Publications

Dynamic probabilistic risk assessment with K-shortest-paths planning for generating discrete dynamic event trees

Conventional risk assessment methods are often not well suited for fast-changing dynamic and complex systems since the results from the analysis may be averages or valid for a short time before the system's state changes. A response to this problem is dynamic probabilistic risk assessment (DPRA), which considers the ever-changing nature of such systems and how their dynamic behavior affects the likelihood of future accident scenarios. Performing DPRA is difficult for complex systems - i.e., systems with many interconnected subsystems and components, for example, autonomous systems. There is a combinatorial "explosion" when considering how component failures affect one another and the overall system performance, known in the DPRA literature as the "state explosion problem", causing DPRA methods to have poor computational performance for large-scale systems. Although solutions to state explosion alleviate the average-case performance, most DPRA methods remain computationally expensive, with exponential worst-case time complexities. In this paper, a method for solving DPRA problems with K-Shortest-Paths planning algorithms is proposed. The method, called KPRA, consists in framing a subset of DPRA problems as relaxed versions of the K-Shortest-Paths (KSP) planning problem, allowing these DPRA problems to be solved by a graph search algorithm called K*, which has a theoretical log-linear worst-case complexity. Therefore, in theory, KPRA with K* solves DPRA problems with computational performance better than exponential. KPRA was implemented and applied to a case study of DPRA for an autonomous ship for validation and comparison with conventional DPRA methods. The case study consists of two ships, one of them autonomous, in a crossing encounter with a possible collision risk. The task is to find the most critical situations for the autonomous ship, i.e., the scenarios where its collision risk is the highest. KPRA's performance in solving the case study is compared with two conventional DPRA methods. The results show that the KPRA implementation in this work can solve the case study, i.e., produce an output equivalent to the other methods, with a polynomial worst-case computational complexity, i.e., more efficiently than the other methods with exponential complexities.

A Risk Management Framework for Unmanned Underwater Vehicles Focusing on Human and Organizational Factors

This paper presents a risk management framework (RMF) for unmanned underwater vehicles (UUV). UUV are tethered or untethered vehicles operating in hazardous surroundings. The RMF, as one of the first for UUV, emphasizes the need for considering human and organizational factors impact on risk. A case study on risk assessment has been carried out, covering the risk of loss and mission abort of an autonomous underwater vehicle. It is based on a case study of the Applied Underwater Robotics Laboratory of NTNU, which operates several UUV. The assessment applies human reliability analysis, fault tree analysis, and event tree analysis. The case study identified measures for risk reduction, such as improvement and adaptation of procedures for maintenance, planning of missions, and fault recognition and solving.

Risk and Interdependencies in Critical Infrastructures

Today's society is completely dependent on critical networks such as water supply, sewage, electricity, ICT and transportation. Risk and vulnerability analyses are needed to grasp the impact of threat

Development of dynamic safety envelopes for autonomous remotely operated underwater vehicles

This paper describes the implementation of dynamic safety envelopes for Autonomous Remotely Operated Vehicles (AROVs). A safety envelope is defined as a three-dimensional spatial area around the AROV, which forms a virtual protective barrier against collision with known and unknown obstacles in the subsea environment. The Octree method is used to setup the cuboidal shape of the proposed safety envelope. A Fuzzy Inference System (FIS) is modeled to derive the size of the dynamic safety envelope. The three inputs of the proposed FIS are vehicle velocity, probability of acoustic sensor failure and time to collision risk indicator. A user interface allows for verification and visualization of the resulting dynamic safety envelope during live laboratory tests. The results show that similar to vehicular envelopes in other industries, dynamic safety envelopes can be implemented on AROVs. The proposed dynamic safety envelope may be used to model the behavior of AROVs when confronted with different collision scenarios.

Analysis of the Repairability of Ship Machinery Failures

No abstract is provided for this article.

A Novel Stpa Approach to Software Safety and Security in Autonomous Maritime Systems Design

For autonomous maritime systems, tasks and responsibilities are moving from the human operator to hardware and software, which means that the software part grows in size and complexity. Software failures may be introduced from the early life cycle phases intentionally or unintentionally, and these must be mitigated by safe and secure design approaches. This paper addresses the need for systematic and efficient software failure identification and risk mitigation and proposes a novel approach by extending the Systems-Theoretic Process Analysis (STPA) with the System Modeling Language (SysML) as a basis. To demonstrate the proposed method, a case study on a semi-autonomous ferry's navigation system that operates in automatic or manual control mode is performed. The control structure and its extension are modeled utilizing implementation platform independent software, hardware, and human operator parts, covering both the dynamic and static aspects of the software functions from the software specification. The focus is on creating an avoidance map data structure, including both moving and static obstacles to be avoided by the ferry and the subsequent process of collision risk warning calculation. An implementation platform independent software failure questionnaire is developed and applied for a structured and guided search of potential software failures. The criticality of the identified software failures is evaluated over the development of loss scenarios covering cascading failure effects in software. In the case study, the identified software failures are evaluated in a loss scenario where the ferry operates under foggy conditions. Lastly, related to the hazard evaluation and risk reduction of critical software failures, the paper discusses the classic and novel approaches to mitigation in the form of fallback procedures and operational constraints. The paper shows that critical software failures may be handled by design and testing techniques to minimize the potential impact on autonomous systems´ safety and security.

DERIVING SAFETY REQUIREMENT HIERARCHIES FOR FAMILIES OF MARITIME SYSTEMS

Ensuring the safety of advanced maritime vessels is a challenging task. While technological developments provide new options for their design and operation, the criteria for certification, such as class rules intended to ensure safety, may not be flexible enough to accommodate rapid changes. Innovation may enable more efficient, greener, and smarter systems but it may also introduce new hazards that are not addressed by current safety requirements. This paper proposes a method aimed at developing requirement hierarchies that are generic for a family of systems (such as a class of ships) and that can be adapted and specialised for a subset of the family or a particular system. Systems-theoretic process analysis (STPA) is used to develop safety requirements that are structured in a way that ensures that they can easily be kept up to date to accommodate new technological solutions and new alternatives for the design and operation of maritime vessels.

Application of systems engineering to integrate ageing management into maintenance management of oil and gas facilities

Oil companies and relevant institutions are becoming increasingly aware that effective measures must be put in place to extend the life of installations that are approaching, or have passed, the end of their design lifetime. The implementation of ageing management (AM) facilitates ensuring that the degradation of the installations is properly controlled and mitigated, and their integrity is maintained during the life extension. Integrating AM within an existing process such as maintenance management, which shares various goals and objectives with AM, seems to have several advantages over the alternative of creating a new process for AM. A key issue is to identify and optimize the changes in the maintenance management process for addressing and managing ageing. This paper reports on the use of a systems engineering approach and information models for identifying the “as is” and “to be” processes of existing maintenance management of an oil and gas facility in order to fulfill the new requirements for AM. The primary contribution of this report is to demonstrate the power of these models, combined with a systems engineering process, to reverse engineer legacy practices as the basis for introducing new processes, procedures and training. ©2013 Wiley Periodicals, Inc. Syst Eng 16:

Organisational safety indicators in aquaculture—a preliminary study

The aquaculture industry has since the 70's grown to become one of the most important industries in Norway.A safety challenge for the Norwegian fish farming companies is escape of salmon.During the last decade, the main cause to escapes has changed from structural failures to "human errors".The paper addresses the need for improving safety in fish farming operations by implementing systematic means for risk management.The objective of this preliminary study has been to evaluate whether the Operational Safety Condition (OSC) method provides a feasible tool for identifying and understanding organisational factors and conditions that influence safety levels at the fish farms.The basis for the study is escape of fish.The results demonstrates that OSC seems to be a promising tool for audits of the organisational safety conditions in aquaculture companies.

Bayesian network for decision making on ageing facilities

No abstract is provided for this article.

Online Probabilistic Risk Assessment of Complex Marine Systems

This book offers decision support tools to help operators to make better decisions and methodologies to improve the safety of automated maritime system

Risk Management in Aquaculture: Integrating Sustainability Perspectives

The aquaculture industry in Norway produced 1.3 million metric tons of fish in 2014, and further expansion is expected if the main sustainability challenges related to production and operation are mitigated. Major biological, operational and environmental challenges are parasite infection, fish escape, fish health, human injuries and fatalities. The larger farms, exposed locations, and sustainability challenges related to more production of salmon increases the need for efficient decision support methods and risk management. The combined effect of the technological development, with increased remote operation, autonomy and automation, and the production and operational challenges related to sustainability means that an interdisciplinary and systemic approach integrating risks to the environment, as well as to fish welfare and human safety, is needed. Therefore, the main contents of such a risk management approach are outlined in this paper. Potential users are fish farming companies, but the paper also addresses the need for an industry standard for sustainability and risk performance monitoring, which should be of interest to authorities and the whole industry. The paper concludes that risk management and sustainable development are complementary concepts that benefit each other because efficient risk management is decisive for achieving sustainability in aquaculture.

Risk Management of Autonomous Marine Systems and Operations

Autonomous systems may lead to smarter and more efficient operations, but emerging risks are involved, because of lack of knowledge and operational experience with such systems, and challenges related to verification of safe performance. The objective of this paper is to clarify, categorize, and classify risk related to autonomous marine systems, and establish a foundation for risk management of such systems. Autonomous systems are usually associated with unmanned systems, but several manned systems, e.g., offshore oil and gas rigs and ships with complex automation and dynamic positioning (DP) systems, have certain control functionality that may be characterized as autonomous. Therefore, this paper addresses both manned and unmanned systems with different levels of autonomy. This means that the concept of autonomy in this paper includes a range of systems and operations with increasing complexity and major hazard potential, even though autonomous ships are used to exemplify. Hence, the paper addresses a broader approach in contrast to the traditional focus on robotics.

A structured approach to improved condition monitoring

Improved condition monitoring of production equipment enhances process safety and the ability to prepare maintenance, to perform maintenance efficiently, and thus reduce downtime and associated costs. Currently, there is a somewhat limited focus on condition monitoring of static equipment, such as heat exchangers and separators. This is due to organizational barriers, available technology, and budget constraints at management level. The objective of this article is to present a three-step approach that supports the decision-maker in the selection of condition monitoring methods for production equipment. The approach is exemplified by a heat exchanger and the focus is on condition monitoring in the operational phase, including assessment of life cycle costs (LCC).

A system engineering approach to subsea spill risk management

In recent years, environmental protection has received more attention in society. In addition to the ecological effect of a hydrocarbon release into the sea, its environmental impact is assessed by considering the amount of pollutant discharged. Therefore, limiting the impact of a spill consists in lowering the volume of oil released and effective early detection is necessary for implementation of mitigating measures. Standards and guidelines have been established for developing effective sensor networks in the subsea templates for both monitoring purposes and data collection. Sensors provide various and heterogeneous amount of information about the subsea template they are monitoring. According to recent definitions of risk, the level of knowledge should be considered during the risk assessment and evaluation phases for better managing potential impacts. The information provided by sensor networks indeed may be used in this perspective. For example, sensor functionality may be included in dynamic fault tree analysis in updating the information about system deviations’ frequency. The work in this paper is focused on risk management using information provided from subsea sensor networks. The study adopts a top-down approach inspired by systems engineering to analyse the communication patterns among the different stakeholders. A real reference case from the oil and gas industry located in an environmentally sensitive area on the Norwegian Continental Shelf is used for testing the suggested approach. The case study refers to subsea monitoring of oil leakages from the wellhead templates. Different sensor configurations are considered in order to identify the one able to provide the most reliable information. Insights from the case study highlight how sensor data analysis may improve risk management and support operational decision making.

Maintenance strategies for deep‐sea offshore wind turbines

Purpose The objective of this paper is to outline a framework that guides the development of sound maintenance strategies and policies for deep‐sea offshore wind turbines. Design/methodology/approach An important challenge with offshore wind energy production is to reduce the high operation and maintenance costs. To decrease complexity, and structure the maintenance strategy developing process, systems engineering principles are used. Findings The framework facilitates integration of fragmented but valuable information from different disciplines in the development of sound maintenance strategies. In addition, the framework may be used to identify knowledge gaps, and areas for further research. Research limitations/implications The paper refers to research on deep‐sea offshore wind turbines, which is in its infancy, with a limited amount of data yet available for verification and validation. Deep‐sea offshore installations are not commercialized, and few pilot installations have been installed. Originality/value The design of the offshore wind turbines determines operation and maintenance features. Reducing operation and maintenance costs is necessary to make deep‐sea offshore wind projects viable in the first place. The framework contributes to the complicated development of maintenance strategies for a system not yet realized.

A Brief Overview of Some Methods and Approaches for Investigating Interdependencies in Critical Infrastructures

This chapter presents methods for analysing interdependencies in critical infrastructures. In general, there are three groups of methods for analysing interdependencies; (1) conceptual, (2) model and simulation and (3) empirical and knowledge-based approaches. Examples of methods belonging to these groups are presented. The latter part of the chapter discusses challenges related to modelling, focusing on how to deal with complexity, trade-offs between abstraction and fidelity, choice of consequence measures and obtaining information.

A Systematic Review of Risk Metrics for AI and Autonomous Systems