Development of a model to predict the mechanical properties of adhesives based on the formulation

300 Pages·2015·7.85 MB·English

THESIS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

Development of a model to predict the mechanical
properties of adhesives based on the formulation

by

Rosa Maria Moreira de Paiva

Supervisor:

Lucas Filipe Martins da Silva

DEMec, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto,
Portugal

Co-Supervisor:

Carlos Alberto Conceição António

DEMec, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto,
Portugal

May, 2015
© Rosa Maria Moreira de Paiva
Departamento de Engenharia Mecânica
Faculdade de Engenharia da Universidade do Porto

Rua Dr. Roberto Frias
4200-465 Porto
Portugal
ABSTRACT

In order to contribute to the development of research in the field of adhesives
for the footwear industry, this study aimed to develop mixed numerical-
experimental models aiming to predict and optimize the mechanical properties
of adhesives using their weight compositions as design variables.
In this work polyurethane solvent based adhesives were considered. The
characteristics and properties that polyurethane polymers, resins and additives
confer to the adhesive were determined. For evaluation and control of the
resultant mechanical properties, the most common tests used by the footwear
industry were performed. These are the peel strength and the creep rate.
In the literature, it’s possible to find several works based on adhesives,
specifically about their composition. However, there are no studies regarding
the mathematical models to optimize polyurethane solvent based adhesive
formulations.
In this type of adhesives, it is necessary to take into consideration that there are
factors which determine the efficiency of the adhesive joints, such as the type of
substrates that are to be bonded and the surface treatment. Thus, for the
implementation of this work, the following materials were considered: natural
leather for the upper, polyurethane (PU) and thermoplastic rubber (TR) for the
soles. Chemical and physical treatments were applied, such as halogenation
and mechanical carding, respectively.
Therefore, the design variables were the constituent materials of the formulation
of the polyurethane solvent based adhesive. The single-objective or the multi-
objective optimization techniques were applied aiming to determine optimal
adhesive formulations, improving in these ways the efficiency of the adhesive
joints. The models were built using Genetic Algorithms supported by Artificial
Neural Networks and Global Sensitivity Analysis concepts.

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From this research it was concluded that it is possible to build mixed numerical-
experimental models aiming to predict and optimize the mechanical properties
of adhesive joints. The models show robustness and capability to solve a wide
variety of problems in footwear industry.

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RESUMO

No sentido de contribuir para o desenvolvimento da investigação na área dos
adesivos para a indústria do calçado, este trabalho teve como objectivo a
determinação de modelos híbridos numéricos e experimentais capazes de
prever e optimizar as propriedades mecânicas das juntas adesivas usando as
composições dos constituintes como variáveis de projecto.
Neste trabalho foram considerados adesivos de poliuretano de base solvente,
sendo determinadas experimentalmente as características e influências que os
polímeros de poliuretano, resinas e aditivos conferem ao produto adesivo. Na
indústria do calçado, as propriedades mecânicas controladas são a resistência
ao arrancamento e a resistência à temperatura. Deste modo, foram aplicadas
como técnicas a força de arrancamento e a taxa de fluência.
Na literatura, é possível encontrar vários trabalhos sobre adesivos, mais
concretamente sobre a sua composição. No entanto, não existem pesquisas no
que se refere a modelos matemáticos capazes de optimizar formulações de
adesivos de poliuretano à base de solvente.
Neste tipo de adesivos, há que ter em conta a existência de factores que
determinam a eficiência das juntas adesivas, como é o caso do tipo de
substratos que se pretendem colar e os tratamentos de superfície necessários
para a obtenção da junta adesiva ideal. Assim sendo, para a execução deste
trabalho, foram considerados os materiais seguintes: pele natural, solas de
poliuretano (PU) e solas de borracha termoplástica (TR). Foram aplicados
tratamentos químicos e físicos, nomeadamente a halogenação e a cardagem
mecânica.
Deste modo, as variáveis de projecto foram as matérias-primas constituintes da
formulação do adesivo de poliuretano à base de solvente. As técnicas de
optimização com um único objectivo ou com multi-objectivos foram aplicadas
com o intuito de determinar formulações óptimas, melhorando desta forma a
eficiência das juntas adesivas. Os modelos foram construídos usando

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Algoritmos Genéticos apoiados por conceitos de redes neurais artificiais e de
análise global de sensibilidade.
A partir desta investigação concluiu-se que é possível construir modelos
híbridos numéricos e experimentais com o objectivo de prever e optimizar as
propriedades mecânicas de juntas adesivas. Os modelos mostram robustez e
capacidade para resolver uma ampla variedade de problemas na indústria do
calçado.

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ACKNOWLEDGEMENTS

I would like to express my sincere gratitude to my supervisor Prof. Lucas FM.
da Silva for his intellectual and academic support, for believing in my project
and for giving me the opportunity to work under his supervision, which made my
idea a reality.
A special thanks to my co-supervisor Prof. Carlos A.C. António for the
involvement in my work and for sharing his knowledge with me about the
optimization using Artificial Neuronal Network (ANN) and Genetic Algorithm
(GA) in Fortran.
I would like to thank to all my colleagues at ADFEUP group, Ricardo Carbas,
Mariana Banea, Ana Queirós, Filipe Chaves for the friendship and for
interesting discussions about adhesives. A special thanks to Eduardo Marques
for the contributions made to this work.
During my work in FEUP, I had the support of the company CIPADE –
Indústria e Investigação e Desenvolvimento de Produtos Adesivos, S.A.
where I work since 2003; I want to acknowledge them because they understood
my efforts and choices in these three years.
I would like to thank to my friends and colleagues for their friendship and moral
support.
Finally, I would like to thank to my family, especially my daughter that was born
during this project, for their unconditional love, patience and support, that made
possible the realization of this work.

This thesis is dedicated to the memory of my brother (Marco Paiva).

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CONTENTS

LIST OF PUBLICATIONS …………………………………………….……………. ix
GLOSSARY ………………………………………………………………………….xi
SUMMARY OF THESIS ………………………………………………...………….. 1
1. INTRODUCTION ………………………………………………………..…….… 1
1.1. Motivation ………………………………………………….…. 1
1.2. Problem Definition……………………………………………. 1
1.3. Objective …………………………………………………….... 2
1.4. Research methodology ……………………………………... 2
1.5. Outline of the thesis …………………………………………. 5
2. ADHESIVES TESTED …………………………………….………………….. 11
3. EXPERIMENTAL TESTS …………….………………….…………………... 13
3.1. Peel strength ………………………….….………………… 13
3.2. Creep rate …………………………….….…………………. 14
4. NUMERICAL MODELING …………………………….…….………………… 15
4.1. Artificial Neuronal Network (ANN) .…….…………………. 16
4.2. Sensitivity Analysis (SA) ………….…….…………………. 17
5. OPTIMIZATION FRAMEWORK …………………….……….………….….... 18
5.1. Single-objective Optimization …..………….……………… 20
5.2. Multi-objective Optimization …..…………………………... 23
6. CONCLUSIONS …………………………………..…………………………… 25
7. FUTURE WORK ………………………………..……………………………… 26
REFERENCES ……………………………………………………………………... 27
APPENDED PAPERS ……………………………………………………………... 31
PAPER 1 …………………………………………………………………..... 33

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PAPER 2 …………………………………………………………………….. 81
PAPER 3 …………………………………………………………………... 107
PAPER 4 …………………………………………………………………... 137
PAPER 5 …………………………………………………………………... 165
PAPER 6 …………………………………………………………………... 199
PAPER 7 …………………………………………………………………... 237

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