3,822 research outputs found

    Turbofan forced mixer-nozzle internal flowfield. Volume 3: A computer code for 3-D mixing in axisymmetric nozzles

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    A finite difference method is developed for making detailed predictions of three dimensional subsonic turbulent flow in turbofan lobe mixers. The governing equations are solved by a forward-marching solution procedure which corrects an inviscid potential flow solution for viscous and thermal effects, secondary flows, total pressure distortion and losses, internal flow blockage and pressure drop. Test calculations for a turbulent coaxial jet flow verify that the turbulence model performs satisfactorily for this relatively simple flow. Lobe mixer flows are presented for two geometries typical of current mixer design. These calculations included both hot and cold flow conditions, and both matched and mismatched Mach number and total pressure in the fan and turbine streams

    Adapting concurrency throttling and voltage–frequency scaling for dense eigensolvers

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    We analyze power dissipation and energy consumption during the execution of high-performance dense linear algebra kernels on multi-core processors. On top of this analysis, we propose and evaluate several strategies to adapt concurrency throttling and the voltage–frequency setting in order to obtain an energy-efficient execution of LAPACK’s routine dsytrd. Our strategies take into account the differences between the memory-bound and CPU-bound kernels that govern this routine, and whether problem data fits into the processor’s last level cache.This work was supported by the CICYT Project TIN2011-23283 of MINECO and FEDER, the EU Project FP7 318793 “EXA2GREEN”, and the FPU program of the Ministerio de Educación, Cultura y Deporte

    Assessing the potential of autonomous submarine gliders for ecosystem monitoring across multiple trophic levels (plankton to cetaceans) and pollutants in shallow shelf seas

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    A combination of scientific, economic, technological and policy drivers is behind a recent upsurge in the use of marine autonomous systems (and accompanying miniaturized sensors) for environmental mapping and monitoring. Increased spatial–temporal resolution and coverage of data, at reduced cost, is particularly vital for effective spatial management of highly dynamic and heterogeneous shelf environments. This proof-of-concept study involves integration of a novel combination of sensors onto buoyancy-driven submarine gliders, in order to assess their suitability for ecosystem monitoring in shelf waters at a variety of trophic levels. Two shallow-water Slocum gliders were equipped with CTD and fluorometer to measure physical properties and chlorophyll, respectively. One glider was also equipped with a single-frequency echosounder to collect information on zooplankton and fish distribution. The other glider carried a Passive Acoustic Monitoring system to detect and record cetacean vocalizations, and a passive sampler to detect chemical contaminants in the water column. The two gliders were deployed together off southwest UK in autumn 2013, and targeted a known tidal-mixing front west of the Isles of Scilly. The gliders’ mission took about 40 days, with each glider travelling distances of >1000 km and undertaking >2500 dives to depths of up to 100 m. Controlling glider flight and alignment of the two glider trajectories proved to be particularly challenging due to strong tidal flows. However, the gliders continued to collect data in poor weather when an accompanying research vessel was unable to operate. In addition, all glider sensors generated useful data, with particularly interesting initial results relating to subsurface chlorophyll maxima and numerous fish/cetacean detections within the water column. The broader implications of this study for marine ecosystem monitoring with submarine gliders are discussed

    YodaNN: An Architecture for Ultra-Low Power Binary-Weight CNN Acceleration

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    Convolutional neural networks (CNNs) have revolutionized the world of computer vision over the last few years, pushing image classification beyond human accuracy. The computational effort of today's CNNs requires power-hungry parallel processors or GP-GPUs. Recent developments in CNN accelerators for system-on-chip integration have reduced energy consumption significantly. Unfortunately, even these highly optimized devices are above the power envelope imposed by mobile and deeply embedded applications and face hard limitations caused by CNN weight I/O and storage. This prevents the adoption of CNNs in future ultra-low power Internet of Things end-nodes for near-sensor analytics. Recent algorithmic and theoretical advancements enable competitive classification accuracy even when limiting CNNs to binary (+1/-1) weights during training. These new findings bring major optimization opportunities in the arithmetic core by removing the need for expensive multiplications, as well as reducing I/O bandwidth and storage. In this work, we present an accelerator optimized for binary-weight CNNs that achieves 1510 GOp/s at 1.2 V on a core area of only 1.33 MGE (Million Gate Equivalent) or 0.19 mm2^2 and with a power dissipation of 895 {\mu}W in UMC 65 nm technology at 0.6 V. Our accelerator significantly outperforms the state-of-the-art in terms of energy and area efficiency achieving 61.2 TOp/s/[email protected] V and 1135 GOp/s/[email protected] V, respectively

    Feasibility Study: Vertical Farm EDEN

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    Hundreds of millions of people around the world do not have access to sufficient food. With the global population continuing to increase, the global food output will need to drastically increase to meet demands. At the same time, the amount of land suitable for agriculture is finite, so it is not possibly to meet the growing demand by simply increasing the use of land. Thus, to be able to feed the entire global population, and continue to do so in the future, it will be necessary to drastically increase the food output per land area. One idea which has been recently discussed in the scientific community is called Vertical Farming (VF), which cultivates food crops on vertically stacked levels in (high-rise) buildings. The Vertical Farm, so it is said, would allow for more food production in a smaller area. Additionally, a Vertical Farm could be situated in any place (e.g. Taiga- or desert regions, cities), which would make it possible to reduce the amount of transportation needed to deliver the crops to the supermarkets. The technologies required for the Vertical Farm are well-known and already being used in conventional terrestrial greenhouses, as well as in the designs of bioregenerative Life Support Systems for space missions. However, the economic feasibility of the Vertical Farm, which will determine whether this concept will be developed or not, has not yet been adequately assessed. Through a Concurrent Engineering (CE) process, the DLR Institute for Space Systems (RY) in Bremen, aims to apply its know-how of Controlled Environment Agriculture (CEA) Technologies in space systems to provide valuable spin-off projects on Earth and to provide the first engineering study of a Vertical Farm to assess its economic feasibility

    A new column collapse apparatus for the characterisation of the flowability of granular materials

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    The packaging industry is lacking a standard methodology to characterise the granular flow of a wide range of powders and grains in actual handling conditions. We present a new fully-instrumented granular column collapse apparatus for the experimental investigation of granular flow phenomena, by a quasi-two-dimensional set-up with novel features including: a lifting gate activated by a parallelogram mechanism for material release; a reversible pneumatic circuit to impose fluidised and vacuum conditions to the initial granular column; a set of load cells to monitor the basal load distribution during flow propagation; a 3D laser line profile sensor to scan the free surface morphology of the samples at rest; and a high-speed video recording set to capture near-wall flow visualisations and relevant kinematic measures by particle image velocimetry. The selected results on dry flows of oat flakes, copper sulphate fertiliser, and talc powder samples show their distinctive flow dynamics, indicating the good flowability of fertiliser compared to the poor flowability of talc. This research has implications for the selection and design of bulk solids handling equipment, and the calibration and validation of mechanical and numerical models.Peer ReviewedPostprint (author's final draft

    Asynchronous and Multiprecision Linear Solvers - Scalable and Fault-Tolerant Numerics for Energy Efficient High Performance Computing

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    Asynchronous methods minimize idle times by removing synchronization barriers, and therefore allow the efficient usage of computer systems. The implied high tolerance with respect to communication latencies improves the fault tolerance. As asynchronous methods also enable the usage of the power and energy saving mechanisms provided by the hardware, they are suitable candidates for the highly parallel and heterogeneous hardware platforms that are expected for the near future
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