A framework for good biofilm reactor modeling practice (GBRMP)

Bruce E. Rittmann, Joshua P. Boltz, Doris Brockmann, Glen T. Daigger, Eberhard Morgenroth*, Kim Helleshøj Sørensen, Imre Takács, Mark Van Loosdrecht, Peter A. Vanrolleghem

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

38 Citations (Scopus)

Abstract

A researcher or practitioner can employ a biofilm model to gain insight into what controls the performance of a biofilm process and for optimizing its performance. While a wide range of biofilmmodeling platforms is available, a good strategy is to choose the simplest model that includes sufficient components and processes to address the modeling goal. In most cases, a onedimensional biofilm model provides the best balance, and good choices can range from handcalculation analytical solutions, simple spreadsheets, and numerical-method platforms. What is missing today is clear guidance on how to apply a biofilm model to obtain accurate and meaningful results. Here, we present a five-step framework for good biofilm reactor modeling practice (GBRMP). The first four steps are (1) obtain information on the biofilm reactor system, (2) characterize the influent, (3) choose the plant and biofilm model, and (4) define the conversion processes. Each step demands that the model user understands the important components and processes in the system, one of the main benefits of doing biofilm modeling. The fifth step is to calibrate and validate the model: System-specific model parameters are adjusted within reasonable ranges so that model outputs match actual system performance. Calibration is not a simple 'by the numbers' process, and it requires that the modeler follows a logical hierarchy of steps. Calibration requires that the adjusted parameters remain within realistic ranges and that the calibration process be carried out in an iterative manner. Once each of steps 1 through 5 is completed satisfactorily, the calibrated model can be used for its intended purpose, such as optimizing performance, trouble-shooting poor performance, or gaining deeper understanding of what controls process performance.

Original languageEnglish
Pages (from-to)1149-1164
Number of pages16
JournalWater Science and Technology
Volume77
Issue number5
DOIs
Publication statusPublished - 1 Mar 2018

Keywords

  • Biofilm
  • Framework
  • Good practice
  • Modeling
  • Reactor

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