BRITE Pivot: Advancing Knowledge in Water-Shell Structure Interaction Through Discovery of Efficient Hydrodynamic and Structural Thin-shell Forms

这个促进工程变革和公平进步的研究思路（BRITE）枢轴奖资助有可能导致水结构相互作用的科学发现的研究，以实现沿海恢复力的创新方法。通往这些发现的道路建立并发展了一个新的领域，即“建筑工程”，这是由三个学科的整合所代表的：结构工程，海岸工程和建筑。建筑工程的设计目标是海岸灾害工程（安全性，耐久性和鲁棒性），结构艺术（效率，经济性和优雅性）和可持续性（低环境影响）。 在最好的情况下，水产工程等于适应性水产，其特点是没有/低后悔战略（相对较低的成本和预测未来气候下的巨大利益），并具有共同利益（服务于一个以上的目的）。 研究成果通过实现沿海结构的稳健设计而造福社会，同时通过薄壳形式使用更少的质量，以及可能更优雅，对社区和生态系统的干扰更小的设计。在结构工程领域，大量的研究已经证明了薄壳结构形式的显著强度，其中“壳”是指固有的几何曲率，而“薄”是指大的跨厚比。 研究目标是通过水壳结构相互作用的基础知识的进步，使用综合方法：水动力学分析，有限元结构分析和机器学习工具，实现建筑工程和适应性建筑设计目标。具体而言，该研究将发现高效的水动力薄壳结构形式，这些形式广泛应用于沿海弹性，例如海堤，防洪屏障，浮动防波堤，沿海桥梁和沿海建筑立面。由于薄壳结构可能容易受到破碎波的危险脉冲（冲击）力，数值方法包括拉格朗日为基础的多相（水和空气）光滑粒子流体动力学（SPH）模型。 这些复杂的模型将在小规模和大规模的实验程序进行验证。 机器学习方法将用于（1）在给定波浪特性的情况下获得有效的结构薄壳形式，以及（2）开发这些形式上的波浪压力的预测方程。 总的来说，该项目将推进知识之间的关系图案薄壳结构形状/形式和（非）破碎波力。此外，该研究建立了一个新的跨学科领域，并展示了一种综合方法，以找到优化的海岸结构形式和预测波压方程。该奖项反映了NSF的法定使命，并已被认为是值得支持的评估使用基金会的智力价值和更广泛的影响审查标准。

This Boosting Research Ideas for Transformative and Equitable Advances in Engineering (BRITE) Pivot award funds research that has the potential to lead to scientific discoveries in water-structure interaction to enable innovative approaches to coastal resilience. The path to these discoveries establishes and grows a new field, “aquatectural engineering,” which is represented by an integration of three disciplines: structural engineering, coastal engineering, and architecture. The design goals of aquatectural engineering are those of coastal hazard engineering (safety, durability, and robustness), structural art (efficiency, economy, and elegance), and sustainability (low environmental impact). At its best, aquatectural engineering equals adaptable aquatecture, which is characterized by no/low regret strategies (relatively low cost and large benefits under predicted future climates) and has co-benefits (serves more than one purpose). The research outcomes benefit society by enabling robust designs of coastal structures while using less mass via thin-shell forms, and designs that are potentially more elegant and less intrusive to the community and ecosystem. In the field of structural engineering, a plethora of studies have demonstrated the significant strength of thin-shell structural forms, where “shell” refers to the inherent geometric curvature, and “thin” refers to the large span-to-thickness ratio. The research objective is to enable aquatectural engineering and adaptable aquatecture design goals through the advancement of fundamental knowledge in water-shell structure interaction using integrative approaches: hydrodynamic analyses, finite element structural analyses, and machine learning tools. Specifically, the research will discover efficient hydrodynamic thin-shell structural forms that have broad application to coastal resilience such as seawalls, flood barriers, floating breakwaters, coastal bridges, and coastal building facades, for example. Since thin-shell structures could be susceptible to dangerous impulse (impact) forces of breaking waves, the numerical approach includes Lagrangian-based multiphase (water and air) smoothed particle hydrodynamic (SPH) models. These complex models will be validated with experimental programs at small scale and large scale. Machine learning methods will be used to (1) arrive at efficient structural thin-shell forms given wave characteristics and (2) develop predictive equations for the wave pressure on these forms. Overall, the project will advance knowledge in the relationship between patterned thin-shell structural shapes/forms and (non)breaking wave forces. In addition, this research establishes a new interdisciplinary field, and demonstrates an integrative approach to find optimized coastal structure forms and predictive wave pressure equations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.