Application of statistical methods and process models for the design and analysis of activated sludge wastewater treatment plants (WWTPs)
Abstract (Summary)
The purpose of this study is to investigate statistical procedures to qualify uncertainty,
and explicitly evaluate its impact on wastewater treatment plants (WWTPs). The goal is
to develop a statistical-based procedure to design WWTPs that provide reliable protection
of water quality, instead of making overly conservative assumptions and adopting
empirical safety factors. An innovative Monte Carlo based procedure was developed to
quantify the risk of violating effluent as a function of various design decisions. A
simulation program called StatASPS was developed to conduct Monte Carlo simulations
combined with the ASM1 model.
A random influent generator was developed to describe the statistical characteristics of
the influent components of WWTPs. Prior to modeling, a two-directional exponential
smoothing (TES) method was developed to replace those non-randomly missing data
during weekends and holidays. The best models were selected based on various statistics
and the ability to forecast future values. The time series models were then used to
generate random influent variables with the same statistical characteristics as the original
data.
The best Monte Carlo simulations were conducted using historical influent data and sitespecific
parameter distributions, according to the applications to both the Oak Ridge and
Seneca WWTPs. This indicates that parameter uncertainty was more effective in
predicting uncertainty in plant performance than influent variability. The ultimate
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simulations were conducted using one-month’s influent data, considering limitations of
computing technologies. Application of the method to the two plants demonstrated that
this method provided a reliable and reasonable estimate of the uncertainty of plant
performance. The best predictions of plant uncertainty were obtained by determining the
distribution for the most sensitive parameter and holding all other model parameters
constant.
The StatASPS procedure proved to be a reliable and reasonable method to design costeffective
WWTPs. With further development, this procedure could provide engineers and
regulators with a high degree of confidence that the plant will perform as required,
without resorting to overly conservative assumptions or large safety factors.
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Bibliographical Information:
Advisor:
School:The University of Tennessee at Chattanooga
School Location:USA - Tennessee
Source Type:Master's Thesis
Keywords:
ISBN:
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