ORIGINAL PAPER
Regression analysis of experimental data in a study of the performance of a flat flame burner
 
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Department of Mechanical Engineering, Manufacturing and Thermal Engineering, Technical University of Sofia, Faculty of Engineering and Pedagogy of Sliven, Bulgaria
 
 
Submission date: 2024-01-26
 
 
Final revision date: 2024-03-04
 
 
Acceptance date: 2024-03-06
 
 
Publication date: 2024-06-19
 
 
Corresponding author
Ivan Antonov Petrov   

Department of Mechanical Engineering, Manufacturing and Thermal Engineering, Technical University of Sofia, Faculty of Engineering and Pedagogy of Sliven, Burgasko Shose Blvd 59, 8800, Sliven, Bulgaria
 
 
Polityka Energetyczna – Energy Policy Journal 2024;27(2):89-104
 
KEYWORDS
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ABSTRACT
The complex nature of the combustion process, which simultaneously obeys the laws of thermodynamics, heat transfer, aerodynamics and the chemical kinetics of oxidation reactions, makes numerical modelling very difficult and the experimental approach is currently playing a crucial role in their investigation. The modern highly developed theory of experimental design combines various analytical procedures that allow, with a minimum number of experiments, the obtaining of maximum information about the physical or technological processes under investigation, the properties of materials and phenomena. The ability to determine the influence of the main mode and design parameters on the geometrical characteristics of the flare is a prerequisite for effectively influencing the combustion process in order to intensify it. The present work is an introduction to the methods of planning and knowledge of multifactorial experiments, including: the preparation, conduct and processing of experimental results; mastering the methodology of experimental research; using the methods of mathematical statistics and regression analysis to plan experiments; developing the ability to analyze the object of study; correctly selecting the optimization parameter and the essential factors of the object of study; building an experiment planning matrix to obtain an adequate mathematical model of the object. The objective of this work is to propose an approach to study the effect of mode and design parameters, on the basic dimensions and shape of the gas flare, based on regression analysis of experimental data in the study of the performance of a flat flame burner.
METADATA IN OTHER LANGUAGES:
Polish
Analiza regresji danych eksperymentalnych w badaniu wydajności palnika z płaskim płomieniem
eksperyment czynnikowy, analiza regresji, spalanie, palnik o płaskim płomieniu
Złożony charakter procesu spalania, który jednocześnie podlega prawom termodynamiki, wymiany ciepła, aerodynamiki i kinetyce chemicznej reakcji utleniania, sprawia, że modelowanie numeryczne jest bardzo trudne, a podejście eksperymentalne odgrywa obecnie kluczową rolę w ich badaniach. Nowoczesna, wysoko rozwinięta teoria projektowania eksperymentów łączy w sobie różne procedury analityczne, które pozwalają przy minimalnej liczbie eksperymentów uzyskać maksimum informacji o badanych procesach fizycznych lub technologicznych, właściwościach materiałów i zjawiskach. Umiejętność określenia wpływu trybu głównego i parametrów konstrukcyjnych na charakterystykę geometryczną płomienia jest warunkiem skutecznego oddziaływania na proces spalania w celu jego intensyfikacji. Niniejszy artykuł stanowi wprowadzenie do metod planowania i wiedzy o eksperymentach wieloczynnikowych, obejmujące: przygotowanie, prowadzenie i przetwarzanie wyników eksperymentów; opanowanie metodyki badań eksperymentalnych; wykorzystanie metod statystyki matematycznej i analizy regresji do planowania eksperymentów; rozwijanie umiejętności analizy przedmiotu studiów; prawidłowy dobór parametru optymalizacyjnego i istotnych czynników przedmiotu badań; zbudowanie macierzy planowania eksperymentu w celu uzyskania odpowiedniego modelu matematycznego obiektu. Celem artykułu jest zaproponowanie podejścia do badania wpływu trybu i parametrów projektowych na podstawowe wymiary i kształt pochodni gazowej, w oparciu o analizę regresji danych eksperymentalnych w badaniu wydajności palnika z płaskim płomieniem.
REFERENCES (29)
1.
Ansari et al. 2019 – Ansari, E., Menucci, T., Shahbakhti, M. and Naber, J. 2019. Experimental investigation into effects of high reactive fuel on combustion and emission characteristics of the Diesel – Natural gas Reactivity Controlled Compression Ignition engine. Applied Energy 239, pp. 948–956, DOI: 10.1016/j.apenergy.2019.01.256.
 
2.
Antony, J. 2003. Design of Experiments for Engineers and Scientists. (1st ed.), Amsterdam: Butterworth Heinemann.
 
3.
Antony, J. 2023. Design of Experiments in the service industry: a critical literature review and future research directions. Design of Experiments for Engineers and Scientists (Third Edition), pp. 233–248, DOI: 10.1016/B978-0-443-15173-6.00005-6.
 
4.
Antony, J. 2014. 6. Full Factorial Designs. Design of Experiments for Engineers and Scientists (Second Edition), pp. 63–85, DOI: 10.1016/B978-0-08-099417-8.00006-7.
 
5.
Centi et al. 2023 – Cenci, F., Pankajakshan, A., Facco, P. and Galvanin, F. 2023. An exploratory model-based design of experiments approach to aid parameters identification and reduce model prediction uncertainty. Computers & Chemical Engineering 177, DOI: 10.1016/j.compchemeng.2023.108353.
 
6.
Degtyarev, D.A. A step-by-step methodology for conducting a multifactorial experiment. [Online] http://manyfactors.ru [Accessed: 2024-04-05].
 
7.
Denev et al. 2021 – Denev, I., Ivanov, I. and Atanasov, K. 2021. Experimental Study of the Air Exchange in Livestock Building. 2021 6th International Symposium on Environment-Friendly Energies and Applications (EFEA), Sofia, Bulgaria, pp. 1–6, DOI: 10.1109/EFEA49713.2021.9406239.
 
8.
de Prada et al. 2019 – de Prada, C., Pantelides, C.C. and Pitarch, J.L. 2019. Special Issue on “Process Modelling and Simulation”. Processes 7(8), DOI: 10.3390/pr7080511.
 
9.
Dostiyarov et al. 2022 – Dostiyarov, A., Beloev, H., Anuarbekov, M. and Iliev, I. 2022. Numerical modelling biogas combustion in the novel burner. 2022 8th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE), Ruse, Bulgaria, pp. 1–4, DOI: 10.1109/EEAE53789.2022.9831416.
 
10.
Eriksson et al. 2008 – Eriksson, L., Johansson, E., Kettaneh-Wold, N., Wikström, C. and Wold, S. 2008. Design of Experiments. (3rd ed.), Umeå: MKS Umetrics AB.
 
11.
González, A.G. 1998. Two level factorial experimental designs based on multiple linear regression models: a tutorial digest illustrated by case studies. Analytica Chimica Acta 360(1–3), pp. 227–241, DOI: 10.1016/S0003-2670(97)00701-0.
 
12.
Hatami et al. 2015 – Hatami, M., Cuijpers, M.C.M. and Boot, M.D. 2015. Experimental optimization of the vanes geometry for a variable geometry turbocharger (VGT) using a Design of Experiment (DoE) approach. Energy Conversion and Management 106, pp. 1057–1070, DOI: 10.1016/j.enconman.2015.10.040.
 
13.
Ivanov et al. 2022 – Ivanov, I., Kostov, K., Atanasov, K., Denev, I. and Krystev, N. 2022. Analysis of the air exchange in livestock building through the computational fluid dynamics. EUREKA: Physics and Engineering (3), pp. 28–39, DOI: 10.21303/2461-4262.2022.002349.
 
14.
Jamshidnezhad, M. 2015. 1. Introduction. Experimental Design in Petroleum Reservoir Studies, pp. 1–8, DOI: 10.1016/B978-0-12-803070-7.00001-6.
 
15.
Kostov et al. 2021 – Kostov, K., Ivanov, I. and Atanasov, K. 2021. Development and analysis of a new approach for simplified determination of the heating and the cooling loads of livestock buildings. Eureka: Physics and Engineering (2), pp. 87–98, DOI: 10.21303/2461-4262.2021.001310.
 
16.
Kostov et al. 2022 – Kostov, K.V., Denev, I.N. and Krystev, N.Y. 2022. Research of the combustion process in the initial mixing section of the injection gas burner. Polityka Energetyczna – Energy Policy Journal 25(3), pp. 21–34, DOI: 10.33223/epj/152805.
 
17.
Krishna Prasad, R. and Srivastava, S.N. 2009. Electrochemical degradation of distillery spent wash using catalytic anode: Factorial design of experiments. Chemical Engineering Journal 146(1), pp. 22–29, DOI: 10.1016/j.cej.2008.05.008.
 
18.
Krystev, N. 2021. Multiplying the Effect of Nitrogen Oxides Reduction Under Vortex Burner Conditions at Gas Fuel Injection. 2021 6th International Symposium on Environment-Friendly Energies and Applications (EFEA), Sofia, Bulgaria, pp. 1–4, DOI: 10.1109/EFEA49713.2021.9406255.
 
19.
Kumar et al. 2022 – Sathish Kumar, T., Vignesh, R., Ashok, B., Saiteja, P., Jacob, A., Karthick, C., Jeevanantham, A.K., Senthilkumar, M. and Muhammad Usman, K. 2022. Application of statistical approaches in IC engine calibration to enhance the performance and emission Characteristics: A methodological review. Fuel 324(B), DOI: 10.1016/j.fuel.2022.124607.
 
20.
Lyubimova, O.N. and Sisykov, V.V. 2017. Construction and checking regression models when processing the results of factorial experiments.
 
21.
Madani et al. 2015 – Madani, S., Gheshlaghi, R., Mahdavi, M.A., Sobhani, M. and Elkamel, A. 2015. Optimization of the performance of a double-chamber microbial fuel cell through factorial design of experiments and response surface methodology. Fuel 150, pp. 434–440, DOI: 10.1016/j.fuel.2015.02.039.
 
22.
Makzumova et al. 2023 – Makzumova, A.K., Sarakeshova, N.N., Dostiyarov, A.M. and Iliev, I.K. 2023. Study of the aerodynamics of air flow in burners using the Comsol Multiphysics software. IOP Conference Series: Earth and Environmental Science 1234(1), DOI: 10.1088/1755-1315/1234/1/012014.
 
23.
Mihaluta et al. 2008 – Mihaluta, M., Martin, P. and Dantan, J.Y. 2008. Manufacturing process modelling and simulation. ICME, Italy, 7 p., hal-00999479f [Online] https://hal.archives-ouvertes.... [Accessed: 2024-03-23].
 
24.
Montgomery, D.C. 2013. Design and Analysis of Experiments. (8th ed.), New Jersey: Wiley.
 
25.
Novik, F.S. and Arsov, Y.B. 1981. Experiment planning in metals technology. Sofia: State Technical Publishing House.
 
26.
Pilling, M. 2009. From elementary reactions to evaluated chemical mechanisms for combustion models. Proceedings of the Combustion Institute 32(1), pp. 27–44, DOI: 10.1016/j.proci.2008.08.003.
 
27.
Saltelli et al. 2000 – Saltelli, A., Scott, M. and Chen, K. (Eds.) 2000 – Sensitivity Analysis. Chichester: Wiley.
 
28.
Tomlin, A. 2013. The role of sensitivity and uncertainty analysis in combustion modelling. Proceedings of the Combustion Institute 34(1), pp. 159–176, DOI: 10.1016/j.proci.2012.07.043.
 
29.
Zlateva et al. 2020 – Zlateva, P., Penkova, N. and Krumov, K. 2020. Analysis of combustion efficiency at boilers operating on different fuels. 2020 7th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE), Ruse, Bulgaria, pp. 1–4, DOI: 10.1109/EEAE49144.2020.9278784.
 
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