Prediction of rheometric properties of compounds by using artificial neural networks
The ability of an Artificial Neural Network (ANN) to evaluate the variability of rheometric properties of rubber compounds from their formulation is presented. Because of the complexity and non-linearity of mixing processes, an exact mathematical treatment of the problem is extremely difficult, or e...
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| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
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Rubber Division of the American Chemical Society
2001
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| Acceso en línea: | Registro en Scopus DOI Handle Registro en la Biblioteca Digital |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
| LEADER | 04007caa a22004697a 4500 | ||
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| 001 | PAPER-2080 | ||
| 003 | AR-BaUEN | ||
| 005 | 20230518203125.0 | ||
| 008 | 190411s2001 xx ||||fo|||| 00| 0 eng|d | ||
| 024 | 7 | |2 scopus |a 2-s2.0-24044532056 | |
| 040 | |a Scopus |b spa |c AR-BaUEN |d AR-BaUEN | ||
| 030 | |a RCTEA | ||
| 100 | 1 | |a Schwartz, G.A. | |
| 245 | 1 | 0 | |a Prediction of rheometric properties of compounds by using artificial neural networks |
| 260 | |b Rubber Division of the American Chemical Society |c 2001 | ||
| 270 | 1 | 0 | |m Schwartz, G.A.; Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Ciudad Universitaria, Buenos Aires (1428), Argentina; email: schwartz@df.uba.ar |
| 506 | |2 openaire |e Política editorial | ||
| 504 | |a Kraus, G., (1965) Reinforcement of Elastomers, , John Wiley & Sons, New York | ||
| 504 | |a (1980) Goodyear Tech Book for the Rubber Process Industries, , Goodyear Tire & Rubber Company, Akron, Ohio | ||
| 504 | |a Cichocki, A., Unbehauen, R., (1996) Neural Networks for Optimization and Signal Processing, , John Wiley & Sons, New York | ||
| 504 | |a Hertz, J., Krogh, A., Palmer, R.G., (1990) Introduction to the Theory of Neural Computation, , Addison Wesley, Redwood City, CA | ||
| 504 | |a Ni, H., Hunkeler, D., (1997) Polymer, 38, p. 667 | ||
| 504 | |a Welsh, F.E., Emerson, R.J., (1997) Tire Technol. Int., p. 96 | ||
| 504 | |a Amraee, I.A., Teimorian, A.R., (1997) Tire Technol. Int., p. 91 | ||
| 504 | |a Derringer, G.C., (1988) Rubber Chem. Technol., 61, p. 377 | ||
| 504 | |a Box, G.E.P., Hunter, W.G., Hunter, J.S., (1978) Statistics for Experimenters, , John Wiley & Sons, New York | ||
| 504 | |a Smallwood, H., (1944) J. Appl. Phys., 15, p. 758 | ||
| 504 | |a (1948) Rubber Chem. Tech., 21, p. 667 | ||
| 504 | |a Einstein, A., (1906) Ann. Physik, 19, p. 289 | ||
| 504 | |a Einstein, A., (1911) Ann. Physik, 34, p. 1591 | ||
| 504 | |a Studebaker, M.L., (1957) Rubber Chem. Technol., 30, p. 1400 | ||
| 504 | |a Studebaker, M.L., Nabors, L.G., (1957) Rubber Age, 80, p. 837 | ||
| 520 | 3 | |a The ability of an Artificial Neural Network (ANN) to evaluate the variability of rheometric properties of rubber compounds from their formulation is presented. Because of the complexity and non-linearity of mixing processes, an exact mathematical treatment of the problem is extremely difficult, or even impossible. The use of artificial neural networks (ANNs) might be very useful to analyze these processes, since they have the ability to map nonlinear relationships without prior information about process or system models. In this work a three-layer ANN is used and the optimum parameters are determined. The results are compared with theoretical and experimental published data. The dependence of the rheometric properties as a function of compound components is also analyzed. Finally, the sensibility matrix concept is introduced. The sensibility matrix allows us to calculate the minimum expected variability, for a given compound, due to the weight tolerances of its components. |l eng | |
| 593 | |a Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Ciudad Universitaria, Buenos Aires (1428), Argentina | ||
| 773 | 0 | |d Rubber Division of the American Chemical Society, 2001 |g v. 74 |h pp. 116-123 |k n. 1 |p Rubber Chem Technol |x 00359475 |t Rubber Chemistry and Technology | |
| 856 | 4 | 1 | |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-24044532056&doi=10.5254%2f1.3547632&partnerID=40&md5=079196ad527e5db079ce74514534ec46 |y Registro en Scopus |
| 856 | 4 | 0 | |u https://doi.org/10.5254/1.3547632 |y DOI |
| 856 | 4 | 0 | |u https://hdl.handle.net/20.500.12110/paper_00359475_v74_n1_p116_Schwartz |y Handle |
| 856 | 4 | 0 | |u https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00359475_v74_n1_p116_Schwartz |y Registro en la Biblioteca Digital |
| 961 | |a paper_00359475_v74_n1_p116_Schwartz |b paper |c PE | ||
| 962 | |a info:eu-repo/semantics/article |a info:ar-repo/semantics/artículo |b info:eu-repo/semantics/publishedVersion | ||
| 999 | |c 63033 | ||