Structural optimization with several discrete design variables per part by outer approximation

Stolpe, Mathias; Sandal, Kasper

doi:10.1007/s00158-018-1941-3

Cited by 15 publications

(11 citation statements)

References 38 publications

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“…Other optimization approaches using meta-heuristic algorithms were reported by AlHamaydeh et al (2017) and Kaveh and Sabeti (2018), however, without realistic load assumptions. The problem of discrete design variables was addressed by Stolpe and Sandal (2018). All mentioned works represent tube sizing algorithms applied to the OC4 jacket substructure 2 (Popko et al, 2014) for the National Renewable Energy Laboratory (NREL) 5 MW reference turbine (Jonkman et al, 2009), where the initial structural topology is maintained even in case of strong tube diameter and wall thickness variations.…”

Section: Introductionmentioning

confidence: 99%

A comparison study on jacket substructures for offshore wind turbines based on optimization

Häfele¹,

Gebhardt²,

Rolfes³

2018

Preprint

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Abstract. The structural optimization problem of jacket substructures for offshore wind turbines is commonly considered as a pure tube dimensioning problem with given topology, minimizing the entire mass of the structure. However, this approach goes along with the assumption that the given topology is fixed in any case. The present work contributes to the improvement of the state of the art by utilizing more detailed models for geometry, costs, and structural design code checks. They are assembled in an optimization scheme, in order to consider the jacket optimization problem from a different point of view 5 that is closer to practical applications. The objective function is replaced by a sum term comprising several cost terms. To address the issue of high demand of numerical capacity, a machine learning approach based on Gaussian process regression is applied to reduce numerical cost and enhance the number of considered design load cases. The proposed approach is meant to provide decision guidance in the first phase of wind farm planning. A numerical example for a NREL 5 MW turbine under FINO3 environmental conditions is computed by two effective optimization methods (sequential quadratic programming and 10 an interior-point method), allowing for the estimation of characteristic design variables of a jacket substructure. In order to resolve the mixed-integer problem formulation, multiple subproblems with fixed integer design variables are solved. The approach shows reasonable and promising results, useful both for further research and technical applications.

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Section: Introductionmentioning

confidence: 99%

A comparison study on jacket substructures for offshore wind turbines based on optimization

Häfele¹,

Gebhardt²,

Rolfes³

2018

Preprint

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“…The structural optimization design is used to obtain the optimal structure of the gantry machine under the constraint conditions of stiffness, strength, vibration resistance, and so on and realize the optimal performance objectives such as lightweight structure and minimum stress concentration (Stolpe and Sandal, 2018), which can be described as follows.…”

Section: Lightweight Structural Optimization Design Methods For Gantrymentioning

confidence: 99%

Study on lightweight structural optimization design system for gantry machine tool

Liu

Mao

2019

Concurrent Engineering

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In order to improve the efficiency and effectiveness of the lightweight design of the gantry machine tool, a lightweight structural optimization design system for the gantry machine tool was constructed. Serialized gantry machine tools were parametrically modeled, and a load model with multiple operating conditions was established. A twice optimization design method integrating zero-order optimization, parameter rounding, and structural re-optimization was proposed. Using the proposed method, a lightweight structural optimization design system for gantry machine tool with parametric design, lightweight design, and other functions was developed. The developed gantry machine tool lightweight structural optimization design system was applied to complete the lightweight structural optimization design of gantry frame of a certain gantry machine tool, so the structural parameters of the gantry frame were optimized. Although the maximum stress and the maximum deformation of the gantry frame increases within the allowable range, the experimental comparison before and after the optimization shows that the mass of the whole gantry frame is reduced by 9.24%, which is beneficial to save the manufacturing cost. The research results show that the constructed lightweight structural optimization design system of the gantry machine tool has high engineering practicality.

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“…Other optimization approaches using meta-heuristic algorithms were reported by AlHamaydeh et al (2017) and Kaveh and Sabeti (2018) but without comprehensive load assumptions. The problem of discrete design variables was addressed by Stolpe and Sandal (2018). Oest et al (2018) presented a jacket optimization study, where different simulation codes were deployed to perform structural code checks.…”

Section: Introductionmentioning

confidence: 99%

A comparison study on jacket substructures for offshore wind turbines based on optimization

2019

View full text Add to dashboard Cite

Abstract. The structural optimization problem of jacket substructures for offshore wind turbines is commonly regarded as a pure tube dimensioning problem, minimizing the entire mass of the structure. However, this approach goes along with the assumption that the given topology is fixed in any case. The present work contributes to the improvement of the state of the art by utilizing more detailed models for geometry, costs, and structural design code checks. They are assembled in an optimization scheme, in order to consider the jacket optimization problem from a different point of view that is closer to practical applications. The conventional mass objective function is replaced by a sum of various terms related to the cost of the structure. To address the issue of high demand of numerical capacity, a machine learning approach based on Gaussian process regression is applied to reduce numerical expenses and enhance the number of considered design load cases. The proposed approach is meant to provide decision guidance in the first phase of wind farm planning. A numerical example for a National Renewable Energy Laboratory (NREL) 5 MW turbine under FINO3 environmental conditions is computed by two effective optimization methods (sequential quadratic programming and an interior-point method), allowing for the estimation of characteristic design variables of a jacket substructure. In order to resolve the mixed-integer problem formulation, multiple subproblems with fixed-integer design variables are solved. The results show that three-legged jackets may be preferable to four-legged ones under the boundaries of this study. In addition, it is shown that mass-dependent cost functions can be easily improved by just considering the number of jacket legs to yield more reliable results.

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Structural optimization with several discrete design variables per part by outer approximation

Cited by 15 publications

References 38 publications

A comparison study on jacket substructures for offshore wind turbines based on optimization

A comparison study on jacket substructures for offshore wind turbines based on optimization

Study on lightweight structural optimization design system for gantry machine tool

A comparison study on jacket substructures for offshore wind turbines based on optimization

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