A novel driver hazard perception sensitivity model based on drivers’ characteristics: A simulator study

Objective: Considering the high annual number of fatal driving accidents in Iran, any approach for reducing the number or severity of driving accidents is a positive step toward decreasing accident-related losses. Accidents can often be avoided by a timely reaction of the driver. One of the steps before reacting to a hazard is perception. Some driver characteristics may affect road hazard perception. In this research, it was assumed that various driver characteristics, including demographic characteristics and cognitive characteristics, have an impact on driver perception.

Methods: The driving simulator used in this research provides various scenarios; for example, passing a pedestrian or animal across the road or placing fixed objects in a 2-lane separated rural road for 2 groups of experienced and inexperienced drivers under day and night lighting conditions. The go/no-go test was carried out in order to assess drivers’ attention to driving tasks and inhibitory control. A structural equation model (SEM) was used to estimate the relation between driver characteristics and sensitivity to road hazard perception. A new hazard perception index was proposed based on the time intervals in the hazard vulnerability.

Results: The results show that the most effective variables in the analysis of sensitivity to hazard perception are driving experience (in kilometers) during the last 3 years and road lighting conditions. Moreover, hazard perception sensitivity was improved by better inhibitory control, selective attention, and decision making, more carefulness, the average amount of daily sleep, and marital status.

Conclusion: The results of this research may be useful in educating and advertising programs. It also could enhance sensitivity to perception of hazards such as pedestrians, animals, and fixed obstacles among young and novice drivers.     

Simulation and application of a disaster spread model in Chemical Disaster Network

In the research field of chemical safety, the computer-aided simulation for occurrence and process of disasters has become a major trend in current research, in which the establishment of evolution system for chemical multi disasters is the key point. In the paper, the study lays emphasis on the simulation and application of a spread model for chemical multi disasters. After establishing a disaster network, we defined microcosmic elements of spread model specifically. Combined with guideline of chemical disaster (e.g. guideline of heat flux for damages or injure, guideline of evaluation for buildings based explosion and overpressure, and guideline of evaluation for human exposure to toxic gases), the weight of impact can be computed using new comprehensive algorithms. Simultaneously, the paper also uses an approach on simulating multiple failure events to describe random factors of triggering disasters. At last, the experimental case of alkyl aluminum leakage in a polypropylene plant shows the result of simulation with table of 5 major series of disasters and distribution diagram of nodes (disasters) in disaster network. This proves the validity and practicability of the simulation system in the establishment and feedback of contingency plan of large-scale petrochemical enterprises.     

Hydrodynamic and ecological assessment of nearshore restoration: A modeling study

Along the Pacific Northwest coast, much of the estuarine habitat has been lost over the last century to agricultural land use, residential and commercial development, and transportation corridors. As a result, many of the ecological processes and functions have been disrupted. To protect and improve these coastal habitats that are vital to aquatic species, many projects are currently underway to restore estuarine and coastal ecosystems through dike breaches, setbacks, and removals. Understanding site-specific information on physical processes is critical for improving the success of such restoration actions. In this study, a three-dimensional hydrodynamic model was developed to simulate estuarine processes in the Stillaguamish River estuary, where restoration of a 160-acre parcel through dike setback has been proposed. The model was calibrated to observed tide, current, and salinity data for existing conditions and applied to simulate the hydrodynamic responses to two restoration alternatives. Model results were then combined with biophysical data to predict habitat responses within the restoration footprint. Results showed that the proposed dike removal would result in desired tidal flushing and conditions that would support four habitat types on the restoration footprint. At the estuary scale, restoration would substantially increase the proportion of area flushed with freshwater (<5 ppt) at flood tide. Potential implications of predicted changes in salinity and flow dynamics are discussed relative to the distribution of tidal marsh habitat.     

Passive and active adaptive management: approaches and an example

Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. Yet there remains considerable confusion about what adaptive management entails, and how to actually make resource decisions adaptively. A key but somewhat ambiguous distinction in adaptive management is between active and passive forms of adaptive decision making. The objective of this paper is to illustrate some approaches to active and passive adaptive management with a simple example involving the drawdown of water impoundments on a wildlife refuge. The approaches are illustrated for the drawdown example, and contrasted in terms of objectives, costs, and potential learning rates. Some key challenges to the actual practice of AM are discussed, and tradeoffs between implementation costs and long-term benefits are highlighted.     

Adaptive management of natural resources--framework and issues

Adaptive management, an approach for simultaneously managing and learning about natural resources, has been around for several decades. Interest in adaptive decision making has grown steadily over that time, and by now many in natural resources conservation claim that adaptive management is the approach they use in meeting their resource management responsibilities. Yet there remains considerable ambiguity about what adaptive management actually is, and how it is to be implemented by practitioners. The objective of this paper is to present a framework and conditions for adaptive decision making, and discuss some important challenges in its application. Adaptive management is described as a two-phase process of deliberative and iterative phases, which are implemented sequentially over the timeframe of an application. Key elements, processes, and issues in adaptive decision making are highlighted in terms of this framework. Special emphasis is given to the question of geographic scale, the difficulties presented by non-stationarity, and organizational challenges in implementing adaptive management.     

Flow and transport characteristics at an Epinephelus guttatus (red hind grouper) spawning aggregation site in St. Thomas (US Virgin Islands)

This study characterizes the flow field at a spawning site located at the shelf break of a Caribbean island for the Epinephelus guttatus (red hind grouper) in relation to this species spawning events. In order to understand the oceanographic dynamics targeted by the fishes, current measurements were profiled throughout the water column for almost a year at the spawning site. The characteristics of the flow field and its evolution after spawning were investigated by using a numerical ocean model that resolved the observed tide and simulated the island scale flow where passive, neutrally buoyant virtual particles were released for 10 days to trace the flow pathways.Observed currents during the spawning period revealed that the flow was vertically sheared, to the south and weakest at the bottom, and to the west or east at the surface. The tidal analysis revealed that the flow at the time of spawning was directed across and on-shelf, although weaker close to the bottom. The model showed that the initial on-shelf transport was counteracted by the bottom flow directed to the shelf break, where virtual particles were entrained by the downwelling flow. A significant percent of particles resided less than two hundred meters deep, in the vicinity of the chlorophyll maximum and returned to the shelf break, close to the release location within 8-10 days. This journey was largely controlled by the timing between downwelling at the spawning site and upwelling further east at the shelf break, which was driven by the coupling between wind and tide induced vertical movements at the shelf break and deeper. The release location, vertical rotation of its flow field, and its transport properties were shown to be relatively resilient to the passage of transient sub-mesoscale eddies as well as to acute mesoscale flow reversals, suggesting that physical retention is maximized in the area surrounding the spawning site.     

Calculating ecological carrying capacity of shellfish aquaculture using mass-balance modeling: Narragansett Bay, Rhode Island

Increasing growth in the aquaculture industry demands ecosystem-based techniques for management if that growth is to be ecologically sustainable and promote equity among users of the ecosystems in which it occurs. Models of carrying capacity can be used to responsibly limit the growth of aquaculture in increasingly crowded coastal areas. Narragansett Bay, Rhode Island, USA is one such crowded coastal region experiencing a rapid increase in bivalve aquaculture. An ecosystem mass-balance model was used to calculate the ecological carrying capacity of bivalve aquaculture. Cultured oyster biomass is currently at 0.47 t km⁻² and could be increased 625 times without exceeding the ecological carrying capacity of 297 t km⁻². This translates to approximately 38,950 t of harvested cultured oysters annually which is 4 times the total estimated annual harvest of finfish. This potential for growth is due to the high primary productivity and large energy throughput to detritus of this ecosystem. Shellfish aquaculture has potential for continued growth and is unlikely to become food limited due, in part, to the large detritus pool.     

Highlights of LNG risk technology

The authors have recently undertaken a major review of LNG consequence modeling, compiling a wide range of historical information with more recent experiments and modeling approaches in a book entitled “LNG Risk-Based Safety: Modeling and Consequence Analysis”. All the main consequence routes were reviewed – discharge, evaporation, pool and jet fire, vapor cloud explosions, rollover, and Rapid Phase Transitions (RPT’s). In the book, experimental data bases are assembled for tests on pool spread and evaporation, burn rates, dispersion, fire and radiation and effects on personnel and structures. The current paper presents selected highlights of interest: lessons learned from historical development and experience, comparison of predictions by various models, varying mechanisms for LNG spread of water, a modeling protocol to enable acceptance of newer models, and unresolved technical issues such as cascading failures, fire engulfment of a carrier, the circumstances for a possible LNG BLEVE, and accelerated evaporation by LNG penetration into water.     

New approach to calculate the probability of ignition

The probabilistic approach to the evaluation of fire hazard and the effectiveness of fire-precaution measures enables a rational response to the randomness of fire outbreaks. This article employs the statistical analysis methods to elucidate the causes for the ignition of fire on a random sample of industrial buildings in the Republic of Slovenia. The analyses are based on the Structural Equation Modeling (SEM), which is a well established and important statistical analysis technique in the fields of social science, biology, psychology and medicine, but hitherto rarely applied in safety research. The results of the study demonstrate that for the analyzed random sample of industrial buildings the frequency of fire outbreaks statistically significantly depends only on the presence and the probability of exposure to the heat sources (flames, sparks, and hot surfaces), but does not significantly depend on the available quantity of flammable materials within the industrial structure.