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Biomedical subjects

K J Keesman

Publications and source records attributed to K J Keesman.

8 recordsLinked to original sources

Forward and backward uncertainty propagation: an oxidation ditch modelling example.

In the field of water technology, forward uncertainty propagation is frequently used, whereas backward uncertainty propagation is rarely used. In forward uncertainty analysis, one moves from a given (or assumed) parameter subspace towards the corresponding distribution of the output or objective function. However, in the backward uncertainty propagation, one moves in the reverse direction, from the distribution function towards the parameter subspace. Backward uncertainty propagation, which is a generalisation of parameter estimation error analysis, gives information essential for designing experimental or monitoring programmes, and for tighter bounding of parameter uncertainty intervals. The procedure of carrying out backward uncertainty propagation is illustrated in this technical note by working example for an oxidation ditch wastewater treatment plant. Results obtained have demonstrated that essential information can be achieved by carrying out backward uncertainty propagation analysis.

Forecasting↗

Evaluation of control strategies using an oxidation ditch benchmark.

This paper presents validation and implementation results of a benchmark developed for a specific full-scale oxidation ditch wastewater treatment plant. A benchmark is a standard simulation procedure that can be used as a tool in evaluating various control strategies proposed for wastewater treatment plants. It is based on model and performance criteria development. Testing of this benchmark, by comparing benchmark predictions to real measurements of the electrical energy consumptions and amounts of disposed sludge for a specific oxidation ditch WWTP, has shown that it can (reasonably) be used for evaluating the performance of this WWTP. Subsequently, the validated benchmark was then used in evaluating some basic and advanced control strategies. Some of the interesting results obtained are the following: (i) influent flow splitting ratio, between the first and the fourth aerated compartments of the ditch, has no significant effect on the TN concentrations in the effluent, and (ii) for evaluation of long-term control strategies, future benchmarks need to be able to assess settlers' performance.

Benchmarking↗

Respirometry-based on-line model parameter estimation at a full-scale WWTP.

This paper describes part of a project to develop a systematic approach to knowledge extraction from on-line respirometric measurements in support of wastewater treatment plant control and operation. The paper deals with the following issues: (1) test of the implementation of an automatic set-up consisting of a continuous laboratory respirometer integrated in a mobile trailer with sampling and dosing equipment, and data-acquisition and communication system; (2) assessment of activated sludge/sewage characteristics from sludge respirograms by model parameter estimation; (3) comparison of the parameter estimates with regular plant data and information obtained from supplementary wastewater respirograms. The paper describes the equipment and some of its measuring results from a period of one week at a large-scale wastewater treatment plant. The measurements were evaluated in terms of the common activated sludge modelling practice. The automatic set-up allowed reliable measurements during at least one week. The data were used to calibrate two different version of the model, and independent parameter estimates were obtained.

Bioreactors↗

Oxygen transfer rate estimation in oxidation ditches from clean water measurements.

Standard methods for the determination of oxygen transfer rate are based on assumptions that are not valid for oxidation ditches. This paper presents a realistic and simple new method to be used in the estimation of oxygen transfer rate in oxidation ditches from clean water measurements. The new method uses a loop-of-CSTRs model, which can be easily incorporated within control algorithms, for modelling oxidation ditches. Further, this method assumes zero oxygen transfer rates (KLa) in the unaerated CSTRs. Application of a formal estimation procedure to real data revealed that the aeration constant (k = KLaVA, where VA is the volume of the aerated CSTR) can be determined significantly more accurately than KLa and VA. Therefore, the new method estimates k instead of KLa. From application to real data, this method proved to be more accurate than the commonly used Dutch standard method (STORA, 1980).

Fresh Water↗

Parameter estimation procedure for complex non-linear systems: calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch.

When applied to large simulation models, the process of parameter estimation is also called calibration. Calibration of complex non-linear systems, such as activated sludge plants, is often not an easy task. On the one hand, manual calibration of such complex systems is usually time-consuming, and its results are often not reproducible. On the other hand, conventional automatic calibration methods are not always straightforward and often hampered by local minima problems. In this paper a new straightforward and automatic procedure, which is based on the response surface method (RSM) for selecting the best identifiable parameters, is proposed. In RSM, the process response (output) is related to the levels of the input variables in terms of a first- or second-order regression model. Usually, RSM is used to relate measured process output quantities to process conditions. However, in this paper RSM is used for selecting the dominant parameters, by evaluating parameters sensitivity in a predefined region. Good results obtained in calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch proved that the proposed procedure is successful and reliable.

Automation↗

Endogenous model state and parameter estimation from an extensive batch experiment.

In this paper an extensive batch experiment of endogenous process behavior in an aerobic biodegradation process is presented. From these experimental data, comprising measurements of MLVSS (mixed liquor volatile suspended solids) and respiration rate, in a first step the states and unknown parameters in a four-compartmental model are reconstructed analytically. Subsequently, for a selected set of states and parameters, using the results of the previous step, a recursive state estimation procedure, in particular an Extended Kalman filter-based observer, is applied to deal with the noise properties of the data appropriately. From this it appears that the initially proposed model structure, and especially the hydrolysis term, has to be modified.

Aerobiosis↗

Analysis of endogenous process behavior in activated sludge.

In this article, an autonomous four-compartment model that describes the endogenous respiration in an aerobic biodegradation process is proposed and analyzed theoretically. First, the multi-time scale of the system's behavior, to be taken into account in subsequent analyses, is emphasized. Then, an identifiability and observability study, given measurements of MLVSS (mixed liquor volatile suspended solids) and respiration rate, is performed for use under practical circumstances, such as in state and parameter estimation. It appears that the process is observable, but not fully identifiable. Hence, for the identification of some of the model parameters, additional measurements or experiments, also indicated here, have to be performed. Furthermore, it is shown that, under quasi-steady state conditions which, in general, appear shortly after initialization of an endogenous respiration experiment, the model can be reduced significantly. Finally, results of parameter estimation from available data are presented and discussed.

Aerobiosis↗

Optimal parametric sensitivity control for the estimation of kinetic parameters in bioreactors.

In this paper the well-known problem of optimal input design is considered. In particular, the focus is on input design for the estimation of kinetic parameters in bioreactors. The problem is formulated as follows: given the model structure (f,g), which is assumed to be affine in the input, and the specific parameter of interest theta;(k) find a feedback law that maximizes the sensitivity of the model output to the parameter under different flow conditions in the bioreactor and, possibly, minimize the input or state costs. Analytical solutions to these problems are presented. As an example a bioreactor with a biomass that grows according to the well-known Monod kinetics is considered.

Bioreactors↗