Critical Analysis of Train Derailments in Canada through Process Safety Techniques and Insights into Enhanced Safety Management Systems

Canada’s rail transportation network is a critical part of Canada’s integrated supply chain which connects industries, consumers, and resource sectors to ports on the Atlantic and Pacific coasts. One transportation activity that is essential to most industries, especially oil and manufacturing, is the rail transport of dangerous goods (DG). Although rail transportation of DG is beneficial to Canada’s economy, not paying attention to the safe transportation of these types of goods can have irreparable effects on the economy, human lives, and the environment. Recent rail accidents, such as Lake Wabamun in 2005 and Lac-Mégantic in 2013, have shown that there is still room to increase the safety of transportation of DG by rail through improving railways’ safety management systems (SMS). As a result, investigations to increase the safety of rail transportation of DG have been started. This work is part of these initiatives focusing on enhancing railways’ SMS, particularly DG main-track train derailments. The current study applied detailed root cause analysis (RCA), the bow tie analysis (BTA), and incident databases to identify the main causes and consequences of these types of accidents (2007–2017). Then, the relationship between these factors and gaps in SMS elements were identified and the frequency of each factor was investigated. The results showed that the main gaps are related to process and equipment integrity, incident investigation, and company standards, codes, and regulations. Furthermore, some useful recommendations are presented to improve the management of each SMS element and reduce these gaps.

A Novel Integrated Fuzzy-Rough MCDM Model for Evaluation of Companies for Transport of Dangerous Goods

The organization and execution of the transport of dangerous goods is conditioned by a series of legal, technical, technological, safety, and engineering requirements, which must be met. In this way, a complex system is created which has a large number of participants and in which optimization should be performed at each stage from all the above aspects. The main goal of this paper is to create a novel Fuzzy-Rough MCDM (Multiple-Criteria Decision-Making) for the evaluation of companies engaged in the transport of dangerous goods. A group decision-making model was created to evaluate 11 transport companies based on nine legal, technical, technological criteria. The improved fuzzy stepwise weight assessment ratio analysis (IMF SWARA) method was used to calculate the criterion weights, while transport companies were ranked based on Rough Measurement Alternatives and Ranking according to the COmpromise Solution (R-MARCOS). The integration of these methods into a single model that combines two theories of uncertainty, fuzzy and rough, was performed for the first time in this study, which represents a significant contribution. The results show that the most significant criteria are as follows: dangerous goods are classified and permitted under ADR (Agreement Concerning the International Carriage of Dangerous Goods by Road), the prescribed documents are in the transport unit, and the equipment is in the transport unit. When it comes to the evaluation results of companies, it can be noticed that A1 and A4 show the best performance, while A8 and A9 are in the last position. In order to test the stability of the model developed, sensitivity analysis, comparative analysis, and the influence of the dynamic formation of the initial matrix were created.

Travel Time Reliability-Based Rescue Resource Scheduling for Accidents Concerning Transport of Dangerous Goods by Rail

The characteristics of railway dangerous goods accidents are very complex. The rescue of railway dangerous goods accidents should consider the timeliness of rescue, the uncertainty of traffic environment and the diversity of rescue resources. Thus, the purpose of this paper is to confront the rescue resources scheduling problem of railway dangerous goods accident by considering factors such as rescue capacity, rescue demand and response time. Based on the analysis of travel time and reliability for rescue route, a multi-objective scheduling model of rescue resources based on travel time reliability is constructed in order to minimize the total arrival time of rescue resources and to maximize total reliability. The proposed model is more reliable than the traditional model due to the consideration of travel time reliability of rescue routes. Moreover, a two-stage algorithm is designed to solve this problem. A multi-path algorithm with bound constraints is used to obtain the set of feasible rescue routes in the first stage, and the NSGA-II algorithm is used to determine the scheduling of rescue resources for each rescue center. Finally, the two-stage algorithm is tested on a regional road network, and the results show that the designed two-stage algorithm is valid for solving the rescue resource scheduling problem of dangerous goods accidents and is able to obtain the rescue resource scheduling scheme in a short period of time.

Environmental Impact Modeling for Transportation of Hazardous Liquids

Modeling the effects of leakage in the transport of hazardous liquids is a highly topical issue, not only in the field of environmental engineering. This article’s introduction presents relevant information and statistical sources, analyzes selected scientific and professional publications, and characterizes the results of selected research projects. The applied approaches, methods, and results of our research specify the processes of developing and testing a theoretical model of spreading the impacts of leakage of hazardous liquids on biological components of the environment. The proposed model for predicting the environmental impacts of hazardous liquid (HL) leakage during transport is a crucial risk management tool in the planning of transport of dangerous goods. It also enables the creation of comprehensive information systems that monitor the transport unit in real-time, indicate the presence of significant habitats along the transport route, and draw attention to possible threats, in particular to the health and lives of people and the environment. The main result of the presented research is the application of a computational model for determining the parameters of the dangerous zone in case of HL leakage and its graphical plotting along the transport route, estimating the probability of impacting the selected place by leaking HL. The model application results are presented in the form of calculated frequency of impacting the set of points in the vicinity of the HL transport route. Defined standardized frequencies of HL infiltration above a specified limit in liters per square meter in the event of leakage of the entire volume of HL from a road tanker (leaked volume of 30 m3) form the basic set of information for creating relevant risk maps near busy traffic routes and subsequent selection of ecologically and spatially optimal routes.

The Importance of the Human Factor in Safety for the Transport of Dangerous Goods

This article discusses the issues related to the safety for the transport of dangerous goods by road. Research on accidents in transport unambiguously points to the human factor, which is the most responsible for causing accidents. Determining the causes of driver unreliability in the human−vehicle−environment system requires thorough research. Unfortunately, in this case, experimental research with human involvement is limited in scope. This leaves modeling and simulation of the behavior of the human factor, i.e., the driver transporting dangerous goods. The human being, because of its complexity, is a challenging element to parameterize. The literature presents various attempts to model human actions. Herein, the authors used heuristic methods, specifically fuzzy set techniques, to build a human factor model. In these models, human actions were specified using a verbal or linguistic description. The specificity of the fuzzy sets allowed for “naturally” limiting the “precision” in describing human behavior. The model was built based on the author’s questionnaire and expert research, based on which individual features were selected. Then, the traits were assigned appropriate states. The output parameter of the model was λL—the intensity of human error. The obtained values of the intensity of the accident caused by the driver’s error were implemented into the author’s method of risk assessment. They constituted one of the factors determining the probability of an accident in the transport of dangerous goods, which allowed for determining the optimal route for the transport of these goods characterized by the lowest risk of an undesirable event on the route. The article presents the model’s assumptions, structure, and the features included in the model, all of which have the most significant influence on shaping the intensity of human error. The results of the simulation studies showed a diversified effect of the analyzed characteristics on the driver’s efficiency.