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At least 19 records

Towards a Rigorous Basis for Specific Operations Risk Assessment of UAS

The Specific Operations Risk Assessment (SORA) guidance represents the consensus of various national aviation authorities on a common process to identify, qualitatively assess, and manage the safety risk posed by unmanned aircraft systems (UAS), when preparing the safety case required for regulatory approval to conduct certain types of operations. As such, it can be considered a de facto standard, being increasingly adopted by various relevant stakeholders. This paper first gives an overview of the SORA process and associated methods, identifying a number of inconsistencies in risk identification and assessment, also discussing plausible strategies to close the associated gaps. Then, we give a well-founded basis for the applicable concepts, such as barrier integrity, assurance, and robustness, following which we present a preliminary and simple probabilistic formalization of the underpinning barrier-based safety model. We illustrate our overall approach through a worked example, also discussing how a Bayesian framework can facilitate extending and enhancing our initial formalization. We conclude with a discussion of the opportunities afforded by our approach, such as a well-founded basis for barrier selection, whilst addressing the associated challenges. The main objective of this work is to complement the current SORA guidance through a principled, mathematicallybased approach to risk assessment, particularly when it is applied to higher-risk operational concepts that warrant greater rigor in safety assessment and assurance.

Safety Cases↗

Lunar Landing Operational Risk Model

Characterizing the risk of spacecraft goes beyond simply modeling equipment reliability. Some portions of the mission require complex interactions between system elements that can lead to failure without an actual hardware fault. Landing risk is currently the least characterized aspect of the Altair lunar lander and appears to result from complex temporal interactions between pilot, sensors, surface characteristics and vehicle capabilities rather than hardware failures. The Lunar Landing Operational Risk Model (LLORM) seeks to provide rapid and flexible quantitative insight into the risks driving the landing event and to gauge sensitivities of the vehicle to changes in system configuration and mission operations. The LLORM takes a Monte Carlo based approach to estimate the operational risk of the Lunar Landing Event and calculates estimates of the risk of Loss of Mission (LOM) - Abort Required and is Successful, Loss of Crew (LOC) - Vehicle Crashes or Cannot Reach Orbit, and Success. The LLORM is meant to be used during the conceptual design phase to inform decision makers transparently of the reliability impacts of design decisions, to identify areas of the design which may require additional robustness, and to aid in the development and flow-down of requirements.

Mattenberger, Chris↗

Evidence-Based Process for Assessing Teamwork Competencies in Applicant Performance in High-Risk, Operational Occupations

In this work, we provide a detailed look at how behavioral competencies necessary for high-risk, operational jobs, including task- and person-oriented aspects of teamwork, leadership, and followership, should be defined and operationalized in context. These competencies are thought to positively predict performance in aerospace professions. Indeed, the assessments applied in high stakes selection contexts and the way associated behavioral competencies are evaluated must be carefully considered to ensure that optimal applicants are selected. We provide insight into the behavioral competency development and measurement process, elaborating upon particularly critical competencies (i.e., team orientation) and describing challenges to measurement.

Isabel Bilotta↗

The importance of operations, risk, and cost assessment to space transfer systems design

This paper examines several methodologies which contribute to comprehensive subsystem cost estimation. The example of a space-based lunar space transfer vehicle (STV) design is used to illustrate how including both primary and secondary factors into cost affects the decision of whether to use aerobraking or propulsion for earth orbit capture upon lunar return. The expected dominant cost factor in this decision is earth-to-orbit launch cost driven by STV mass. However, to quantify other significant cost factors, this cost comparison included a risk analysis to identify development and testing costs, a Taguchi design of experiments to determine a minimum mass aerobrake design, and a detailed operations analysis. As a result, the predicted cost advantage of aerobraking, while still positive, was subsequently reduced by about 30 percent compared to the simpler mass-based cost estimates.

Ball, J. M.↗

Quantification of Operational Risk Using A Data Mining

What is Data Mining? - Data Mining is the process of finding actionable information hidden in raw data. - Data Mining helps find hidden patterns, trends, and important relationships often buried in a sea of data - Typically, automated software tools based on advanced statistical analysis and data modeling technology can be utilized to automate the data mining process

Perera, J. Sebastian↗

Ground Risk Informed Operational Planning for Small Unmanned Aerial Systems

Increasing quantities of small Unmanned Aerial Systems (sUAS) operations present many challenges in terms of safe adoption and integration into existing airspace. The ability to study and quantify the risk to third parties on the ground prior to flight is an important step toward enabling Beyond Visual Line of Sight (BVLOS) operations. The Ground Risk Assessment Service Provider (GRASP) software is a capability developed by NASA to assist with third-party risk quantification and risk-informed flight planning. In this paper, two nominal flight paths intended to represent an infrastructure inspection mission are evaluated using the software to demonstrate its utility. A method is also introduced for adding other NASA-developed capabilities into a single architecture to assess a broader set of operational risks associated with BVLOS operations. These capabilities include a navigation system performance prediction tool, a high fidelity vehicle dynamics model, high resolution wind field data, and other information pertinent to operators. Data produced by these capabilities are combined to enable use of the Performance Based Navigation (PBN) concept borrowed from conventional aviation, providing quantified flight path uncertainty for where the sUAS is likely to be relative to its nominal flight plan. Ground risk is assessed within this region of uncertainty, giving a higher level of confidence in the solution compared to an analysis of only the nominal flight path.

Ground Risk↗

An Evidenced-Based Approach for Estimating Decompression Sickness Risk in Aircraft Operations

Estimating the risk of decompression Sickness (DCS) in aircraft operations remains a challenge, making the reduction of this risk through the development of operationally acceptable denitrogenation schedules difficult. In addition, the medical recommendations which are promulgated are often not supported by rigorous evaluation of the available data, but are instead arrived at by negotiation with the aircraft operations community, are adapted from other similar aircraft operations, or are based upon the opinion of the local medical community. We present a systematic approach for defining DCS risk in aircraft operations by analyzing the data available for a specific aircraft, flight profile, and aviator population. Once the risk of DCS in a particular aircraft operation is known, appropriate steps can be taken to reduce this risk to a level acceptable to the applicable aviation community. Using this technique will allow any aviation medical community to arrive at the best estimate of DCS risk for its specific mission and aviator population and will allow systematic reevaluation of the decisions regarding DCS risk reduction when additional data are available.

Robinson, Ronald R.↗

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗

Human Research Program Human Health Countermeasures Element Extravehicular Activity (EVA) Risk Standing Review Panel (SRP)

The Extravehicular Activity (EVA) Risk Standing Review Panel (SRP) was favorably impressed by the operational risk management approach taken by the Human Research Program (HRP) Integrated Research Plan (IRP) to address the stated life sciences issues. The life sciences community at the Johnson Space Center (JSC) seems to be focused on operational risk management. This approach is more likely to provide risk managers with the information they need at the time they need it. Concerning the information provided to the SRP by the EVA Physiology, Systems, and Performance Project (EPSP), it is obvious that a great deal of productive activity is under way. Evaluation of this information was hampered by the fact that it often was not organized in a fashion that reflects the "Gaps and Tasks" approach of the overall Human Health Countermeasures (HHC) effort, and that a substantial proportion of the briefing concerned subjects that, while interesting, are not part of the HHC Element (e.g., the pressurized rover presentation). Additionally, no information was provided on several of the tasks or how they related to work underway or already accomplished. This situation left the SRP having to guess at the efforts and relationship to other elements, and made it hard to easily map the EVA Project efforts currently underway, and the data collected thus far, to the gaps and tasks in the IRP. It seems that integration of the EPSP project into the HHC Element could be improved. Along these lines, we were concerned that our SRP was split off from the other participating SRPs at an early stage in the overall agenda for the meeting. In reality, the concerns of EPSP and other projects share much common ground. For example, the commonality of the concerns of the EVA and exercise physiology groups is obvious, both in terms of what reduced exercise capacity can do to EVA capability, and how the exercise performed during an EVA could contribute to an overall exercise countermeasure prescription.

Norfleet, William↗

Robotic Recon for Human Exploration

Robotic reconnaissance has the potential to significantly improve scientific and technical return from lunar surface exploration. In particular, robotic recon may increase crew productivity and reduce operational risk for exploration. However, additional research, development and field-testing is needed to mature robot and ground control systems, refine operational protocols, and specify detailed requirements. When the new lunar surface campaign begins around 2020, and before permanent outposts are established, humans will initially be on the Moon less than 10% of the time. During the 90% of time between crew visits, robots will be available to perform surface operations under ground control. Understanding how robotic systems can best address surface science needs, therefore, becomes a central issue Prior to surface missions, lunar orbiters (LRO, Kaguya, Chandrayyan-1, etc.) will map the Moon. These orbital missions will provide numerous types of maps: visible photography, topographic, mineralogical and geochemical distributions, etc. However, remote sensing data will not be of sufficient resolution, lighting, nor view angle, to fully optimize pre-human exploration planning, e.g., crew traverses for field geology and geophysics. Thus, it is important to acquire supplemental and complementary surface data. Robotic recon can obtain such data, using robot-mounted instruments to scout the surface and subsurface at resolutions and at viewpoints not achievable from orbit. This data can then be used to select locations for detailed field activity and prioritize targets to improve crew productivity. Surface data can also help identify and assess terrain hazards, and evaluate alternate routes to reduce operational risk. Robotic recon could be done months in advance, or be part of a continuing planning process during human missions.

Deans, Matthew↗