Recently, structural adhesives have become significant in the shaping of structural elements, especially in thin-walled structures, where they replace or supplement traditional connection methods. However, adhesive-bonded joints are highly susceptible to internal structural imperfections due to their application technique and the nature of the adhesive. These material inconsistencies impact the strength parameters and the mechanical behavior of the entire connection. This study proposes a simplified method for the probabilistic numerical modeling of structural imperfections in an adhesive layer. The adhesive is modeled as an uncorrelated random field with weakened elements representing structural imperfections randomly scattered throughout its entire volume. The percentage of these imperfections (in relation to the total volume) is adopted as a random variable. By conducting experimental tests on dogbone specimens of a selected adhesive and comparing them to adequate numerical tests with varying volumes of weakened elements, the determination of the representative imperfection volume of the investigated adhesive became possible. Based on these tests, the calibration of the probability density function to describe the volume of the imperfections may be performed. Furthermore, the application of the random model for an adhesive-bonded single lap joint is shown to be viable. Finally, the calculation of a probability-based mechanical response (in this case, the normal force at critical elongation) of the single lap joint with structural imperfections is performed, and its resultant reliability is assessed and evaluated.

Random field-based simulational identification of potential levels of material imperfections of adhesive-bonded joints

Eremeyev V.;
2025-01-01

Abstract

Recently, structural adhesives have become significant in the shaping of structural elements, especially in thin-walled structures, where they replace or supplement traditional connection methods. However, adhesive-bonded joints are highly susceptible to internal structural imperfections due to their application technique and the nature of the adhesive. These material inconsistencies impact the strength parameters and the mechanical behavior of the entire connection. This study proposes a simplified method for the probabilistic numerical modeling of structural imperfections in an adhesive layer. The adhesive is modeled as an uncorrelated random field with weakened elements representing structural imperfections randomly scattered throughout its entire volume. The percentage of these imperfections (in relation to the total volume) is adopted as a random variable. By conducting experimental tests on dogbone specimens of a selected adhesive and comparing them to adequate numerical tests with varying volumes of weakened elements, the determination of the representative imperfection volume of the investigated adhesive became possible. Based on these tests, the calibration of the probability density function to describe the volume of the imperfections may be performed. Furthermore, the application of the random model for an adhesive-bonded single lap joint is shown to be viable. Finally, the calculation of a probability-based mechanical response (in this case, the normal force at critical elongation) of the single lap joint with structural imperfections is performed, and its resultant reliability is assessed and evaluated.
2025
Adhesive imperfections; Adhesive-bonded joints; Probabilistic analysis; Random fields; Reliability
File in questo prodotto:
File Dimensione Formato  
BPASTS_2025_73_1_4389.pdf

accesso aperto

Tipologia: versione editoriale (VoR)
Dimensione 5.19 MB
Formato Adobe PDF
5.19 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/432985
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact