JZUS - Journal of Zhejiang University SCIENCE

Journal of Zhejiang University SCIENCE A 2012 Vol.13 No.5 P.344-352

Non-linear relationship between combustion kinetic parameters and coal quality

Author(s): Jian-guo Yang, Xiao-long Zhang, Hong Zhao, Li Shen
Affiliation(s): State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China
Corresponding email(s): zhaohong@zju.edu.cn
Key Words: Kinetic parameter, Coal property, Thermo-gravimetry (TG), Support vector regression machine (SVR), Differential evolution

Share this article to： More <<< Previous Article \|Next Article >>>

Abstract: Combustion kinetic parameters (i.e., activation energy and frequency factor) of coal have been proven to relate closely to coal properties; however, the quantitative relationship between them still requires further study. This paper adopts a support vector regression machine (SVR) to generate the models of the non-linear relationship between combustion kinetic parameters and coal quality. Kinetic analyses on the thermo-gravimetry (TG) data of 80 coal samples were performed to prepare training data and testing data for the SVR. The models developed were used in the estimation of the combustion kinetic parameters of ten testing samples. The predicted results showed that the root mean square errors (RMSEs) were 2.571 for the activation energy and 0.565 for the frequency factor in logarithmic form, respectively. TG curves defined by predicted kinetic parameters were fitted to the experimental data with a high degree of precision.

Reference

[1]Avsar, G., Altinel, H., Yilmaz, M.K., Guzel, B., 2010. Synthesis, characterization, and thermal decomposition of fluorinated salicylaldehyde Schiff base derivatives (salen) and their complexes with copper(II). Journal of Thermal Analysis and Calorimetry, 101(1):199-203.

[2]Balasundaram, S., Kapil, A., 2010. On Lagrangian support vector regression. Expert Systems with Applications, 37(12):8784-8792.

[3]Cherkassky, V., Ma, Y.Q., 2004. Practical selection of SVM parameters and noise estimation for SVM regression. Neural Networks, 17(1):113-126.

[4]Coats, A.W., Redfern, J.P., 1965. Kinetic parameters from thermogravimetric data. II. Journal of Polymer Science Part B: Polymer Letters, 3(11):917-920.

[5]Cumming, J.W., 1984. Reactivity assessment of coals via a weighted mean activation energy. Fuel, 63(10):1436-1440.

[6]da Silva Filho, C.G., Miliol, F.E., 2008. A thermogravimetric analysis of the combustion of a Brazilian mineral coal. Química Nova, 31(1):98-103.

[7]Du, S.W., Chen, W.H., Lucas, J.A., 2010. Pulverized coal burnout in blast furnace simulated by a drop tube furnace. Energy, 35(2):576-581.

[8]Ebrahimi-Kahrizsangi, R., Abbasi, M.H., 2008. Evaluation of reliability of Coats-Reffern method for kinetic analysis of non-isothermal TGA. Transactions of Nonferrous Metals Society of China, 18(1):217-221.

[9]Faúndez, J., Arenillas, A., Rubiera, F., García, X., Gordon, A.L., Pis, J.J., 2005. Ignition behaviour of different rank coals in an entrained flow reactor. Fuel, 84(17):2172-2177.

[10]Gämperle, R., Müller, S.D., Koumoutsakos, P., 2002. A Parameter Study for Differential Evolution. In: Grmela, A., Mastorakis, N.E. (Eds.), Advances in Intelligent Systems, Fuzzy Systems, Evolutionary Computation. Zürich, Switzerland, p.293-298.

[11]GB/T 214-2007. Determination of Total sulfur in Coal. Standards Press of China, Beijing, China (in Chinese).

[12]GB/T 19227-2008. Determination of Nitrogen in Coal. Standards Press of China, Beijing, China (in Chinese).

[13]GB/T 212-2008. Proximate Analysis of Coal. Standards Press of China, Beijing, China (in Chinese).

[14]GB/T 476-2008. Determination of Carbon and Hydrogen in Coal. Standards Press of China, Beijing, China (in Chinese).

[15]Haykiri-Açma, H., Ersoy-Meriçboyu, A., Küçükbayrak, S., 2002. Combustion reactivity of different rank coals. Energy Conversion and Management, 43(4):459-465.

[16]Iplikci, S., 2010. Support vector machines based neuro-fuzzy control of non-linear systems. Neurocomputing, 73(10-12):2097-2107.

[17]Janković, B., 2011. Thermal degradation process of the cured phenolic triazine thermoset resin (Primaset® PT-30). Part I. Systematic non-isothermal kinetic analysis. Thermo-chimica Acta, 519(1-2):114-124.

[18]Jiang, X.M., Han, X.X., Cui, Z.G., 2007. Progress and recent utilization trends in combustion of Chinese oil shale. Progress in Energy and Combustion Science, 33(6):552-579.

[19]Kizgut, S., Yilmaz, S., 2004. Characterization and non-isothermal decomposition kinetics of some Turkish bituminous coals by thermal analysis. Fuel Processing Technology, 85(2-3):103-111.

[20]Koga, N., Tanaka, H., 1988. Significance of kinetic compensation effect in the thermal decomposition of a solid. Thermochimica Acta, 135(C):79-84.

[21]Koga, N., Sesták, J., 1991. Kinetic compensation effect as a mathematical consequence of the exponential rate constant. Thermochimica Acta, 182(2):201-208.

[22]Kohavi, R., 1995. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. Proceedings of the 14th International Joint Conference on Artificial Intelligence, Citeseer, Montreal. Quebec, Canada, p.1137-1143.

[23]Kök, M.V., 2011a. Characterization of medium and heavy rude oils using thermal analysis techniques. Fuel Processing Technology, 92(5):1026-1031.

[24]Kök, M.V., 2011b. Thermo-oxidative characterization and kinetics of tar sands. Energy, 36(8):5338-5342.

[25]Kök, M.V., Özbas, E., Hicyilmaz, C., Karacan, Ö., 1997. Effect of particle size on the thermal and combustion properties of coal. Thermochimica Acta, 302(1-2):125-130.

[26]Kök, M.V., Pokol, G., Keskin, C., Madarasz, J., Bagci, S., 2004. Combustion characteristics of lignite and oil shale samples by thermal analysis techniques. Journal of Thermal Analysis and Calorimetry, 76(1):247-254.

[27]Küçükbayrak, S., Haykiri-Açma, H., Ersoy-Meriçboyu, A., Yaman, S., 2001. Effect of lignite properties on reactivity of lignite. Energy Conversion and Management, 42(5):613-626.

[28]Liu, Z., Wang, Q., Zou, Z., Tan, G., 2011. Arrhenius parameters determination in non-isothermal conditions for the uncatalyzed gasification of carbon by carbon dioxide. Thermochimica Acta, 512(1-2):1-4.

[29]MacCallum, J.R., Munro, M.V., 1992. The kinetic compensation effect for the thermal decomposition of some polymers. Thermochimica Acta, 203:457-463.

[30]Man, C.K., Gibbins, J.R., 2011. Factors affecting coal particle ignition under oxyfuel combustion atmospheres. Fuel, 90(1):294-304.

[31]Meyer, D., Leisch, F., Hornik, K., 2003. The support vector machine under test. Neurocomputing, 55(1-2):169-186.

[32]Müller, K., Smola, A., Rätsch, G., Schölkopf, B., Kohlmorgen, J., Vapnik, V., 1997. Predicting Time Series with Support Vector Machines. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, J.D. (Eds.), Artificial Neural Networks. Springer-Verlag, Berlin, p.999-1004.

[33]Nizam, M., Mohamed, A., Hussain, A., 2010. Dynamic voltage collapse prediction in power systems using support vector regression. Expert Systems with Applications, 37(5):3730-3736.

[34]Ronkkonen, J., Kukkonen, S., Price, K.V., 2005. Real-Parameter Optimization with Differential Evolution. IEEE Congress on Evolutionary Computation, Edinburgh, Scotland, p.506-513.

[35]Salzberg, S.L., 1997. On comparing classifiers: Pitfalls to avoid and a recommended approach. Data Mining and Knowledge Discovery, 1(3):317-328.

[36]Shen, Y., Guo, B., Yu, A., Zulli, P., 2009. Model study of the effects of coal properties and blast conditions on pulverized coal combustion. ISIJ International, 49(6):819-826.

[37]Smith, S.E., Neavel, R.C., Hippo, E.J., Miller, R.N., 1981. DTGA combustion of coals in the Exxon coal library. Fuel, 60(6):458-462.

[38]Storn, R., 1996. On the Usage of Differential Evolution for Function Optimization. Biennial Conference of the North American Fuzzy Information Processing Society (NAFIPS), IEEE. Berkeley, Germany, p.519-523.

[39]Storn, R., Price, K., 1995. Differential Evolution—A Simple and Efficient Adaptive Scheme for Global Optimization Over Continuous Spaces. Technical Report No. TR-95-012, International Computer Science Institute, Berkeley, CA.

[40]Storn, R., Price, K., 1997. Differential evolution—A simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 11(4):341-359.

[41]Syed, S., Qudaih, R., Talab, I., Janajreh, I., 2011. Kinetics of pyrolysis and combustion of oil shale sample from thermogravimetric data. Fuel, 90(4):1631-1637.

[42]Vleeskens, J.M., Nandi, B.N., 1986. Burnout of coals: Comparative bench-scale experiments on pulverized fuel and fluidized bed combustion. Fuel, 65(6):797-802.

[43]Wang, B., Yan, R., Zheng, Y., Zhao, H., Zheng, C., 2011. Mechanistic investigation of chemical looping combustion of coal with Fe₂O₃ oxygen carrier. Fuel, 90(7):2359-2366.

[44]Wang, J.H., Chang, L.P., Li, F., Xie, K.C., 2010. A study on the combustion properties of Western Chinese coals. Energy Sources Part A: Recovery Utilization and Environmental Effects, 32(11):1040-1051.

[45]Yip, K., Ng, E., Li, C.Z., Hayashi, J., Wu, H.W., 2011. A mechanistic study on kinetic compensation effect during low-temperature oxidation of coal chars. Proceedings of the Combustion Institute, 33(2):1755-1762.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Similar articles

- Go to

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

Reference