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Assessment of municipal solid waste settlement models based on field-scale data analysis.

机译:基于现场规模数据分析的城市固体废物沉降模型评估。

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摘要

An evaluation of municipal solid waste (MSW) settlement model performance and applicability was conducted based on analysis of two field-scale datasets: (1) Yolo and (2) Deer Track Bioreactor Experiment (DTBE). Yolo data were used to assess a multi-layer immediate settlement analysis and model applicability to represent compression behavior in conventional and bioreactor landfills. The DTBE included four waste layers constituting a composite waste thickness. Settlement data for each waste layer were simulated to assess variation in model parameters, and a composite waste settlement prediction was completed via applying average DTBE model parameters to each waste layer and summing settlement to represent measured settlement at the top of the waste column.;The multi-layer immediate settlement analysis developed for Yolo provides a framework to estimate the initial waste thickness and waste thickness at end-of-immediate compression. An empirical estimate of the immediate compression ratio (Cc' = 0.23) combined with precompression stress (10 to 15 kPa) and recompression ratio = 1/10·Cc' yielded the target immediate settlement for the Yolo test cells. A precompression stress and recompression ratio may need to be included when using empirical estimates of Cc' to predict under small vertical stress (e.g., less than 15 kPa).;Simulation of the Yolo test cells with all settlement models via least squares optimization yielded high coefficient of determinations ( R2 > 0.83). However, empirical models (power creep, logarithmic, and hyperbolic) are not recommended for use in MSW settlement modeling due to non-representative long-term MSW behavior, limited physical significance of model parameters, and the requirement of measured data to determine model parameters.;Settlement models that combine mechanical creep and biocompression into a single mathematical function (i.e., Gibson and Lo and Chen-2010) are formulated to constrain all time-dependent settlement to a single process with finite magnitude, which limits model applicability. Overall, all other models used in this analysis, which either have the capability to simulate complete MSW compression behavior (Sowers, Marques, Babu, Chen-2012) or where an immediate compression component can be added to the model (Gourc and Machado), were shown to provide accurate simulations and predictions of field-scale datasets.;The Gourc model included the lowest number of total and optimized model parameters and yielded high statistical performance for the DTBE prediction (R2 = 0.99). The Gourc model was also found to be the most applicable and straightforward to implement and is recommended for use in practice. All other models that included unique functions for immediate compression, mechanical creep, and biocompression (Machado, Sowers, Marques, Babu, and Chen-2012) are capable of yielding satisfactory MSW simulations and predictions; however, additional model and/or model constraints are necessary for implementing these models.
机译:基于两个现场规模的数据集:(1)Yolo和(2)鹿径生物反应器实验(DTBE),对城市固体废物(MSW)沉降模型的性能和适用性进行了评估。 Yolo数据用于评估多层立即沉降分析和模型适用性,以代表常规和生物反应器垃圾填埋场的压缩行为。 DTBE包括四个废物层,构成了复合废物的厚度。模拟每个废物层的沉降数据以评估模型参数的变化,并通过将平均DTBE模型参数应用于每个废物层并汇总沉降量以表示废物柱顶部的测量沉降量来完成复合废物沉降预测。为Yolo开发的多层立即沉降分析提供了一个框架,用于估算初始废物厚度和即时压缩结束时的废物厚度。对即时压缩比(Cc'= 0.23)结合预压缩应力(10至15 kPa)和再压缩比= 1/10·Cc'的经验估计得出了Yolo测试电池的目标即时沉降。当使用Cc'的经验估计值来预测较小的垂直应力(例如,小于15 kPa)时,可能需要包括预压缩应力和再压缩比。通过最小二乘法优化对所有沉降模型的Yolo测试单元进行模拟得出的结果很高确定系数(R2> 0.83)。但是,不建议将经验模型(幂蠕变,对数和双曲线)用于MSW沉降建模中,因为长期的MSW行为不具有代表性,模型参数的物理意义有限,并且需要确定模型参数的实测数据制定了将机械蠕变和生物压缩结合到单个数学函数中的沉降模型(即Gibson和Lo和Chen-2010),以将所有与时间相关的沉降限制在单个过程中,且幅度有限,这限制了模型的适用性。总体而言,此分析中使用的所有其他模型都具有模拟完整的MSW压缩行为的能力(Sowers,Marques,Babu,Chen-2012),或者可以在模型中添加立即压缩分量(Gourc和Machado),可以显示出准确的模拟结果和现场规模数据集的预测结果。Gourc模型包括最少的总体参数和优化的模型参数,并且在DTBE预测方面具有很高的统计性能(R2 = 0.99)。还发现Gourc模型是最适用且最容易实现的模型,建议在实践中使用。所有其他模型都具有即时压缩,机械蠕变和生物压缩的独特功能(Machado,Sowers,Marques,Babu和Chen-2012),能够产生令人满意的城市固体废弃物模拟和预测。但是,实现这些模型需要附加的模型和/或模型约束。

著录项

  • 作者

    Kwak, Seungbok.;

  • 作者单位

    Colorado State University.;

  • 授予单位 Colorado State University.;
  • 学科 Engineering Civil.
  • 学位 M.S.
  • 年度 2014
  • 页码 84 p.
  • 总页数 84
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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