Mass Loss Due to Sputtering and Thermal Processes in Meteoroid Ablation

Conventional meteoroid theory assumes that the dominant mode of ablation is by evaporation following intense heating during atmospheric flight. In this paper we consider the question of whether sputtering may provide an alternative disintegration process of some importance.For meteoroids in the mass range from 10^-3 to 10^-13 kg and covering a meteor velocity range from 11 to 71 km/s, we numerically modeled both thermal ablation and sputtering ablation during atmospheric flight. We considered three meteoroid models believed to be representative of asteroidal (3300 kg m^-3 mass density), cometary (1000 kg m^-3) and porous cometary (300 kg m^-3) meteoroid structures. Atmospheric profiles which considered the molecular compositions at different heights were used in the sputtering calculations. We find that while in many cases (particularly at low velocities and for relatively large meteoroid masses) sputtering contributes only a small amount of mass loss during atmospheric flight, in some cases sputtering is very important. For example, a 10^-10 kg porous meteoroid at 40 km/s will lose nearly 51% of its mass by sputtering, while a 10^-13 kg asteroidal meteoroid at 60 km/s will lose nearly 83% of its mass by sputtering. We argue that sputtering may explain the light production observed at very great heights in some Leonid meteors. The impact of this work will be most dramatic for very small meteoroids such as those observed with large aperture radars.Comment: in pdf form, 48 pgs incl figures and table

Transverse Λ0\Lambda^0 polarization in inclusive quasi-real photoproduction at the current fragmentation

It is shown that the recent HERMES data on the transverse $\Lambda^0$ polarization in the inclusive quasi-real photoproduction at $x_F>0$ can be accommodated by the strange quark scattering model. Relations with the quark recombination approach are discussed.Comment: 5 pages, 3 figures, accepted by Eur. Phys. J.

Robust statistics towards detection of the 21 cm signal from the Epoch of Reionization

© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. We explore methods for robust estimation of the 21 cm signal from the Epoch of Reionization (EoR). A Kernel Density Estimator (KDE) is introduced for measuring the spatial temperature fluctuation power spectrum from the EoR. The KDE estimates the underlying probability distribution function of fluctuations as a function of spatial scale, and contains different systematic biases and errors to the typical approach to estimating the fluctuation power spectrum. Extraction of histograms of visibilities allows moments analysis to be used to discriminate foregrounds from 21 cm signal and thermal noise. We use the information available in the histograms, along with the statistical dis-similarity of foregrounds from two independent observing fields, to robustly separate foregrounds from cosmological signal, while making no assumptions about the Gaussianity of the signal. Using two independent observing fields to robustly discriminate signal from foregrounds is crucial for the analysis presented in this paper. We apply the techniques to 13 h of Murchison Widefield Array EoR data over two observing fields. We compare the output to that obtained with a comparative power spectrum estimation method, and demonstrate the reduced foreground contamination using this approach. Using the second moment obtained directly from the KDE distribution functions yields a factor of 2-3 improvement in power for k < 0.3 h Mpc-1 compared with a matched delay space power estimator, while weighting data by additional statistics does not offer significant improvement beyond that available for thermal noise-only weights

Analytical solutions for wall slip effects on magnetohydrodynamic oscillatory rotating plate and channel flows in porous media using a fractional burgers viscoelastic model

A theoretical analysis of magnetohydrodynamic (MHD) incompressible flows of Burger's fluid through a porous medium in a rotating frame of reference is presented. The constitutive model of a Burger's fluid is used based on a fractional calculus formulation. Hydrodynamic slip at the wall (plate) is incorporated and a fractional generalized Darcy model deployed to simulate porous medium drag force effects. Three different cases are considered- namely, flow induced by a general periodic oscillation at a rigid plate, periodic flow in a parallel plate channel and finally Poiseuille flow. In all cases the plate (s) boundary (ies) are electrically-non-conducting and small magnetic Reynolds is assumed, negating magnetic induction effects. The well-posed boundary value problems associated with each case are solved via Fourier transforms. Comparisons are made between the results derived with and without slip conditions. 4 special cases are retrieved from the general fractional Burgers model, viz Newtonian fluid, general Maxwell viscoelastic fluid, generalized Oldroyd-B fluid and the conventional Burger’s viscoelastic model. Extensive interpretation of graphical plots is included. We study explicitly the influence on wall slip on primary and secondary velocity evolution. The model is relevant to MHD rotating energy generators employing rheological working fluids

Path-based reuse distance analysis

Profiling can effectively analyze program behavior and provide critical information for feedback-directed or dynamic optimizations. Based on memory profiling, reuse distance analysis has shown much promise in predicting data locality for a program using inputs other than the profiled ones. Both wholeprogram and instruction-based locality can be accurately predicted by reuse distance analysis. Reuse distance analysis abstracts a cluster of memory references for a particular instruction having similar reuse distance values into a locality pattern. Prior work has shown that a significant number of memory instructions have multiple locality patterns, a property not desirable for many instruction-based memory optimizations. This paper investigates the relationship between locality patterns and execution paths by analyzing reuse distance distribution along each dynamic path to an instruction. Here a path is defined as the program execution trace from the previous access of a memory location to the current access. By differentiating locality patterns with the context of execution paths, the proposed analysis can expose optimization opportunities tailored only to a specific subset of paths leading to an instruction. In this paper, we present an effective method for path-based reuse distance profiling and analysis. We have observed that a significant percentage of the multiple locality patterns for an instruction can be uniquely related to a particular execution path in the program. In addition, we have also investigated the influence of inputs on reuse distance distribution for each path/instruction pair. The experimental results show that the path-based reuse distance is highly predictable, as a function of the data size, for a set of SPEC CPU2000 programs