958 resultados para systems safety


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This thesis highlights the limitations of the existing car following models to emulate driver behaviour for safety study purposes. It also compares the capabilities of the mainstream car following models emulating driver behaviour precise parameters such as headways and Time to Collisions. The comparison evaluates the robustness of each car following model for safety metric reproductions. A new car following model, based on the personal space concept and fish school model is proposed to simulate more precise traffic metrics. This new model is capable of reflecting changes in the headway distribution after imposing the speed limit form VSL systems. This research facilitates assessing Intelligent Transportation Systems on motorways, using microscopic simulation.

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In the long term, with development of skill, knowledge, exposure and confidence within the engineering profession, rigorous analysis techniques have the potential to become a reliable and far more comprehensive method for design and verification of the structural adequacy of OPS, write Nimal J Perera, David P Thambiratnam and Brian Clark. This paper explores the potential to enhance operator safety of self-propelled mechanical plant subjected to roll over and impact of falling objects using the non-linear and dynamic response simulation capabilities of analytical processes to supplement quasi-static testing methods prescribed in International and Australian Codes of Practice for bolt on Operator Protection Systems (OPS) that are post fitted. The paper is based on research work carried out by the authors at the Queensland University of Technology (QUT) over a period of three years by instrumentation of prototype tests, scale model tests in the laboratory and rigorous analysis using validated Finite Element (FE) Models. The FE codes used were ABAQUS for implicit analysis and LSDYNA for explicit analysis. The rigorous analysis and dynamic simulation technique described in the paper can be used to investigate the structural response due to accident scenarios such as multiple roll over, impact of multiple objects and combinations of such events and thereby enhance the safety and performance of Roll Over and Falling Object Protection Systems (ROPS and FOPS). The analytical techniques are based on sound engineering principles and well established practice for investigation of dynamic impact on all self propelled vehicles. They are used for many other similar applications where experimental techniques are not feasible.

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Safety at railway level crossings (RLX) is one part of a wider picture of safety within the whole transport system. Governments, the rail industry and road organisations have used a variety of countermeasures for many years to improve RLX safety. New types of interventions are required in order to reduce the number of crashes and associated social costs at railway crossings. This paper presents the results of a large research program which aimed to assess the effectiveness of emerging Intelligent Transport Systems (ITS) interventions, both on-road and in-vehicle based, to improve the safety of car drivers at RLXs in Australia. The three most promising technologies selected from the literature review and focus groups were tested in an advanced driving simulator to provide a detailed assessment of their effects on driver behaviour. The three interventions were: (i) in-vehicle visual warning using a GPS/smartphone navigation-like system, (ii) in-vehicle audio warning and; (iii) on-road intervention known as valet system (warning lights on the road surface activated as a train approaches). The effects of these technologies on 57 participants were assessed in a systematic approach focusing on the safety of the intervention, effects on the road traffic around the crossings and driver’s acceptance of the technology. Given that the ITS interventions were likely to provide a benefit by improving the driver’s awareness of the crossing status in low visibility conditions, such conditions were investigated through curves in the track before arriving at the crossing. ITS interventions were also expected to improve driver behaviour at crossings with high traffic (blocking back issue), which were also investigated at active crossings. The key findings are: (i) interventions at passive crossings are likely to provide safety benefits; (ii) the benefits of ITS interventions on driver behaviour at active crossings are limited; (iii) the trialled ITS interventions did not show any issues in terms of driver distraction, driver acceptance or traffic delays; (iv) these interventions are easy to use, do not increase driver workload substantially; (v) participants’ intention to use the technology is high and; (vi) participants saw most value in succinct messages about approaching trains as opposed to knowing the RLX locations or the imminence of a collision with a train.

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"HPIP/I-06(3.5)EW"--Back cover.

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The development of effective safety regulations for unmanned aircraft systems (UAS) is an issue of paramount concern for industry. The development of this framework is a prerequisite for greater UAS access to civil airspace and, subsequently, the continued growth of the UAS industry. The direct use of the existing conventionally piloted aircraft (CPA) airworthiness certification framework for the regulation of UAS has a number of limitations. The objective of this paper is to present one possible approach for the structuring of airworthiness regulations for civilian UAS. The proposed approach facilitates a more systematic, objective and justifiable method for managing the spectrum of risk associated with the diversity of UAS and their potential operations. A risk matrix is used to guide the development of an airworthiness certification matrix (ACM). The ACM provides a structured categorisation that facilitates the future tailoring of regulations proportionate to the levels of risk associated with the operation of the UAS. As a result, an objective and traceable link may be established between mandated regulations and the overarching objective for an equivalent level of safety to CPA. The ACM also facilitates the systematic consideration of a range of technical and operational mitigation strategies. For these reasons, the ACM is proposed as a suitable method for the structuring of an airworthiness certification framework for civil or commercially operated UAS (i.e., the UAS equivalent in function to the Part 21 regulations for civil CPA) and for the further structuring of requirements on the operation of UAS in un-segregated airspace.

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A proactive risk management strategy seeks to prevent accidents from taking place and maintain the safety of a system. In this context, the task of identifying and disseminating early warning signs and signals is among the most important. The problem is that warning signs that are present before an accident takes place are often being overlooked and not picked up or identified as warning signs. If these warning signs were responded to, then an accident may be averted. Accidents occuring in the critical domain of a drinking water treatments works can have serious implications for the public health of consumers of the water supplied. Realising and comprehending early warning signs is a major challenge for the domain of systems safety and especially in the domain of a water treatment works. The approaches that are typically used to enhance the realisation, comprehension and dissemination of early warning signs in the water treatment domain in Ireland mainly involves the creation of accident scenarios, the use of monitoring data and procedures for the dissemination of warnings. While all of these approaches are all useful to inform the mental or process models of possible accident scenarios, nevertheless, accidents are still occurring in this domain. Therefore, a new approach to enhance the comprehension of and effective dissemination of early warning signs is required in order to improve safety and proactive risk management strategies. The contributions of this thesis is the provision of a set of attributes associated with the early warning sign concept that provides meaningful data on the early warning signs and allows recipients to better comprehend them. The values of these attributes were customised for application in the water treatment domain. This research proves that early warning signs at a water treatment works received with information on their attributes are comprehended and communicated more effectively and efficiently than the usual pragmatic approach and thereby improves the safety and proactive risk management strategies.

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Software-based control of life-critical embedded systems has become increasingly complex, and to a large extent has come to determine the safety of the human being. For example, implantable cardiac pacemakers have over 80,000 lines of code which are responsible for maintaining the heart within safe operating limits. As firmware-related recalls accounted for over 41% of the 600,000 devices recalled in the last decade, there is a need for rigorous model-driven design tools to generate verified code from verified software models. To this effect, we have developed the UPP2SF model-translation tool, which facilitates automatic conversion of verified models (in UPPAAL) to models that may be simulated and tested (in Simulink/Stateflow). We describe the translation rules that ensure correct model conversion, applicable to a large class of models. We demonstrate how UPP2SF is used in themodel-driven design of a pacemaker whosemodel is (a) designed and verified in UPPAAL (using timed automata), (b) automatically translated to Stateflow for simulation-based testing, and then (c) automatically generated into modular code for hardware-level integration testing of timing-related errors. In addition, we show how UPP2SF may be used for worst-case execution time estimation early in the design stage. Using UPP2SF, we demonstrate the value of integrated end-to-end modeling, verification, code-generation and testing process for complex software-controlled embedded systems. © 2014 ACM.

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In some applications like fault analysis, fault location, power quality studies, safety analysis, loss analysis, etc., knowing the neutral wire and ground currents and voltages could be of particular interest. In order to investigate effects of neutrals and system grounding on the operation of the distribution feeders with faults, in this research a hybrid short circuit algorithm is generalized. In this novel use of the technique, the neutral wire and assumed ground conductor are explicitly represented. Results obtained from several case studies using IEEE 34-node test network are presented and discussed.

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National Highway Traffic Safety Administration, Washington, D.C.

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Real-time software systems are rarely developed once and left to run. They are subject to changes of requirements as the applications they support expand, and they commonly outlive the platforms they were designed to run on. A successful real-time system is duplicated and adapted to a variety of applications - it becomes a product line. Current methods for real-time software development are commonly based on low-level programming languages and involve considerable duplication of effort when a similar system is to be developed or the hardware platform changes. To provide more dependable, flexible and maintainable real-time systems at a lower cost what is needed is a platform-independent approach to real-time systems development. The development process is composed of two phases: a platform-independent phase, that defines the desired system behaviour and develops a platform-independent design and implementation, and a platform-dependent phase that maps the implementation onto the target platform. The last phase should be highly automated. For critical systems, assessing dependability is crucial. The partitioning into platform dependent and independent phases has to support verification of system properties through both phases.

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Users of safety-critical systems are expected to effectively control or monitor complex systems, with errors potentially leading to catastrophe. For such systems, safety is of paramount importance and must be designed into the human-machine interface. While many case studies show how inadequate design practice led to poor safety and usability, concrete guidance on good design practices is scarce. The paper argues that the pattern language paradigm, widely used in the software design community, is a suitable means of documenting appropriate design strategies. We discuss how typical usability-related properties (e.g., flexibility) need some adjustment to be used for assessing safety-critical systems, and document a pattern language, based on corresponding "safety-usability" principles

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Motion planning, or trajectory planning, commonly refers to a process of converting high-level task specifications into low-level control commands that can be executed on the system of interest. For different applications, the system will be different. It can be an autonomous vehicle, an Unmanned Aerial Vehicle(UAV), a humanoid robot, or an industrial robotic arm. As human machine interaction is essential in many of these systems, safety is fundamental and crucial. Many of the applications also involve performing a task in an optimal manner within a given time constraint. Therefore, in this thesis, we focus on two aspects of the motion planning problem. One is the verification and synthesis of the safe controls for autonomous ground and air vehicles in collision avoidance scenarios. The other part focuses on the high-level planning for the autonomous vehicles with the timed temporal constraints. In the first aspect of our work, we first propose a verification method to prove the safety and robustness of a path planner and the path following controls based on reachable sets. We demonstrate the method on quadrotor and automobile applications. Secondly, we propose a reachable set based collision avoidance algorithm for UAVs. Instead of the traditional approaches of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking control set design for the aircraft to avoid collision. We apply our approach to collision avoidance scenarios of quadrotors and fixed-wing aircraft. In the second aspect of our work, we address the high level planning problems with timed temporal logic constraints. Firstly, we present an optimization based method for path planning of a mobile robot subject to timed temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specifications such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications. Secondly, we also present a timed automaton based method for planning under the given timed temporal logic specifications. We use metric interval temporal logic (MITL), a member of the MTL family, to represent the task specification, and provide a constructive way to generate a timed automaton and methods to look for accepting runs on the automaton to find an optimal motion (or path) sequence for the robot to complete the task.

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The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.