Stepped Leader Progression and Speed Evolution in a Thunderstorm: Theoretical Model

This paper presents a theoretical model to describe the progression of leading (falling) lightnings in storms (stepped leaders). Stepped leaders move down from the thundercloud base to the encounter point with an upward streamer. First, the existing models, related to the advance of leading lightnings, are analyzed. Then, a novel theory is presented. The proposed model describes both the leader progression and speed. It aims at explaining the leader progression as a succession of several steps, or branches, that form the well-known tree-like shape. The speed of advance per step is described as a function of various parameters: the charge concentration surface diameter and the step length, among others. The derived formulas include two new parameter named ( χ ) and G. χ is the ratio between the guide beam length ( L ) and the diameter of the circle, inside the cloud, where the charges are concentrated ( D ) . G relates density of charges, as explained herein.

Assessment of radioactivity from selected soil samples from Halfa Aljadida area, Sudan

In this research, the results of radon concentration, surface and mass exhalation rates, radium concentration, effective dose rate and the alpha index have been investigated in a number of 198 soil samples that have been collected from various residential locations of Halfa Aljadida area, Sudan. The can technique, containing CR-39 have been used. From our results, the average value of soil gas radon concentration was found to be 1.96±0.22 kBq·m−3. The average values of surface and mass exhalation rates were 1.73±0.19 Bq·m−2·h−1 and 34.79±3.87 mBq·kg−1·h−1, respectively. The radium concentration average value was 8.06±0.90 Bq·kg−1. While the average value of the effective dose rate was recorded to be 54.69±6.11 mSv·y−1. The average value of alpha index of studied samples was (4.03±0.45)×10−2. From the study, a good positive and linear correlation between radium concentration, surface and mass exhalation rates of soil samples were present. In addition to that, a positive and linear correlation between radium and radon concentrations was found. Finally, a comparison between the results and other findings was conducted and the results imply the fact that the area under consideration is safe as if the health hazard are mentioned.

Exploring concentration, surface area and surface chemistry effects of colloidal aggregates on fat crystal networks

An investigation into the effects of concentration, surface area and surface chemistry of silica aggregates on a model fat-structured system.

Corrosion Prevention Approach for gas and oil Refinery Tanks

Tanks and pressurized vessels are one of the main equipments in the gas and oil refinery industry. Every petroleum industry has a lot of tanks. Gas and oil are corrosive materials, therefore the corrosion losses cost large amount of money and time every year. The severity of corrosion depends on various working parameters such as H2S level, partial pressure of CO2, temperature, chloride concentration, surface films and oxide contents.

Geostatistical integration and uncertainty in pollutant concentration surface under preferential sampling

In this paper the focus is on environmental statistics, with the aim of estimating the concentration surface and related uncertainty of an air pollutant. We used air quality data recorded by a network of monitoring stations within a Bayesian framework to overcome difficulties in accounting for prediction uncertainty and to integrate information provided by deterministic models based on emissions meteorology and chemico-physical characteristics of the atmosphere. Several authors have proposed such integration, but all the proposed approaches rely on representativeness and completeness of existing air pollution monitoring networks. We considered the situation in which the spatial process of interest and the sampling locations are not independent. This is known in the literature as the preferential sampling problem, which if ignored in the analysis, can bias geostatistical inferences. We developed a Bayesian geostatistical model to account for preferential sampling with the main interest in statistical integration and uncertainty. We used PM10 data arising from the air quality network of the Environmental Protection Agency of Lombardy Region (Italy) and numerical outputs from the deterministic model. We specified an inhomogeneous Poisson process for the sampling locations intensities and a shared spatial random component model for the dependence between the spatial location of monitors and the pollution surface. We found greater predicted standard deviation differences in areas not properly covered by the air quality network. In conclusion, in this context inferences on prediction uncertainty may be misleading when geostatistical modelling does not take into account preferential sampling.