On the issue of trend and noise in the estimation of extreme rainfall properties.

Up until today extreme rainfall properties are frequently applied in sewer design guidelines. Uncertainty in the estimation of such properties will hence directly influence the dimensions of sewers, structures and pumps. In this paper the issue of potential trend and noise in the estimation is investigated for 6 rain series ranging from 19 to 55 years in duration. Different to recent research that predicts a climate induced-increase in heavy precipitation no clear indication for such trend was found in the investigated historical rain series. Another important aspect is the length of the rain series that is required for the estimation of extreme rainfall properties and the associated uncertainty. The analysis indicates that at least a period of 10 years should be used for the estimation. But even so the possible deviation expressed in terms of the 90 percentile is in the order of 5 to 10% of the 'true value', defined as the value derived when the whole given series is used for the estimation.     

Robust vector control of induction motors using full-order observer in consideration of core loss

This paper proposes a method for designing a robust full-order observer for vector-controlled induction motors taking core loss into account. Although conventional research focuses on parameter identification, global stability of the identification remains questionable. Therefore, robustness against some parameters is required. This paper describes the design of a robust full-order observer which takes core loss into account, using both the gain-scheduled H/sub /spl infin// control and the linear matrix inequality technique. This design always results in a stable controller. The robustness of the proposed method against variations of resistances is evaluated by experiments.     

Knowledge-based control and case-based diagnosis based upon empirical knowledge and fuzzy logic for the SBR plant.

Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.     

Photocatalytic oxidation of low concentration 2,4-D solution with new TiO2 fiber catalyst in a continuous flow reactor.

Environmental pollution by low concentrations of 2,4-Dichlorophenoxyacetic acid (2,4-D) is a concern these days due to ever increasingly stringent regulations. Photocatalysis with immobilized TiO2 fiber is a promising oxidation method. Laboratory experiments on photocatalytic degradation of 0.045 mmol l(-1) 2,4-D with the world's first high-strength TiO2 fiber catalyst were carried out in a continuous flow reactor in which the degradations were, in general, similar to those with high 2,4-D concentrations investigated elsewhere. Degradation and mineralization of 2,4-D were significantly enhanced with no initial pH adjustments. The rate constants for total organic carbon (TOC) without pH adjustment were about two-fold bigger than the pH adjustment cases. CO2 gas measurement and carbon mass-balance were carried out for the first time, where about 34% organic carbon converted into CO2 gas during four-hour oxidation. 2,4-Dichlorophenol (2,4-DCP), phenol, benzyl alcohol and two unknowns (RT = 2.65 and 3.78 min.) were detected as aromatic intermediates while Phenol was the new aromatic in HPLC analysis. Dechlorination efficiencies were high (> 70%) in all the cases, and more than 90% efficiencies were observed in chloride mass balance. Bigger flow rates and solution temperature fixed at 20 degrees C without pH adjustment greatly enhanced 2,4-D mineralization. These results can be an important basis in applying the treatment method for dioxin-contaminated water and wastewater.     

On the effect of spatial variances in historical rainfall time series to CSO performance evaluation.

Historical, high-resolution rain series are the backbone of modern combined sewer overflow (CSO) structure design. These rain series are the input to the computational estimation of the performance of the measures with respect to CSO pollution abatement. However, those historical precipitation measurements are available at only a few locations. Frequently rain series have to be used from gauging stations at a significant distance. In order to judge and to compensate for this influence an estimate between rain characteristics and combined sewer outflow (CSO) performance indicators would be useful. In this paper such correlations have been sought for a collection of 37 rain series covering large areas of Europe. It was found that the mean annual rain volume can explain most of the variances for the performance indicators Number of overflows and CSO volume. For explaining the spatial differences in the efficiency of the CSO structure another rain characteristic, i.e. the maximum event with a return period of one year, is to be used.     

Efficient design and operation of a data acquisition system for pressurized pipeline systems.

The unsteady flow analysis of pipeline systems provides useful guidelines for implementing data acquisition components such as data filtering ranges, sensor locations and sampling frequencies. A theoretical integration among hydraulics, free vibration analysis and signal processing is proposed for a comprehensive approach aiming at enhanced design and operation of data acquisition system. Transient analysis is performed to extract flow variation by a valve modulation in a pipeline system. Frequency transformation analysis is developed to convert pressure variations between time domain and frequency domain. Free vibration analysis provides spatial distribution of impedance characteristics and pressure variation for determining optimum sensor location. A real-time filter can be designed to secure valid signals of any particular unsteady event. Hypothetical and experimental applications show that the proposed method has potentials of the leakage detection of a pipeline system as well as an efficient design of data acquisition system.