86 resultados para Explosive eruptions
Resumo:
Describes the development and testing of a robotic system for charging blast holes in underground mining. The automation system supports four main tactical functions: detection of blast holes; teleoperated arm pose control; automatic arm pose control; and human-in-the-loop visual servoing. We present the system architecture, and analyse the major components, Hole detection is crucial for automating the process, and we discuss theoretical and practical aspects in detail. The sensors used are laser range finders and cameras installed in the end effector. For automatic insertion, we consider image processing techniques to support visual servoing the tool to the hole. We also discuss issues surrounding the control of heavy-duty mining manipulators, in particular, friction, stiction, and actuator saturation.
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This study evaluated the physiological tolerance times when wearing explosive and chemical (>35kg) personal protective equipment (PPE) in simulated environmental extremes across a range of differing work intensities. Twelve healthy males undertook nine trials which involved walking on a treadmill at 2.5, 4 and 5.5 km.h-1 in the following environmental conditions, 21, 30 and 37 °C wet bulb globe temperature (WBGT). Participants exercised for 60 min or until volitional fatigue, core temperature reached 39 °C, or heart rate exceeded 90% of maximum. Tolerance time, core temperature, skin temperature, mean body temperature, heart rate and body mass loss were measured. Exercise time was reduced in the higher WBGT environments (WBGT37
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This project focused on maximising the detection range of an eye-safe stand-off Raman system for use in detecting explosives. Investigation of the effect on detection range through differing laser parameters in this thesis provided optimal laser settings to achieve the largest possible detection range of explosives, while still remaining under the eye-safe limit.
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Background Explosive ordnance disposal (EOD) technicians are often required to wear specialised clothing combinations that not only protect against the risk of explosion but also potential chemical contamination. This heavy (>35kg) and encapsulating ensemble is likely to increase physiological strain by increasing metabolic heat production and impairing heat dissipation. This study investigated the physiological tolerance times of two different chemical protective undergarments, commonly worn with EOD personal protective clothing, in a range of simulated environmental extremes and work intensities Methods Seven males performed eighteen trials wearing two ensembles. The trials involved walking on a treadmill at 2.5, 4 and 5.5 km.h-1 at each of the following environmental conditions, 21, 30 and 37°C wet bulb globe temperature (WBGT). The trials were ceased if the participants’ core temperature reached 39°C, if heart rate exceeded 90% of maximum, if walking time reached 60 minutes or due to volitional fatigue. Results Physiological tolerance times ranged from 8 to 60 min and the duration (mean difference: 2.78 min, P>0.05) were similar in both ensembles. A significant effect for environment (21>30>37°C WBGT, P<0.05) and work intensity (2.5>4>5.5 km.h-1, P< 0.05) was observed in tolerance time. The majority of trials across both ensembles (101/126; 80.1%) were terminated due to participants achieving a heart rate equivalent to greater than 90% of their maximum. Conclusions Physiological tolerance times wearing these two chemical protective undergarments, worn underneath EOD personal protective clothing, were similar and predominantly limited by cardiovascular strain.
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Objective Explosive ordnance disposal (EOD) often requires technicians to wear multiple protective garments in challenging environmental conditions. The accumulative effect of increased metabolic cost coupled with decreased heat dissipation associated with these garments predisposes technicians to high levels of physiological strain. It has been proposed that a perceptual strain index (PeSI) using subjective ratings of thermal sensation and perceived exertion as surrogate measures of core body temperature and heart rate, may provide an accurate estimation of physiological strain. Therefore, this study aimed to determine if the PeSI could estimate the physiological strain index (PSI) across a range of metabolic workloads and environments while wearing heavy EOD and chemical protective clothing. Methods Eleven healthy males wore an EOD and chemical protective ensemble while walking on a treadmill at 2.5, 4 and 5.5 km·h− 1 at 1% grade in environmental conditions equivalent to wet bulb globe temperature (WBGT) 21, 30 and 37 °C. WBGT conditions were randomly presented and a maximum of three randomised treadmill walking trials were completed in a single testing day. Trials were ceased at a maximum of 60-min or until the attainment of termination criteria. A Pearson's correlation coefficient, mixed linear model, absolute agreement and receiver operating characteristic (ROC) curves were used to determine the relationship between the PeSI and PSI. Results A significant moderate relationship between the PeSI and the PSI was observed [r = 0.77; p < 0.001; mean difference = 0.8 ± 1.1 a.u. (modified 95% limits of agreement − 1.3 to 3.0)]. The ROC curves indicated that the PeSI had a good predictive power when used with two, single-threshold cut-offs to differentiate between low and high levels of physiological strain (area under curve: PSI three cut-off = 0.936 and seven cut-off = 0.841). Conclusions These findings support the use of the PeSI for monitoring physiological strain while wearing EOD and chemical protective clothing. However, future research is needed to confirm the validity of the PeSI for active EOD technicians operating in the field.
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The Jericho kimberlite (173.1. ±. 1.3. Ma) is a small (~. 130. ×. 70. m), multi-vent system that preserves products from deep (>. 1. km?) portions of kimberlite vents. Pit mapping, drill core examination, petrographic study, image analysis of olivine crystals (grain size distributions and shape studies), and compositional and mineralogical studies, are used to reconstruct processes from near-surface magma ascent to kimberlite emplacement and alteration. The Jericho kimberlite formed by multiple eruptions through an Archean granodiorite batholith that was overlain by mid-Devonian limestones ~. 1. km in thickness. Kimberlite magma ascended through granodiorite basement by dyke propagation but ascended through limestone, at least in part, by locally brecciating the host rocks. After the first explosive breakthrough to surface, vent deepening and widening occurred by the erosive forces of the waxing phase of the eruption, by gravitationally induced failures as portions of the vent margins slid into the vent and, in the deeper portions of the vent (>. 1. km), by scaling, as thin slabs burst from the walls into the vent. At currently exposed levels, coherent kimberlite (CK) dykes (<. 40. cm thick) are found to the north and south of the vent complex and represent the earliest preserved in-situ products of Jericho magmatism. Timing of CK emplacement on the eastern side of the vent complex is unclear; some thick CK (15-20. m) may have been emplaced after the central vent was formed. Explosive eruptive products are preserved in four partially overlapping vents that are roughly aligned along strike with the coherent kimberlite dyke. The volcaniclastic kimberlite (VK) facies are massive and poorly sorted, with matrix- to clast-supported textures. The VK facies fragmented by dry, volatile-driven processes and were emplaced by eruption column collapse back into the volcanic vents. The first explosive products, poorly preserved because of partial destruction by later eruptions, are found in the central-east vent and were formed by eruption column collapse after the vent was largely cleared of country rock debris. The next active vent was either the north or south vent. Collapse of the eruption column, linked to a vent widening episode, resulted in coeval avalanching of pipe margin walls into the north vent, forming interstratified lenses of country rock-rich boulder breccias in finer-grained volcaniclastic kimberlite. South vent kimberlite has similar characteristics to kimberlite of the north vent and likely formed by similar processes. The final eruptive phase formed olivine-rich and moderately sorted deposits of the central vent. Better sorting is attributed to recycling of kimberlite debris by multiple eruptions through the unconsolidated volcaniclastic pile and associated collapse events. Post-emplacement alteration varies in intensity, but in all cases, has overprinted the primary groundmass and matrix, in CK and VK, respectively. Erosion has since removed all limestone cover.
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Montserrat now provides one of the most complete datasets for understanding the character and tempo of hazardous events at volcanic islands. Much of the erupted material ends up offshore, and this offshore record may be easier to date due to intervening hemiplegic sediments between event beds. The offshore dataset includes the first scientific drilling of volcanic island landslides during IODP Expedition 340, together with an unusually comprehensive set of shallow sediment cores and 2-D and 3-D seismic surveys. Most recently in 2013, Remotely Operated Vehicle (ROV) dives mapped and sampled the surface of the main landslide deposits. This contribution aims to provide an overview of key insights from ongoing work on IODP Expedition 340 Sites offshore Montserrat.Key objectives are to understand the composition (and hence source), emplacement mechanism (and hence tsunami generation) of major landslides, together with their frequency and timing relative to volcanic eruption cycles. The most recent major collapse event is Deposit 1, which involved ~1.8 km cubed of material and produced a blocky deposit at ~12-14ka. Deposit 1 appears to have involved not only the volcanic edifice, but also a substantial component of a fringing bioclastic shelf, and material locally incorporated from the underlying seafloor. This information allows us to test how first-order landslide morphology (e.g. blocky or elongate lobes) is related to first-order landslide composition. Preliminary analysis suggests that Deposit 1 occurred shortly before a second major landslide on the SW of the island (Deposit 5). It may have initiated English's Crater, but was not associated with a major change in magma composition. An associated turbidite-stack suggests it was emplaced in multiple stages, separated by at least a few hours and thus reducing the tsunami magnitude. The ROV dives show that mega-blocks in detail comprise smaller-scale breccias, which can travel significant distances without complete disintegration. Landslide Deposit 2 was emplaced at ~130ka, and is more voluminous (~8.4km cubed). It had a much more profound influence on the magmatic system, as it was linked to a major explosive mafic eruption and formation of a new volcanic centre (South Soufriere Hills) on the island. Site U1395 confirms a hypothesis based on the site survey seismic data that Deposit 2 includes a substantial component of pre-existing seafloor sediment. However, surprisingly, this pre-existing seafloor sediment in the lower part of Deposit 2 at Site U1395 is completely undeformed and flat lying, suggesting that Site U1395 penetrated a flat lying block. Work to date material from the upper part of U1396, U1395 and U1394 will also be summarised. This work is establishing a chronostratigraphy of major events over the last 1 Ma, with particularly detailed constraints during the last ~250ka. This is helping us to understand whether major landslides are related to cycles of volcanic eruptions.
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The Bruneau–Jarbidge eruptive center of the central Snake River Plain in southern Idaho, USA produced multiple rhyolite lava flows with volumes of <10 km³ to 200 km³ each from ~11.2 to 8.1 Ma, most of which follow its climactic phase of large-volume explosive volcanism, represented by the Cougar Point Tuff, from 12.7 to 10.5 Ma. These lavas represent the waning stages of silicic volcanism at a major eruptive center of the Yellowstone hotspot track. Here we provide pyroxene compositions and thermometry results from several lavas that demonstrate that the demise of the silicic volcanic system was characterized by sustained, high pre-eruptive magma temperatures (mostly ≥950 °C) prior to the onset of exclusively basaltic volcanism at the eruptive center. Pyroxenes display a variety of textures in single samples, including solitary euhedral crystals as well as glomerocrysts, crystal clots and annealed microgranular inclusions of pyroxene ±magnetite± plagioclase. Pigeonite and augite crystals are unzoned, and there are no detectable differences in major and minor element compositions according to textural variety — mineral compositions in the microgranular inclusions and crystal clots are identical to those of phenocrysts in the host lavas. In contrast to members of the preceding Cougar Point Tuff that host polymodal glass and mineral populations, pyroxene compositions in each of the lavas are characterized by single rather than multiple discrete compositional modes. Collectively, the lavas reproduce and extend the range of Fe–Mg pyroxene compositional modes observed in the Cougar Point Tuff to more Mg-rich varieties. The compositionally homogeneous populations of pyroxene in each of the lavas, as well as the lack of core-to-rim zonation in individual crystals suggest that individual eruptions each were fed by compositionally homogeneous magma reservoirs, and similarities with the Cougar Point Tuff suggest consanguinity of such reservoirs to those that supplied the polymodal Cougar Point Tuff. Pyroxene thermometry results obtained using QUILF equilibria yield pre-eruptive magma temperatures of 905 to 980 °C, and individual modes consistently record higher Ca content and higher temperatures than pyroxenes with equivalent Fe–Mg ratios in the preceding Cougar Point Tuff. As is the case with the Cougar Point Tuff, evidence for up-temperature zonation within single crystals that would be consistent with recycling of sub- or near-solidus material from antecedent magma reservoirs by rapid reheating is extremely rare. Also, the absence of intra-crystal zonation, particularly at crystal rims, is not easily reconciled with cannibalization of caldera fill that subsided into pre-eruptive reservoirs. The textural, compositional and thermometric results rather are consistent with minor re-equilibration to higher temperatures of the unerupted crystalline residue from the explosive phase of volcanism, or perhaps with newly generated magmas from source materials very similar to those for the Cougar Point Tuff. Collectively, the data suggest that most of the pyroxene compositional diversity that is represented by the tuffs and lavas was produced early in the history of the eruptive center and that compositions across this range were preserved or duplicated through much of its lifetime. Mineral compositions and thermometry of the multiple lavas suggest that unerupted magmas residual to the explosive phase of volcanism may have been stored at sustained, high temperatures subsequent to the explosive phase of volcanism. If so, such persistent high temperatures and large eruptive magma volumes likewise require an abundant and persistent supply of basalt magmas to the lower and/or mid-crust, consistent with the tectonic setting of a continental hotspot.
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The crystallization of amorphous semiconductors is a strongly exothermic process. Once initiated the release of latent heat can be sufficient to drive a self-sustaining crystallization front through the material in a manner that has been described as explosive. Here, we perform a quantitative in situ study of explosive crystallization in amorphous germanium using dynamic transmission electron microscopy. Direct observations of the speed of the explosive crystallization front as it evolves along a laser-imprinted temperature gradient are used to experimentally determine the complete interface response function (i.e., the temperature-dependent front propagation speed) for this process, which reaches a peak of 16 m/s. Fitting to the Frenkel-Wilson kinetic law demonstrates that the diffusivity of the material locally/immediately in advance of the explosive crystallization front is inconsistent with those of a liquid phase. This result suggests a modification to the liquid-mediated mechanism commonly used to describe this process that replaces the phase change at the leading amorphous-liquid interface with a change in bonding character (from covalent to metallic) occurring in the hot amorphous material.
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This investigation aimed to quantify metabolic rate when wearing an explosive ordnance disposal (EOD) ensemble (~33kg) during standing and locomotion; and determine whether the Pandolf load carriage equation accurately predicts metabolic rate when wearing an EOD ensemble during standing and locomotion. Ten males completed 8 trials with metabolic rate measured through indirect calorimetry. Walking in EOD at 2.5, 4.0 and 5.5km·h−1 was significantly (p < 0.05) greater than matched trials without the EOD ensemble by 49% (127W), 65% (213W) and 78% (345W), respectively. Mean bias (95% limits of agreement) between predicted and measured metabolism during standing, 2.5, 4 and 5.5km·h−1 were 47W (19 to 75W); −111W (−172 to −49W); −122W (−189 to −54W) and −158W (−245 to −72W), respectively. The Pandolf equation significantly underestimated measured metabolic rate during locomotion. These findings have practical implications for EOD technicians during training and operation and should be considered when developing maximum workload duration models and work-rest schedules.
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Bomb attacks carried out by terrorists, targeting high occupancy buildings, have become increasingly common in recent times. Large numbers of casualties and property damage result from overpressure of the blast followed by failing of structural elements. Understanding the blast response of multi-storey buildings and evaluating their remaining life have therefore become important. Response and damage analysis of single structural components, such as columns or slabs, to explosive loads have been examined in the literature, but the studies on blast response and damage analysis of structural frames in multi-storey buildings is limited and this is necessary for assessing the vulnerability of them. This paper investigates the blast response and damage evaluation of reinforced concrete (RC) frames, designed for normal gravity loads, in order to evaluate their remaining life. Numerical modelling and analysis were carried out using the explicit finite element software, LS DYNA. The modelling and analysis takes into consideration reinforcement details together and material performance under higher strain rates. Damage indices for columns are calculated based on their residual and original capacities. Numerical results generated in the can be used to identify relationships between the blast load parameters and the column damage. Damage index curve will provide a simple means for assessing the damage to a typical multi-storey building RC frame under an external bomb circumstance.
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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
Resumo:
Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.
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For nearly twenty-five years, the field of youth studies has employed the same conceptual tools to explain the conduct of young people, tools that inexorably lead to the same recurrent conclusions-youth equals resistance, youth equals alienation, youth equals problem. This book offers a way out of this theoretical Groundhog Day. Starting with the familiar notion of youth subcultures, but also addressing topics such as young women's magazines, 'at risk' youth, anorexia nervosa, and HIV/AIDS programs, this book examines the way in which youth is produced as both a governmental object and a set of practices of the self. Employing the ideas of Foucault, Rose and Mauss, this new approach attempts to reinvigorate what is an important-yet slumbering-area of research.