期刊文献+
共找到6篇文章
< 1 >
每页显示 20 50 100
Functions of Chinese in Secondary EFL Classroom in China 被引量:1
1
作者 mingfa yao Caijin Zeng 《Sino-US English Teaching》 2006年第7期38-42,共5页
The use of native language in EFL teaching is very common. Although teachers avoid using it, the native language, however, is sometimes quite necessary in practical language teaching. In this paper, the authors invest... The use of native language in EFL teaching is very common. Although teachers avoid using it, the native language, however, is sometimes quite necessary in practical language teaching. In this paper, the authors investigate the use of native language (Chinese) by two teachers in English classroom, analyze and interpret the functions of Chinese in detail. We argue that far from being viewed as a random activity, use of native language can be seen as a purposeful activity. 展开更多
关键词 use of native language functions secondary EFL classroom
下载PDF
Simulation of Automotive Engine Phase Signal Based on Closed-Loop Strategy
2
作者 Runlong Cui mingfa yao Tao Chen 《Transactions of Tianjin University》 EI CAS 2017年第4期394-400,共7页
In this paper, an automotive engine phase signal simulation algorithm is proposed based on a closed-loop feedback strategy, and its corresponding model is built. The signal incentives are carried out in the front-end,... In this paper, an automotive engine phase signal simulation algorithm is proposed based on a closed-loop feedback strategy, and its corresponding model is built. The signal incentives are carried out in the front-end, and the synchronization capture and comparison are conducted in the back-end. The phase simulation of signal output is achieved using closed-loop strategy, which can effectively eliminate the inconsistency between crankshaft and camshaft phases, and thus the accuracy and flexibility of phase signal generation are guaranteed. Experimental results show that the proposed algorithm is real time, and the deviation of simulated signals from actual phase signals is small. © 2017, Tianjin University and Springer-Verlag Berlin Heidelberg. 展开更多
关键词 Crankshafts Engines
下载PDF
Combustion and AI
3
作者 mingfa yao 《Energy and AI》 2023年第4期1-2,共2页
Combustion science has been a classical science since human beings learned to drill wood to make fire.Through the first and second industrial revolutions,the combustion science has been more and more closely integrate... Combustion science has been a classical science since human beings learned to drill wood to make fire.Through the first and second industrial revolutions,the combustion science has been more and more closely integrated with propulsion power devices or other thermal power conversion devices,including internal combustion engine[1],gas turbine[2],thermal power plant[3],etc. 展开更多
关键词 POWER THERMAL COMBUSTION
下载PDF
Development of a simplified n-heptane/methane model for high-pressure direct-injection natural gas marine engines 被引量:3
4
作者 Jingrui LI Haifeng LIU +5 位作者 Xinlei LIU Ying YE Hu WANG Xinyan WANG Hua ZHAO mingfa yao 《Frontiers in Energy》 SCIE CSCD 2021年第2期405-420,共16页
High-pressure direct-injection (HPDI) of natu- ral gas is one of the most promising solutions for future ship engines, in which the combustion process is mainly controlled by the chemical kinetics. However, the employ... High-pressure direct-injection (HPDI) of natu- ral gas is one of the most promising solutions for future ship engines, in which the combustion process is mainly controlled by the chemical kinetics. However, the employment of detailed chemical models for the multi-dimensional combustion simulation is significantly expensive due to the large scale of the marine engine. In the present paper, a reduced n-heptane/methane model consisting of 35-step reactions was constructed using multiple reduction approaches. Then this model was further reduced to include only 27 reactions by utilizing the HyChem (Hybrid Chemistry) method. An overall good agreement with the experimentally measured ignition delay data of both n-heptane and methane for these two reduced models was achieved and reasonable predictions for the measured laminar flame speeds were obtained for the 35-step model. But the 27-step model cannot predict the laminar flame speed very well. In addition, these two reduced models were both able to reproduce the experimentally measured in-cylinder pressure and heat release rate profiles for a HPDI natural gas marine engine, the highest error of predicted combustion phase being 6.5%. However, the engine-out CO emission was over-predicted and the highest error of predicted NOx emission was less than 12.9%. The predicted distributions of temperature and equivalence ratio by the 35-step and 27-step models are similar to those of the 334-step model. However, the predicted distributions of OH and CH2O are significantly different from those of the 334-step model. In short, the reduced chemical kinetic models developed provide a high-efficient and dependable method to simulate the characteristics of combustion and emissions in HPDI natural gas marine engines. 展开更多
关键词 high-pressure direct-injection natural gas chemical kinetics combustion modelling marine engine
原文传递
Large eddy simulation of spray combustion using flamelet generated manifolds combined with artificial neural networks 被引量:5
5
作者 Yan Zhang Shijie Xu +3 位作者 Shenghui Zhong Xue-Song Bai Hu Wang mingfa yao 《Energy and AI》 2020年第2期33-42,共10页
In the present work,artificial neural networks(ANN)technique combined with flamelet generated manifolds(FGM)is proposed to mitigate the memory issue of FGM models.A set of ANN models is firstly trained using a 68-spec... In the present work,artificial neural networks(ANN)technique combined with flamelet generated manifolds(FGM)is proposed to mitigate the memory issue of FGM models.A set of ANN models is firstly trained using a 68-species mass fractions in mixture fraction-progress variable space.The ANN prediction accuracy is examined in large eddy simulation(LES)and Reynolds averaged Navier-Stokes(RANS)simulations of spray combustion.It is shown that the present ANN models can properly replicate the FGM table for most of the species mass fractions.The network models with relative error less than 5%are considered in RANS and LES to simulate the Engine Combustion Network(ECN)Spray H flames.Validation of the method is firstly conducted in the framework of RANS.Both non-reacting and reacting cases show the present method predicts very well the trend of spray and combustion process under different ambient temperatures.The results show that FGM-ANN can replicate the ignition delay time(IDT)and lift-off length(LOL)precisely as the conventional FGM method,and the results agree very well with the experiments.With the help of ANN,it is possible to achieve high efficiency and accuracy,with a significantly reduced memory requirement of the FGM models.LES with FGM-ANN is then applied to explore the detailed spray combustion process.Chemical explosive mode analysis(CEMA)approach is used to identify the local combustion modes.It is found that before the spray flame is developed to the steady-state,the high CH_(2)O zone is always associated with ignition mode.However,high CH_(2)O zone together with high OH zone is dominated by the burned mode after the steady-state.The lift-off position is dominated mainly by the diffusion mode. 展开更多
关键词 Flamelet generated manifolds Artificial neural networks Engine combustion network Spray H Chemical explosive mode analysis
下载PDF
Development of the ignition delay prediction model of n-butane/hydrogen mixtures based on artificial neural network 被引量:1
6
作者 Yanqing Cui Qianlong Wang +4 位作者 Haifeng Liu Zunqing Zheng Hu Wang Zongyu Yue mingfa yao 《Energy and AI》 2020年第2期136-147,共12页
Based on the experimental ignition delay results of n-butane/hydrogen mixtures in a rapid compression machine,a Genetic Algorithm(GA)optimized Back Propagation(BP)neural network model is originally developed for ignit... Based on the experimental ignition delay results of n-butane/hydrogen mixtures in a rapid compression machine,a Genetic Algorithm(GA)optimized Back Propagation(BP)neural network model is originally developed for ignition delay prediction.In the BP model,the activation function,learning rate and the neurons number in the hidden layer are optimized,respectively.The prediction ability of the BP model is validated in wide operating ranges,i.e.,compression pressures from 20 to 25 bar,compression temperatures from 722 to 987 K,equivalence ratios from 0.5 to 1.5 and molar ratios of hydrogen(X_(H2))from 0 to 75%.Compared with the BP model,the GA optimized BP model could increase the average correlation coefficient from 0.9745 to 0.9890,in the opposite,the average Mean Square Error(MSE)decreased from 2.21 to 1.06.On the other hand,to assess the BP-GA model prediction ability in the never-seen-before cases,a limited BP-GA model is fostered in the𝑋X_(H2) range from 0 to 50%to predict the ignition delays at the cases of𝑋X_(H2)=75%.It is found that the predicted ignition delays are underestimated due to the training dataset lacking of“acceleration feature”that happened at𝑋X_(H2)=75%.However,three possible options are reported to improve the prediction accuracy in such never-seen-before cases. 展开更多
关键词 Back propagation(BP)neural network Genetic algorithm(GA) Ignition delay n-Butane/hydrogen mixtures
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部