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Feasibility of hydrogen fuel cell technology for railway intercity services:a case study for the Piedmont in North Carolina

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Railway Engineering Science 2021年第3期29卷 258-270页

作者： Orwell Madovi Andreas Hoffrichter Nick Little Shanelle N.Foster Raphael Isaac Department of Electrical and Computer Engineering Michigan State University428 South Shaw LaneRoom 2120East LansingMI 48824USA Center for Railway Research&Education Broad College of BusinessMichigan State University3535 Forest RoadRoom C-36LansingMI 48910USA

Diesel fuel combustion results in exhaust containing air pollutants and greenhouse gas *** railway vehicles use diesel fuel as their energy *** emissions,as well as concerns about economical,alternative power supply,have driven efforts to move to hydrogen motive *** fuel cell technology applied to railways offers the opportunity to eliminate harmful exhaust emissions and the potential for a low-or zero-emission energy supply ***,only multiple-unit trains with hydrail technology operate *** of an Integrated Hybrid Train Simulator for intercity railway is *** proposed tool incorporates the effect of powertrain components during the wheel-to-tank *** to its predecessors,the proposed reconfigurable tool provides high fidelity with medium requirements and minimum computation *** train simulation and the federal government’s Greenhouse gases,Regulated Emissions,and Energy use in Transportation(GREET)model are used in combination to evaluate the feasibility of various train and powertrain *** Piedmont intercity service operating in North Carolina is used as a case *** study includes six train configurations and powertrain options as well as nine hydrogen supply options in addition to the diesel *** results show that a hydrail option is not only feasible,but a low-or zero-carbon hydrogen supply chain could be possible.

关键词： Hydrail Life cycle assessment criteria pollutants Well-to-wheel Single train simulation Modeling

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Prediction of Ambient PM10 Concentration with Artificial Neural Network

Prediction of Ambient PM10 Concentration with Artificial Neu...

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The 10th EPMESC

作者： L. H. Lam K. M. Mok Department of Civil and Environmental Engineering Faculty of Science and Technology University of Macau Macau SAR China Department of Civil and Environmental Engineering Faculty of Science and Technology University of Macau Macau SAR China

This paper presents the design of building economic and flexible artificial neural network (ANN) model for the prediction of PM10 concentration 24-hour-ahead. In stead of relying purely on historical

关键词： PM10 prediction criteria pollutants meteorological effect artificial neural network

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