Advanced controlling of anaerobic digestion by means of hierarchical neural networks

In this work several feed-forward back propagation neural networks (FFBP) were trained in order to model, and subsequently control, methane production in anaerobic digesters. To produce data for the training of the neural nets, four anaerobic continuous stirred tank reactors were operated in steady-state conditions at organic loading rates (Br) of about 2 kg m(-3) d(-1) chemical oxygen demand, and disturbed by pulse-like increase of the organic loading rate. For the pulses additional carbon sources like flour, sucrose, 1,2-diethylen glycol or vegetable oil were added to the basic feed, which consisted of surplus and primary sludge of a local waste-water treatment plant, to increase the chemical oxygen demand. Measured parameters were: gas composition, methane production rate, volatile fatty acid concentration, pH, redox potential, volatile suspended solids and chemical oxygen demand of feed and effluent. A hierarchical system of nets was developed and embedded in a decision support system to find out which is the best feeding profile for the next time steps in advance. A 3-3-1 FFBP simulated the pH with a regression coefficient of 0.82. A 9-3-3 FFBP simulated the volatile fatty acid concentration in the sludge with a regression coefficient of 0.86. And a 9-3-2 FFBP simulated the gas production and gas composition with a regression coefficient of 0.90 and 0.80, respectively. A lab-scale anaerobic continuous stirred tank reactor controlled by this tool was able to maintain a methane concentration of about 60% at a rather high gas production rate of between 5 and 5.6 m3 m(-3) d(-1).     

Start‐up and recovery of a biogas‐reactor using a hierarchical neural network‐based control tool

Due to its intricate internal biological structure the process of anaerobic digestion is difficult to control. The aim of any applied process control is to maximize methane production and minimize the chemical oxygen demand of the effluent and surplus sludge production. Of special interest is the start‐up and adaptation phase of the bioreactor and the recovery of the biocoenose after a toxic event. It is shown that the anaerobic digestion of surplus sludge can be effectively modeled by means of a hierarchical system of neural networks and a prediction of biogas production and composition can be made several time‐steps in advance. Thus it was possible to optimally control the loading rate during the start‐up of a non‐adapted system and to recover an anaerobic reactor after a period of heavy organic overload. During the controlled period an optimal feeding profile that allowed a minimum loading rate of 6 kg COD m^?3 d^?1 to be maintained was found. Maximum loading rates higher than 12 kg COD m^?3 d^?1 were often reached without destabilizing the system. The control strategy resulted simultaneously in a high level of gas production of about 3 m³_biogas m^?3_reactor and a methane content in the biogas of about 70%. To visualize the effects of the control strategy on the reactor's operational space the data were processed using a data‐mining program based on Kohonen Self‐Organizing Maps. Copyright © 2003 Society of Chemical Industry     

History of the University Clinic of Dermatology and Venereology in Graz. A review of 125 years (1873-1998)

An outbreak of Serratia marcescens infections occurred in a university tertiary-care hospital. Alcohol-free chlorhexidine solutions were contaminated with S marcescens. The majority of patient and chlorhexidine strains had similar pulsed field-gel electrophoresis banding patterns. Chlorhexidine was recalled, and the rate of S marcescens isolation returned to baseline. Chlorhexidine without alcohol should not be used as an antiseptic.     

An integrated assessment of options for rural wastewater management in Austria.

This paper reports a recently finished, interdisciplinary project on rural wastewater management in Austria. The objective of the project was to study alternative wastewater management options based on separation of the wastewater into its constituent parts, and to compare them with conventional ones. Thereby, a feasibility study of both conventional and alternative options for wastewater management in six model regions was carried out. Life cycle costs and social acceptance were analysed by using a case study-based assessment approach. However, hygienic and environmental risks were evaluated on a more general level. In order to complement the findings, a survey on urine separation system users in the Solar City of Linz was conducted. Based on these assessments and empirical findings, the paper concludes that options using a full separation of all wastewater fractions should be considered with care. Options based on a separation of only grey water and black water or in the liquid/solid phase can offer ecological and financial advantages over conventional options. Further, options combining wastewater management and regional biogas plants were identified as an interesting solution. However, legal constraints restrict this option currently.