The Experts below are selected from a list of 1284 Experts worldwide ranked by ideXlab platform
Christopher Tuck - One of the best experts on this subject based on the ideXlab platform.
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3d printing of aluminium alloys additive manufacturing of aluminium alloys using selective laser melting
Progress in Materials Science, 2019Co-Authors: Nesma T. Aboulkhair, Ian A. Ashcroft, Christopher Tuck, Marco Simonelli, Luke Parry, Richard J M HagueAbstract:Abstract Metal Additive Manufacturing (AM) processes, such as selective laser melting (SLM), enable the fabrication of arbitrary 3D-structures with unprecedented degrees of freedom. Research is rapidly progressing in this field, with promising results opening up a range of possible applications across both scientific and industrial sectors. Many sectors are now benefiting from fabricating complex structures using AM technologies to achieve the objectives of light-weighting, increased functionality, and part number reduction, among others. AM also lends potential in fulfilling demands for reducing the cost and design-to-manufacture time. Aluminium alloys are of the main material systems receiving attention in SLM research, being favoured in many high-value applications. However, processing them is challenging due to the difficulties associated with laser-melting aluminium where parts suffer various defects. A number of studies in recent years have developed approaches to remedy them and reported successful SLM of various Al-alloys and have gone on to explore its potential application in advanced Componentry. This paper reports on recent advancements in this area and highlights some key topics requiring attention for further progression. It aims to develop a comprehensive understanding of the interrelation between the various aspects of the subject, as this is essential to demonstrate credibility for industrial needs.
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Selective laser melting of aluminum alloys
Mrs Bulletin, 2017Co-Authors: Nesma T. Aboulkhair, Nicola M. Everitt, Ian Maskery, Ian A. Ashcroft, Christopher TuckAbstract:Metal additive manufacturing (AM) processes, such as selective laser melting, enable powdered metals to be formed into arbitrary 3D shapes. For aluminium alloys, which are desirable in many high-value applications for their low density and good mechanical performance, selective laser melting is regarded as challenging due to the difficulties in laser melting aluminium powders. However, a number of studies in recent years have demonstrated successful aluminium processing, and have gone on to explore its potential for use in advanced, AM Componentry. In addition to enabling the fabrication of highly complex structures, selective laser melting produces parts with characteristically fine microstructures that yield distinct mechanical properties. Research is rapidly progressing in this field, with promising results opening up a range of possible applications across scientific and industrial sectors. This paper reports on recent developments in this area of research as well as highlighting some key topics that require further attention.
Marta Marocchi - One of the best experts on this subject based on the ideXlab platform.
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a complex magma reservoir system for a large volume intra to extra caldera ignimbrite mineralogical and chemical architecture of the vei8 permian ora ignimbrite italy
Journal of Volcanology and Geothermal Research, 2015Co-Authors: Madelaine Ann Willcock, Giuseppe Maria Bargossi, Roberto F Weinberg, Giorgio Gasparotto, Raymond Alexander Fernand Cas, Guido Giordano, Marta MarocchiAbstract:Abstract Intra-caldera settings record a wealth of information on caldera-forming processes, yet field study is rarely possible due to lack of access and exposure. The Permian Ora Formation, Italy, preserves > 1000 m of vertical section through its intra-caldera succession. This provides an excellent opportunity to detail its mineralogical and geochemical architecture and gain understanding of the eruption evolution and insight into the pre-eruptive magma system. Detailed juvenile clast phenocryst and matrix crystal fragment point count and image analysis data, coupled with bulk-rock chemistry and single mineral compositional data, show that the Ora ignimbrite succession is rhyolitic (72.5–77.7% SiO2), crystal-rich (~ 25–57%; average 43%) and has a constant main mineral population (volcanic quartz + sanidine + plagioclase + biotite). Although a seemingly homogeneous ignimbrite succession, important subtle but detectable lateral and vertical variations in modal mineralogy and bulk-rock major and trace elements are identified here. The Ora Formation is comprised of multiple lithofacies, dominated by four densely welded ignimbrite lithofacies. They are crystal-rich, typically lithic-poor ( The Southern and Northern intra-caldera ignimbrite successions are discriminated by variations in total biotite crystal abundance. Detailed mineralogical and chemical data records decreases across the caldera system from south to north in biotite phenocrysts in the groundmass of juvenile clasts (average 12–2%), matrix biotite (average 7.5–2%) and plagioclase crystal fragments (average 18–6%), and total crystal fragment abundance in the matrix (average 47–37%); a biotite compositional change to iron-rich (0.57–0.78 Fe); and bulk-rock element decreases in Fe2O3, MgO, P2O5, Ce, Hf, V, La and Zr, and increases in SiO2, Y and Nb, with TiO2. Together, the changes enable subtle distinction of the Southern and Northern successions, indicating that the Northern deposits are more evolved. Furthermore, the data reveals discrimination within the Northern succession, with the northwestern extra-caldera fine-crystal-rich lithofacies, having a distinct texture, Componentry and composition. The Componentry variation, mineralogical and chemical ranges identified here are consistent with an eruption from a heterogeneous magma system. Our results suggest that the Ora magma was likely stored in multiple chambers within a genetically related magma reservoir network. The mineralogical and chemical architecture together with stratigraphic relationships, enable interpretation of eruption sequence. Caldera eruption is proposed to have commenced in the south and progressed to the north, forming the two pene-contemporaneous caldera depressions. Moreover, this data illustrates heterogeneity and local zonation from base-to-top of the main intra-caldera and extra-caldera successions. These variations together with crystal fragment size variations between ignimbrite lithofacies support the hypothesis of a multi-vent eruption process, incremental caldera in-filling by subtly compositionally different pyroclastic flow pulses, and a lower intensity eruption style ( Willcock et al., 2013 , Willcock et al., 2014 ).
Nesma T. Aboulkhair - One of the best experts on this subject based on the ideXlab platform.
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3d printing of aluminium alloys additive manufacturing of aluminium alloys using selective laser melting
Progress in Materials Science, 2019Co-Authors: Nesma T. Aboulkhair, Ian A. Ashcroft, Christopher Tuck, Marco Simonelli, Luke Parry, Richard J M HagueAbstract:Abstract Metal Additive Manufacturing (AM) processes, such as selective laser melting (SLM), enable the fabrication of arbitrary 3D-structures with unprecedented degrees of freedom. Research is rapidly progressing in this field, with promising results opening up a range of possible applications across both scientific and industrial sectors. Many sectors are now benefiting from fabricating complex structures using AM technologies to achieve the objectives of light-weighting, increased functionality, and part number reduction, among others. AM also lends potential in fulfilling demands for reducing the cost and design-to-manufacture time. Aluminium alloys are of the main material systems receiving attention in SLM research, being favoured in many high-value applications. However, processing them is challenging due to the difficulties associated with laser-melting aluminium where parts suffer various defects. A number of studies in recent years have developed approaches to remedy them and reported successful SLM of various Al-alloys and have gone on to explore its potential application in advanced Componentry. This paper reports on recent advancements in this area and highlights some key topics requiring attention for further progression. It aims to develop a comprehensive understanding of the interrelation between the various aspects of the subject, as this is essential to demonstrate credibility for industrial needs.
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Selective laser melting of aluminum alloys
Mrs Bulletin, 2017Co-Authors: Nesma T. Aboulkhair, Nicola M. Everitt, Ian Maskery, Ian A. Ashcroft, Christopher TuckAbstract:Metal additive manufacturing (AM) processes, such as selective laser melting, enable powdered metals to be formed into arbitrary 3D shapes. For aluminium alloys, which are desirable in many high-value applications for their low density and good mechanical performance, selective laser melting is regarded as challenging due to the difficulties in laser melting aluminium powders. However, a number of studies in recent years have demonstrated successful aluminium processing, and have gone on to explore its potential for use in advanced, AM Componentry. In addition to enabling the fabrication of highly complex structures, selective laser melting produces parts with characteristically fine microstructures that yield distinct mechanical properties. Research is rapidly progressing in this field, with promising results opening up a range of possible applications across scientific and industrial sectors. This paper reports on recent developments in this area of research as well as highlighting some key topics that require further attention.
Le Pennec Jean-luc - One of the best experts on this subject based on the ideXlab platform.
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The milling factory : Componentry-dependent fragmentation and fines production in pyroclastic flows
2016Co-Authors: Bernard J., Le Pennec Jean-lucAbstract:In order to decipher the mobility of hazardous small-volume pyroclastic flows (PFs), we investigate here the role of clast fragmentation and production of fine particles (
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The milling factory: Componentry-dependent fragmentation and fines production in pyroclastic flows
'Geological Society of America', 2016Co-Authors: Bernard Julien, Le Pennec Jean-lucAbstract:International audienceIn order to decipher the mobility of hazardous small-volume pyroclastic flows (PFs), we investigate here the role of clast fragmentation and production of fine particles (
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Highly explosive eruption of the monogenetic 8.6 ka BP La Vache et Lassolas scoria cone complex (Chaine des Puys, France)
2016Co-Authors: Jordan S. C., Roche Olivier, Le Pennec Jean-luc, Gurioli L., Boivin P.Abstract:The eruption of the trachy-basaltic La Vache and Lassolas cone complex was the youngest eruption (ca. 8.6 ka BP) and one of the most violent in the Chaine des Puys, France. Here we present field data and results of grain size, Componentry and clast density measurements of different layers of the widespread tephra deposit that is associated with this cone-forming eruption. Our data indicates five main eruption phases comprising a vent opening phase, a second sustained highly explosive phase, a third and fourth violent Strombolian phase and a fifth dominantly effusive phase. The layer formed by the opening phase is rich in lithic material, which was previously considered to be the result of phreatomagmatic activity. The data presented here on the Componentry and textures of the pyroclastic material contradict this hypothesis. We propose instead that the material of the basal layer results from fragmentation caused by the explosion of a first arriving gas-dominated phase. The variations in eruption intensity during the main eruption phases are interpreted here to be the result of gas segregation within the plumbing system and fluxes in the magma ascent rate during the eruption. Significant amount of gas segregation is indicated by the deposition of both gas-poor and gas-rich material and by the presence of plate tephra. This is also supported by the simultaneous ejection of tephra and lava from both cones during most of the explosive activity. We suggest that gas segregation occurred within shallow intrusions and that fresh ascending material in the main conduit mixed with degassed material that flow back into the conduit from the intrusion before fragmentation. The interaction of the ascending magma and the opening of intrusions may have controlled the evolution and explosivity of the eruption. The high explosivity at the beginning of the eruption and the wide dispersal area, demonstrate that scoria cone eruptions in monogenetic fields can impose a major threat to the population and infrastructures nearby as these events may occur with little warning, and therefore research on this kind of eruptions is of a major importance to better understand the processes driving these events
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Eruption Source Parameters for forecasting ash dispersion and deposition from vulcanian eruptions at Tungurahua volcano : insights from field data from the July 2013 eruption
2016Co-Authors: Parra R., Le Pennec Jean-luc, Bernard Benjamin, Narvaez D., Hasselle N., Folch A.Abstract:Tungurahua volcano, located in the central area of the Ecuadorian Sierra, is erupting intermittently since 1999 alternating between periods of quiescence and explosive activity. Volcanic ash has been the most frequent and widespread hazard provoking air contamination episodes and impacts on human health, animals and crops in the surrounding area. After two months of quiescence, Tungurahua erupted violently on 14th July 2013 generating short-lived eruptive columns rising up to 9 km above the vent characterized as a vulcanian eruption. The resulting fallout deposits were sampled daily during and after the eruptions to determine grain size distributions and perform morphological and Componentry analyses. Dispersion and sedimentation of ash were simulated numerically coupling the meteorological Weather Research Forecasting (WRF) with the volcanic ash dispersion FALL3D models. The combination of field and numerical studies allowed constraining the Eruption Source Parameters (ESP) for this event, which could be used to forecast ash dispersion and deposition from future vulcanian eruptions at Tungurahua. This set of pre-defined ESP was further validated using two different eruptions, as blind test, occurring on 16th December 2012 and 1st February 2014
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Eruption Source Parameters for forecasting ash dispersion and deposition from vulcanian eruptions at Tungurahua volcano: Insights from field data from the July 2013 eruption
'Elsevier BV', 2016Co-Authors: Parra René, Le Pennec Jean-luc, Bernard Benjamin, Narváez Diego, Hasselle Nathalie, Folch ArnauAbstract:International audienceTungurahua volcano, located in the central area of the Ecuadorian Sierra, is erupting intermittently since 1999 alternating between periods of quiescence and explosive activity. Volcanic ash has been the most frequent and widespread hazard provoking air contamination episodes and impacts on human health, animals and crops in the surrounding area. After two months of quiescence, Tungurahua erupted violently on 14th July 2013 generating short-lived eruptive columns rising up to 9 km above the vent characterized as a vulcanian eruption. The resulting fallout deposits were sampled daily during and after the eruptions to determine grain size distributions and perform morphological and Componentry analyses. Dispersion and sedimentation of ash were simulated numerically coupling the meteorological Weather Research Forecasting (WRF) with the volcanic ash dispersion FALL3D models. The combination of field and numerical studies allowed constraining the Eruption Source Parameters (ESP) for this event, which could be used to forecast ash dispersion and deposition from future vulcanian eruptions at Tungurahua. This set of pre-defined ESP was further validated using two different eruptions, as blind test, occurring on 16th December 2012 and 1st February 2014
Laurent Schmalen - One of the best experts on this subject based on the ideXlab platform.
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end to end deep learning of optical fiber communications
Journal of Lightwave Technology, 2018Co-Authors: Boris Karanov, Mathieu Chagnon, Felix Thouin, Tobias A Eriksson, Henning Bulow, Domanic Lavery, P Bayvel, Laurent SchmalenAbstract:In this paper, we implement an optical fiber communication system as an end-to-end deep neural network, including the complete chain of transmitter, channel model, and receiver. This approach enables the optimization of the transceiver in a single end-to-end process. We illustrate the benefits of this method by applying it to intensity modulation/direct detection (IM/DD) systems and show that we can achieve bit error rates below the 6.7% hard-decision forward error correction (HD-FEC) threshold. We model all Componentry of the transmitter and receiver, as well as the fiber channel, and apply deep learning to find transmitter and receiver configurations minimizing the symbol error rate. We propose and verify in simulations a training method that yields robust and flexible transceivers that allow—without reconfiguration—reliable transmission over a large range of link dispersions. The results from end-to-end deep learning are successfully verified for the first time in an experiment. In particular, we achieve information rates of 42 Gb/s below the HD-FEC threshold at distances beyond 40 km. We find that our results outperform conventional IM/DD solutions based on two- and four-level pulse amplitude modulation with feedforward equalization at the receiver. Our study is the first step toward end-to-end deep learning based optimization of optical fiber communication systems.
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end to end deep learning of optical fiber communications
arXiv: Information Theory, 2018Co-Authors: Boris Karanov, Mathieu Chagnon, Felix Thouin, Tobias A Eriksson, Henning Bulow, Domanic Lavery, P Bayvel, Laurent SchmalenAbstract:In this paper, we implement an optical fiber communication system as an end-to-end deep neural network, including the complete chain of transmitter, channel model, and receiver. This approach enables the optimization of the transceiver in a single end-to-end process. We illustrate the benefits of this method by applying it to intensity modulation/direct detection (IM/DD) systems and show that we can achieve bit error rates below the 6.7\% hard-decision forward error correction (HD-FEC) threshold. We model all Componentry of the transmitter and receiver, as well as the fiber channel, and apply deep learning to find transmitter and receiver configurations minimizing the symbol error rate. We propose and verify in simulations a training method that yields robust and flexible transceivers that allow---without reconfiguration---reliable transmission over a large range of link dispersions. The results from end-to-end deep learning are successfully verified for the first time in an experiment. In particular, we achieve information rates of 42\,Gb/s below the HD-FEC threshold at distances beyond 40\,km. We find that our results outperform conventional IM/DD solutions based on 2 and 4 level pulse amplitude modulation (PAM2/PAM4) with feedforward equalization (FFE) at the receiver. Our study is the first step towards end-to-end deep learning-based optimization of optical fiber communication systems.