Laboratory and on-site tests for rapid runway repair

The attention to rapid pavement repair has grown fast in recent decades: this topic is strategic for the airport management process for civil purposes and peacekeeping missions. This work presents the results of laboratory and on-site tests for rapid runway repair, in order to analyse and compare technical and mechanical performances of 12 different materials currently used in airport. The study focuses on site repairs, a technique adopted most frequently than repairs with modular elements. After describing mechanical and physical properties of the examined materials (2 bituminous emulsions, 5 cement mortars, 4 cold bituminous mixtures and 1 expanding resin), the study presents the results of carried out mechanical tests. The results demonstrate that the best performing material is a one-component fast setting and hardening cement mortar with graded aggregates. This material allows the runway reopening 6 h after the work. A cold bituminous mixture (bicomponent premixed cold asphalt with water as catalyst) and the ordinary cement concrete allow the reopening to traffic after 18 h, but both ensure a lower service life (1000 coverages) than the cement mortar (10,000 coverages). The obtained results include important information both laboratory level and field, and they could be used by airport management bodies and road agencies when scheduling and evaluating pavement repairs

Influence of grain size, shape and compaction on georadar waves: example of an Aeolian dune

Many Ground Penetrating Radar (GPR) profiles acquired in dry aeolian environment have shown good reflectivity inside present-day dunes. We show that the origin of this reflectivity is related to changes in grain size distribution, packing and/or grain shape in a sandy material. We integrate these three parameters into analytical models for bulk permittivity in order to predict the reflections and the velocity of GPR waves. We consider two GPR cross-sections acquired over Aeolian dunes in the Chadian desert. The 2D migration of GPR data suggests that dunes contain different kinds of bounding surfaces. We discuss and model three kinds of reflections using reasonable geological hypothesis about Aeolian sedimentation processes. The propagation and the reflection of radar waves are calculated using the 1D wavelet modelling method in spectral domain. The results of the forward modelling are in good accordance with real observed data

Chemical Vapor Deposition of silicon nanodots on TiO2 submicronic powders in vibrated fluidized bed

Silicon nanodots have been deposited on TiO2 submicronic powders in a vibrated Fluidized Bed Chemical Vapor Deposition (FBCVD) reactor from silane SiH4. Deposition conditions involving very low deposition rates have been studied. After treatment, powders are under the form of micronic agglomerates. In the operating range tested, this agglomerates formation mainly depends on the fluidization conditions and not on the CVD parameters. The best results have been obtained for anatase TiO2 powders for which the conditions of fluidization have been the most optimized. For these anatase powders, agglomerates are porous. SEM and TEM imaging prove that silicon nanodots (8-10 nm in size) have been deposited on the surface of particles and that this deposition is uniform on the whole powders and conformal around each grain, even if not fully continuous. Raman spectroscopy shows that the TiO2 powders have been partially reduced into TiO2-x during deposition. The TiO2 stoichiometry can be recovered by annealing under air, and IR spectroscopy indicates that the deposited silicon nanodots have been at least partly oxidized into SiO2 after this annealing

Morphological granulometry for classification of evolving and ordered texture images.

In this work we investigate the use of morphological granulometric moments as texture descriptors to predict time or class of texture images which evolve over time or follow an intrinsic ordering of textures. A cubic polynomial regression was used to model each of several granulometric moments as a function of time or class. These models are then combined and used to predict time or class. The methodology was developed on synthetic images of evolving textures and then successfully applied to classify a sequence of corrosion images to a point on an evolution time scale. Classification performance of the new regression approach is compared to that of linear discriminant analysis, neural networks and support vector machines. We also apply our method to images of black tea leaves, which are ordered according to granule size, and very high classification accuracy was attained compared to existing published results for these images. It was also found that granulometric moments provide much improved classification compared to grey level co-occurrence features for shape-based texture images

Modeling of evolving textures using granulometries

This chapter describes a statistical approach to classification of dynamic texture images, called parallel evolution functions (PEFs). Traditional classification methods predict texture class membership using comparisons with a finite set of predefined texture classes and identify the closest class. However, where texture images arise from a dynamic texture evolving over time, estimation of a time state in a continuous evolutionary process is required instead. The PEF approach does this using regression modeling techniques to predict time state. It is a flexible approach which may be based on any suitable image features. Many textures are well suited to a morphological analysis and the PEF approach uses image texture features derived from a granulometric analysis of the image. The method is illustrated using both simulated images of Boolean processes and real images of corrosion. The PEF approach has particular advantages for training sets containing limited numbers of observations, which is the case in many real world industrial inspection scenarios and for which other methods can fail or perform badly. [41] G.W. Horgan, Mathematical morphology for analysing soil structure from images, European Journal of Soil Science, vol. 49, pp. 161–173, 1998. [42] G.W. Horgan, C.A. Reid and C.A. Glasbey, Biological image processing and enhancement, Image Processing and Analysis, A Practical Approach, R. Baldock and J. Graham, eds., Oxford University Press, Oxford, UK, pp. 37–67, 2000. [43] B.B. Hubbard, The World According to Wavelets: The Story of a Mathematical Technique in the Making, A.K. Peters Ltd., Wellesley, MA, 1995. [44] H. Iversen and T. Lonnestad. An evaluation of stochastic models for analysis and synthesis of gray-scale texture, Pattern Recognition Letters, vol. 15, pp. 575–585, 1994. [45] A.K. Jain and F. Farrokhnia, Unsupervised texture segmentation using Gabor filters, Pattern Recognition, vol. 24(12), pp. 1167–1186, 1991. [46] T. Jossang and F. Feder, The fractal characterization of rough surfaces, Physica Scripta, vol. T44, pp. 9–14, 1992. [47] A.K. Katsaggelos and T. Chun-Jen, Iterative image restoration, Handbook of Image and Video Processing, A. Bovik, ed., Academic Press, London, pp. 208–209, 2000. [48] M. K¨oppen, C.H. Nowack and G. R¨osel, Pareto-morphology for color image processing, Proceedings of SCIA99, 11th Scandinavian Conference on Image Analysis 1, Kangerlussuaq, Greenland, pp. 195–202, 1999. [49] S. Krishnamachari and R. Chellappa, Multiresolution Gauss-Markov random field models for texture segmentation, IEEE Transactions on Image Processing, vol. 6(2), pp. 251–267, 1997. [50] T. Kurita and N. Otsu, Texture classification by higher order local autocorrelation features, Proceedings of ACCV93, Asian Conference on Computer Vision, Osaka, pp. 175–178, 1993. [51] S.T. Kyvelidis, L. Lykouropoulos and N. Kouloumbi, Digital system for detecting, classifying, and fast retrieving corrosion generated defects, Journal of Coatings Technology, vol. 73(915), pp. 67–73, 2001. [52] Y. Liu, T. Zhao and J. Zhang, Learning multispectral texture features for cervical cancer detection, Proceedings of 2002 IEEE International Symposium on Biomedical Imaging: Macro to Nano, pp. 169–172, 2002. [53] G. McGunnigle and M.J. Chantler, Modeling deposition of surface texture, Electronics Letters, vol. 37(12), pp. 749–750, 2001. [54] J. McKenzie, S. Marshall, A.J. Gray and E.R. Dougherty, Morphological texture analysis using the texture evolution function, International Journal of Pattern Recognition and Artificial Intelligence, vol. 17(2), pp. 167–185, 2003. [55] J. McKenzie, Classification of dynamically evolving textures using evolution functions, Ph.D. Thesis, University of Strathclyde, UK, 2004. [56] S.G. Mallat, Multiresolution approximations and wavelet orthonormal bases of L2(R), Transactions of the American Mathematical Society, vol. 315, pp. 69–87, 1989. [57] S.G. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, pp. 674–693, 1989. [58] B.S. Manjunath and W.Y. Ma, Texture features for browsing and retrieval of image data, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, pp. 837–842, 1996. [59] B.S. Manjunath, G.M. Haley and W.Y. Ma, Multiband techniques for texture classification and segmentation, Handbook of Image and Video Processing, A. Bovik, ed., Academic Press, London, pp. 367–381, 2000. [60] G. Matheron, Random Sets and Integral Geometry, Wiley Series in Probability and Mathematical Statistics, John Wiley and Sons, New York, 1975

The origin of beach sediments on the North Queensland coast

Petrographic and granulometric analyses of North Queensland beach sediments indicate their affinity with sediments delivered to the coast by rivers, and it is shown that the beaches are largely derived from fluvial sediment reworked, sorted and distributed by the dominant south-easterly waves in coastal waters. Beach sediments are generally quartzose, with subordinate felspars and admixtures of coralline sediment near fringing reefs and lithic material near river mouths and rocky shore sectors. The prevailing northerly drift of shore sediment is reduced, and locally reversed, on sectors sheltered from the dominant south-easterly waves by headlands, reefs and islands. Variations in beach sediment are related to wave conditions, distance from river-mouth sources, and patterns of drift. Four Mile Beach, near Port Douglas, is identified as anomalous in its morphological and sedimentological characteristics. It has been cut off from former sources of sediment, both fluvial and longshore, as a result of reef extension around the mouth of Mowbray River, and is now essentially a relict beach system attaining sedimentological maturity

Abundance of small individuals influences the effectiveness of processing techniques for deep-sea nematodes

Nematodes are the most abundant metazoans of deep-sea benthic communities, but knowledge of their distribution is limited relative to larger organisms. Whilst some aspects of nematode processing techniques, such as extraction, have been extensively studied, other key elements have attracted little attention. We compared the effect of (1) mesh size (63, 45, and 32 μm) on estimates of nematode abundance, biomass, and body size, and (2) microscope magnification (50 and 100×) on estimates of nematode abundance at bathyal sites (250-3100 m water depth) on the Challenger Plateau and Chatham Rise, south-west Pacific Ocean. Variation in the effectiveness of these techniques was assessed in relation to nematode body size and environmental parameters (water depth, sediment organic matter content, %silt/clay, and chloroplastic pigments). The 63-μm mesh retained a relatively low proportion of total nematode abundance (mean ±SD = 55 ±9%), but most of nematode biomass (90 ± 4%). The proportion of nematode abundance retained on the 45-μm mesh in surface (0-1 cm) and subsurface (1-5 cm) sediment was significantly correlated (P < 0.01) with %silt/clay (R² = 0.39) and chloroplastic pigments (R² = 0.29), respectively. Variation in median nematode body weight showed similar trends, but relationships between mean nematode body weight and environmental parameters were either relatively weak (subsurface sediment) or not significant (surface sediment). Using a low magnification led to significantly lower (on average by 43%) nematode abundance estimates relative to high magnification (P < 0.001), and the magnitude of this difference was significantly correlated (P < 0.05) with total nematode abundance (R²p = 0.53) and the number of small (≤ 250 μm length) individuals (R²p = 0.05). Our results suggest that organic matter input and sediment characteristics influence the abundance of small nematodes in bathyal communities. The abundance of small individuals can, in turn, influence abundance estimates obtained using different mesh sizes and microscope magnifications

Forecasting volcanic ash dispersal and coeval resuspension during the April-May 2015 Calbuco eruption

Atmospheric dispersion of volcanic ash from explosive eruptions or from subsequent fallout deposit resuspension causes a range of impacts and disruptions on human activities and ecosystems. The April-May 2015 Calbuco eruption in Chile involved eruption and resuspension activities. We overview the chronology, effects, and products resulting from these events, in order to validate an operational forecast strategy for tephra dispersal. The modelling strategy builds on coupling the meteorological Weather Research and Forecasting (WRF/ARW) model with the FALL3D dispersal model for eruptive and resuspension processes. The eruption modelling considers two distinct particle granulometries, a preliminary first guess distribution used operationally when no field data was available yet, and a refined distribution based on field measurements. Volcanological inputs were inferred from eruption reports and results from an Argentina-Chilean ash sample data network, which performed in-situ sampling during the eruption. In order to validate the modelling strategy, results were compared with satellite retrievals and ground deposit measurements. Results indicate that the WRF-FALL3D modelling system can provide reasonable forecasts in both eruption and resuspension modes, particularly when the adjusted granulometry is considered. The study also highlights the importance of having dedicated datasets of active volcanoes furnishing first-guess model inputs during the early stages of an eruption.Fil: Reckziegel, Florencia Mabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Bustos, Emilce. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Leonardo, Mingari. Ministerio de Defensa. Secretaria de Planeamiento. Servicio Meteorológico Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Baez, Walter Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones en Energía no Convencional. Universidad Nacional de Salta. Facultad de Ciencias Exactas. Departamento de Física. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Villarosa, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Folch Duran, Arnau. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; EspañaFil: Collini, E.. Ministerio de Defensa. Secretaria de Planeamiento. Servicio Meteorológico Nacional; Argentina. Ministerio de Defensa. Armada Argentina. Servicio de Hidrografía Naval; ArgentinaFil: Viramonte, Jose German. Universidad Nacional de Salta; ArgentinaFil: Romero, J.. Centro de Investigación y Difusión de Volcanes de Chile; Chile. Universidad de Atacama; ChileFil: Osores, María Soledad. Comision Nacional de Actividades Espaciales; Argentina. Ministerio de Defensa. Secretaria de Planeamiento. Servicio Meteorológico Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin