Yield stress as a rheological proxy for compressibility and permeability evolution during compression-dominated...

Sludge compressibility and permeability are key descriptors of mechanical dewatering efficiency, but conventional measurement methods (e.g., consolidation tests) are typically time-consuming, which restricts their use for timely process optimization. Yield stress (σ_y), reflecting floc structure and network strength, shows potential for predicting dewatering performance. However, existing studies predominantly focus on lab-scale processes, which inadequately represent real-world conditions. This study systematically investigated the dynamic evolution of sludge pore structure, σ_y, compressibility, and permeability under actual plant conditions using a polypropylene diaphragm filter press coupled with a practical conditioning strategy (basic aluminum chloride in conjunction with cationic polyacrylamide). Advanced characterization techniques, including low-field nuclear magnetic resonance, computed tomography, and rheological analyses, were employed to monitor structural and mechanical changes. Mechanical compression significantly reduced pore size and total porosity while increasing the proportion of isolated pores, leading to denser floc networks. Concurrently, σ_y, storage modulus (G'), and complex modulus (G∗) exhibited continuous increases, with σ_y showing a remarkable 458% enhancement (from 3278 to 18,300 Pa), indicating enhanced structural rigidity. In contrast, the compressibility index (C_c) and permeability coefficient (k) declined by 72.7% (from 2.79 to 0.76) and 85.2% (from 8.04 × 10^-6 to 1.19 × 10^-6 cm/s), respectively, reflecting deteriorated dewaterability. Strong negative correlations were revealed between σ_y and both C_c (R² = 0.827, 0.856, and 0.889, respective; p < 0.05) and k (R² = 0.845, 0.892, and 0.920, respective; p < 0.05), underscoring the potential of σ_y as a reliable proxy for sludge dewatering performance. Overall, the results demonstrate that σ_y measurements can be used to predict and optimize sludge dewatering outcomes under realistic compression conditions, thereby providing a bridge between laboratory findings and full-scale operation. These insights extend the application scope of rheological metrics and offer a practical tool for improving full-scale sludge management strategies.