Numerical analysis of Wells turbine for wave power conversion

The sea wave energy is one of the high potential renewable energy sources. The Wells turbine as the main part of the Oscillalting Water Column energy plant is analyzed in this paper.  The Wells turbine uses air flow produced by the pressure change inside the oscillating water column. Efficient energy transformation is achieved with the use of self-rectifying Wells air turbine. Since the tangential force of the rotor acts only in one direction even though airflow is oscillating, turbine rotates always in the same direction. Series of numerical simulations are performed using software package FLUENT for the wide span of non-dimensional flow rate coefficient (fi) and employing three different turbulent models. Structured numerical mesh and application of the axisymmetric periodical boundary conditions raised the accuracy of the numerical model while reducing computational load three times compared to the model with the fully meshed domain. Finally, operation of the OWC plant consisting of the air chamber and the turbine was simulated for the Adriatic sea maritime conditions, giving satisfactory energy output considering compact dimension of the whole plant

DISPERSION MODELLING APPROACH TO MONITORING AND PREDICTING INDUSTRY INDUCED AIR POLLUTION

Modeliranje onečišćenja zraka postalo je esencijalno za razumijevanja načina kojim emisije onečišćujućih tvari iz industrijskih kompleksa, cestovnog transporta i ostalih izvora emisija utječu na dinamiku okoliša. Korištenjem standardiziranoga modela disperzije ISCST3 izrađen je sustav za kontinuirano procjenjivanje prizemnih koncentracija onečišćujućih tvari. Opisan je automatizirani pristup prikupljanju emisija i meteoroloških podataka te izvršena evaluacija za odabrano vrijeme na temelju analize cjelogodišnjih mjerenih podataka emisija i meteoroloških podataka.The air quality modeling approach has become essential in understanding the way in which air pollution emissions from industrial complexes, vehicles and other sources influence the dynamics of the environment. A system for continuous prediction of ground level concentrations of air pollutants has been developed using the standardized dispersion model ISCST3. An automated emission preprocessor and meteorology collector has been integrated into the system. Finally, after conducting an annual analysis of the measured data, the system was evaluated for specific datasets

Contamination source detection in water distribution networks

Numeričkim hidrauličkim simulacijama mreže cijevi računaju se piezometrične visine i protoci u unutarnjim točkama cijevi i drugim hidrauličkim elementima mreže. Osim tih proračuna, cilj simulacije također može biti i širenje polutanata ili otopine u cijevnoj mreži. Širenje polutanata kroz vodnodistribucijsku mrežu cijevi uglavnom je uvjetovano svojstvima procesa miješanja u križnim cijevnim spojevima. Realno miješanje u križnom spoju nalazi se unutar pretpostavke modela potpunoga miješanja i modela nepotpunoga miješanja. U ovom radu pokazan je postupak inverznoga modeliranja kako bi se odredio izvor zagađenja unutar mreže cijevi. Pretpostavljamo situaciju u kojem se koncentracije zagađenja mjere u jednom, dva ili više čvorova mreže. Rezultati mjerenja koriste se kao polazište za postupak inverznoga traganja za izvorom zagađenja. Taj je postupak pokazan i verificiran na jednom eksperimentalnom modelu.The numerical hydraulic simulation of pipe networks calculates the heads and discharges at the inner points of pipes and other non-pipe elements of the network. Besides these calculations, contaminant and solutes spreading in the pipe network can be of interest, too. The contamination spreading through the water-distribution pipe networks is controlled mainly by mixing properties at pipe junctions. Real mixing that can occur within a pipe junction lies between the complete-mixing model and incomplete-mixing model assumptions. In this paper, we demonstrate the inverse modeling in trying to detect the source of contamination within the pipe network. We assume a scenario where contaminant concentrations are measured in one, two or more nodes of the pipe network. These results are used as a starting point for the inverse source detecting procedure. The inverse source detection procedure is shown and verified on an experimental model

Numerical simulations of hydraulic transients in hydropower plant Jajce II

Hydraulic transients in hydropower plant Jajce II (Bosnia and Herzegovina) were simulated with 1D unsteady pipe flow model. High accuracy of the model was accomplished with the use of non-conservative formulation of an unsteady pipe flow model incorporating a modified instantaneous acceleration-based unsteady friction model and second order flux limited numerical scheme. In order to apply the model, complex dual surge tank geometry needed to be represented with a unified surge tank. The numerical model was validated against the measured data on three simulation scenarios, defined with different turbine discharge reductions. Simulation results show a very good agreement between the computed and measured piezometric heads, both in amplitude and frequency of the oscillation

DISPERSION MODELLING APPROACH TO MONITORING AND PREDICTING INDUSTRY INDUCED AIR POLLUTION

Modeliranje onečišćenja zraka postalo je esencijalno za razumijevanja načina kojim emisije onečišćujućih tvari iz industrijskih kompleksa, cestovnog transporta i ostalih izvora emisija utječu na dinamiku okoliša. Korištenjem standardiziranoga modela disperzije ISCST3 izrađen je sustav za kontinuirano procjenjivanje prizemnih koncentracija onečišćujućih tvari. Opisan je automatizirani pristup prikupljanju emisija i meteoroloških podataka te izvršena evaluacija za odabrano vrijeme na temelju analize cjelogodišnjih mjerenih podataka emisija i meteoroloških podataka.The air quality modeling approach has become essential in understanding the way in which air pollution emissions from industrial complexes, vehicles and other sources influence the dynamics of the environment. A system for continuous prediction of ground level concentrations of air pollutants has been developed using the standardized dispersion model ISCST3. An automated emission preprocessor and meteorology collector has been integrated into the system. Finally, after conducting an annual analysis of the measured data, the system was evaluated for specific datasets

Improving efficiency in air pollution numerical simulations

Procjenjivanje onečišćenja zraka predstavlja važan segment sustava za ocjenu utjecaja onečišćenja na zdravlje ljudi i okoliša. Temeljni, zakonom propisani, postupak procjenjivanja je korištenje standardiziranih modela kakvoće zraka. Modeli kakvoće zraka učestalo se primjenjuju pri višegodišnjim analizama emisija onečišćujućih tvari iz novih potencijalnih postrojenja te pri kontinuiranom procjenjivanju i praćenju imisija iz postojećih izvora. Takve simulacije zahtijevaju iznimnu količinu informacija za pripremu te odabir modela kakvoće sa primjerenom učinkovitošću i točnosti izračunatih koncentracija onečišćenja. Analizom različitih modela disperzije i kakvoće zraka odabran je CALPUFF model disperzije. Učinkovitost je povećana na dvije razine. Prva razina odnosi se na efikasniji i robusniji način prikupljanja i pripreme svih potrebnih podataka za CALPUFF model disperzije. U d rugom d ijelu p ovećana je učinkovitost modela disperzije dimnih oblaka korištenjem grafičkih procesora opće namjene (GPGPU). Postupak paralelizacije postojećeg računalnog koda proveden je na proračunski najzahtjevnijem segmentu modela. Rezultati paralelizacije CALPUFF modela disperzije uspoređeni su sa osnovnom serijskom varijantom proračuna.Air pollution forecasting presents major segment for mitigation of air pollution effects on humans and environment. Regulatory modeling techniques have been established for such purposes. Air quality models, nowadays, are often used for longtime analysis of emitted pollutants from newly planned sources, for continuous forecasts from current sources. Such simulations need high number of different input parameters and selection of efficient model for each specific purpose in order to obtain accurate ground level concentrations. Different air quality m odels have been t horoughly a nalyzed with a conclusion t hat CALPUFF m odel i s most suited for wide range of applications. Furthermore, the model was made more effective by raising the efficiency of model input data delivery and preparation. Moreover, the model was programmed for parallel execution on general purpose graphical processors (GPGPU). A process of parallelization was conducted on the code segment that consume the most compute time of the entire model. Results of raised efficiency of CALPUFF dispersion model have been compared to the results of current serial model version

Improving efficiency in air pollution numerical simulations

Procjenjivanje onečišćenja zraka predstavlja važan segment sustava za ocjenu utjecaja onečišćenja na zdravlje ljudi i okoliša. Temeljni, zakonom propisani, postupak procjenjivanja je korištenje standardiziranih modela kakvoće zraka. Modeli kakvoće zraka učestalo se primjenjuju pri višegodišnjim analizama emisija onečišćujućih tvari iz novih potencijalnih postrojenja te pri kontinuiranom procjenjivanju i praćenju imisija iz postojećih izvora. Takve simulacije zahtijevaju iznimnu količinu informacija za pripremu te odabir modela kakvoće sa primjerenom učinkovitošću i točnosti izračunatih koncentracija onečišćenja. Analizom različitih modela disperzije i kakvoće zraka odabran je CALPUFF model disperzije. Učinkovitost je povećana na dvije razine. Prva razina odnosi se na efikasniji i robusniji način prikupljanja i pripreme svih potrebnih podataka za CALPUFF model disperzije. U d rugom d ijelu p ovećana je učinkovitost modela disperzije dimnih oblaka korištenjem grafičkih procesora opće namjene (GPGPU). Postupak paralelizacije postojećeg računalnog koda proveden je na proračunski najzahtjevnijem segmentu modela. Rezultati paralelizacije CALPUFF modela disperzije uspoređeni su sa osnovnom serijskom varijantom proračuna.Air pollution forecasting presents major segment for mitigation of air pollution effects on humans and environment. Regulatory modeling techniques have been established for such purposes. Air quality models, nowadays, are often used for longtime analysis of emitted pollutants from newly planned sources, for continuous forecasts from current sources. Such simulations need high number of different input parameters and selection of efficient model for each specific purpose in order to obtain accurate ground level concentrations. Different air quality m odels have been t horoughly a nalyzed with a conclusion t hat CALPUFF m odel i s most suited for wide range of applications. Furthermore, the model was made more effective by raising the efficiency of model input data delivery and preparation. Moreover, the model was programmed for parallel execution on general purpose graphical processors (GPGPU). A process of parallelization was conducted on the code segment that consume the most compute time of the entire model. Results of raised efficiency of CALPUFF dispersion model have been compared to the results of current serial model version

Air Pollution Dispersion Modeling in Port Areas

For the last couple of decades, environmental protection awareness within port areas is gaining ever more importance. Ports can have a tremendous impact on the environment, especially in terms of air pollution. The main pollution sources are various port activities such as road and rail traffic, cargo handling and marine vessel operations. Air quality models can be of great help in estimating the effect on the ambient air quality from one or more sources emitting pollutants to the atmosphere. One of those models is the widely used Gaussian Plume dispersion approach. Based on existing measurements and port activity data, models can simulate the dispersion of air pollutants caused by activities and operations taking place within the port. By using historical data, they can simulate the current state of the air quality in the port and with the help of weather predictions simulate possible future situation. Simulations can assist the port manager/operator in the decision-making process in order to optimize various activities within the port and minimize their impact on the environment. One of the main objectives of the Horizon 2020 Project PIXEL (Port IoT for environmental leverage) is the deployment of environmental pollution models which can aid in the decision-making processes within the port domain. This paper reviews the current advances in the field of air pollution modelling with a special emphasis on port scenarios