38 research outputs found

    Prediction of two-phase flow patterns in upward inclined pipes via deep learning

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    The industrial process involving gas liquid flows is one of the most frequently encountered phenomena in the energy sectors. However, traditional methods are practically unable to reliably identify flow patterns if additional independent variables/parameters are to be considered rather than gas and liquid superficial velocities. In this paper, we reported an approach to predict flow pattern along upward inclined pipes (0–90°) via deep learning neural networks, using accessible parameters as inputs, namely, superficial velocities of individual phase and inclination angles. The developed approach is equipped with deep learning neural network for flow pattern identification by experimental datasets that were reported in the literature. The predictive model was further validated by comparing its performance with well-established flow regime forecasting methods based on conventional flow regime maps. Besides, the intensity of key features in flow pattern prediction was identified by the deep learning algorithm, which is difficult to be captured by commonly used correlation approache

    Lagrangian actuator model for wind turbine wake aerodynamics

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    As a continuation of authors’ previous work, this work extends and hackles the numerical method for wind turbine wakes based on the vortex method, and proposes the Lagrangian actuator model (LAM) which is used for the representation of the wind turbine rotor under the Lagarangian framework. This paper provides two examples of the LAM, the Lagrangian actuator line (LAL) model and the Lagrangian actuator disc (LAD) model, and constructs matching numerical methods for wake predictions respectively. Those methods have high computation efficiency, and the results coincide with the wind tunnel test data well. Moreover, based on that, a vorticity description framework centered on vortex geometric structures is established to illustrate wind turbine wake phenomena and explore the wake evolution mechanism

    Safety analysis of Railway Transportation of Dangerous goods

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    In the past decade, the demand for dangerous goods (DG) that can be used forindustrial, farming, mining, manufacturing, and pharmaceutical products has surgedwith the rapid development of industrialization. Almost 55,000 billion tonnekilometersof Dangerous Goods (DG) are transported annually by the railroad,accounting for approximately 51% of the total DG traffic volume in Europe. However,the increase in DG rail traffic has led to double the number of accidents involving DGin the last decade. Therefore, due to the increase in the volume of DG shipment andits impact on the environment, the safety of transporting DG has become more of aconcern to the public. The thesis analyzes the current situation of DG railroad transportation in Europe,including the shipment volume and accident/release rate. Fault tree analysismethodology was used to identify and assess the events contributing to DG involvedrelease accidents. Then lastly, recommendations based on the probability analysiswere proposed for improving DG rail transportation safety. The main result fromthis study is that more than half of the DG is transported by railway, and the DGtransported in Europe are mainly flammable liquids and compressed/liquefied gases,which are mainly transported by tank wagons. Due to the increase in the traffic volumeof DG transported since 2007, the trend of DG involved accidents in EU countriesbetween 2011 and 2020 presents an overall increasing trend. The same trend can alsobe observed in the tank wagon derailment/ collision-caused release rate at the sameperiod

    Safety analysis of Railway Transportation of Dangerous goods

    No full text
    In the past decade, the demand for dangerous goods (DG) that can be used forindustrial, farming, mining, manufacturing, and pharmaceutical products has surgedwith the rapid development of industrialization. Almost 55,000 billion tonnekilometersof Dangerous Goods (DG) are transported annually by the railroad,accounting for approximately 51% of the total DG traffic volume in Europe. However,the increase in DG rail traffic has led to double the number of accidents involving DGin the last decade. Therefore, due to the increase in the volume of DG shipment andits impact on the environment, the safety of transporting DG has become more of aconcern to the public. The thesis analyzes the current situation of DG railroad transportation in Europe,including the shipment volume and accident/release rate. Fault tree analysismethodology was used to identify and assess the events contributing to DG involvedrelease accidents. Then lastly, recommendations based on the probability analysiswere proposed for improving DG rail transportation safety. The main result fromthis study is that more than half of the DG is transported by railway, and the DGtransported in Europe are mainly flammable liquids and compressed/liquefied gases,which are mainly transported by tank wagons. Due to the increase in the traffic volumeof DG transported since 2007, the trend of DG involved accidents in EU countriesbetween 2011 and 2020 presents an overall increasing trend. The same trend can alsobe observed in the tank wagon derailment/ collision-caused release rate at the sameperiod

    Hydrodynamic and Energy Capture Properties of a Cylindrical Triboelectric Nanogenerator for Ocean Buoy

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    It is rather challenging to collect ocean wave energy at high efficiency because of its ultra-low frequencies and variable amplitudes. Triboelectric Nanogenerator (TENG) technology is more suitable for harvesting low-frequency than electromagnetic power generation technology. In this work, we designed a built-in cylindrical Triboelectric Nanogenerator (C-TENG) installed inside the ocean buoy (BUOY-41). The hydrodynamic properties of the C-TENG are consistent with the ocean buoy, which are calculated by CFD software (Star-CCM+). The Energy Capture Properties of the C-TENG are established by the finite element software (COMSOL). The C-TENG has high power density (30 mW/m2) and can meet the power demand of the ocean buoy (10 mW). The implementation of the present work is of great academic value and practical significance for the development of efficient marine renewable energy conversion technology, enhancement of marine equipment energy replenishment, enrichment of hydrodynamic theories and revealing of the complex mechanisms
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