Full Text:   <1602>

Summary:  <1484>

CLC number: TK16

On-line Access: 2019-06-05

Received: 2018-11-22

Revision Accepted: 2019-05-06

Crosschecked: 2019-05-25

Cited: 0

Clicked: 3704

Citations:  Bibtex RefMan EndNote GB/T7714


Shi-quan Shan


-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE A 2019 Vol.20 No.6 P.431-446


Radiative energy flux characteristics and model analysis for one-dimensional fixed-bed oxy-coal combustion

Author(s):  Shi-quan Shan, Zhi-jun Zhou, Zhi-hua Wang, Ke-fa Cen

Affiliation(s):  State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   shiquan1204@zju.edu.cn, zhouzj@zju.edu.cn

Key Words:  Radiative energy flux, Fixed-bed, Oxy-coal combustion, Artificial neural network (ANN), Energy quality-splitting conversion

Shi-quan Shan, Zhi-jun Zhou, Zhi-hua Wang, Ke-fa Cen. Radiative energy flux characteristics and model analysis for one-dimensional fixed-bed oxy-coal combustion[J]. Journal of Zhejiang University Science A, 2019, 20(6): 431-446.

@article{title="Radiative energy flux characteristics and model analysis for one-dimensional fixed-bed oxy-coal combustion",
author="Shi-quan Shan, Zhi-jun Zhou, Zhi-hua Wang, Ke-fa Cen",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Radiative energy flux characteristics and model analysis for one-dimensional fixed-bed oxy-coal combustion
%A Shi-quan Shan
%A Zhi-jun Zhou
%A Zhi-hua Wang
%A Ke-fa Cen
%J Journal of Zhejiang University SCIENCE A
%V 20
%N 6
%P 431-446
%@ 1673-565X
%D 2019
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1800648

T1 - Radiative energy flux characteristics and model analysis for one-dimensional fixed-bed oxy-coal combustion
A1 - Shi-quan Shan
A1 - Zhi-jun Zhou
A1 - Zhi-hua Wang
A1 - Ke-fa Cen
J0 - Journal of Zhejiang University Science A
VL - 20
IS - 6
SP - 431
EP - 446
%@ 1673-565X
Y1 - 2019
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1800648

This paper describes the radiative energy flux characteristics of fixed-bed oxy-coal combustion for the purpose of guiding the quality-splitting conversion of combustion energy. An experiment was performed in a tube furnace at a temperature range of 800–1200 °C in O2/N2 and O2/CO2 atmospheres, and the radiative intensity was measured. It was found that an increase in oxygen concentration and temperature could increase the radiative intensity more than 1.5 to 2 fold during combustion, and the radiative energy flux was higher for semi-coke than coal by about 16%–27%. The radiative energy results could be described by a semi-empirical model and an artificial neural network (ANN) model. The results showed that the errors of the ANN were less than 0.01%, and demonstrated the superiority of the ANN. This study provides guidance for subsequent research on quality-splitting conversion of combustion energy.

This paper did the research on radiative energy flux of coal and semi-coke bed combustion in O2/N2 and O2/CO2 atmosphere with a tube furnace experiment rig and the semi-empirical model and the artificial neural network model. The paper proposed a new method to study the bed combustion characters of fuels in oxy-fuel atmosphere. The models are good by comparation with exp. data and can be useful to describe the radiation heat transfer process in the same combustion conditions.


目的:1. 从辐射能利用角度出发,探究一维固定床煤粉富氧燃烧的辐射能流特性,为固体燃料燃烧能量分质分级转化应用提供参考; 2. 对比研究半经验模型与人工神经网络模型这两种建模方法,为人工神经网络模型在后续研究中的应用提供参考.
创新点:1. 提出燃烧光热能量分级转化的概念,为燃烧光热能量分质分级转化系统提供研究基础; 2. 从辐射能量利用的角度研究煤粉燃烧的辐射能流特性; 3. 不局限于实验报告,基于实验数据探究2种建模方法,揭示神经网络模型的优势.
方法:1. 在一维管式炉反应器上进行实验,探究不同燃烧条件下煤粉富氧燃烧的辐射能流特征; 2. 基于辐射传热理论,通过半经验模型描述煤粉在固定床中燃烧的辐射能流; 3. 训练神经网络模型来描述实验结果,通过对比2种方法来揭示神经网络模型在预测结果方面的优势.
结论:1. 固定床煤燃烧过程中的挥发分及煤烟会降低辐射能; 可利用低挥发分燃料以及增大氧浓度来提高火焰辐射能比例. 2. 较高的燃烧温度是提升燃烧辐射能比例最重要的因素; 实践中可以通过采用高热值燃料以及烟气回热等方法来提高燃烧温度. 3. 多联产半焦燃烧辐射能比例高于原煤; 可通过煤热解多联产技术与半焦燃烧光热能量分级利用相结合的方式构成新的煤炭高效清洁利用系统. 4. 人工神经网络不但可以对实验结果进行建模,还能够很好地预测未知工况结果,因此值得在更多的后续研究中使用.

关键词:辐射能流; 固定床; 富氧燃烧; 人工神经网络; 能量分质分级转化

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Andersson K, Johansson R, Johnsson F, et al., 2008. Radiation intensity of propane-fired oxy-fuel flames: implications for soot formation. Energy & Fuels, 22(3):1535-1541.

[2]Barbieri ES, Spina PR, Venturini M, 2012. Analysis of innovative micro-CHP systems to meet household energy demands. Applied Energy, 97:723-733.

[3]Bejarano PA, Levendis YA, 2008. Single-coal-particle combustion in O2/N2 and O2/CO2 environments. Combustion and Flame, 153(1-2):270-287.

[4]Böckh P, Wetzel T, 2012. Heat Transfer: Basics and Practice. Springer-Verlag, Berlin Heidelberg, Germany.

[5]Da Y, Xuan YM, Li Q, 2016. From light trapping to solar energy utilization: a novel photovoltaic–thermoelectric hybrid system to fully utilize solar spectrum. Energy, 95:200-210.

[6]Dincer I, Zamfirescu C, 2014. Advanced Power Generation Systems. Elsevier, Amsterdam, the Netherlands.

[7]Esfe MH, 2017. Designing an artificial neural network using radial basis function (RBF-ANN) to model thermal conductivity of ethylene glycol–water-based TiO2 nanofluids. Journal of Thermal Analysis and Calorimetry, 127(3):2125-2131.

[8]Gao SP, Zhao JT, Wang ZQ, et al., 2013. Effect of CO2 on pyrolysis behaviors of lignite. Journal of Fuel Chemistry and Technology, 41(3):257-264.

[9]Ge LC, Zhang YW, Wang ZH, et al., 2017. A novel power generation system based on the cascade utilization of coal: concept and preliminary experimental results. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 39(19):1955-1962.

[10]Green AS, Waite ML, 2017. Designing chain grate stoker links to reduce polluting and particulate emissions. Journal of the Energy Institute, 90(3):424-430.

[11]Kangwanpongpan T, França FHR, da Silva RC, et al., 2012. New correlations for the weighted-sum-of-gray-gases model in oxy-fuel conditions based on HITEMP 2010 database. International Journal of Heat and Mass Transfer, 55(25-26):7419-7433.

[12]Liu LL, Kumar S, Wang ZH, et al., 2017. Catalytic effect of metal chlorides on coal pyrolysis and gasification part I. Combined TG-FTIR study for coal pyrolysis. Thermochimica Acta, 655:331-336.

[13]Liu LL, Yuan Y, Kumar S, et al., 2018. Catalytic effect of metal chlorides on coal pyrolysis and gasification part II. Effects of acid washing on coal characteristics. Thermochimica Acta, 666:41-50.

[14]Liu X, Chen MQ, Yu D, 2013. Oxygen enriched co-combustion characteristics of herbaceous biomass and bituminous coal. Thermochimica Acta, 569:17-24.

[15]Long R, Li BD, Liu ZC, et al., 2016. Performance analysis of a solar-powered electrochemical refrigerator. Chemical Engineering Journal, 284:325-332.

[16]Modest MF, 2013. Radiative Heat Transfer, 3rd Edition. Academic Press, Amsterdam, the Netherlands.

[17]Rajh B, Yin CG, Samec N, et al., 2018. Advanced CFD modelling of air and recycled flue gas staging in a waste wood-fired grate boiler for higher combustion efficiency and greater environmental benefits. Journal of Environmental Management, 218:200-208.

[18]Rao ZH, Zhao YM, Huang CL, et al., 2015. Recent developments in drying and dewatering for low rank coals. Progress in Energy and Combustion Science, 46:1-11.

[19]Sefidari H, Razmjoo N, Strand M, 2014. An experimental study of combustion and emissions of two types of woody biomass in a 12-MW reciprocating-grate boiler. Fuel, 135:120-129.

[20]Shan SQ, Zhou ZJ, 2019. Second law analysis of spectral radiative transfer and calculation in one-dimensional furnace cases. Entropy, 21(5):461.

[21]Shan SQ, Zhou ZJ, Chen LP, et al., 2017. New weighted-sum-of-gray-gases model for typical pressurized oxy-fuel conditions. International Journal of Energy Research, 41(15):2576-2595.

[22]Shan SQ, Qian B, Zhou ZJ, et al., 2018. New pressurized WSGG model and the effect of pressure on the radiation heat transfer of H2O/CO2 gas mixtures. International Journal of Heat and Mass Transfer, 121:999-1010.

[23]Shan SQ, Zhou ZJ, Cen KF, 2019. An innovative integrated system concept between oxy-fuel thermo-photovoltaic device and a Brayton-Rankine combined cycle and its preliminary thermodynamic analysis. Energy Conversion and Management, 180:1139-1152.

[24]Stanley C, Mojiri A, Rosengarten G, 2016. Spectral light management for solar energy conversion systems. Nanophotonics, 5(1):161-179.

[25]Turns SR, 2012. An Introduction to Combustion: Concepts and Applications, 3rd Edition. McGraw-Hill Higher Education, New York, USA.

[26]Tyagi VV, Kaushik SC, Tyagi SK, 2012. Advancement in solar photovoltaic/thermal (PV/T) hybrid collector technology. Renewable and Sustainable Energy Reviews, 16(3):1383-1398.

[27]Vodička M, Haugen NE, Gruber A, et al., 2018. NOx formation in oxy-fuel combustion of lignite in a bubbling fluidized bed–modelling and experimental verification. International Journal of Greenhouse Gas Control, 76:208-214.

[28]Wang YL, Ma ZY, You HH, et al., 2018. Development of a NOx emission model with seven optimized input parameters for a coal-fired boiler. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 19(4):315-328.

[29]Xu J, Sun R, Ismail TM, et al., 2018. Nitrogen/NO conversion characteristics of coal chars prepared using different pyrolysis procedures under combustion conditions. Fuel, 211:484-491.

[30]Yin CG, Yan JY, 2016. Oxy-fuel combustion of pulverized fuels: combustion fundamentals and modeling. Applied Energy, 162:742-762.

[31]Yörük CR, Meriste T, Sener S, et al., 2018. Thermogravimetric analysis and process simulation of oxy-fuel combustion of blended fuels including oil shale, semicoke, and biomass. International Journal of Energy Research, 42(6):2213-2224.

[32]Zhang ZZ, Zhu MM, Li JB, et al., 2018. Experimental study of ignition and combustion characteristics of single particles of Zhundong lignite. Energy & Fuels, 32(4):4221-4226.

[33]Zhou H, Li Y, Tang Q, et al., 2017. Combining flame monitoring techniques and support vector machine for the online identification of coal blends. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 18(9):677-689.

[34]Zhou ZJ, Hu X, You Z, et al., 2013. Oxy-fuel combustion characteristics and kinetic parameters of lignite coal from thermo-gravimetric data. Thermochimica Acta, 553:54-59.

[35]Zhou ZJ, Ding L, Wu L, et al., 2014. Comparison of structure and gasification reactivity of rapid pyrolysis chars of coal water slurries and parent coals. Energy Technology, 2(3):284-291.

[36]Zhou ZJ, Guo LZ, Chen LP, et al., 2018. Study of pyrolysis of brown coal and gasification of coal-water slurry using the ReaxFF reactive force field. International Journal of Energy Research, 42(7):2465-2480.

Open peer comments: Debate/Discuss/Question/Opinion


Please provide your name, email address and a comment

Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2023 Journal of Zhejiang University-SCIENCE