Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in activated sludge water resource recovery facilities (WRRF). Mathematical models for predicting activated sludge solids settling velocity include parameters that show irreducible epistemic uncertainty. Therefore, reliable and periodic calibration of the settling velocity model is key for predicting activated sludge process capacity, thus averting possible failures under wet-weather flow- and filamentous bulking conditions. The two main knowledge gaps addressed here are: (1) Do constitutive functions for hindered and compression settling exist, for which all velocity parameters can be uniquely estimated? (2) What is the optimum sensor data requirement of developing reliable settling velocity functions? Innovative settling column sensor and full-scale data were used to identify and validate amended Vesilind function for hindered settling and a new exponential function for compression settling velocity using one-dimensional and computational fluid dynamics simulations. Results indicate practical model identifiability under well-settling and filamentous bulking conditions.

二级沉淀池（SST）是活性污泥水资源回收设施（WRRF）中对水力最敏感的单元操作。预测活性污泥固体沉降速度的数学模型包括显示不可减少的认识不确定性的参数。因此，沉降速度模型的可靠且定期的校准对于预测活性污泥的处理能力至关重要，从而避免了在潮湿天气下流动和长丝状堆积条件下可能发生的故障。这里解决的两个主要知识差距是：（1）是否存在用于阻碍和压缩沉降的本构函数，可以唯一估计所有速度参数？（2）开发可靠的沉降速度函数的最佳传感器数据要求是什么？使用一维和计算流体动力学模拟，使用创新的沉降柱传感器和满量程数据来识别和验证修正的Vesilind函数以防止障碍沉降，并使用新的指数函数压缩沉降速度。结果表明在沉降良好和丝状膨松条件下的实际模型可识别性。