Prediction and Optimization of Mechanical Properties of Polypropylene/Waste Tire Powder Blends using a Hybrid Artificial Neural Network-Genetic Algorithm (GA-ANN)
Free accessResearch articleFirst published online January, 2008
Prediction and Optimization of Mechanical Properties of Polypropylene/Waste Tire Powder Blends using a Hybrid Artificial Neural Network-Genetic Algorithm (GA-ANN)
Blends of Polypropylene (PP) and waste ground rubber tire powder are studied with respect to the effect of ethylene—propylene—diene monomer (EPDM) and polypropylene grafted maleic anhydride (PP-g-MA) compatibilizer content by using the Design of Experiments methodology, whereby the effect of the four polymers content on the final mechanical properties are predicted. Uniform design method is especially adopted for its advantages. Optimization is done using hybrid Artificial Neural Network-Genetic Algorithm technique. A rubber formulary with respect to the four ingredients are optimized having maximum tensile strength and then compared with a blend predicted to have maximum elongation at break. It is concluded that the blends show fairly good properties provided that it has a relatively higher concentration of PP-g-MA and EPDM content. SEM investigations also corroborates with the observed mechanical properties. A quantitative relationship is then shown between the material concentration and the mechanical properties as a set of contour plots, which are then tested and confirmed experimentally to conform to the optimum blend ratio.
Adhikari, B. , De, D. and Maiti, S. (2000). Reclamation and recycling of waste rubber, Progress in Polymer Science, 25(7): 909—948.
2.
Fuhrmann, I. and Karger-Kocsis , J. (1999). Effects of Ground Tyre Rubber (GTR) on the Mechanical Properties of Thermoplastic Blends, Kautschuk Gummi unt Kunstoffe,52(12): 836—841.
3.
Bagheri, A., Willians, M.A. and Pearson, R.A. (1997). Use of Surface Modified Recycled Rubber Particles for Toughening of Epoxy Polymers, Polymer Engineering and Science, 37(2): 245—251.
4.
Koning, C., van Duin, M., Pagnoulle, C. and Jerome, C.R. (1998). Strategies for Compatibilization of Polymer Blends , Progress in Polymer Science, 23(4): 707—757.
5.
George, S., Joseph, R.Thomas, S. and Varughese, K.T. (1995). Blends of Isotactic Polypropylene and Nitrile Rubber: Morphology, Mechanical Properties and Compatibilization, Polymer, 36(23): 4405—4416.
6.
Thorn, A.D. and Robinson, R.A. (1994). Chapter-1: Compound Design, In: Bhowmick, A.K., Hall, M.M. and Benarey, H. (eds), Rubber Products Manufacturing Technology, pp. 97—98, Marcel Dekker , New York.
7.
Del Vecchio, R.J. (1997). Basics of Response Surface Methods, In: Understanding Design of Experiments: A Primer for Technologists, 83, Chapter 15, pp. 83—90, Hanser/Gardner Publications. Inc., Cincinati, USA.
8.
Derringer, G.C. (1988). Statistical Methods in Rubber Research and Development, Rubber Chemistry and Technology,61(3): 377—421.
9.
Lewis, C., Bunapa, R. and Kiatkamjornwong, S. (2003). Effect of Rubber Ratio, Carbon Black Level, and Accelerator Level on Natural Rubber/Bromobutyl Rubber Blend Properties, Journal of AppliedPolymer Science, 90(11): 3059—3068.
10.
Kukreja, T.R. , Kumar, D., Prasad , K., Chauhan, R.C., Choe, S. and Kundu, P.P. (2002). Optimisation of Physical and Mechanical Properties of Rubber Compounds by Response Surface Methodology——Two Component Modelling using Vegetable Oil and Carbon Black, Polymer Testing,38(7): 1417—1422.
11.
Maridass, B. and Gupta, B.R. (2004). Performance Optimization of a Counter Rotating Twin Screw Extruder for Recycling Natural Rubber Vulcanizates using Response Surface Methodology, Polymer Testing,23(4): 377—385.
12.
Fang, K.T., Lin, D.K.J., Winker, P. and Zhang, Y. (2000). Uniform Design: Theory and Applications, Technometrics, 42(3): 237—248.
13.
Cao, Y. , Zheng, Y.Y. and Fang, B. (2004). Optimization of Polymerase Chain Reaction-amplified Conditions using the Uniform Design Method, Journal of Chemical Technology andBiotechnology , 79(8): 910—913.
14.
Lee, A.W.M. , Chan, W.F., Yuen , F.S.Y., Tse , P.K., Liang, Y.Z. and Fang, K.T. (1997). An Example of a Sequential Uniform Design: Application in Capillary Electrophoresis, Chemometrics and Intelligent LaboratorySystems, 39(1): 11—18.
15.
Guan, F.Y., Wu, H.F. and Luo, Y. (1997). A Novel Strategy for Systematic Optimization of Micellar Electrokinetic Chromatography Separations, Analytica Chimica Acta, 342(2—3): 133—144.
16.
Leung, S.Y.L. , Chan, W.H., Leung , C.H. and Luk , C.H. (1998). Screening the Fabrication Conditions of Ultrafilration Membranes by using Uniform Design and Regression Analysis Methods, Chemometrics and Intelligent LaboratorySystems, 40(2): 203—213.
17.
Fang, Q., Yeung, H.W., Leung, H.W. and Huie, C.W. (2000). Micelle Mediated Extraction and Preconcentration of Ginsenosides from Chinese Herbal Medicine, Journal of Chromatography A, 904(1): 47—55.
18.
Xu, C.P. and Yung, J.W. (2003). Optimization of Submerged-Culture Condittions for Mycelial Growth and Exo-biopolymer Production by Auricularia Polytricha (wood ears fungus) using the Methods of Uniform Design and Regression Analysis, Biotechnology and AppliedBiochemistry, 38(2): 193—199.
19.
Ebube, N.K. , Ababio, G.O. and Adeyeye, C.M. (2000). Preformulation Studies and Characterization of the Physicochemical Properties of Amorphous Polymers using Artificial Neural Networks, International Journal of Pharmaceutics,196(1): 27—31.
20.
White, H. (1992). Artificial Neural Networks: Approximation and Learning Theory, Blackwell, New York.
21.
Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization, and Machine Llearning, Addison-Wesley , London.
22.
Sadeghi, B.H.M. (2000). ABP-Neural Network Predictor Model for Plastic Injection Molding Process, Journal of MaterialsProcessing Technology, 103(3): 411—416.
23.
Chow, T.T., Zhang, G.O., Lin, Z. and Song, C.L. (2002). Global Optimization of Absorption Chiller System by Genetic Algorithm and Neural Network, Energy Build, 34(1): 103—109.
24.
Cook, D.F., Ragsdale, C.T. and Major, R.L. (2000). Combining a Neural Network with a Genetic Algorithm for Process Parameter Optimization, Engineering Applications of Artificial Intelligence, 13(4): 391—396.
25.
Woll, S.L.B. and Cooper, D.J. (1997). Pattern-based Closed-loop Quality Control for the Injection Molding Process, Polymer Engineering and Science , 37(5): 801—812.
26.
Chen, C.R. and Ramaswany, H.S. (2002). Modeling and Optimization of Variable Retort Temperature (VRT) Thermal Processing using Coupled Neural Networks and Genetic Algorithms, Journal ofFood Engineering, 53(3): 209—220.
27.
Ozcelik, B. and Erzurumlu, T. (2005). Determination of Affecting Dimensional Parameters on Warpage of thin Shell Plastic Parts using Integrated Response Surface Method and Genetic Algorithm, International Communications in Heat and Mass Transfer, 32(8): 1085—1094.
28.
Scaffaro, R. , Dintcheva, N.T., Nocilla, M.A. and La Mantia , F.P. (2005). Formulation, Characterization and Optimization of the Processing Condition of Blends of Recycled Polyethylene and Ground Tyre Rubber: Mechanical and Rheological Analysis, Polymer Degradation and Stability,90(2): 281—287.
29.
Montgomery, D.C. (1991). Design and Analysis of Experiments, John Wiley and Sons Inc., New York, USA.
30.
Xin, Z., Kim, J.K., Liu, L., Liu, M., Gao, L., Shi, X. and Chen, X. (2004). Application of the Uniform Experimental Design Method for Rubber Formulation, In: Proceedings of the International Rubber Conference IRC-2004, Beijing , People's Republic of China, Vol. 3, pp. 478—482.
31.
Rajalingam, P. and Baker, W.E. (1992). The Role of Functional Polymers in Ground Rubber Tire-Polyethylene Composites, Rubber Chemistry and Technology,65(5): 908—916.
32.
Phan, T.T.M. , De Nicola, A.J. and Schadler, L.S. (1998). Effect of Addition of Polyoxypropylenediamine on the Morphology and Mechanical Properties of Maleated Polypropylene/Maleated Rubber Blends, Journal of AppliedPolymer Science, 68(9): 1451—1472.
33.
Radonjic, G. (1999). Compatibilization Effects of Styrenic/Rubber Block Copolymers in Polypropylene/Polystyrene Blends, Journal of AppliedPolymer Science, 72(2): 291—307.
34.
Becker, D., Roeder,J., Oliveira, R.V.B., Soldi,V. and Pires, A.T.N. (2003). Blend of Thermosetting Polyurethane Waste with Polypropylene: Influence of CompatibilizinAgent on Interface Domains and Mechanical Properties, Polymer Testing,22(2): 225—230.
35.
Neilsen, I.E. and Landel, R.F. (1994). Mechanical Properties of Polymers and Composites, Marcel Dekker, New York.
36.
Krauss, G. (1965). Reinforcement of Elastomers, Interscience Publishers, New York.
37.
Naskar, A.K. , Bhowmick, A.K. and De , S.K. (2001). Thermoplastic Elastomeric Composition Based on Ground Rubber Tire, Polymer Engineering and Science, 41(6): 1087—1098.
38.
Guo, B. , Cao, Y., Jia , D. and Qui , Q. (2004). Thermoplastic Elastomers Derived from Scrap Rubber Powder/LLDPE Blend with LLDPE-graft-(Epoxidized Natural Rubber) Dual Compatibilizer, Macromoecular Materials and Engineering,289(4): 360—367.
