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Shape optimization of hydraulic structures: an example of an optimum design of a fish passage

EasyChair Preprint no. 322

12 pagesDate: July 4, 2018

Abstract

This paper presents a practical methodology targeting end users considering completing shape optimization studies of hydraulic structures using numerical modelling tools. The methodology starts by defining the optimization problem, as well as identifying the relevant problem constraints. Design variables in shape optimization studies are configuration of structures (such as length or spacing of groynes, orientation and layout of breakwaters, etc.) whose optimal orientation is not known a priori. The optimization problem is solved numerically using an optimization algorithm that defines, tests and evaluates a multitude of new shapes, which are internally generated and simulated using a numerical model that solves the governing equations. The developed methodology is tested on an example of an optimum design of a fish passage, where the design variables are the length and the position of slots. The objective function in the example minimizes the desired velocity between the slots, while respecting the constraints of the problem (related to how far apart the slots could ultimately be). The example problem uses the TELEMAC-2D numerical model for the solution of shallow water equations, driven by global numerical optimization algorithms (gradient-based optimizers and genetic algorithms).

Keyphrases: engineering design, hydraulic engineering, numerical model, optimization algorithm, optimization problem, shape optimization, shape optimization problem, shape optimization study

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:322,
  author = {Pat Prodanovic and Cedric Goeury and Fabrice Zaoui and Riadh Ata and Jacques Fontaine and Pablo Tassi and Yoann Audouin},
  title = {Shape optimization of hydraulic structures: an example of an optimum design of a fish passage},
  howpublished = {EasyChair Preprint no. 322},

  year = {EasyChair, 2018}}
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