Driver Workload Response to In-Vehicle Device Operations

A central concern of Intelligent Transportation Systems (ITS) is the effect of in-vehicle devices (e.g., cell phones, navigation systems, radios, etc.) on driver performance and safety. As diverse and innovative technologies are designed and implemented for in-vehicle use, questions regarding the presence and use of these devices assume progressively greater importance. Further concerns for advanced driver training require us to develop and validate reliable and effective procedures for assessing such effects. This work examines a number of candidate procedures, in particular the evaluation of change in cognitive workload as a strategy by which such goals might be achieved.     

Effectiveness of a Light-Weight Ice-Vest for Body Cooling While Wearing Fire Fighter’s Protective Clothing in the Heat

The aim of the study was to examine the effects of wearing an ice-vest (ca 1 kg) on physiological and subjective responses in fire fighters. The experiments were carried out on a treadmill in a hot-dry environment. The physical cooling effect of the ice-vest was measured with a thermal manikin. The ice-vest effectively reduced skin temperatures under the vest. On average, heart rate was 10 beats/min lower, the amount of sweating was reduced by 13%, and subjective sensations of effort and warmth were lower during work with the ice-vest compared to work without it. Thermal manikin tests indicated that the useful energy available from the vest for body cooling was rather high (58%). In conclusion, the ice-vest reduces physiological and subjective strain responses during heavy work in the heat, and may promote efficient work time by 10%.     

Experimental investigation of hydrogen–air deflagrations and detonations in semi-confined flat layers

This paper presents results of an experimental investigation on the deflagration and deflagration-to-detonation transition (DDT) in an obstructed (blockage ratio BR = 50%), semi-confined flat layer filled with uniform hydrogen–air mixtures. The effect of mixture reactivity depending on flat layer thickness and its width is studied to evaluate the critical conditions for sonic flame propagation and the possibility for detonation onset. The experiments were performed in a transparent, rectangular channel with a length of 2.5 m. The flat layer thickness was varied from 0.06 to 0.24 m and the experiments were performed for different channel widths of 0.3, 0.6 and 0.9 m. The experimental results show flame velocity vs. hydrogen concentration for different thicknesses and widths of the semi-confined flat layer. Three different flame propagation regimes were observed: slow subsonic flame (M << 1), sonic deflagration (M ～ 1) and detonation (M >> 1). It is shown that flame acceleration (FA) to sonic speed is independent of the width of the flat layer. The critical expansion ratio for effective flame acceleration to sonic speed was found to be linearly dependent on the reciprocal layer thickness.     

Analysis of underlying causes of investigated loss of containment incidents in Dutch Seveso plants using the Storybuilder method

In the Netherlands there are around 400 “Seveso” sites that fall under the Dutch Major Hazards Decree (BRZO) 1999. Between 2006 and 2010 the Dutch Labour Inspectorate's Directorate for Major Hazard Control completed investigations of 118 loss of containment incidents involving hazardous substances from this group. On the basis of investigation reports the incidents were entered in a tailor-made tool called Storybuilder developed for the Dutch Ministry of Social Affairs and Employment for identifying the dominant patterns of technical safety barrier failures, barrier task failures and underlying management causes associated with the resulting loss of control events. The model is a bow-tie structure with six lines of defence, three on either side of the central loss of containment event. In the first line of defence, failures in the safety barriers leading to loss of control events were primarily equipment condition failures, pre start-up and safeguarding failures and process deviations such as pressure and flow failures. These deviations, which should have been recovered while still within the safe envelope of operation, were missed primarily because of inadequate indication signals that the deviations have occurred. Through failures of subsequent lines of defence they are developing into serious incidents. Overall, task failures are principally failures to provide adequate technical safety barriers and failures to operate provided barriers appropriately. Underlying management delivery failures were mainly found in equipment specifications and provisions, procedures and competence. The competence delivery system is especially important for identifying equipment condition, equipment isolation for maintenance, pre-start-up status and process deviations. Human errors associated with operating barriers were identified in fifty per cent of cases, were mostly mistakes and feature primarily in failure to prevent deviations and subsequently recover them. Loss of control associated with loss of containment was primarily due to the containment being bypassed (72% of incidents) and less to material strength failures (28%). Transfer pipework, connections in process plant and relief valves are the most frequent release points and the dominant release material is extremely flammable. It is concluded that the analysis of a large number of incidents in Storybuilder can support the quantification of underlying causes and provide evidence of where the weak points exist in major hazard control in the prevention of major accidents.     

Worst-case identification of gas dispersion for gas detector mapping using dispersion modeling

To quickly and accurately quantify the material release in process units, gas detectors may be placed according to the results of gas dispersion modeling. DNV's PHAST software is one of the most useful and reliable tools for material dispersion modeling. In this software, fluid dispersion is modeled based on the process conditions, the weather conditions and the specifications of the material release point. However, varying weather conditions throughout the year and the exact determination of the release point on the plot plan and the release elevation are problematic; these issues cause the results to be non-exact and non-integrated. Choosing the most appropriate conditions is challenging. In this paper, a scheme was provided to select the most appropriate conditions for gas dispersion modeling. This scheme approaches modeling based on the worst-case scenario (the situation in which the dispersed gas reaches the detector later in comparison to the other cases). Therefore, different weather conditions, release elevations and release points on the plot plan were modeled for an absorber tower of the Gonbadli Dehydration Unit of the Khangiran Refinery. The worst case of each release condition was then chosen. Finally, gas detectors were placed using the gas dispersion modeling results based on the worst-case scenario.     

A new approach for layout optimization in maintenance workshops with safety factors: The case of a gas transmission unit

In this study, an Integrated Simulation-Data Envelopment Analysis (DEA) approach is presented for optimum facility layout of maintenance workshop in a gas transmission unit. The process of repair of incoming parts includes various operations on different facilities. The layout problem in this system involves determining the optimum location of all maintenance shop facilities. Layout optimization plays a crucial role in this type of problems in terms of increasing the efficiency of main production line. Standard types of layouts including U, S, W, Z and straight lines are considered. First, the maintenance workshop is modeled with discrete-event-simulation. Time in system, average waiting time, average machine utilization, average availability of facilities, average queue length of facilities (AL) and average operator utilization are obtained from simulation as key performance indicators (KPIs) of DEA. Also, safety index and number of operators are considered as other KPIs. Finally, a unified non-radial Data Envelopment Analysis (DEA) is presented with respect to the stated KPIs to rank all layouts alternatives and to identify the best configuration. Principle Component Analysis (PCA) is used to validate and verify the results. Previous studies do not consider safety factor in layout design problems. This is the first study that presents an integrated approach for identification of optimum layout in a maintenance workshop of gas transmission unit by incorporating safety and conventional factors.     

Environmental risk mapping of accidental pollution and its zonal prevention in a city

Accidental releases of pollution can have severe environmental, societal, economic, and institutional consequences. This paper considers the use of risk mapping of accidental pollution events, and zonal prevention measures for alleviating the impact on large urban areas. An Environmental Pollution Accident Risk Mapping (EPARM) model is constructed according to a mapping index system supported by quantitative sub-models dedicated to evaluating the risk arising from different sources of potential accidental pollution. The EPARM approach consists of identifying suitable indexes, assessment of environmental risk at regional and national scales based on information on previous pollution accidents and the prevailing environmental and social conditions, and use of GIS to map the overall risk. A case study of pollution accidents in Minghang District, Shanghai, China is used to demonstrate the effectiveness of the model. The paper also proposes a systemic framework for accidental environmental pollution risk prevention, and detailed countermeasures for specific risk zones.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.