Identification to rheological parameters identification of fresh cementitious suspensions

Le travail de thèse s'inscrit dans la modélisation numérique de l'écoulement des matériaux cimentaires à l'état frais couplée à un outil d'identification des paramètres. Il traite en particulier l'étape de mise en place de l'identification par analyse inverse. D'abord, une analyse de la littérature fait ressortir l'existence d'outils rhéométriques dédiés aux suspensions cimentaires ; le passage des grandeurs macroscopiques à celles locales est faite, soit par le biais de l'utilisation de géométries conventionnelles, soit au moyen de méthodes de calibration. Néanmoins, ces outils ne permettent pas de trouver une signature rhéologique unique pour une même suspension. De plus, les stratégies d'identification des paramètres relatifs aux matériaux cimentaires frais sont peu nombreuses et limitées aux données locales. Ensuite, une stratégie qui consiste à identifier les paramètres d'une loi supposée, directement à partir des mesures macroscopiques simulées (couples, vitesses de rotation imposées au mobile de cisaillement) a été développée et validée en 2D, en discutant notamment de l'efficacité des algorithmes d'optimisation testés (méthode du simplexe et algorithmes génétiques), en fonction du degré de connaissances que l'utilisateur a du matériau. Enfin, la méthode a été appliquée en 3D sur des fluides modèles supposés homogènes. Elle apparaît efficace en fluide pseudo-plastique, notamment par combinaison des algorithmes d'optimisation. Mais il reste des obstacles à lever en fluide visco-plastique, vraisemblablement liés aux outils expérimentaux plutôt qu'à la procédure d'identification elle-même.The thesis work is part of the numerical modeling of the flow of cementitious materials in the fresh state coupled with an identification procedure of the parameters. It deals in particular with the step of the development of the identification by inverse analysis. First,the literature review reveals the existence of rheometric tools dedicated to cementitious suspensions; The passage from the macroscopic quantities to the local ones is made either by the use of conventional geometries or by means of calibration methods. Nevertheless, these tools do not make it possible to find the expected single rheological signature for a given suspension. In addition, there are few studies reporting strategies for identifying constitutive parameters in the case of fresh cement-based materials and they are limited to local data. Then, a strategy consisting in identifying the parameters of a supposed law, directly on the basis of the simulated macroscopic measurements (torques, rotational speeds imposed on the shearing tool) was developed and validated in 2D, discussing in particular the efficiency Of the optimization algorithms tested (simplex method and genetic algorithms), according to the degree of knowledge that the user has of the material. Finally, the method has been applied in 3D on model fluids, assuming that they are homogeneous. The method appears effective in the case of pseudo-plastic fluid, in particular by combining both optimization algorithms used. But there remain obstacles to overcome in the case of visco-plastic fluids, probably related to the experimental tools rather than to the procedure of identification itself

Constitutive parameter identification: An application of inverse analysis to the flow of cement-based suspensions in the fresh state from synthetic data

WOS:000395847500002International audienceRheometers with specific impellers, developed to characterize the behavior of cement-based suspensions in the fresh state, are used to limit the heterogeneities induced during shearing but they make the identification of the rheological parameters less straightforward compared to conventional rheometers. This paper presents the inverse analysis method and discusses the quality of this identification procedure when applied to such materials. The procedure includes a CFD simulation based on the finite element method using a Herschel-Bulkley model. Two kinds of optimization algorithms are used: a deterministic simplex method and a stochastic genetic method. As a first step of a larger study, the procedure reported in this paper used 2D synthetic data, i.e. 2D numerically generated experimental data. Two numerical vis-coplastic materials, characterized by shear-thinning and shear-thickening, were selected and studied. The results obtained with the two algorithms are systematically compared to the known parameter solution. Three approaches corresponding to three levels of user's knowledge about the material under study are considered successively: (1) the user has no a priori knowledge about the material, (2) the user knows whether the material is shear-thinning or shear-thickening and (3) the user is able to estimate the behavior index. The time-consuming genetic method appears to be suitable when the a priori knowledge of the material is slight, whereas the simplex method gives a reliable solution in a few iterations when the level of knowledge is higher. Both algorithms encounter more difficulties with the shear-thinning material than with the shear-thickening one. In this paper, the advantage provided by the genetic method regarding the non-uniqueness of the identification procedure for real experimental data is also highlighted: this method provides a collection of satisfactory solutions among which the user can select the optimal one based on his scientific background and/or on further experimental test results