CIESC Journal ›› 2012, Vol. 63 ›› Issue (12): 4048-4054.DOI: 10.3969/j.issn.0438-1157.2012.12.044

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Dynamic DO simulation for aerobic nitrification process in SBR with constant aeration intensity: model identification and KLa determination

ZHU Ao, GUO Jianhua, WANG Shuying, PENG Yongzhen   

  1. Key Laboratory of Beijing for Water Quality Science and Water Environmental Recovery Engineering, Engineering Research Center of Beijing, Beijing University of Technology, Beijing 100124, China
  • Received:2012-04-16 Revised:2012-08-02 Online:2012-09-04 Published:2012-12-05
  • Supported by:

    supported by the National Natural Science Foundation of China(21177005).

SBR恒曝气量好氧硝化过程动态DO模拟:模型辨识与KLa确定

朱奥, 郭建华, 王淑莹, 彭永臻   

  1. 北京工业大学北京市水质科学与水环境恢复工程重点实验室, 北京市污水脱氮 除磷处理与过程控制工程技术研究中心, 北京100124
  • 通讯作者: 彭永臻
  • 作者简介:朱奥(1987-),男,硕士研究生。
  • 基金资助:

    国家自然科学基金项目(21177005);北京市属高等学校人才强教计划资助项目。

Abstract: A two-step nitrification model was built by simplifying the standard activated sludge model No.1,and dynamic dissolved oxygen(DO)simulation can be done for aerobic nitrification process in a sequencing batch reactor(SBR)with constant aeration intensity.The parameters in the model could be distinguished into two groups by model identification:in a group parameter values can be directly obtained,including yield coefficient,DO saturation coefficient(or substrate coefficient),and in other group parameter values needed to be estimated by optimization algorithm.Adopting the parameter values recommended by literatures,dynamic processes were simulated for important process variables,which revealed multi-DO levels and fitted well with the real response trend in SBR operation.Optimal experimental design method was employed for obtaining dynamic DO data of aerobic nitrification process in the SBR with typical aeration intensity,from which the values of KLa and SOeq could be determined by theoretical analysis and second order differential treatment of these data.Then,further parameter estimation could be optimal based on the model identification and KLa determination.

Key words: DO simulation, sequencing batch reactor(SBR), nitrification model, structural identification, optimal experimental design(OED)

摘要: 通过简化活性污泥法1号模型(activated sludge model No.1,ASM1)建立两步硝化反应的数学模型,实现了对序批式反应器(sequencing batch reactor,SBR)恒曝气量好氧过程中溶解氧(dissolved oxygen,DO)动态变化过程的数学模拟,模型辨识科学地区分了可以直接取值的参数包括产率系数、DO饱和常数(或底物饱和常数)和需要重新估计的参数。采用文献推荐参数值模拟了过程中主要状态变量的动力学过程,模拟结果呈现出了多个DO平台,这与实际反应结果数据相符,验证了所建模型的正确性。优化实验设计,获取了典型SBR恒曝气好氧硝化过程动态DO数据,通过理论分析和对数据进行二阶微分处理提出了确定总氧传递系数KLa和相对饱和溶解氧SOeq的简单方法,为后续参数估计奠定了基础。

关键词: DO模拟, 序批式反应器, 硝化模型, 结构辨识, 优化实验设计

CLC Number: