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.

Application of the Advanced Methods to Investigate Incidents and Drilling Engineering Principles to Prevent Critical Wear-Out of Downhole Equipment When Drilling Wells in Chayandinskoye Field

The pressing challenge is the abnormally rapid wear of well logging equipment and drilling tools when drilling wells in pay zone of Chayandinskoye field. Wear-out of BHA stabilizers within one run makes directional drilling inefficient and results in additional trips to replace equipment. Wear-out of drill pipes results in emergencies risk increase. To prevent such incidents the necessity arises to conduct an unscheduled inspection, reject and replace drilling tools. All these conditions entail increase in drilling time and decline in profitability. Problem analysis and expert review was made by drilling optimization specialists from DD Contractor jointly with the experts from R&D Center and Operator Company. This paper discusses how cooperation of the engineers from three companies as well as a particular approach to incident investigation and drilling engineering made it possible to identify the most critical factors, which contribute to a standard BHA wear, to work out measures to prevent similar situations in future and select an alternative BHA. The gained experience has been successfully disseminated to the other wells in Chayandinskoye field and other fields in Eastern Siberia; and the incident investigation methods and drilling engineering procedures are effectively applied under the other projects.

Steganalysis of the methods of concealing information in graphic containers

Aim. Today, there is a pressing matter of protection against steganography-based attacks against information systems. These attacks present a danger as they use the most common data files – especially graphics files – as containers that deliver malicious code to a system or cause a leak of sensitive information. Developing methods of detecting such hidden information is the responsibility of a special subsection of steganography, the steganalysis. Such methods should be extensively used in computer forensics as part of security incident investigation, as well as in automated security systems with integrated modules for analyzing data files for malicious or dangerous information. An important feature of such activities is the need to examine a wide variety of elements and containing files. In particular, it is required to verify not only the colour values of the pixels in images, but their frequency characteristics as well. This raises a number of important questions associated with the best practices of applying steganalysis algorithms and making correct conclusions based on the outputs. The paper aims to briefly analyse the most important and relevant methods of steganalysis, both spatial and frequency, as well as to make conclusions regarding their performance and ways to analyse the outputs based on the test results of the software that implements such methods. Methods. The steganalysis of concealment within the least significant bits of an image’s pixels uses Pearson’s Chi-square statistical analysis, as well as the Regular-Singular method that involves signature analysis of pixel groups and analytical geometry tools for estimating the relative volume of the hidden message. The Koch-Zhao method of steganalysis is used for the purpose of detecting information embedded in the frequency-domain image representation. It also allows identifying the parameters required for extracting the hidden message. Results. A software suite was created that includes the software implementations of the analysed methods. The suite was submitted to a number of tests in order to evaluate the outputs of the examined methods. For the purpose of testing, a sample of images of various formats was compiled, in which information was embedded using a number of methods. Based on the results of the sample file analysis, conclusions were made regarding the efficiency of the analysed methods and interpretation of the outputs. Conclusion. Based on the test results, conclusions were made on the accuracy of the steganalysis methods in cases of varied size of the embedded message and methods of its concealment. The patterns identified with the help of the analysis outputs allowed defining a number of rules for translating the outputs into conclusions on the identification of the fact of detection of hidden information and estimation of its size.

Survey of junior doctors' perspective of serious incident reviews

AimsSerious incidents according to NHS England (2015) are incidents where the consequences to patients, families and carers, staff or organisations are so significant or potential for learning are so great that a heightened response is justified. There is anectoctal evidence that this process is potentially difficult for junior doctors and the primary purpose of learning may be lost due to the stress involved.Our aim was to evaluate junior doctors perspective of serious incident reviews. A secondary aim was to organise local and regional workshops based on the outcome of our findings to address misconceptions around serious incident investigations.MethodA survey was developed using survey monkey and distributed to all trainees across the Mersey region through the Medical Education teams.The junior doctors range from core trainees to higher trainees. The survey encouraged the use of free texting if necessary.Results from the survey were then analysedResult18 junior doctors across the 3 mental health Trusts in the Mersey region responded.12 respondents have been involved in a serious incident investigation in the past and 9 of the respondents stated that they did not recieve any support during the process. Out of the 3 that were supported, one rated the support as poor and frightening.55.56% af all respondents found the process of serious incident reviews hard to understand.66% of all respondents admitted that they are aware that the purpose of the review is for learning purposes.100% of respondents agreed that a workshop to discuss the purpose and process of serious incidents investigation to aid their understanding would be useful.ConclusionFrom the survey, we concluded that junior doctors do have some understanding of incident reviews process but they still do not feel comfortable with the idea of being under ‘investigation'.It is also important that formal support is made available during the process.We organised a workshop in one of the 3 Trusts which was well attended and junior doctors asked if they could sit on review panels for experiential learning. This is to be presented to govenance teams across the mental health trusts in the region.Further workshop across the 2 remaining Trusts could not be organised due to COVID-19 pandemic.

Focusing the Safety Spotlight: How Safety Intelligence Can Inform Systemic Patient Safety Initiatives

This panel discussion at the 2021 Human Factors and Ergonomics Society (HFES) Healthcare Symposium (HCS) touched upon several topics related to actioning safety intelligence to improve patient safety. The panel had representation from both Canada and England across a broad range of human factors expertise in healthcare: from the perspective of academic research, operational hospital work, patient safety incident investigation and national healthcare policy, and a nationwide healthcare liability insurer. The panelists began with defining safety intelligence and distinguishing between safety intelligence and safety wisdom. The panel provided an engaging and insightful discussion on several topics including data collection, analysis and actioning upon the insights gained. In addition, the panel discussed strategies for demonstrating value in improving patient safety, and emphasised the importance of aligning one’s work with existing initiatives in the organisation, as well as the importance of collaborating with various stakeholders across the system to affect meaningful change.

Medical device error and failure reporting: Learning from the car industry

Background Improving the design of technology relies in part, on the reporting of performance failures in existing devices. Healthcare has low levels of formal reporting of performance and failure of medical equipment. This paper examines methods of reporting in the car industry and healthcare and aims to understand differences and identify opportunities for improvement within healthcare. Methods A literature search was carried out in Pubmed, Medline, Embase, Engineering Village, Scopus. NHS England and MHRA publications and guidelines were also reviewed. Focus was placed on the current system of reporting in both industries, known degree of patient harm, initiating factors, barriers, quality and methods of incident investigation and their validity. The findings were used to compare error reporting system in the two industries. Results Derivation of healthcare incident data from different sources means the full extent of patient harm is not known. For example, in 2012 there were 13,549 and 38,395 incidents reported by MHRA and NRLS (National Reporting and Learning System) respectively leading to uncertainties on the extent of the problem. The car industry emphasises the role of reporting source in ensuring data quality. Utilising some aspects of this approach might benefit healthcare reporting. These include a specific reporting system that stresses the importance of organisational learning in improving safety and recognises the limitations of root cause analysis. Conclusions Learning from reporting systems within the car industry may help the healthcare sector improve its own reporting, aiding healthcare performance.

Incorporating Automatic Satellite Detections of Oil Spills with Numerical Fate and Trajectory Modeling

ABSTRACT In recent years, access to freely available and commercial satellite imagery, such as Sentinel-1, RADARSAT-2, COSMO-SkyMed, and TerrsSAR-X, increased to the level where most global waters are observed at least once per day by one of these satellite platforms. The availability of this data combined with technological advancements in machine-learning and smart image segmentation allows for the potential to automatically detect oil spills and reduce the likelihood of false alarms. This improved satellite monitoring could result in early discovery of releases and the ability to launch a quicker response to mitigate potential damages. Numerical modeling will be used in combination with the detection results to determine the fate and trajectory of the oil as well as to hindcast where the oil was released. Implementing models into the process facilitates an effective response and incident investigation by determining where the oil is spreading and discovering where the oil originated. In 2019, Petroleum Research Newfoundland and Labrador (PRNL) launched a project led by C-CORE and RPS titled SpillSight to conduct a study into this technology for automatically detecting spills by satellite and modelling the outputs.