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Published in: Engineering with Computers 2/2020

29-01-2019 | Original Article

A multi-objective sequential method for manufacturing cost and structural optimization of modular steel towers

Authors: Paolo Cicconi, Vincenzo Castorani, Michele Germani, Marco Mandolini, Alessio Vita

Published in: Engineering with Computers | Issue 2/2020

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Abstract

This paper proposes a methodological approach for the multi-objective optimization of steel towers made from prefabricated cylindrical stacks that are typically used in the oil and gas sector. The goal is to support engineers in designing economical products while meeting structural requirements. The multi-objective optimization approach involves the minimization of the weights and costs related to the manufacturing and assembly phases. The method is based on three optimization levels. The first is used in the preliminary design phase when a company receives a request for proposal. Here, minimal information on the order is available, and the time available to formulate an offer is limited. Thus, parametric cost models and simplified 1-D geometries are used in the optimization loop performed by genetic algorithms. The second phase, the embodiment design phase, starts when an offer becomes an order based on the results of the first stage. Simplified shell geometries and advanced parametric cost models are used in the optimization loop, which present a restricted problem domain. In the last phase involving detailed design, a full 3-D computer-aided design model is generated, and specific finite-element method simulations are performed. The cost estimations, given the high levels of detail considered, are analytic and are performed using dedicated software.

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Metadata
Title
A multi-objective sequential method for manufacturing cost and structural optimization of modular steel towers
Authors
Paolo Cicconi
Vincenzo Castorani
Michele Germani
Marco Mandolini
Alessio Vita
Publication date
29-01-2019
Publisher
Springer London
Published in
Engineering with Computers / Issue 2/2020
Print ISSN: 0177-0667
Electronic ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-019-00709-0

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