Hydraulic Modelling And Calibration Of The Upper Silesian Waterworks In Poland

Our paper presents the preliminary results of hydraulic modelling and calibration of a complex water transfer and distribution system of Upper Silesian Waterworks PLC (USW). A new approach to quasi real-time model calibration and validation in connection with an integrated ICT system will be presented. The USW is the biggest water company in Poland and one of the biggest in Europe delivering water to over 3 million customers in Silesian Metropolis, on the area covering about 4.3 thousand square kilometres, with the main water network which is over 880 km long. This water distribution system incorporates central and western sub-regions of Silesia (Silesian Metropolis) supplying water in the amount of about 400 000 m3/d. The USW water transportation system is a mix of pressure and gravity mains (with diameters ranging between 300 mm and 1800 mm) conveying the water to several local (municipal) distribution systems and bulk buyers (industrial). The area is characterised by a great diversity of terrain altitude, heavy concentration of industry and severe mining damages. This dynamic environment requires constant update of WDN topology and real-time water demand from wholesale customers (towns and cities, coal mines, steel, energy, automotive, machinery and chemical industry). For calibration and validation of hydraulic model we used the extensive telemetry system composed of 180 monitoring stations (including wholesale customers meters, reservoirs, tanks, pumping stations etc.). This system contains over 800 sensors measuring flow rate, pressure, turbidity and chlorine residual. The existing database of measurements will be temporarily supported by mobile measurement points used for identification of hydraulic properties of selected groups of pipelines. Hydraulic model (based on EPANET) is an element of the integrated ICT system for comprehensive water network management, consisting of several modules: GIS, CIS, SCADA as well as tools for multi-criteria optimisation and forecasting

Automated Meter Reading For Water Demand Forecast And Hydraulic Modelling Of The Municipal Water Distribution System In Mikołów, Poland

This paper presents preliminary results of a project aimed at utilising automated meter reading (AMR) system for water demand forecasting and hydraulic modelling of Mikołów (Poland) water distribution system. This system will allow for near-real time collection of hydraulic data. Accurate estimation and prediction of the demand patterns of the customers is a crucial element affecting accuracy of hydraulic model. AMR will be used to analyse the behaviour of individual household-based water consumption. Calibration and validation of the model will be realised by combining existing SCADA system and mobile (temporary) measurement points. Total length of the main water distribution system in Mikołów (pop. 40 000) is about 310 km, with 117 km of service pipelines. Water in amount of 300 000 m3 per month is supplied to over 7600 individual clients and bulk (industrial) customers. All connections to water network will be equipped with automated meter and incorporated into existing monitoring system. The existing telemetry system for Mikołów is composed of 30 stations measuring flow rate and pressure in the water distribution network (WDN). A hybrid AMR system will be used. It combines local reading of meters by two-way RF units with telemetry stations sending signals using mobile network (GSM) to the main database server. This server contains a database of water consumption readings for individual customers. To take advantage of the AMR system a detailed hydraulic model of the Mikołów WDN was build. The hydraulic model will be later coupled with an integrated ICT system for comprehensive management of the water distribution network. The seamless connection between model and GIS, CIS and SCADA modules will allow for the network topology update, automatic re-calibration, water demand reading and forecasting

Safety and efficacy of interferon-alfa2b (IFN) in the treatment of patients with mycosis fungoides

W niniejszej pracy przedstawiono własne, jednoośrodkowe doświadczenia dotyczące stosowania interferonu w pierwszej linii leczenia systemowego ziarniniaka grzybiastego. Badaniem objęto grupę chorych leczonych w Centrum Onkologii w Bydgoszczy, u których po wyczerpaniu możliwości leczenia miejscowego oraz w stopniu zaawansowania Ib–III podjęto terapię systemową. Maksymalny czas prowadzenia terapii sięgał 3 lat. Interferon alfa jest leczeniem dobrze tolerowanym, skutkującym poprawąjakości życia u 80% chorych. Lek ten powoduje znaczną bądź całkowitą remisję trwającą do kilkunastu miesięcy. Terapia ziarniniaka grzybiastego jest leczeniem choroby przewlekłej, co wpływa na zasady prowadzenia terapii.This paper reports our own experience on interferon-alpha as the first-line systemic treatment of mycosis fungoides in the group of patients with advanced stages of disease after failure of skin-directedtherapies. Therapy resulted in improved quality of life and long-lasting, high response rate up to 80%. Given chronic character of MF special account must be taken not only to efficacy of the therapy, but also the safety

Conditions for the solvability of a nonlinear boundary value problem of the flow of a viscous fluid

.The author presents a discussion of existence, uniqueness and convergence of finite difference approximations for Navier-Stokes equations with convection in a two-dimensional rectangle with sufficiently small data

Computer aided management of communal waterworks

W artykule omówiono aktualny stan informatyzacji w krajowych przedsiębiorstwach wodociągowych i trendy rozwojowe w tym zakresie, podano możliwości względnie szybkiego usprawnienia zarządzania przedsiębiorstwami wodociągowymi za pomocą nowoczesnych technik i technologii informatycznych oraz zaprezentowano koncepcję zintegrowanego systemu informatycznego zarządzania siecią wodociągową opracowaną w Instytucie Badań Systemowych PAN (IBS PAN) i wdrażaną w kilku krajowych przedsiębiorstwach wodociągowych.In the paper the actual state of computerization of Polish communal waterworks and the existing trends in this area are described. Also the capabilities to change the present unsatisfied situation by means of modern ict techniques are proposed and the concept and computer realization of an ict system for complex management of communal water networks are presented. The system has been developed at the systems research institute of Polish Academy of sciences and it is tested or implemented currently in some Polish waterworks

Control of Pumps of Water Supply Network under Hydraulic and Energy Optimisation Using Artificial Intelligence

This article presents several algorithms for controlling water supply system pumps. The aim of having control is the hydraulic optimisation of the network, i.e., ensuring the desired pressure in its recipient nodes, and minimising energy costs of network operation. These two tasks belong to the key issues related to the management and operation of water supply networks, apart from the reduction in water losses caused by network failures and ensuring proper water quality. The presented algorithms have been implemented in an Information and Communications Technology (ICT) system developed at the Systems Research Institute of the Polish Academy of Sciences (IBS PAN) and implemented in the waterworks GPW S.A. in Katowice/Poland

Modelling the Steady State of Sewage Networks as a Support Tool for Their Planning and Analysis

Fundamental questions connected with the modelling of communal sewage networks have been considered and formulas used to model the functioning of the basic network have been analyzed. The problem described concerns gravitational sewage networks divided by nodes into branches and sectors. Simulation of the steady state functioning of sewage networks is commonly carried out on the basis of nomograms in the form of charts, in which the relations between network parameters like channel diameters, flow rates, hydraulic slopes and flow velocities are described. In traditional design, the values of such parameters are simply read from such nomogram chart tables. Another way of simulating the functioning of a network is the use of professional software, like SWMM, that models sewage flows along the channels by means of differential equations de-scribing the movement of fluids. In both approaches, the user is a mechanical operator of a "black box" procedure. In this paper, another way of simulating the functioning of sewage net-works has been presented. Numerical solutions of nonlinear equations describing the physical phenomena of sewage flows are applied and explained. The presented algorithms were developed to model the steady state of a sewage network enabling a quick analysis of the network parameters and the possibility of fast, simple and comprehensible network modeling and design. (original abstract

Prediction of wastewater quality indicators at the inflow to the wastewater treatment plant using data mining methods

In the study, models developed using data mining methods are proposed for predicting wastewater quality indicators: biochemical and chemical oxygen demand, total suspended solids, total nitrogen and total phosphorus at the inflow to wastewater treatment plant (WWTP). The models are based on values measured in previous time steps and daily wastewater inflows. Also, independent prediction systems that can be used in case of monitoring devices malfunction are provided. Models of wastewater quality indicators were developed using MARS (multivariate adaptive regression spline) method, artificial neural networks (ANN) of the multilayer perceptron type combined with the classification model (SOM) and cascade neural networks (CNN). The lowest values of absolute and relative errors were obtained using ANN+SOM, whereas the MARS method produced the highest error values. It was shown that for the analysed WWTP it is possible to obtain continuous prediction of selected wastewater quality indicators using the two developed independent prediction systems. Such models can ensure reliable WWTP work when wastewater quality monitoring systems become inoperable, or are under maintenance

Prediction of wastewater quality indicators at the inflow to the wastewater treatment plant using data mining methods

In the study, models developed using data mining methods are proposed for predicting wastewater quality indicators: biochemical and chemical oxygen demand, total suspended solids, total nitrogen and total phosphorus at the inflow to wastewater treatment plant (WWTP). The models are based on values measured in previous time steps and daily wastewater inflows. Also, independent prediction systems that can be used in case of monitoring devices malfunction are provided. Models of wastewater quality indicators were developed using MARS (multivariate adaptive regression spline) method, artificial neural networks (ANN) of the multilayer perceptron type combined with the classification model (SOM) and cascade neural networks (CNN). The lowest values of absolute and relative errors were obtained using ANN+SOM, whereas the MARS method produced the highest error values. It was shown that for the analysed WWTP it is possible to obtain continuous prediction of selected wastewater quality indicators using the two developed independent prediction systems. Such models can ensure reliable WWTP work when wastewater quality monitoring systems become inoperable, or are under maintenance

Modeling of Heavy Metal (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and PAH Content in Stormwater Sediments Based on Weather and Physico-Geographical Characteristics of the Catchment-Data-Mining Approach

The processes that affect sediment quality in drainage systems show high dynamics and complexity. However, relatively little information is available on the influence of both catchment characteristics and meteorological conditions on sediment chemical properties, as those issues have not been widely explored in research studies. This paper reports the results of investigations into the content of selected heavy metals (Ni, Mn, Co, Zn, Cu, Pb, and Fe) and polycyclic aromatic hydrocarbons (PAHs) in sediments from the stormwater drainage systems of four catchments located in the city of Kielce, Poland. The influence of selected physico-geographical catchment characteristics and atmospheric conditions on pollutant concentrations in the sediments was also analyzed. Based on the results obtained, statistical models for forecasting the quality of stormwater sediments were developed using artificial neural networks (multilayer perceptron neural networks). The analyses showed varied impacts of catchment characteristics and atmospheric conditions on the chemical composition of sediments. The concentration of heavy metals in sediments was far more affected by catchment characteristics (land use, length of the drainage system) than atmospheric conditions. Conversely, the content of PAHs in sediments was predominantly affected by atmospheric conditions prevailing in the catchment. The multilayer perceptron models developed for this study had satisfactory predictive abilities; the mean absolute error of the forecast (Ni, Mn, Zn, Cu, and Pb) did not exceed 21%. Hence, the models show great potential, as they could be applied to, for example, spatial planning for which environmental aspects (i.e., sediment quality in the stormwater drainage systems) are accounted