Starburst-driven galactic winds: I. Energetics and intrinsic X-ray emission

We have performed an extensive hydrodynamical parameter study of starburst-driven galactic winds, motivated by the latest observation data on the best-studied starburst galaxy M82. We study how the wind dynamics, morphology and X-ray emission depend on the host galaxy's ISM distribution, starburst star formation history and strength, and presence and distribution of mass-loading by dense clouds. We find that the soft X-ray emission from galactic winds comes from low filling factor (ff < 2 per cent) gas, which contains only a small fraction (f < 10 per cent) of the mass and energy of the wind, irrespective of whether the wind models are strongly mass-loaded or not. X-ray observations of galactic winds therefore do not directly probe the gas that contains the majority of the energy, mass or metal-enriched gas in the outflow. The soft X-ray emission comes from gas at a wide range different temperatures and densities. Estimates of the physical properties of the hot gas in starburst galaxies, based on fitting the standard simple spectral models to existing X-ray spectra, should therefore be treated with extreme suspicion. The majority of the thermal and kinetic energy of these winds is in a volume filling hot, T approx 10^7 K, component which is extremely difficult to probe observationally due to its low density and hence low emissivity. Most of the total energy is in the kinetic energy of this hot gas, a factor which must be taken into account when attempting to constrain wind energetics observationally. We also find that galactic winds are efficient at transporting large amounts of energy out of the host galaxy, in contrast to their inefficiency at transporting mass out of star-forming galaxies. (Abridged)Comment: Accepted for publication in MNRAS. Letter page size postscript available from http://adcam.pha.jhu.edu/~dks/dks_published.htm

A Design Process Centric Application of State Space Modeling as a Function of Communications and Cognitive Skills Assessments.

Humans have a reliable basic probabilistic intuition. We utilize our probabilistic intuition in many day-to-day activities such as driving. In fact any interaction that occurs in the presence of other independent actors requires some probabilistic assessment. While we are good at sorting between rare and common events, determining if these events are statistical significant is always subject to scrutiny. Quite often the bounds of statistical significance are at ends with the ‘common sense’ expectation. While our probabilistic intuition is good for first moment effects such as driving a car, throwing a football and understanding simplistic mathematical models, our probabilistic intuition fails when we need to evaluate secondary effects such as high speed turns, playing golf or understanding complex mathematical models. When our probabilistic intuition is challenged misinterpretation of results and skewed perspectives of possible outcomes will occur. The work presented in this dissertation provides a mathematical formulation that will provide a guide to when our probabilistic intuition will be challenged. This dissertation will discuss the development of the Process Failure Estimation Technique (ProFET). A multitude of potential team parameters could have been selected, interpersonal communication effectiveness and cognitive skill assessments seemed the most obvious first steps. This is due to the prolific discussion on communication and the general acceptance of the cognitive testing as an indicator of performance potential. The teams skill set must be variable with respect to time in order to accomplish the required objectives of each phase of the design process. ProFET develops a metric for the design process that is sensitive to the team composition and structure. This metric is applied to a domain that is traditionally devoid of objective scoring. With the use of ProFET more informed decisions on team structure and composition can be made at critical junctions of the design process. Specifically, ProFET looks at how variability propagates through the design activities as opposed to attempting to quantify the actual values of design activities, which is the focus of the majority of other design research.PhDNaval Architecture and Marine EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116679/1/jdstrick_1.pd