Concurrent hpk-Mesh Adaptation and Shape Optimization of Complex Geometries through an Adjoint-Based Discontinuous Petrov-Galerkin Isogeometric Analysis

通过基于伴随的不连续 Petrov-Galerkin 等几何分析并行 hpk 网格自适应和复杂几何形状优化

• 批准号: RGPIN-2019-04791
• 负责人: Nadarajah, Sivakumaran
• 金额: $ 5.54万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=737863
• 关键词: Concurrent; hpk; Mesh; Adaptation; Shape

The past decade has seen the application of adjoint-based optimization frameworks for the multidisciplinary design of aerodynamic surfaces as well as mesh adaptation to increase the accuracy of integrated functions such as lift and drag coefficients. Both adjoint-based design optimization and mesh adaptation have been advanced independently but not investigated concurrently. Aerodynamic shape optimization algorithms must facilitate the design of the next generation of commercial aircraft to meet future global standards on the environmental impact of aviation. The European Union's Clean Sky and NASA's Environmentally Responsible Aviation (ERA) Project have placed benchmarks on the type of performance improvements that are expected on future aircraft designs. The community, therefore, is at a critical juncture to innovate and develop radically new aircraft designs. Computational tools that allow airframe manufacturers to both design aircraft with superior high-lift aerodynamic performance and accurately resolve far-field acoustic signatures within a single numerical framework are invaluable. Such capabilities are unlike the current practice of employing multiple numerical tools that only prolong the design cycle and arrive at sub-optimal designs. Thus, the long-term vision of the research program is to establish a common framework using a high-order discontinuous Petrov-Galerkin scheme for the concurrent mesh adaptation and shape optimization to increase the performance of aerodynamic surfaces. The research program has the potential to make a transformative impact on the design of the next generation of commercial aircraft. The research training will provide graduate students an enriching environment to contribute and define an emerging field. Scholars will graduate with skills in formulating research questions, communicating their ideas, receiving critiques, and being trained on the next-generation of high-performance computing. The long-term impact of this research program will produce highly skilled personnel and enable Canada to remain a leader in current aircraft technology.

在过去的十年中，基于伴随的优化框架应用了空气动力表面的多学科设计以及网状改编，以提高集成功能（例如升力和阻力系数）的准确性。基于伴随的设计优化和网格适应性均已独立提出，但未同时研究。空气动力学优化算法必须促进下一代商用飞机的设计，以满足对航空环境影响的未来全球标准。欧盟的清洁天空和NASA对环境负责的航空项目（ERA）项目为未来飞机设计预期的绩效改进类型奠定了基准。因此，社区是创新和开发新的飞机设计的关键时刻。允许机身制造商可以在单个数值框架内设计具有出色高速空气动力学性能的飞机的计算工具，并且可以准确地解决远场声学签名。这样的功能与当前使用多种数值工具仅延长设计周期并达到次级设计的数值工具不同。这是研究计划的长期视觉是使用高阶不连续的彼得 - 盖尔金方案来建立一个共同的框架，以同时进行网格适应和形状优化，以提高空气动力表面的性能。该研究计划有可能对下一代商用飞机的设计产生变革性的影响。研究培训将为研究生一个丰富的环境，以贡献和定义新兴领域。学者将毕业，以提出研究问题，传达他们的想法，接受批判性以及接受高性能计算的下一代培训，毕业。该研究计划的长期影响将产生高技能的人，并使加拿大能够成为当前飞机技术的领导者。