New end-to-end digital framework for optimized manufacturing and maintenance of next generation aircraft composite structures.

GENEX项目旨在开发一种基于增强计算模型的新型端到端数字双驱动框架，嵌入飞机部件和制造/维修过程的跨学科知识，以支持复合材料部件的优化制造，使飞机能够连续运行，并改善复合材料维修过程，以确保飞机的安全性和适航性。首先，将开发自动化ATL工艺，结合基于太赫兹的过程中监测以及混合孪生模拟方法，以实现创新的可再加工可回收（3R）树脂和最先进的热塑性复合材料的生态高效和先进制造。其次，将实施创新的基于数据和物理的机器学习算法，用于损伤检测和定位，结合先进的基于高性能计算（HPC）的多物理和人工智能驱动的数字孪生工具，用于疲劳寿命预测，将信息从优化的板载压阻传感器数据网络与低功耗无线通信平台连接，以进行健康和使用评估和预后。第三，将进一步开发增强现实工具以及用于表面清洁和监测的新型激光辅助方法，智能监测和复合材料修复毯的现场定制加热，以在人工围巾修复操作中提供额外的帮助，提高修复过程的可靠性，同时支持MRO实践的修改和虚拟认证。因此，一个新的数字双驱动框架将被实施到一个通用的IIoT平台中，以集成开发的模型和获取的数据，提供双向的数据流，并实现整体和全面的数据管理方法，确保在整个飞机生命周期中充分创建，捕获，共享和重用知识。

GENEX project aims at developing a novel end-to-end digital twin-driven framework based on enhanced computational models, which embed the interdisciplinary knowledge of the aircraft components and the manufacturing/repairing processes, to support the optimized manufacturing of composites parts, enable the continuous operation of aircrafts and improve the composites repairing processes for ensuring aircraft´s safety and airworthiness. First, automated ATL process coupled with THz-based in-process monitoring together with hybrid-twin simulation methods will be developed for eco-efficient and advance manufacturing of innovative reprocessable repairable-recyclable (3R)-resin-and state-of-the-art thermoplastic composites. Second, innovative data- and physics-based machine learning algorithms for damage detection and location combined with advanced high-performance computing (HPC)-based multi-physics and artificial intelligent-powered digital twin tools for fatigue life prediction, will be implemented to transform information from optimized onboard piezoresistive sensors data networks interfaced with low-power wireless communication platform to health and usage assessment and prognosis. Third, augmented reality tools together with novel laser-assisted methods for surface cleaning and monitoring, smart monitoring and in-situ tailored heating of composite repair blankets will be further developed to provide additional assistance in manual scarf repair operations, increasing reliability of repair process, while supporting the modification and virtual certification of MRO practices. Thus, a novel digital twin-driven framework will be implemented into a common IIoT platform to integrate the developed models and data acquired, providing bidirectional dataflow, and enabling the implementation of a holistic and comprehensive data management methodology ensuring to adequately create, capture, share, and reuse knowledge along the entire aircraft lifecycle.