Reduced basis method for managed pressure drilling based on a model with local nonlinearities

To circumvent restrictions of conventional drilling methods, such as slow control actions and inability to drill depleted reservoirs, a drilling method called managed pressure drilling (MPD) has been developed. In MPD, single-phase flow processes can be modeled as a feedback interconnection of a high-order linear system and a low-order nonlinear system. These nonlinearities appear locally both inside and at the boundaries of the computational domain. To obtain a fast simulation platform for real-time purposes (eg, online model-based controller implementation), model order reduction is required for MPD. However, the local nonlinearities render applying model order reduction techniques challenging. In this study, a new approach is proposed to deal with such nonlinearities within the reduced basis (RB) context and it is successfully tested on a model for MPD. Contrary to the classical RB technique, the proposed approach not only does not generate nonphysical spikes at the locations of these local nonlinearities but also yields high speedup factors. The obtained reduced-order model can be used for efficient online simulation and controller design for drilling systems with MPD.     

Microbial community structure in activated sludge floc analysed by fluorescence in situ hybridization and its relation to floc stability

The efficiency of activated sludge treatment plants is dependent on the solid-liquid separation properties of the activated sludge. A critical parameter is the stability of the microbial flocs. Weak flocs deflocculate easily leaving increased concentrations of suspended solids in the effluent. The knowledge about how different bacteria are attached to the flocs and their influence on the bioflocculation is limited. In this study, the deflocculation of different phylogenetic groups of bacteria in activated sludge from a full scale plant was investigated. The experiments were carried out by using a shear method where the sludge flocs are deflocculated under controlled shear conditions. The degree of deflocculation was measured as increase in turbidity of the supernatant. Identification and quantification of the microbial community structure of both total activated sludge and deflocculated bacteria were conducted with group-specific gene probes for broad groups of bacteria (Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria and Actinobacteria) and fluorescence in situ hybridization (FISH). The microbial community structure of the deflocculated bacteria was different compared to the total activated sludge with a higher abundance of Gammaproteobacteria in the supernatant indicating that different groups of bacteria are bound with different strength to the floc surface. The results show that the bacteria in the outer parts of the flocs are relatively loosely bound to the floc matrix and can be easily eroded from the surface when exposed to shear.     

Flocculation of activated sludge flocs by stimulation of the aerobic biological activity

Activated sludge flocs are known to deflocculate under short-term anaerobic conditions, but little is known about possible reflocculation under subsequent aerobic conditions. When activated sludge flocs from two wastewater treatment plants deflocculated under anaerobic conditions with well-defined shear conditions, they could be almost, but not completely, reflocculated by aeration for 1-2 h under the same shear conditions. If the biological activity was reduced by adding azide, chloramphenicol or by decreasing the temperature, no or only very little reflocculation took place. This indicated that the reflocculation was under direct or indirect microbial control. Only a small part of the reflocculation was due to improved flocculation properties obtained by oxidation of Fe(II) to Fe(III), which is a better flocculant. Fe(II) was produced under the anaerobic conditions by microbial iron reduction, and it was oxidized to Fe(III) within less than one hour after the aeration was started. However, by comparing two different sludges with different capabilities for iron reduction, iron oxidation and responses to substrate addition, it was found that the aerobic biological activity most likely was of greatest significance for the observed reflocculation and floc formation under aerobic conditions. This was further supported by adding organic substrates (glucose or ethanol) during the aerobic reflocculation phase, which promoted reflocculation. However, some substrates had the opposite effect (acetate and lactate), where a deterioration of the reflocculation was observed, probably due to different responses from different groups of microorganisms in the sludges.     

Singular perturbation theory and its application to the computation of electromagnetic fields

In the past decade the theory of singular perturbations has been well-established. The techniques developed to solve singular perturbation problems were succesfully applied to practical problems. In this paper we will give a brief survey of singular perturbation theory and discuss a possible application to the computation of electromagnetic fields.     

Dynamics in maximal settling capacity in an activated sludge treatment plant with highly loaded secondary settlers.

Secondary settling dynamics at maximal capacity were investigated at a full scale wastewater treatment plant which utilizes a unique process solution incorporating pre-denitrification with post-nitrification in nitrifying trickling filters. Since nitrogen removal is greater when more secondary effluent is recirculated to the trickling filters, the secondary settlers generally operate at close to their maximal capacity. The settling and flocculation properties of the activated sludge are therefore a major capacity-determining factor for plant operation. Due to the short sludge age, the flocculation properties, with respect to both thickening and clarification, can change quickly. The dynamics in these changes were studied and the factors that determine the maximal settling capacity were assessed. Solids flux curves were constructed from batch settling tests and compared with the actual maximal settling capacities.     

Mining process models with non-free-choice constructs

Process mining aims at extracting information from event logs to capture the business process as it is being executed. Process mining is particularly useful in situations where events are recorded but there is no system enforcing people to work in a particular way. Consider for example a hospital where the diagnosis and treatment activities are recorded in the hospital information system, but where health-care professionals determine the “careflow.” Many process mining approaches have been proposed in recent years. However, in spite of many researchers’ persistent efforts, there are still several challenging problems to be solved. In this paper, we focus on mining non-free-choice constructs, i.e., situations where there is a mixture of choice and synchronization. Although most real-life processes exhibit non-free-choice behavior, existing algorithms are unable to adequately deal with such constructs. Using a Petri-net-based representation, we will show that there are two kinds of causal dependencies between tasks, i.e., explicit and implicit ones. We propose an algorithm that is able to deal with both kinds of dependencies. The algorithm has been implemented in the ProM framework and experimental results shows that the algorithm indeed significantly improves existing process mining techniques.     

Decomposing Petri nets for process mining: A generic approach

The practical relevance of process mining is increasing as more and more event data become available. Process mining techniques aim to discover, monitor and improve real processes by extracting knowledge from event logs. The two most prominent process mining tasks are: (i) process discovery: learning a process model from example behavior recorded in an event log, and (ii) conformance checking: diagnosing and quantifying discrepancies between observed behavior and modeled behavior. The increasing volume of event data provides both opportunities and challenges for process mining. Existing process mining techniques have problems dealing with large event logs referring to many different activities. Therefore, we propose a generic approach to decompose process mining problems. The decomposition approach is generic and can be combined with different existing process discovery and conformance checking techniques. It is possible to split computationally challenging process mining problems into many smaller problems that can be analyzed easily and whose results can be combined into solutions for the original problems.     

Metal catalyzed free radical copolymerization of allyl chloroacetate and N-propyl maleimide: a mass spectrometry study

Summary The copolymerization of allyl chloroacetate (ACAc) and N-propyl maleimide (PMI), catalyzed by Cu(I)Br or ferric(III) acetylacetonate (Fe(acac)₃) at 110°C, respectively, was studied through electron-impact mass spectrometry. Both Cu(I)Br and Fe(acac)₃ catalyzed the copolymerization by an atom transfer process. However, the copolymerization of ACAc and PMI was not in an alternative way, because propyl maleimide has high tendency to form homogeneous polymeric segments under the conditions of this work. Received: 7 March 2002 /Revised: 20 June 2002/ Accepted: 1 July 2002