Jinliang Zhu¹, Xiulei Wang¹, Guihua Wang¹, Xianglin Zhong², Zhenguo Li³, Zhiming Wang¹, Ke Sun^1,*, Shuzhan Bai^1,*

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

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 tailpipe NO_x have been quantitatively… More >

Xia Li^1,2, Peifeng Niu^1,*, 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 NO_X 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. And then, according to… More >