Safety-critical Areas Research Articles

Outcome evaluation of an educational programme for preventing recidivism by adult firesetters

PurposeIn intervening to prevent recidivism by adult firesetters, there is a dearth of standardised interventions and relatedly of controlled outcome evaluations. Although education is a common firesetter intervention, it is unclear if this changes behaviour of adults; a research situation the current study aimed to address.Design/methodology/approachThe rate of actual fire recidivism of participants of a standardised educational programme was compared using Cooke’s (1989) equation to expected rates based on the firesetting history of 93 referrals.FindingsResults indicated a significant large effect for the difference between the frequencies of expected and actual firesetting re-offences.Research limitations/implicationsLimitations of the one-group pretest–posttest design are discussed with respect to potential confounds.Practical implicationsThis paper adds to the literature on adult firesetter interventions and lends support to the use of fire education to prevent fire recidivism. It provides the first empirically validated example of a structured education programme for adult firesetters. Of interest to services piloting new intervention programmes, it reports an operationally efficient methodology for preliminary evaluation.Originality/valueTo the best of the authors’ knowledge, this is the first reported outcome study of a fire safety education programme for adults. The methodology adopted represents a means of preliminary evaluation in safety-critical areas where traditional evaluation designs are infeasible.

Real-time temperature calculation and temperature prediction of wet multi-plate clutches

Many applications of wet multi-plate clutches are within safety-critical areas since malfunction or failure of the clutch is often equivalent to “loss of drive”.The main criterion for the estimation of damage and endurance of wet multi-plate clutches is the temperature on the friction interface. Owing to the thin, rotating geometry of the plates, determination of relevant temperatures in operation mode is almost impossible. State of the art is that there is no general applicable model for real-time estimation of clutch temperatures during operation.This contribution presents a validated parametric real-time temperature model that is applicable to various use cases and operating conditions. The model enables the calculation of the actual clutch temperature during operation and the prediction of temperature for future shifting operations.The model is validated by comparing temperature measurements from a component test rig and from the KUPSIM thermal clutch design tool with the developed real-time temperature calculation. The validity of the model for serial parts from industry and automotive applications under various load cases (clutch mode, continuous slip, non-steady slip) is demonstrated. The deviation between measurement and calculation are typically very small (< 5 K). The temperature prediction allows a highly accurate (deviations typically < 5 K) conservative prediction of the thermal load for future shifting operations.The model can thus contribute to the increase of operational safety of wet multi-plate clutches while at the same time facilitating optimal component design by reducing thermal over-dimensioning of clutches.

Perturbation-based methods for explaining deep neural networks: A survey

• Overview of the black box problem in DNNs and XAI research. • Survey of perturbation-based attribution methods for different input data types. • Future directions for research on perturbation paradigm. Deep neural networks (DNNs) have achieved state-of-the-art results in a broad range of tasks, in particular the ones dealing with the perceptual data. However, full-scale application of DNNs in safety-critical areas is hindered by their black box-like nature, which makes their inner workings nontransparent. As a response to the black box problem, the field of explainable artificial intelligence (XAI) has recently emerged and is currently rapidly growing. The present survey is concerned with perturbation-based XAI methods, which allow to explore DNN models by perturbing their input and observing changes in the output. We present an overview of the most recent research focusing on the differences and similarities in the applications of perturbation-based methods to different data types, from extensively studied perturbations of images to the just emerging research on perturbations of video, natural language, software code, and reinforcement learning entities.

Investigation of the Influence of Tool Rake Angles on Machining of Inconel 718

It is essential for superalloys (e.g., Inconel 718) to obtain an anticipated surface integrity after machining, especially for safety critical areas (e.g., aerospace). As one of the main characteristics for cutting tools, the rake angle has been recognized as a key factor that can significantly influence the machining process. Although there are large research interests and outcomes in the machining of nickel-based superalloys, most of them focus on the surface integrity and macroscale temperature observation, whereas the temperature distribution in the tool rake face is not clear. Thus, it is necessary to investigate the basic role of rake angles and the tool–workpiece interaction mechanism to determine the machining condition variations and surface integrity. In the present study, both experimental and numerical methods are employed to explore the cutting force, thermal distribution, and shear angles during the process and the metallurgy characteristics of the subsurface after machining, as well as the mechanical properties. The research has emphasized the importance of rake angles on both the cutting process and machined surface integrity, and has revealed the microscale temperature distribution in the tool rake face, which is believed to have a close relationship with the tool crater wear. In addition, it is clearly presented that the surface generated with positive rake angle tools generates the minimum subsurface deformation and less strain hardening on the workpiece.

Augmented Markov Model for Enhancing Hazard Rate Result of Safety Critical Systems Possessing Diverse Redundant Architecture

Safety-critical systems in various industries such as transportation or nuclear energy have been paid more attention with the development of societies due to increased attachment of importance to the life of human, their property, and nature. While developing such systems, detailed availability and safety characteristics are to be taken into account in parallel with architectural design decisions such as synchronization between different computing units or real-time task management. For fulfilling top-level requirements in international standards, ambitious quantitative targets like 0.012 FIT for HW units are to be reached where the industry has difficulties to achieve it. In this paper, this problem is handled by proposing an augmented Markov model for diverse architectures that is superior to the formulas provided in the main safety standard IEC 61508 and previous studies. With the proposed method it is possible to cover all safety-relevant states, which leads to more accuracy and lower hazard rates helping to reach these ambitious quantitative targets. Besides, the reliability parameters are investigated and optimized to increase safety performance. Consequently, the proposed novel model including enhanced reliability parameters is used for an industry application, namely safety-critical computer used for unmanned metro and high-speed rail transportation. The result obtained by the proposed model is compared with the results obtained using state of art models in literature and using the formulas in IEC 61508. As domain independent references IEC 61508 and Markovian approach are used in the paper, this study is applicable to other safety critical areas such as automotive or avionic industry.

A collaborative virtual reality environment for liver surgery planning

Surgical planning software is a key component in the treatment of tumor diseases. However, desktop-based systems provide only limited visualization and interaction opportunities. Moreover, collaborative planning among members of a surgical team is only possible to a limited extent. In this work, a collaborative virtual reality (VR) environment to assist liver surgeons in tumor surgery planning is presented. Our aim is to improve virtual resection planning between surgeons in a remote or co-located environment. The system allows surgeons to define and adjust virtual resections on patient-specific organ 3D surfaces and 2D image slices. Changes on both modalities are synchronized, which will enable surgeons to iterate and refine the resection surfaces quickly. In addition, a real-time risk map visualization is presented that displays safety margins around tumors. An evaluation performed by liver surgeons provides information on potential benefits, such as the possibility to visualize complex cases and assessing the safety-critical areas, applicability, and limitations for further improvement.

Effectiveness of risk awareness perception training in dynamic simulator scenarios involving salient distractors

The Risk Awareness Perception Training (RAPT) has been shown to improve latent hazard anticipation in young drivers. However, previous evaluation scenarios in a driving simulator often lacked either dynamic road environment features or control for such variations. The current study investigated whether the effectiveness of RAPT persists even in the presence of dynamic and salient distractors. Twenty RAPT-trained drivers and twenty-one Placebo-trained young drivers (aged 18–21) drove through eight simulated driving scenarios with latent hazards. A pedestrian avatar served as a distractor and was placed across from the latent hazard location. In half of the scenarios, the pedestrian remained static while in the other half the pedestrian started to move, without potential interference with the driver’s travelling path, as the drivers approached the latent hazard. Consistent with previous research, RAPT-trained drivers demonstrated better latent hazard anticipation performance than Placebo-trained drivers regardless of dynamic movement of the pedestrian avatar. Additionally, RAPT-trained drivers adopted wider scanning patterns and fixated more frequently on both the latent hazard and the pedestrian compared to Placebo-trained drivers. The results imply that RAPT may protect drivers from being distracted by dynamic stimuli and allow them to scan safety–critical areas containing latent hazards. Furthermore, RAPT may not only improve tactical hazard anticipation skills, but also modal hazard anticipation skills in young drivers.

Oil Spill Response Planning For Amazon Region–A Crude Carrier Study Case

It is well-known that an adequate planning process is paramount for a response success in oil spill events. This is especially true for tankers leakages due to its dynamic nature and potential to cause severe environmental harms. Moreover, one of the most challenging planning dimensions for an adequate response is, certainly, the human and material mobilization logistics, which can be strongly limited in remote regions. In South America, one of the most worldwide preserved rainforest areas, the Amazon, which consists of more than 5 million square kilometers and contains a thousand rivers, is also one of the most remote area, with important logistics challenges for almost any human activity. Despite all these difficulties, however, since 1986 Brazil has been producing an average of 35.000 bpd of oil at Urucu Field, located close to the city of Coari, around 400 miles from the province capital, Manaus. Once produced, this oil is pumped through a pipeline until a terminal at Solimões river, where is loaded in tankers destined to Manaus. Although contingency facilities exist in these two cities, there is no support installation in any point over the 342 nautical miles of the journey. Therefore, this study aimed at identifying the major operational risks of this naval transport and at analyzing some specific contingency planning aspects. Initially, a total of 12 safety critical areas were identified during a field inspection trip along Solimões and Amazon rivers. For each point, a qualitative risk analysis was developed, using tropical environmental sensitivities indexes and an empirical oil slick forecast modelling, as well as an oil weathering modelling using the ADIOS2 computational package. Finally, a verification checklist with a scorecard system was developed and applied, in order to assess the oil spill response feasibility and rank the critical spots over the rivers courses. For all the points evaluated, around 30% of all accidental hypothesis were associated with a catastrophic risk, with most being identified as potentially causing a severe environmental impact. Besides, all the estimated response times calculated were insufficient to avoid oiling of the riverbanks. Finally, due also to strong currents and other limiting environmental conditions, all critical point displayed low scores for the response feasibility evaluation, with poor logistics being a key parameter. From these results, navigational safety recommendations and oil spill response planning guidelines were developed in order to minimize an accident occurrence probability and, hence, the risk associated with it.

CHALLENGES IN HOMOLOGATION PROCESS OF VEHICLES WITH ARTIFICIAL INTELLIGENCE

The traditional automotive homologation processes aim to ensure the safety of vehicles on public roads. Autonomous Vehicles (AV) with Artificial Intelligence (AI) are difficult to account for in these conventional processes. This research aims to map and attempt to close the gaps in the areas of testing and approval of such automated and connected vehicles. During our research into the homologation process of traditional vehicles; functional safety issues, challenges of AI in safety critical systems, along with questions of cyber security were investigated. Our process focuses on the integration of the already existing functions and prototypes into new products safely. As a key result, we managed to identify the main gaps between Information and Communication Technology (ICT) and automotive technology: the rigidity of the automotive homologation process, functional safety, AI in safety critical areas and we propose a solution.

Integrity for autonomous vehicles and towards a novel alert limit determination method

Integrity is one critical performance indicator for navigation in safety-critical applications such as autonomous vehicles. Alert limit is one of the representative parameters in integrity monitoring which defines the maximum tolerable positioning error for an operation to safely proceed. But the integrity requirements for global navigation satellite system (GNSS) assessment are quite different from those for other applications. For autonomous vehicles, a reasonable alert limit needs to ensure the vehicle security and take full advantage of the space between vehicle and lane as much as possible. Based on the analysis of integrity application differences from civil aviation to autonomous vehicles, an improved alert limit determination method is proposed in this paper. The kinematic model is firstly introduced into the online determination of alert limit. The integrity risk on two sides are allocated optimally respect to the road geometry and kinematic model. The fixed cuboid bounding box is replaced by a subversive fan-shaped bounding box which is more reasonable to cover the safety-critical areas. The discussion compared with the Ford model also verified the superiority of the proposed method. Finally the paper also gives the alert limits calculated based on the Chinese standards and hopefully it could provide some references for the navigation integrity assessment for autonomous vehicles.

Numerical and experimental investigation of tool geometry effect on residual stresses in orthogonal machining of Inconel 718

Residual stress has become more important than ever with the increasing performance requirement of components especially for those applied in safety-critical areas. As the machining process is fundamentally correlated with the acquired component properties, it is essential to fully understand the formation mechanism of residual stresses in the cutting process and its influence on the performance of the component. This paper presents results based on numerical and experimental analysis on the effect of tool geometry on thermal-mechanical load and residual stresses in orthogonal machining Inconel718 alloy. The Coupled Eulerian-Lagrangian (CEL) method is used to simulate the effect of tool geometry on temperatures, forces, equivalent plastic strains, and residual stresses. The local normal/tangential stress is introduced to determine the degree of the tensile plastic deformation induced by the tool. It is observed that a negative rake angle and a sharp edge radius tool tend to generate more compressive stress on the machined surface than the ones generated with positive rake angle tools and/or lager edge radius. Besides, an increase in flank wear produces less magnitude of compressive stress in subsurface due to a decreased local normal stress caused by increased flank contact length.

A Performance Analysis Framework of Time-Triggered Ethernet Using Real-Time Calculus

With increasing demands of deterministic and real-time communication, network performance analysis is becoming an increasingly important research topic in safety-critical areas, such as aerospace, automotive electronics and so on. Time-triggered Ethernet (TTEthernet) is a novel hybrid network protocol based on the Ethernet standard; it is deterministic, synchronized and congestion-free. TTEthernet with a time-triggered mechanism meets the real-time and reliability requirements of safety-critical applications. Time-triggered (TT) messages perform strict periodic scheduling following the offline schedule tables. Different scheduling strategies have an effect on the performance of TTEthernet. In this paper, a performance analysis framework is designed to analyze the end-to-end delay, backlog bounds and resource utilization of network by real-time calculus. This method can be used as a base for the performance evaluation of TTEthernet scheduling. In addition, this study discusses the impacts of clock synchronization and traffic integration strategies on TT traffic in the network. Finally, a case study is presented to prove the feasibility of the performance analysis framework.

Linear and Nonlinear Deformation Effects in the Permanent GNSS Network of Cyprus.

Permanent Global Navigation Satellite Systems (GNSS) reference stations are well established as a powerful tool for the estimation of deformation induced by man-made or physical processes. GNSS sensors are successfully used to determine positions and velocities over a specified time period, with unprecedented accuracy, promoting research in many safety-critical areas, such as geophysics and geo-tectonics, tackling problems that torment traditional equipment and providing deformation products with absolute accuracy. Cyprus, being located at the Mediterranean fault, exhibits a very interesting geodynamic regime, which has yet to be investigated thoroughly. Accordingly, this research revolves around the estimation of crustal deformation in Cyprus using GNSS receivers. CYPOS (CYprus POsitioning System), a network of seven permanent GNSS stations has been operating since 2008, under the responsibility of the Department of Lands and Surveys. The continuous flow of positioning data collected over this network, offers the required information to investigate the behavior of the crustal deformation field of Cyprus using GNSS sensors for the first time. This paper presents the results of a multi-year analysis (11/2011–01/2017) of daily GNSS data and provides inferences of linear and nonlinear deforming signals into the position time series of the network stations. Specifically, 3D station velocities and seasonal periodic displacements are jointly estimated and presented via a data stacking approach with respect to the IGb08 reference frame.

Enhancement of Safety and Design in Cargo Handling Spaces to Prevent Accidental Fire or Explosion in Oil Tankers and FPSOs

Over the last few decades, there have been a significant number of accidents on crude oil tankers, floating production storage and offloading (FPSO) and offshore units due to fire and explosion, which have resulted in loss of lives, assets, and environmental damage. These incidents increase scrutiny and questions on the current level of safety design in hydrocarbon handling spaces and other high-risk spaces in oil tankers and FPSOs. There are many factors which may contribute to these incidents, including; defects of equipment and components, overlook during design, inappropriate maintenance procedure and history, improper workmanship, and lack of company safety procedures and instruction during maintenance and emergency responses. This study is focused on and has discussed all safety aspects and barriers for the enclosed cargo-handling spaces in tankers and offshore units. Various existing regulations, standards, and guidelines have addressed safety design of enclosed cargo-handling spaces. These requirements and guidelines are referred and investigated to identify typical industry gaps in design and to recommend best engineering practices. The proposed key design recommendations may be considered at the early design stage of new building or conversion projects to enhance the overall safety and to reduce the likelihood of critical safety events. 1. Introduction The offshore and marine industry face many inherent risks such as failure of equipment and structural integrity, collision, grounding, dropped objects, leakages, fire and explosions. Because of the constant transfer and handling of hydrocarbons in operational profile, oil tankers and floating production storage and offloading (FPSO) units have significant potential fire and explosion risks unless sound safety barriers are considered throughout all phases of the design and the construction. Often a FPSO conversion project, which uses an ageing crude oil tanker, is the preferred choice to provide a functioning FPSO facility to the offshore oil production market in timely manner. When compared with newbuilding FPSOs, a conversion project can provide shorter construction schedule and cost reduction benefits. Considerable number of FPSOs operating in the market apply a conversion-type approach, using existing oil tankers to convert to FPSOs. In a FPSO conversion project, the existing cargo pump room is used for the hydrocarbon cargo handling, transfer and offloading operations. The use of the conventional cargo pump room configuration in newly operating FPSOs has come under scrutiny compared with newbuilding projects, which typically install independent cargo pumps, such as a submergible or deepwell type, within each tank which minimizes the risk of hydrocarbon leaks to other confined spaces. The conventional pump room configuration has always presented high risks and concerns due to confined spaces, many potential leak sources, hydrocarbon handling equipment and piping, where leaks can build an explosive environment easily, and the location is situated near the safety critical areas such as accommodation, engine room, and control spaces.

The Performance Quantitative Model Based on the Specification and Relation of the Component

The trustworthiness of software is crucial to some safety critical areas. Performance is an important attribute of software trustworthiness. Software component technology is the mainstream technology of software development. How to achieve the performance of component systems efficiently and accurately is a challenging issue for component-based software development. In this paper, the performance quantification method of the component is proposed. First, performance specification is formally defined. Second, a refinement relation is introduced and the performance quantification method of the component system is presented. Finally, a case study is given to illustrate the effectiveness of the method.

Innovative technologies in training and education for maintenance team of NPPs

Many industries, such as nuclear power plants, chemical industry, oil and gas industry have dangerous working environments and hazardous conditions for employees. Maintenance, inspection and decommissioning activities in these safety-critical areas mean a serious risk, downtime is a significant financial loss. The Virtual Reality Training Platform is reflecting on this shortcoming, by providing the possibility for maintenance workers to be trained and prepared for unexpected scenarios, and to learn complex maintenance protocols without being exposed to unnecessary danger, like high temperature, radiation, etc. Employees can have training for equipment maintenance, dismantling of facilities at closed NPP Units. One of the most significant and unique added value of the immersive virtual reality solution is that the operator can experience lifelike emergencies (detonation, shutdown) under psychological pressure, while all of the physiology indicators can be monitored like eye-tracking. Users can work together anywhere in the world. A huge financial outage in industrial production is the preparation and maintenance downtime, which can be significantly reduced by the Virtual Training platform. This method can increase the accuracy, safety, reliability, and accountability of the maintenance and decommissioning procedures, while operational costs can be reduced as well.

\u2018The big buzz\u2019: a qualitative study of how safe care is perceived, understood and improved in general practice

BackgroundExploring frontline staff perceptions of patient safety is important, because they largely determine how improvement interventions are understood and implemented. However, research evidence in this area is very limited. This study therefore: explores participants’ understanding of patient safety as a concept; describes the factors thought to contribute to patient safety incidents (PSIs); and identifies existing improvement actions and potential opportunities for future interventions to help mitigate risks.MethodsA total of 34 semi-structured interviews were conducted with 11 general practitioners, 12 practice nurses and 11 practice managers in the West of Scotland. The data were thematically analysed.ResultsPatient safety was considered an important and integral part of routine practice. Participants perceived a proportion of PSIs as being inevitable and therefore not preventable. However, there was consensus that most factors contributing to PSIs are amenable to improvement efforts and acknolwedgement that the potential exists for further enhancements in care procedures and systems. Most were aware of, or already using, a wide range of safety improvement tools for this purpose. While the vast majority was able to identify specific, safety-critical areas requiring further action, this was counter-balanced by the reality that additional resources were a decisive requirment.ConclusionThe perceptions of participants in this study are comparable with the international patient safety literature: frontline staff and clinicians are aware of and potentially able to address a wide range of safety threats. However, they require additional resources and support to do so.

On the track of human errors - Procedure and results of an innovative assembly planning method

Manual assembly operations are the endmost place of the production process and with it represent a melting pot for organizational, time-related and qualitative errors of manufacturing. Because competitive advantages are increasingly determined in the manual assembly, the creation of economical and reliable work steps is of fundamental importance for future business success. For that reason, at the institute of the authors, a procedure has been developed to use the knowledge of the Expert System for Task Taxonomy that was originally developed to evaluate the error rate of control and surveillance activities in safety critical areas for creating a computer-aided expert system that allows predicting human error probabilities for manual assembly operations. Applying this expert system, production processes can already be optimized during the phase of product design by avoiding critical process steps at an early stage of the planning process. On the basis of a case study, this paper introduces the conception of an Excel-based software tool that allows an automated application of the developed assembly planning method and thereby, generates reliable risk analyses of manual work tasks with little expenditure of personnel and time.

A Subjective and Objective Integration Approach of Determining Weights for Trustworthy Measurement

The trustworthiness of the software is crucial to some safety-critical areas. Often, it is measured through the trustworthy degree of software attributes. Weights play key roles in obtaining accurate measurement. How to determine weights of different attributes is a challenge. In this paper, we propose an approach for determining weights. First, we construct positive reciprocal matrices by the evaluations of different experts, and the subjective weights are obtained by aggregating the matrices. In addition, we prove that the aggregation matrix preserves some properties, which further shows that our method is reasonable. Then, we acquire objective weights based on the trustworthy degrees of the attributes and the subjective weights. Finally, we propose an approach for determining weights based on the subjective and objective integration. A case study is presented, which shows that the proposed method is effective.

Dependability analysis of cyber physical systems

As cyber physical system (CPS) is often used in safety critical areas, dependability of the system is an important issue that needs to be analysed. Any failure on the components of the CPS could result in a degradation of the physical state, which then causes major harm to life and/or property. Since the concept of dependence leads to that of trust, the subsystems of the CPS should be dependable to each other to deliver the requested services as specified without failing during its operation. In this study, the authors apply Markov chain to model and analyse the component dependability of CPSs and propose the recovery techniques to guarantee a high level of dependability so as to take care of assuring the continuity of system operation.