling phytoplankton variability.

Mcclain, Charles R.↗
DOE OSTI2016

Sensitivity study for s process nucleosynthesis in AGB stars

In this paper we present a large-scale sensitivity study of reaction rates in the main component of the s process. The aim of this study is to identify all rates, which have a global effect on the s process abundance distribution and the three most important rates for the production of each isotope. We have performed a sensitivity study on the radiative {sup 13}C-pocket and on the convective thermal pulse, sites of the s process in AGB stars. We identified 22 rates, which have the highest impact on the s-process abundances in AGB stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1993

On-board B-ISDN fast packet switching architectures. Phase 2: Development. Proof-of-concept architecture definition report

For the next-generation packet switched communications satellite system with onboard processing and spot-beam operation, a reliable onboard fast packet switch is essential to route packets from different uplink beams to different downlink beams. The rapid emergence of point-to-point services such as video distribution, and the large demand for video conference, distributed data processing, and network management makes the multicast function essential to a fast packet switch (FPS). The satellite's inherent broadcast features gives the satellite network an advantage over the terrestrial network in providing multicast services. This report evaluates alternate multicast FPS architectures for onboard baseband switching applications and selects a candidate for subsequent breadboard development. Architecture evaluation and selection will be based on the study performed in phase 1, 'Onboard B-ISDN Fast Packet Switching Architectures', and other switch architectures which have become commercially available as large scale integration (LSI) devices.

Shyy, Dong-Jye↗
NASA NTRS1996

Maximum ADPE Approach for a High Rate CCSDS Return Link Processing System

The earth observing system data and operations system (EDOS) multi-mission data processing and distribution system for the earth observing system is considered. The EDOS was based on the Consultative Committee for Space Data Systems (CCSDS) protocols. The development included the challenge of developing and demonstrating a 150 Mbps CCSDS return link processing capability for the support of the first EDOS delivery. The approach used general-purpose automated data processing equipment (ADPE) and minimized the use of customized hardware. The way in which the system was developed is described. The principle design decisions and the performance benchmark results are presented.

Krimchansky, Alexander↗
NASA NTRS2008

Orchestrator Telemetry Processing Pipeline

Orchestrator is a software application infrastructure for telemetry monitoring, logging, processing, and distribution. The architecture has been applied to support operations of a variety of planetary rovers. Built in Java with the Eclipse Rich Client Platform, Orchestrator can run on most commonly used operating systems. The pipeline supports configurable parallel processing that can significantly reduce the time needed to process a large volume of data products. Processors in the pipeline implement a simple Java interface and declare their required input from upstream processors. Orchestrator is programmatically constructed by specifying a list of Java processor classes that are initiated at runtime to form the pipeline. Input dependencies are checked at runtime. Fault tolerance can be configured to attempt continuation of processing in the event of an error or failed input dependency if possible, or to abort further processing when an error is detected. This innovation also provides support for Java Message Service broadcasts of telemetry objects to clients and provides a file system and relational database logging of telemetry. Orchestrator supports remote monitoring and control of the pipeline using browser-based JMX controls and provides several integration paths for pre-compiled legacy data processors. At the time of this reporting, the Orchestrator architecture has been used by four NASA customers to build telemetry pipelines to support field operations. Example applications include high-volume stereo image capture and processing, simultaneous data monitoring and logging from multiple vehicles. Example telemetry processors used in field test operations support include vehicle position, attitude, articulation, GPS location, power, and stereo images.

Powell, Mark↗
DOE OSTI2022

Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm

Abstract Droplet-level interactions in clouds are often parameterized by a modified gamma fitted to a “global” droplet size distribution. Do “local” droplet size distributions of relevance to microphysical processes look like these average distributions? This paper describes an algorithm to search and classify characteristic size distributions within a cloud. The approach combines hypothesis testing, specifically, the Kolmogorov–Smirnov (KS) test, and a widely used class of machine learning algorithms for identifying clusters of samples with similar properties: density-based spatial clustering of applications with noise (DBSCAN) is used as the specific example for illustration. The two-sample KS test does not presume any specific distribution, is parameter free, and avoids biases from binning. Importantly, the number of clusters is not an input parameter of the DBSCAN-type algorithms but is independently determined in an unsupervised fashion. As implemented, it works on an abstract space from the KS test results, and hence spatial correlation is not required for a cluster. The method is explored using data obtained from the Holographic Detector for Clouds (HOLODEC) deployed during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The algorithm identifies evidence of the existence of clusters of nearly identical local size distributions. It is found that cloud segments have as few as one and as many as seven characteristic size distributions. To validate the algorithm’s robustness, it is tested on a synthetic dataset and successfully identifies the predefined distributions at plausible noise levels. The algorithm is general and is expected to be useful in other applications, such as remote sensing of cloud and rain properties. Significance Statement A typical cloud can have billions of drops spread over tens or hundreds of kilometers in space. Keeping track of the sizes, positions, and interactions of all of these droplets is impractical, and, as such, information about the relative abundance of large and small drops is typically quantified with a “size distribution.” Droplets in a cloud interact locally, however, so this work is motivated by the question of whether the cloud droplet size distribution is different in different parts of a cloud. A new method, based on hypothesis testing and machine learning, determines how many different size distributions are contained in a given cloud. This is important because the size distribution describes processes such as cloud droplet growth and light transmission through clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Fickian dispersion is anomalous

The thesis put forward here is that the occurrence of Fickian dispersion in geophysical settings is a rare event and consequently should be labeled as anomalous. What people classically call anomalous is really the norm. In a Lagrangian setting, a process with mean square displacement which is proportional to time is generally labeled as Fickian dispersion. With a number of counter examples we show why this definition is fraught with difficulty. In a related discussion, we show an infinite second moment does not necessarily imply the process is super dispersive. By employing a rigorous mathematical definition of Fickian dispersion we illustrate why it is so hard to find a Fickian process. We go on to employ a number of renormalization group approaches to classify non-Fickian dispersive behavior. Scaling laws for the probability density function for a dispersive process, the distribution for the first passage times, the mean first passage time, and the finite-size Lyapunov exponent are presented for fixed points of both deterministic and stochastic renormalization group operators. The fixed points of the renormalization group operators are p-self-similar processes. A generalized renormalization group operator is introduced whose fixed points form a set of generalized self-similar processes. Finally, power-law clocks are introduced to examine multi-scaling behavior. Several examples of these ideas are presented and discussed.

58 GEOSCIENCES↗
NASA NTRS1991

Studies of volatiles and organic materials in early terrestrial and present-day outer solar system environments

A review and partial summary of projects within several areas of research generally involving the origin, distribution, chemistry, and spectral/dielectric properties of volatiles and organic materials in the outer solar system and early terrestrial environments are presented. The major topics covered include: (1) impact delivery of volatiles and organic compounds to the early terrestrial planets; (2) optical constants measurements; (3) spectral classification, chemical processes, and distribution of materials; and (4) radar properties of ice, hydrocarbons, and organic heteropolymers.

Sagan, Carl↗
DOE OSTI2026

An Integrated Modeling Framework for Sediment Dynamics During Urban Flooding: Application to Hurricane Harvey in Houston

Floodwater can mobilize and redistribute large volumes of sediment from upland to downstream urban areas, threatening infrastructure, water quality, and ecosystem health. However, existing modeling approaches often fail to capture sediment dynamics in urban floodplains due to the lack of integration between upland hydrological processes and riverine sediment transport. This study presents the first integrated modeling framework that couples the Energy Exascale Earth System Model (E3SM) land component, which simulates runoff and hillslope erosion, with TELEMAC-GAIA, a two-dimensional hydrodynamic and sediment transport model. This framework enables the fully distributed, process-based simulation of high-resolution (as fine as 30 m) sediment dynamics from hillslopes to floodplains. Applied to a highly urbanized watershed in Houston during Hurricane Harvey, this framework reproduced observed water levels at 16 USGS gauges (median R 2 = 0.83 and KGE = 0.78), key sediment dynamics such as sediment transport and deposition processes, and reproduced spatial deposition patterns consistent with LiDAR-derived data. Based on the simulation, we estimate 8.0 million m 3 of event-scale sediment deposition, including 5.7 million m 3 trapped in the flood-control reservoirs and 2.3 million m 3 deposited along major channels and floodplains. Using a representative unit removal cost, this corresponds to an estimated dredging cost of $581 million for total deposition. These results provide a first-order, physically based quantification of Harvey-scale sediment impacts. This study provides a valuable tool for the holistic analysis of sediment dynamics triggered by extreme urban flooding, supporting flood-resilience planning. More broadly, it highlights the importance of integrating physically based hydrological processes for urban flooding and sediment research.

Hurricane Harvey↗
DOE OSTI2015

Using spatial statistical methods to determine an effective minimum detectable activity - 15681

Instrument minimum detectable activity (MDA) is generally established by collecting multiple measurements over time of a single representative background location to estimate a probability distribution of instrument readings. A reading that is considered to be greater than would be expected from the background probability distribution (i.e., a low-probability event) is deemed to be sufficiently unlikely that it must be attributable to added radioactivity and is therefore used as the instrument MDA. An effective MDA can be determined from spatially distributed data that are much lower than the instrument MDA. This has been accomplished using a large number of spatially distributed data points (from a radiation survey) where patterns of elevated survey readings can be distinguished from background at levels. Given the variation of the instrument response and the relatively low regulatory action levels, it is vital to establish MDA thresholds that are well below corrective action levels. Processing of radiological survey data with the use of histogram binning and geo-statistics in enabling pattern recognition can be used to establish effective field MDAs that are much lower than instrument MDAs. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2011

Modification of Particle Distributions by MHD Instabilities II

The modification of particle distributions by low amplitude magnetohydrodynamic modes is an important topic for magnetically confined plasmas. Low amplitude modes are known to be capable of producing significant modification of injected neutral beam profiles, and the same can be expected in burning plasmas for the alpha particle distributions. Flattening of a distribution in an island due to phase mixing and portions of phase space becoming stochastic lead to modification of the particle distribution, a process extremely rapid in the time scale of an experiment but still very long compared to the time scale of guiding center simulations. Large amplitude modes can cause profile avalanche and particle loss. Thus it is very valuable to be able to predict the temporal evolution of a particle distribution produced by a given spectrum of magnetohydrodynamic modes. In this paper we further develop and investigate the use of a new method of determining domains of phase space in which good KAM surfaces do not exist and use this method to examine a well documented case of profile modification by instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1979

Comparison of calculated and measured ion densities on the dayside of Venus

Data from the Pioneer Venus ion mass spectrometers are compared with model calculations of the ion density distributions appropriate for daytime conditions. The model assumes diffusive equilibrium upper boundary conditions for the major ions (O2(+), O(+), CO2(+), He(+), and H(+)); the agreement between the calculated and measured gross behavior of these ions is reasonably good except for H(+), which may be influenced strongly by convective transport processes. The distributions of five minor ions (C(+), N(+), NO(+), CO(+), and N2(+)) are also calculated for the chemically controlled region (less than approximately 200 km); the agreements are, in general, poor, an indication that the present understanding of the Venus minor ion chemistry is still incomplete.

Nagy, A. F.↗