Surface roughness is critical for bonding applications, as it directly influences the mechanisms occurring at the adhesive interface. Abrasive Waterjet texturing has emerged as a promising technique for functionalizing surfaces, but predicting the surface characteristics from stochastic impact-based processes remains a challenge. This study aimed to develop a numerical model capable of forecasting key morphological parameters for AWJ-textured surfaces with pilotable treatment coverage. The proposed model was optimized through theoretical analysis and confronted to topographical data from polymer samples treated with low-density AWJ using standard parameters. Profilometry measurements were supported by a custom post-treatment algorithm to remove artefacts and assess the characteristics of individual particle impacts (number, repartition, dimensions). The predicted roughness showed a 94% concordance to the measured values.

Adhesive bonding modelling is often realised using cohesive zone models (CZM). For pure mode I loading, these laws represent the cohesive stress versus the interface displacement evolution designated as traction-separation laws (TSL). They enable the description of the interface irreversible phenomena such as damage and/or plasticity, while permitting a refined evaluation of the cohesive stress along the overlap. However, these laws are usually chosen a priori. For brittle and ductile adhesives the TSL shapes usually chosen are, respectively, bilinear softening and elasto-plastic. But the development of direct CZM measurements has highlighted that the law shapes can be more complex. The wrong initial choice of the TSL shape can then have an impact on the simulation results reliability. In this article, several methods used to evaluate CZM parameters are compared in terms of TSL shape robustness. Synthetic noisy data generated from a trapezoidal CZM are used for the inverse identification of a bilinear softening TSL. By applying this procedure on different types of synthetic measurements (respectively, Force-displacement, J-integral, backface strain and DIC) the ability of these techniques to capture parameters for a chosen CZM shape that is not the right one enables a rigorous evaluation the robustness to the law shape.

Il existe de nombreuses methodes pour determiner les modeles de zone cohesives en mode I. Une de ces methodes consiste a realiser une optimisation inverse sur les donnees d’essais mesurees en presupposant une forme de loi de traction-separation. Classiquement, elle est choisie de forme bilineaire. Cependant, en raison du developpement des techniques de mesure avec notamment la correlation d’image numerique ou le placement de jauges de mesures resistives, differents types de reponses mecaniques peuvent etre obtenus. Il apparait alors possible que l’estimation des parametres depende de la reponse mecanique choisie. Une revue des differentes methodes de mesures utilisees lors d’essais DCB en mode I a donc ete realisee. Cette etude a permis de mettre en evidence que les plus utilisees sont la courbe force-deplacement, l’integrale J, les jauges (backface strain) et l’analyse de la fleche et rotation des substrats. Un modele analytique a ensuite ete mis en place afin de simuler leurs sensibilites aux parametres du modele de zone cohesive. Cette etude permet de mettre en evidence l’influence des parametres de la loi de traction-separation. Ces resultats sont ensuite nuances par une analyse des contraintes experimentales et theoriques de ces methodes.

Adhesive bondline mechanical behaviour is frequently described with cohesive zone models (CZM). For mode I loading condition these phenomenological laws simply represent the evolution of the peel stress as a function of the two adherends relative displacement normal to the joint. Generally, these laws are identified rather than really measured using experimental data obtained from crack initiation and propagation experiments such as the Double Cantilever Beam Test (DCB). The uncertainty on parameter estimation are generally not indicated, as for a DCB test it is only the critical energy release rate that has the most influence on the results. However, the uncertainties on the other parameters prevent the use of the identified TSL for other mechanical tests where mode I solicitations are predominant. In this article, the purpose is to evaluate the methodologies reliability for the assessment of mode I CZM. To do so, several methods used to evaluate CZM parameters are compared in terms parameter estimation reliability. Synthetic noisy data are considered for a χ² function minimisation. Then, sensitivity calculations are performed to determine the estimated parameters standard deviation. By applying this procedure on different type of synthetic measurements (respectively P(Δ), J(δ,θ), backface strain and DIC) the ability of these different techniques to capture the best parameters for a chosen CZM shape can be rigorously evaluated.

Adhesive bonding is usually modelled using cohesive zone models (CZM) which are defined by traction-separation (TS) law. For mode I loading condition these phenomenological laws simply represent the evolution of the peel stress as a function of the two adherends relative displacement normal to the joint. However, TS law shape is often empirically chosen rather than being measured. The uncertainty on parameter estimation is generally not indicated even though it strongly influences the reliability of the bonded joint strength prediction. Moreover there are several mechanical data that can be obtained experimentally from crack initiation and propagation experiments on a Double Cantilever Beam Test (DCB). In general, TS parameters are chosen from load-displacement curves, which is the most straightforward mechanical response to obtain. However, the development of digital image correlation has enabled to access more numerous data, such as adherends’ deflection and rotation along the overlap and at loading point. The latter can be directly used to obtain the J integral. Adherends’ deformation can also be measured through the use of resistive strain gauges. Therefore, these different identification methods need to be compared in terms of parameter estimation confidence intervals. To do so, a numerical test campaign has been carried out for each mechanical response (i.e. load-displacement, J integral, and strain measurement) a synthetic noise is added to the nominal response in order to artificially represent measurement data. The noisy response is then used for the identification of the parameters using a nonlinear least square minimization. Once the data are fitted, the parameters sensitivity and confidence intervals can then be established enabling the rigorous evaluation of these different techniques to capture the best parameters for a chosen CZM shape.

Structural adhesive bonding importance has been growing steadily in the last decades as transport sector’s current problematic is to there products’ reduce mass. In addition, compared to riveting and welding, adhesive bonding offers better properties when joining dissimilar materials such as metals and composites which are a pair used more and more frequently. However, adhesive bonding suffers great-ly from a lack of confidence from industries as validating the bond quality need either destructive testing or long and costly nondestructive testing. Both these solutions can hardly be implemented at an industrial level. Nevertheless, with the implementation of robotics it is possible to auto-mate and control the entire bonding processes. In this con-text a collaborative project called S3PAC (Systeme de Supervision et de Simulation de la Production d’Assemblage par Collage) has been launched in order to offer a fully supervised and automated industrial bonding process.