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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Effect of Dust Coagulation Dynamics on the Geometry of Aggregates

Master equation gives a more fundamental description of stochastic coagulation processes rather than popular Smoluchowski's equation. In order to examine the effect of the dynamics on the geometry of resulting aggregates, we study Master equation with a rigorous Monte Carlo algorithm. It is found that Cluster-Cluster aggregation model is a good approximation of orderly growth and the aggregates have fluffy structures with a fractal dimension approx. 2. A scaling analysis of Smoluchowski's equation also supports this conclusion.

Nakamura, R.↗
NASA NTRS1997

Cluster Observations for Combined X-Ray and Sunyaev-Zel'dovich Estimates of Peculiar Velocities and Distances

Measurements of the peculiar velocities of galaxy clusters with respect to the Hubble flow allow the determination of the gravitational field from all matter in the universe, not just the visible component. The Sunyaev-Zel'dovich (SZ) effect (the inverse-Compton scattering of cosmic microwave background photons by the hot gas in clusters of galaxies) allows these velocities to be measured without the use of empirical distance indicators. Additionally, because the magnitude of the SZ effect is independent of redshift, the technique can be used to measure velocities out to the epoch of cluster formation. The SZ technique requires a determination of the temperature of the hot cluster gas from X-ray observations, and measurements of the SZ effect at millimeter wavelengths to separate the contribution from the thermal motions within the gas from that of the cluster peculiax velocity. We have constructed a bolometric receiver, the Sunyaev-Zel'dovich Infrared Experiment, specifically to make measurements of the SZ effect at millimeter wavelengths in order to apply the SZ technique to peculiar velocity measurements. This receiver has already been used to set limits to the peculiar velocities of two galaxy clusters at z approx. 0.2. As a test of the SZ technique, the double cluster pair Abell 222 and 223 was selected for observation. Measurements of the redshifts of the two components suggest that, if the clusters are gravitationally bound, they should exhibit a relative velocity of 10OO km/ s, well above the expected precision of 200 km/ s (set by astrophysical confusion) that is expected from the SZ method. The temperature can be measured from ASCA data which we obtained for this cluster pair. However, in order to ensure that the temperature estimate from the ASCA data was not dominated by cooling flows within the cluster, we requested ROSAT HRI observations of this cluster pair. Analysis of the X-ray properties of the cluster pair is continuing by combining the ROSAT observations funded under this proposal, archival PSPC data and our own PI ASCA data. The imaging data shows that neither cluster has a strong cooling flow, although A223 is the more compact of the two components. A223 also has a sub-cluster projected 1 Mpc to the North. The observed properties of this cluster pair are strikingly similar to those of the well-studied pair of A399 and A401 which are widely believed to be interacting and are in the initial stages of merging. This strengthens our selection of this cluster pair as a test for cluster peculiar motions. Combining these X-ray observations with SUZIE measurements of the SZ effect will provide important constraints on cluster merger models. This part of the program has been heavily delayed by bad weather at Mauna Kea, however SZ observations were obtained in November 1997 as part of a separately funded effort. These data are currently being analyzed.

Lange, A. E.↗
NASA NTRS2004

The Physical Properties of Intracluster Gas at z > 1

We have used XMM-Newton, Chandra and HST/ACS data on one of the most distant clusters known to date, RDCS1252-29 at z= 1.24, to measure the mass of its baryonic and dark components for the first time at these large redshifts. By comparing physical properties of cluster galaxies and of the X-ray emitting intra-cluster medium (including the iron abundance) with those in low-redshift clusters, we have found that little evolution has taken place over 60% of the lifetime of the Universe. This suggests that most of the stars formed at z>approx.3 and metal enrichment processes took place early in the evolutionary history of galaxy clusters. These findings have a strong bearing on galaxy and cluster evolution models.

Rosati, Piero↗
NASA NTRS2008

Benchmark Comparison of Dual- and Quad-Core Processor Linux Clusters with Two Global Climate Modeling Workloads

This viewgraph presentation details the science and systems environments that NASA High End computing program serves. Included is a discussion of the workload that is involved in the processing for the Global Climate Modeling. The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models integrated using the Earth System Modeling Framework (ESMF). The GEOS-5 system was used for the Benchmark tests, and the results of the tests are shown and discussed. Tests were also run for the Cubed Sphere system, results for these test are also shown.

McGalliard, James↗
NASA NTRS2011

Infrared Spectroscopy of Naphthalene Aggregation and Cluster Formation in Argon Matrices

Fourier-transform mid-infrared absorption spectra of mixed argon/naphthalene matrices at 5 K are shown with ratios of argon-to-naphthalene that vary from 1000 to 0. These spectra show the changes as naphthalene clustering and aggregation occurs, with moderate spectral shifts affecting the C-H vibrational modes and relatively small or no shifts to the C-C and C-C-C vibrational modes. The possible contribution of homogeneous naphthalene clusters to the interstellar unidentified infrared bands is discussed. The contribution of polycyclic aromatic hydrocarbon (PAH) clusters to the 7.7 micron emission plateau and the blue shading of the 12.7 micron emission band are identified as promising candidates for future research. In addition, since PAH clusters are model components of Jupiter and Titan's atmospheres, the information presented here may also be applicable to the spectroscopy of these objects.

Roser, J. E.↗
NASA NTRS2017

An Orbital Meteoroid Stream Survey Using the Southern Argentina Agile Meteor Radar (SAAMER) Based on a Wavelet Approach

Over a million individually measured meteoroid orbits were collected with the Southern Argentina Agile MEteor Radar (SAAMER) between 2012-2015. This provides a robust statistical database to perform an initial orbital survey of meteor showers in the Southern Hemisphere via the application of a 3D wavelet transform. The method results in a composite year from all 4 years of data, enabling us to obtain an undisturbed year of meteor activity with more than one thousand meteors per day. Our automated meteor shower search methodology identified 58 showers. Of these showers, 24 were associated with previously reported showers from the IAU catalogue while 34 showers are new and not listed in the catalogue. Our searching method combined with our large data sample provides unprecedented accuracy in measuring meteor shower activity and description of shower characteristics in the Southern Hemisphere. Using simple modeling and clustering methods we also propose potential parent bodies for the newly discovered showers.

Meteor showers↗
NASA NTRS1999

Climate Ocean Modeling on a Beowulf Class System

With the growing power and shrinking cost of personal computers, the availability of fast ethernet interconnections, and public domain software packages, it is now possible to combine them to build desktop parallel computers at a fraction of what it would cost to buy systems of comparable power from supercomputer companies.

Beowulf↗
NASA NTRSDate not supplied

Unsupervised Change Detection for Space Habitats Using 3D Point Clouds

This work presents an algorithm for scene change detection from point clouds to enable autonomous robotic caretaking in future space habitats. Autonomous robotic systems will help maintain future deep-space habitats, such as the Gateway space station, which will be uncrewed for extended periods. Existing scene analysis software used on the International Space Station (ISS) relies on manually-labeled images for detecting changes. In contrast, the algorithm presented in this work uses raw, unlabeled point clouds as inputs. The algorithm first applies modified Expectation-Maximization Gaussian Mixture Model (GMM) clustering to two input point clouds. It then performs change detection by comparing the GMMs using the Earth Mover’s Distance. The algorithm is validated quantitatively and qualitatively using a test dataset collected by an Astrobee robot in the NASA Ames Granite Lab comprising single frame depth images taken directly by Astrobee and full-scene reconstructed maps built with RGB-D and pose data from Astrobee. The runtimes of the approach are also analyzed in depth. The source code is publicly released to promote further development.

robotics↗
DOE OSTI2015

Low-temperature swelling in LWR internal components: a computational assessment

A modern cluster dynamics model has been used to investigate the materials and irradiation parameters that control microstructural evolution under the relatively low-temperature exposure conditions that are representative of the operating environment for in-core light water reactor components. The focus is on components fabricated from austenitic stainless steel. The model accounts for the synergistic interaction between radiation-produced vacancies and the helium that is produced by nuclear transmutation reactions. Cavity nucleation rates are shown to be relatively high in this temperature regime (275 to 325 °C), but are sensitive to assumptions about the fine-scale microstructure produced under low-temperature irradiation. The cavity nucleation rates observed run counter to the expectation that void swelling would not occur under these conditions. This expectation was based on previous research on void swelling in austenitic steels in fast reactors. This misleading impression arose primarily from an absence of relevant data. The results of the computational modeling are generally consistent with recent data obtained by examining ex-service components. The long-term objective of this research is to provide a predictive model of void swelling at relevant lifetime exposures to support extended reactor operations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

High Performance Computing Based Parallel HIearchical Modal Association Clustering (HPAR HMAC)

For many applications, clustering is a crucial step in order to gain insight into the makeup of a dataset. The best approach to a given problem often depends on a variety of factors, such as the size of the dataset, time restrictions, and soft clustering requirements. The HMAC algorithm seeks to combine the strengths of 2 particular clustering approaches: model-based and linkage-based clustering. One particular weakness of HMAC is its computational complexity. HMAC is not practical for mega-scale data clustering. For high-definition imagery, a user would have to wait months or years for a result; for a 16-megapixel image, the estimated runtime skyrockets to over a decade! To improve the execution time of HMAC, it is reasonable to consider an multi-core implementation that utilizes available system resources. An existing imple-mentation (Ray and Cheng 2014) divides the dataset into N partitions - one for each thread prior to executing the HMAC algorithm. This implementation benefits from 2 types of optimization: parallelization and divide-and-conquer. By running each partition in parallel, the program is able to accelerate computation by utilizing more system resources. Although the parallel implementation provides considerable improvement over the serial HMAC, it still suffers from poor computational complexity, O(N2). Once the maximum number of cores on a system is exhausted, the program exhibits slower behavior. We now consider a modification to HMAC that involves a recursive partitioning scheme. Our modification aims to exploit divide-and-conquer benefits seen by the parallel HMAC implementation. At each level in the recursion tree, partitions are divided into 2 sub-partitions until a threshold size is reached. When the partition can no longer be divided without falling below threshold size, the base HMAC algorithm is applied. This results in a significant speedup over the parallel HMAC.

Patlolla, Dilip R↗
DOE OSTI2019

A Hybrid Tour-Based Model For Energy Analysis Of Multi-Modal Intra-City Freight: A Case Study Of Autonomous Electric Vehicles: Preprint

With the emergence of cutting-edge transportation technologies, such as electric vehicles, connected and autonomous vehicles, and drones, the adoption of multimodal freight mobility has the potential to improve efficiency and save more energy. This paper proposes a hybrid tour-based model to evaluate the energy impact of multimodal intra-city freight movement for future scenarios. The model is built based on the traveling salesman problem model and clustering techniques. A case study using autonomous electric vehicles for package delivery is evaluated. The study was conducted using data analyzed from the Columbus, Ohio, metropolitan area. The initial results show that multimodal package delivery using autonomous electric vehicles reduced total travel time by 45% and saved total energy use by 19%, but increased total vehicle miles traveled by 15% when compared with the baseline scenario.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

A Hybrid Tour-Based Model for Energy Analysis of Multi-Modal Intra-City Freight: A Case Study of Autonomous Electric Vehicles

With the emergence of cutting-edge transportation technologies, such as electric vehicles (EVs), connected and autonomous vehicles, and drones, the adoption of multimodal freight mobility has the potential to improve efficiency and save more energy. This paper proposes a hybrid tour-based model to evaluate the energy impact of multimodal intra-city freight movement for future scenarios. The model is built based on the traveling salesman problem model and clustering techniques. A case study using autonomous electric vehicles for package delivery is evaluated. The study was conducted using data analyzed from the Columbus, Ohio, metropolitan area. The initial results show that multimodal package delivery using autonomous EVs reduced total travel time by 45% and saved total energy use by 19%, but increased total vehicle miles traveled by 15% when compared with the baseline scenario.

25 ENERGY STORAGE↗
DOE OSTI2023

Demographic Information Incorporated Household Energy Consumption Analysis: Preprint

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗
DOE OSTI2023

Demographic Information Incorporated Household Energy Consumption Analysis

The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.

building loads↗
NASA NTRS2005

Small-Scale Drop-Size Variability: Empirical Models for Drop-Size-Dependent Clustering in Clouds

By analyzing aircraft measurements of individual drop sizes in clouds, it has been shown in a companion paper that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)), where 0 less than or equals D(r) less than or equals 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and a Poisson distribution of cloud drops, these models illustrate strong drop clustering, especially with larger drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics, including how fast rain can form. For radiative transfer theory, clustering of large drops enhances their impact on the cloud optical path. The clustering phenomenon also helps explain why remotely sensed cloud drop size is generally larger than that measured in situ.

Marshak, Alexander↗