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Modeling and Optimization of Composite Brake Friction Materials Formulation

Khazaei, Ali | 2013

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 44671 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Shojaei, Akbar
  7. Abstract:
  8. Automotive brake pad is one of the most widely used composites. Commonly, more than 10 components are applied to make these materials and due to the large number of components and interactions between them, choice, explaination of the behavior and optimization of brake friction materials are some industry's challenges. Until now, some methods have been presented to design and optimization of these materials, but due to different complexities, there is lack of practical method that could be used for explaining the tribological behavior, engineering calculation and optimization of brake friction materials. Today, formulation of the current brake pads in the industry has mainly come from trial and error and empirical methods and It could be mentioned that current products are not optimal.
    Genetic programming is a relatively new method for generating empirical models. This method could generate suitable input - output models in complex and nonlinear systems. In this work, first, by performing of 31 experiments (by considering the number of experiments in the literature for achieving acceptable results for design or prediction of the behavior of brake pads), achieved data were used to model two important properties of friction materials (specific wear rate and friction coefficient). With the literature review and study different components and their roles in brake friction materials, it has tried to select more practical ingredients for different roles. 85% of the data were used to generate the models and the rest were used to evaluate that. Finally, two equations were obtained with the average absolute relative error (for specific wear rate and friction coefficient, respectively) of 1.93% and 1.92% for the training data and 2.39% and 1.42% for the testing data. In addition, after obtaining an appropriate model to predict the behavior of brake pads and analyzing the models, achieving models beside a formulation cost function, applied to multi objective optimization of the formulation with using non-dominated sorting genetic algorithm II (NSGA II) method. This optimization offers some formulations with minimum specific wear rate and maximum friction coefficient in different cost levels. The proposed method could solve the problem of lacking good modeling and optimization method in the friction materials filed
  9. Keywords:
  10. Frictional Material ; Modeling ; Optimization ; Genetic Algorithm ; Formulation ; Genetic Programming

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