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Discrete material optimization with sandwich failure constraints

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F21%3APU141384" target="_blank" >RIV/00216305:26210/21:PU141384 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/content/pdf/10.1007/s00158-021-03006-x.pdf" target="_blank" >https://link.springer.com/content/pdf/10.1007/s00158-021-03006-x.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s00158-021-03006-x" target="_blank" >10.1007/s00158-021-03006-x</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Discrete material optimization with sandwich failure constraints

  • Original language description

    Discrete material optimization (DMO) is a method, which was originally developed for designing composite structures via multi-material topology optimization principles. Current study applies DMO to sandwich structures with variable thickness in the core and face sheets. Each layer contains design variables for available materials. Materials are combined through interpolation schemes to define properties of the layer. The objective function (mass of the structure) and the failure constraints are interpolated via Rational Approximation of Material Properties (RAMP) in order to calculate with smooth variables, but achieve discrete results. This enables gradient optimization via Interior Point Optimizer (IPOPT) with constraints on maximum stress, wrinkling, and crimping. Structure is modeled by the finite element method, which calculates element forces and moments repeatedly as the stiffness of the structure changes during optimization. Element loads are used by the first-order shear deformation theory to evaluate the stresses in the layers to obtain failure constraints requested in each iteration by the gradient optimizer. Solution is demonstrated on the plate examples showing material distribution and discreteness level. In addition, constraint aggregation by Kreisselmeier-Steinhauser (KS) function was utilized to decrease the number of constraints in the optimization.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION

  • ISSN

    1615-147X

  • e-ISSN

    1615-1488

  • Volume of the periodical

    64

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    11

  • Pages from-to

    2513-2523

  • UT code for WoS article

    000673035000001

  • EID of the result in the Scopus database

    2-s2.0-85110450020