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Risk Assessment of Obstacle Collision for UAVs under Off-nominal Conditions

Enabling operations of unmanned aerial vehicles (UAVs) in low-altitude airspace demands the need of robust risk monitoring framework for assessing the safety of airspace, ground structures and people. As widespread applications emerge, the need of risk assessment becomes increasingly important for UAV flights beyond visual line-of-sight, especially subjected to off-nominal conditions introduced by component failures, degraded controllability or environmental disturbances such as wind gusts in an urban canyon. From a safety perspective, collision with obstacles can be detrimental not only to the vehicle and payload, but also to the structure and people on ground. Although it is safe to assume that approved UAVs would be equipped with collision avoidance systems, risk of collision which can be predicted for a flight trajectory even before the UAV encounters any obstacle is beneficial to resolve contingencies in its decision-making under off-nominal conditions. In this paper, a framework is presented for computing the risk of collision with obstacle based on a UAV’s predicted trajectory, proximity to static and dynamic obstacles, sub-system state-of-health and external wind conditions. The conditional probability of trajectory deviation is generated using a Bayesian Belief Network (BBN) based on on-board sensor measurements. Further, a kinematic 3-DOF model is implemented to compute deviation in UAV’s trajectory subjected to one case study of off-nominal condition i.e. wind gusts. Finally, the integrated risk factor is demonstrated on real data from experimental flights of an octocopter at NASA Langley Research Center, in presence of simulated obstacles and wind conditions. The proposed approach would enable risk-informed decision making process for timely mitigation of current and future unsafe events.

Bayesian network

3D Representation of UAV-obstacle Collision Risk Under Off-nominal Conditions

Safe operations of autonomous unmanned aerial vehicles (UAVs) in low-altitude airspace with beyond visual line-of-sight (BVLOS) flights demand robust risk monitoring of airspace as well as of people and property on ground. One of the safety critical factors for UAV flights is the risk of collision with static and dynamic obstacles in proximity to its flight path. This paper presents a detailed formulation of risk of obstacle collision incorporating the effects of off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts. The risk is represented in terms of a matrix with rows corresponding to the likelihood of occurrence of collision and columns representing severity of collision to the vehicle and surrounding structures. Risk likelihood is generated using a Bayesian Belief Network (BBN) that compiles knowledge from related Failure Modes and Effects Analysis (FMEAs) and Subject Matter Experts (SMEs) to determine the probability of collision based on on-board sensor measurements indicative of vehicle health and controllability. Risk severity is computed utilizing a point-mass 3D kinematic model of the vehicle in presence of wind. The proposed risk factor is demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in presence of simulated obstacles and wind conditions. Effect of varying wind conditions, level of controllability and obstacle measurement noise on the risk factor is demonstrated. The proposed approach enables risk-informed decision making for timely mitigation of current and future unsafe events in autonomous systems.

risk analysis

Exploration Medical Capability Science and Research Overview and Update

The mission of the Exploration Medical Capability (ExMC) Element is to advance medical system design and risk-informed decision making for exploration beyond low Earth orbit to promote human health and performance in space. In order to accomplish this mission, the Element takes a progressively Earth-independent approach to three main areas: 1)answering key clinical and science research questions that will help to address the challenges of providing medical care in the extreme environment of space, 2)applying systems engineering processes to medical system design with the goal of developing robust requirements that can be fully integrated into future space exploration vehicle designs, and 3)developing and demonstrating novel medical technologies that will improve future medical capabilities in space. This presentation will focus on selected scientific and technical conceptual drivers for the Element, the current and future research risks and gaps, and provide an overview of the Element’s progress in 2020.

Kris Lehnhardt

3D Representation of UAV-obstacle Collision Risk under off-nominal conditions

Safe operations of autonomous unmanned aerial vehicles (UAVs) in low-altitude airspace with beyond visual line-of-sight (BVLOS) flights demand robust risk monitoring of airspace as well as of people and property on ground. One of the safety critical factors for UAV flights is the risk of collision with static and dynamic obstacles in proximity to its flight path. This paper presents a detailed formulation of risk likelihood of obstacle collision incorporating the effects of off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts. The deviation in the planned trajectory caused due to wind is computed utilizing a point-mass 3D kinematic simulation model of the vehicle. Likelihood of risk for the flight plan is then analyzed based on generating the probability of collision for each point in the trajectory. The proposed risk factor is demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in presence of simulated obstacles and wind conditions. Effect of varying wind conditions, distance from obstacles, level of controllability and obstacle measurement noise on the risk factor is demonstrated. The proposed approach enables risk-informed decision making for timely mitigation of current and future unsafe events in autonomous systems.

Portia Banerjee

A Practical Approach to Uncertainty Quantification Using Probability Boxes

To date, while the use of CFD for aerospace vehicle design and development is prevalent, the documentation of uncertainties associated with the simulations are rare. Instead, the current state-of-the-art relies heavily on the experience of the CFD practitioner to estimate the uncertainty associated with their simulations through simple sensitivity studies or subject matter expertise. This practice will have to be replaced with a formal uncertainty quantification (UQ) process if CFD is to play an expanded role in the research and engineering design community, test and evaluation community, and ultimately certification for flight. Accounting for uncertainties in a formal manner is a tedious process. Moreover, the typical CFD practitioner is not likely to be familiar with formal UQ methods. These factors have prevented the adoption of UQ methods in the engineering design and development cycle. This presentation will outline a credible approach to UQ using Probability Boxes that is straightforward to apply, and can readily be automated using existing UQ tool sets such as the DAKOTA packaged developed at Sandia. The added expense incurred when moving away from a deterministic CFD process to a stochastic one that captures uncertainties to enable risk-informed decision making will be discussed, as well as effective ways to reduce the computational costs.

Uncertainty Quantification

Exploration Medical Capability Science and Research Overview and Update

The mission of the Exploration Medical Capability (ExMC) Element is to advance medical system design and risk-informed decision making for exploration beyond Low Earth Orbit to promote human health and performance in space. To accomplish this mission, ExMC focuses on several key areas: • Investigating specific risks that are relevant for human exploration spaceflight, including in-flight medical conditions, degraded or toxic medications, and renal stones • Developing medical probabilistic risk analysis tools that are integrated with systems engineering processes to inform the medical system trade space and support the development of robust requirements • Demonstrating and defining requirements for a prototype clinical decision support system • Developing and demonstrating novel medical technologies that will improve future medical capabilities in space This presentation will focus on selected scientific and technical conceptual drivers for the Element and its current and future research risks and gaps while providing an overview of the Element’s progress in 2021 and areas of focus for 2022.

Benjamin Easter

Electromagnetic Compatibility Test and Analysis Campaign of NASA's Mars 2020 Rover Final Submission

NASA's Mars 2020 Perseverance Rover—with a launch window opening July 2020, and landing expected February 2021—has mission objectives to look for evidence of habitability, seek biosignatures of past life, collect and cache samples for possible future return to Earth, and prepare for future human missions to Mars. The Rover platform is similar to the previous Mars Science Laboratory (MSL) “Curiosity” rover that landed in 2012 but contains a new suite of scientific instruments and upgrades to existing functionality: seven new and/or upgraded scientific payloads, an upgraded arm and sampling system, and a Helicopter demonstration. These changes—along with new efficiency goals to operate more Rover subsystems concurrently and thus collect more science—presented new electromagnetic compatibility (EMC) challenges. In this paper, we will describe the campaign to ensure Mars 2020 mission success from an electromagnetic environment perspective: 1) confirming existing MSL heritage subsystems and EMC requirements were compatible with the new Mars 2020 mission objectives, 2) engaging with engineers and scientists early in the project to identify and evaluate risks before hardware assembly and performing ambitious risk reduction tests, 3) undertaking a comprehensive subsystem qualification test program based on tailored MIL-STD-461F requirements, occasionally leading to redesign, 4) synthesizing the data collected to perform detailed analyses toward the goal of making risk-informed decisions at a system level. The spacecraft successfully completed all three planned system level tests, demonstrating self-compatibility with minimal impact to operations from electromagn

Gonzales, Edward C

Electromagnetic Compatibility Test and Analysis Campaign of NASA's Mars 2020 Rover

NASA's Mars 2020 Rover—with a launch window opening July 2020, and landing expected February 2021—has mission objectives to look for evidence of habitability, seek biosignatures of past life, collect and cache samples for possible future return to Earth, and prepare for future human missions. The Rover platform is similar to the previous Mars Science Laboratory (MSL) “Curiosity” rover that landed in 2012 but contains a new suite of scientific instruments and upgrades to existing functionality. The scientific payload includes a trio of chemical analysis tools (PIXL, SHERLOC, SuperCam), a ground penetrating radar (RIMFAX), an upgraded weather station (MEDA), upgraded high resolution camera (MastCam-Z), and an oxygen-producing experiment (MOXIE). These changes—along with new efficiency goals to operate more Rover subsystems concurrently and thus collect more science—presented new electromagnetic compatibility (EMC) challenges. In this paper, we will describe the campaign to ensure Mars 2020 mission success from an electromagnetic environment perspective: 1) confirming existing MSL heritage subsystems and EMC requirements were compatible with the new Mars 2020 mission objectives, 2) engaging with engineers and scientists early in the project to identify and evaluate risks before hardware assembly and performing ambitious risk reduction tests, 3) undertaking a comprehensive subsystem qualification test program based on tailored MIL-STD-461F requirements, occasionally leading to redesign, 4) synthesizing the data collected to perform detailed analyses toward the goal of making risk-informed decisions at a system level. The spacecraft has successfully completed all three planned system level tests, demonstrating self-compatibility with minimal impact to operations from electromagnetic interference in all mission phases.

Gonzales, Edward C

NASA’s Revised Planetary Protection Policy and Implementation

NASA has updated its planetary protection policy and implementation approach in response to advances in scientific understanding of solar system targets, upcoming mission opportuni-ties for exploration and sample return, and the private sector’s emerging capability to plan missions to Earth’s Moon and Mars. In September 2021, the NASA Procedural Requirements NPR 8715.24, entitled “Planetary Protection Provisions for Robotic Extraterrestrial Missions” was released which repositions planetary protection in existing NASA mission and program management structures, introduces risk-informed decision making, expands on key roles and responsibilities for both programmatic and the Oÿce of Safety and Mission Assurance, updates the categorization process and streamlines the planetary protection documentation approval and schedule. NASA is working on a more detailed technical standard to accompany NPR 8715.24 which will include the detailed technical requirements to address organic contamina-tion, inadvertent impact avoidance, biological control and management, end of mission disposal and restricted Earth-Return sample safety and assurance. This report to the COSPAR com-munity will describe the current NASA planetary protection policy and its alignment with the revised COSPAR planetary protection policy. NASA’s plans for updating the supporting “Handbook for Implementing Planetary Protection Technical Requirements” and future policies for addressing planetary protection of crewed missions will also be presented.

Elaine Seasly

Probability of Obstacle Collision for UAVs in Presence of Wind

For incorporation of unmanned aerial vehicles into the National Airspace, ensuring safety of the airspace including the vehicles, people, and property on the ground is of utmost importance. One of the safety-critical factors for unmanned aviation flights is the risk of deviating from a planned trajectory resulting in a variety of hazards, including potential loss of separation between vehicle and obstacles or unexpected battery energy consumption. Off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts can lead to unacceptable unexpected deviations from the flight trajectory. It is essential to accurately model such effects on the flight trajectory while computing safety thresholds such as minimum separation from surrounding obstacles, available battery resource to complete the mission or determining delay in the expected time of arrival of flights. In this paper, a tool is presented based on Gaussian Process Regression for wind representation over a pre-defined trajectory for fast, yet approximated, in-time evaluation of possible trajectory deviations caused by wind gusts. The deviation in the planned trajectory caused by wind is further simulated utilizing a 6 degrees-of-freedom (DOF) UAV trajectory simulator comprising of a rotorcraft lumped-mass model with LQRI controller. Both steady-state wind and wind gust effects are investigated. The probability of collision with obstacle is computed and demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in the presence of simulated obstacles and wind conditions. Effect of varying wind conditions and varying UAV airspeed is further demonstrated on experimental flights in the presence of wind measured by ground based weather service stations. The proposed approach would eventually benefit timely mitigation of current and future safety-critical events in autonomous systems by enabling risk-informed decision making.

Portia Banerjee

NASA’s Revised Planetary Protection Policy and Implementation

NASA has updated its planetary protection policy and implementation approach in response to advances in scientific understanding of solar system targets, upcoming mission opportunities for exploration and sample return, and the private sector’s emerging capability to plan missions to Earth’s Moon and Mars. In September 2021, the NASA Procedural Requirements NPR 8715.24, entitled “Planetary Protection Provisions for Robotic Extraterrestrial Missions” was released which repositions planetary protection in existing NASA mission and program management structures, introduces risk-informed decision making, expands on key roles and responsibilities for both programmatic and the Office of Safety and Mission Assurance, updates the categorization process and streamlines the planetary protection documentation approval and schedule. NASA is working on a more detailed technical standard to accompany NPR 8715.24 which will include the detailed technical requirements to address organic contamination, inadvertent impact avoidance, biological control and management, end of mission disposal and restricted Earth-Return sample safety and assurance. This report to the COSPAR community will describe the current NASA planetary protection policy and its alignment with the revised COSPAR planetary protection policy. NASA’s plans for updating the supporting “Handbook for Implementing Planetary Protection Technical Requirements” and future policies for addressing planetary protection of crewed missions will also be presented.

Planetary Protection

NASA’s Revised Planetary Protection Policy and Implementation

NASA has updated its planetary protection policy and implementation approach in response to advances in scientific understanding of solar system targets, upcoming mission opportunities for exploration and sample return, and the private sector’s emerging capability to plan missions to Earth’s Moon and Mars. In September 2021, the NASA Procedural Requirements NPR 8715.24, entitled “Planetary Protection Provisions for Robotic Extraterrestrial Missions” was released which repositions planetary protection in existing NASA mission and program management structures, introduces risk-informed decision making, expands on key roles and responsibilities for both programmatic and the Office of Safety and Mission Assurance, updates the categorization process and streamlines the planetary protection documentation approval and schedule. NASA is working on a more detailed technical standard to accompany NPR 8715.24 which will include the detailed technical requirements to address organic contamination, inadvertent impact avoidance, biological control and management, end of mission disposal and restricted Earth-Return sample safety and assurance. This report to the COSPAR community will describe the current NASA planetary protection policy and its alignment with the revised COSPAR planetary protection policy. NASA’s plans for updating the supporting “Handbook for Implementing Planetary Protection Technical Requirements” and future policies for addressing planetary protection of crewed missions will also be presented.

Elaine Seasly

Considering Risk and Resilience in Decision-Making

This paper examines the concepts of decision-making, risk analysis, uncertainty and resilience analysis. The relation between risk, vulnerability, and resilience is analyzed. The paper describes how complexity, uncertainty, and ambiguity are the most critical factors in the definition of the approach and criteria for decision-making. Uncertainty in its various forms is what limits our ability to offer definitive answers to questions about the outcomes of alternatives in a decision-making process. It is shown that, although resilience-informed decision-making would seem fundamentally different from risk-informed decision-making, this is not the case as resilience-analysis can be easily incorporated within existing analytic-deliberative decision-making frameworks.

Torres-Pomales, Wilfredo

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

"Making Safety Happen" Through Probabilistic Risk Assessment at NASA

NASA is using Probabilistic Risk Assessment (PRA) as one of the tools in its Safety & Mission Assurance (S&MA) tool belt to identify and quantify risks associated with human spaceflight. This paper discusses some of the challenges and benefits associated with developing and using PRA for NASA human space programs. Some programs have entered operation prior to developing a PRA, while some have implemented PRA from the start of the program. It has been observed that the earlier a design change is made in the concept or design phase, the less impact it has on cost and schedule. Not finding risks until the operation phase yields much costlier design changes and major delays, which can result in discussions of just accepting the risk. Risk contributors identified by PRA are not just associated with hardware failures. They include but are not limited to crew fatality due to medical causes, the environment the vehicle and crew are exposed to, the software being used, and the reliability of the crew performing required actions. Some programs have entered operation prior to developing a PRA, and while PRA can still provide a benefit for operations and future design trades, the benefit of implementing PRA from the start of the program provides the added benefit of informing design and reducing risk early in program development. Currently, NASA’s International Space Station (ISS) program is in its 20th year of on-orbit operations around the Earth and has several new programs in the design phase preparing to enter the operation phase all of which have active (or living) PRAs. These programs incorporate PRA as part of their Risk-Informed, Decision-Making (RIDM) process. For new NASA human spaceflight programs discussion begins with mission concept, establishing requirements, forming the PRA team, and continues through the design cycles into the operational phase. Several examples of PRA related applications and observed lessons are included.

Applications

2009 Space Shuttle Probabilistic Risk Assessment Overview

Loss of a Space Shuttle during flight has severe consequences, including loss of a significant national asset; loss of national confidence and pride; and, most importantly, loss of human life. The Shuttle Probabilistic Risk Assessment (SPRA) is used to identify risk contributors and their significance; thus, assisting management in determining how to reduce risk. In 2006, an overview of the SPRA Iteration 2.1 was presented at PSAM 8 [1]. Like all successful PRAs, the SPRA is a living PRA and has undergone revisions since PSAM 8. The latest revision to the SPRA is Iteration 3. 1, and it will not be the last as the Shuttle program progresses and more is learned. This paper discusses the SPRA scope, overall methodology, and results, as well as provides risk insights. The scope, assumptions, uncertainties, and limitations of this assessment provide risk-informed perspective to aid management s decision-making process. In addition, this paper compares the Iteration 3.1 analysis and results to the Iteration 2.1 analysis and results presented at PSAM 8.

Hamlin, Teri L.

An Integrated Reliability and Physics-Based Risk Modeling Approach for Assessing Human Spaceflight Systems

This paper presents an integrated reliability and physics-based risk modeling approach for assessing human spaceflight systems. The approach is demonstrated using an example, end-to-end risk assessment of a generic-crewed space transportation system during a reference mission to the International Space Station. The behavior of the system is modeled using analysis techniques from multiple disciplines in order to properly capture the dynamic time- and state- dependent consequences of failures encountered in different mission phases. We discuss how to combine traditional reliability analyses with Monte Carlo simulation methods and physics-based engineering models to produce loss-of- mission and loss-of-crew risk estimates supporting risk-based decision-making and requirement verification. This approach facilitates risk-informed design by providing more realistic representation of system failures and interactions; identifying key risk-driving sensitivities, dependencies, and assumptions; and tracking multiple figures of merit within a single, responsive assessment framework that can readily incorporate evolving design information throughout system development.

Risk assessment

NASA System Safety Handbook: System Safety Framework and Concepts for Implementation - Volume 1

System safety assessment is defined in NPR 8715.3C, NASA General Safety Program Requirements as a disciplined, systematic approach to the analysis of risks resulting from hazards that can affect humans, the environment, and mission assets. Achievement of the highest practicable degree of system safety is one of NASA's highest priorities. Traditionally, system safety assessment at NASA and elsewhere has focused on the application of a set of safety analysis tools to identify safety risks and formulate effective controls.1 Familiar tools used for this purpose include various forms of hazard analyses, failure modes and effects analyses, and probabilistic safety assessment (commonly also referred to as probabilistic risk assessment (PRA)). In the past, it has been assumed that to show that a system is safe, it is sufficient to provide assurance that the process for identifying the hazards has been as comprehensive as possible and that each identified hazard has one or more associated controls. The NASA Aerospace Safety Advisory Panel (ASAP) has made several statements in its annual reports supporting a more holistic approach. In 2006, it recommended that "... a comprehensive risk assessment, communication and acceptance process be implemented to ensure that overall launch risk is considered in an integrated and consistent manner." In 2009, it advocated for "... a process for using a risk-informed design approach to produce a design that is optimally and sufficiently safe." As a rationale for the latter advocacy, it stated that "... the ASAP applauds switching to a performance-based approach because it emphasizes early risk identification to guide designs, thus enabling creative design approaches that might be more efficient, safer, or both." For purposes of this preface, it is worth mentioning three areas where the handbook emphasizes a more holistic type of thinking. First, the handbook takes the position that it is important to not just focus on risk on an individual basis but to consider measures of aggregate safety risk and to ensure wherever possible that there be quantitative measures for evaluating how effective the controls are in reducing these aggregate risks. The term aggregate risk, when used in this handbook, refers to the accumulation of risks from individual scenarios that lead to a shortfall in safety performance at a high level: e.g., an excessively high probability of loss of crew, loss of mission, planetary contamination, etc. Without aggregated quantitative measures such as these, it is not reasonable to expect that safety has been optimized with respect to other technical and programmatic objectives. At the same time, it is fully recognized that not all sources of risk are amenable to precise quantitative analysis and that the use of qualitative approaches and bounding estimates may be appropriate for those risk sources. Second, the handbook stresses the necessity of developing confidence that the controls derived for the purpose of achieving system safety not only handle risks that have been identified and properly characterized but also provide a general, more holistic means for protecting against unidentified or uncharacterized risks. For example, while it is not possible to be assured that all credible causes of risk have been identified, there are defenses that can provide protection against broad categories of risks and thereby increase the chances that individual causes are contained. Third, the handbook strives at all times to treat uncertainties as an integral aspect of risk and as a part of making decisions. The term "uncertainty" here does not refer to an actuarial type of data analysis, but rather to a characterization of our state of knowledge regarding results from logical and physical models that approximate reality. Uncertainty analysis finds how the output parameters of the models are related to plausible variations in the input parameters and in the modeling assumptions. The evaluation of unrtainties represents a method of probabilistic thinking wherein the analyst and decision makers recognize possible outcomes other than the outcome perceived to be "most likely." Without this type of analysis, it is not possible to determine the worth of an analysis product as a basis for making decisions related to safety and mission success. In line with these considerations the handbook does not take a hazard-analysis-centric approach to system safety. Hazard analysis remains a useful tool to facilitate brainstorming but does not substitute for a more holistic approach geared to a comprehensive identification and understanding of individual risk issues and their contributions to aggregate safety risks. The handbook strives to emphasize the importance of identifying the most critical scenarios that contribute to the risk of not meeting the agreed-upon safety objectives and requirements using all appropriate tools (including but not limited to hazard analysis). Thereafter, emphasis shifts to identifying the risk drivers that cause these scenarios to be critical and ensuring that there are controls directed toward preventing or mitigating the risk drivers. To address these and other areas, the handbook advocates a proactive, analytic-deliberative, risk-informed approach to system safety, enabling the integration of system safety activities with systems engineering and risk management processes. It emphasizes how one can systematically provide the necessary evidence to substantiate the claim that a system is safe to within an acceptable risk tolerance, and that safety has been achieved in a cost-effective manner. The methodology discussed in this handbook is part of a systems engineering process and is intended to be integral to the system safety practices being conducted by the NASA safety and mission assurance and systems engineering organizations. The handbook posits that to conclude that a system is adequately safe, it is necessary to consider a set of safety claims that derive from the safety objectives of the organization. The safety claims are developed from a hierarchy of safety objectives and are therefore hierarchical themselves. Assurance that all the claims are true within acceptable risk tolerance limits implies that all of the safety objectives have been satisfied, and therefore that the system is safe. The acceptable risk tolerance limits are provided by the authority who must make the decision whether or not to proceed to the next step in the life cycle. These tolerances are therefore referred to as the decision maker's risk tolerances. In general, the safety claims address two fundamental facets of safety: 1) whether required safety thresholds or goals have been achieved, and 2) whether the safety risk is as low as possible within reasonable impacts on cost, schedule, and performance. The latter facet includes consideration of controls that are collective in nature (i.e., apply generically to broad categories of risks) and thereby provide protection against unidentified or uncharacterized risks.

Dezfuli, Homayoon