Consideration of reactivity initiated accidents for TRU recycling in LWRs

Response of a PWR core loaded with Combined Non-Fertile and UO2 (CONFU) fuel assemblies to control rod ejection accident was evaluated. A number of core arrangements and TRU fuel compositions were considered and the results were compared with the performance of a reference all-UO2 core. The comparison was based on the results of a simple point kinetics model with thermal reactivity feedbacks and temperature dependant materials properties. The reactivity coefficients and core average kinetics parameters were obtained from the full core 3D neutronic simulations. The results show that application of the CONFU assembly concept causes only minor deviation of fuel performance characteristics in reactivity initiated accidents. This is a consequence of relatively small loadings of TRU in the CONFU assembly and therefore dominating role of conventional UO2 fuel in the neutronic performance of the core.

Computer modelling of human behaviour in aircraft fire accidents

The mathematical simulation of the evacuation process has a wide and largely untapped scope of application within the aircraft industry. The function of the mathematical model is to provide insight into complex behaviour by allowing designers, legislators, and investigators to ask ‘what if’ questions. Such a model, EXODUS, is currently under development, and this paper describes its evolution and potential applications. EXODUS is an egress model designed to simulate the evacuation of large numbers of individuals from an enclosure, such as an aircraft. The model tracks the trajectory of each individual as they make their way out of the enclosure or are overcome by fire hazards, such as heat and toxic gases. The software is expert system-based, the progressive motion and behaviour of each individual being determined by a set of heuristics or rules. EXODUS comprises five core interacting components: (i) the Movement Submodel — controls the physical movement of individual passengers from their current position to the most suitable neighbouring location; (ii) the Behaviour Submodel — determines an individual's response to the current prevailing situation; (iii) the Passenger Submodel — describes an individual as a collection of 22 defining attributes and variables; (iv) the Hazard Submodel — controls the atmospheric and physical environment; and (v) the Toxicity Submodel — determines the effects on an individual exposed to the fire products, heat, and narcotic gases through the Fractional Effective Dose calculations. These components are briefly described and their capabilities and limitations are demonstrated through comparison with experimental data and several hypothetical evacuation scenarios.

The AASK database V4.0: aircraft accident statistics and knowledge. A database to record human experience of evacuation in aviation accidents

This paper describes the AASK database. The AASK database is unique as it is a record of human behaviour during survivable aviation accidents. The AASK database is compiled from interview data compiled by agencies such as the NTSB and the AAIB. The database can be found on the website http://fseg.gre.ac.uk

Aircraft accident statistics and knowledge database: analyzing passenger behavior in aviation accidents

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of passenger accounts from survivable aviation accidents/incidents compiled from interview data collected by agencies such as the US NTSB. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It also plays a significant role in the development of the airEXODUS aircraft evacuation model, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes the latest version of the database (Version 4.0) and includes some analysis of passenger behavior during actual accidents/incidents.

An analysis of the passenger to cabin crew ratio and exit reliability based on past survivable aviation accidents

A hotly debated issue in the area of aviation safety is the number of cabin crew members required to evacuate an aircraft in the event of an emergency. Most countries regulate the minimum number required for the safe operation of an aircraft, but these rulings are based on little if any scientific evidence. Another issue of concern is the failure rate of exits and slides. This paper examines these issues using the latest version of Aircraft Accident Statistics and Knowledge database AASK V4.0, which contains information from 105 survivable crashes and more than 2,000 survivors, including accounts from 155 cabin crew members.

CAA paper 2006/01: a database to record human experience of evacuation in aviation accidents: the aircraft accident statistics and knowledge database (AASK)

This report concerns the development of the AASK V4.0 database (CAA Project 560/SRG/R+AD). AASK is the Aircraft Accident Statistics and Knowledge database, which is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from interviews of the occupants involved in aircraft accidents. The AASK database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. With support from the UK CAA (Project 277/SRG/R&AD), AASK V3.0 was developed. This was an on-line prototype system available over the internet to selected users and included a significantly increased number of passenger accounts compared with earlier versions, the introduction of cabin crew accounts, the introduction of fatality information and improved functionality through the seat plan viewer utility. The most recently completed AASK project (Project 560/SRG/R+AD) involved four main components: a) analysis of the data collected in V3.0; b) continued collection and entry of data into AASK; c) maintenance and functional development of the AASK database; and d) user feedback survey. All four components have been pursued and completed in this two-year project. The current version developed in the last year of the project is referred to as AASK V4.0. This report provides summaries of the work done and the results obtained in relation to the project deliverables.

Modelling road traffic accidents using macroscopic second-order models of traffic flow

In this paper, we introduce a macroscopic model for road traffic accidents along highway sections. We discuss the motivation and the derivation of such a model, and we present its mathematical properties. The results are presented by means of examples where a section of a crowded one-way highway contains in the middle a cluster of drivers whose dynamics are prone to road traffic accidents. We discuss the coupling conditions and present some existence results of weak solutions to the associated Riemann Problems. Furthermore, we illustrate some features of the proposed model through some numerical simulations. © The authors 2012.

Dioxins released from chemical accidents

Discrepancies in environmental budgets of dioxin-like compounds may be explained by emissions from accidents involving chlorinated organic chemicals. This source may have important implications for regulation inventories. © 1995 Nature Publishing Group.

Industrial accidents involving release of chemicals into the environment:Ecotoxicology

Major industrial accidents pose a serious threat to surrounding habitats. Each accident is unique in terms of pollutants released, pollutant concentrations and pollutant dispersal. The habitats receiving the pollutant(s) are also unique. These factors mean that assessing the environmental and ecological impact of any given pollution event will be complex. Case histories of the biological impact of chemicals released from industrial accidents are reviewed to determine how to assess ecotoxicity of pollutants involved.

Myopia, spectacle wear, and risk of bicycle accidents among rural Chinese secondary school students: the Xichang Pediatric Refractive Error Study report no. 7.

OBJECTIVE: To study the effect of myopia and spectacle wear on bicycle-related injuries in rural Chinese students. Myopia is common among Chinese students but few studies have examined its effect on daily activities. METHODS: Data on visual acuity, refractive error, current spectacle wear, and history of bicycle use and accidents during the past 3 years were sought from 1891 students undergoing eye examinations in rural Guangdong province. RESULTS: Refractive and accident data were available for 1539 participants (81.3%), among whom the mean age was 14.6 years, 52.5% were girls, 26.8% wore glasses, and 12.9% had myopia of less than -4 diopters in both eyes. More than 90% relied on bicycles to get to school daily. A total of 2931 accidents were reported by 423 participants, with 68 requiring medical attention. Male sex (odds ratio, 1.55; P < .001) and spectacle wear (odds ratio, 1.38; P = .04) were associated with a higher risk of accident, but habitual visual acuity and myopia were unassociated with the crash risk, after adjusting for age, sex, time spent riding, and risky riding behaviors. CONCLUSION: These results may be consistent with data on motor vehicle accidents implicating peripheral vision (potentially compromised by spectacle wear) more strongly than central visual acuity in mediating crash risk.

Power Law Behavior and Self-similarity in Modern Industrial Accidents

Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.