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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Self-organizing map (SOM) of space acceleration measurement system (SAMS) data

In this paper, space acceleration measurement system (SAMS) data have been classified using self-organizing map (SOM) networks without any supervision; i.e., no a priori knowledge is assumed regarding input patterns belonging to a certain class. Input patterns are created on the basis of power spectral densities of SAMS data. Results for SAMS data from STS-50 and STS-57 missions are presented. Following issues are discussed in details: impact of number of neurons, global ordering of SOM weight vectors, effectiveness of a SOM in data classification, and effects of shifting time windows in the generation of input patterns. The concept of 'cascade of SOM networks' is also developed and tested. It has been found that a SOM network can successfully classify SAMS data obtained during STS-50 and STS-57 missions.

STS-57 Shuttle Project↗
NASA NTRS1999

The Role of Self-Organized Criticality in the Substorm Phenomenon and its Relation to Localized Reconnection in the Magnetospheric Plasma Sheet

Evidence is presented that suggests there is a significant self-organized criticality (SOC) component in the dynamics of substorms in the magnetosphere. Observations of BBFs, fast flows, localized dipolarizations, plasma turbulence, etc. are taken to show that multiple localized reconnection sites provide the basic avalanche phenomenon in the establishment of SOC in the plasma sheet. First results are presented from a continuing plasma physical study of this avalanche process. A one-dimensional resistive MHD model of a magnetic field reversal is discussed. Resistivity, in this model, is self-consistently generated in response to the excitation of an idealized current-driven instability. When forced by convection of magnetic flux into the field reversal region, the model yields rapid magnetic field annihilation through a dynamic behavior that is shown to exhibit many of the characteristics of SOC. Over a large range of forcing strengths, the annihilation rate is shown to self-adjust to balance the rate at which flux is convected into the reversal region. Several analogies to magnetotail dynamics are discussed: (1) It is shown that the presence of a localized criticality in the model produces a remarkable stability in the global configuration of the field reversal while simultaneously exciting extraordinarily dynamic internal evolution. (2) Under steady forcing, it is shown that a loading-unloading cycle may arise that, as a consequence of the global stability, is quasi-periodic and, therefore, predictable despite the presence of internal turbulence in the field distribution. Indeed, it is shown that the global loading-unloading cycle is a consequence of the internal turbulence. (3) It is shown that, under steady, strong forcing the loading-unloading cycle vanishes. Instead, a recovery from a single unloading persists indefinitely. The field reversal is globally very steady while internally it is very dynamic as field annihilation goes on at the rate necessary to match the strong forcing. From this result we speculate that steady magnetospheric convection events result when the plasma sheet has been driven close to criticality over an extended spatial domain. During these events, we would expect to find localized reconnection sites distributed over the spatial domain of near criticality and we would expect to find plasma sheet transport in that domain to be closely related to that of BBF and fast flow events.

Klimas, Alex J.↗
NASA NTRS2000

Self-organizing biochemical cycles

I examine the plausibility of theories that postulate the development of complex chemical organization without requiring the replication of genetic polymers such as RNA. One conclusion is that theories that involve the organization of complex, small-molecule metabolic cycles such as the reductive citric acid cycle on mineral surfaces make unreasonable assumptions about the catalytic properties of minerals and the ability of minerals to organize sequences of disparate reactions. Another conclusion is that data in the Beilstein Handbook of Organic Chemistry that have been claimed to support the hypothesis that the reductive citric acid cycle originated as a self-organized cycle can more plausibly be interpreted in a different way.

NASA Discipline Exobiology↗
DOE OSTI2026

Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method

Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Probing the impact of oxygen negative ions on the self-organized pattern in 1 atm DC glow with liquid anode

In an atmospheric DC glow discharge with a liquid anode, the plasma anode glow attached to the grounded liquid surface under certain conditions self-organizes into coherent patterns. Optical emission spectroscopy revealed that the emission consists primarily of the second positive system of nitrogen, N 2 (C-B), whose excitation energy is low and sensitive to changes in the electron energy distribution. In addition to electrons, negative ions can accumulate in the anode sheath and affect the local space charge. It has been speculated that these negative ions play a role in pattern formation at the anode surface. In this work, the role of oxygen negative ions was explored. It was found that the formation of anode patterns requires at least a 7% volume fraction of oxygen in the ambient gas. Results showed that O 2 - is the dominant negative ion species in atmospheric DC glow discharge, with a density of ~10 12 cm -3 . While the presence of oxygen appears to be crucial for pattern formation, this study indicated that patterns still formed without geometric changes even when 62% of negative ions in the plasma were detached by a laser. This suggests that negative ions do not support the patterns, while oxygen's heating effect may induce instability at the anode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1992

Self-organized rock textures and multiring structure in the Duolun crater

The Duolun impact crater is a multiring basin located 200 km north of Beijing. From the center to the edge of the crater there are innermost rim, inner ring, outer rim, and outermost ring. Recently, we have found some self-organized textures or chaos phenomena in shock-metamorphic rocks from the Duolun impact crater, such as turbulence in matrices of impact glass, oscillatory zoning, or chemical chaos of spherulites in spherulitic splashed breccia, fractal wavy textures or self-similar wavy textures with varied scaling in impact glass, and crystallite beams shaped like Lorentz strange attractors. The rare phenomena indicate that the shock-metamorphic rocks from Duolun crater are formed far from equilibrium. If impact cratering generates momentarily under high-pressure and superhigh-temperature, occurrence of those chaos phenomena in shock-metamorphic rock is not surprising.

Wu, Siben↗
DOE OSTI2026

Dark Energy Survey Year 6 results: Clustering redshifts and importance sampling of self-organized-maps 𝑛⁡(𝑧) realizations for 3 × 2 ⁢pt samples

This work is part of a series establishing the redshift framework for the 3 × 2 ⁢pt analysis of the Dark Energy Survey Year 6 (DES Y6). For DES Y6, photometric redshift distributions are estimated using self-organizing maps (SOMs), calibrated with spectroscopic and many-band photometric data. To overcome limitations from color-redshift degeneracies and incomplete spectroscopic coverage, we enhance this approach by incorporating clustering-based redshift constraints (clustering-z, or WZ) from angular cross-correlations with BOSS and eBOSS galaxies and eBOSS quasar samples. We define a WZ likelihood and apply importance sampling to a large ensemble of SOM-derived 𝑛⁡(𝑧) realizations, selecting those consistent with the clustering measurements to produce a posterior sample for each lens and source bin. The analysis uses angular scales corresponding to 1.5–5 Mpc to optimize signal-to-noise ratio while mitigating modeling uncertainties and marginalizes over redshift-dependent galaxy bias and other systematics informed by the N-body simulation CARDINAL . While a sparser spectroscopic reference sample limits WZ constraining power at 𝑧 >1.1, particularly for source bins, we demonstrate that combining SOM with WZ improves redshift accuracy and enhances the overall cosmological constraining power of DES Y6. As a result, we estimate an improvement in 𝑆 8 of approximately 10% for cosmic shear and 3 ×2⁢pt analysis, primarily due to the WZ calibration of the source samples.

Cosmological parameters↗
NASA NTRS1991

Self-organization and clustering algorithms

Kohonen's feature maps approach to clustering is often likened to the k or c-means clustering algorithms. Here, the author identifies some similarities and differences between the hard and fuzzy c-Means (HCM/FCM) or ISODATA algorithms and Kohonen's self-organizing approach. The author concludes that some differences are significant, but at the same time there may be some important unknown relationships between the two methodologies. Several avenues of research are proposed.

Bezdek, James C.↗
NASA NTRS1992

Self-organization of cosmic radiation pressure instability. II - One-dimensional simulations

The clustering of statistically uniform discrete absorbing particles moving solely under the influence of radiation pressure from uniformly distributed emitters is studied in a simple one-dimensional model. Radiation pressure tends to amplify statistical clustering in the absorbers; the absorbing material is swept into empty bubbles, the biggest bubbles grow bigger almost as they would in a uniform medium, and the smaller ones get crushed and disappear. Numerical simulations of a one-dimensional system are used to support the conjecture that the system is self-organizing. Simple statistics indicate that a wide range of initial conditions produce structure approaching the same self-similar statistical distribution, whose scaling properties follow those of the attractor solution for an isolated bubble. The importance of the process for large-scale structuring of the interstellar medium is briefly discussed.

Hogan, Craig J.↗
NASA NTRS2005

Self-Organizing-Map Program for Analyzing Multivariate Data

SOM_VIS is a computer program for analysis and display of multidimensional sets of Earth-image data typified by the data acquired by the Multi-angle Imaging Spectro-Radiometer [MISR (a spaceborne instrument)]. In SOM_VIS, an enhanced self-organizing-map (SOM) algorithm is first used to project a multidimensional set of data into a nonuniform three-dimensional lattice structure. The lattice structure is mapped to a color space to obtain a color map for an image. The Voronoi cell-refinement algorithm is used to map the SOM lattice structure to various levels of color resolution. The final result is a false-color image in which similar colors represent similar characteristics across all its data dimensions. SOM_VIS provides a control panel for selection of a subset of suitably preprocessed MISR radiance data, and a control panel for choosing parameters to run SOM training. SOM_VIS also includes a component for displaying the false-color SOM image, a color map for the trained SOM lattice, a plot showing an original input vector in 36 dimensions of a selected pixel from the SOM image, the SOM vector that represents the input vector, and the Euclidean distance between the two vectors.

Li, P. Peggy↗
NASA NTRS2016

Atmospheric Drivers of Greenland Surface Melt Revealed by Self-Organizing Maps

Recent acceleration in surface melt on the Greenland ice sheet (GrIS) has occurred concurrently with a rapidly warming Arctic and has been connected to persistent, anomalous atmospheric circulation patterns over Greenland. To identify synoptic setups favoring enhanced GrIS surface melt and their decadal changes, we develop a summer Arctic synoptic climatology by employing self-organizing maps. These are applied to daily 500 hPa geopotential height fields obtained from the Modern Era Retrospective Analysis for Research and Applications reanalysis, 1979-2014. Particular circulation regimes are related to meteorological conditions and GrIS surface melt estimated with outputs from the Modèle Atmosphérique Régional. Our results demonstrate that the largest positive melt anomalies occur in concert with positive height anomalies near Greenland associated with wind, temperature, and humidity patterns indicative of strong meridional transport of heat and moisture. We find an increased frequency in a 500 hPa ridge over Greenland coinciding with a 63% increase in GrIS melt between the 1979-1988 and 2005-2014 periods, with 75.0% of surface melt changes attributed to thermodynamics, 17% to dynamics, and 8.0% to a combination. We also confirm that the 2007-2012 time period has the largest dynamic forcing relative of any period but also demonstrate that increased surface energy fluxes, temperature, and moisture separate from dynamic changes contributed more to melt even during this period. This implies that GrIS surface melt is likely to continue to increase in response to an ever warmer future Arctic, regardless of future atmospheric circulation patterns.

anomalies↗
NASA NTRS2006

Automated Classification of Thermal Infrared Spectra Using Self-organizing Maps

Existing and planned space missions to a variety of planetary and satellite surfaces produce an ever increasing volume of spectral data. Understanding the scientific informational content in this large data volume is a daunting task. Fortunately various statistical approaches are available to assess such data sets. Here we discuss an automated classification scheme based on Kohonen Self-organizing maps (SOM) we have developed. The SUM process produces an output layer were spectra having similar properties lie in close proximity to each other. One major effort is partitioning this output layer into appropriate regions. This is prefonned by defining dosed regions based upon the strength of the boundaries between adjacent cells in the SOM output layer. We use the Davies-Bouldin index as a measure of the inter-class similarities and intra-class dissimilarities that determines the optimum partition of the output layer, and hence number of SOM clusters. This allows us to identify the natural number of clusters formed from the spectral data. Mineral spectral libraries prepared at Arizona State University (ASU) and John Hopkins University (JHU) are used to test and evaluate the classification scheme. We label the library sample spectra in a hierarchical scheme with class, subclass, and mineral group names. We use a portion of the spectra to train the SOM, i.e. produce the output layer, while the remaining spectra are used to test the SOM. The test spectra are presented to the SOM output layer and assigned membership to the appropriate cluster. We then evaluate these assignments to assess the scientific meaning and accuracy of the derived SOM classes as they relate to the labels. We demonstrate that unsupervised classification by SOMs can be a useful component in autonomous systems designed to identify mineral species from reflectance and emissivity spectra in the therrnal IR.

Roush, Ted L.↗
DOE OSTI2024

Self-Organized Stress Distributions in Polycrystalline Materials [Dissertation]

Understanding stress distributions in solid materials is complicated by the fact that most materials are polycrystalline in nature, with each crystal having an elastically anisotropic reaction to force. This study is to gain a better understanding on how external forces placed on a polycrystal are related to internal reactions within and between the grains. The hypothesis is that the stress distribution in porous to fully dense materials are self-organized based on strong contacts between and within the individual grains created by force chains. Force chains, commonly known in loaded granular materials, and could be the phenomenon that connect micro to macro deformation. Scale bridging measurements conducted through Raman spectroscopy, Atomic Force Microscopy, and Digital Image Correlation will be used to create stress maps, modulus maps, and elastic strain maps across a variety of geological and pharmaceutical polycrystals. When possible, the resulting maps will be compared to current homogenization schemes and a full field models. Finite element modeling will be used to assess whether the patterning seen in the experimental map is a reasonable approximation based on the orientation data of the samples used. A minimum of three publications is projected to be accomplished focusing each on a different method to experimentally test and analyze stress distributions.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Self-organization via active exploration in robotic applications. Phase 2: Hybrid hardware prototype

In many environments human-like intelligent behavior is required from robots to assist and/or replace human operators. The purpose of these robots is to reduce human time and effort in various tasks. Thus the robot should be robust and as autonomous as possible in order to eliminate or to keep to a strict minimum its maintenance and external control. Such requirements lead to the following properties: fault tolerance, self organization, and intelligence. A good insight into implementing these properties in a robot can be gained by considering human behavior. In the first phase of this project, a neural network architecture was developed that captures some fundamental aspects of human categorization, habit, novelty, and reinforcement behavior. The model, called FRONTAL, is a 'cognitive unit' regulating the exploratory behavior of the robot. In the second phase of the project, FRONTAL was interfaced with an off-the-shelf robotic arm and a real-time vision system. The components of this robotic system, a review of FRONTAL, and simulation studies are presented in this report.

Oegmen, Haluk↗
NASA NTRS1991

Self-organization of cosmic radiation pressure instability

Under some circumstances the absorption of radiation momentum by an absorbing medium opens the possibility of a dynamical instability, sometimes called 'mock gravity'. Here, a simplified abstract model is studied in which the radiation source is assumed to remain spatially uniform, there is no reabsorption or reradiated light, and no forces other than radiative pressure act on the absorbing medium. It is shown that this model displays the unique feature of being not only unstable, but also self-organizing. The structure approaches a statistical dynamical steady state which is almost independent of initial conditions. In this saturated state the absorbers are concentrated in thin walls around empty bubbles; as the instability develops the big bubbles get bigger and the small ones get crushed and disappear. A linear analysis shows that to first order the thin walls are indeed stable structures. It is speculated that this instability may play a role in forming cosmic large-scale structure.

Hogan, Craig J.↗
NASA NTRS1993

Self-Organized Criticality and Phase Problem in Magnetoaocustic Emission Burst in Ferromagnets

Two types of ferromagnets, pure iron and steel with varying geometry and microstructural properties, were prepared for the present study of magnetoacoustic emission (MAE). The purpose was to separate the effects of structural property variations from changes caused by differences in the sample geometry. The position and shape of the leading MAE sub-burst and its variation among the samples are explained by magnetic anisotropy and the results of numerical simulations which utilized the concept of self-organized criticality (SOC). The amplitude and duration of the second sub-burst, which previously was thought to occur as a result of a complicated interaction between non-180 deg domain walls and lattice defects, can easily be explained by the results of our simulation.

Namkung, M.↗
NASA NTRS1993

A new approach for designing self-organizing systems and application to adaptive control

There is tremendous interest in the design of intelligent machines capable of autonomous learning and skillful performance under complex environments. A major task in designing such systems is to make the system plastic and adaptive when presented with new and useful information and stable in response to irrelevant events. A great body of knowledge, based on neuro-physiological concepts, has evolved as a possible solution to this problem. Adaptive resonance theory (ART) is a classical example under this category. The system dynamics of an ART network is described by a set of differential equations with nonlinear functions. An approach for designing self-organizing networks characterized by nonlinear differential equations is proposed.

Ramamoorthy, P. A.↗
DOE OSTI2024

Self-organization in collisionless, high- β turbulence

The magnetohydrodynamic (MHD) equations, as a collisional fluid model that remains in local thermodynamic equilibrium (LTE), have long been used to describe turbulence in myriad space and astrophysical plasmas. Yet, the vast majority of these plasmas, from the solar wind to the intracluster medium (ICM) of galaxy clusters, are only weakly collisional at best, meaning that significant deviations from LTE are not only possible but common. Recent studies have demonstrated that the kinetic physics inherent to this weakly collisional regime can fundamentally transform the evolution of such plasmas across a wide range of scales. Here, we explore the consequences of pressure anisotropy and Larmor-scale instabilities for collisionless, β $\gg$ 1, turbulence, focusing on the role of a self-organizational effect known as ‘magneto-immutability’. We describe this self-organization analytically through a high-β, reduced ordering of the Chew–Goldberger–Low-MHD (CGL-MHD) equations, finding that it is a robust inertial-range effect that dynamically suppresses magnetic-field-strength fluctuations, anisotropic-pressure stresses and dissipation due to heat fluxes. As a result, the turbulent cascade of Alfvénic fluctuations continues below the putative viscous scale to form a robust, nearly conservative, MHD-like inertial range. These findings are confirmed numerically via Landau-fluid CGL-MHD turbulence simulations that employ a collisional closure to mimic the effects of microinstabilities. We find that microinstabilities occupy a small (~5%) volume-filling fraction of the plasma, even when the pressure anisotropy is driven strongly towards its instability thresholds. We discuss these results in the context of recent predictions for ion-vs-electron heating in low-luminosity accretion flows and observations implying suppressed viscosity in ICM turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗