Debris Flux Comparisons From The Goldstone Radar, Haystack Radar, and Hax Radar Prior, During, and After the Last Solar Maximum

The continual monitoring of low Earth orbit (LEO) debris environment using highly sensitive radars is essential for an accurate characterization of these dynamic populations. Debris populations are continually evolving since there are new debris sources, previously unrecognized debris sources, and debris loss mechanisms that are dependent on the dynamic space environment. Such radar data are used to supplement, update, and validate existing orbital debris models. NASA has been utilizing radar observations of the debris environment for over a decade from three complementary radars: the NASA JPL Goldstone radar, the MIT Lincoln Laboratory (MIT/LL) Long Range Imaging Radar (known as the Haystack radar), and the MIT/LL Haystack Auxiliary radar (HAX). All of these systems are highly sensitive radars that operate in a fixed staring mode to statistically sample orbital debris in the LEO environment. Each of these radars is ideally suited to measure debris within a specific size region. The Goldstone radar generally observes objects with sizes from 2 mm to 1 cm. The Haystack radar generally measures from 5 mm to several meters. The HAX radar generally measures from 2 cm to several meters. These overlapping size regions allow a continuous measurement of cumulative debris flux versus diameter from 2 mm to several meters for a given altitude window. This is demonstrated for all three radars by comparing the debris flux versus diameter over 200 km altitude windows for 3 nonconsecutive years from 1998 through 2003. These years correspond to periods before, during, and after the peak of the last solar cycle. Comparing the year to year flux from Haystack for each of these altitude regions indicate statistically significant changes in subsets of the debris populations. Potential causes of these changes are discussed. These analysis results include error bars that represent statistical sampling errors, and are detailed in this paper

Dynamically Slow Processes in Supercooled Water Confined Between Hydrophobic Plates

We study the dynamics of water confined between hydrophobic flat surfaces at low temperature. At different pressures, we observe different behaviors that we understand in terms of the hydrogen bonds dynamics. At high pressure, the formation of the open structure of the hydrogen bond network is inhibited and the surfaces can be rapidly dehydrated by decreasing the temperature. At lower pressure the rapid ordering of the hydrogen bonds generates heterogeneities that are responsible for strong non-exponential behavior of the correlation function, but with no strong increase of the correlation time. At very low pressures, the gradual formation of the hydrogen bond network is responsible for the large increase of the correlation time and, eventually, the dynamical arrest of the system and of the dehydration process.Comment: 14 pages, 3 figure

Effect of hydrogen bond cooperativity on the behavior of water

Four scenarios have been proposed for the low--temperature phase behavior of liquid water, each predicting different thermodynamics. The physical mechanism which leads to each is debated. Moreover, it is still unclear which of the scenarios best describes water, as there is no definitive experimental test. Here we address both open issues within the framework of a microscopic cell model by performing a study combining mean field calculations and Monte Carlo simulations. We show that a common physical mechanism underlies each of the four scenarios, and that two key physical quantities determine which of the four scenarios describes water: (i) the strength of the directional component of the hydrogen bond and (ii) the strength of the cooperative component of the hydrogen bond. The four scenarios may be mapped in the space of these two quantities. We argue that our conclusions are model-independent. Using estimates from experimental data for H bond properties the model predicts that the low-temperature phase diagram of water exhibits a liquid--liquid critical point at positive pressure.Comment: 18 pages, 3 figure

Probabilistic Search for Object Segmentation and Recognition

The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range data of the scene. A new statistical criterion, the truncated object probability, is introduced to infer an optimal sequence of object hypotheses to be evaluated for their match to the data. The truncated probability is partly determined by prior knowledge of the objects and partly learned from data. Some experiments on sequence quality and object segmentation and recognition from stereo data are presented. The article recovers classic concepts from object recognition (grouping, geometric hashing, alignment) from the probabilistic perspective and adds insight into the optimal ordering of object hypotheses for evaluation. Moreover, it introduces point-relation densities, a key component of the truncated probability, as statistical models of local surface shape.Comment: 18 pages, 5 figure

More than one dynamic crossover in protein hydration water

Studies of liquid water in its supercooled region have led to many insights into the structure and behavior of water. While bulk water freezes at its homogeneous nucleation temperature of approximately 235 K, for protein hydration water, the binding of water molecules to the protein avoids crystallization. Here we study the dynamics of the hydrogen bond (HB) network of a percolating layer of water molecules, comparing measurements of a hydrated globular protein with the results of a coarse-grained model that has been shown to successfully reproduce the properties of hydration water. With dielectric spectroscopy we measure the temperature dependence of the relaxation time of protons charge fluctuations. These fluctuations are associated to the dynamics of the HB network of water molecules adsorbed on the protein surface. With Monte Carlo (MC) simulations and mean--field (MF) calculations we study the dynamics and thermodynamics of the model. In both experimental and model analyses we find two dynamic crossovers: (i) one at about 252 K, and (ii) one at about 181 K. The agreement of the experiments with the model allows us to relate the two crossovers to the presence of two specific heat maxima at ambient pressure. The first is due to fluctuations in the HB formation, and the second, at lower temperature, is due to the cooperative reordering of the HB network

Statistical Estimation of Orbital Debris Populations with a Spectrum of Object Size

Orbital debris is a real concern for the safe operations of satellites. In general, the hazard of debris impact is a function of the size and spatial distributions of the debris populations. To describe and characterize the debris environment as reliably as possible, the current NASA Orbital Debris Engineering Model (ORDEM2000) is being upgraded to a new version based on new and better quality data. The data-driven ORDEM model covers a wide range of object sizes from 10 microns to greater than 1 meter. This paper reviews the statistical process for the estimation of the debris populations in the new ORDEM upgrade, and discusses the representation of large-size (greater than or equal to 1 m and greater than or equal to 10 cm) populations by SSN catalog objects and the validation of the statistical approach. Also, it presents results for the populations with sizes of greater than or equal to 3.3 cm, greater than or equal to 1 cm, greater than or equal to 100 micrometers, and greater than or equal to 10 micrometers. The orbital debris populations used in the new version of ORDEM are inferred from data based upon appropriate reference (or benchmark) populations instead of the binning of the multi-dimensional orbital-element space. This paper describes all of the major steps used in the population-inference procedure for each size-range. Detailed discussions on data analysis, parameter definition, the correlation between parameters and data, and uncertainty assessment are included

Ab initio van der Waals interactions in simulations of water alter structure from mainly tetrahedral to high-density-like

The structure of liquid water at ambient conditions is studied in ab initio molecular dynamics simulations using van der Waals (vdW) density-functional theory, i.e. using the new exchange-correlation functionals optPBE-vdW and vdW-DF2. Inclusion of the more isotropic vdW interactions counteracts highly directional hydrogen-bonds, which are enhanced by standard functionals. This brings about a softening of the microscopic structure of water, as seen from the broadening of angular distribution functions and, in particular, from the much lower and broader first peak in the oxygen-oxygen pair-correlation function (PCF), indicating loss of structure in the outer solvation shells. In combination with softer non-local correlation terms, as in the new parameterization of vdW-DF, inclusion of vdW interactions is shown to shift the balance of resulting structures from open tetrahedral to more close-packed. The resulting O-O PCF shows some resemblance with experiment for high-density water (A. K. Soper and M. A. Ricci, Phys. Rev. Lett., 84:2881, 2000), but not directly with experiment for ambient water. However, an O-O PCF consisting of a linear combination of 70% from vdW-DF2 and 30% from experiment on low-density liquid water reproduces near-quantitatively the experimental O-O PCF for ambient water, indicating consistency with a two-liquid model with fluctuations between high- and low-density regions