Krist V. Gernaey

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This review paper focuses on modelling of wastewater treatment plants (WWTP). White-box modelling is widely applied in this field, with learning, design and process optimisation as the main applications. The introduction of the ASM model family by the IWA task group was of great importance, providing researchers and practitioners with a standardised set of(More)
The reliability of cellulose hydrolysis models is studied using the NREL model. An identifiability analysis revealed that only 6 out of 26 parameters are identifiable from the available data (typical hydrolysis experiments). Attempting to identify a higher number of parameters (as done in the original NREL model) results in significant errors on the(More)
This paper proposes a risk assessment model for settling problems of microbiological origin in activated sludge systems (filamentous bulking, foaming and rising sludge). The aim of the model is not to diagnose microbiology-related solids separation problems with absolute certainty but to quantify in dynamic scenarios whether simulated operational procedures(More)
  • Magnus Carlquist, Rita Lencastre Fernandes, Søren Helmark, Anna-Lena Heins, Luisa Lundin, Søren J Sørensen +2 others
  • 2012
BACKGROUND Traditionally average values of the whole population are considered when analysing microbial cell cultivations. However, a typical microbial population in a bioreactor is heterogeneous in most phenotypes measurable at a single-cell level. There are indications that such heterogeneity may be unfavourable on the one hand (reduces yields and(More)
The evaluation of activated sludge control strategies in wastewater treatment plants (WWTP) via mathematical modelling is a complex activity because several objectives; e.g. economic, environmental, technical and legal; must be taken into account at the same time, i.e. the evaluation of the alternatives is a multi-criteria problem. Activated sludge models(More)
Keywords: Uncertainty analysis Sensitivity analysis Stochastic optimization Bioethanol production Monte-Carlo simulations a b s t r a c t This study presents the development and application of a systematic model-based framework for bio-process optimization. The framework relies on the identification of sources of uncertainties via global sensitivity(More)