Aerospace composites mechanical damage prediction through multi-scale modelling

通过多尺度建模进行航空航天复合材料机械损伤预测

• 批准号: RGPIN-2016-06412
• 负责人: Lévesque, Martin
• 金额: $ 4.23万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=657357
• 关键词: Aerospace; composites; mechanical; damage; prediction

The replacement of metallic aerospace parts by the introduction of composites in the 1960's offered the promises of lighter aircraft. Lighter aircraft consume less fuel, which provides a competitive advantage to aircraft manufacturers, and reduce polluting emanations, which is essential to ensure Earth's sustainability. Yet, weight savings in Canadian aircraft range from 0 to 5%, whereas senior aerospace composites experts believe that it could safely be around 15%, and beyond with new composites. Prohibitively expensive certification costs and over-conservative safety factors contribute to this poor performance. This situation must absolutely be remedied to maintain Canada's competitiveness in aerospace.***Accurate composites predictive damage models could significantly decrease the weight of composite parts, since: i) some certification tests could be replaced by predictions, which would accelerate the introduction newer materials of improved performance and ii) accurate models will lead to lower safety factors, and hence, to lighter aircraft. The World Wide Failure Exercise on composites revealed that current models cannot predict composite failure within reasonable accuracy for every load case. Composites damage is a complex process initiated by sub-micron cracks that propagate through the hierarchy of scales. Classical continuum mechanic is ill-suited for handling these discontinuities. ***The proposed research program aims at developing a multi-scale framework for predicting composites failure by simultaneously investigating: i) experimental methods for identifying relevant material parameters, ii) models for predicting composites damage initiation and propagation and iii) numerical strategies for delivering efficient composites damage predictions. The program relies on Peridynamics, which is a relatively new formulation for continuum mechanics that eludes most of the classical approaches' shortcomings. ***The research will be carried out by 4 PhD students and 1 post-doctoral fellow, supported by 13 undergraduate students and 1 research associate. Most graduate students will be co-supervised by professors of complementary expertise (experimental, theoretical and numerical). Every PhD student will perform a short-time (2-3 weeks) internship with well-known international experts, as well as a four-month internship in an aerospace company as part of a larger training program aiming at improving the aerospace industry readinyness level of graduate students.***This program should trigger the essential paradigm shift for properly addressing composites damage prediction, and hence reap the full weight reduction potential composites offer. The methodology is tailored for the aerospace industry to accelerate its transfer with the next generation of experts that will be specifically trained for that objective throughout the program. *** *** *** **

通过在1960年代引入复合材料来代替金属航空航天零件提供了更轻的飞机的承诺。较轻的飞机消耗的燃料减少，这为飞机制造商提供了竞争优势，并减少了污染的发射，这对于确保地球的可持续性至关重要。然而，加拿大飞机的体重节省量从0％到5％不等，而高级航空航天复合材料专家认为，它可以安全地达到15％及以外的新复合材料。昂贵的认证成本和过度保守的安全因素有助于这种绩效差。必须绝对修复这种情况以维持加拿大在航空航天中的竞争力。改善性能和ii）准确的模型将导致较低的安全因子，从而导致较轻的飞机。在复合材料上的全球故障练习表明，当前模型无法预测每个负载案例中合理准确性内的复合故障。复合材料损坏是一个复杂的过程，该过程是通过尺度层次结构传播的亚微米裂纹引发的。古典连续机械师不适合处理这些不连续性。 ***拟议的研究计划旨在通过同时研究来开发一个多规模框架来预测复合材料的失败：i）用于识别相关材料参数的实验方法，ii）预测复合材料损害启动和传播的模型以及iiii）的数值策略）有效的复合材料损坏预测。该计划依赖于Peridynegics，这是连续机械的相对较新的配方，它消除了大多数经典方法的缺点。 ***这项研究将由4名博士生和1名博士后研究员进行，并由13名本科生和1名研究助理提供支持。大多数研究生将由补充专业知识教授（实验，理论和数值）共同监督。每位博士生都将与著名的国际专家进行短期（2-3周）实习，并在航空航天公司进行四个月的实习，这是一项更大的培训计划的一部分，旨在提高航空航天行业的阅读水平***该计划应触发基本范式转移，以适当解决复合材料的损害预测，因此获得了全部减轻体重的潜在复合材料提供的。该方法是为航空航天行业量身定制的，可以通过下一代专家加速其转移，这些专家将在整个计划中专门针对该目标进行培训。 *** *** *** **