Small hypervelocity particles captured in aerogel collectors: Location,extraction, handling and storage

Abstract— It has now been about a decade since the first demonstrations that hypervelocity particles could be captured, partially intact, in aerogel collectors. But the initial promise of a bonanza of partially‐intact extraterrestrial particles, collected in space, has yet to materialize. One of the difficulties that investigators have encountered is that the location, extraction, handling and analysis of very small (10 μm and less) grains, which constitute the vast majority of the captured particles, is challenging and burdensome. Furthermore, current extraction techniques tend to be destructive over large areas of the collectors. Here we describe our efforts to alleviate some of these difficulties. We have learned how to rapidly and efficiently locate captured particles in aerogel collectors, using an automated microscopic scanning system originally developed for experimental nuclear astrophysics. We have learned how to precisely excavate small access tunnels and trenches using an automated micromanipulator and glass microneedles as tools. These excavations are only destructive to the collector in a very small area—this feature may be particularly important for excavations in the precious Stardust collectors. Using actuatable silicon microtweezers, we have learned how to extract and store “naked” particles—essentially free of aerogel—as small as 3 μm in size. We have also developed a technique for extracting particles, along with their terminal tracks, still embedded in small cubical aerogel blocks. We have developed a novel method for storing very small particles in etched nuclear tracks. We have applied these techniques to the extraction and storage of grains captured in aerogel collectors (Particle Impact Experiment, Orbital Debris Collector Experiment, Comet‐99) in low Earth orbit.     

A geospatial framework to estimate depth of scour under buildings due to storm surge in coastal areas

Hurricanes and tropical storms represent one of the major hazards in coastal communities. Storm surge generated by strong winds and low pressure from these systems have the potential to bring extensive flooding in coastal areas. In many cases, the damage caused by the storm surge may exceed the damage from the wind resulting in the total collapse of buildings. Therefore, in coastal areas, one of the sources for major structural damage could be due to scour, where the soil below the building that serves as the foundation is swept away by the movement of the water. The existing methodologies to forecast hurricane flood damage do not differentiate between the different damage mechanisms (e.g., inundation vs. scour). Currently, there are no tools available that predominantly focus on forecasting scour-related damage for buildings. Such a tool could provide significant advantages for planning and/or preparing emergency responses. Therefore, the focus of this study was to develop a methodology to predict possible scour depth due to hurricane storm surges using an automated ArcGIS tool that incorporates the expected hurricane conditions (flow depth, velocity, and flood duration), site-specific building information, and the associated soil types for the foundation. A case study from Monmouth County (NJ), where the scour damages from 2012 Hurricane Sandy were recorded after the storm, was used to evaluate the accuracy of the developed forecasting tool and to relate the scour depth to potential scour damage. The results indicate that the developed tool provides relatively consistent results with the field observations.     

Social vulnerability in the context of bushfire risk at the urban-bush interface in Sydney: a case study of the Blue Mountains and Ku-ring-gai local council areas

In the recent past, Australia has experienced several catastrophic hazard events and the frequency and intensity of such events is expected to increase in the future. Natural hazards can rarely be fully prevented, yet their losses can be minimized if the necessary preparedness and mitigation actions are taken before an event occurs. Identification of vulnerable groups is an important first step in any preparedness and emergency management planning process. Social vulnerability refers to population characteristics that influence the capacity of a community to prepare for, respond to and recover from disasters. Factors that contribute to social vulnerability are often hidden and difficult to capture. This study analyzes the relative levels of social vulnerability of communities at the urban?Cbush interface in the Blue Mountains and Ku-ring-gai local council areas in New South Wales (NSW), Australia. We tested whether a standardized social vulnerability index could be developed using a pre-existing set of indicators. We created an exploratory principle component analysis model using Australian Bureau of Statistics 2006 census data at the Census Collection District (CCD) level. We identified variables contributing to social vulnerability and used the component scores to develop a social vulnerability index. Finally, the social vulnerability index was mapped at the CCD level. Our results indicate that both contributors to and the level of social vulnerability differ between and within communities. In other words, they are spatially variable. They show different spatial patterns across the areas, which provides useful information for identifying communities that are most likely to experience negative disaster impacts due to their socio-demographic characteristics.     

A new magnitude category disaggregation approach for temporal high‐resolution rainfall intensities

Simulation of quick runoff components such as surface runoff and associated soil erosion requires temporal high‐resolution rainfall intensities. However, these data are often not available because such measurements are costly and time consuming. Current rainfall disaggregation methods have shortcomings, especially in generating the distribution of storm events. The objectives of this study were to improve point rainfall disaggregation using a new magnitude category rainfall disaggregation approach. The procedure is introduced using a coupled disaggregation approach (Hyetos and cascade) for multisite rainfall disaggregation. The new procedure was tested with ten long‐term precipitation data sets of central Germany using summer and winter precipitation to determine seasonal variability. Results showed that dividing the rainfall amount into four daily rainfall magnitude categories (1–10, 11–25, 26–50, >50 mm) improves the simulation of high rainfall intensity (convective rainfall). The Hyetos model category approach (Hyetos_Cat) with seasonal variation performs representative to observed hourly rainfall compared with without categories on each month. The mean absolute percentage accuracy of standard deviation for hourly rainfall is 89.7% in winter and 95.6% in summer. The proposed magnitude category method applied with the coupled Hyetos_Cat–cascade approach reproduces successfully the statistical behaviour of local 10‐min rainfall intensities in terms of intermittency as well as variability. The root mean square error performance statistics for disaggregated 10‐min rainfall depth ranges from 0.20 to 2.38 mm for summer and from 0.12 to 2.82 mm for the winter season in all categories. The coupled stochastic approach preserves the statistical self‐similarity and intermittency at each magnitude category with a relatively low computational burden. Copyright © 2014 John Wiley & Sons, Ltd.     

Volcanological and petrological evolution of Marsili Seamount (southern Tyrrhenian Sea)

A swath bathymetric survey was conducted on Marsili Volcano, the biggest seamount in the Tyrrhenian Sea. It stands 3000 m above the surrounding oceanic crust of the 3500 m-deep Marsili back-arc basin and is axially located within the basin. The seamount has an elongated shape and presents distinctive morphology, with narrow (<1000 m) ridges, made up of several elongated cones, on the summit zone and extensive cone fields on its lower flanks. A dredging campaign carried out at water depths varying between 3400 and 600 m indicates that most of Marsili Seamount is composed of medium-K calc-alkaline basalts. Evolved high-K andesites were only recovered from the small cones on the summit axis zone. Petrological and geochemical characteristics of the least differentiated basalts reveal that at least two varieties of magmas have been erupted on the Marsili Volcano. Group 1 basalts have plagioclase and olivine as dominant phases and show lower Al, Ca, K, Ba, Rb and Sr, and higher Fe, Na, Ti and Zr with respect to a second type of basaltic magma. Group 2 basalts reveal the presence of clinopyroxene as an additional phenocryst phase. In addition, the two basaltic magmas have different original pre-eruptive H₂O content (group 1, H₂O-poor and group 2, H₂O-rich). Moreover, comparison of the compositional trends and mineralogical compositions obtained from MELTS [Ghiorso, M.S., Sack, R.O., Contrib. Mineral. Petrol. 119 (1995) 197–212] fractional crystallization calculations reveal that the evolved andesites can only exclusively be derived from a low-pressure (0.3 kbar) fractionation of magmas compositionally similar to the least evolved group 2 basalts. Finally, we suggest that the high vesicularity of the basalts sampled at relatively great depths (>2400 m) on the edifice is governed by H₂O and, probably, CO₂ exsolution and is not a feature indicative of shallow water depth eruption.     

Data selection using support vector regression

Geophysical data sets are growing at an ever-increasing rate, requiring computationally efficient data selection(thinning)methods to preserve essential information. Satellites, such as Wind Sat, provide large data sets for assessing the accuracy and computational efficiency of data selection techniques. A new data thinning technique, based on support vector regression(SVR), is developed and tested. To manage large on-line satellite data streams, observations from Wind Sat are formed into subsets by Voronoi tessellation and then each is thinned by SVR(TSVR). Three experiments are performed. The first confirms the viability of TSVR for a relatively small sample, comparing it to several commonly used data thinning methods(random selection, averaging and Barnes filtering), producing a 10% thinning rate(90% data reduction), low mean absolute errors(MAE) and large correlations with the original data. A second experiment, using a larger dataset, shows TSVR retrievals with MAE < 1 m s-1and correlations 0.98. TSVR was an order of magnitude faster than the commonly used thinning methods. A third experiment applies a two-stage pipeline to TSVR, to accommodate online data. The pipeline subsets reconstruct the wind field with the same accuracy as the second experiment, is an order of magnitude faster than the nonpipeline TSVR. Therefore, pipeline TSVR is two orders of magnitude faster than commonly used thinning methods that ingest the entire data set. This study demonstrates that TSVR pipeline thinning is an accurate and computationally efficient alternative to commonly used data selection techniques.     

Varved sediments of Lake Yoa (Ounianga Kebir,Chad) reveal progressive drying of the Sahara during the last 6100 years

The sedimentological and geochemical properties of a 7·47 m long laminated sequence from hypersaline Lake Yoa in northern Chad have been investigated, representing a unique, continuous 6100 year long continental record of climate and environmental change in the eastern Central Sahara. These data were used to reconstruct the Mid to Late Holocene history of this currently hyper‐arid region, in order to address the question of whether the Mid Holocene environmental transition from a humid to a dry Sahara was progressive or abrupt. This study involved a suite of analyses, including petrographic and scanning electron microscope examination of thin sections, X‐ray diffraction, X‐radiography, granulometry, loss on ignition and magnetic susceptibility. The potential of micro‐X‐ray fluorescence core scanning was tested at very high resolution. Detailed microscopic investigation revealed the sedimentary processes responsible for the formation of the fine laminations, identified the season during which they were formed, and confirmed their annually rhythmic nature. High‐resolution X‐ray fluorescence core scanning allowed the distinction of each individual lamination over the entire record, opening new perspectives for the study of finely laminated sediment sequences. Geochemical and mineralogical data reveal that, due to decreasing monsoon rainfall combined with continuous and strong evaporation, the hydrologically open and fresh Mid Holocene Lake Yoa slowly evolved into the present‐day hypersaline brine depleted in calcium, which has existed for about the past 1050 years. During the oldest part of the investigated period, Lake Yoa probably contained a permanently stratified lower water column that was nevertheless disrupted relatively frequently by mixing events. Deep‐water anoxia became more stable because of increased salinity‐driven density stratification. In parallel, the sediment grain‐size proxies record a progressive increase of aeolian input in the course of the last 6100 years. Altogether, all geochemical and sedimentological indicators point to a progressive drying of the eastern Central Sahara, strengthening previous conclusions based on palaeoecological indicators.