The solar wind structures associated with cosmic ray decreases and particle acceleration in 1978-1982

The time histories of particles in the energy range 1 MeV to 1 GeV at times of all greater than 3 percent cosmic ray decreases in the years 1978 to 1982 are studied. Essentially all 59 of the decreases commenced at or before the passages of interplanetary shocks, the majority of which accelerated energetic particles. We use the intensity-time profiles of the energetic particles to separate the cosmic ray decreases into four classes which we subsequently associate with four types of solar wind structures. Decreases in class 1 (15 events) and class 2 (26 events) can be associated with shocks which are driven by energetic coronal mass ejections. For class 1 events the ejecta is detected at 1 AU whereas this is not the case for class 2 events. The shock must therefore play a dominant role in producing the depression of cosmic rays in class 2 events. In all class 1 and 2 events (which comprise 69 percent of the total) the departure time of the ejection from the sun (and hence the location) can be determined from the rapid onset of energetic particles several days before the shock passage at Earth. The class 1 events originate from within 50 deg of central meridian. Class 3 events (10 decreases) can be attributed to less energetic ejections which are directed towards the Earth. In these events the ejecta is more important than the shock in causing a depression in the cosmic ray intensity. The remaining events (14 percent of the total) can be attributed to corotating streams which have ejecta material embedded in them

Interaction of particles with a cavitation bubble near a solid wall

Hard particle erosion and cavitation damage are two main wear problems that can affect the internal components of hydraulic machinery such as hydraulic turbines or pumps. If both problems synergistically act together, the damage can be more severe and result in high maintenance costs. In this work, a study of the interaction of hard particles and cavitation bubbles is developed to understand their interactive behavior. Experimental tests and numerical simulations using computational fluid dynamics (CFD) were performed. Experimentally, a cavitation bubble was generated with an electric spark near a solid surface, and its interaction with hard particles of different sizes and materials was observed using a high-speed camera. A simplified analytical approach was developed to model the behavior of the particles near the bubble interface during its collapse. Computationally, we simulated an air bubble that grew and collapsed near a solid wall while interacting with one particle near the bubble interface. Several simulations with different conditions were made and validated with the experimental data. The experimental data obtained from particles above the bubble were consistent with the numerical results and analytical study. The particle size, density and position of the particle with respect to the bubble interface strongly affected the maximum velocity of the particles

Numerical Simulations of Shock and Rarefaction Waves Interacting With Interfaces in Compressible Multiphase Flows

Developing a highly accurate numerical framework to study multiphase mixing in high speed flows containing shear layers, shocks, and strong accelerations is critical to many scientific and engineering endeavors. These flows occur across a wide range of scales: from tiny bubbles in human tissue to massive stars collapsing. The lack of understanding of these flows has impeded the success of many engineering applications, our comprehension of astrophysical and planetary formation processes, and the development of biomedical technologies. Controlling mixing between different fluids is central to achieving fusion energy, where mixing is undesirable, and supersonic combustion, where enhanced mixing is important. Iron, found throughout the universe and a necessary component for life, is dispersed through the mixing processes of a dying star. Non-invasive treatments using ultrasound to induce bubble collapse in tissue are being developed to destroy tumors or deliver genes to specific cells. Laboratory experiments of these flows are challenging because the initial conditions and material properties are difficult to control, modern diagnostics are unable to resolve the flow dynamics and conditions, and experiments of these flows are expensive. Numerical simulations can circumvent these difficulties and, therefore, have become a necessary component of any scientific challenge. Advances in the three fields of numerical methods, high performance computing, and multiphase flow modeling are presented: (i) novel numerical methods to capture accurately the multiphase nature of the problem; (ii) modern high performance computing paradigms to resolve the disparate time and length scales of the physical processes; (iii) new insights and models of the dynamics of multiphase flows, including mixing through hydrodynamic instabilities. These studies have direct applications to engineering and biomedical fields such as fuel injection problems, plasma deposition, cancer treatments, and turbomachinery.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133458/1/marchdf_1.pd

Laser diagnostics for microgravity droplet studies

Rapid advances have recently been made in numerical simulation of droplet combustion under microgravity conditions, while experimental capabilities remain relatively primitive. Calculations can now provide detailed information on mass and energy transport, complex gas-phase chemistry, multi-component molecular diffusion, surface evaporation and heterogeneous reaction, which provides a clearer picture of both quasi-steady as well as dynamic behavior of droplet combustion. Experiments concerning these phenomena typically result in pictures of the burning droplets, and the data therefrom describe droplet surface regression along with flame and soot shell position. With much more precise, detailed, experimental diagnostics, significant gains could be made on the dynamics and flame structural changes which occur during droplet combustion. Since microgravity experiments become increasingly more expensive as they progress from drop towers and flights to spaceborne experiments, there is a great need to maximize the information content from these experiments. Sophisticated measurements using laser diagnostics on individual droplets and combustion phenomena are now possible. These include measuring flow patterns and temperature fields within droplets, vaporization rates and vaporization enhancement, radical species profiling in flames and gas-phase flow-tagging velocimetry. Although these measurements are sophisticated, they have undergone maturation to the degree where with some development, they are applicable to studies of microgravity droplet combustion. This program beginning in September of 1992, will include a series of measurements in the NASA Learjet, KC-135 and Drop Tower facilities for investigating the range of applicability of these diagnostics while generating and providing fundamental data to ongoing NASA research programs in this area. This program is being conducted in collaboration with other microgravity investigators and is aimed toward supplementing their experimental efforts

A machine learning framework for data driven acceleration of computations of differential equations

We propose a machine learning framework to accelerate numerical computations of time-dependent ODEs and PDEs. Our method is based on recasting (generalizations of) existing numerical methods as artificial neural networks, with a set of trainable parameters. These parameters are determined in an offline training process by (approximately) minimizing suitable (possibly non-convex) loss functions by (stochastic) gradient descent methods. The proposed algorithm is designed to be always consistent with the underlying differential equation. Numerical experiments involving both linear and non-linear ODE and PDE model problems demonstrate a significant gain in computational efficiency over standard numerical methods

Radio to Gamma-Ray Emission from Shell-type Supernova Remnants: Predictions from Non-linear Shock Acceleration Models

Supernova remnants (SNRs) are widely believed to be the principal source of galactic cosmic rays. Such energetic particles can produce gamma-rays and lower energy photons via interactions with the ambient plasma. In this paper, we present results from a Monte Carlo simulation of non-linear shock structure and acceleration coupled with photon emission in shell-like SNRs. These non-linearities are a by-product of the dynamical influence of the accelerated cosmic rays on the shocked plasma and result in distributions of cosmic rays which deviate from pure power-laws. Such deviations are crucial to acceleration efficiency and spectral considerations, producing GeV/TeV intensity ratios that are quite different from test particle predictions. The Sedov scaling solution for SNR expansions is used to estimate important shock parameters for input into the Monte Carlo simulation. We calculate ion and electron distributions that spawn neutral pion decay, bremsstrahlung, inverse Compton, and synchrotron emission, yielding complete photon spectra from radio frequencies to gamma-ray energies. The cessation of acceleration caused by the spatial and temporal limitations of the expanding SNR shell in moderately dense interstellar regions can yield spectral cutoffs in the TeV energy range; these are consistent with Whipple's TeV upper limits on unidentified EGRET sources. Supernova remnants in lower density environments generate higher energy cosmic rays that produce predominantly inverse Compton emission at super-TeV energies; such sources will generally be gamma-ray dim at GeV energies.Comment: 62 pages, AASTeX format, including 1 table and 11 figures, accepted for publication in The Astrophysical Journal (Vol 513, March 1, 1999