R. Le Riche

Bio: R. Le Riche is an academic researcher from Mines ParisTech. The author has contributed to research in topics: Engineering optimization & System identification. The author has an hindex of 12, co-authored 19 publications receiving 720 citations. Previous affiliations of R. Le Riche include Mines Saint-Etienne & École Normale Supérieure.

A constrained, globalized, and bounded Nelder–Mead method for engineering optimization

Abstract: One of the fundamental difficulties in engineering design is the multiplicity of local solutions. This has triggered much effort in the development of global search algorithms. Globality, however, often has a prohibitively high numerical cost for real problems. A fixed cost local search, which sequentially becomes global, is developed in this work. Globalization is achieved by probabilistic restarts. A spacial probability of starting a local search is built based on past searches. An improved Nelder–Mead algorithm is the local optimizer. It accounts for variable bounds and nonlinear inequality constraints. It is additionally made more robust by reinitializing degenerated simplexes. The resulting method, called the Globalized Bounded Nelder–Mead (GBNM) algorithm, is particularly adapted to tackling multimodal, discontinuous, constrained optimization problems, for which it is uncertain that a global optimization can be afforded. Numerical experiments are given on two analytical test functions and two composite laminate design problems. The GBNM method compares favorably with an evolutionary algorithm, both in terms of numerical cost and accuracy.

Identification of the four orthotropic plate stiffnesses using a single open-hole tensile test

Abstract: The identification of mechanical parameters for real structures is still a challenge. With the improvement of optical full-field measurement techniques, it has become easier, but in spite of many publications showing the feasibility of such methods, experimental results are still scarce. In this paper we present a first step towards a global approach of mechanical identification for composite materials. The chosen mechanical test is an open-hole tensile test according to standard recommendations. For the moment, experimental data are provided by a moire interferometry setup. The global principle of the identification developed in this paper is to minimize a discrepancy between experimental and theoretical results, expressed as a cost function, using a Levenberg-Marquardt algorithm. This approach has the advantage of having high adaptability, largely because the optical system, the signal processing as well as the mechanical aspects, can be taken into consideration by the model. In this paper we consider different types of cost functions, which are tested using an identifiability criterion. Although mechanically based cost functions have been studied, a simpler mathematical form is finally more efficient. Two different models were tested. The first is an analytical model based on the Lekhnitskii approach. This approach has the advantage of being a meshless solution; however, the results appeared to be partially false due to boundary effects, leading to a second approach, a classical finite element analysis. The resulting identified values are similar to values from classical mechanical tests (within 6%). which, in practice, validates our approach.

Bayesian Identification of Elastic Constants in Multi-Directional Laminate from Moiré Interferometry Displacement Fields

Abstract: The ply elastic constants needed for classical lamination theory analysis of multi-directional laminates may differ from those obtained from unidirectional laminates because of three dimensional effects. In addition, the unidirectional laminates may not be available for testing. In such cases, full-field displacement measurements offer the potential of identifying several material properties simultaneously. For that, it is desirable to create complex displacement fields that are strongly influenced by all the elastic constants. In this work, we explore the potential of using a laminated plate with an open-hole under traction loading to achieve that and identify all four ply elastic constants (E 1 , E 2 , ν 12 , G 12 ) at once. However, the accuracy of the identified properties may not be as good as properties measured from individual tests due to the complexity of the experiment, the relative insensitivity of the measured quantities to some of the properties and the various possible sources of uncertainty. It is thus important to quantify the uncertainty (or confidence) with which these properties are identified. Here, Bayesian identification is used for this purpose, because it can readily model all the uncertainties in the analysis and measurements, and because it provides the full coupled probability distribution of the identified material properties. In addition, it offers the potential to combine properties identified based on substantially different experiments. The full-field measurement is obtained by moire interferometry. For computational efficiency the Bayesian approach was applied to a proper orthogonal decomposition (POD) of the displacement fields. The analysis showed that the four orthotropic elastic constants are determined with quite different confidence levels as well as with significant correlation. Comparison with manufacturing specifications showed substantial difference in one constant, and this conclusion agreed with earlier measurement of that constant by a traditional four-point bending test. It is possible that the POD approach did not take full advantage of the copious data provided by the full field measurements, and for that reason that data is provided for others to use (as on line material attached to the article).

Overview of Identification Methods of Mechanical Parameters Based on Full-field Measurements

Abstract: This article reviews recently developed methods for constitutive parameter identification based on kinematic full-field measurements, namely the finite element model updating method (FEMU), the constitutive equation gap method (CEGM), the virtual fields method (VFM), the equilibrium gap method (EGM) and the reciprocity gap method (RGM) Their formulation and underlying principles are presented and discussed These identification techniques are then applied to full-field experimental data obtained on four different experiments, namely (i) a tensile test, (ii) the Brazilian test, (iii) a shear-flexural test, and (iv) a biaxial test Test (iv) features a non-uniform damage field, and hence non-uniform equivalent elastic properties, while tests (i), (ii) and (iii) deal with the identification of uniform anisotropic elastic properties Tests (ii), (iii) and (iv) involve non-uniform strain fields in the region of interest

Particle swarm optimization

Abstract: Gerhard Venter (gventer_vrand.conl) *Vanderpla(ds Research and Development, bit.1767 S 8th St'reef. Suite 100, Colorado Springs. CO 80906Jaroslaw Sobieszczanski-Sobieski (j.sobieski:_larc.nasa.gov) *A_4SA Lcmgley Research Ce,_terMS 240, Hampton, I:4 23681-2199The purpose of this paper is to show how the search algorithm, known as par-ticle swarm optimization performs. Here, particle swarm optimization ks appliedto structural design problems, but the method.has a much wider range of possi-ble applications. The paper's new contributions are improvements to the particleswarm optimization algorithm and conclusions and recommendations as to theutility of the algorithm. Results of numerical experiments for both continuousand discrete applications are presented in the paper. The results indicate that theparticle swarm optimization algorithm does locate the constrained minimum de-sign in continuous applications with very good precision, albeit at a much highercomputational cost than that of a typical gradient based optimizer. However, thetrue potential of particle swarm optimization is primarily in applications withdiscrete and/or discontinuous functions and variables. Additionally, particleswarm optimization has the potential of e3_icient computation with very largenumbers of concurrently operating processors.