An artificial neutral network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

Paper

Jahirul, M. L., Senadeera, W., Brooks, P., Brown, R. J., Situ, R., Pham, P. X. and Masri, A. R.. 2013. "An artificial neutral network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions." Piantadosi, J., Anderssen, R. S. and Boland, J. (ed.) 20th International Congress on Modelling and Simulation (MODSIM2013). Adelaide, Australia 01 - 06 Dec 2013 Australia. Modelling and Simulation Society of Australia and New Zealand . https://doi.org/10.36334/modsim.2013.G6.jahirul
Paper/Presentation Title

An artificial neutral network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

Presentation TypePaper
AuthorsJahirul, M. L. (Author), Senadeera, W. (Author), Brooks, P. (Author), Brown, R. J. (Author), Situ, R. (Author), Pham, P. X. (Author) and Masri, A. R. (Author)
EditorsPiantadosi, J., Anderssen, R. S. and Boland, J.
Journal or Proceedings TitleProceedings of the 20th International Congress on Modelling and Simulation (MODSIM2013)
Number of Pages7
Year2013
PublisherModelling and Simulation Society of Australia and New Zealand
Place of PublicationAustralia
ISBN9780987214331
Digital Object Identifier (DOI)https://doi.org/10.36334/modsim.2013.G6.jahirul
Web Address (URL) of Paperhttp://www.mssanz.org.au/modsim2013/authorsA-B.html#b
Web Address (URL) of Conference Proceedingshttps://mssanz.org.au/modsim2013/papersbysession.html
Conference/Event20th International Congress on Modelling and Simulation (MODSIM2013)
Event Details
Rank
C
C
C
C
C
C
C
Event Details
20th International Congress on Modelling and Simulation (MODSIM2013)
Parent
International Congress on Modelling and Simulation
Delivery
In person
Event Date
01 to end of 06 Dec 2013
Event Location
Adelaide, Australia
Event Venue
Adelaide Convention Centre
Event Web Address (URL)
Abstract

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and
physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

KeywordsANN model, biodiesel, kinematic viscosity, temperature dependence
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 2020401703. Energy generation, conversion and storage (excl. chemical and electrical)
Byline AffiliationsQueensland University of Technology
University of the Sunshine Coast
James Cook University
University of Sydney
Institution of OriginUniversity of Southern Queensland
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Jahirul, M. I., Senadeera, W., Brown, R. J. and Moghaddam, L.. 2014. "Estimation of biodiesel properties from chemical composition – an artificial neural network (ANN) approach." International Scientific Journal of Environmental Science. 3 (3), pp. 1-7.
Analysis of strain-rate dependent mechanical behavior of single chondrocyte: a finite element study
Gu, YuanTong, Nguyen, Trung Dung, Oloyede, Adekunle and Senadeera, Wijitha. 2014. "Analysis of strain-rate dependent mechanical behavior of single chondrocyte: a finite element study." International Journal of Computational Methods. 11 (1 (Supplement)), pp. 1344005-1. https://doi.org/10.1142/S0219876213440052
A particle based model to simulate microscale morphological changes of plant tissues during drying
Karunasena, H. C. P., Senadeera, W., Brown, R. J. and Gu, Y. T.. 2014. "A particle based model to simulate microscale morphological changes of plant tissues during drying." Soft Matter. 10 (29), pp. 5249-5268. https://doi.org/10.1039/c4sm00526k
The influence of abrasive pretreatment on hot air drying of grape
Adiletta, Giuseppina, Senadeera, Wijitha, Liguori, Loredana, Crescitelli, Alessio, Albanese, Donatella and Russo, Paula. 2015. "The influence of abrasive pretreatment on hot air drying of grape." Food and Nutrition Sciences. 6, pp. 355-364. https://doi.org/10.4236/fns.2015.63036
Numerical investigation of plant tissue porosity and its influence on cellular level shrinkage during drying
Karunasena, H. C. P., Gu, Y. T., Brown, R. J. and Senadeera, W.. 2015. "Numerical investigation of plant tissue porosity and its influence on cellular level shrinkage during drying." Biosystems Engineering. 132, pp. 71-87. https://doi.org/10.1016/j.biosystemseng.2015.02.002
Influence of drying conditions on the moisture diffusion during single stage and two stage fluidized bed drying of bovine intestine for pet food
Alves-Filho, O., Senadeera, W. and Eikevik, T.. 2013. "Influence of drying conditions on the moisture diffusion during single stage and two stage fluidized bed drying of bovine intestine for pet food." Goncharova-Alves, S., Alves-Filho, O. and Eikevik, T. M. (ed.) 6th Nordic Drying Conference (NDC2013). Copenhagen, Denmark 05 - 07 Jun 2013 Copenhagen, Denmark.
Drying condition effects on fluidization quality and fluidization velocity at initial and final stages of cubical particulates for pet food
Alves-Filho, O., Senadeera, W. and Eikevik, T.. 2013. "Drying condition effects on fluidization quality and fluidization velocity at initial and final stages of cubical particulates for pet food." Goncharova-Alves, S., Alves-Filho, O. and Eikevik, T. M. (ed.) 6th Nordic Drying Conference (NDC2013). Copenhagen, Denmark 05 - 07 Jun 2013 Copenhagen, Denmark.
Application of meshfree methods to numerically simulate microscale deformations of different plant food materials during drying
Karunasena, H. C. P., Brown, R. J., Gu, Y. T. and Senadeera, W.. 2015. "Application of meshfree methods to numerically simulate microscale deformations of different plant food materials during drying." Journal of Food Engineering. 146, pp. 209-226. https://doi.org/10.1016/j.jfoodeng.2014.09.011
The use of artificial neural networks for identifying sustainable biodiesel feedstocks
Jahirul, Mohammed I., Brown, Richard J., Senadeera, Wijitha, O'Hara, Ian M. and Ristovski, Zoran D.. 2013. "The use of artificial neural networks for identifying sustainable biodiesel feedstocks." Energies. 6 (8), pp. 3764-3806. https://doi.org/10.3390/en6083764
Scanning electron microscopic study of microstructure of gala apples during hot air drying
Karunasena, H. C. P., Hesami, P., Senadeera, W., Gu, Y. T., Brown, R. J. and Oloyede, A.. 2014. "Scanning electron microscopic study of microstructure of gala apples during hot air drying." Drying Technology: an international journal. 32 (4), pp. 455-468. https://doi.org/10.1080/07373937.2013.837479
Numerical investigation of case hardening of plant tissue during drying and its influence on the cellular-level shrinkage
Karunasena, H. C. P., Gu, Y.T., Brown, R. J. and Senadeera, W.. 2015. "Numerical investigation of case hardening of plant tissue during drying and its influence on the cellular-level shrinkage." Drying Technology: an international journal. 33 (6), pp. 713-734. https://doi.org/10.1080/07373937.2014.982759
Biodiesel production from non-edible beauty leaf (Calophyllum inophyllum) oil: process pptimization using response surface methodology (RSM)
Jahirul, Mohammad I., Koh, Wenyong, Brown, Richard J., Senadeera, Wijitha, O'Hara, Ian and Moghaddam, Lalehvash. 2014. "Biodiesel production from non-edible beauty leaf (Calophyllum inophyllum) oil: process pptimization using response surface methodology (RSM)." Energies. 7 (8), pp. 5317-5331. https://doi.org/10.3390/en7085317
Numerical Modeling of Morphological Changes of Food Plant Materials during Drying
Karunasena, H. C. P. and Senadeera Wijitha. 2017. "Numerical Modeling of Morphological Changes of Food Plant Materials during Drying ." Zhang, Min, Bhandari, Bhesh and Fang, Zhongxiang (ed.) Handbook of Drying of Vegetables and Vegetable Products. United Kingdom. CRC Press. pp. 387-427
The Drying Constant and its Effect on the Shrinkage Constant of Different-Shaped Food Particulates
Senadeera, Wijitha. 2008. "The Drying Constant and its Effect on the Shrinkage Constant of Different-Shaped Food Particulates." International Journal of Food Engineering. 4 (8). https://doi.org/10.2202/1556-3758.1219
Drying constant and shrinkage constant relations of different shaped food particulates: empirical models
Senadeera, W.. 2008. "Drying constant and shrinkage constant relations of different shaped food particulates: empirical models." Thorat, B. N. and Mujumdar, A. S. (ed.) 16th International Drying Symposium (IDS 2008). Hyderabad, India 09 - 12 Nov 2008 https://doi.org/10.1080/07373930903221812
Fluidization characteristics of moist food particles
Senadeera, Wijitha, Wijesinghe, Bandu, Young, Gordon and Bhandari, Bhesh. 2006. "Fluidization characteristics of moist food particles." International Journal of Food Engineering. 2 (1), pp. 1-13. https://doi.org/10.2202/1556-3758.1047
Modeling dimensional shrinkage of shaped foods in fluidized bed drying
Senadeera, Wijitha, Bhandari, Bhesh R., Young, Gordon and Wijesinghe, Bandu. 2005. "Modeling dimensional shrinkage of shaped foods in fluidized bed drying." Journal of Food Processing and Preservation. 29 (2), pp. 109-119. https://doi.org/10.1111/j.1745-4549.2005.00017.x
Influence of shapes of selected vegetable materials on drying kinetics during fluidized bed drying
Senadeera, Wijitha, Bhandari, Bhesh R., Young, Gordon and Wijesinghe, Bandu. 2003. "Influence of shapes of selected vegetable materials on drying kinetics during fluidized bed drying." Journal of Food Engineering. 58 (3), pp. 277-283. https://doi.org/10.1016/S0260-8774(02)00386-2
Methods for effective fluidization of particulate food materials
Senadeera, Wijitha, Bhandari, Bhesh R., Young, Gordon and Wijesinghe, Bandu. 2000. "Methods for effective fluidization of particulate food materials." Drying Technology: an international journal. 18 (7), pp. 1537-1557. https://doi.org/10.1080/07373930008917792
Physical properties and fluidization behaviour of fresh green bean particulates during fluidized bed drying
Senadeera, W., Bhandari, B., Young, G. and Wijesinghe, B.. 2000. "Physical properties and fluidization behaviour of fresh green bean particulates during fluidized bed drying." Food and Bioproducts Processing. 78 (C1), pp. 43-47. https://doi.org/10.1205/096030800532707