Browse Topic: Risk assessments
Aircraft Certification is a mature and complex bureaucracy that has successfully ensured a very high degree of safety of aircraft design, construction, operation and maintenance. Outside of a very few doing the work, there is a general lack of knowledge of certification details. For novel technologies such as electric power, and innovative configurations such as multi-rotors, the rules are far less mature and still emerging and so also poorly understood. Within the Advanced Air Mobility (AAM) initiative, many new aircraft developments are underway using novel configurations, and the public announcements of regulatory progress toward FAA or EASA Type Certification capitalize on this ignorance by being vague or even misleading. Honeywell conceived the Regulatory Readiness Level (RRL) indicator as an objective measure of certification status to serve the AAM industry and ecosystem, with applicability across aviation. The released RRL Version 1 now enables credible, objective assessment of
The airframe digital twin analysis framework developed at the National Research of Canada is being transposed to safe life applications for rotorcraft components. A probabilistic safe life prediction approach, consisting of uncertain material property data and uncertain load spectra is used to calculate risk assessment metrics, such as the cumulative probability of failure, the hazard rate, and the average hazard rate as a function of time. A demonstration of this approach is presented for a CH-146 Griffon component, for which the uncertain loads are estimated from a model developed through machine learning. This preliminary assessment shows the feasibility of using digital twin concepts as a viable alternative to traditional deterministic life predictions, with the potential to reduce maintenance costs and increase aircraft availability.
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This SAE EDGE™ Research Report builds a comprehensive picture of the current state-of-the-art of human-robot applications, identifying key issues to unlock the technology’s potential. It brings together views of recognized thought leaders to understand and deconstruct the myths and realities of human- robot collaboration, and how it could eventually have the impact envisaged by many.Current thinking suggests that the emerging technology of human-robot collaboration provides an ideal solution, combining the flexibility and skill of human operators with the precision, repeatability, and reliability of robots. Yet, the topic tends to generate intense reactions ranging from a “brave new future” for aircraft manufacturing and assembly, to workers living in fear of a robot invasion and lost jobs.It is widely acknowledged that the application of robotics and automation in aerospace manufacturing is significantly lower than might be expected. Reasons include product variability, size, design
Quantitative Risk Assessment has become essential in rotorcraft safety risk management. Measures of risk include Cumulative Fleet Risk (also called Risk Factor), Risk per Flight, and Risk per Flight Hour. Each measure applies to a different situation and can produce the same or different predictions of future risk. Risk for a large fleet of aircraft might be accurately predicted by Cumulative Fleet Risk, whereas Risk per Flight or Risk per Flight Hour might be best for a small fleet of rotorcraft, a flight test program, or a fleet with low flight hours. Calculating risk per flight hour seems as simple as dividing the number of previous occurrences by the flight hours for the total fleet, but this is appropriate only in the case of random distribution. Most failures that lead to hazards are not random because the failure mechanism has a specific cause. A more appropriate method is to develop the future event forecast using Quantitative Risk Assessment, then divide that by the future
Military rotorcraft engines operating in harsh environments routinely ingest large quantities of mineral dust, which can degrade components and ultimately reduce operability. Time off-wing for unscheduled maintenance is a costly burden, both financially and operationally. Rapidly predicting engine deterioration rates as a function of the mission presents an opportunity to optimise flow of supplies, better manage fleets, and perform safety risk assessments when dust loading is expected to be particularly high. In the current contribution, we present our ongoing efforts in this field with a new methodology for assessing the effectiveness of inertial particle separators and quantifying the changes they impart to the inbound dust. We demonstrate that both the concentration reduction and the modification to the particle size distribution can be made on the basis of a single independent variable- a generalised Stokes number for inertial particle separators- and a single performance parameter
This SAE Standard describes methods to understand the risks associated with vehicle mobile air conditioning (MAC) systems in all aspects of a vehicle’s lifecycle including design, production, assembly, operation, and end of life. Information for input to the risk assessment is provided in the appendices of this document. This information should not be considered to be complete, but only a reference of some of the data needed for a complete analysis of the risk associated with the use of refrigerants in MAC systems.
Unmanned aerial vehicles (UAVs) are an emerging technology with a large variety of commercial and military applications. In-flight icing occurs during flight in supercooled clouds or freezing precipitation and is a potential hazard to all aircraft. In-flight icing on UAVs imposes a major limitation on the operational envelope. This report describes the unsettled topics related to UAV icing. First, typical UAV applications and the general hazards of icing are described. Second, an overview of the special technical characteristics of icing on autonomous and unmanned aircraft is given. Third, the operational challenges for flight in icing conditions are discussed. Fourth, technologies for ice protection that mitigate the icing hazard are introduced. Fifth, the tools and methods required to understand UAV icing and to develop aircraft with cold-weather capabilities are presented. Finally, an assessment of the current and future regulations regarding icing on UAVs is provided.Icing is a key
Loss of Tail rotor Effectiveness (LTE) is a critical low-speed aerodynamic flight characteristic that causes an unanticipated rapid yaw rate that will not subside on its own. Multiple factors influence this aerodynamic condition, like environmental conditions, helicopter model specifications and phases of flight. However, predictions of which of those elements cause a higher risk for LTE has not been determined as of yet. Because of this knowledge gap, pilots are often not trained well enough to proactively recognize the proximity to LTE, leading to several accidents in which the pilot fails to maintain directional control. This study begins to characterize the factors that contribute to LTE and the importance of this to helicopter safety. An LTE bowtie diagram is proposed to support hazard risk assessment and mitigation. The diagram is built through accident reviews and aims to give pilots a schematic summary of all the scenarios that may lead to LTE. Further, a new systematic filter
The success of the flight mission is closely related to a wide set of factors that must be taken into consideration. Combining all these elements together, the risk associated to the flight can raise significantly, eventually resulting in a situation in which the flight should be cancelled, unless some mitigation of the risk factors are applied. The aim is the understanding of the expectable human abilities and limitations, in correlation with the aircraft status and all the external elements related to the flight. Following the guidance contained in Ref.1, this knowledge has being applied in the definition of a standardize approach for the design of the risk assessment procedures and software requirements. For the safety of the flight, it is essential that the pilot is able to discern in advance between a low and a high risk flight. With a Flight Risk Analysis Tool (FRAT) the pilot can proactively identify the hazard with a visual representation of the risk, applying an evaluation
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