Failure IS An Option: Assessing Final Clarifier Performance by Quantifying Uncertainty Associated with State Point Analyses (SPA) through Monte Carlo with Latin Hypercube Sampling (MC-LHS)

WRRF modeling typically involves simulating an entire facility, but it can also be used to assess the performance of specific unit processes. For example, FC performance is often quantified through the application of a state point analysis (SPA). This analysis utilizes pre-determined (or assumed) settling parameters (e.g., theoretical maximum sludge settling velocity, v0) to predict whether a clarifier is operating successfully or is in a failure mode (i.e., state point failure or underflow failure) at a given concentration of mixed liquor suspended solids (MLSS), solids flux, overflow, and underflow (see Figure 1). Though useful for determining general operation performance, SPAs rely heavily on uncertain model parameters and inputs without acknowledging the potential impact that these assumptions can have on calculated outputs. Further, these evaluations are often carried out with limited sludge characteristic data outside of sludge volume index (SVI). Recommendations stemming from these analyses could result in oversized – or worse, undersized – FCs. Therefore, the objective of this work is to leverage statistically rigorous, high-throughput uncertainty quantification methods to provide a more thorough understanding of solids flux variability, ultimately enabling WRRF practitioners to manage risk by having a more holistic view of FC performance.