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Neutrino Analysis of the September 2010 Crab Nebula Flare and Time-Integrated Constraints on Neutrino Emission from the Crab Using IceCube

We present the results for a search of high-energy muon neutrinos with the IceCube detector in coincidence with the Crab nebula flare reported on September 2010 by various experiments. Due to the unusual flaring state of the otherwise steady source we performed a prompt analysis of the 79-string configuration data to search for neutrinos that might be emitted along with the observed gamma-rays. We performed two different and complementary data selections of neutrino events in the time window of 10 days around the flare. One event selection is optimized for discovery of E(sub v)(sup -2) neutrino spectrum typical of 1st order Fermi acceleration. A similar event selection has also been applied to the 40-string data to derive the time-integrated limits to the neutrino emission from the Crab [35]. The other event selection was optimized for discovery of neutrino spectra with softer spectral index and TeV energy cut-offs as observed for various galactic sources in gamma-rays. The 90% CL best upper limits on the Crab flux during the 10 day flare are 4.73 x 10(exp -11) per square centimeter per second TeV(sup -1) for an E(sub v)(sup -2) neutrino spectrum and 2.50 x 10(exp -10) per square centimeter per second TeV(sup -1) for a softer neutrino spectra of E(sub v)(sup -2.7), as indicated by Fermi measurements during the flare. IceCube has also set a time-integrated limit on the neutrino emission of the Crab using 375.5 days of livetime of the 40-string configuration data. This limit is compared to existing models of neutrino production from the Crab and its impact on astrophysical parameters is discussed. The most optimistic predictions of some models are already rejected by the IceCube neutrino telescope with more than 90% CL.

Abbasi, R.

Neutrino Analysis of the September 2010 Crab Nebula Flare and Time-integrated Constraints on Neutrino Emission From the Crab Using IceCube

We present the results for a search of high-energy muon neutrinos with the IceCube detector in coincidence with the Crab nebula flare reported on September 2010 by various experiments. Due to the unusual flaring state of the otherwise steady source we performed a prompt analysis of the 79-string configuration data to search for neutrinos that might be emitted along with the observed gamma-rays. We performed two different and complementary data selections of neutrino events in the time window of 10 days around the flare. One event selection is optimized for discovery of E(sub nu)(sup -2) neutrino spectrum typical of 1st order Fermi acceleration. A similar event selection has also been applied to the 40-string data to derive the time-integrated limits to the neutrino emission from the Crab [35]. The other event selection was optimized for discovery of neutrino spectra with softer spectral index and TeV energy cut-offs as observed for various galactic sources in gamma-rays. The 90% CL best upper limits on the Crab flux during the 10 day flare are 4.73 x 10(exp -11) per square centimeter per second TeV (sup -1) for an E(sub nu) (sup -2) neutrino spectrum and 2.50 x 10(exp -10) per square centimeter per second TeV(sup -1) for a softer neutrino spectra of E(sub nu)(sup -2.7), as indicated by Fermi measurements during the flare. IceCube has also set a time-integrated limit on the neutrino emission of the Crab using 375.5 days of livetime of the 40-string configuration data. This limit is compared to existing models of neutrino production from the Crab and its impact on astrophysical parameters is discussed. The most optimistic predictions of some models are already rejected by the IceCube neutrino telescope with more than 90% CL.

Stamatikos, M.

Nuclear Technology Selection and Preliminary Integration at St. Charles and Carrollton Chemical Plants

Nuclear energy is identified as a valuable candidate for decarbonizing industrial facilities as a non-emitting baseload energy source capable of dispatching energy as needed for an integrated facility. As industrial facilities are unique, analyzing what nuclear technology is the best candidate should be evaluated on a case-by-case basis. For two identified facilities of the Dow Chemical Company, an ideal mix of nuclear energy resources is calculated, and integration strategies are put forward. This research was funded through a Gateway for Accelerated Innovation in Nuclear (GAIN) Nuclear Energy Voucher, specifically seeking near-term engineering solutions for the technical issue of introducing nuclear generated energy into the Dow chemical facilities. The research is split into four main phases: background on reactors and chemical facilities, preliminary engineering analysis determining how reactor technologies may be integrated with specific facilities, site characterization and discrete hazards analysis, and finally an optimization of reactor-facility selection through the use of Framework for Optimization of ResourCes and Economics (FORCE) tools.

22 GENERAL STUDIES OF NUCLEAR REACTORS

A medium sensitivity X-ray survey using the Einstein Observatory - The log N-log S relation for extragalactic X-ray sources

The paper presents results of an X-ray survey of about 50 sq deg of the high galactic latitude sky at sensitivities in the range of 7 x 10 to the -14 to 5 x 10 to the -12 ergs/sq cm/s. The number-flux relation is derived for the extragalactic population to yield a best-fit power-law slope of 1.53 + or - 0.16, and the content of the sample is analyzed in terms of types of sources, appearing to be significantly different from the content of similar samples selected at higher fluxes. The medium sensitivity sample of extragalactic sources is dominated by active galactic nuclei, while samples selected at higher fluxes and higher energies are dominated by clusters of galaxies. Thus, the number-flux relation for extragalactic sources may be interpreted to a first approximation as the sum of the two different distributions with flatter and steeper slopes describing clusters and AGNs, respectively.

Maccacaro, T.

X-ray-selected M dwarfs and the diffuse X-ray background

A systematic optical identification program was carried out for serendipitous X-ray sources discovered by the Einstein Observatory. A total of 104 were detected above the threshold flux of 3 x 10 to the -13th ergs/sq cm per sec in the 114 sq deg survey region; 11 of these 104 sources are dM stars. Including X-ray-selected M dwarfs from the LMC survey, the Medium Sensitivity Survey, and the Einstein Deep Survey, a dwarf M star composite X-ray spectrum was constructed; the best-fit thermal model yields kT = 1.3 + or - 0.3 keV, consistent with typical active star spectra. An M dwarf X-ray luminosity function was also constructed and it is concluded that the integrated contribution to the diffuse soft (0.28-1.0 keV) X-ray background from such stars is less than 10 percent, a factor of more than about 2 lower than previous estimates. This result is consistent with a limit on the dwarf M star contribution derived from a spectral decomposition of the observed X-ray background spectrum.

Caillault, J.-P.

An assessment of image reconstruction from balloon-borne and the IRAS data

Angular resolution and structural information from the far-infrared mapping of astronomical sources (Galactic star forming regions, spiral galaxies, etc.) made using the TIFR 1 m balloon-borne telescope and the IRAS have been compared. The effective wavelengths of the TIFR two-band photometer are 58 and 150 microns. From IRAS, the survey COADD data, additional observations (AO's) made with the survey detectors with different Macros (DPS, DSD, DPM), as well as the chopped photometric channel (CPC) data have been considered here. The observed signals have been processed using different deconvolution strategies, either based on a maximum entropy method (MEM) developed at TIFR or the HiRes package developed at IPAC. Relative merits of each of these, under different conditions of signal to noise ratio, are highlighted. The following sources have been selected for illustration: Carina complex, W31 region, IRAS 10361-5830 (all Galactic), M101 and M81 (extragalactic). The main conclusions are: far-infrared maps from MEM deconvolution of balloon-borne data have the best angular resolution; MEM deconvolution of IRAS AO's gives resolution comparable to HiRes but with less amount of computation, though the dynamic range in MEM maps is less than in HiRes maps.

Ghosh, S. K.

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali

The Rise of SN 2014J in the Nearby Galaxy M 82

We report on the discovery of SN 2014J in the nearby galaxy M 82. Given its proximity, it offers the best opportunity to date to study a thermonuclear supernova over a wide range of the electromagnetic spectrum. Optical, near-IR and mid-IR observations on the rising lightcurve, orchestrated by the intermediate Palomar Transient Factory (iPTF), show that SN 2014J is a spectroscopically normal Type Ia supernova, albeit exhibiting high-velocity features in its spectrum and heavily reddened by dust in the host galaxy. Our earliest detections start just hours after the fitted time of explosion. We use high-resolution optical spectroscopy to analyze the dense intervening material and do not detect any evolution in the resolved absorption features during the lightcurve rise. Similarly to other highly reddened Type Ia supernovae, a low value of total-to-selective extinction, R (sub V) less than or approximately equal to 2, provides the best match to our observations. We also study pre-explosion optical and near-IR images from HST with special emphasis on the sources nearest to the SN location.

galaxy

Investing American Recovery and Reinvestment Act Funds to Advance Capability, Reliability, and Performance in NASA Wind Tunnels

The National Aeronautics and Space Administration's (NASA) Aeronautics Test Program (ATP) is implementing five significant ground-based test facility projects across the nation with funding provided by the American Recovery and Reinvestment Act (ARRA). The projects were selected as the best candidates within the constraints of the ARRA and the strategic plan of ATP. They are a combination of much-needed large scale maintenance, reliability, and system upgrades plus creating new test beds for upcoming research programs. The projects are: 1.) Re-activation of a large compressor to provide a second source for compressed air and vacuum to the Unitary Plan Wind Tunnel at the Ames Research Center (ARC) 2.) Addition of high-altitude ice crystal generation at the Glenn Research Center Propulsion Systems Laboratory Test Cell 3, 3.) New refrigeration system and tunnel heat exchanger for the Icing Research Tunnel at the Glenn Research Center, 4.) Technical viability improvements for the National Transonic Facility at the Langley Research Center, and 5.) Modifications to conduct Environmentally Responsible Aviation and Rotorcraft research at the 14 x 22 Subsonic Tunnel at Langley Research Center. The selection rationale, problem statement, and technical solution summary for each project is given here. The benefits and challenges of the ARRA funded projects are discussed. Indirectly, this opportunity provides the advantages of developing experience in NASA's workforce in large projects and maintaining corporate knowledge in that very unique capability. It is envisioned that improved facilities will attract a larger user base and capabilities that are needed for current and future research efforts will offer revenue growth and future operations stability. Several of the chosen projects will maximize wind tunnel reliability and maintainability by using newer, proven technologies in place of older and obsolete equipment and processes. The projects will meet NASA's goal of integrating more efficient, environmentally safer, and less energy consuming hardware and processes into existing tunnel systems. These include Environmental Protection Agency-approved refrigerants, energy efficient motors, and faster, flexible tunnel data systems.

Sydnor, Goerge H.

A Review and Comparison of Different Sensitivity Analysis Techniques in Practice

There exist many methods for sensitivity analysis readily available to the practitioner. While each seeks to help the modeler answer the same general question – How do sources of uncertainty or changes in the model inputs relate to uncertainty in the output? – different methods are associated with different assumptions, constraints, and required resources, leading to conclusions that may vary in interpretability and level of detail. Thus, it is crucial that the practitioner selects the desired sensitivity analysis method judiciously, making sure to match the selected approach to the specifics of their problem and to their desired objectives. In this chapter, we provide a practical overview of a collection of widely used, widely available sensitivity analysis methods. We focus on global sensitivity approaches, which seek to characterize how uncertainty in the model output may be allocated to sources of uncertainty in model inputs across the entire input space. Generally, this will require the practitioner to specify a probability distribution over the input space. On the other hand, methods for local sensitivity analysis do not require this specification but they have more limited utility, providing insight into sources of uncertainty associated only with a particular, specified location in the input space. Our hope is that this chapter may serve as a decision-making tool for practitioners, helping to guide the selection of a sensitivity analysis approach that will best fit their needs. To support this goal, we have selected a suite of approaches to cover, which, while not exhaustive, we believe provides a flexible and robust sensitivity analysis toolkit. All methods included are widely used and available in standard software packages.

97 MATHEMATICS AND COMPUTING

Identification of High Performance, Low Environmental Impact Materials and Processes Using Systematic Substitution (SyS)

Process analysis can identify opportunities for efficiency improvement including cost reduction, increased safety, improved quality, and decreased environmental impact. A thorough, systematic approach to materials and process selection is valuable in any analysis. New operations and facilities design offer the best opportunities for proactive cost reduction and environmental improvement, but existing operations and facilities can also benefit greatly. Materials and processes that have been used for many years may be sources of excessive resource use, waste generation, pollution, and cost burden that should be replaced. Operational and purchasing personnel may not recognize some materials and processes as problems. Reasons for materials or process replacement may include quality and efficiency improvements, excessive resource use and waste generation, materials and operational costs, safety (flammability or toxicity), pollution prevention, compatibility with new processes or materials, and new or anticipated regulations.

Dhooge, P. M.

20-GHz phased-array-fed antennas utilizing distributed MMIC modules

The feasibility of phased-array-fed dual-reflector systems with distributed power and phase control, and utilizing monolithic microwave integrated circuit modules, is demonstrated. Secondary radiation patterns for various antenna configurations, calculated using a method in which the phased array for each scanning direction is simulated by a fictitious point source, are computed to determine the achievable EIRP levels, sidelobe isolation, and cross-polarization isolation. The focal-region-fed Cassegrain reflector was found to be best suited for fixed multiple beam applications, while the phased-array-fed dual-reflector configuration was selected for multiple scanning beams. Key elements of the phased-array design including a radiating square horn and a square orthomode transducer were fabricated and tested.

Sorbello, R. M.

Atacama Cosmology Telescope measurements of a large sample of candidates from the Massive and Distant Clusters of WISE Survey: Sunyaev-Zeldovich effect confirmation of MaDCoWS candidates using ACT

Context. Galaxy clusters are an important tool for cosmology, and their detection and characterization are key goals for current and future surveys. Using data from the Wide-field Infrared Survey Explorer (WISE), the Massive and Distant Clusters of WISE Survey (MaDCoWS) located 2839 significant galaxy overdensities at redshifts 0.7 . z . 1.5, which included extensive follow-up imaging from the Spitzer Space Telescope to determine cluster richnesses. Concurrently, the Atacama Cosmology Telescope (ACT) has produced large area millimeter-wave maps in three frequency bands along with a large catalog of Sunyaev-Zeldovich (SZ)-selected clusters as part of its Data Release 5 (DR5). Aims. We aim to verify and characterize MaDCoWS clusters using measurements of, or limits on, their thermal SZ effect signatures. We also use these detections to establish the scaling relation between SZ mass and the MaDCoWS-defined richness. Methods. Using the maps and cluster catalog from DR5, we explore the scaling between SZ mass and cluster richness. We do this by comparing cataloged detections and extracting individual and stacked SZ signals from the MaDCoWS cluster locations. We use complementary radio survey data from the Very Large Array, submillimeter data from Herschel, and ACT 224 GHz data to assess the impact of contaminating sources on the SZ signals from both ACT and MaDCoWS clusters. We use a hierarchical Bayesian model to fit the mass-richness scaling relation, allowing for clusters to be drawn from two populations: one, a Gaussian centered on the mass-richness relation, and the other, a Gaussian centered on zero SZ signal. Results. We find that MaDCoWS clusters have submillimeter contamination that is consistent with a gray-body spectrum, while the ACT clusters are consistent with no submillimeter emission on average. Additionally, the intrinsic radio intensities of ACT clusters are lower than those of MaDCoWS clusters, even when the ACT clusters are restricted to the same redshift range as the MaDCoWS clusters. We find the best-fit ACT SZ mass versus MaDCoWS richness scaling relation has a slope of p1 = 1.84+0.15 −0.14, where the slope is defined as M ∝ λ p1 15 and λ15 is the richness. We also find that the ACT SZ signals for a significant fraction (∼57%) of the MaDCoWS sample can statistically be described as being drawn from a noise-like distribution, indicating that the candidates are possibly dominated by low-mass and unvirialized systems that are below the mass limit of the ACT sample. Further, we note that a large portion of the optically confirmed ACT clusters located in the same volume of the sky as MaDCoWS are not selected by MaDCoWS, indicating that the MaDCoWS sample is not complete with respect to SZ selection. Finally, we find that the radio loud fraction of MaDCoWS clusters increases with richness, while we find no evidence that the submillimeter emission of the MaDCoWS clusters evolves with richness. Conclusions. We conclude that the original MaDCoWS selection function is not well defined and, as such, reiterate the MaDCoWS collaboration’s recommendation that the sample is suited for probing cluster and galaxy evolution, but not cosmological analyses. We find a best-fit mass-richness relation slope that agrees with the published MaDCoWS preliminary results. Additionally, we find that while the approximate level of infill of the ACT and MaDCoWS cluster SZ signals (1–2%) is subdominant to other sources of uncertainty for current generation experiments, characterizing and removing this bias will be critical for next-generation experiments hoping to constrain cluster masses at the sub-percent level.

large

Selected Theoretical Studies Group contributions to the 14th International Cosmic Ray conference

The galactic distribution of H2 was studied through gamma radiation and through X-ray, optical, and infrared absorption measurements from SAS-2 and other sources. A comparison of the latitude distribution of gamma-ray intensity with reddening data shows reddening data to give the best estimate of interstellar gas in the solar vicinity. The distribution of galactic cosmic ray nucleons was determined and appears to be identical to the supernova remnant distribution. Interactions between ultrahigh energy cosmic-ray nuclei and intergalactic photon radiation fields were calculated, using the Monte Carlo method.

Source record

3D Photocatalytic Air Processor for Dramatic Reduction of Life Support Mass and Complexity

To dramatically reduce the cost and risk of CO2 management systems in future extended missions, we have conducted preliminary studies on the materials and device development for advanced "artificial photosynthesis" reaction systems termed the High Tortuosity PhotoElectroChemical (HTPEC) system. Our Phase I studies have demonstrated that HTPEC operates in much the same way a tree would function, namely directly contacting the cabin air with a photocatalyst in the presence of light and water (as humidity) to immediately conduct the process of CO2 reduction to O2 and useful, "tunable" carbon products. This eliminates many of the inefficiencies associated with current ISS CO2 management systems. We have laid the solid foundation for Phase II work to employ novel and efficient reactor geometries, lighting approaches, 3D manufacturing methods and in-house grown novel catalytic materials.The primary objective of the proposed work is to demonstrate the scientific and engineering foundation for light-activated, compact devices capable of converting CO2 to O2 and mission-relevant carbon compounds. The proposed HTPEC CO2 management system will demonstrate a novel pathway with high efficiency and reliability in a compact, lightweight reactor architecture. The proposed HTPEC air processing concept can be developed in multiple architectures, such as centralized processing as well as "artificial leaves" distributed throughout the cabin that utilize pre-existing cabin ventilation (wind). Additionally, HTPEC can be deployed with spectrally tunable collection channels for selectable product generation. HTPEC employs light as its only energy source to remove and convert waste CO2 using a non-toxic composite catalyst.We have demonstrated in the Phase I studies the production, tunability and robustness of the novel composite catalysts following the preliminary work in the Chen laboratory. Additionally, we have designed, fabricated and tested all components of HTPEC device with active materials, including flow modeling to optimize flow mixing and pressure drop as well as the production of ethylene and other larger hydrocarbons. To best determine how this technology could be implemented, we also performed system integration optimization and trade studies. This includes parameters such as mass, volume, power in relation to selected mission configurations, CO2 delivery methods and light source/delivery approaches.

Artificial Photosynthesis

Foundations of measurement and instrumentation

The user of instrumentation has provided an understanding of the factors that influence instrument performance, selection, and application, and of the methods of interpreting and presenting the results of measurements. Such understanding is prerequisite to the successful attainment of the best compromise among reliability, accuracy, speed, cost, and importance of the measurement operation in achieving the ultimate goal of a project. Some subjects covered are dimensions; units; sources of measurement error; methods of describing and estimating accuracy; deduction and presentation of results through empirical equations, including the method of least squares; experimental and analytical methods of determining the static and dynamic behavior of instrumentation systems, including the use of analogs.

Warshawsky, Isidore

Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model

This paper examines various sources of error in MIT's improved top oil temperature rise over ambient temperature model and estimation process. The sources of error are the current parameter estimation technique, quantization noise, and post-processing of the transformer data. Results from this paper will show that an output error parameter estimation technique should be selected to replace the current least squares estimation technique. The output error technique obtained accurate predictions of transformer behavior, revealed the best error covariance, obtained consistent parameter estimates, and provided for valid and sensible parameters. This paper will also show that the output error technique should be used to minimize errors attributed to post-processing (decimation) of the transformer data. Models used in this paper are validated using data from a large transformer in service.

Morris, A. Terry