[1]邓仁健,宋雨佳,任伯帜,等.基于灵敏度分析的ASM2d数学模型参数集校核方法[J].中国给水排水,2022,38(11):83-90.
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基于灵敏度分析的ASM2d数学模型参数集校核方法

中国给水排水[ISSN:1000-4062/CN:12-1073/TU] 卷: 第38卷 期数: 2022年第11期 页码: 83-90 栏目: 出版日期: 2022-06-01
Title:
Check Method of ASM2d Mathematical Model Parameter Set Based on Sensitivity Analysis
作者:
邓仁健1， 宋雨佳1， 任伯帜1， 周赛军1， 张金松2
（1.湖南科技大学 土木工程学院，湖南 湘潭 411201；2.深圳市水务<集团>有限公司，广东 深圳 518030）
Author(s):
DENG　Ren-jian1， SONG　Yu-jia1， REN　Bo-zhi1， ZHOU　Sai-jun1， ZHANG　Jin-song2
（1. School of Civil Engineering， Hunan University of Science and Technology， Xiangtan 411201， China； 2. Shenzhen Water Co. Ltd.， Shenzhen 518030， China）
关键词:
ASM2d;  数学模型;  参数集;  校核;  灵敏度分析
Keywords:
ASM2d;  mathematical model;  parameter set;  check;  sensitivity analysis
摘要:
针对ASM2d模型应用过程中需校核的参数多、数据量大、各参数之间相互影响等问题，提出了以灵敏度分析、参数集识别和目标函数求解为一体的模型参数集校核方法，并利用该方法对MSBR工艺的ASM2d模型参数进行了校核。结果表明，18 个模型参数会对模拟预测结果产生影响，其中12 个参数需要校核，包括3个化学计量数（YPAO、YH和YPO4）、9 个动力学参数（μAUT、bAUT、KNH4、bH、ηNO3、μPAO、bpp、bPAO和qpp）。对参数校核以后的模型进行动态模拟检验发现，出水SS、COD、NH4+-N、NO3--N、TP和TN的模拟值与实测值之间的平均相对偏差分别为6.0%、9.0%、15.7%、9.6%、14.9%和7.0%，但NH4+-N和TP的平均绝对误差仅为0.21和0.13 mg/L，模型具有较高的预测精度，证明该参数校核方法可行。
Abstract:
There are many parameters to check, large amount of data and mutual influence among parameters in the application of ASM2d model. To solve these problems, a model parameter set check method, which integrated sensitivity analysis, parameter set identification and objective function solution,was proposed and applied to check the parameters of MSBR process in ASM2d model. Eighteen model parameters affected the simulation prediction results, of which 12 parameters needed to be checked, including 3 stoichiometric parameters (YPAO, YH and YPO4) and 9 kinetic parameters (μAUT, bAUT, KNH4, bH, ηNO3, μPAO, bpp, bPAO and qpp). The model was tested by dynamic simulation after checking the parameters. The average relative deviations between the simulated values and measured values of SS, COD, NH4+-N, NO3--N, TP and TN were 6.0%, 9.0%, 15.7%, 9.6%, 14.9% and 7.0%, respectively, but the average absolute errors of NH4+-N and TP were only 0.21 mg/L and 0.13 mg/L, indicating that the model has high prediction accuracy and the parameter check method is feasible.

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更新日期/Last Update: 2022-06-01