The main objective of this project is to collaborate with aviation stakeholders (airspace regulators, airline operators, air traffic controllers and engine manufacturers) to enable the UK airspace infrastructure sector to use existing environmental science to minimize the risk of volcanic ash to aircraft. The specific project partners for this project are the Civil Aviation Authority (the UK's airspace infrastructure regulator), and British Airways (one of the UK's largest airline operators). The challenge facing the CAA is that new aircraft engine susceptibility guidelines from the engine manufacturers describe engine tolerance limits in terms of a dosage (i.e accumulated concentration over time) rather than a peak concentration. However, there are no fit-for-purpose tools for the aviation industry to estimate along-flight volcanic ash dosage. The CAA thus need new tools to support any decision to change volcanic ash regulations from current peak ash concentration limits to along-flight ash dosage limits. The challenge facing BA is, given such a change in regulation, how to plan safe flight-routes and evaluate post-flight exposure to volcanic ash. In this project we will address these challenges by combining volcanic ash concentration charts and optimal flight-routing software to create a proof-of-concept tool which will allow along-flight ash dosages and the associated uncertainty to be calculated for the first time. We will use this tool to determine the sensitivity of along-flight ash dosage estimations to the spatial and temporal resolution of the volcanic ash information. This will be achieved by combining volcanic ash data, generated during the NERC funded PURE programme, with time optimum routing software, developed as part of the NERC funded EXTRA project. The new knowledge developed in the project will be used by the CAA to support strategic decision making and will enable new regulations to be developed that are based on the latest understanding of volcanic ash hazard to aircraft engines. These new regulations will result in a more resilient UK airspace infrastructure. The proof-of-concept tools developed in the project will demonstrate how airline operators, such as British Airways, could implement these changes in operational flight planning procedures. This tool will also encourage the use of uncertainty information in operational decision making procedures. In summary, the project will take existing research and translate it into information that is relevant to the aviation industry leading to clear benefits for the whole aviation sector. The project will last 12 months and cost £111k at 80% FEC

Computers increasingly play vital roles in organisations - e.g., hospitals or factories - which thus become computer-based systems . The dependability of these systems is a major societal concern. In response, EPSRC funded the Dependability Interdisciplinary Research Collaboration (DIRC) between City, Edinburgh, Lancaster, Newcastle and York universities. DIRC was based on the premise that dependability must be studied not as a purely technical issue, but as a socio-technical property of the combination of a computing system with the environments in which it is procured, developed and used. DIRC thus assembled a world class interdisciplinary team of computer scientists, psychologists, sociologists and statisticians, which has achieved substantial results through a rare degree of collaboration between engineering and social sciences.INDEED will build on DIRC's results to address important challenges in extending these results and combining them with current practices, to ensure a real, long-term impact on the design and evaluation of dependable systems. It will apply a multidisciplinary approach in four major research activities:Timing and Structure. This work will further develop DIRC's time band concept for reasoning about processes that unfold on different time scales, from microseconds to days, within a system. We will define an appropriate descriptive language, and extend it to deal with probabilistic relationships between events in different time bands. We will then build a software tool to use in case studies, to validate the use of time bands in structuring dependable systems. Adaptation and diversity. This activity will help designers and assessors of socio-technical systems to address some of the hard problems caused by the difficulty of predicting how people adapt to computers. We will give designers greatly enhanced abilities to analyse quantitatively, control and exploit the phenomena of adaptation and diversity, which although often recognised in informal terms need more thorough and formal treatment. Our focus will be data-rich, knowledge intensive activities that are increasingly supported by automation.Responsibility and trust. Inappropriate allocation or perception of responsibilities, and inappropriate levels of trust in the various system components, are important causes of failure in computer-based systems. This work will support the modelling, management and analysis of responsibility and trust during the design and deployment of such systems, by developing the necessary notations, techniques and software tools.Confidence and Uncertainty in dependability cases. A case is the web of evidence and reasoning through which system dependability is assessed. DIRC defined confidence-based cases, which describe dependability claims together with the degree of confidence that can be had in them. We will produce methods for detailing and structuring cases, using the results of work on time bands; guidance for using more diverse evidence and arguments towards increasing confidence; new interdisciplinary understanding of the factors causing people to trust a case less (or more) than its contents warrant.These activities are integrated into a coherent programme of work. An integration mechanism is the use of real-world case studies where we work with our partners in the project (Voca, British Energy, CAA and Qinetiq) to challenge and validate our research.

Computers increasingly play vital roles in organisations - e.g., hospitals or factories - which thus become computer-based systems . The dependability of these systems is a major societal concern. In response, EPSRC funded the Dependability Interdisciplinary Research Collaboration (DIRC) between City, Edinburgh, Lancaster, Newcastle and York universities. DIRC was based on the premise that dependability must be studied not as a purely technical issue, but as a socio-technical property of the combination of a computing system with the environments in which it is procured, developed and used. DIRC thus assembled a world class interdisciplinary team of computer scientists, psychologists, sociologists and statisticians, which has achieved substantial results through a rare degree of collaboration between engineering and social sciences.INDEED will build on DIRC's results to address important challenges in extending these results and combining them with current practices, to ensure a real, long-term impact on the design and evaluation of dependable systems. It will apply a multidisciplinary approach in four major research activities:Timing and Structure. This work will further develop DIRC's time band concept for reasoning about processes that unfold on different time scales, from microseconds to days, within a system. We will define an appropriate descriptive language, and extend it to deal with probabilistic relationships between events in different time bands. We will then build a software tool to use in case studies, to validate the use of time bands in structuring dependable systems. Adaptation and diversity. This activity will help designers and assessors of socio-technical systems to address some of the hard problems caused by the difficulty of predicting how people adapt to computers. We will give designers greatly enhanced abilities to analyse quantitatively, control and exploit the phenomena of adaptation and diversity, which although often recognised in informal terms need more thorough and formal treatment. Our focus will be data-rich, knowledge intensive activities that are increasingly supported by automation.Responsibility and trust. Inappropriate allocation or perception of responsibilities, and inappropriate levels of trust in the various system components, are important causes of failure in computer-based systems. This work will support the modelling, management and analysis of responsibility and trust during the design and deployment of such systems, by developing the necessary notations, techniques and software tools.Confidence and Uncertainty in dependability cases. A case is the web of evidence and reasoning through which system dependability is assessed. DIRC defined confidence-based cases, which describe dependability claims together with the degree of confidence that can be had in them. We will produce methods for detailing and structuring cases, using the results of work on time bands; guidance for using more diverse evidence and arguments towards increasing confidence; new interdisciplinary understanding of the factors causing people to trust a case less (or more) than its contents warrant.These activities are integrated into a coherent programme of work. An integration mechanism is the use of real-world case studies where we work with our partners in the project (Voca, British Energy, CAA and Qinetiq) to challenge and validate our research.

Computers increasingly play vital roles in organisations - e.g., hospitals or factories - which thus become computer-based systems . The dependability of these systems is a major societal concern. In response, EPSRC funded the Dependability Interdisciplinary Research Collaboration (DIRC) between City, Edinburgh, Lancaster, Newcastle and York universities. DIRC was based on the premise that dependability must be studied not as a purely technical issue, but as a socio-technical property of the combination of a computing system with the environments in which it is procured, developed and used. DIRC thus assembled a world class interdisciplinary team of computer scientists, psychologists, sociologists and statisticians, which has achieved substantial results through a rare degree of collaboration between engineering and social sciences.INDEED will build on DIRC's results to address important challenges in extending these results and combining them with current practices, to ensure a real, long-term impact on the design and evaluation of dependable systems. It will apply a multidisciplinary approach in four major research activities:Timing and Structure. This work will further develop DIRC's time band concept for reasoning about processes that unfold on different time scales, from microseconds to days, within a system. We will define an appropriate descriptive language, and extend it to deal with probabilistic relationships between events in different time bands. We will then build a software tool to use in case studies, to validate the use of time bands in structuring dependable systems. Adaptation and diversity. This activity will help designers and assessors of socio-technical systems to address some of the hard problems caused by the difficulty of predicting how people adapt to computers. We will give designers greatly enhanced abilities to analyse quantitatively, control and exploit the phenomena of adaptation and diversity, which although often recognised in informal terms need more thorough and formal treatment. Our focus will be data-rich, knowledge intensive activities that are increasingly supported by automation.Responsibility and trust. Inappropriate allocation or perception of responsibilities, and inappropriate levels of trust in the various system components, are important causes of failure in computer-based systems. This work will support the modelling, management and analysis of responsibility and trust during the design and deployment of such systems, by developing the necessary notations, techniques and software tools.Confidence and Uncertainty in dependability cases. A case is the web of evidence and reasoning through which system dependability is assessed. DIRC defined confidence-based cases, which describe dependability claims together with the degree of confidence that can be had in them. We will produce methods for detailing and structuring cases, using the results of work on time bands; guidance for using more diverse evidence and arguments towards increasing confidence; new interdisciplinary understanding of the factors causing people to trust a case less (or more) than its contents warrant.These activities are integrated into a coherent programme of work. An integration mechanism is the use of real-world case studies where we work with our partners in the project (Voca, British Energy, CAA and Qinetiq) to challenge and validate our research.

The economic cost of the Eyjafjallajökull eruption in Iceland in 2010 due to the closure of UK and European airspace has been estimated at around £200m/day solely for the airline industry with total subsequent impacts on the global economy estimated at US$5bn. This volcanic event is economically the most high-impact, high-consequence regional scale volcanic event in recent history, and resilience to such events needs to be significantly increased. Assessing the economic risk of reoccurrence of such an event and development of this network is the goal of Developing the Resilience to Icelandic Volcanic Eruptions within the UK (DRIVE-UK). Economic resilience can be built by minimising the impact of such eruptions on UK and European airspace closure, which can be achieved through developing a more robust network of near-real-time observations. Observations need to be made in near-real-time as only then will decisions based on the measurements be able to guide the Civil Aviation Authority and National Air Traffic Service as to the necessity to close UK and European airspace. The sensors that will be considered are: satellite measurements, dedicated aircraft measurements, balloon borne instruments and lidar instruments. While each of these types of measurements played an important role in qualitative detection of volcanic ash from the Eyjafjallajökull eruption, the algorithms used for accurate determination of volcanic ash mass for each type of sensor had not been specifically developed, resulting in considerable time consuming post-processing. This resulted in accurate quantitative mass estimates only being available days, weeks, or months after the measurements had been made. Only by introducing new algorithms, data analysis techniques, and new novel measurements will closure of airspace in future volcanic ash episodes be avoided.