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All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

LANDSAT D local user terminal study

The effect of the changes incorporated in the LANDSAT D system on the ability of a local user terminal to receive, record and process data in real time was studied. Alternate solutions to the problems raised by these changes were evaluated. A loading analysis was performed in order to determine the quantities of data that a local user terminal (LUT) would be interested in receiving and processing. The number of bits in an MSS and a TM scene were calculated along with the number of scenes per day that an LUT might require for processing. These then combined to a total number of processed bits/day for an LUT as a function of sensor and coverage circle radius.

Alexander, L.↗
NASA NTRS1982

An unbiased survey of field star X-ray emission

To determine the X-ray luminosity function of normal stars, 1700 stars brighter than 10th magnitude were surveyed by the imaging proportional counter aboard the Einstein Observatory. Seventy star positions were found to contain excess X-ray counting rates. The number of stars per square degree in a number of magnitude intervals was calculated as a function of spectral type and luminosity class, and the total number of stars for each spectral type brighter than magnitude 9.5 derived in this manner was compared with the 1700-star sample. The agreement is good, as is that between the surface density of soft X-ray sources and the number of stellar emitters predicted from the field star survey. It is concluded that stars probably do not contribute significantly to the diffuse soft X-ray background. The findings are consistent with the notion that stellar age and/or rotation velocity are important determinants of stellar X-ray emission level.

Helfand, D. J.↗
NASA NTRS2004

Life in the Fast Lane for Protein Crystallization and X-Ray Crystallography

The common goal for structural genomic centers and consortiums is to decipher as quickly as possible the three-dimensional structures for a multitude of recombinant proteins derived from known genomic sequences. Since X-ray crystallography is the foremost method to acquire atomic resolution for macromolecules, the limiting step is obtaining protein crystals that can be useful of structure determination. High-throughput methods have been developed in recent years to clone, express, purify, crystallize and determine the three-dimensional structure of a protein gene product rapidly using automated devices, commercialized kits and consolidated protocols. However, the average number of protein structures obtained for most structural genomic groups has been very low compared to the total number of proteins purified. As more entire genomic sequences are obtained for different organisms from the three kingdoms of life, only the proteins that can be crystallized and whose structures can be obtained easily are studied. Consequently, an astonishing number of genomic proteins remain unexamined. In the era of high-throughput processes, traditional methods in molecular biology, protein chemistry and crystallization are eclipsed by automation and pipeline practices. The necessity for high rate production of protein crystals and structures has prevented the usage of more intellectual strategies and creative approaches in experimental executions. Fundamental principles and personal experiences in protein chemistry and crystallization are minimally exploited only to obtain "low-hanging fruit" protein structures. We review the practical aspects of today s high-throughput manipulations and discuss the challenges in fast pace protein crystallization and tools for crystallography. Structural genomic pipelines can be improved with information gained from low-throughput tactics that may help us reach the higher-bearing fruits. Examples of recent developments in this area are reported from the efforts of the Southeast Collaboratory for Structural Genomics (SECSG).

Pusey, Marc L.↗
NASA NTRS2005

Life in the fast lane for protein crystallization and X-ray crystallography

The common goal for structural genomic centers and consortiums is to decipher as quickly as possible the three-dimensional structures for a multitude of recombinant proteins derived from known genomic sequences. Since X-ray crystallography is the foremost method to acquire atomic resolution for macromolecules, the limiting step is obtaining protein crystals that can be useful of structure determination. High-throughput methods have been developed in recent years to clone, express, purify, crystallize and determine the three-dimensional structure of a protein gene product rapidly using automated devices, commercialized kits and consolidated protocols. However, the average number of protein structures obtained for most structural genomic groups has been very low compared to the total number of proteins purified. As more entire genomic sequences are obtained for different organisms from the three kingdoms of life, only the proteins that can be crystallized and whose structures can be obtained easily are studied. Consequently, an astonishing number of genomic proteins remain unexamined. In the era of high-throughput processes, traditional methods in molecular biology, protein chemistry and crystallization are eclipsed by automation and pipeline practices. The necessity for high-rate production of protein crystals and structures has prevented the usage of more intellectual strategies and creative approaches in experimental executions. Fundamental principles and personal experiences in protein chemistry and crystallization are minimally exploited only to obtain "low-hanging fruit" protein structures. We review the practical aspects of today's high-throughput manipulations and discuss the challenges in fast pace protein crystallization and tools for crystallography. Structural genomic pipelines can be improved with information gained from low-throughput tactics that may help us reach the higher-bearing fruits. Examples of recent developments in this area are reported from the efforts of the Southeast Collaboratory for Structural Genomics (SECSG).

Review↗
NASA NTRS2005

Small-Scale Drop Size Variability: Impact on Estimation of Cloud Optical Properties

Most cloud radiation models and conventional data processing techniques assume that the mean number of drops of a given radius is proportional to volume. The analysis of microphysical data on liquid water drop sizes shows that, for sufficiently small volumes, this proportionality breaks down; the number of cloud drops of a given radius is instead proportional to the volume raised to a drop size-dependent nonunit power. The coefficient of proportionality, a generalized drop concentration, is a function of the drop size. For abundant small drops the power is unity as assumed in the conventional approach. However, for rarer large drops, it falls increasingly below unity. This empirical fact leads to drop clustering, with the larger drops exhibiting a greater degree of clustering. The generalized drop concentration shows the mean number of drops per cluster, while the power characterizes the occurrence frequency of clusters. With a fixed total number of drops in a cloud, a decrease in frequency of clusters is accompanied by a corresponding increase in the generalized concentration. This initiates a competing process missed in the conventional models: an increase in the number of drops per cluster enhances the impact of rarer large drops on cloud radiation while a decrease in the frequency suppresses it. Because of the nonlinear relationship between the number of clustered drops and the volume, these two opposite tendencies do not necessarily compensate each other. The data analysis suggests that clustered drops likely have a stronger radiative impact compared to their unclustered counterpart; ignoring it results in underestimation of the contribution from large drops to cloud horizontal optical path.

Knyazikhin, Y.↗
NASA NTRS1976

Cryogenic wind tunnels: Unique capabilities for the aerodynamicist

The cryogenic wind-tunnel concept as a practical means for improving ground simulation of transonic flight conditions. The Langley 1/3-meter transonic cryogenic tunnel is operational, and the design of a cryogenic National Transonic Facility is undertaken. A review of some of the unique capabilities of cryogenic wind tunnels is presented. In particular, the advantages of having independent control of tunnel Mach number, total pressure, and total temperature are highlighted. This separate control over the three tunnel parameters will open new frontiers in Mach number, Reynolds number, aeroelastic, and model-tunnel interaction studies.

Hall, R. M.↗
NASA NTRS2000

Fusion of AIRSAR and TM Data for Parameter Classification and Estimation in Dense and Hilly Forests

The expanded remotely sensed data space consisting of coincident radar backscatter and optical reflectance data provides for a more complete description of the Earth surface. This is especially useful where many parameters are needed to describe a certain scene, such as in the presence of dense and complex-structured vegetation or where there is considerable underlying topography. The goal of this paper is to use a combination of radar and optical data to develop a methodology for parameter classification for dense and hilly forests, and further, class-specific parameter estimation. The area to be used in this study is the H. J. Andrews Forest in Oregon, one of the Long-Term Ecological Research (LTER) sites in the US. This area consists of various dense old-growth conifer stands, and contains significant topographic relief. The Andrews forest has been the subject of many ecological studies over several decades, resulting in an abundance of ground measurements. Recently, biomass and leaf-area index (LAI) values for approximately 30 reference stands have also become available which span a large range of those parameters. The remote sensing data types to be used are the C-, L-, and P-band polarimetric radar data from the JPL airborne SAR (AIRSAR), the C-band single-polarization data from the JPL topographic SAR (TOPSAR), and the Thematic Mapper (TM) data from Landsat, all acquired in late April 1998. The total number of useful independent data channels from the AIRSAR is 15 (three frequencies, each with three unique polarizations and amplitude and phase of the like-polarized correlation), from the TOPSAR is 2 (amplitude and phase of the interferometric correlation), and from the TM is 6 (the thermal band is not used). The range pixel spacing of the AIRSAR is 3.3m for C- and L-bands and 6.6m for P-band. The TOPSAR pixel spacing is 10m, and the TM pixel size is 30m. To achieve parameter classification, first a number of parameters are defined which are of interest to ecologists for forest process modeling. These parameters include total biomass, leaf biomass, LAI, and tree height. The remote sensing data from radar and TM are used to formulate a multivariate analysis problem given the ground measurements of the parameters. Each class of each parameter is defined by a probability density function (pdf), the spread of which defines the range of that class. High classification accuracy results from situations in which little overlap occurs between pdfs. Classification results provide the basis for the future work of class-specific parameter estimation using radar and optical data. This work was performed in part by the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, and in part by the NASA Ames Research Center, Moffett Field, CA, both under contract from the National Aeronautics and Space Administration.

Moghaddam, Mahta↗
NASA NTRS2000

Giant Impacts and the Distribution of Planetary Obliquities

We have conducted a set of approximately 200 numerical experiments to test the hypothesis that a giant impact leading to the formation of Earth's Moon could have occurred tens of millions of years after most of the small debris in the inner Solar System had been incorporated into terrestrial planets or been removed from the region. More than half of these simulations ended with a giant impact between two of the five terrestrial planets that were initially present. Neglecting any rotational angular momentum prior to the collision, the merged planet typically has a rotation period of less than five hours. The mean planetary obliquity is 91.7 degrees, and the median is 87.9 degrees; thus, there is no statistically significant difference between the number of bodies with prograde rotation and the number with retrograde rotation. There is a paucity of planets with obliquity close to 90 degrees, but the total number of impacts was too small for this result to be of much significance. Several encounters leading to collisions are dominated by three-body effects, with the velocity at impact being slightly less than the free-space escape velocity of the two bodies; the obliquity distribution produced by these impacts appears to be random.

Lissauer, Jack J.↗
NASA NTRS2004

Autonomous Environment-Monitoring Networks

Autonomous environment-monitoring networks (AEMNs) are artificial neural networks that are specialized for recognizing familiarity and, conversely, novelty. Like a biological neural network, an AEMN receives a constant stream of inputs. For purposes of computational implementation, the inputs are vector representations of the information of interest. As long as the most recent input vector is similar to the previous input vectors, no action is taken. Action is taken only when a novel vector is encountered. Whether a given input vector is regarded as novel depends on the previous vectors; hence, the same input vector could be regarded as familiar or novel, depending on the context of previous input vectors. AEMNs have been proposed as means to enable exploratory robots on remote planets to recognize novel features that could merit closer scientific attention. AEMNs could also be useful for processing data from medical instrumentation for automated monitoring or diagnosis. The primary substructure of an AEMN is called a spindle. In its simplest form, a spindle consists of a central vector (C), a scalar (r), and algorithms for changing C and r. The vector C is constructed from all the vectors in a given continuous stream of inputs, such that it is minimally distant from those vectors. The scalar r is the distance between C and the most remote vector in the same set. The construction of a spindle involves four vital parameters: setup size, spindle-population size, and the radii of two novelty boundaries. The setup size is the number of vectors that are taken into account before computing C. The spindle-population size is the total number of input vectors used in constructing the spindle counting both those that arrive before and those that arrive after the computation of C. The novelty-boundary radii are distances from C that partition the neighborhood around C into three concentric regions (see Figure 1). During construction of the spindle, the changing spindle radius is denoted by h. It is the final value of h, reached before beginning construction on the next spindle, that is denoted by r. During construction of a spindle, if a new vector falls between C and the inner boundary, the vector is regarded as completely familiar and no action is taken. If the new vector falls into the region between the inner and outer boundaries, it is considered unusual enough to warrant the adjustment of C and r by use of the aforementioned algorithms, but not unusual enough to be considered novel. If a vector falls outside the outer boundary, it is considered novel, in which case one of several appropriate responses could be initiation of construction of a new spindle.

Hand, Charles↗
NASA NTRS2020

Using GLM Flash Density, Flash Area, and Flash Energy to Diagnose Tropical Cyclone Structure and Intensification

Increased lightning in tropical cyclones (TCs) is typically associated with intensification, but significant lightning outbreaks are also observed in weakening storms. The total number of lightning flashes in a TC is not always a reliable indicator of TC intensity evolution. Issues with the range and detection efficiency of ground-based networks, particularly for intracloud lightning. Physical processes such as vertical wind shear can intensify asymmetric convection while also weakening the TC. The commissioning of the Geostationary Lightning Mapper (GLM) aboard GOES-16 and GOES-17 marked, for the first time, the presence of an operational lightning detector in geostationary orbit. In addition to flash density (the number of flashes per unit area per unit time), GLM also provides continuous observations of flash area and total optical energy.

Duran, Patrick↗
NASA NTRS2014

The Meteoroid Fluence at Mars Due to Comet C/2013 A1 (Siding Spring)

Long-period comet C/2013 A1 (Siding Spring) will experience a close encounter with Mars on 2014 Oct 19. A collision between the comet and the planet has been ruled out, but the comet's coma may envelop Mars and its man-made satellites. By the time of the close encounter, five operational spacecraft will be present near Mars. Characterizing the coma is crucial for assessing the risk posed to these satellites by meteoroid impacts. We present an analytic model of cometary comae that describes the spatial and size distributions of cometary dust and meteoroids. This model correctly reproduces, to within an order of magnitude, the number of impacts recorded by Giotto near 1P/Halley [1] and by Stardust near comet 81P/Wild 2 [2]. Applied to Siding Spring, our model predicts a total particle fluence near Mars of 0.02 particles per square meter. In order to determine the degree to which Siding Spring's coma deviates from a sphere, we perform numerical simulations which take into account both gravitational effects and radiative forces. We take the entire dust component of the coma and tail continuum into account by simulating the ejection and evolution of dust particles from comet Siding Spring. The total number of particles simulated is essentially a free parameter and does not provide a check on the total fluence. Instead, these simulations illustrate the degree to which the coma of Siding Spring deviates from the perfect sphere described by our analytic model (see Figure). We conclude that our analytic model sacrifices less than an order of magnitude in accuracy by neglecting particle dynamics and radiation pressure and is thus adequate for order-of-magnitude fluence estimates. Comet properties may change unpredictably and therefore an analytic coma model that enables quick recalculation of the meteoroid fluence is highly desirable. NASA's Meteoroid Environment Office is monitoring comet Siding Spring and taking measurements of cometary brightness and dust production. We will discuss our coma model and nominal fluence taking the latest observations into account.

Moorhead, A.↗
DOE OSTI2022

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. Here, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES's bidding, scheduling, and control decisions and the energy market's clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1988

Changes in fiber composition of soleus muscle during rat hindlimb suspension

A technique in which the gravitational load in the rear limbs of rats was chronically reduced is used to study soleus muscle atrophy in near-zero-gravity conditions. The results show a decline in the number of fibers in groups that contained the slow isoenzyme of myosin and which were classified as type I. The total number of fibers did not change, and fibers containing the intermediate isoenzyme and those classified as type IIa increased. The results are consistent with either a change in the composition within existing fibers or a simultaneous loss of slow fibers accompanied by de novo synthesis of intermediate and fast fibers.

Templeton, G. H.↗
DOE OSTI2025

Improved heavy-ion PID using scintillation light detector with neural network analysis: a Monte Carlo simulation study

The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the system is affected by a large variation. This work presents and discusses a method for adjusting the total number of detected photons to account for variation in the photon collection efficiency as a function of the position of the light source within the scintillating medium. The method was developed and validated by processing data from systematic simulation studies based on GEANT4 that model the response of the Energy Loss Optical Scintillation System (ELOSS) detector. The position of the charged particle is calculated using a deep neural network algorithm. This is accomplished by analyzing the distribution of scintillation light recorded by the array of photosensors. The estimated particle position is then used to calculate the correction factor and adjust the amount of captured light to account for variations in the photon collection efficiency. The neural network algorithm provides excellent tracking capabilities, achieving sub-millimeter position resolution and an angular resolution of 12 mrad, approaching the performance of traditional tracking detectors (e.g., drift chambers). The present method can be generalized to any optical scintillation system where the photon collection efficiency depends on the position of the impinging particle.

Heavy-ion detectors↗
NASA NTRS1995

High-mass X-ray binary populations. 1: Galactic modeling

Modern stellar evolutionary tracks are used to calculate the evolution of a very large number of massive binary star systems (M(sub tot) greater than or = 15 solar mass) which cover a wide range of total masses, mass ratios, and starting separations. Each binary is evolved accounting for mass and angular momentum loss through the supernova of the primary to the X-ray binary phase. Using the observed rate of star formation in our Galaxy and the properties of massive binaries, we calculate the expected high-mass X-ray binary (HMXRB) population in the Galaxy. We test various massive binary evolutionary scenarios by comparing the resulting HMXRB predictions with the X-ray observations. A major goal of this study is the determination of the fraction of matter lost from the system during the Roche lobe overflow phase. Curiously, we find that the total numbers of observable HMXRBs are nearly independent of this assumed mass-loss fraction, with any of the values tested here giving acceptable agreement between predicted and observed numbers. However, comparison of the period distribution of our HMXRB models with the observed period distribution does reveal a distinction among the various models. As a result of this comparison, we conclude that approximately 70% of the overflow matter is lost from a massive binary system during mass transfer in the Roche lobe overflow phase. We compare models constructed assuming that all X-ray emission is due to accretion onto the compact object from the donor star's wind with models that incorporate a simplified disk accretion scheme. By comparing the results of these models with observations, we conclude that the formation of disks in HMXRBs must be relatively common. We also calculate the rate of formation of double degenerate binaries, high velocity detached compact objects, and Thorne-Zytkow objects.

Dalton, William W.↗
DOE OSTI2026

Statistics of base polytopes in F-theory

We propose a new statistical ensemble of toric bases for elliptic Calabi-Yaus used in F-theory models, by focusing on only the convex hull of the base, i.e., the base polytope. This physically motivated coarse-graining greatly simplifies the combinatorial complexity of the part of the 4d F-theory landscape with toric bases. We develop a Monte Carlo approach that randomly samples the base polytopes within fixed boxes, with proper statistical weights. We first apply the algorithm to the set of 2d base polytopes, generating an enlarged set of toric 2d bases that include certain types of codimension-two (4,6) points, and we validate our approach against exact numbers. We then explore the set of 3d base polytopes which fit in a set of “maximal” 3d boxes, and estimate the total number of inequivalent 3d base polytopes to be 10 85 –10 90 . We provide statistical data such as the distribution of non-Higgsable gauge groups on these bases. Amusingly, a similar method can also be applied to generate reflexive polytopes in various dimensions. In both the reflexive and base polytope cases, the number of relevant polytopes obeys a Gaussian distribution as a function of the number of vertices, which can be understood in terms of other results on random polytopes in the math literature.

Differential and algebraic geometry↗
DOE OSTI2020

Performance and Accuracy Implications of Parallel Split Physics-Dynamics Coupling in the Energy Exascale Earth System Atmosphere Model

Simultaneous calculation of atmospheric processes is faster than calculating processes one at a time. This type of parallelism is beneficial or perhaps even necessary to provide good performance on modern supercomputers, which achieve faster performance through increased processor count rather than improved clock speed. The scalability of the Energy Exascale Earth System Model (E3SM) Atmosphere Model (EAM) is limited by the fluid dynamics which scales up to the number of mesh cells in the global mesh. In contrast, the suite of physics parameterizations in EAM is scalable up to the total number of physics columns, which is an order of magnitude greater than the number of mesh cells. A proposed solution to unlocking the greater potential performance from the physics suite is to solve the physics and dynamics in parallel. This work represents a first attempt at parallel splitting of the grid-scale fluid dynamics model and the subgrid-scale physics parameterizations in a global atmosphere model. We will demonstrate that switching to parallel physics-dynamics coupling extends the scalability of the EAM to up to 3 times the previous peak scalability limit and is up to 20% faster than the sequentially split coupling at the highest core counts and the same time step. Decadal simulations of both coupling approaches show very little impact to the model climate. This improved performance does not come without drawbacks, however. Parallel splitting requires a shorter time step and other modifications which largely offset performance gains. A mass fixer is required for conservation. Techniques for mitigating these issues are also discussed.

97 MATHEMATICS AND COMPUTING↗