A Global Sensitivity Analysis Methodology for Anaerobic Digestion Models
through Functional Principal Components Projection
Abstract
Sensitivity analysis (SA) for the influence of model parametric
constants has been integral in the use of mathematical kinetic models
for design and operation of various anaerobic digestion applications.
Using Anaerobic Digestion Model No. 1 (ADM1) as case study, this work
aimed to broaden the approach for SA on the time-dependent model outputs
of anaerobic digestion models by demonstrating the use of functional
principal component analysis (fPCA) scores as input analysis variables
into global SA (GSA) for the influence of stoichiometric parameters in
ADM1. The methodology involved the following: Morris’ screening design
as the GSA technique; ADM1 biomass yield and product yield coefficients
as GSA parameters; and ADM1 outputs transformation via fPCA to generate
principal component (PC) scores for GSA. Results indicate that 95-99%
of the variations in the time-dependent outputs can be captured by the
PCs after fPCA transformation, and that the first PC is sufficient to
represent the model outputs. Ranked Morris sensitivity indices
calculated from the first PC scores revealed the stoichiometric
parameters that dominantly affect kinetic responses and those that are
least sensitive. The ranking of stoichiometric sensitivities can be used
for various purposes including driving mechanisms identification, and
mathematical model modification.