Sediment removal in large capacity oil-grit separators

油砂分离器(OGSS)是雨水处理的主要工具之一，用于去除径流中的油、砂粒和沉积物，保护基础设施和环境。这项研究的重点是安装在整个社区、工业工厂、城市重建或其他大型开发项目的大容量OGS(LCOGS)。该项目是与一个行业合作伙伴(加拿大拉法基)合作提出的，目的是产生关于LCOGS性能的比例效应的新知识，并开发一种可应用于不同规模和类型的OGSS的性能评估程序。研究包括全面的数值模拟、实地调查和数据分析。将在与合作伙伴合作进行的实地工作中收集现有几个LCOGS设施的作业数据。计算流体动力学模型将基于LCOGS的设计和可变的流入条件而开发。这项研究需要对三维流态、水动力和沉积过程进行计算。现场信息和现有的实验室数据将有助于在不同的尺度上验证该模型。现有的OGS性能数据和模拟结果将被用来检查几个尺度参数，并开发不同设计、水流条件和泥沙特性下的泥沙清除效率的预测工具。这项研究采用了一种创新的方法，将现有信息与来自建模和实地工作的新数据结合起来，为利益攸关方制定了一项评估程序。总体而言，项目成果将为正确使用OGS单元提供基于科学的知识和工具，有助于保护环境免受城市过度污染的影响。

Oil-Grit Separators (OGSs) are one of the primary stormwater management tools to remove oil, grit and sediment from runoff, which safeguard infrastructure and protect the environment. This research focuses on large-capacity OGSs (LCOGS) that are installed for an entire neighbourhood, an industrial plant, urban redevelopments or other large developments. The project is proposed in collaboration with an industry partner (Lafarge, Canada) to generate new knowledge on scaling effects on the performance of LCOGSs and to develop a performance estimation procedure that can be applied for the different sizes and types of OGSs. The research includes comprehensive numerical modelling, fieldwork, and data analysis. Operational data from several existing LCOGS installations will be collected during fieldwork conducted in collaboration with the partners. Computational Fluid Dynamics models will be developed based on the LCOGS designs and variable inflow conditions. Computations of the three-dimensional flow pattern, hydrodynamics and sedimentation processes are required for this research. Field information and existing laboratory data will help to verify the model at different scales. Existing OGS performance data and modelling results will be used to examine several scaling parameters and to develop prediction tools for sediment removal efficiency under different designs, flow conditions and sediment properties. The research adopts an innovative approach to integrating existing information with new data from modelling and field work to develop an assessment procedure for stakeholders. Overall, the project results will provide science-based knowledge and tools for correct uses of OGS units that contribute to protecting the environment from excess urban pollution.