摘要
Sludge blanket height （SBH） is an important parameter in the clarifier design, operation and control. Based on an overview and classification of SBH algorithms, a modified SBH algorithm is proposed by incorporating a threshold concentration limit into a relative concentration sharp change algorithm to eliminate the disturbance of compression interfaces on the correct simulation of SBH. Pilot-scale test data are adopted to compare reliability of three SBH algorithms reported in literature and the modified SBH algorithm developed in this paper. Calculated results demonstrate that the three SBH algorithms give results with large deviation （〉 50%） from measured SBH, especially under low solid flux conditions. The modified algorithm is computationally efficient and reliable in matching the measured data. It is incorporated into a one- dimensional clarifier model for stable simulation of pilot-scale experimental clarifier data and into dynamic simulation of a full-scale wastewater treatment plant （WWTP） clarifier data.
Sludge blanket height （SBH） is an important parameter in the clarifier design, operation and control. Based on an overview and classification of SBH algorithms, a modified SBH algorithm is proposed by incorporating a threshold concentration limit into a relative concentration sharp change algorithm to eliminate the disturbance of compression interfaces on the correct simulation of SBH. Pilot-scale test data are adopted to compare reliability of three SBH algorithms reported in literature and the modified SBH algorithm developed in this paper. Calculated results demonstrate that the three SBH algorithms give results with large deviation （〉 50%） from measured SBH, especially under low solid flux conditions. The modified algorithm is computationally efficient and reliable in matching the measured data. It is incorporated into a one- dimensional clarifier model for stable simulation of pilot-scale experimental clarifier data and into dynamic simulation of a full-scale wastewater treatment plant （WWTP） clarifier data.
基金
supported by the National Natural Science Foundation of China (Grant No.501380107)
