Advanced numerical models for predicting the load and environmentally dependent behaviour of adhesives and adhesively bonded joints

• Tipo: Capítulo ou Parte de Livro
• Data: 2019

Autores

Marques, EAS (Autor) FEUP; Akhavan Safar, A (Autor) Outra; Campilho, RDSG (Autor) Outra; Ricardo Carbas (Autor) FEUP; da Silva, LFM (Autor) FEUP

Indexação

Scopus - 7 Citações

Outras Informações

ID Authenticus: P-00R-913

DOI: 10.1007/978-3-030-30355-6_10

Abstract (EN): Adhesive bonding is a very flexible and efficient joining method which has been extensively adopted in applications where low structural weight and high mechanical performance is a required. However, the design process and strength prediction methods for bonded joints is still a topic where intensive research is being carried out, especially when taking into consideration the recent advances in adhesive formulations. Several methods, both analytical and numerical, are currently available for accurately modelling the behaviour of adhesive joints under quasi-static loads and in unaged conditions. However, experimental testing has also demonstrated that adhesives and adhesive joints exhibit a large degree of sensitivity to the cyclic loading and the environmental conditions, which can result in drastic changes to the mechanical behaviour of a joint. Such changes pose significant challenges when designing bonded structures and modelling the long-term behaviour of an adhesive joint, necessitating the development of advanced models, able to introduce a variable degree of degradation as a function of several environmental variables. This work presents a description of several cohesive zone models, able to simulate damage, by first discussing the state of the art techniques available for modelling of adhesives and adhesive joints, followed by the description of the specific approaches that can be employed for studying the behaviour under impact rates, fatigue and hygrothermal ageing. © Springer Nature Switzerland AG 2019.

Idioma: Inglês

Tipo (Avaliação Docente): Científica