Risk management can be defined as coordinated activities to conduct and control an organization with consideration of risk. Recently, risk management strategies have been developed to change the approach to hazards and risks. Resilience as a safety management theory considers the technical and social aspects of systems simultaneously. Resilience in process industries, as a socio-technical system, has four aspects of early detection, error-tolerant design, flexibility, and recoverability. Meanwhile, process industries' resilience has three phases: avoidance, survival, and recovery, determining the transition between normal state, process upset event, and catastrophic event. There may be various technical and social failures such as regulatory and human or organizational items that can lead to upset or catastrophic events. In the avoidance phase, the upset event is predicted, and thus, the system remains in a normal state. For the survival phase, the system state is assumed to be an upset process event, and the system tries to survive through the unhealthy process conditions or remains in the same state, probably with low performance. In the recovery phase, the system is supposed to be catastrophic, and the emergency barriers are prioritized to show the severity of the consequences and response time, leading to a resumption of a normal state. Therefore, a resilience-based network can be designed for process industries to show its inherent dynamic transition in nature. In this study, network data envelopment analysis (DEA), as a mathematical model, is used to evaluate the relative efficiency of the process industries regarding a network transition approach based on the system's internal structure. First, a resilience-based network is designed to consist of three states of normal, upset, and catastrophic events. Then, the efficiency of each industrial department, which is defined as decision-making units (DMUs), is evaluated using network DEA. As a case study, a refinery that is considered a critical process industry is assessed. Using the proposed model shows the efficient and inefficient DMUs in each of three states of normal, upset, and catastrophic events of the process and the projection onto efficient frontiers. Besides calculating the network efficiency, the performance of each state is extracted to precisely differentiate between DMUs. The results of this study, which is one of the fewest cases in the area of performance evaluation of process industries with a network approach, indicated a robust viewpoint for monitoring and assessment of risks. 相似文献
Objective: To reduce the severity of injuries and the number of cyclist deaths in traffic accidents, active safety devices providing cyclist detection are considered to be effective countermeasures. The features of car-to-bicycle collisions need to be known in detail to develop such safety devices.
Methods: The study investigated near-miss situations captured by drive recorders installed in passenger cars. Because similarities in the approach patterns between near-miss incidents and real-world fatal cyclist accidents in Japan were confirmed, we analyzed the 229 near-miss incident data via video capturing bicycles crossing the road in front of forward-moving cars. Using a video frame captured by a drive recorder, the time to collision (TTC) was calculated from the car's velocity and the distance between the car and bicycle at the moment when the bicycle initially appeared.
Results: The average TTC in the cases where bicycles emerged from behind obstructions was shorter than that in the cases where drivers had unobstructed views of the bicycles. In comparing the TTC of car-to-bicycle near-miss incidents to the previously obtained results of car-to-pedestrian near-miss incidents, it was determined that the average TTC in car-to-bicycle near-miss incidents was significantly longer than that in car-to-pedestrian near-miss incidents.
Conclusions: When considering the TTC in the test protocol of evaluation for safety performance of active safety devices, we propose individual TTCs for evaluation of cyclist and pedestrian detections, respectively. In the test protocols, the following 2 scenarios should be employed: bicycle emerging from behind an unobstructed view and bicycle emerging from behind obstructions. 相似文献
The incorporation of land use (LU) data with socioeconomic data is a main issue in modelling. This is as a result of difference in data model and scale. This study proposed and tested the change–pattern approach, which allows the incorporation of these data sets in modelling LU change. Focusing on LU dynamics for a selected part of the Thames Gateway within the City of London, the approach tested two different methods of input selection for the modelling operations. Variables selected from these two methods serve as inputs into several neural networks tested in order to identify the direction of change for each of the LU types within the study area. The result shows that direction of LU change across the study area could be identified when spatial morphology of the area and socioeconomic variables are considered. Some classes of change could be identified fairly accurately using landscape metrics indicating level of fragmentation, extent of LU patches, shape complexity of LU patches in combination with some socioeconomic variables. 相似文献