Experimental and artificial neural network approach for forecasting of traffic air pollution in urban areas: The case of subotica

In the recent years, artificial neural networks have been used to predict the concentrations of various gaseous pollutants in ambient air, mainly to forecast mean daily particle concentrations. The data on traffic air pollution, irrespective of whether they are obtained by measuring or modeling, represent an important starting point for planning effective measures to improve air quality in urban areas. The aim of this study was to develop a mathematical model for predicting daily concentrations of air pollution caused by the traffic in urban areas. For the model development, experimental data have been collected for 10 months, covering all four seasons. The data about hourly concentration levels of suspended particles with aerodynamic diameter less than 10 μm (PM10) and meteorological data (temperature, air humidity, speed and direction of wind), measured at the measuring station in the town of Subotica from June 2008 to March 2009, served as the basis for developing an artificial neural networks based model for forecasting mean daily concentrations of PM10

Influence of ambience temperature and operational-constructive parameters on landfill gas generation - Case study Novi Sad

Researches in the area of landfill gas generation and energy utilization are currently underway and widespread in the world for several reasons: reducing effects of greenhouse gases, possibilities for utilizing alternative energy sources, reducing conventional energy resources exploitation, and environmental protection. First part of this research is conducted with an aim to establish the influence of meteorological parameters, primarily ambience temperature, on the methane generation processes at Novi Sad landfill. The second part of the research refers to functional characteristics of landfill such as the waste age, closing practice, and the age of certain parts of landfill body, as well as the waste depth and quantity of generated methane. Based on several years of investigation, it is concluded that methane generation varies in the range of 0-34 vol. % m3/m3, and that seasonal variations have significant influence on methane generation. At low temperatures, during winter, methane generation and migration is stagnant while in summer periods, due to higher temperatures, the process of methane generation is more intensive

Finite element analysis of devitalized teeth

Elimination of a large part of dental tissues during root canal treatment affects the mechanical behavior of devitalized teeth. The present study addresses how much dentin removal affects changes in mechanical behaviors of the intact tooth and tooth with root canal treatment. In order to estimate the tooth weakening, we performed aн experimental assessment of critical force and numerical Finite Element Method (FEM) analysis with the intention to analyze stresses distributions. The results showed that root canal treatment had significant influence on stress distributions. By analysis of retrieved results, it is concluded that this study is an efficient framework which could be applied in a number of different cases, so that practitioners could analyze and prepare the treatment with more certainty.Publishe

Trauma of the frontal region is influenced by the volume of frontal sinuses. A finite element study

Anatomy of frontal sinuses varies individually, from differences in volume and shape to a rare case when the sinuses are absent. However, there are scarce data related to influence of these variations on impact generated fracture pattern. Therefore, the aim of this study was to analyse the influence of frontal sinus volume on the stress distribution and fracture pattern in the frontal region. The study included four representative Finite Element models of the skull. Reference model was built on the basis of computed tomography scans of a human head with normally developed frontal sinuses. By modifying the reference model, three additional models were generated: a model without sinuses, with hypoplasic, and with hyperplasic sinuses. A 7.7 kN force was applied perpendicularly to the forehead of each model, in order to simulate a frontal impact. The results demonstrated that the distribution of impact stress in frontal region depends on the frontal sinus volume. The anterior sinus wall showed the highest fragility in case with hyperplasic sinuses, whereas posterior wall/inner plate showed more fragility in cases with hypoplasic and undeveloped sinuses. Well-developed frontal sinuses might, through absorption of the impact energy by anterior wall, protect the posterior wall and intracranial contents.This work was supported in part by grants from the Serbian Ministry of Education, Science and Technological Development III45005, III41007, ON174028 and EU project FP7 ICT SIFEM 600933

A GIS based technique for determination of optimal number and spatial location of waste bins - case study of Kragujevac

This paper concerns the development of a methodology aimed at determination of optimal number of waste bins as well as their spatial locations. The methodology used was based on Geographic information system which handled different sets of information, such as street direction, spatial location of objects and number of inhabitants, location of waste bins and radius of coverage. The study was conducted on a district in a center of the City of Kragujevac. The results indicated reduction of 24% in number of collection points and 33,4% in number of waste bins without reducing the quality of provided services. It has led to costs and time savings for waste collection and also to environmental benefits.Publishe

METHODOLOGY FOR REDUCTION OF GHG EMISSIONS FROM MUNICIPAL SOLID WASTE COLLECTION AND TRANSPORT

Collection and transport of municipal solid waste (MSW), as a part of solid waste management, have a great environmental impact due to exhaust emissions from fuel combustion. Distance traveled appears as one of the most influencing parameter in total fuel consumed. This paper presents a general methodology for route optimization using Geographic Information System (GIS). The necessary databases were created and established methodology was applied to waste collection and transport system in the city of Kragujevac. Using GIS software one typical route was optimized. Furthermore, fuel consumption and associated exhaust emissions vary in different waste collection and transport stages. Waste collection and transport circuit was divided into four different stages. The estimation of Greenhouse Gas (GHG) emissions for optimized route was made and compared to estimated emissions of current route. Calculations, which also include vehicle speed as very important parameter, indicated great savings in GHG emissions

Energetsko-ekološke performanse optimizovanog sistema za sakupljanje čvrstog otpada

Sakupljanje i transport cvrstog otpada u urbanim sredinama predstavlja veoma teiak i komplikovan problem. Upravo ove funkcije sistema za upravljanje evrstim otpadom ucestvuju sa najvećim udelom u ukupnim troškovima samog sistema. Cilj ovog istraživanja je određivanje energetskih i ekoloskih performansi sistema za upravljanje čvrstim otpadom grada Kragujevca i mogućnosti njihovih unapređenja putem optimizacije putanja kretanja komunalnih vozila.Formirane su odgovarajuće baze podataka na nivou GIS zahteva i razvijena nova metodologija za optimizaciju. GIS softverskim paketom detaljno su analizirane sve putanje komunalnih vozila i kao rezultat dobijena je ušteda od 14% u ukupnom pređenom putu. lmajući u vidu da su komunalna vozila veliki zagađivači životne sredine, ostvarene uštede,pored ekonomskih, imaju i veliki ekološki značaj. Korišcenjem metodologije "procene životnog veka" ( LCA - Life Cycle Assessment) urađena je uporedna analiza uticaja na životnu sredinu postojeceg i optimizovanog sistema za, sakupljanje i transport otpada.Publishe

Experimental and artificial neural network approach for forecasting of traffic air pollution in urban areas: The case of Subotica

In the recent years, artificial neural networks (ANNs) have been used to predict the concentrations of various gaseous pollutants in ambient air, mainly to forecast mean daily particle concentrations. The data on traffic air pollution, irrespective of whether they are obtained by measuring or modelling, represent an important starting point for planning effective measures to improve air quality in urban areas. The aim of this study was to develop a mathematical model for predicting daily concentrations of air pollution caused by the traffic in urban areas. For the model development, experimental data have been collected for 10 months, covering all four seasons. The data about hourly concentration levels of suspended particles with aerodynamic diameter less than 10 μm (PM10) and meteorological data (temperature, air humidity, speed and direction of ind), measured at the measuring station in the town of Subotica from June 2008 to March 2009, served as the basis for developing an ANN-based model for forecasting mean daily concentrations of PM10. The quality of the ANN model was assessed on the basis of the statistical parameters, such as RMSE, MAE, MAPE, and r

Simulacija radnih karakteristika hidrauličkih turbomašina

In this paper an accurate and efficient numerical algorithm for simulation of three-dimensional turbomachinery flows is presented. This model is used later for turbomachinery performance prediction. Mathematical model is based on the RANS equations that are written in non-inertial frame of reference. Reynolds stresses are approximated with Boussinesq hypothesis using two-equation k-ω near-wall turbulence closure. Discretization of convective fluxes of the mean flow equation is performed using central differences, by explicitly added eigenvalue scaling non-isotropic matrixvalued artificial dissipation. In turbulence closure equations, numerical convective fluxes are approximated according to Roe second order upwind scheme in conjunction with monotone (TVD) variable extrapolations. The semi-discrete equations are advanced in time using a four stage explicit Runge-Kutta scheme enhanced with local time stepping, variable coefficient implicit residual smoothing and multigrid acceleration. Developed software is applied for numerical analysis of work processes in the model of NEL mixed-flow bowl pump. Obtained numerical results are in good agreement with the available experimental data in the operating conditions at the best efficiency point (BEP). Also, turbopump performances are simulated for number flow rates and constant shaft speed, corresponding to the off-design operating conditions. According to information from numerical experiment, methodology for design performance characteristics is shown. By further improvement of mathematical model, the developed methodology enables that, from an engineer's perspective, numerical experiment could be a useful, low-cost tool in comparison with the expensive measurements. Using the dimensionless characteristics as well as theory of conformity, the turbopump performance can be calculated within the wide operating regimes in a relatively simple way.Publishe

Residual life estimation of a thermal power plant component: The high-pressure turbine housing case

This study focuses on the estimation of residual life of damaged thermal power plant components. The high-pressure turbine housing was chosen as an example of thermal power plant component where, during the years of exploitation, damage appeared in the form of dominant crack. Residual life estimation procedure, based upon experimental and numerical methods has been introduced and applied. Material properties were determined experimentally both at room and operating temperature, while all necessary calculations were performed by the special finite element method, so-called X-FEM. The residual life estimation of the damaged high-pressure turbine housing was performed by applying the Paris's law for crack growth analysis