4 research outputs found

    From Boatyard to Museum: 3D laser scanning and digital modelling of the Qatar Museums watercraft collection, Doha, Qatar

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    This is the final version of the article. Available from Wiley via the DOI in this record.This article presents the results of a project to 3D laser scan and digitally model 14 watercraft from the Qatar Museums collection, comprising a range of regional vessels: most had not been surveyed previously. The project used the resulting point clouds generated 2D naval lines and orthographic records of the vessels in their current condition, and photorealistic 3D digital models for gallery display. This case study provides illustrative examples of the intermediate stages and final outputs. It assesses the pros and cons of 3D laser scanning as a survey technology for nautical scholars in terms of the time, cost, and skillset, as well as logistical considerations. It also compares the accuracy of traditional hand survey methods.We wish to thank QM for enabling and funding this research (Grant number SL-05894)

    Misfires identification in tunnel blasts

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    Due to economic gain the use of explosives for rock breaking has been the preferred choice in the mining industry for extracting minerals and the construction industries for driving tunnels and underground excavations. Although misfires are not an expected outcome in any form of blasting operations, however, due to the confined nature of underground blast the likelihood of blasthole misfires occurring is increased compared to that of a surface blast. Past research on the use of explosives for rock breaking have been concerned with issues about improving the effective use of explosive energy neglecting such effect as safety hazards and increased operational cost resulting from blasthole misfires. This research project investigate misfires in tunnel blasts with the aim of developing method(s) of minimising it occurrence during the blast design and identify blasthole misfires should they occur. Through a series of test blasts carried out at the Holman’s Test Mine operated by the Camborne School of Mines, three identification techniques based on blast emission data were developed namely; Electro-Magnetic Pulse (EMP Signature), Light (Optical Signature) and seismic (Vibration Signature). The study therefore concluded that whilst no one single method developed could effectively identify blasthole misfires in tunnel blasts, the vibration signature approach is the most pragmatic method for misfire identification in tunnel blasts as measurements are remotely undertaken. Moreover, blast vibration is well understood and part of almost all tunnel blasting operation. The blast vibration measurements and analyses undertaken during the course of this research resulted in the identification of potential blasthole misfires and aided in the safe retrieval of unexploded detonators and explosives cartridges. As a result of the research project several misfires were identified immediately after full face tunnel blasts at the Holmans’ Test Mine and appropriate measures taken to handle the misfires.EThOS - Electronic Theses Online ServiceLondon Metal ExchangeGBUnited Kingdo

    3D LASER SCANNING AND MODELLING OF THE DHOW HERITAGE FOR THE QATAR NATIONAL MUSEUM

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    Curating boats can be difficult. They are complex structures, often demanding to conserve whether in or out of the water; they are usually large, difficult to move on land, and demanding of gallery space. Communicating life on board to a visiting public in the terra firma context of a museum can be difficult. Boats in their native environment are inherently dynamic artifacts. In a museum they can be static and divorced from the maritime context that might inspire engagement. New technologies offer new approaches to these problems. 3D laser scanning and digital modeling offers museums a multifaceted means of recording, monitoring, studying and communicating watercraft in their care. In this paper we describe the application of 3D laser scanning and subsequent digital modeling. Laser scans were further developed using computer-generated imagery (CGI) modeling techniques to produce photorealistic 3D digital models for development into interactive, mediabased museum displays. The scans were also used to generate 2D naval lines and orthographic drawings as a lasting curatorial record of the dhows held by the National Museum of Qatar

    Outlining of high quality coking coal by concentration–volume fractal model and turning bands simulation in East-Parvadeh coal deposit, Central Iran

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    Artículo de publicación ISIThis study aims at identifying the proper parts of C1 and B2 coking coal seams in the North block of East-Parvadeh coal deposit (Central Iran) using the concentration–volume (C–V) fractal modeling according to sulfur and ash values which were calculated by turning bands conditional simulation. The C–V log–log plots were generated based on results of 100 realizations derived via turning bands simulation which show seven different geochemical populations for both sulfur and ash data in B2 seam which has a relatively good quality for coking coal with sulfur and ash values lower than 1.548% and 6.39% respectively. Additionally, C–V log–log plots indicate that there are seven and six for sulfur and ash geochemical populations in C1 seam containing a proper coal quality with respect to sulfur and ash values less than 1.41% and 6.92% respectively. High quality populations are located in the northern and western parts of the studied area which correlated with USGS standard. The logratio matrix was used for the correlation between results obtained by the C–V fractal modeling and geological particulars consisting of pyritic veins and ash coals. Based on the logratio matrix for sulfur values higher than 3.55% and 3.39% for C1 and B2, respectively, low quality parts of the seams have good correlation with pyritic veins in the eastern and central parts of the area. Moreover, there are high values of overall accuracy (OA) for correlation between parts of the seams with high values of ash which are 47.86% and 39.81% for C1 and B2, respectively, and ash coals obtained by geological data
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