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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Modulation/demodulation techniques for satellite communications. Part 4: Appendices

The use of the Viterbi algorithm in a general context is examined. The generalized transfer function bounds are given which permit the following applications to be carried out: maximum likelihood demodulation of such bandwidth modulations as minimum-shift-keying and continuous phase frequency-shift-keying, demodulation of intersymbol interference and partial response signals, estimation and smoothing, and simultaneous phase synchronization, and data detection. Sufficient conditions are reviewed for tightening Chernoff and Rhattacharyya bounds.

Omura, J. K.↗
NASA NTRS2019

The Effects of an Improved Dynamic Vegetation Phenology Representation in a Global Land Surface Model

Evapotranspiration (ET) is a major driver of the interaction between the land surface and the atmosphere through its component mechanisms, including plant transpiration (T) and soil evaporation. To accurately capture land-atmosphere interactions in global Earth System Models, it is thus critical that the underlying land surface models accurately model both the land hydrology as well as the dynamic response of vegetation to environmental drivers. In an effort to introduce a more realistic vegetation representation, the NASA Catchment land surface model, which is part of the Goddard Earth Observing System (GEOS), has previously been merged with the carbon and nitrogen physics modules of the Community Land Model version 4, resulting in the new Catchment-CN model. Catchment-CN has inherited the advanced treatment of land surface hydrology of Catchment, but is additionally able to dynamically model the response of vegetation to environmental drivers, in contrast to the fixed vegetation climatology that was prescribed in Catchment. Recently, the parameterization of Catchment-CN vegetation has been augmented to better account for variability of vegetation responses to external forcings within existing plant functional types, and vegetation parameters have been calibrated against Moderate Resolution Imaging Spectrometer observations of the fraction of absorbed photosynthetically radiation. These efforts have led to a significant reduction in the RMSE of modeled photosynthetic activity with respect to observations.This presentation investigates the effect of the improved vegetation representation on the partitioning of ET within Catchment-CN. Specifically, we compare global maps of the T:ET ratio across different temporal scales in (1) the original Catchment model, (2) the original Catchment-CN model, and (3) the augmented and calibrated Catchment-CN model. The modeled T and ET estimates are compared against a comprehensive set of ground observations from various field studies, as well as independent global T:ET estimates from different ET algorithms provided in the context of the Water Cycle Observation Multi-mission Strategy ? Evapotranspiration (WACMOS-ET) initiative.

Kolassa, J.↗
DOE OSTI2022

Estimating the randomness of quantum circuit ensembles up to 50 qubits

Random quantum circuits have been utilized in the contexts of quantum supremacy demonstrations, variational quantum algorithms for chemistry and machine learning, and blackhole information. The ability of random circuits to approximate any random unitaries has consequences on their complexity, expressibility, and trainability. To study this property of random circuits, we develop numerical protocols for estimating the frame potential, the distance between a given ensemble and the exact randomness. Our tensor-network-based algorithm has polynomial complexity for shallow circuits and is high-performing using CPU and GPU parallelism. We study 1. local and parallel random circuits to verify the linear growth in complexity as stated by the Brown–Susskind conjecture, and; 2. hardware-efficient ansätze to shed light on its expressibility and the barren plateau problem in the context of variational algorithms. Our work shows that large-scale tensor network simulations could provide important hints toward open problems in quantum information science.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

Lossless Compression of Classification-Map Data

A lossless image-data-compression algorithm intended specifically for application to classification-map data is based on prediction, context modeling, and entropy coding. The algorithm was formulated, in consideration of the differences between classification maps and ordinary images of natural scenes, so as to be capable of compressing classification- map data more effectively than do general-purpose image-data-compression algorithms. Classification maps are typically generated from remote-sensing images acquired by instruments aboard aircraft (see figure) and spacecraft. A classification map is a synthetic image that summarizes information derived from one or more original remote-sensing image(s) of a scene. The value assigned to each pixel in such a map is the index of a class that represents some type of content deduced from the original image data for example, a type of vegetation, a mineral, or a body of water at the corresponding location in the scene. When classification maps are generated onboard the aircraft or spacecraft, it is desirable to compress the classification-map data in order to reduce the volume of data that must be transmitted to a ground station.

Hua, Xie↗
DOE OSTI2022

ConKer: An algorithm for evaluating correlations of arbitrary order

Context. High order correlations in the cosmic matter density have become increasingly valuable in cosmological analyses. However, computing these correlation functions is computationally expensive. Aims. We aim to circumvent these challenges by developing a new algorithm called ConKer for estimating correlation functions. Methods. This algorithm performs convolutions of matter distributions with spherical kernels using FFT. Since matter distributions and kernels are defined on a grid, it results in some loss of accuracy in the distance and angle definitions. We study the algorithm setting at which these limitations become critical and suggest ways to minimize them. Results. ConKer is applied to the CMASS sample of the SDSS DR12 galaxy survey and corresponding mock catalogs, and is used to compute the correlation functions up to correlation order n = 5. We compare the n = 2 and n = 3 cases to traditional algorithms to verify the accuracy of the new algorithm. We perform a timing study of the algorithm and find that three of the four distinct processes within the algorithm are nearly independent of the catalog size N , while one subdominant component scales as O ( N ). The dominant portion of the calculation has complexity of O ( N c 4/3 log N c ), where N c is the of cells in a three-dimensional grid corresponding to the matter density. Conclusions. We find ConKer to be a fast and accurate method of probing high order correlations in the cosmic matter density, then discuss its application to upcoming surveys of large-scale structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Characterization of a Pixelated Cadmium Telluride Detector System Using a Polychromatic X-Ray Source and Gold Nanoparticle-Loaded Phantoms for Benchtop X-Ray Fluorescence Imaging

In this paper, the imaging dose and scan time have been considered as the two major constraints for routine benchtop x-ray fluorescence computed tomography (XFCT) imaging. One way to address this issue is to acquire x-ray fluorescence (XRF) signals in parallel through a 2D array of single-crystal detectors or a pixelated detector along with the cone-beam x-ray source. To identify a detector system suitable for this purpose, a commercially available, fully spectroscopic cadmium telluride (CdTe) pixelated detector, HEXITEC (High-Energy X-ray Imaging Technology), was tested under the experimental conditions optimized for benchtop XFCT imaging of gold nanoparticles (GNPs). Specifically, two different parallel-hole stainless steel collimators were fabricated and coupled with the detector for seamless integration into our existing benchtop cone-beam XFCT system. After the detector deployment, this benchtop XFCT system was used to detect XRF photons from GNP-loaded phantoms. A pixel-merging algorithm was introduced to enhance the sensitivity of XRF photon detection thereby minimizing the scan time. The effect of pixel-level charge sharing correction algorithms was investigated within the context of benchtop XFCT imaging. The detector energy resolution, in terms of the full width at half maximum (FWHM) values at different gold K-shell XRF energies, was also determined. Of the two charge sharing correction algorithms examined, the charge sharing addition gave better sensitivity than the charge sharing discrimination (csd). On the other hand, under the current experimental conditions, the energy resolution of the HEXITEC detector was the best with the csd and estimated to be 1.56 keV FWHM at 66-69 keV photon energy. Overall, despite some degradation of the detector energy resolution (compared with typical single crystal CdTe detectors), the HEXITEC detector enabled parallel data acquisition under the experimental conditions typical of benchtop XFCT imaging and operated well within our benchtop XFCT setup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1995

Parallel adaptive mesh refinement within the PUMAA3D Project

To enable the solution of large-scale applications on distributed memory architectures, we are designing and implementing parallel algorithms for the fundamental tasks of unstructured mesh computation. In this paper, we discuss efficient algorithms developed for two of these tasks: parallel adaptive mesh refinement and mesh partitioning. The algorithms are discussed in the context of two-dimensional finite element solution on triangular meshes, but are suitable for use with a variety of element types and with h- or p-refinement. Results demonstrating the scalability and efficiency of the refinement algorithm and the quality of the mesh partitioning are presented for several test problems on the Intel DELTA.

Freitag, Lori↗
DOE OSTI2022

A Novel Method for Controlling Crud Deposition in Nuclear Reactors Using Optimization Algorithms and Deep Neural Network Based Surrogate Models

This work presents the use of a high-fidelity neural network surrogate model within a Modular Optimization Framework for treatment of crud deposition as a constraint within light-water reactor core loading pattern optimization. The neural network was utilized for the treatment of crud constraints within the context of an advanced genetic algorithm applied to the core design problem. This proof-of-concept study shows that loading pattern optimization aided by a neural network surrogate model can optimize the manner in which crud distributes within a nuclear reactor without impacting operational parameters such as enrichment or cycle length. Several analysis methods were investigated. Analysis found that the surrogate model and genetic algorithm successfully minimized the deviation from a uniform crud distribution against a population of solutions from a reference optimization in which the crud distribution was not optimized. Strong evidence is presented that shows boron deposition in crud can be optimized through the loading pattern. This proof-of-concept study shows that the methods employed provide a powerful tool for mitigating the effects of crud deposition in nuclear reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1977

An improved algorithm for the isolation of polynomial real zeros

THe Collins-Loos algorithm for computing isolating intervals for the zeros of an integer polynomial requires the evaluation of polynomials at rational points. This implies the use of arbitrary precision integer arithmetic. It is shown how careful use of single precision, floating point arithmetic within the context of a slightly modified algorithm can make the calculation considerably faster and no less exact. Typically, 95% or more of the evaluations can be done without exact arithmetic. The precise speedup depends on the relative costs of the arithmetic in a given implementation. The implementation on DEC KL-10 computer is some 5 to 10 times faster than the original Univac 1110 implementation in SAC-I.

Fateman, R. J.↗
NASA NTRS2009

Experimental Performance of a Genetic Algorithm for Airborne Strategic Conflict Resolution

The Autonomous Operations Planner, a research prototype flight-deck decision support tool to enable airborne self-separation, uses a pattern-based genetic algorithm to resolve predicted conflicts between the ownship and traffic aircraft. Conflicts are resolved by modifying the active route within the ownship s flight management system according to a predefined set of maneuver pattern templates. The performance of this pattern-based genetic algorithm was evaluated in the context of batch-mode Monte Carlo simulations running over 3600 flight hours of autonomous aircraft in en-route airspace under conditions ranging from typical current traffic densities to several times that level. Encountering over 8900 conflicts during two simulation experiments, the genetic algorithm was able to resolve all but three conflicts, while maintaining a required time of arrival constraint for most aircraft. Actual elapsed running time for the algorithm was consistent with conflict resolution in real time. The paper presents details of the genetic algorithm s design, along with mathematical models of the algorithm s performance and observations regarding the effectiveness of using complimentary maneuver patterns when multiple resolutions by the same aircraft were required.

Karr, David A.↗
NASA NTRS2009

Experimental Performance of a Genetic Algorithm for Airborne Strategic Conflict Resolution

The Autonomous Operations Planner, a research prototype flight-deck decision support tool to enable airborne self-separation, uses a pattern-based genetic algorithm to resolve predicted conflicts between the ownship and traffic aircraft. Conflicts are resolved by modifying the active route within the ownship's flight management system according to a predefined set of maneuver pattern templates. The performance of this pattern-based genetic algorithm was evaluated in the context of batch-mode Monte Carlo simulations running over 3600 flight hours of autonomous aircraft in en-route airspace under conditions ranging from typical current traffic densities to several times that level. Encountering over 8900 conflicts during two simulation experiments, the genetic algorithm was able to resolve all but three conflicts, while maintaining a required time of arrival constraint for most aircraft. Actual elapsed running time for the algorithm was consistent with conflict resolution in real time. The paper presents details of the genetic algorithm's design, along with mathematical models of the algorithm's performance and observations regarding the effectiveness of using complimentary maneuver patterns when multiple resolutions by the same aircraft were required.

Karr, David A.↗
DOE OSTI2024

End-Use Savings Shapes Measure Documentation: Variable Refrigerant Flow With 25% Upsizing Allowance for Heating

This documentation focuses on a single end-use savings shape upgrade - a variable refrigerant flow with heat recovery (VRF HR) heating and cooling system coupled with a dedicated outdoor air system (DOAS) for ventilation and where 25% upsizing (or 125% of the original size) is allowed for heating in colder climates (i.e., heating dominant regions). This document will primarily discuss the additional changes to the sizing algorithm and modeling approach, while a comprehensive overview of the fundamental modeling methodology and background of the VRF HR DOAS upgrade, including applicability and other key assumptions can be found in the original documentation: Variable Refrigerant Flow with Heat Recovery and Dedicated Outdoor Air System. To provide more context on the 25% upsizing algorithm, if the building is a cooling dominant (e.g., design cooling load higher than design heating load ), then the outdoor unit capacity of the VRF heat pump is sized based on the design cooling load. However, if the building is heating dominant, then this building is a candidate for the 25% upsizing allowance. Once the 25% upsizing is allowed, if the 25% upsized capacity (or 125% from the original size) represented with design condition exceeds the design heating load, then the design heating load is used for calculating the rated capacity of the outdoor unit. And if the 25% upsized capacity represented with the design condition does not exceed the design heating load, then the 25% upsized capacity represented with rated condition is used for the capacity of the outdoor unit while the remaining heating load is handled with the supplemental/backup electric resistance coil.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Micro Baselines for Operational Technology Environments

Critical infrastructure stakeholders need to baseline their networks to understand expected communications. Top-down approaches to baselining rely on observables that are generally available but lack properties upon which traditional statistical tools depend. We propose to construct micro-baselines: signatures within operational networks based on observables associated with specific events. Such observables are informed by precursor analysis reports of historical cyber attacks on operational environments developed by Cybersecurity for Operational Technology Environments (CyOTE). Baseline measurements depend upon context beyond the cyber domain. An energy plant's baseline running in the summer may statistically differ from a similar facility in a colder region. Domain knowledge must be integrated to apply general micro-baselining algorithms to a facility-specific context. Therefore, we propose to explore the feasibility of transferring micro baselining algorithms across different facilities. Facilities that implement the same processes in different geographic locations will be compared relative to observable measurements used in micro-baselining for comparable events. One evaluation approach would condition or augment dynamic observables measured within a facility network testbed with additional observables derived from geographic context or infrastructure dependencies such as those provided by the All-Hazards Analysis tool.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1980

Parallel processing implementations of a contextual classifier for multispectral remote sensing data

The applicability of parallel processing schemes to the implementation of a contextual classification algorithm which exploits the spatial and spectral context of a multispectral remote sensing pixel to achieve classification is examined. Two algorithms for classifying each multivariate pixel taking into account the probable classifications of neighboring pixels are presented which make use of a size three horizontally linear neighborhood, and the serial computational complexity of the more efficient algorithm is shown to grow in proportion to the number of pixels and the cube of the number of possible categories. The implementation of the more efficient algorithm on a CDC Flexible Processor system and on a multimicroprocessor system such as the proposed PASM is then discussed. It is noted that the use of N processors to perform the calculations N times faster than a single processor overcomes the principal disadvantage of contexual classifiers, i.e., their computational complexity.

Siegel, H. J.↗
NASA NTRS1980

Context distribution estimation for contextual classification of multispectral image data

A classification algorithm incorporating contextual information in a general, statistical manner is presented. Methods are investigated for obtaining adequate estimates of the context distribution (a statistical characterization of context) upon which the classification algorithm depends. Finally, a method of estimating optimal algorithm parameters prior to performing preliminary classifications is explored.

Tilton, J. C.↗
NASA NTRS1981

Contextual classification of multispectral image data: An unbiased estimator for the context distribution

A key input to a statistical classification algorithm, which exploits the tendency of certain ground cover classes to occur more frequently in some spatial context than in others, is a statistical characterization of the context: the context distribution. An unbiased estimator of the context distribution is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real LANDSAT data sets are presented and contrasted with results from non-contextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Tilton, J. C.↗
DOE OSTI2023

A group finder algorithm optimised for the study of local galaxy environments

Context. The majority of galaxy group catalogues available in the literature use the popular friends-of-friends algorithm which links galaxies using a linking length. One potential drawback to this approach is that clusters of points can be linked with thin bridges which may not be desirable. In order to study galaxy groups, it is important to obtain realistic group structures. Aim. Here, in this study, we present a new simple group finder algorithm, TD-ENCLOSER, that finds the group that encloses a target galaxy of interest. Methods. TD-ENCLOSER is based on the kernel density estimation method which treats each galaxy, represented by a zero-dimensional particle, as a two-dimensional circular Gaussian. The algorithm assigns galaxies to peaks in the density field in order of density in descending order (‘top down’) so that galaxy groups ‘grow’ around the density peaks. Outliers in under-dense regions are prevented from joining groups by a specified hard threshold, while outliers at the group edges are clipped below a soft (blurred) interior density level. Results. The group assignments are largely insensitive to all free parameter variations apart from the hard density threshold and the kernel standard deviation, although this is a known feature of density-based group finder algorithms and it operates with a computing speed that increases linearly with the size of the input sample. In preparation for a companion paper, we also present a simple algorithm to select unique representative groups when duplicates occur. Conclusions. TD-ENCLOSER is tested on a mock galaxy catalogue using a smoothing scale of 0.3 Mpc and is found to be able to recover the input group distribution with sufficient accuracy to be applied to observed galaxy distributions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Performance and Accuracy Assessment of Line Marching Algorithm Computations Utilizing GPUs Within a Predictive GNSS Quality Service

This paper presents a detailed analysis of the accuracy and performance of line marching algorithms executing on a GPU. In the context of an accurate Global Navigation Satellite System(GNSS) quality of service simulation, horizon sky-plots are a useful tool to determine satellite visibility in the presence of obstructions from objects, such as buildings or dense foliage. In order to accurately model satellite visibility at a point of interest on a map, a horizon plot can identify the viewing angles at which objects are blocking the sky. This computation requires traversing a line starting at the point of interest on a 2D altitude map, moving outward for every azimuth angle. To explore the performance of this computation, we propose a new dynamic stopping condition for the traversal of the line, benefiting from objects close to the point of interest. We compare the accuracy of common line marching algorithms, and consider their parallel performance when developed in CUDA. We find that our proposed stopping condition for line marching provides a significant improvement in performance in urban canyon sky-plots, as compared to previous work. Additionally, these results show that simpler algorithms, such as the digital differential analyzer line algorithm, are better suited for GPUs than more sophisticated schemes such as Bresenham’s algorithm, specifically in the context of sky-plothorizon computations. The trade-off between accuracy and performance is analyzed and providing guidance that depends on the targeted goal of the GNSS application.

GNSS↗