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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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NASA NTRS2002

Redshifts for a Sample of Radio-Selected Poor Clusters

Multifiber optical spectroscopy has been performed on galaxies in the vicinity of strong, nearby radio galaxies. These radio galaxies were selected from the, 3CR and B2 catalogs based on their exclusion from the Abell catalog, which is puzzling given the hypothesis that an external medium is required to confine the radio plasma of such galaxies. Velocities derived from the spectra were used to confirm the existence of groups and poor clusters in the fields of most of the radio galaxies. We find that all radio galaxies with classical Fanaroff-Riley type I morphologies prove to reside in clusters, whereas the other radio galaxies often appear to be recent galaxy-galaxy mergers in regions of low galaxy density. These findings confirm the earlier result that the existence of extended X-ray emission combined with a statistical excess of neighboring galaxies can be used to identify poor clusters associated with radio galaxies.

Miller, Neal A.↗
DOE OSTI2024

Redshift evolution and covariances for joint lensing and clustering studies with DESI Y1

ABSTRACT Galaxy–galaxy lensing (GGL) and clustering measurements from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) data set promise to yield unprecedented combined-probe tests of cosmology and the galaxy–halo connection. In such analyses, it is essential to identify and characterize all relevant statistical and systematic errors. We forecast the covariances of DESI Y1 GGL + clustering measurements and the systematic bias due to redshift evolution in the lens samples. Focusing on the projected clustering and GGL correlations, we compute a Gaussian analytical covariance, using a suite of N-body and lognormal simulations to characterize the effect of the survey footprint. Using the DESI one percent survey data, we measure the evolution of galaxy bias parameters for the DESI luminous red galaxy (LRG) and bright galaxy survey (BGS) samples. We find mild evolution in the LRGs in $0.4 < z < 0.8$, subdominant to the expected statistical errors. For BGS, we find less evolution for brighter absolute magnitude cuts, at the cost of reduced sample size. We find that for a redshift bin width $\Delta z = 0.1$, evolution effects on DESI Y1 GGL is negligible across all scales, all fiducial selection cuts, all fiducial redshift bins. Galaxy clustering is more sensitive to evolution due to the bias squared scaling. Nevertheless the redshift evolution effect is insignificant for clustering above the 1-halo scale of $0.1h^{-1}$ Mpc. For studies that wish to reliably access smaller scales, additional treatment of redshift evolution is likely needed. This study serves as a reference for GGL and clustering studies using the DESI Y1 sample.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2000

Constraints on Cosmological Parameters From The Sunyaev-Zel'dovich Effect and Thermal Bremsstrahlung

We discuss the possibility of constraining cosmological parameters using the Sunyaev-Zel'dovich (SZ) effect and thermal bremsstrahlung caused by intra-cluster gas in clusters of galaxies. The new generation of X-ray satellites and ground based interferometers dedicated to SZ observations will enable one to reduce uncertainties in these measurements, and thus make this method potentially quite promising in the near future. The importance of this method is that, unlike most other methods, it is based on physical principles, no 'standard candles' or 'rulers' needed. We estimate the accuracy achievable in the determination of the matter density, OMEGA(sub m), the cosmological constant, OMEGA(sub LAMBDA), and the Hubble constant, h, using the redshift dependence of the angular diameter distance derived from observations in the near future. We demonstrate that constraints from the angular diameter distance are orthogonal to those from Cosmic Microwave Background (CMB) fluctuations in the parameter space defined by OMEGA(sub m), OMEGA(sub LAMBDA), and h. Assuming a statistical error of five percent in the angular diameter distance for each cluster in a sample of five hundred clusters, we show that the redshift dependence of the angular diameter distance combined with constraints from CMB fluctuations can put stringent constraints on OMEGA(sub m) (+/- 0.03), OMEGA(sub LAMBDA) (+/- 0.03) and h (+/- 0.03, 3(sigma) errors). We also show that, with as few as 50 clusters between redshifts 0.01 and 1.5 with an assumed 10% statistical error in the angular diameter distance determination, one can distinguish between models with zero cosmological constant and spatially flat models with a cosmological constant with high confidence level (independently from the supernova results) and put meaningful constraints on OMEGA(sub m) (+/- 0.01), OMEGA(sub LAMBDA) (+/- 0.01) and h (+/- 0.01, 3(sigma) errors). With the expected advances in observational technology, we will be limited by systematic errors. We discuss the sources of systematic errors and how they can be reduced.

Molnar, S. M.↗
DOE OSTI2024

Leveraging graph clustering techniques for cyber‐physical system analysis to enhance disturbance characterisation

Abstract Cyber‐physical systems have behaviour that crosses domain boundaries during events such as planned operational changes and malicious disturbances. Traditionally, the cyber and physical systems are monitored separately and use very different toolsets and analysis paradigms. The security and privacy of these cyber‐physical systems requires improved understanding of the combined cyber‐physical system behaviour and methods for holistic analysis. Therefore, the authors propose leveraging clustering techniques on cyber‐physical data from smart grid systems to analyse differences and similarities in behaviour during cyber‐, physical‐, and cyber‐physical disturbances. Since clustering methods are commonly used in data science to examine statistical similarities in order to sort large datasets, these algorithms can assist in identifying useful relationships in cyber‐physical systems. Through this analysis, deeper insights can be shared with decision‐makers on what cyber and physical components are strongly or weakly linked, what cyber‐physical pathways are most traversed, and the criticality of certain cyber‐physical nodes or edges. This paper presents several types of clustering methods for cyber‐physical graphs of smart grid systems and their application in assessing different types of disturbances for informing cyber‐physical situational awareness. The collection of these clustering techniques provide a foundational basis for cyber‐physical graph interdependency analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Clustering and Cliques in Preferential Attachment Random Graphs with Edge Insertion

In this paper, we investigate the global clustering coefficient (a.k.a transitivity) and clique number of graphs generated by a preferential attachment random graph model with an additional feature of allowing edge connections between existing vertices. Specifically, at each time step t, either a new vertex is added with probability f(t), or an edge is added between two existing vertices with probability 1 – f(t). We establish concentration inequalities for the global clustering and clique number of the resulting graphs under the assumption that f(t) is a regularly varying function at infinity with index of regular variation –$\gamma$, where $\gamma$ $\in$ [0, 1). Finally, we also demonstrate an inverse relation between these two statistics: the clique number is essentially the reciprocal of the global clustering coefficient.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

What determines the stellar mass functions in globular clusters?

We analyze the dependence of stellar mass function slopes for a sample of 17 globular clusters on a variety of cluster parameters. The principal novelty of our approach is the use of appropriate multivariate statistical methods to disentangle the complex situation which is present in this problem: the slopes depend simultaneously on more than one variable, and many cluster parameters are mutually correlated. We find that the mass function slopes in the range M/M(solar) = 0.5-0.8 are largely determined by the position in the Galaxy and to a lesser extent by the cluster metallicity. Clusters closer to the Galactic center or plane have shallower mass function slopes. At a given distance to the Galactic center, clusters closer to the Galactic plane have shallower mass function slopes. At a given R(GC) and/or Z(GP), more metal-rich clusters have shallower mass function slopes. Thus, the monovariate correlations with the position or metallicity are both correct, but only partial, and in terms of slopes, biased descriptions of the situation. We present trivariate least-squares solutions where the mass function slopes can be predicted within the measurement accuracy. This relation can serve as a powerful observational constraint for theories of globular cluster formation and evolution, and it is one of the tightest correlations between globular cluster properties now known.

Djorgovski, S.↗
DOE OSTI2022

Revisiting the Definition of Rapid Intensification of Tropical Cyclones by Clustering the Initial Intensity and Inner‐Core Size

Abstract Rapid intensification (RI) of tropical cyclones (TCs) provides a great challenge in operational forecasting and contributes significantly to the development of major TCs. RI is commonly defined as an increase in the maximum sustained surface wind speed of at least a certain threshold within 24 hr. The most widely used threshold is 30 kt (15.4 m/s), which was determined statistically. Here we propose a new definition for RI by objectively clustering TCs using the intensification rate, initial intensity, and radius of the maximum wind speed (RMW). A group of 770 samples is separated at a threshold of 45 kt (23.2 m/s). The threshold is 40 kt (20.6 m/s) for the western North Atlantic, where TC size measurements are more reliable. Monte Carlo experiments demonstrate that the proposed threshold is robust even considering the uncertainty in RMW of as high as 30 km. We show that, when a TC undergoes RI, its maximum wind speed is approximately 60 ± 15 kt (30.9 ± 7.7 m/s) and the RMW is 45 ± 20 km. The new threshold outperforms the conventional threshold of 30 kt/24 hr in describing the bimodal distribution of lifetime maximum intensity and explaining the annual count of Category 5 TCs. This new definition provides a more physically based threshold and describes a more reliable representation of extreme events. Although more comparisons are needed for operational application, it is likely to be desirable for case‐based process studies and could provide a more valuable metric for TC intensification classification and research.

Li, Yi↗
DOE OSTI2021

An analytic hybrid halo + perturbation theory model for small-scale correlators: baryons, halos, and galaxies

In this work, we update Halo Zeldovich Perturbation Theory (HZPT, [1]), an analytic model for the two-point statistics of dark matter, to describe halo and galaxy clustering, and galaxy-matter cross-correlation on nonlinear scales. The model correcting Zeldovich has an analytic Fourier transform, and therefore is valid in both configuration space and Fourier space. The model is accurate at the 2%-level or less for P_mm (k< 1 h/Mpc), P_hm (k< 1 h/Mpc), P_hh (k< 2 h/Mpc), P gm (k< 1 h/Mpc), P gg (k< 1 h/Mpc), ξ mm (r> 1 Mpc/h), ξ hm (r> 2 Mpc/h), ξ hh (r> 2 Mpc/h), ξ gm (r> 1 Mpc/h), ξ gg (r> 2 Mpc/h), for LRG-like mock galaxies. We show that the HZPT model for matter correlators can account for the effects of a wide range of baryonic feedback models and provide two extended dark matter models which are of 1% (3%) accuracy for k < 10 (8) h/Mpc. We explicitly model the non-perturbative features of halo exclusion for the halo-halo and galaxy-galaxy correlators, as well as the presence of satellites for galaxy-matter and galaxy-galaxy correlation functions. We perform density estimation using N-body simulations and a wide range of HOD galaxy mocks to obtain correlations of model parameters with the cosmological parameters Ω m and σ 8 . HZPT can provide a fast, interpretable, and analytic model for combined-probe analyses of redshift surveys using scales well into the non-linear regime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Cluster spin glass correlations and dynamics in Zn 0.5⁢ Mn 0.5⁢ Te

Here, we present a combined magnetometry, muon spin-relaxation (𝜇⁢SR), and neutron-scattering study of the insulating spin glass Zn 0.5 ⁢Mn 0.5 ⁢Te, for which magnetic Mn 2+ and nonmagnetic Zn 2+ ions are randomly distributed on a face-centered cubic lattice. The magnetometry and 𝜇⁢SR results confirm a spin freezing transition around 𝑇 𝑓 ≈ 23 K, with the spin-fluctuation rate decreasing gradually and somewhat inhomogeneously through the sample volume as the temperature decreases toward 𝑇 𝑓 . Characteristic spin-correlation times well above 𝑇 𝑓 are on the order of 10 −10 s, much slower than typically observed in canonical spin glasses but in line with expectations for a cluster spin glass. Using magnetic pair distribution function (mPDF) analysis and reverse Monte Carlo (RMC) modeling of the magnetic diffuse neutron-scattering data, we show that the spin-glass ground state consists of clusters of spins exhibiting short-range-ordered type-III antiferromagnetic correlations with a locally ordered moment of 3.1⁢(1)⁢𝜇 B between nearest-neighbor spins. The type-III correlations decay exponentially as a function of spin separation distance with a correlation length of approximately 5 Å. The diffuse magnetic scattering and corresponding mPDF show no significant changes across 𝑇 𝑓 , indicating that the dynamically fluctuating short-range spin correlations in the paramagnetic state retain the same basic type-III configuration that characterizes the spin-glass state; the only change apparent from the neutron-scattering data is a gradual reduction of the correlation length and locally ordered moment with increasing temperature. Taken together, these results paint a unique and detailed picture of the local magnetic structure and dynamics in Zn 0.5 ⁢Mn 0.5⁢ Te and provide strong evidence that this material is best described as a cluster spin glass. In addition, this work showcases a statistical method for extracting diffuse scattering signals from neutron powder diffraction data, which we developed to facilitate the mPDF and RMC analysis of the neutron data. This method has the potential to be broadly useful for neutron powder diffraction experiments on a variety of materials with short-range atomic or magnetic order.

magnetism↗
DOE OSTI2025

Geospatial analysis of preterm and small-for-gestational age births in Washington D.C.

Background: This study is based on the recognition that adverse pregnancy outcomes significantly affect maternal and infant health, leading to increased morbidity and mortality. These outcomes are shaped by a complex interplay of individual-level factors—like maternal age and education—and community-level influences, including socio-economic status and access to healthcare. Understanding these determinants is crucial for developing effective public health strategies, especially for marginalized populations, by identifying high-risk areas and informing targeted interventions that address both individual and structural barriers. Methods: We utilized geospatial analysis to explore the association between individual- and community-level factors and adverse pregnancy outcomes, specifically preterm birth (PTB) and small-for-gestational-age (SGA) birthweight in Washington, D.C. We used Empirical Bayes smoothing methods to calculate rates of adverse birth outcomes from 2010 to 2018 at the U.S. Census tract–level. Spatial scan statistics were used to investigate if adverse birth outcomes clustered in specific areas. ANOVA tests were conducted for individual- and community-level factors within identified clusters. Results: Spatial analysis identified significant high-risk clusters for PTB and SGA infants primarily in southeastern Washington, D.C., particularly in Wards 7 and 8. Individuals residing within these clusters experienced a 47% increased risk of PTB (RR = 1.467) and a 56% increased risk of SGA (RR = 1.560) compared to those outside clusters. Space–time analysis revealed temporal variation, with PTB clusters persisting from 2011 to 2014 and SGA clusters extending through 2017. Compared to low-risk clusters, high-risk clusters had younger birthing individuals (mean age ~26.5 vs. ~33 years), lower maternal college degree attainment (~20% vs. ~80%), higher rates of late or no prenatal care (~16% vs. 11%), and increased prevalence of smoking and hypertension (all P < 0.001). Community-level indicators showed lower median household incomes ($\$40,000$ vs. ~$\$105,000$), greater poverty (~16% vs. ~7% below $\$10,000$/year), higher public assistance use (~32% vs. ~5%), and reduced healthcare access (greater distances to emergency and specialty care) in high-risk areas (all P < 0.001). Neighborhood deprivation indices were significantly elevated, commutes were longer, and population density was lower in these clusters. These findings highlight that adverse birth outcomes cluster in neighborhoods with pronounced socioeconomic and health disparities. Conclusion: High-risk birth clusters highlight intertwined factors: individual, socio-economic, and geographic. Addressing these requires comprehensive interventions focusing on social and structural determinants of health.

Birth outcomes↗
DOE OSTI2024

FORESTR: Finding, Organizing, Representing, Explaining, Summarizing, and Thinning Random forests

Random forests have become popular models used for data driven predictions. As a result, random forests are currently used or being considered for high-consequence mission applications in national security, such as the prediction of yield from optical signals and malware detection. While random forests may provide accurate predictions, the complexity of the algorithm causes a lack of interpretability. Random forests are an ensemble of regression or decision trees. Individual regression and decision trees are interpretable, but ensembles are inherently difficult to interpret due to the compilation of many models. We aim to increase the interpretability of random forests by finding patterns in the ensemble of trees that can be used to “thin” (or remove) trees. As a starting point, in this report, we develop a new distance metric for quantifying the similarity between trees based on their topologies (i.e., shapes). We base the metric on a novel distance metric for graphs that is a proper mathematical distance, is invariant to transformations, has registration between graphs, and computes topological evolutions between graphs. We use the tree distance metric to compute tree statistics such as a “mean tree” and to identify clusters of trees. We apply the developed methodology to a toy dataset and a mission relevant product inspection dataset to demonstrate how the metric can provide insight into random forests. Furthermore, we discuss the limitations of the approach and ideas for future research into how the metric could be used as a thinning tool to develop less complex models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg$^{2}$ over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg$^{2}$ using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg$^{2}$ program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

An application of cluster analysis for determining homogeneous subregions: The agroclimatological point of view

A stratification oriented to crop area and yield estimation problems was performed using an algorithm of clustering. The variables used were a set of agroclimatological characteristics measured in each one of the 232 municipalities of the State of Rio Grande do Sul, Brazil. A nonhierarchical cluster analysis was used and the pseudo F-statistics criterion was implemented for determining the "cut point" in the number of strata.

Parada, N. D. J.↗
NASA NTRS1987

Coherent motion induced fluctuations in the primary transition region of a plane shear layer

The naturally occurring large scale motions in a single stream shear layer (that is initiated from a fully turbulent boundary layer) are made evident by the induced velocities in the entrainment region beyond the active shear layer. The distinctive attributes of these induced motions are particularly evident in the Michigan State Univerity Free Shear Flow Facility since the total test section length (3m) is nominally the same as the location of the first, fully formed, coherent motion, ca/x theta (0) = 400 (or 2.5 m). Hence, detailed studies of the induced motions can be executed. Individual coherent motions are identified by the induced velocity signatures and conditional-ensemble statistics are used to represent the irrotational field properties. Clusters of such motions exist; some of their properties are substantially different from the unconditionally averaged values.

Foss, J. F.↗
NASA NTRS1994

Galaxy pairs in deep HST images: Evidence for evolution in the galaxy merger rate

We use four deep serendipitous fields observed with the Hubble Space Telescope (HST) Wide-Field Camera to constrain the rate of galaxy merging between the current epoch and z approximately equals 0.7. Since most mergers occur between members of bound pairs, the merger rate is given to a good approximation by (half) the rate of disappearance of galaxies in pairs. An objective criterion for pair membership shows that 34% +/- 9% of our HST galaxies with I = 18-22 belong to pairs, compared to 7% locally. This means that about 13% of the galaxy population has disappeared due to merging in the cosmic epoch corresponding to this magnitude interval (or 0.1 approximately less than z approximately less than 0.7). Our pair fraction is a lower limit: correction for pair members falling below our detection threshold might raise the fraction to approximately 50%. Since we address only two-galaxy merging, these values do not include physical systems of higher multiplicity. Incorporating I-band field-galaxy redshift distributions, the pair fraction grows with redshift as alpha(1 + z)(exp 3.5 +/- 0.5) and the merger rate as (1 + z)(exp 2.5 +/- 0.5). This may have significant implications for the interpretation of galaxy counts (disappearance of faint blue galaxies), the cosmological evolution of faint radio sources and quasars (which evolve approximately as (1 + z)(exp 3), the similarity in the power law is necessary but not sufficient evidence for a causal relation), statistics of QSO companions, the galaxy content in distant clusters, and the merging history of a 'typical' galaxy.

Burkey, Jordan M.↗
NASA NTRS1997

Structural Qualification of Composite Airframes

The development of fundamental approaches for predicting failure and elongation characteristics of fibrous composites are summarized in this document. The research described includes a statistical formulation for individual fiber breakage and fragmentation and clustered fiber breakage, termed macrodefects wherein the aligned composite may represent a structural component such as a reinforcing bar element, a rebar. Experimental work conducted in support of the future exploitation of aligned composite rebar elements is also described. This work discusses the experimental challenges associated with rebar tensile test evaluation and describes initial numerical analyses performed in support of the experimental program.

Kedward, Keith T.↗
DOE OSTI2023

Limits of Detection for EXAFS Characterization of Heterogeneous Single-Atom Catalysts

Single-atom catalysts (SACs), consisting of individual metal atoms dispersed on a support, attract attention due to their unique reactivity, efficient use of precious metals, and precise chemical tunability. Characterization of the metal species is crucial to substantiate structure–function relationships. Authors often use—and referees often require—X-ray absorption spectroscopy (XAS) data to prove the absence of clustered metal (or metal oxide) structures after pre-treatment and under in situ or operando conditions. However, there has been no critical assessment of the limitations of XAS in substantiating such conclusive statements, which is particularly important given the potential outsized influence of minority catalyst structures in dictating catalytic activity. Here, in this article, we quantitatively assess the detection limits of XAS to identify metal (or metal oxide) clusters in samples containing predominantly single atoms by modeling the extended X-ray absorption fine structure (EXAFS) of mixtures of structures. We identified that a significant fraction of clusters can coexist with SAC active sites (e.g., ~10% metallic Pt or ~40% oxidized Pt clusters in Pt/CeO 2 SACs), while eluding detection via EXAFS with any statistical significance. To generalize these conclusions, a descriptor-based screening of bulk metal oxides using a continuous Cauchy wavelet transform was proposed that suggests certain materials for which differentiating atomically dispersed metal species and metal oxide clusters would be infeasible by EXAFS (e.g., ReO x ). Based on this analysis, we suggest best practices for the study of SACs using EXAFS and provide recommendations to ensure that conclusions do not outpace the evidence used to support them. In this rapidly expanding research area, rigorous characterization will lead to greater understanding of the behavior of SACs and ultimately improved catalytic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗