Optimal design of a novel cylindrical sandwich panel with double arrow auxetic core under air blast loading

Lan, Xuke; Huang, Qi; Zhou, Tianfei; Feng, Shunshan

doi:10.1016/j.dt.2019.09.010

Cited by 46 publications

(10 citation statements)

References 27 publications

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“…Owing to their several attractive characteristics, the ANN approach has been extensively used in numerous applications in engineering, medicine, meteorology, economics, psychology and many other fields [34,35,37,38]. In light of this, several studies have explored the use of ANN's to the assessment of sandwich composite panels [39][40][41][42][43][44][45][46][47]. However, with regard to honeycomb core sandwich composites, there tends to be a scarcity of studies that attempt to establish a generalized prediction model that can capture the influence of each of the honeycomb core's geometrical parameters [cell wall thickness (t), and the cell wall angle (φ), cell wall length (a), core thicknesses (D)].…”

Section: Artificial Neural Network (Ann) Modellingmentioning

confidence: 99%

Artificial Neural Network–Particle Swarm Optimization (ANN-PSO) Approach for Behaviour Prediction and Structural Optimization of Lightweight Sandwich Composite Heliostats

2021

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The necessity to diminish the heliostats’ cost so that central tower concentrating solar power (CSP) systems can stride to the forefront to become the technology of choice for generating renewable electricity is obliging the industry to consider innovative designs, leading to new materials being implemented into the development of heliostats. Honeycomb sandwich composites offer a lightweight but stiff structure that appear to be an ideal substitute for existing heliostat mirrors and their steel supporting trusses, avoiding large drive units and reducing energy consumption. However, realizing a honeycomb sandwich composite as a heliostat, among a multitude of possible combinations can be tailored from, that delivers the best trade-off between the panel’s weight reduction (broadly equates to cost) and structural integrity is cumbersome and challenging due to the complex nonlinear material behaviour, along with the large number of design variables and performance constraints. We herein offer a simulation–optimization model for behaviour prediction and structural optimization of lightweight honeycomb sandwich composite heliostats utilizing artificial neural network (ANN) technique and particle swarm optimization (PSO) algorithm. Considering various honeycomb core configurations and several loading conditions, a thorough investigation was carried out to optimally choose the training algorithm, number of neurons in the hidden layer, activation function in a network and the suitable swarm size that delivers the best performance for convergence and processing time. Carried out for three case scenarios, each with different design requirements, the results showed that the proposed integrated ANN-PSO approach provides a useful, flexible and time-efficient tool for heliostat designers to predict and optimize the structural performance of honeycomb sandwich composite-based heliostats as per desired requirements. Knowing that heliostats in the field are not all subjected to the same wind conditions, this method offers flexibility to tailor heliostats independently, allowing them to be made lighter depending on the local wind speed in the field. This could lead to reductions in the size of drive units used to track the heliostat, and the foundations required to support these structures. Such reductions would deliver real cost savings, which are currently an impediment to the wider spread use of CSP systems.

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Section: Artificial Neural Network (Ann) Modellingmentioning

confidence: 99%

Artificial Neural Network–Particle Swarm Optimization (ANN-PSO) Approach for Behaviour Prediction and Structural Optimization of Lightweight Sandwich Composite Heliostats

2021

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“…Luo et al proposed and designed an auxetic re-entrant blast wall (ARBW) to improve anti-explosion performance of blast walls in off-shore platforms [158]. Since curved structures can support external loads better owing to their curvature, Lan et al designed a novel cylindrical double arrowhead cored sandwich panel [159]. The results of extensive investigations on sandwich structures show promise in bringing about a manifold improvement in the quality of blast curtains, bullet-proof vests and bullet-proof helmets The worldwide market for these protective products is huge.…”

Section: Defencementioning

confidence: 99%

Cellular Auxetic Structures for Mechanical Metamaterials: A Review

Kelkar

Kim

Cho

et al. 2020

Sensors

156

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Recent advances in lithography technology and the spread of 3D printers allow us a facile fabrication of special materials with complicated microstructures. The materials are called “designed materials” or “architectured materials” and provide new opportunities for material development. These materials, which owing to their rationally designed architectures exhibit unusual properties at the micro- and nano-scales, are being widely exploited in the development of modern materials with customized and improved performance. Meta-materials are found to possess superior and unusual properties as regards static modulus (axial stress divided by axial strain), density, energy absorption, smart functionality, and negative Poisson’s ratio (NPR). However, in spite of recent developments, it has only been feasible to fabricate a few such meta-materials and to implement them in practical applications. Against such a backdrop, a broad review of the wide range of cellular auxetic structures for mechanical metamaterials available at our disposal and their potential application areas is important. Classified according to their geometrical configuration, this paper provides a review of cellular auxetic structures. The structures are presented with a view to tap into their potential abilities and leverage multidimensional fabrication advances to facilitate their application in industry. In this review, there is a special emphasis on state-of-the-art applications of these structures in important domains such as sensors and actuators, the medical industry, and defense while touching upon ways to accelerate the material development process.

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“…Zhao et al [32] proposed a theoretical model for predicting the dynamic crushing strength of double-arrowed auxetic structure and the theoretical model was validated by numerical results. Lan et al [33] designed a novel cylindrical sandwich panel with double arrow auxetic core and built the numerical model. The blast resistance and energy absorption capacity were investigated.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the dynamic behavior of composite gradient double‐arrow auxetic structure under local impact load

Zeng

et al. 2022

Polymer Composites

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Based on the design concept of functionally graded materials, the composite gradient double-arrow auxetic structures were designed and fabricated. The thickness of core layers demonstrates an increasing trend for positive gradient structure, while a decreasing trend for negative gradient structure. The thickness of core layers keeps constant for homogeneous structure. The dynamic response and failure modes of the double-arrow auxetic structure with different gradient distributions of wall thickness were obtained by foam projectile impact experiments. The influence of the gradient distribution of core wall thickness on the impact resistance of composite double-arrow auxetic structures under local impact load was investigated. The results demonstrated that the gradient distribution of core wall thickness has an important influence on the dynamic response and failure modes of the structure. The negative gradient auxetic structure revealed more excellent impact resistance compared with the positive gradient auxetic structure. In addition, the response of the gradient double-arrow auxetic structure under local impact load was simulated by ABAQUS/Explicit, and the simulation results were in good agreement with the experimental results. Combined with the experimental and numerical simulation results, it was found that the negative gradient distribution of core wall thickness had an obvious improvement on the impact resistance of composite double-arrow auxetic structure under local impact load.

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Optimal design of a novel cylindrical sandwich panel with double arrow auxetic core under air blast loading

Cited by 46 publications

References 27 publications

Artificial Neural Network–Particle Swarm Optimization (ANN-PSO) Approach for Behaviour Prediction and Structural Optimization of Lightweight Sandwich Composite Heliostats

Artificial Neural Network–Particle Swarm Optimization (ANN-PSO) Approach for Behaviour Prediction and Structural Optimization of Lightweight Sandwich Composite Heliostats

Cellular Auxetic Structures for Mechanical Metamaterials: A Review

Investigation on the dynamic behavior of composite gradient double‐arrow auxetic structure under local impact load

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