A novel lattice structure topology optimization method with extreme anisotropic lattice properties

Zhang, Chenghu; Liu, Ji‐Kai; Yuan, Zhiling; Xu, Shuzhi; Zou, Bin; Li, Lei; Ma, Yongsheng

doi:10.1093/jcde/qwab051

Cited by 26 publications

(3 citation statements)

References 69 publications

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“…Apart from data-driven TO, some works try to achieve non-iterative optimisation [296][297][298][299][300][301][302][303][304][305][306][307][308][309][310][311][312][313], or intend to replace the typical FEM process, creating meta-models [314][315][316][317][318][319][320][321][322][323][324][325][326][327][328][329][330][331][332]. Other approaches try to reduce the dimensionality of the design space [333][334][335].…”

Section: Machine Learning Applied To Topology Optimisationmentioning

confidence: 99%

On Topology Optimisation Methods and Additive Manufacture for Satellite Structures: A Review

Hurtado-Pérez,

Pablo-Sotelo,

Ramírez-López

et al. 2023

Aerospace

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Launching satellites into the Earth’s orbit is a critical area of research, and very demanding satellite services increase exponentially as modern society takes shape. At the same time, the costs of developing and launching satellite missions with shorter development times increase the requirements of novel approaches in the several engineering areas required to build, test, launch, and operate satellites in the Earth’s orbit, as well as in orbits around other celestial bodies. One area with the potential to save launching costs is that of the structural integrity of satellites, particularly in the launching phase where the largest vibrations due to the rocket motion and subsequent stresses could impact the survival ability of the satellite. To address this problem, two important areas of engineering join together to provide novel, complete, and competitive solutions: topology optimisation methods and additive manufacturing. On one side, topology optimisation methods are mathematical methods that allow iteratively optimising structures (usually by decreasing mass) while improving some structural properties depending on the application (load capacity, for instance), through the maximisation or minimisation of a uni- or multi-objective function and multiple types of algorithms. This area has been widely active in general for the last 30 years and has two main core types of algorithms: continuum methods that modify continuous parameters such as density, and discrete methods that work by adding and deleting material elements in a meshing context. On the other side, additive manufacturing techniques are more recent manufacturing processes aimed at revolutionising manufacturing and supply chains. The main exponents of additive manufacturing are Selective Laser Melting (SLM) (3D printing) as well as Electron Beam Melting (EBM). Recent trends show that topology-optimised structures built with novel materials through additive manufacturing processes may provide cheaper state-of-the-art structures that are fully optimised to better perform in the outer-space environment, particularly as part of the structure subsystem of novel satellite systems. This work aims to present an extended review of the main methods of structural topology optimisation as well as additive manufacture in the aerospace field, with a particular focus on satellite structures, which may set the arena for the development of future satellite structures in the next five to ten years.

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Section: Machine Learning Applied To Topology Optimisationmentioning

confidence: 99%

On Topology Optimisation Methods and Additive Manufacture for Satellite Structures: A Review

Hurtado-Pérez,

Pablo-Sotelo,

Ramírez-López

et al. 2023

Aerospace

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“…Comprising an interlinked network of struts, the micro-lattice possesses high porosity and low density, endowing it with exceptional structural efficiency. Consequently, micro-lattice structures have been used to produce lightweight structural components (Terriault and Brailovski, 2018; Graziosi et al , 2022; Letoy and Zhao, 2022) and topologically optimized configurations (Zhang et al , 2021; Kim and Park, 2021). In addition, they have proven instrumental in regulating thermal conductivity and relevant heat transfer characteristics through appropriate manipulation of lattice porosity (Maloney et al , 2012; You and Park, 2021; You et al , 2022).…”

Section: Introductionmentioning

confidence: 99%

Direct slicing of microcellular structures for digital light processing (DLP) additive manufacturing

Oh,

Park

2024

RPJ

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Purpose Additive Manufacturing (AM) conventionally necessitates an intermediary slicing procedure using the standard tessellation language (STL) data, which can be computationally burdensome, especially for intricate microcellular architectures. This study aims to propose a direct slicing method tailored for digital light processing-type AM processes for the efficient generation of slicing data for microcellular structures. Design/methodology/approach The authors proposed a direct slicing method designed for microcellular structures, encompassing micro-lattice and triply periodic minimal surface (TPMS) structures. The sliced data of these structures were represented mathematically and then convert into 2D monochromatic images, bypassing the time-consuming slicing procedures required by 3D STL data. The efficiency of the proposed method was validated through data preparations for lattice-based nasopharyngeal swabs and TPMS-based ellipsoid components. Furthermore, its adaptability was highlighted by incorporating 2D images of additional features, eliminating the requirement for complex 3D Boolean operations. Findings The direct slicing method offered significant benefits upon implementation for microcellular structures. For lattice-based nasopharyngeal swabs, it reduced data size by a factor of 1/300 and data preparation time by a factor of 1/8. Similarly, for TPMS-based ellipsoid components, it reduced data size by a factor of 1/60 and preparation time by a factor of 1/16. Originality/value The direct slicing method allows for bypasses the computational burdens associated with traditional indirect slicing from 3D STL data, by directly translating complex cellular structures into 2D sliced images. This method not only reduces data volume and processing time significantly but also demonstrates the versatility of sliced data preparation by integrating supplementary features using 2D operations.

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“…The lattice structure is a kind of cellular material with the regular repeating structure of their unit cell [ 1 ]. Owing to its extraordinary mechanical performances, e.g., specific mechanical strength [ 2 ], ultra-low density [ 3 ], tunable thermal conductivity [ 4 ], and negative Poisson’s ratio [ 5 ], etc., lattice structures have been applied to medical [ 6 , 7 ], energy absorption [ 8 , 9 ], aerospace [ 10 , 11 ], nuclear engineering [ 3 ], flexible and wearable devices [ 12 ]. Traditionally, lattice structures are fabricated via water jet cutting [ 13 ], investment casting [ 14 ], and wire-woven methods [ 15 ], which cause waste of materials, limited design flexibility, and difficulty in manufacturing microstructures.…”

Section: Introductionmentioning

confidence: 99%

Smart Lattice Structures with Self-Sensing Functionalities via Hybrid Additive Manufacturing Technology

He,

Wang,

Yang

et al. 2023

Micromachines

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Lattice structures are a group of cellular materials composed of regular repeating unit cells. Due to their extraordinary mechanical properties, such as specific mechanical strength, ultra-low density, negative Poisson’s ratio, etc., lattice structures have been widely applied in the fields of aviation and aerospace, medical devices, architecture, and automobiles. Hybrid additive manufacturing (HAM), an integrated manufacturing technology of 3D printing processes and other complementary processes, is becoming a competent candidate for conveniently delivering lattice structures with multifunctionalities, not just mechanical aspects. This work proposes a HAM technology that combines vat photopolymerization (VPP) and electroless plating process to fabricate smart metal-coated lattice structures. VPP 3D printing process is applied to create a highly precise polymer lattice structure, and thereafter electroless plating is conducted to deposit a thin layer of metal, which could be used as a resistive sensor for monitoring the mechanical loading on the structure. Ni-P layer and copper layer were successfully obtained with the resistivity of 8.2×10−7Ω⋅m and 2.0 ×10−8 Ω⋅m, respectively. Smart lattice structures with force-loading self-sensing functionality are fabricated to prove the feasibility of this HAM technology for fabricating multifunctional polymer-metal lattice composites.

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A novel lattice structure topology optimization method with extreme anisotropic lattice properties

Cited by 26 publications

References 69 publications

On Topology Optimisation Methods and Additive Manufacture for Satellite Structures: A Review

On Topology Optimisation Methods and Additive Manufacture for Satellite Structures: A Review

Direct slicing of microcellular structures for digital light processing (DLP) additive manufacturing

Smart Lattice Structures with Self-Sensing Functionalities via Hybrid Additive Manufacturing Technology

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