Fire Safety Analysis of a Railway Compartment using Computational Fluid Dynamics

Trains are considered to be the safest on-land transportation means for both passengers and cargo. Train accidents have been mainly disastrous, especially in case of fire, where the consequences are extensive loss of life and goods. The fire would generate smoke and heat which would spread quickly inside the railway compartments. Both heat and smoke are the primary reasons of casualties in a train. This study has been carried out to perform numerical analysis of fire characteristics in a railway compartment using commercial Computational Fluid Dynamics code ANSYS. Non-premixed combustion model has been used to simulate a fire scenario within a railway compartment, while Shear Stress Transport k-ω turbulence model has been used to accurately predict the hot air turbulence parameters within the compartment. The walls of the compartment have been modelled as no-slip stationary adiabatic walls, as is observed in real life conditions. Carbon dioxide concentration (CO2), temperature distribution and air flow velocity within the railway compartment has been monitored. It has been observed that the smoke above the fire source flows to both sides of the compartment. The highest temperature zone is located downstream the fire source, and gradually decreases with the increase in the distance from the fire source. It can be seen that CFD can be used as an effective tool in order to analyse the evolution of fire in railway compartments with reasonable accuracy. The paper also briefly discusses the topical reliability issues

NODDI-SH: a computational efficient NODDI extension for fODF estimation in diffusion MRI

Diffusion Magnetic Resonance Imaging (DMRI) is the only non-invasive imaging technique which is able to detect the principal directions of water diffusion as well as neurites density in the human brain. Exploiting the ability of Spherical Harmonics (SH) to model spherical functions, we propose a new reconstruction model for DMRI data which is able to estimate both the fiber Orientation Distribution Function (fODF) and the relative volume fractions of the neurites in each voxel, which is robust to multiple fiber crossings. We consider a Neurite Orientation Dispersion and Density Imaging (NODDI) inspired single fiber diffusion signal to be derived from three compartments: intracellular, extracellular, and cerebrospinal fluid. The model, called NODDI-SH, is derived by convolving the single fiber response with the fODF in each voxel. NODDI-SH embeds the calculation of the fODF and the neurite density in a unified mathematical model providing efficient, robust and accurate results. Results were validated on simulated data and tested on \textit{in-vivo} data of human brain, and compared to and Constrained Spherical Deconvolution (CSD) for benchmarking. Results revealed competitive performance in all respects and inherent adaptivity to local microstructure, while sensibly reducing the computational cost. We also investigated NODDI-SH performance when only a limited number of samples are available for the fitting, demonstrating that 60 samples are enough to obtain reliable results. The fast computational time and the low number of signal samples required, make NODDI-SH feasible for clinical application

Multilevel Threshold Secret and Function Sharing based on the Chinese Remainder Theorem

A recent work of Harn and Fuyou presents the first multilevel (disjunctive) threshold secret sharing scheme based on the Chinese Remainder Theorem. In this work, we first show that the proposed method is not secure and also fails to work with a certain natural setting of the threshold values on compartments. We then propose a secure scheme that works for all threshold settings. In this scheme, we employ a refined version of Asmuth-Bloom secret sharing with a special and generic Asmuth-Bloom sequence called the {\it anchor sequence}. Based on this idea, we also propose the first multilevel conjunctive threshold secret sharing scheme based on the Chinese Remainder Theorem. Lastly, we discuss how the proposed schemes can be used for multilevel threshold function sharing by employing it in a threshold RSA cryptosystem as an example

A screening method for ranking chemicals by their fate and behaviour in the environment and potential toxic effects in humans following non-occupational exposure

A large number of chemicals are released intentionally or unintentionally into the environment each year. These include thousands of substances that are currently listed worldwide and several hundred new substances added annually (Mücke et al., 1986). When these compounds are used, they can reach microorganisms, plants, animals and man either in their original state or in the form of reaction and degradation products via air, water, soil or foodstuffs. Hence environmental chemicals can occur in practically all environmental compartments and ecosystems. It is not feasible to conduct assessments of human exposure and possible associated health effects for all chemicals. Even if the necessary resources were available, reliable data for a quantitative evaluation are likely to be absent in most cases. This has led to the development of schemes for prioritising compounds likely to be of environmental significance. Such schemes can be used to direct future research efforts towards the prioritised compounds. This study was commissioned by the Department of Health (DH) as part of a broader research activity that aims to identify key priority chemicals of concern to human health at routine levels of environmental exposure. The main pathways of human exposure are shown in Figure 1.1. A review of the principal prioritisation schemes used by different organisations to assess the significance of chemical release into the environment has been conducted by the MRC Institute for Environment and Health (IEH, 2003). This review showed that the approaches used by different organisations vary widely, depending on the initial reasons for which the schemes were developed. The basic information presented in the review was used to develop a simple screening method for ranking chemicals. The model used in this prioritisation scheme is outlined in Figure 1.2. The main purpose in developing the prioritisation scheme for DH was to develop a dedicated priority setting method capable of identifying chemicals in air, water, soil and foodstuffs that might pose a significant risk to human health following low level environmental exposure. The methodology was developed in order to identify compounds that required further assessment and those that had data gaps. More detailed risk assessments were conducted at a later stage on those compounds prioritised as being of high importancea. The screening methodology was developed for ‘existing chemicals’ as these are of greatest concern because data on their toxicity and/or fate and behaviour are often unknownb. The production of a priority list was designed to highlight compounds that required further regulatory measures to reduce exposure of the general population and for which an in-depth risk characterisation would be necessary to assist in the evaluation and implementation of activities for reducing environmental risks. This might include an assessment of the costs of such risks to human health and the costs of reduction measures. As the scheme also aimed to identify data gaps that might warrant further investigation, the application of default categories for chemicals with no data was also considered. The overall aim was to develop a screening methodology that is quick, clear and simple to use and that can easily be revised to take into account new information on compounds as and when it becomes available. a Benzene (IEH Report on Benzene in the Environment, R12); 4,6-dichlorocresol, hexachloro-1,3-butadiene, tetrachlorobenzene, 2,4,6-trichlorophenol (reports to DH; available from MRC Institute for Environment and Health b ‘Existing Substances’ are those that were placed in the European Union (EU) market before 1981. Prior to 1981 regulatory requirements were related to products intended for certain uses (e.g. veterinary medicines) and did not require assessment of the hazardous properties of any substance before they were released into the market. For substances placed on the market after 1981 (classified as ‘New Substances’) there is a legal requirement to conduct such assessments. Regulatory agencies require the collection of extensive documentation for safety before a chemical, for example, can be used in foods or commercial products. IEH Web Report W14, posted March 2004 at http://www.le.ac.uk/ieh/ 4 This report describes how physicochemical properties and toxicological data were incorporated into a screening model to assess the potential fate and transfer of chemicals between different environmental compartments and to predict the potential human exposure to toxic chemicals through the inhalation of contaminated air and the ingestion of water and food. It must be stressed, however, that the method devised is a simple screening process and that a more detailed assessment is necessary to determine the potential transfer through the foodchain of a chemical and the full extent of any adverse health effects. Sections 2 and 4 present the physicochemical properties, toxicological data and algorithms used to screen the compounds. Section 3 summarises the groups of chemicals that were included in the screening process. The results of the prioritisation scheme and comments on their limitations and constraints are presented in Section 5