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NASA NTRS2018

Survey of Methods to Predict Controller Workload for Real-Time Monitoring of Airspace Safety

The Real Time Safety Monitoring (RTSM) approach allows for assessment and prediction of the safety margin in the National Airspace System (NAS) to help preempt incidents and accidents, rather than having to reactively mitigate them. In RTSM, the NAS is modeled using state variables, and safety metrics are defined in terms of these state variables. The safety metrics have been classified as weather-related, airspace-related, and human-related. Many of the formulated human-related safety metrics need an estimate of the controller workload for their computation. However, this computation is not trivial. Hence, in this report, we perform a literature survey to identify the different factors that enable the computation of controller workload and categorize these factors. Next, we describe studies undertaken to determine a minimal set of factors that pro- vide a correct assessment of controller workload. Lastly, we survey approaches for evaluating how well the selected factors correlate with the controllers' subjective assessment of their workload. Based on this survey, we present factors beneficial to computing and predicting controller workload in real time, and discuss the status of data sources necessary for these computations.

National Airspace System↗

NASA NTRS2018

Annex H - SORA & UTM

This is a briefing to provide an overview of the contents of the Annex H of the Specific Operation Risk Assessment (SORA) document. This annex focuses on the application of UTM to SORA methodology.

UTM (Unmanned Aviation Systems)↗

NASA NTRS2010

System Architectural Considerations on Reliable Guidance, Navigation, and Control (GN and C) for Constellation Program (CxP) Spacecraft

This final report summarizes the results of a comparative assessment of the fault tolerance and reliability of different Guidance, Navigation and Control (GN&C) architectural approaches. This study was proactively performed by a combined Massachusetts Institute of Technology (MIT) and Draper Laboratory team as a GN&C "Discipline-Advancing" activity sponsored by the NASA Engineering and Safety Center (NESC). This systematic comparative assessment of GN&C system architectural approaches was undertaken as a fundamental step towards understanding the opportunities for, and limitations of, architecting highly reliable and fault tolerant GN&C systems composed of common avionic components. The primary goal of this study was to obtain architectural 'rules of thumb' that could positively influence future designs in the direction of an optimized (i.e., most reliable and cost-efficient) GN&C system. A secondary goal was to demonstrate the application and the utility of a systematic modeling approach that maps the entire possible architecture solution space.

Dennehy, Cornelius J.↗

NASA NTRS2018

Effects of Aircraft Health on Airspace Safety

This manuscript investigates the effects of aircraft health on the surrounding airspace, and proposes a methodology to understand how different aircraft-level faults (system faults, communication faults, etc.) can adversely affect the safety of the airspace, and qualitatively assess the impact of such faults on airspace safety metrics (such as congestion, controller/pilot workload, etc.). The topic of systems health management deals with continuously monitoring the performance of an engineering system, identifying and detecting the presence of faults, predicting the growth/progression of faults, computing the remaining useful life, and aiding online decision-making for the robust, continued operation of such engineering systems. The topic of real-time airspace modeling and safety analysis deals with defining and computing safety metrics for airspace operations in order to support risk-informed decision-making activities for various airspace entities including pilots, air traffic controllers, airlines, etc. This report presents recent research efforts that focus on combining multiple aspects of the aforementioned topics, and investigates the impact of aircraft-level faults on the airspace safety

Aircraft Health↗

NASA NTRS1993

Risk management for the Space Exploration Initiative

Probabilistic Risk Assessment (PRA) is a quantitative engineering process that provides the analytic structure and decision-making framework for total programmatic risk management. Ideally, it is initiated in the conceptual design phase and used throughout the program life cycle. Although PRA was developed for assessment of safety, reliability, and availability risk, it has far greater application. Throughout the design phase, PRA can guide trade-off studies among system performance, safety, reliability, cost, and schedule. These studies are based on the assessment of the risk of meeting each parameter goal, with full consideration of the uncertainties. Quantitative trade-off studies are essential, but without full identification, propagation, and display of uncertainties, poor decisions may result. PRA also can focus attention on risk drivers in situations where risk is too high. For example, if safety risk is unacceptable, the PRA prioritizes the risk contributors to guide the use of resources for risk mitigation. PRA is used in the Space Exploration Initiative (SEI) Program. To meet the stringent requirements of the SEI mission, within strict budgetary constraints, the PRA structure supports informed and traceable decision-making. This paper briefly describes the SEI PRA process.

Buchbinder, Ben↗

NASA NTRS2020

End-to-End Assessment of Artemis-1 Development Flight Instrumentation

As the space industry continues to strive for more efficient launch vehicles they must rely on increasingly accurate predictive models. Verification of models typically requires physical testing. Flight data measurements offer the most real and therefore the most accurate data for model correlation. As NASA prepares for the inaugural launch of their new Space Launch System (SLS), Artemis-1, they must rely heavily on predictive system models to ensure flight safety. Artemis-1 will be an unmanned scientific mission with the intent of blazing a trail for future manned missions. NASA has implemented a system of Development Flight Instrumentation (DFI) in the hopes of recovering useful flight data during liftoff and ascent to aid in correlating their predictive models to ensure human safety in future missions. An end-to-end assessment of the DFI system was performed to verify data acquired during Artemis-1 would be adequate for the targeted flight test objectives (FTOs). This was accomplished using a computational simulation of all sensors and Data Acquisition (DAQ) parameters to investigate any potential problem areas in the current architecture. Input nominal signals were approximated and injected into the system model. Synthesized acquired signals were recovered to verify FTO success.

Flight measurement↗

NASA NTRSDate not supplied

A Model-Based Systems Engineering Evaluation of the Evolution to an In-Time Aviation Safety Management System

In 2018, as result of a recommendation from the National Academies, NASA began to prototype an In-Time Aviation Safety Management System(IASMS). The purpose of the IASMS is to enable innovative aviation operations and greater heterogeneity of the overall National Airspace (NAS) by automating much of the safety monitoring, assessment, and risk and hazard mitigation functionspresent in today’s Safety Management Systems (SMS). NASA has worked together with early industry collaborators to understand how such a system might work and has published several early Concepts of Operation (ConOps) and other technical memoranda that illustrate the primary considerations for selected aviation domains. The shift from an SMS to an IASMS is predicated on several assumptions, including: 1.) automating safety functions will decrease the amount of time necessary for risk and hazard identification and analysis, making it more likely that safety concerns are understood ‘in-time’ to mitigate them, and 2.) an IASMS will allow easier tailoring of safety management processes to the particular risks and hazards inherent to that aviation operation. In this paper, we begin to validate these assumptions through the use of Model-Based Systems Engineering (MBSE).

In-time Aviation Safety Management System↗

NASA NTRS1999

A Probabilistic Approach of Incorporating Safety and Reliability in System Designs for a Manned Mission to Mars

Conceptual stages in mission design often lack the input of quantitative safety and reliability assessments, simply because failure rates or other data are not yet available for systems that have not yet been designed. Absence of such data should not, however, prevent the development of a quantitative risk models with placeholders for missing data. Functions (that is, actions the systems must perform) in mission design will eventually require system probabilities of success, and there could be much learned from surrogate data, adequately bounded in uncertainty, used in a large event tree model of a complex mission.

Railsback, Jan W.↗

NASA NTRS1994

Generalized implementation of software safety policies

As part of a research program in the engineering of software for safety-critical systems, we are performing two case studies. The first case study, which is well underway, is a safety-critical medical application. The second, which is just starting, is a digital control system for a nuclear research reactor. Our goal is to use these case studies to permit us to obtain a better understanding of the issues facing developers of safety-critical systems, and to provide a vehicle for the assessment of research ideas. The case studies are not based on the analysis of existing software development by others. Instead, we are attempting to create software for new and novel systems in a process that ultimately will involve all phases of the software lifecycle. In this abstract, we summarize our results to date in a small part of this project, namely the determination and classification of policies related to software safety that must be enforced to ensure safe operation. We hypothesize that this classification will permit a general approach to the implementation of a policy enforcement mechanism.

Knight, John C.↗

NASA NTRS2007

GN&C Engineering Best Practices For Human-Rated Spacecraft Systems

The NASA Engineering and Safety Center (NESC) recently completed an in-depth assessment to identify a comprehensive set of engineering considerations for the Design, Development, Test and Evaluation (DDT&E) of safe and reliable human-rated spacecraft systems. Reliability subject matter experts, discipline experts, and systems engineering experts were brought together to synthesize the current "best practices" both at the spacecraft system and subsystems levels. The objective of this paper is to summarize, for the larger Community of Practice, the initial set of Guidance, Navigation and Control (GN&C) engineering Best Practices as identified by this NESC assessment process.

Dennehy, Cornelius J.↗

NASA NTRS2007

GN&C Engineering Best Practices for Human-Rated Spacecraft Systems

Dennehy, Cornelius J.↗

NASA NTRS2008

GN&C Engineering Best Practices for Human-Rated Spacecraft System

Dennehy, Cornelius J.↗

NASA NTRS1992

Developing a safe on-orbit cryogenic depot

New U.S. space initiatives will require technology to realize planned programs such as piloted lunar and Mars missions. Key to the optimal execution of such missions are high performance orbit transfer vehicles and propellant storage facilities. Large amounts of liquid hydrogen and oxygen demand a uniquely designed on-orbit cryogenic propellant depot. Because of the inherent dangers in propellant storage and handling, a comprehensive system safety program must be established. This paper shows how the myriad and complex hazards demonstrate the need for an integrated safety effort to be applied from program conception through operational use. Even though the cryogenic depot is still in the conceptual stage, many of the hazards have been identified, including fatigue due to heavy thermal loading from environmental and operating temperature extremes, micrometeoroid and/or depot ancillary equipment impact (this is an important problem due to the large surface area needed to house the large quantities of propellant), docking and maintenance hazards, and hazards associated with extended extravehicular activity. Various safety analysis techniques were presented for each program phase. Specific system safety implementation steps were also listed. Enhanced risk assessment was demonstrated through the incorporation of these methods.

Bahr, Nicholas J.↗

NASA NTRS2003

A Survey of Logic Formalisms to Support Mishap Analysis

Mishap investigations provide important information about adverse events and near miss incidents. They are intended to help avoid any recurrence of previous failures. Over time, they can also yield statistical information about incident frequencies that helps to detect patterns of failure and can validate risk assessments. However, the increasing complexity of many safety critical systems is posing new challenges for mishap analysis. Similarly, the recognition that many failures have complex, systemic causes has helped to widen the scope of many mishap investigations. These two factors have combined to pose new challenges for the analysis of adverse events. A new generation of formal and semi-formal techniques have been proposed to help investigators address these problems. We introduce the term mishap logics to collectively describe these notations that might be applied to support the analysis of mishaps. The proponents of these notations have argued that they can be used to formally prove that certain events created the necessary and sufficient causes for a mishap to occur. These proofs can be used to reduce the bias that is often perceived to effect the interpretation of adverse events. Others have argued that one cannot use logic formalisms to prove causes in the same way that one might prove propositions or theorems. Such mechanisms cannot accurately capture the wealth of inductive, deductive and statistical forms of inference that investigators must use in their analysis of adverse events. This paper provides an overview of these mishap logics. It also identifies several additional classes of logic that might also be used to support mishap analysis.

Johnson, Chris↗

NASA NTRS2010

Distributed Impact Detector System (DIDS) Health Monitoring System Evaluation

Damage due to impacts from micrometeoroids and orbital debris is one of the most significant on-orbit hazards for spacecraft. Impacts to thermal protection systems must be detected and the damage evaluated to determine if repairs are needed to allow safe re-entry. To address this issue for the International Space Station Program, Langley Research Center and Johnson Space Center technologists have been working to develop and implement advanced methods for detecting impacts and resultant leaks. LaRC funded a Small Business Innovative Research contract to Invocon, Inc. to develop special wireless sensor systems that are compact, light weight, and have long battery lifetimes to enable applications to long duration space structures. These sensor systems are known as distributed impact detection systems (DIDS). In an assessment, the NASA Engineering and Safety Center procured two prototype DIDS sensor units to evaluate their capabilities in laboratory testing and field testing in an ISS Node 1 structural test article. This document contains the findings of the assessment.

Prosser, William H.↗

NASA NTRS2011

How Can You Support RIDM/CRM/RM Through the Use of PRA

Probabilistic Risk Assessment (PRA) is one of key Risk Informed Decision Making (RIDM) tools. It is a scenario-based methodology aimed at identifying and assessing Safety and Technical Performance risks in complex technological systems.

DoVemto. Tpmu↗

NASA NTRS2015

Simplified Methodology to Estimate the Maximum Liquid Helium (LHe) Cryostat Pressure from a Vacuum Jacket Failure

The aircraft-based Stratospheric Observatory for Infrared Astronomy (SOFIA) is a platform for multiple infrared astronomical observation experiments. These experiments carry sensors cooled to liquid helium temperatures. The liquid helium supply is contained in large (i.e., 10 liters or more) vacuum-insulated dewars. Should the dewar vacuum insulation fail, the inrushing air will condense and freeze on the dewar wall, resulting in a large heat flux on the dewar's contents. The heat flux results in a rise in pressure and the actuation of the dewar pressure relief system. A previous NASA Engineering and Safety Center (NESC) assessment provided recommendations for the wall heat flux that would be expected from a loss of vacuum and detailed an appropriate method to use in calculating the maximum pressure that would occur in a loss of vacuum event. This method involved building a detailed supercritical helium compressible flow thermal/fluid model of the vent stack and exercising the model over the appropriate range of parameters. The experimenters designing science instruments for SOFIA are not experts in compressible supercritical flows and do not generally have access to the thermal/fluid modeling packages that are required to build detailed models of the vent stacks. Therefore, the SOFIA Program engaged the NESC to develop a simplified methodology to estimate the maximum pressure in a liquid helium dewar after the loss of vacuum insulation. The method would allow the university-based science instrument development teams to conservatively determine the cryostat's vent neck sizing during preliminary design of new SOFIA Science Instruments. This report details the development of the simplified method, the method itself, and the limits of its applicability. The simplified methodology provides an estimate of the dewar pressure after a loss of vacuum insulation that can be used for the initial design of the liquid helium dewar vent stacks. However, since it is not an exact tool, final verification of the dewar pressure vessel design requires a complete, detailed real fluid compressible flow model of the vent stack. The wall heat flux resulting from a loss of vacuum insulation increases the dewar pressure, which actuates the pressure relief mechanism and results in high-speed flow through the dewar vent stack. At high pressures, the flow can be choked at the vent stack inlet, at the exit, or at an intermediate transition or restriction. During previous SOFIA analyses, it was observed that there was generally a readily identifiable section of the vent stack that would limit the flow – e.g., a small diameter entrance or an orifice. It was also found that when the supercritical helium was approximated as an ideal gas at the dewar condition, the calculated mass flow rate based on choking at the limiting entrance or transition was less than the mass flow rate calculated using the detailed real fluid model2. Using this lower mass flow rate would yield a conservative prediction of the dewar’s wall heat flux capability. The simplified method of the current work was developed by building on this observation.

Ungar, Eugene K.↗

NASA NTRS2024

Control Effectiveness: Metric Development and Application to Resilient Lunar Habitat Design

System safety engineering in its bare essence involves identifying, assessing, and mitigating, or controlling, hazards. Appropriate safety controls are selected using hazard reduction precedence principles, prior experience, or by assessing their impact on residual risk (together with other factors like cost). We propose a control effectiveness metric as one way to systematically and consistently evaluate potential safety controls individually and thereby facilitate selecting a shortlist of potential controls for subsequent integrated evaluation. The control effectiveness metric considers a safety control’s availability when needed, the probability that its design is adequate in addressing the targeted hazard, the probability that the design will be implemented as intended, and the relationship between the time it takes for the safety control to address its target hazard and the time before the hazard propagates. We demonstrated the use of our metric on a lunar habitat design using a physics-based habitat simulator. High control effectiveness and safety controls result in a habitat with high resilience, while low control effectiveness results in lower resilience.

Rashi Jain↗