Failure process and optimal design of hybrid adhesive joints - a microscale experimental and numerical approach

混合粘合接头的失效过程和优化设计——微尺度实验和数值方法

• 批准号: EP/T020695/1
• 负责人: Xiaonan Hou
• 金额: $ 27.72万
• 依托单位: Lancaster University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FT020695%2F1
• 关键词: Failure; process; optimal; design; hybrid

With development of new engineering materials, hybrid structures are now widely used to achieve desired performances by applying new materials instead of conventional ones. This is especially so in the automotive, aerospace and defence industries, since it is a major method to achieve enhanced performance, better fuel efficiency and to minimise greenhouse gas emissions. This technique is being rapidly exploited in other high-value manufacturing-based economies such as Germany and the US. To fabricate hybrid structures, adhesive joining technique attracts more attentions due to their advantage of enabling cost-effective, highly integrated structures with a uniform load distribution and improved damage tolerance. However, there are still some limitations to the use of adhesive joining in hybrid structures. The concept of "hybrid joint" involves a combination of two or more different constituents, with different material properties. To date, there is no well-established theory, which can describe the relationships among the combination of constituents, geometric configuration (microstructures of interfaces and adhesive layer, thickness and overlap of adhesives, etc.) and the overall performance of a hybrid joint. Furthermore, optimization of hybrid adhesive joints is another challenge, since the number of possible effective factors for hybrid adhesive joints is significantly higher than conventional joints and the factors are interactional. In practice, there is no effective optimization method for hybrid joints. Those limitations have resulted in the tendency to "overdesign" hybrid-joining structures. Therefore, the project will focus on a fundamental study of failure mechanisms of a hybrid adhesive joint, and the development of an optimization strategy, which aligns with perspectives from both academia and industry. To achieve the objectives, the project has four main work packages (WPs). In WP1, the failure mechanism of the joint will be analysed using advanced testing facilities, with consideration of the effects of microstructure. Then, in WP2, a DEM model will be developed to describe the mechanical properties of the joint and generate essential date points for optimization. Based on the results of WPs 1 and 2, an optimization algorithm will be developed in WP3 using DoE and Genetic Programming techniques for generating optimal design for hybrid adhesive joints according to design requirements. Finally, case studies will be carried out based on real-world applications for validation. It is intended that the outcomes of the project will substantially overcome the current limitations of the researches in this field and allow a step change in development of high-performance hybrid structures in high value manufacturing.

随着新型工程材料的发展，通过应用新材料代替传统材料，混杂结构得到了广泛的应用，以达到预期的性能。这在汽车、航空航天和国防行业尤其如此，因为这是实现更高性能、更好燃油效率和最大限度减少温室气体排放的主要方法。这种技术正在德国和美国等其他以制造业为基础的高价值经济体迅速被利用。在制造混杂结构方面，粘接技术因其具有高性价比、高集成度、载荷分布均匀和提高损伤容限等优点而受到越来越多的关注。然而，粘结连接在混合结构中的应用仍有一定的局限性。“混合接头”的概念涉及两个或两个以上具有不同材料特性的不同成分的组合。到目前为止，还没有成熟的理论来描述成分组合、几何结构(界面和粘结层的微观结构、粘结剂的厚度和重叠等)之间的关系。以及混合动力关节的整体性能。此外，混杂胶接接头的优化是另一个挑战，因为混杂胶接接头的可能影响因素的数量明显高于传统接头，并且这些因素是相互作用的。在实践中，对于混杂节点还没有一种有效的优化方法。这些限制导致了“过度设计”混合连接结构的趋势。因此，该项目将专注于混合胶接失效机理的基础研究，并开发符合学术界和工业界观点的优化策略。为实现这些目标，该项目有四个主要工作包(WPS)。在WP1中，将使用先进的测试设备分析接头的失效机理，并考虑微观结构的影响。然后，在WP2中，将开发一个DEM模型来描述接头的力学特性，并生成必要的数据点进行优化。基于WPS 1和2的结果，将在WP3中使用DOE和遗传编程技术开发优化算法，以根据设计要求生成混合胶接的优化设计。最后，将基于真实世界的应用进行案例研究以进行验证。该项目的成果将在很大程度上克服目前该领域研究的局限性，并使高价值制造中高性能混合结构的开发发生阶段性变化。

项目成果

A parametric study of adhesive bonded joints with composite material using black-box and grey-box machine learning methods: Deep neuron networks and genetic programming

• DOI: 10.1016/j.compositesb.2021.108894
• 发表时间: 2021-04-30
• 期刊: COMPOSITES PART B-ENGINEERING
• 影响因子: 13.1
• 作者: Gu, Zewen;Liu, Yiding;Hou, Xiaonan
• 通讯作者: Hou, Xiaonan

A novel genetic expression programming assisted calibration strategy for discrete element models of composite joints with ductile adhesives

• DOI: 10.1016/j.tws.2022.109985
• 发表时间: 2022-11
• 期刊: Thin-Walled Structures
• 影响因子: 6.4
• 作者: Xing-er Wang;Armin Yousefi Kanani;Kai Pang;Jian Yang-;Jianqiao Ye;X. Hou

Insights into the micromechanical response of adhesive joint with stochastic surface micro-roughness

• DOI: 10.1016/j.engfracmech.2022.108954
• 发表时间: 2022-11
• 期刊: Engineering Fracture Mechanics
• 影响因子: 5.4
• 作者: Xing-er Wang;Kai Pang;Xu-Hao Huang;Jian Yang-;Jianqiao Ye;X. Hou

Analysis of failure mechanisms of adhesive joints modified by a novel additive manufacturing-assisted method

新型增材制造辅助方法改性粘合接头的失效机制分析

• DOI: 10.1016/j.engstruct.2022.115428
• 发表时间: 2023
• 期刊: Engineering Structures
• 影响因子: 5.5
• 作者: Kanani A

A genetic evolved machine learning approach for 3D DEM modelling of anisotropic materials with full consideration of particulate interactions

• DOI: 10.1016/j.compositesb.2022.110432
• 发表时间: 2023-02
• 期刊: Composites Part B: Engineering
• 作者: Zewen Gu;Xiaoxuan Ding;X. Hou;Jianqiao Ye