Biomedical subjects

A Abusam

Publications and source records attributed to A Abusam.

5 recordsLinked to original sources

PubMed2003

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↗

PubMed2002

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↗

PubMed2002

Modelling the competition between sulphate reducers and methanogens in a thermophilic methanol-fed bioreactor.

Sulphate can be removed from wastewater by means of biological anaerobic reduction to sulphide. The reduction requires the presence of a substrate that can serve as an electron donor. Methanol a suitable electron donor for sulphate reduction under thermophilic conditions. In an anaerobic system containing methanol and sulphate, acetogenic bacteria (AB) and methanogenic archaea (MA) compete with sulphate reducing bacteria (SRB) for methanol or its degradation intermediates. Previously obtained results indicate that at 65 degrees C SRB and MA mainly compete for the intermediate hydrogen instead of methanol. For efficient use of methanol as electron donor for sulphate reduction it is important that for the treatment of sulphate wastewater in an anaerobic reactor SRB out-compete MA. The mechanisms that determine the outcome of the competition are, however, not well understood. This paper describes a model based on growth kinetics of methanol-oxidising AB, and hydrogen-consuming SRB and MA, that can describe the competition between SRB and MA in a methanol-fed bioreactor. We present the model and its calibration using experimental data, and we discuss its shortcomings and suggest possible improvements.

Bioreactors↗

PubMed2001

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↗

PubMed2001

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↗