https://popups.uliege.be/esaform21/index.php?id=3602 Publications of Auteurs Miguel Guimarães Oliveira fr 0 https://popups.uliege.be/esaform21/index.php?id=2502 Nowadays, virtual predictions are essential in the design and development of new engineering parts. A critical aspect for virtual predictions is the accuracy of the constitutive model to simulate the material behavior. A state-of-the-art constitutive model generally involves a large number of parameters, and according to classical procedures, this requires many mechanical experiments for its accurate identification. Fortunately, this large number of mechanical experiments can be reduced using heterogeneous mechanical tests, which provide richer mechanical information than classical homogeneous tests. However, the test’s richness is much dependent on the specimen's geometry and can be improved with the development of new specimens. Therefore, this work aims to design a uniaxial tensile load test that presents heterogeneous strain fields using a shape optimization methodology, by controlling the specimen's interior notch shape. The optimization problem is driven by a cost function composed by several indicators of the heterogeneity present in the specimen. Results show that the specimen's heterogeneity is increased with a non-circular interior notch. The achieved virtual mechanical test originates both uniaxial tension and shear strain states in the plastic region, being the uniaxial tension strain state predominant. Tue, 23 Mar 2021 20:46:27 +0100 Tue, 30 Mar 2021 17:24:34 +0200 https://popups.uliege.be/esaform21/index.php?id=2502 https://popups.uliege.be/esaform21/index.php?id=1486 The development of full-field measurement techniques paved the way for the design of new mechanical tests. However, because these mechanical tests provide heterogeneous strain fields, no closed-form solution exists between the measured deformation fields and the constitutive parameters. Therefore, inverse identification techniques should be used to calibrate constitutive models, such as the widely known finite element model updating (FEMU) and the virtual fields method (VFM). Although these inverse identification techniques follow distinct approaches to explore full-field measurements, they all require using an optimisation technique to find the optimum set of material parameters. Nonetheless, the choice of a suitable optimisation technique lacks attention and proper research. Most studies tend to use a least-squares gradient-based optimisation technique, such as the Levenberg-Marquardt algorithm. This work analyses optimisation algorithms, gradient-based and -free algorithms, for the inverse identification of constitutive model parameters. To avoid needless implementation and take advantage of highly developed programming languages, the optimisation algorithms available in optimisation libraries are used. A FEMU based approach is considered in the calibration of a thermoelastoviscoplastic model. The material parameters governing strain hardening, temperature and strain rate are identified. Results are discussed in terms of efficiency and the robustness of the optimisation processes. Mon, 22 Mar 2021 20:01:49 +0100 Mon, 05 Apr 2021 18:00:57 +0200 https://popups.uliege.be/esaform21/index.php?id=1486