Study on mechanical properties and antifriction of calcium powder filled rubber

2021 ◽  
Author(s):  
Deshang Han ◽  
Gang Yan ◽  
Shaoming Li ◽  
Yi Pan ◽  
Yihui Chen ◽  
...  

2010 ◽  
Vol 31 (3) ◽  
pp. 263-268 ◽  
Author(s):  
H. Montes ◽  
T. Chaussée ◽  
A. Papon ◽  
F. Lequeux ◽  
L. Guy


1972 ◽  
Vol 4 (4-6) ◽  
pp. 534-537
Author(s):  
S. K. Ordzhonikidze ◽  
A. D. Margolin ◽  
P. F. Pokhil


1996 ◽  
Vol 69 (1) ◽  
pp. 15-47 ◽  
Author(s):  
J. D. Ulmer

Abstract The strain dependencies of dynamic mechanical properties of carbon black-filled rubber compounds have been modeled by Kraus. Evaluation of the Kraus model with carbon black loadings up to 110 phr shows that it provides a fairly good overall description of elastic modulus, G′, as a function of strain, γ. The model description of G′ strain dependence improves with decreased carbon black loading, and is very good with carbon black loadings of 50 phr and less. The model description of viscous modulus strain dependence, G″(γ), is less successful than the G′(γ) description. Several empirical modifications of the viscous modulus model are examined. The most improved model is a very good approximation to viscous modulus over a wide experimental strain-range. Its utility, and that of the Kraus G′(γ) model, are illustrated through calculation of simple shear dynamic properties from torsion property measurements on a solid cylinder, where the strain amplitude varies across the specimen radius. The models allow transformation of the apparent moduli, reported as functions of strain amplitude at the cylinder's outer edge, to their true counterparts, G′(γ) and G″(γ), as functions of uniform strain amplitude. Although the G′(γ) and modified G″(γ) models apply to a wide range of experimental strains, some uncertainties associated with each model's accuracy remain, and there are inconsistencies in the relation of one model to the other. Reservations associated with the models might be resolved through refined treatments of the test specimen geometries.



2003 ◽  
Vol 76 (1) ◽  
pp. 145-159 ◽  
Author(s):  
Laurence Ladouce-Stelandre ◽  
Yves Bomal ◽  
Lionel Flandin ◽  
Dominique Labarre

Abstract Composites that incorporate precipitated silica into a vulcanized rubber were investigated for dynamic mechanical properties. Comparing different types of filler, it was found that the mean distance between particles did not alter Payne effect. On the contrary, the amount and morphology of the fillers played a major role on the macroscopic properties. The nature and amount of coupling or covering agents was also found to be an important parameter. A direct relationship between length and efficiency of interface agents was evidenced: longer silanes were more effective than shorter once independently from a covalent bounding to rubber. The set of studied parameters affecting Payne effect can be reduced to only two independents variables: the total amount of silica-rubber interface (a function of the amount of filler and its BET surface) and the quantity and nature of interface agent. From these data an attempt to relate the rubber to filler cohesion to Payne effect is proposed as well as a molecular mechanism derived from Maier and Göritz model. A mathematical treatment of the proposed mechanisms is currently being investigated that might help giving further insights on novel ways to further reduce Payne effect.



Polymers ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2683
Author(s):  
Takashi Kojima ◽  
Takashi Washio ◽  
Satoshi Hara ◽  
Masataka Koishi ◽  
Naoya Amino

A better understanding of the microstructure–property relationship can be achieved by sampling and analyzing a microstructure leading to a desired material property. During the simulation of filled rubber, this approach includes extracting common aggregates from a complex filler morphology consisting of hundreds of filler particles. However, a method for extracting a core structure that determines the rubber mechanical properties has not been established yet. In this study, we analyzed complex filler morphologies that generated extremely high stress using two machine learning techniques. First, filler morphology was quantified by persistent homology and then vectorized using persistence image as the input data. After that, a binary classification model involving logistic regression analysis was developed by training a dataset consisting of the vectorized morphology and stress-based class. The filler aggregates contributing to the desired mechanical properties were extracted based on the trained regression coefficients. Second, a convolutional neural network was employed to establish a classification model by training a dataset containing the imaged filler morphology and class. The aggregates strongly contributing to stress generation were extracted by a kernel. The aggregates extracted by both models were compared, and their shapes and distributions producing high stress levels were discussed. Finally, we confirmed the effects of the extracted aggregates on the mechanical property, namely the validity of the proposed method for extracting stress-contributing fillers, by performing coarse-grained molecular dynamics simulations.



2013 ◽  
Vol 48 (2) ◽  
pp. 114-124 ◽  
Author(s):  
Dong-Wook Kim ◽  
Chang-Hwan Kim ◽  
Ho-Kyun Jung ◽  
Yong-Gu Kang


Polymer ◽  
2001 ◽  
Vol 42 (23) ◽  
pp. 9523-9529 ◽  
Author(s):  
Fumito Yatsuyanagi ◽  
Nozomu Suzuki ◽  
Masayoshi Ito ◽  
Hiroyuki Kaidou




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