High-fidelity simulations for new models that reduce noise pollution

该项目旨在开发一种准确和负担得起的流致噪声预测和缓解方法。这一创新方法基于模拟和数据驱动建模的最新发展，预计将减少环境噪音污染，改善公众健康，并缓解城市化的影响。到目前为止，方法上的局限性阻碍了我们可靠地预测和控制噪声的能力。该项目利用经过验证的高保真模拟和机器学习技术来克服限制，以产生实际噪音缓解所需的科学知识。好处包括更安静的航空航天、海洋和可再生能源技术，创造更愉快的社区。

This project aims to develop a method for accurate and affordable prediction and mitigation of flow-induced noise. The innovative approach, based on recent developments in simulation and data-driven modelling, expects to reduce environmental noise pollution, improve public health and ease the impact of urbanisation. To date methodological limitations have hampered our ability to predict noise reliably and hence control it. This project, exploiting proven high-fidelity simulation and machine-learning techniques to overcome limitations to produce the scientific knowledge required for practical noise mitigation. Benefits include quieter aerospace, marine and renewable energy technologies, creating more pleasant communities.