Sub-space approximations for MDO problems with disparate disciplinary variable dependence

Ollar, Jonathan; Торопов, В. В.; Jones, R T

doi:10.1007/s00158-016-1496-0

Cited by 10 publications

(5 citation statements)

References 26 publications

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“…The Modified Extensible Lattice Sequences (MELS) method [53] was employed for the DOE studies. MELS is a quasi-random sequence designed to distribute the design points in space, minimising clumps and voids evenly, and is based on extensible lattice sequences [54]. The fitting process used the Fit Automatically Selected by Training (FAST) method [53], automatically building the best-fitting functions by testing all implemented methods.…”

Section: Design Explorationmentioning

confidence: 99%

Application of Functionally Graded Shell Lattice as Infill in Additive Manufacturing

2023

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The significance of lightweight designs has become increasingly paramount due to the growing demand for sustainability. Consequently, this study aims to demonstrate the potential of utilising a functionally graded lattice as an infill structure in designing an additively manufactured bicycle crank arm to achieve construction lightness. The authors seek to determine whether functionally graded lattice structures can be effectively implemented and explore their potential real-world applications. Two aspects determine their realisations: the lack of adequate design and analysis methods and the limitations of existing additive manufacturing technology. To this end, the authors employed a relatively simple crank arm and design exploration methods for structural analysis. This approach facilitated the efficient identification of the optimal solution. A prototype was subsequently developed using fused filament fabrication for metals, enabling the production of a crank arm with the optimised infill. As a result, the authors developed a lightweight and manufacturable crank arm showing a new design and analysis method implementable in similar additively manufactured elements. The percentage increase of a stiffness-to-mass ratio of 109.6% was achieved compared to the initial design. The findings suggest that the functionally graded infill based on the lattice shell improves structural lightness and can be manufactured.

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Section: Design Explorationmentioning

confidence: 99%

Application of Functionally Graded Shell Lattice as Infill in Additive Manufacturing

2023

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“…The Modified Extensible Lattice Sequences(MELS) method [52] was employed for the DOE studies. MELS is a quasirandom sequence designed to distribute the design points in space, minimising clumps and voids evenly, and is based on extensible lattice sequences [53]. The fitting process used the Fit Automatically Selected by Training (FAST) method [52], allowing the building automatically best-fitting functions by testing all implemented methods.…”

Section: Design Explorationmentioning

confidence: 99%

Application of Functionally Graded Shell Lattice as Infill in Additive Manufacturing

Kędziora¹,

Decker²,

MUSEYIBOV³

2023

Preprint

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The presented research article shows a functionally graded lattice as an infill structure in designing a 3D printed mechanical element—a bicycle crank arm. The authors want to answer the fundamental question: whether the functionally graded lattice structures can efficiently improve structural performance and how they can be implemented in real complex components. Intuitively, everyone senses that using such elements must bring profit. A good example might be nature, which commonly reaches for such a solution in the skeletons of animals and humans. Two aspects determine their realisations: the lack of adequate construction and analysis methods and the limitations of existing manufacturing methods. Thus, the authors used relatively simple crank arm design and design exploration methods for structural analysis. The design exploration method enabled us to find the optimum solution efficiently. A developed prototype was created utilising additive manufacturing. One of the 3D printing methods - fused filament fabrication technology for metals, allowed the prototype of a crank arm with the optimised infill to be made. As a result, the authors developed a lightweight and manufacturable crank arm showing the new construction and analysis method implementable in similar 3D printed elements.

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“…In [53][54][55], Kriging-based methods have been proposed. A novel approach to constructing the metamodels and trust-region methods based on these ones has been presented in [56][57][58].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Turbulence Model Parameters Using the Global Search Method Combined with Machine Learning

et al. 2022

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The paper considers the slope flow simulation and the problem of finding the optimal parameter values of this mathematical model. The slope flow is modeled using the finite volume method applied to the Reynolds-averaged Navier–Stokes equations with closure in the form of the k−ωSST turbulence model. The optimal values of the turbulence model coefficients for free surface gravity multiphase flows were found using the global search algorithm. Calibration was performed to increase the similarity of the experimental and calculated velocity profiles. The Root Mean Square Error (RMSE) of derivation between the calculated flow velocity profile and the experimental one is considered as the objective function in the optimization problem. The calibration of the turbulence model coefficients for calculating the free surface flows on test slopes using the multiphase model for interphase tracking has not been performed previously. To solve the multi-extremal optimization problem arising from the search for the minimum of the loss function for the flow velocity profile, we apply a new optimization approach using a Peano curve to reduce the dimensionality of the problem. To speed up the optimization procedure, the objective function was approximated using an artificial neural network. Thus, an interdisciplinary approach was applied which allowed the optimal values of six turbulence model parameters to be found using OpenFOAM and Globalizer software.

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Sub-space approximations for MDO problems with disparate disciplinary variable dependence

Cited by 10 publications

References 26 publications

Application of Functionally Graded Shell Lattice as Infill in Additive Manufacturing

Application of Functionally Graded Shell Lattice as Infill in Additive Manufacturing

Application of Functionally Graded Shell Lattice as Infill in Additive Manufacturing

Optimization of Turbulence Model Parameters Using the Global Search Method Combined with Machine Learning

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