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  • Open Access

    ARTICLE

    A Study of the Effect of the Miller Cycle on the Combustion of a Supercharged Marine Diesel Engine

    Lingjie Zhao, Cong Li*

    Energy Engineering, Vol.121, No.5, pp. 1363-1380, 2024, DOI:10.32604/ee.2024.046918 - 30 April 2024

    Abstract The Miller cycle is a program that effectively reduces NOx emissions from marine diesel engines by lowering the maximum combustion temperature in the cylinder, thereby reducing NOx emissions. To effectively investigate the impact of Miller cycle optimum combustion performance and emission capability under high load conditions, this study will perform a one-dimensional simulation of the performance of a marine diesel engine, as well as a three-dimensional simulation of the combustion in the cylinder. A 6-cylinder four-stroke single-stage supercharged diesel engine is taken as the research object. The chassis dynamometer and other related equipment are used to… More >

  • Open Access

    ARTICLE

    Experimental Analysis of the Influence of Exhaust Thermal Management on Engine NOx Emission

    Jinliang Zhu1, Xiulei Wang1, Guihua Wang1, Xianglin Zhong2, Zhenguo Li3, Zhiming Wang1, Ke Sun1,*, Shuzhan Bai1,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.3, pp. 701-711, 2022, DOI:10.32604/fdmp.2022.019311 - 22 February 2022

    Abstract Exhaust thermal management is essential to allow engines to meet the Euro VI emissions standards and reducing nitrogen oxide emissions is one of the most important targets being pursued nowadays. Along these lines, in the present study, engine’s thermal performances have been evaluated on the basis of a WHTC test, namely a transient engine dynamometer schedule defined by the global technical regulation (GTR) developed by the UN ECE GRPE group (the GTR is covering a world-wide harmonized heavy-duty certification (WHDC) procedure for engine exhaust emissions). The influence of thermal management on fuel consumption, intake, and… More >

  • Open Access

    ARTICLE

    Improved Teaching-Learning-Based Optimization Algorithm for Modeling NOX Emissions of a Boiler

    Xia Li1,2, Peifeng Niu1,*, Jianping Liu2, Qing Liu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.1, pp. 29-57, 2018, DOI:10.31614/cmes.2018.04020

    Abstract An improved teaching-learning-based optimization (I-TLBO) algorithm is proposed to adjust the parameters of extreme learning machine with parallel layer perception (PELM), and a well-generalized I-TLBO-PELM model is obtained to build the model of NOX emissions of a boiler. In the I-TLBO algorithm, there are four major highlights. Firstly, a quantum initialized population by using the qubits on Bloch sphere replaces a randomly initialized population. Secondly, two kinds of angles in Bloch sphere are generated by using cube chaos mapping. Thirdly, an adaptive control parameter is added into the teacher phase to speed up the convergent speed. More >

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