Development of a forecasting system for supporting remediation design and process control based on NAPL-biodegradation simulation and stepwise-cluster analysis

摘要: [1] Effective process control is crucial in implementing remediation actions for petroleum-contaminated sites. However, dealing with situ bioremediation practices, difficulties exist incorporating numerical simulation models that are needed forecasting within real-time non-linear optimization frameworks critical supporting the control. With such difficulties, it desired a statistical relationship between system performance and operating condition be established. Nevertheless, systems, many variables can either continuous or discrete, relations among them linear non-linear. These lead to complexities related multivaraite analyses. In this study, has been developed design based on techniques of NAPL-biodegradation (non-aqueous phase liquid biodegradation) stepwise-cluster analysis (SCA). The results indicate effective effects multiple cleanup under various conditions. predicted benzene concentrations have acceptable error levels compared outputs simulation. An model obtaining optimum conditions then proposed illustrate how SCA method used operations. A unique contribution research development multivariate inference associated efforts tackling complex practices.