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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Preventive Power Outage Estimation Based on a Novel Scenario Clustering Strategy

The increasing occurrence of extreme weather events is challenging power grid operation. For extreme weather events, the system operator is responsible for estimating the power outages and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The outputs of an outage prediction model tool are used to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers repair crews and mobile energy resources (MERs). Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative profiles which the system operator can focus on. Finally, case studies on a distribution system evaluate the damage caused by an extreme weather event and verify the effectiveness of the proposed scenario clustering strategy.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗
DOE OSTI2024

Preventive Power Outage Estimation Based on A Novel Scenario Clustering Strategy: Preprint

The increasing occurrence of extreme weather events is challenging the power grid operation. In front of the extreme weather, the system operator is responsible for estimating the power outage and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The predicted vulnerable lines of an outage prediction model tool are utilized to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers the schedule of repair crews and mobile energy resources. Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative ones for straightforward analysis. Finally, case studies on a distribution system evaluate the damage level brought by extreme weather and verify the effectiveness of the proposed scenario clustering strategy.

mobile energy resources↗
DOE OSTI2020

A Clustering-Based Scenario Generation Framework for Power Market Simulation with Wind Integration

A critical step in stochastic optimization models of power system analysis is to select a set of appropriate scenarios and significant numbers of scenario generation methods exist in the literature. This paper develops a clustering based scenario generation method, which aims to improve the performance of existing scenario generation techniques by grouping a set of correlated wind sites into clusters according to their cross-correlations. Copula based models are utilized to model spatiotemporal correlations and the Gibbs sampling is then used to generate scenarios for day-ahead markets. Our results show that the generated scenarios based on clustered wind sites outperform existing approaches in terms of reliability and sharpness and can reduce the total computational time for scenario generation and reduction significantly. The clustering-based framework can therefore provide a better support for real-world market simulations with high wind penetration.

data visualization↗
NASA NTRS1995

A serach for 'failed clusters' of galaxies

We describe a search for a new type of object - large clouds of hot gas with no visible galaxies - which we call failed clusters of galaxies. We calculate the expected X-ray luminosity, temperature, and angular diameter of such objects as a function of total cloud mass and convert the results to expected X-ray fluxes from failed clusters at different redshifts. Using the Einstein Imaging Proportional Counter (IPC) database, we establish a strategy to search for candidate failed clusters. From this initial screening of 1435 IPC fields, 17 candidates are selected for more detailed analysis, which indicates that 10 of these are very probably extended X-ray sources. Optical follow-up on the 10 prime candidates finds eight clusters of galaxies (including six reproted for the first time in this paper), one stellar identification, and one without an obvious optical counterpart (the candidate with the weakest evidence for X-ray extent). Investigation of several candidates with less evidence for X-ray extent yields two additional new clusters of galaxies. A conservative comparison of our results with the Einstein Extended Medium Sensitivity Survey demonstrates that failed clusters are a relatively unimportant contributor to the mass density of the universe. Our inability to find failed clusters is consistent with the hierarchical clustering scenario for the formation of galaxies and clusters.

Tucker, W. H.↗
NASA NTRS1982

The cosmic microwave background radiation as a probe of the large-scale structure of the universe

Cosmological and astrophysical implications of large scale fluctuations in the cosmic microwave background are discussed, with attention given to galaxy formation. Angular anisotropies are mentioned as yielding information on the matter distribution during early epochs, characterized by inhomogeneities which persist on large scales. Factors such as the curvature of the universe and the hypothesis of massive neutrinos with m more than 30 eV affect the observed anomalies, which can be traced backwards to determine the source of nonlinear structures. Neutrino rest masses of less than a few eV imply isothermal fluctuations in the initial conditions, while gaseous fragmentation of adiabatic pancakes does provide a basis for an acceptable galaxy formation and clustering scenario. However, the primordial isothermal fluctuations fit well with observational constraints imposed by a neutrino-dominated universe.

Silk, J.↗
NASA NTRS1985

On percolation as a cosmological test

Difficulties in the use of percolation as a complementary statistic for the galaxy clustering pattern are pointed out by studying simple toy models and dynamical N-body models that represent the competing clustering scenarios. The percolation properties are found not to be very sensitive to the presence of pancakes and strings once they are clumpy, and hence they do not distinguish properly between models that are very different. In the case of very smooth pancakes, the ability to percolate depends on sampling parameters, such as the mean number density and the volume, in a way which is unknown a priori because it depends on the same properties that the test ought to measure. This problem could, in principle, be eased by using volume-limited samples of high mean number density (an order of magnitude denser than the CfA redshift survey volume limited at 4000 km/s) and by comparing to models of identical number density and volume. An alternative approach, based on the sampling effects themselves, may provide a qualitative test for pancakes in samples of lower densities.

Dekel, A.↗
NASA NTRS1992

Higher order correlations of IRAS galaxies

The higher order irreducible angular correlation functions are derived up to the eight-point function, for a sample of 4654 IRAS galaxies, flux-limited at 1.2 Jy in the 60 microns band. The correlations are generally found to be somewhat weaker than those for the optically selected galaxies, consistent with the visual impression of looser clusters in the IRAS sample. It is found that the N-point correlation functions can be expressed as the symmetric sum of products of N - 1 two-point functions, although the correlations above the four-point function are consistent with zero. The coefficients are consistent with the hierarchical clustering scenario as modeled by Hamilton and by Schaeffer.

Meiksin, Avery↗
NASA NTRS1993

Faint blue counts from formation of dwarf galaxies at z approximately equals 1

The nature of faint blue objects (FBO's) has been a source of much speculation since their detection in deep CCD images of the sky. Their high surface density argues against them being progenitors of present-day bright galaxies and since they are only weakly clustered on small scales, they cannot be entities that merged together to form present-day galaxies. Babul & Rees (1992) have suggested that the observed faint blue counts may be due to dwarf elliptical galaxies undergoing their initial starburst at z is approximately equal to 1. In generic hierarchical clustering scenarios, however, dwarf galaxy halos (M is approximately 10(exp 9) solar mass) are expected to form at an earlier epoch; for example, typical 10(exp 9) solar mass halos will virialize at z is approximately equal to 2.3 if the power-spectrum for the density fluctuations is that of the standard b = 2 cold dark matter (CDM) model. Under 'ordinary conditions' the gas would rapidly cool, collect in the cores, and undergo star-formation. Conditions at high redshifts are far from 'ordinary'. The intense UV background will prevent the gas in the dwarf halos from cooling, the halos being released from their suspended state only when the UV flux has diminished sufficiently.

Babul, Arif↗
DOE OSTI2024

Stochastic economic dispatch of wind power under uncertainty using clustering-based extreme scenarios

Operation of power systems with high penetrations of renewable energy sources requires tools for robust decision making under uncertainty. Stochastic economic dispatch and stochastic unit commitment are effective techniques for planning and operation under uncertainty, whose effectiveness depends on the cardinality and quality of the scenario set. Here, this article proposes a machine learning method using -means clustering for capturing relevant physical information from a large population of analog scenarios. Extreme scenario samples drawn from the clusters are used in a two-stage stochastic economic dispatch computation. The effectiveness of the proposed approach is assessed on a synthetic 200-bus system with a geographic footprint over Illinois, USA for four months from each season of WIND Toolkit data. The combination of -means clustering with importance sampling is shown to reduce the total operational cost by over 43% compared to sampling from populations based on heuristic clustering-based methods. Additionally, the variability in the mean cost is about 56% lower than the variability using Monte Carlo sampling. Moreover, the operational cost with the presented approach is shown to be close to the cost calculated based on a hindsight exact wind profile, signifying a highly accurate quantification of wind uncertainty by the presented -means clustering based sampling method.

17 WIND ENERGY↗
NASA NTRS1994

Hot gas in the cold dark matter scenario: X-ray clusters from a high-resolution numerical simulation

A new, three-dimensional, shock-capturing hydrodynamic code is utilized to determine the distribution of hot gas in a standard cold dark matter (CDM) model of the universe. Periodic boundary conditions are assumed: a box with size 85 h(exp -1) Mpc having cell size 0.31 h(exp -1) Mpc is followed in a simulation with 270(exp 3) = 10(exp 7.3) cells. Adopting standard parameters determined from COBE and light-element nucleosynthesis, sigma(sub 8) = 1.05, omega(sub b) = 0.06, and assuming h = 0.5, we find the X-ray-emitting clusters and compute the luminosity function at several wavelengths, the temperature distribution, and estimated sizes, as well as the evolution of these quantities with redshift. We find that most of the total X-ray emissivity in our box originates in a relatively small number of identifiable clusters which occupy approximately 10(exp -3) of the box volume. This standard CDM model, normalized to COBE, produces approximately 5 times too much emission from clusters having L(sub x) is greater than 10(exp 43) ergs/s, a not-unexpected result. If all other parameters were unchanged, we would expect adequate agreement for sigma(sub 8) = 0.6. This provides a new and independent argument for lower small-scale power than standard CDM at the 8 h(exp -1) Mpc scale. The background radiation field at 1 keV due to clusters in this model is approximately one-third of the observed background, which, after correction for numerical effects, again indicates approximately 5 times too much emission and the appropriateness of sigma(sub 8) = 0.6. If we have used the observed ratio of gas to total mass in clusters, rather than basing the mean density on light-element nucleosynthesis, then the computed luminosity of each cluster would have increased still further, by a factor of approximately 10. The number density of clusters increases to z approximately 1, but the luminosity per typical cluster decreases, with the result that evolution in the number density of bright clusters is moderate in this redshift range, showing a broad peak near z = 0.7, and then a rapid decline above redshift z = 3. Detailed computations of the luminosity functions in the range L(sub x) = 10(exp 40) - 10(exp 44) ergs/s in various energy bands are presented for both cluster central regions and total luminosities to be used in comparison with ROSAT and other observational data sets. The quantitative results found disagree significantly with those found by other investigators using semianalytic techniques. We find little dependence of core radius on cluster luminosity and a dependence of temperature on luminosity given by log kT(sub x) = A + B log L(sub x), which is slightly steeper (B = 0.38) than is indicated by observations. Computed temperatures are somewhat higher than observed, as expected, in that COBE-normalized CDM has too much power on the relevant scales. A modest average temperature gradient is found, with temperatures dropping to 90% of central values at 0.4 h(exp -1) Mpc and 70% of central values at 0.9 h(exp -1) Mpc. Examining the ratio of gas to total mass in the clusters normalized to Omega(sub B) h(exp 2) = 0.015, and comparing with observations, we conclude, in agreement with White (1991), that the cluster observations argue for an open universe.

Kang, Hyesung↗
NASA NTRS1992

The efficiency of galaxy formation in clusters

Whether the observed trend in the efficiency of galaxy formation between poor and rich clusters is consistent with CDM-biased galaxy formation scenarios or with other hierarchical clustering scenarios described by a power-law fluctuation spectrum from galaxy to rich cluster scales in a universe with density parameter Omega = 1. A greater statistical correlation is found between galaxy and poor cluster masses than between galaxy and rich cluster masses due to the cluster proximity in filter length. This is the fundamental reason why galaxy formation is more efficient in poor clusters than in rich ones. It is found that the observed trend in the efficiency of galaxy formation and the observed values can be produced within the context of CDM-based galaxy formation scenarios or other scenarios involving flat spectra if X-ray luminous clusters are typically 2-3 sigma objects.

David, Laurence P.↗
DOE OSTI2025

Predicting Dynamic-to-Static Correction Factor from Petrophysical Data and Chemostratigraphy using Unsupervised Machine Learning

Estimating static mechanical properties of stratigraphic layers is critical for optimizing subsurface engineering applications. To estimate dynamic-to-static correction factor F ds (static-to-dynamic Young’s modulus ratio) across the Caney shale interval in Oklahoma, USA, we integrated triaxial test measurements and petrophysical data, including well logs and X-ray fluorescence (XRF) using unsupervised machine learning (ML). We used a novel workflow that includes principal component analysis (PCA) to reduce data set dimensionality of well logs and XRF data sets—both separately and combined—creating three scenarios, and later applied inverse distance weighting (IDW) to derive F ds profiles for these scenarios. Furthermore, we applied K-means clustering on each scenario to predict depositional facies, and built a stiffness zonation profile through chemostratigraphic analysis of the terrigenous elements to validate the predicted F ds . The predicted F ds profile from each scenario using the PCA-IDW method was compared with the constant F ds approach from our previous study by calculating the root mean square error (RMSE). The combined data sets scenario yielded the lowest RMSE value of 0.113, while the RMSE values for the well logs and XRF scenarios were 0.131 and 0.129, respectively. In addition, the predicted F ds from the XRF scenario well-matched the stiffness zonation from the chemostratigraphic analysis that was built using the optimized K-means clustering of nine clusters for that scenario. These methods and findings offer a valuable tool for refining lithological classification and improving the F ds profile, potentially enhancing drilling and stimulation strategies for subsurface energy engineering applications.

clastic rock↗
NASA NTRS2006

The Evolution of the Cluster X-ray Scaling Relations in the Wide Angle ROSAT Pointed Survey Sample at 0.6 < z < 1.0

The X-ray properties of a sample of 11 high-redshift (0.6 < z < 1 .O) clusters observed with Chardm and/or XMM-Newton are used to investigate the evolution of the cluster scaling relations. The observed evolution in the normalization of the L-T, M-T, M(sub 2)-T and M-L relations is consistent with simple self-similar predictions, in which the properties of clusters reflect the properties of the Universe at their redshift of observation. Under the assumption that the model of self-similar evolution is correct and that the local systems formed via a single spherical collapse, the high-redshift L-T relation is consistent with the high-z clusters having virialized at a significantly higher redshift than the local systems. The data are also consistent with the more realistic scenario of clusters forming via the continuous accretion of material. The slope of the L-T relation at high redshift (B = 3.32 +/- 0.37) is consistent with the local relation, and significantly steeper than the self-similar prediction of B = 2. This suggests that the same non-gravitational processes are responsible for steepening the local and high-z relations, possibly occurring universally at z is approximately greater than 1 or in the early stages of the cluster formation, prior to their observation. The properties of the intracluster medium at high redshift are found to be similar to those in the local Universe. The mean surface-brightness profile slope for the sample is Beta = 0.66 +/- 0.05, the mean gas mass fractions within R(sub 2500(z)) and R(200(z)) are 0.069 +/- 0.012 and 0.11 +/- 0.02, respectively, and the mean metallicity of the sample is 0.28 +/- 0.11 Z(sub solar).

Maughan, B. J.↗
NASA NTRS2002

Using Clustering to Establish Climate Regimes from PCM Output

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Oglesby, Robert↗
NASA NTRS1992

Production of recycled pulsars in globular clusters via two-body tidal capture

The numbers of binary systems containing a neutron star that are formed in the cores of globular clusters via two-body tidal capture are investigated. The subsequent evolution of the resulting binary systems is examined. Monte Carlo techniques are employed to trace the histories of many neutron stars in the core of a model globular cluster. Various scenarios for mass stripping during capture and orbital circularization, and the effects of magnetic braking on the circularized orbits are explored. Calculations are carried out for two model clusters: 47 Tuc and Omega Cen. Distributions of orbital periods for newly formed binaries containing a neutron star in orbit with either a main-sequence star or a giant are presented. Each binary is followed until contact between the captured star and the neutron star is established. It is argued that these systems should be regarded as potential progenitors of 'recycled' pulsars.

Di Stefano, R↗
NASA NTRS1992

Semiempirical limits on the thermal conductivity of intracluster gas

A semiempirical method for establishing lower limits on the thermal conductivity of hot gas in clusters of galaxies is described. The method is based on the observation that the X-ray imaging data (e.g., Einstein IPC) for clusters are well described by the hydrostatic-isothermal beta model, even for cooling flow clusters beyond about one core radius. In addition, there are strong indications that noncooling flow clusters (like the Coma Cluster) have a large central region (up to several core radii) of nearly constant gas temperature. This suggests that thermal conduction is an effective means of transporting and redistributing the thermal energy of the gas. This in turn has implications for the extent to which magnetic fields in the cluster are effective in reducing the thermal conductivity of the gas. Time-dependent hydrodynamic simulations for the gas in the Coma Cluster under two separate evolutionary scenarios are presented. One scenario assumes that the cluster potential is static and that the gas has an initial adiabatic distribution. The second scenario uses an evolving cluster potential. These models along with analytic results show that the thermal conductivity of the gas in the Coma Cluster cannot be less than 0.1 of full Spitzer conductivity. These models also show that high gas conductivity assists rather than hinders the development of radiative cooling in the central regions of clusters.

David, Laurence P.↗
NASA NTRS1993

The peculiar velocities of rich clusters in the hot and cold dark matter scenarios

We present the results of a study of the peculiar velocities of rich clusters of galaxies. The peculiar motion of rich clusters in various cosmological scenarios is of interest for a number of reasons. Observationally, one can measure the peculiar motion of clusters to greater distances than galaxies because cluster peculiar motions can be determined to greater accuracy. One can also test the slope of distance indicator relations using clusters to see if galaxy properties vary with environment. We have used N-body simulations to measure the amplitude and rms cluster peculiar velocity as a function of bias parameter in the hot and cold dark matter scenarios. In addition to measuring the mean and rms peculiar velocity of clusters in the two models, we determined whether the peculiar velocity vector of a given cluster is well aligned with the gravity vector due to all the particles in the simulation and the gravity vector due to the particles present only in the clusters. We have investigated the peculiar velocities of rich clusters of galaxies in the cold dark matter and hot dark matter galaxy formation scenarios. We have derived peculiar velocities and associated errors for the scenarios using four values of the bias parameter ranging from b = 1 to b = 2.5. The growth of the mean peculiar velocity with scale factor has been determined and compared to that predicted by linear theory. In addition, we have compared the orientation of force and velocity in these simulations to see if a program such as that proposed by Bertschinger and Dekel (1989) for elliptical galaxy peculiar motions can be applied to clusters. The method they describe enables one to recover the density field from large scale redshift distance samples. The method makes it possible to do this when only radial velocities are known by assuming that the velocity field is curl free. Our analysis suggests that this program if applied to clusters is only realizable for models with a low value of the bias parameter, i.e., models in which the peculiar velocities of clusters are large enough that the errors do not render the analysis impracticable.

Rhee, George F.↗
DOE OSTI2023

Late growth of early-type galaxies in low-z massive clusters

ABSTRACT We study a sample of 936 early-type galaxies (ETGs) located in 48 low-z regular galaxy clusters with M200 ≥ 1014 M⊙ at z < 0.1. We examine variations in the concentration index, radius, and colour gradient of ETGs as a function of their stellar mass and loci in the projected phase space (PPS) of the clusters. We aim to understand the environmental influence on the growth of ETGs according to the time since infall into their host clusters. Our analysis indicates a significant change in the behaviour of the concentration index C and colour gradient around $M_{\ast } \approx 2\times 10^{11} ~M_\odot \equiv \tilde{M}_{\ast }$. Objects less massive than $\tilde{M}_{\ast }$ present a slight growth of C with M*, with negative and approximately constant colour gradients in all regions of the PPS. Objects more massive than $\tilde{M}_{\ast }$ present a slight decrease of C with M*, with colour gradients becoming less negative and approaching zero. We also find that objects more massive than $\tilde{M}_{\ast }$, in all PPS regions, have smaller R90 for a given R50, suggesting a smaller external growth in these objects or even a shrinkage possibly due to tidal stripping. Finally, we estimate different dark matter fractions for galaxies in different regions of the PPS, with the ancient satellites having the largest fractions, fDM ≈ 65 per cent. These results favour a scenario where cluster ETGs experience environmental influence the longer they remain and the deeper into the gravitational potential they lie, indicating a combination of tidal stripping + harassment, which predominate during infall, followed by mergers + feedback effects affecting the late growth of ancient satellites and BCGs.

Astronomy & Astrophysics↗