Understanding the relationship between sludge yield stress (σy) and dewatering performance is essential for optimizing sludge conditioning processes. This study systematically investigates the effects of various conditioning methods-including thermal hydrolysis (TH), freezing/thawing (FT), anaerobic digestion (AD), polyaluminum chloride (PAC), polyacrylamide (PAM), and Fenton treatment (Fenton)-on sludge yield stress and its correlation with dewatering efficiency. Using linear regression, partial least squares regression (PLSR), and correlation heatmap analyses, we reveal significant variations in the correlation between σy and dewatering indexes, including moisture content (Mc), capillary suction time (CST), and bound water proportion (Wb/Wt), depending on the conditioning method and intensity. Under FT and PAM conditioning, σy shows a strong negative linear correlation with dewatering performance, with Pearson's r values exceeding -0.880, indicating that a decrease in σy corresponds to improved dewatering efficiency. Conversely, AD conditioning exhibits a positive linear correlation, with r values up to 0.993, suggesting that an increase in σy correlates with reduced dewatering efficiency. For TH, PAC, and Fenton treatments, the correlation between σy and dewatering metrics is highly sensitive to changes in treatment intensity. In the PLSR analysis, the VIP values, which quantify the importance of each predictor variable, indicate that Wb/Wt in TH conditioning (VIP = 1.649) and CST in PAC (VIP = 1.309) and Fenton (VIP = 1.299) conditioning strongly influence σy. This study highlights the significant impact of conditioning methods and intensities on the correlation between σy and dewatering performance. While σy provides valuable insights as a predictive indicator, its predictive power is limited in more complex conditioning scenarios. Therefore, optimizing conditioning intensity and incorporating multiple rheological parameters are essential for achieving superior sludge dewatering outcomes.
Keywords: Conditioning methods; Correlation analysis; Dewatering performance; Partial least squares regression (PLSR); Sludge treatment; Sludge yield stress.
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