Journées de l'optimisation 2018

HEC Montréal, Québec, Canada, 7 — 9 mai 2018

Horaire Auteurs Mon horaire

WA4 Blackbox and derivative-free optimization IV - Applications

9 mai 2018 10h30 – 12h10

Salle: Hélène Desmarais (48)

Présidée par Aimen Gheribi

3 présentations

  • 10h30 - 10h55

    Surrogate-assisted optimization of model-designed cancer nanotherapy

    • Ibrahim Chamseddine, prés., McGill University
    • Hermann Frieboes, University of Louisville
    • Michael Kokkolaras, McGill University

    Optimization is applied to the design of drug-carrying nanoparticles targeting cancerous tumors. The required model for analysis is computationally expensive. Therefore, a surrogate-assisted approach and the MADS algorithm are used to obtain optimizers of nanoparticle-mediated treatment efficacy. This work provides a quantitative tool to support decisions relevant to precision medicine.

  • 10h55 - 11h20

    Extracting constitutive mechanical parameters in linear elasticity using the virtual fields method within the ordinary state-based peridynamics framework

    • Patrick Diehl, prés., Ecole Polytechnique
    • Rolland Delorme, Ecole Polytechnique Montreal
    • Martin Lévesque, Polytechnique Montréal

    The extraction of material parameters from experimental data is important in experimental mechanics to characterize the material's properties. We briefly introduce the virtual fields method within the ordinary state-based peridynamics framework, which is utilized to define a minimization problem to identify the material parameters. The solution for the minimization problem is obtained by the NOMAD black-box solver. As an application the extraction of material parameters out of 3-point bending experiment is shown. The influence of the usage of experimental data, like noise in the measured data or missing data, on the minimization process is discussed.

  • 11h20 - 11h45

    Determination of optimal compositions and properties for phase change materials. Case study: Solar electric generating station IX

    • Aimen Gheribi, prés., École Polytechnique de Montréal

    Thermal energy storage (TES) is becoming a key technology for the implementation of renewable energies in buildings and in industry, and also in increasing energy eciency of our systems. Moreover, TES will clearly contribute in the decrease of CO2 emissions and climate change mitigation. However, TES systems need a good material selection. Moreover, available materials for TES applications need to be improved and enhanced. Latent heat storage materials also known as phase change materials (PCMs), for which the basic principle is to store the energy through changes of states, oer the most promising technique to store the solar energy. The design of a new PCM consists, above all, in nding, within a more or less broad range of temperature, the specific compositions of local minima on the liquidus surface, i.e. eutectic point or azeotrope-like extrema. Then performance properties are compared in order to select optimal, or at least satisfactory mixtures as possible PCM candidates. However, up
    to now, PCMs design is not really ecient due to the lack of available data for both phase equlibria data, in particular the composition of the singular points upon the liquidus surface (i.e eutectic point or simple minima), and thermophysical properties required to evaluate the materials performance. In this paper we present an efficient tool specically developed for PCM design. This tool can identify the composition of singular points upon the liquidus surface and the material performance, at both the liquid and solid state.