Modelling the Stiffness-Temperature Dependence of Resin-Rubber Blends Cured by High-Energy Electron Beam Radiation Using Global Search Genetic Algorithm
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
1/0589/17
Vedecká Grantová Agentúra MŠVVaŠ SR a SAV
003TnUAD-4/2019
Kultúrna a Edukacná Grantová Agentúra MŠVVaŠ SR
002TnUAD-4/2019
Kultúrna a Edukacná Grantová Agentúra MŠVVaŠ SR
PubMed
33187100
PubMed Central
PMC7696663
DOI
10.3390/polym12112652
PII: polym12112652
Knihovny.cz E-zdroje
- Klíčová slova
- Weibull distribution, dynamic mechanical analysis, electron-beam irradiation, genetic algorithm, resin-rubber blends,
- Publikační typ
- časopisecké články MeSH
Modelling the influence of high-energy ionising radiation on the properties of materials with polymeric matrix using advanced artificial intelligence tools plays an important role in the research and development of new materials for various industrial applications. It also applies to effective modification of existing materials based on polymer matrices to achieve the desired properties. In the presented work, the effects of high-energy electron beam radiation with various doses on the dynamic mechanical properties of melamine resin, phenol-formaldehyde resin, and nitrile rubber blend have been studied over a wide temperature range. A new stiffness-temperature model based on Weibull statistics of the secondary bonds breaking during the relaxation transitions has been developed to quantitatively describe changes in the storage modulus with temperature and applied radiation dose until the onset of the temperature of the additional, thermally-induced polymerisation reactions. A global search real-coded genetic algorithm has been successfully applied to optimise the parameters of the developed model by minimising the sum-squared error. An excellent agreement between the modelled and experimental data has been found.
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Birley A.W., Heath R.J., Scott M.J. Plastic Materials Properties and Applications. 2nd ed. Glasgow; Blackie, NY, USA: 1988.
Ramaswamy R., Sasidharan Achary P. Adhesive Joints, Formation, Characteristics and Testing. 1st ed. Plenum Press; New York, NY, USA: 1984.
Kollek H., Brockmann H., Muller von der Haegen H. Chemistry of curing and adhesion properties of phenolic resins. Int. J. Adhes. Adhes. 1986;6:37–41. doi: 10.1016/0143-7496(86)90070-9. DOI
Parameswaran P.S. Ph.D. Thesis. Cochin University of Science and Technology; Kerala, India: 2009. Modification of Phenol Formaldehyde Resin for Improved Mechanical Properties; p. 263.
Clough R.L. High-energy radiation and polymers: A review of commercial processes and emerging applications. Nucl. Instrum. Methods Phys. Res. B. 2001;185:8–33. doi: 10.1016/S0168-583X(01)00966-1. DOI
Drobny J.G. Ionising Radiation and Polymers: Principles, Technology and Applications. 1st ed. Elsevier; Amsterdam, The Netherlands: 2013.
Kashiwagi M., Hoshi Y. Electron beam Processing System and Its Application. SEI Tech. Rev. 2012;75:47–53.
Singh P.K., Venugopal B.R., Nandini D.R. Effect of Electron Beam Irradiation on Polymers. J. Mod. Mater. 2018;5:24–33. doi: 10.21467/jmm.5.1.24-33. DOI
Juliano A., Nowacka M., Rybak K., Rzepna M. The effects of electron beam radiation on material properties and degradation of commercial PBAT/PLA blend. J. Appl. Polym. Sci. 2019;137:48462.
Rouif S. Radiation cross-linked polymers: Recent developments and new applications. Nucl. Instrum. Methods Phys. Res. B. 2005;236:68–72. doi: 10.1016/j.nimb.2005.03.252. DOI
Allen G.E. Mendel and modern genetics: The legacy for today. Endeavour. 2003;27:63–68. doi: 10.1016/S0160-9327(03)00065-6. PubMed DOI
Nilsson J. Principles of Artificial Intelligence. Springer; New York, NY, USA: 2014.
Kumar M., Hussain M., Upreti N., Gupta D. Genetic algorithm: Review and application. Int. J. Inf. Technol. Knowl. Manag. 2010;2:451–454. doi: 10.2139/ssrn.3529843. DOI
Maaranen H., Miettnen H., Penttinen A. On initial populations of a genetic algorithm for continuous optimisation problems. J. Glob. Optim. 2007;37:405–436. doi: 10.1007/s10898-006-9056-6. DOI
Schmitt L.M. Theory of genetic algorithms. Theor. Comput. Sci. 2001;259:1–61. doi: 10.1016/S0304-3975(00)00406-0. DOI
Jebari K., Madiafi M. Selection methods for genetic algorithms. Int. J. Emerg. Sci. 2013;3:333–344.
Mehta A., Sharma A. Observing the Effect of Elitism on the Performance of GA. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 2013;3:6.
Reeves C.R. Handbook of Metaheuristics. Springer; Boston, MA, USA: 2010.
<sc>U</sc>mbarkar A.J., Sheth P.D. Crossover operators in genetic algorithms: A review. ICTACT J. Soft Comput. 2015;6:1.
Kalyanmoy D., Debayan D. Analysing mutation schemes for real-parameter genetic algorithms. Int. J. Artif. Intell. Soft Comput. 2014;4:1–28.
Bhandari D., Murthy C.A., Pal S.K. Variance as a stopping criterion for genetic algorithms with elitist model. Fundam. Inform. 2012;120:145–164. doi: 10.3233/FI-2012-754. DOI
Çolak Ö.Ü., Çakir Y. Genetic Algorithm Optimisation Method for Parameter Estimation in the Modeling of Storage Modulus of Thermoplastics. Sigma J. Eng. Nat. Sci. 2019;37:981–988.
Çolak Ö.Ü., Cakir Y. Material model parameter estimation with genetic algorithm optimisation method and modeling of strain and temperature dependent behavior of epoxy resin with cooperative-VBO model. Mech. Mater. 2019;135:57–66. doi: 10.1016/j.mechmat.2019.04.023. DOI
Le V.D., Caliez M., Gratton M., Frachon A., Picart D. Mechanical characterisation of a viscous-elastic plastic material, sensitive to hydrostatic pressure and temperature. WIT Trans. Built Environ. 2006;85:211–233.
Kopal I., Vršková J., Labaj I., Ondrušová D., Hybler P., Harničárová M., Valíček J., Kušnerová M. Effect of High-Energy Ionising Radiation on the Mechanical Properties of a Melamine Resin, Phenol-Formaldehyde Resin, and Nitrile Rubber Blend. Materials. 2018;11:2405. doi: 10.3390/ma11122405. PubMed DOI PMC
Abliz D., Duan Y., Steuernagel L., Xie L., Li D., Ziegmann G. Curing Methods for Advanced Polymer Composites—A Review. Polym. Polym. Compos. 2013;21:6. doi: 10.1177/096739111302100602. DOI
Mark J. Physical Properties of Polymers. Cambridge University; Cambridge, UK: 2012.
Zhu R., Wang X., Yang J., Wang Y., Zhang Z., Hou Y., Lin F., Li Y. Influence of Hard Segments on the Thermal, Phase-Separated Morphology, Mechanical, and Biological Properties of Polycarbonate Urethanes. Appl. Sci. 2017;7:306. doi: 10.3390/app7030306. DOI
Wu H., Zhao B., Gao W. Intelligent Computing Topics on Chemical Engineering: A Graph Theory. LAMBERT Academic Publishing; Saarbrücken, Germany: 2016.
Kopal I., Vršková J., Labaj I., Harničárová M., Valíček J., Ondrušová D., Hybler P. ATR-FTIR Analysis of Melamine Resin, Phenol-Formaldehyde Resin and Acrylonitrile-Butadiene Rubber Blend Modified by High-Energy Electron Beam Radiation. In: Öchsner A., Altenbach H., editors. Engineering Design Applications III. Advanced Structured Material. Volume 124. Springer International Publishing; Cham, Switzerland: 2020. pp. 295–307.
Alneamah M., Al-Maamori M. Study of Thermal Stability of Nitrile Rubber/Polyimide Compounds. J. Mater. Chem. 2015;5:1–3.
Siimer K., Christjanson P., Kaljuvee T., Pehk T., Lasn I., Saks I. TG-DTA study of melamine-urea-formaldehyde resins. J. Therm. Anal. Calorim. 2008;92:19–27. doi: 10.1007/s10973-007-8721-4. DOI
Alonso M.V., Oliet M., García J., Rodríguez F., Echeverría J. Master Curve and Time-Temperature-Transformation Cure Diagram of Lignin-Phenolic and Phenolic Resol Resins. J. Appl. Polym. Sci. 2007;103:3362–3369. doi: 10.1002/app.25497. DOI
Sui G., Zhang Z.G., Liang Z.Y., Chen C. Dynamic mechanical studies on epoxy resins cured by electron beam radiation. Mater. Sci. Eng. A. 2003;342:28–37. doi: 10.1016/S0921-5093(02)00314-3. DOI
Gueven O. Advances in Radiation Chemistry of Polymers. IAEA; Vienna, Austria: 2004.
Pekcan Ö., Kara S. Gelation Mechanisms. Mod. Phys. Lett. B. 2012;26:27. doi: 10.1142/S0217984912300190. DOI
Sanditov D.S., Darmaev M.V., Sanditov B.D. On the Relaxation Nature of the Glass Transition of Amorphous Polymers and Low -Molecular Amorphous Materials. Phys. Solid Stat. 2015;57:1666–1672. doi: 10.1134/S1063783415080272. DOI
Wu Y., Zeng M., Xu Q., Hou S., Jin H., Fan L. Effects of glass-to-rubber transition of thermosetting resin matrix on the friction and wear properties of friction materials. Tribol. Int. 2012;54:51–57. doi: 10.1016/j.triboint.2012.05.018. DOI
Yagimli B., Lion A. Experimental investigations and material modelling of curing processes under small deformations. J. Appl. Math. Mech. 2011;91:342–359. doi: 10.1002/zamm.201000096. DOI
Kopal I., Bakošová D., Koštial P., Jančíková Z., Valíček J., Harničárová M. Weibull distribution application on temperature dependence of polyurethane storage modulus. Int. J. Mater. Res. 2016;107:472–476. doi: 10.3139/146.111359. DOI
Kopal I., Harničárová M., Valíček J., Krmela J., Lukáč L. Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems. Polymers. 2019;11:1074. doi: 10.3390/polym11061074. PubMed DOI PMC
Kopal I., Harničárová M., Valíček J., Kušnerová M. Modeling the temperature dependence of dynamic mechanical properties and visco-elastic behavior of thermoplastic polyurethane using artificial neural network. Polymers. 2017;9:519. doi: 10.3390/polym9100519. PubMed DOI PMC
Richeton J., Schlatter G., Vecchio K.S., Rémond Y., Ahzi S. Unified model for stiffness modulus of amorphous polymers across transition temperatures and strain rates. Polymer. 2005;46:8194–8201. doi: 10.1016/j.polymer.2005.06.103. DOI
Goldberg D.E. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley; Boston, MA, USA: 1989.
Haupt R.L., Haupt S.E. Practical Genetic Algorithms. Wiley; Hoboken, NJ, USA: 2004.
Marler R.T., Arora J.S. Survey of Multi-Objective Optimization Methods for Engineering. Struct. Multidiscip. Optim. 2004;26:369–395. doi: 10.1007/s00158-003-0368-6. DOI
Pavai G., Geetha T.V. A Survey on Crossover Operators. ACM Comput. Surv. 2017;49:4. doi: 10.1145/3009966. DOI
Lim S.M., Sultan A.B.M., Sulaiman M.N., Mustapha A., Leong K.Y. Crossover and Mutation Operators of Genetic Algorithms. Int. J. Mach. Learn. Comput. 2017;7:1. doi: 10.18178/ijmlc.2017.7.1.611. DOI
Gupta B. Comparative Study of Genetic Operators and Parameters for Multiprocessor Task Scheduling. Int. J. Comput. Technol. 2015;2:1.
Mahieux C.A. Ph.D. Thesis. Virginia Polytechnic Institute and State University, Faculty of Virginia Tech; Blacksburg, VA, USA: 1999. A Systematic Stiffness-Temperature Model for Polymers and Applications to the Prediction of Composite Behavior.