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生物反应器填埋场有机物预测模型及其参数不确定性分析

霍守亮, 樊石磊, 席北斗, 吕鉴

霍守亮, 樊石磊, 席北斗, 吕鉴. 生物反应器填埋场有机物预测模型及其参数不确定性分析[J]. 北京工业大学学报, 2008, 34(10): 1098-1104.
引用本文: 霍守亮, 樊石磊, 席北斗, 吕鉴. 生物反应器填埋场有机物预测模型及其参数不确定性分析[J]. 北京工业大学学报, 2008, 34(10): 1098-1104.
HUO Shou-liang, FAN Shi-lei, XI Bei-dou, LÜ Jian. Mathematical Model Simulating Organic Variation and Uncertainty Analysis in the Bioreactor Landfill[J]. Journal of Beijing University of Technology, 2008, 34(10): 1098-1104.
Citation: HUO Shou-liang, FAN Shi-lei, XI Bei-dou, LÜ Jian. Mathematical Model Simulating Organic Variation and Uncertainty Analysis in the Bioreactor Landfill[J]. Journal of Beijing University of Technology, 2008, 34(10): 1098-1104.

生物反应器填埋场有机物预测模型及其参数不确定性分析

基金项目: 

国家重点基础研究发展计划项目(2005CB724203).

详细信息
    作者简介:

    霍守亮(1981-),男,安徽霍邱人,助理研究员;吕鉴(1952-),男,江苏南京人,教授.

  • 中图分类号: X703

Mathematical Model Simulating Organic Variation and Uncertainty Analysis in the Bioreactor Landfill

  • 摘要: 为准确预测填埋场渗滤液有机污染物浓度,为填埋场的运行管理提供决策依据,以减少环境污染风险,根据质量守恒和有机物降解动力学原理,建立了填埋场中渗滤液有机物浓度动态变化模型,采用四阶经典Runge-Kutta算法对模型进行了求解,通过室内模拟实验对模型中参数进行了率定,并对模拟结果进行了效率评价和T检验.两填埋柱模拟效率系数分别为0.7766和0.9193,表明了实测值和模拟值具有较好的一致性.T检验的结果表明:模拟值和实测值没有显著性差异.鉴于获取数据的限制.对模型参数进行了敏感性分析,3个关键参数的敏感性指数依次为ki>kls>ksg,同时运用Monte Carlo方法对模型参数进行了不确定性分析,从而使模型能更加全面合理地模拟复杂多变的填埋过程.
    Abstract: The objective of this work is to develop a numerical model to stimulate organic variation accurately in the leachate,to provide support for landfill management,and to minimize the risks of environmental pollution.A mathematical model simulating organic variation in the leachate of bioreactor landfill was presented and demonstrated based on mass balance of contaminants and degradation kinetics.The model was solved numerically using a fourth-order Range-Kutta algorithm and the model parameters were validated by monitoring data.Efficiency assessment and T test were performed for simulating results,and the efficiency coefficients were respectively 0.776 6 and 0.919 3 for column 1 and column 2.T test result showed that the simulating results and monitoring data have no marked difference.Given the limitations in data capture,a sensitivity analysis was performed,highlighting the model's response to changes in input variables.The ensitivity index of k1 was more than that of kls,and it was the least for ksg Moreover,illustrative examples of the model's output are presented to demonstrate effects of data uncertainty on organic concentration by Monte Carlo method.Thus,the numerical model presented in paper can stimulate the organic variation accurately and comprehensively in the complexly changeful landfill.
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出版历程
  • 收稿日期:  2007-06-27
  • 网络出版日期:  2022-12-17

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