Konstantinos E. Kakosimos

Reference Data for the Density and Viscosity of Liquid Aluminum and Liquid Iron

The available experimental data for the density and viscosity of liquid aluminum and iron have been critically examined with the intention of establishing a density and a viscosity standard. All experimental data have been categorized into primary and secondary data according to the quality of measurement specified by a series of criteria. The proposed standard reference correlations for the density of the aluminum and iron are characterized by standard deviations of 0.65% and 0.77% at the 95% confidence level, respectively. The overall uncertainty in the absolute values of the density is estimated to be one of ±0.7% for aluminum and 0.8% for iron, which is worse than that of the most optimistic claims but recognizes the unexplained discrepancies between different methods. The standard reference correlations for the viscosity of aluminum and iron are characterized by standard deviations of 13.7% and 5.7% at the 95% confidence level, respectively. The uncertainty in the absolute values of the viscosity of the two metals is thought to be no larger than the scatter between measurements made with different techniques and so can be said to be ±14% in the case of aluminum and ±6% in the case of iron.

Fires, Explosions, and Toxic Gas Dispersions : Effects Calculation and Risk Analysis

Today’s risk analysis is a very challenging field, and a solid understanding of the calculations procedure associated with it is essential for anyone involved. Fires, Explosions, and Toxic Gas Dispersions: Effects Calculation and Risk Analysis provides an overview of the methods used to assess the risk of fires, explosions, and toxic gas dispersion, and then deduce the subsequent effects and consequences of these events. The authors cover various aspects of such incidents, including the probability that an accident will occur, and how to calculate leaks, heat flux, overpressure, and the concentration of toxic clouds. The book follows by describing the consequences to people (injury or death) and material damages, and it concludes with a discussion of possible causes of destruction and common circumstances that can result in accidents.

Operational Street Pollution Model (OSPM) – a review of performed application and validation studies, and future prospects

Environmental context Trafficked streets are air pollution hot spots where people experience high exposure to hazardous pollutants. Although monitoring networks provide crucial information about measured pollutant levels, the measurements are resource demanding and thus can be performed at only few selected sites. Fast and easily applied street pollution models are therefore necessary tools to provide information about the loadings in streets without measurement activities. We evaluate the Operational Street Pollution Model, one of the most commonly applied models in air pollution management and research worldwide. Abstract Traffic emissions constitute a major source of health hazardous air pollution in urban areas. Models describing pollutant levels in urban streets are thus important tools in air pollution management as a supplement to measurements in routine monitoring programmes. A widely used model in this context is the fast and easy to apply Operational Street Pollution Model (OSPM). For almost 20 years, OSPM has been routinely used in many countries for studying traffic pollution, performing analyses of field campaign measurements, studying efficiency of pollution abatement strategies, carrying out exposure assessments and as reference in comparisons to other models. OSPM is generally considered as state-of-the-art in applied street pollution modelling. This paper outlines the most important findings in OSPM validation and application studies in literature. At the end of the paper, future research needs are outlined for traffic air pollution modelling in general but with outset in the research performed with OSPM.

Application of Detached Eddy Simulation to neighbourhood scale gases atmospheric dispersion modelling

This paper addresses the current important problem of modelling the dispersion of toxic gases released in the urban terrains (i.e. neighbourhood scale) by the Detached Eddy Simulation (DES). This approach is a resolution that lays between the Reynolds Averaged Navier-Stokes and Large Eddy Simulation models and focuses especially on establishing a better balance between efficiency and accuracy. Herein are presented the theoretical approach of a new model, which is based on the DES and the Spalart-Almaras turbulent closure and a number of validation tests like the flow and the dispersion over and around a single building and an array of buildings. Overall, employed validation metrics were within the acceptable limits and the model demonstrated an acceptable agreement with the experimental datasets which confirms the use of this approach for the modelling and dispersion of gases in complex terrains like a city.

Application and evaluation of AERMOD on the assessment of particulate matter pollution caused by industrial activities in the Greater Thessaloniki area

Industrial activities are sources of high emission rates of particulate matter. The existence of many such industrial plants close to a densely populated area can have a severe effect on human health. The effects can be even worse when these emissions are added to existing background concentration levels. This study deals with the assessment of the primary particulate matter pollution caused by industrial activities close to the city of Thessaloniki in Greece. An atmospheric dispersion and regulatory model was employed, i.e. AERMOD from the US Environmental Pollution Agency. A new PM10 emission sources inventory was prepared for the main industrial plants of the area and the annual and monthly average concentrations from 2003 to 2007 were calculated. The results from AERMOD were validated against data from available monitoring stations and showed reasonably good agreement. It was estimated that industry contributes approximately 30% of primary PM10 on the western suburbs of the city and about 7% in the city centre. The effect of the wind direction was also studied and it was illustrated that the frequent southwest winds present higher concentration levels than the strong north ones.

Atmospheric dispersion modelling of the fugitive particulate matter from overburden dumps with numerical and integral models

The present work addresses the problem of atmospheric dispersion of particulate matter (PM) from the overburden dumps of a mine, using a steady–state Lagrangian numerical model (commercial CFD software) and the integral model AERMOD (U.S. EPA). The analysis includes most of the complex physical phenomena in atmospheric diffusion. In the vicinity of the city of Amyndaion in Northern Greece, there is a large mine that provides lignite for the thermal power stations of the Hellenic Public Power Corporation. The excavated land is dumped in nearby open pits, which are planned to be extended towards South. These pits are sources of air–suspended particulate matter that can affect the nearby residential areas. The numerical model was applied for a number of specific meteorological scenarios, while the integral model for five years period. The results from both models showed an increase on the concentration levels, near the residential area, of two orders of magnitude if the dumps expand Southern. The models inter–comparison was based solely on the average yearly concentration and showed a fair agreement. Nevertheless, the numerical model tends to underestimate the concentration levels mainly because of the “limited” number of particles employed in the Langrangian model and the lack of wind–meandering.

Local scale vehicles pollution study in the absence of sufficient data: the case of the city of Thessaloniki

Air quality in urban environments can today be modelled by a large number of computer models (empirical, box models, CFD). OSPM (Operational Street Pollution Model) is one of the most widely used empirical-box models due to its simplicity and its very good performance. However, in most cases the necessary data, even for such simple computations, are not all available, leading to large errors, especially when employed for future planning. The City of Thessaloniki (Greece) was studied as an example, as although few input-data are available, there are enough measurements to validate the model’s results. The current work proposes a methodology for dealing with this lack of data, confirmed by comparison with measured values. Following that, a sensitivity analysis for the most common input parameters is presented. Finally, OSPM is employed to predict the air quality in some highly-possible future scenarios.

Road traffic air and noise pollution exposure assessment – A review of tools and techniques

Road traffic induces air and noise pollution in urban environments having negative impacts on human health. Thus, estimating exposure to road traffic air and noise pollution (hereafter, air and noise pollution) is important in order to improve the understanding of human health outcomes in epidemiological studies. The aims of this review are (i) to summarize current practices of modelling and exposure assessment techniques for road traffic air and noise pollution (ii) to highlight the potential of existing tools and techniques for their combined exposure assessment for air and noise together with associated challenges, research gaps and priorities. The study reviews literature about air and noise pollution from urban road traffic, including other relevant characteristics such as the employed dispersion models, Geographic Information System (GIS)-based tool, spatial scale of exposure assessment, study location, sample size, type of traffic data and building geometry information. Deterministic modelling is the most frequently used assessment technique for both air and noise pollution of short-term and long-term exposure. We observed a larger variety among air pollution models as compared to the applied noise models. Correlations between air and noise pollution vary significantly (0.05-0.74) and are affected by several parameters such as traffic attributes, building attributes and meteorology etc. Buildings act as screens for the dispersion of pollution, but the reduction effect is much larger for noise than for air pollution. While, meteorology has a greater influence on air pollution levels as compared to noise, although also important for noise pollution. There is a significant potential for developing a standard tool to assess combined exposure of traffic related air and noise pollution to facilitate health related studies. GIS, due to its geographic nature, is well established and has a significant capability to simultaneously address both exposures.

Experimental and numerical study of liquefied natural gas (LNG) pool spreading and vaporization on water

The investigation of pool spreading and vaporization phenomenon is an essential part of consequence analysis to determine the severity of LNG spills on water. In this study, release of LNG on water during marine operations is studied through experimental and numerical methods The study involves emulation of an LNG leak from transfer arms during side by side loading operations. The experimental part involves flow of LNG in a narrow trench filled with water and subsequent measurement of pool spreading and vaporization parameters. The numerical part involves CFD simulation using a three dimensional hybrid homogenous Eulerian multiphase solver to model the pool spreading and vaporization phenomenon. In this method, LNG is modeled as dispersed phase droplets which can interact with continuous phases - water and air through interphase models. The numerical study also employs a novel user-defined routine for capturing the LNG vaporization process. The CFD solver was capable of capturing the salient features of LNG pool spreading and vaporization phenomena. It was observed from experiment and CFD simulation that wind influenced both pool spreading and vaporization phenomenon through entrainment and convection.

A parameter estimation and identifiability analysis methodology applied to a street canyon air pollution model

Mathematical models are increasingly used in environmental science thus increasing the importance of uncertainty and sensitivity analyses. In the present study, an iterative parameter estimation and identifiability analysis methodology is applied to an atmospheric model - the Operational Street Pollution Model (OSPMź). To assess the predictive validity of the model, the data is split into an estimation and a prediction data set using two data splitting approaches and data preparation techniques (clustering and outlier detection) are analysed. The sensitivity analysis, being part of the identifiability analysis, showed that some model parameters were significantly more sensitive than others. The application of the determined optimal parameter values was shown to successfully equilibrate the model biases among the individual streets and species. It was as well shown that the frequentist approach applied for the uncertainty calculations underestimated the parameter uncertainties. The model parameter uncertainty was qualitatively assessed to be significant, and reduction strategies were identified. Valuable insights into the functionality of atmospheric dispersion models.Parameter estimation can successfully balance the model biases.Advantages of the parameter estimation and identifiability analysis methodology.The frequentist approach underestimates the parameter uncertainties.Methodology with the potential way to guide future research.