1,238 research outputs found

    Modelling the Risks Remotely Piloted Aircraft Pose to People on the Ground

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    Worldwide there is much e ort being directed towards the development of a framework of air- worthiness regulations for remotely piloted aircraft systems (RPAS). It is now broadly accepted that regulations should have a strong foundation in, and traceability to, the management of the safety risks. Existing risk models for RPAS operations do not provide a simple means for incorporating the wide range of technical and operational controls into the risk analysis and evaluation processes. This paper describes a new approach for modelling and evaluating the risks associated with RPAS operations near populous areas based on the barrier bow tie (BBT) model. A BBT model is used to structure the underlying risk management problem. The model focuses risk analysis, evaluation, and decision making activities on the devices, people, and processes that can be employed to reduce risk. The BBT model and a comprehensive set of example risk controls are presented. The general model can be applied to any RPAS operation. The foundations for quantitative and qualitative assessments using a BBT model are also presented. The modelling and evaluation framework is illustrated through its application to a case-study rotary wing RPAS for two operational scenarios. The model can be used as a basis for determining airworthiness certification requirements for RPAS

    Auralization of Air Vehicle Noise for Community Noise Assessment

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    This paper serves as an introduction to air vehicle noise auralization and documents the current state-of-the-art. Auralization of flyover noise considers the source, path, and receiver as part of a time marching simulation. Two approaches are offered; a time domain approach performs synthesis followed by propagation, while a frequency domain approach performs propagation followed by synthesis. Source noise description methods are offered for isolated and installed propulsion system and airframe noise sources for a wide range of air vehicles. Methods for synthesis of broadband, discrete tones, steady and unsteady periodic, and a periodic sources are presented, and propagation methods and receiver considerations are discussed. Auralizations applied to vehicles ranging from large transport aircraft to small unmanned aerial systems demonstrate current capabilities

    System elements required to guarantee the reliability, availability and integrity of decision-making information in a complex airborne autonomous system

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    Current air traffic management systems are centred on piloted aircraft, in which all the main decisions are made by humans. In the world of autonomous vehicles, there will be a driving need for decisions to be made by the system rather than by humans due to the benefits of more automation such as reducing the likelihood of human error, handling more air traffic in national airspace safely, providing prior warnings of potential conflicts etc. The system will have to decide on courses of action that will have highly safety critical consequences. One way to ensure these decisions are robust is to guarantee that the information being used for the decision is valid and of very high integrity. [Continues.

    An investigation into hazard-centric analysis of complex autonomous systems

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    This thesis proposes a hypothesis that a conventional, and essentially manual, HAZOP process can be improved with information obtained with model-based dynamic simulation, using a Monte Carlo approach, to update a Bayesian Belief model representing the expected relations between cause and effects – and thereby produce an enhanced HAZOP. The work considers how the expertise of a hazard and operability study team might be augmented with access to behavioural models, simulations and belief inference models. This incorporates models of dynamically complex system behaviour, considering where these might contribute to the expertise of a hazard and operability study team, and how these might bolster trust in the portrayal of system behaviour. With a questionnaire containing behavioural outputs from a representative systems model, responses were collected from a group with relevant domain expertise. From this it is argued that the quality of analysis is dependent upon the experience and expertise of the participants but this might be artificially augmented using probabilistic data derived from a system dynamics model. Consequently, Monte Carlo simulations of an improved exemplar system dynamics model are used to condition a behavioural inference model and also to generate measures of emergence associated with the deviation parameter used in the study. A Bayesian approach towards probability is adopted where particular events and combinations of circumstances are effectively unique or hypothetical, and perhaps irreproducible in practice. Therefore, it is shown that a Bayesian model, representing beliefs expressed in a hazard and operability study, conditioned by the likely occurrence of flaw events causing specific deviant behaviour from evidence observed in the system dynamical behaviour, may combine intuitive estimates based upon experience and expertise, with quantitative statistical information representing plausible evidence of safety constraint violation. A further behavioural measure identifies potential emergent behaviour by way of a Lyapunov Exponent. Together these improvements enhance the awareness of potential hazard cases

    Aerial Vehicles

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    This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

    Future technological factors affecting unmanned aircraft systems (UAS):a South African perspective towards 2025

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    The fact that pilots are not physically situated in the aircraft for UAS operations makes the current standards applicable to manned aircraft not suitable for UAS operations (FAA, 2013). FAA (2013:18) states that ―removing the pilot from the aircraft creates a series of performance considerations between manned and unmanned aircraft that need to be fully researched and understood to determine acceptability and potential impact on safe operations in the NAS. According to ERSG (2013), not all technologies necessary to ensure the safe integration of civil UASs into civilian airspace are available today. The extrapolation that can be made based on the above arguments is that advancement of UAS technologies will more likely have a significant bearing on the safe integration of UASs into civilian airspace. Therefore, as an identified research gap, the research/main objective of this research is to identify future technological factors affecting Unmanned Aircraft Systems in the Republic of South Africa leading towards the year 2025

    Risk-based regulation of unmanned aircraft systems

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    The aviation sector is faced with a novel array of new airspace users including Urban Air Mobility (UAM) concepts, personal air mobility vehicles, reusable space launch vehicles, and Unmanned Aircraft Systems (UAS). Focusing on UAS, there is much effort being directed towards the development of safety regulations for this industry. National Aviation Authorities (NAA) have advocated the adoption of a risk-based approach to the development of regulations, whereby regulations are driven by the outcomes of a systematic process to assess and manage identified safety risks. Central to a risk-based approach is the Safety Risk Management Process (SRMP). A review of relevant aviation safety policy, guidance and regulatory material found that aviation safety literature does not adequately address the uncertainty inherent to any SRMP. For example, when measuring risk, only the likelihood and severity are taken into consideration, with uncertainty generally not being mentioned. Where uncertainty is recognised, it is taken into consideration through the use of conservative worst-case assumptions. This can result in the imposition of overly stringent restrictions or worse, regulations that do not adequately mitigate safety risks. Subsequently, providing a more comprehensive treatment of uncertainty in the aviation SRMP is essential to the uptake of a risk-based approach to rule-making. Further, it follows that if assessments of performance can be uncertain, then these uncertainties also need to be accounted for in other NAA regulatory processes such as the regulatory compliance assessment and compliance finding processes. It was found that the current aviation compliance process does not provide an objective means for accounting for uncertainty. As a consequence, compliance assessments can be subjective and inconsistent, with regulators lacking the tools and processes to be able to make objective compliance findings on the basis of compliance risk. A means to enable NAA to account for uncertainty in regulatory compliance processes is needed. The overall aim of this thesis is to improve regulatory outcomes under the new paradigm of risk-based regulation, through providing a conceptual framework for the rational, transparent and systematic treatment of uncertainty in the risk assessment and regulatory decision-making processes. The thesis proposes the application of Bayesian methods and normative decision theory to the aviation safety regulatory process. System Safety Regulations (SSR), commonly referred to as "Part 1309" regulations, for UAS are used as a case study. It is posited that the general theoretical approach proposed in this thesis can improve the objectivity, consistency, and transparency of current aviation regulatory processes. The generalised approaches presented in this thesis enable the adoption of risk-based rulemaking for new aviation sectors and provides the theoretical basis for risk-based compliance; a paradigm shift in how aviation safety regulators approach risk-based regulation

    Coastal Eye: Monitoring Coastal Environments Using Lightweight Drones

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    Monitoring coastal environments is a challenging task. This is because of both the logistical demands involved with in-situ data collection and the dynamic nature of the coastal zone, where multiple processes operate over varying spatial and temporal scales. Remote sensing products derived from spaceborne and airborne platforms have proven highly useful in the monitoring of coastal ecosystems, but often they fail to capture fine scale processes and there remains a lack of cost-effective and flexible methods for coastal monitoring at these scales. Proximal sensing technology such as lightweight drones and kites has greatly improved the ability to capture fine spatial resolution data at user-dictated visit times. These approaches are democratising, allowing researchers and managers to collect data in locations and at defined times themselves. In this thesis I develop our scientific understanding of the application of proximal sensing within coastal environments. The two critical review pieces consolidate disparate information on the application of kites as a proximal sensing platform, and the often overlooked hurdles of conducting drone operations in challenging environments. The empirical work presented then tests the use of this technology in three different coastal environments spanning the land-sea interface. Firstly, I use kite aerial photography and uncertainty-assessed structure-from-motion multi-view stereo (SfM-MVS) processing to track changes in coastal dunes over time. I report that sub-decimetre changes (both erosion and accretion) can be detected with this methodology. Secondly, I used lightweight drones to capture fine spatial resolution optical data of intertidal seagrass meadows. I found that estimations of plant cover were more similar to in-situ measures in sparsely populated than densely populated meadows. Lastly, I developed a novel technique utilising lightweight drones and SfM-MVS to measure benthic structural complexity in tropical coral reefs. I found that structural complexity measures were obtainable from SfM-MVS derived point clouds, but that the technique was influenced by glint type artefacts in the image data. Collectively, this work advances the knowledge of proximal sensing in the coastal zone, identifying both the strengths and weaknesses of its application across several ecosystems.Natural Environment Research Council (NERC
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