Literature DB >> 28980645

Giga-voxel computational morphogenesis for structural design.

Niels Aage1,2, Erik Andreassen1, Boyan S Lazarov1, Ole Sigmund1.   

Abstract

In the design of industrial products ranging from hearing aids to automobiles and aeroplanes, material is distributed so as to maximize the performance and minimize the cost. Historically, human intuition and insight have driven the evolution of mechanical design, recently assisted by computer-aided design approaches. The computer-aided approach known as topology optimization enables unrestricted design freedom and shows great promise with regard to weight savings, but its applicability has so far been limited to the design of single components or simple structures, owing to the resolution limits of current optimization methods. Here we report a computational morphogenesis tool, implemented on a supercomputer, that produces designs with giga-voxel resolution-more than two orders of magnitude higher than previously reported. Such resolution provides insights into the optimal distribution of material within a structure that were hitherto unachievable owing to the challenges of scaling up existing modelling and optimization frameworks. As an example, we apply the tool to the design of the internal structure of a full-scale aeroplane wing. The optimized full-wing design has unprecedented structural detail at length scales ranging from tens of metres to millimetres and, intriguingly, shows remarkable similarity to naturally occurring bone structures in, for example, bird beaks. We estimate that our optimized design corresponds to a reduction in mass of 2-5 per cent compared to currently used aeroplane wing designs, which translates into a reduction in fuel consumption of about 40-200 tonnes per year per aeroplane. Our morphogenesis process is generally applicable, not only to mechanical design, but also to flow systems, antennas, nano-optics and micro-systems.

Entities:  

Year:  2017        PMID: 28980645     DOI: 10.1038/nature23911

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  1 in total

1.  Rapid prototyping of nanotube-based devices using topology-optimized microgrippers.

Authors:  O Sardan; V Eichhorn; D H Petersen; S Fatikow; O Sigmund; P Bøggild
Journal:  Nanotechnology       Date:  2008-11-18       Impact factor: 3.874

  1 in total
  11 in total

1.  Elastic Shape Morphing of Ultralight Structures by Programmable Assembly.

Authors:  Nicholas B Cramer; Daniel W Cellucci; Olivia B Formoso; Christine E Gregg; Benjamin E Jenett; Joseph H Kim; Martynas Lendraitis; Sean S Swei; Greenfield T Trinh; Khanh V Trinh; Kenneth C Cheung
Journal:  Smart Mater Struct       Date:  2019-04-01       Impact factor: 3.585

2.  Artificial Intelligence and Personalized Medicine.

Authors:  Nicholas J Schork
Journal:  Cancer Treat Res       Date:  2019

3.  Engineering: Computational design hits record resolution.

Authors:  Matthijs Langelaar
Journal:  Nature       Date:  2017-10-04       Impact factor: 49.962

4.  Multi-functional topology optimization of Victoria cruziana veins.

Authors:  Hui-Kai Zhang; Jingyi Zhou; Wei Fang; Huichan Zhao; Zi-Long Zhao; Xindong Chen; Hong-Ping Zhao; Xi-Qiao Feng
Journal:  J R Soc Interface       Date:  2022-06-15       Impact factor: 4.293

5.  Nanometer-scale photon confinement in topology-optimized dielectric cavities.

Authors:  Marcus Albrechtsen; Babak Vosoughi Lahijani; Rasmus Ellebæk Christiansen; Vy Thi Hoang Nguyen; Laura Nevenka Casses; Søren Engelberth Hansen; Nicolas Stenger; Ole Sigmund; Henri Jansen; Jesper Mørk; Søren Stobbe
Journal:  Nat Commun       Date:  2022-10-21       Impact factor: 17.694

6.  The mechanical principles behind the golden ratio distribution of veins in plant leaves.

Authors:  Zhi Sun; Tianchen Cui; Yichao Zhu; Weisheng Zhang; Shanshan Shi; Shan Tang; Zongliang Du; Chang Liu; Ronghua Cui; Hongjie Chen; Xu Guo
Journal:  Sci Rep       Date:  2018-09-14       Impact factor: 4.379

7.  Deep elastic strain engineering of bandgap through machine learning.

Authors:  Zhe Shi; Evgenii Tsymbalov; Ming Dao; Subra Suresh; Alexander Shapeev; Ju Li
Journal:  Proc Natl Acad Sci U S A       Date:  2019-02-15       Impact factor: 11.205

8.  Inverse Design Tool for Ion Optical Devices using the Adjoint Variable Method.

Authors:  Lars Thorben Neustock; Paul C Hansen; Zachary E Russell; Lambertus Hesselink
Journal:  Sci Rep       Date:  2019-07-30       Impact factor: 4.379

9.  Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active Learning.

Authors:  Chun-Teh Chen; Grace X Gu
Journal:  Adv Sci (Weinh)       Date:  2020-01-09       Impact factor: 16.806

10.  Topological Design of a Lightweight Sandwich Aircraft Spoiler.

Authors:  Jie Liu; Haifeng Ou; Junfeng He; Guilin Wen
Journal:  Materials (Basel)       Date:  2019-10-01       Impact factor: 3.623

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