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NASA NTRS2001

Quantitative risk assessment system (QRAS)

A quantitative risk assessment system (QRAS) builds a risk model of a system for which risk of failure is being assessed, then analyzes the risk of the system corresponding to the risk model. The QRAS performs sensitivity analysis of the risk model by altering fundamental components and quantifications built into the risk model, then re-analyzes the risk of the system using the modifications. More particularly, the risk model is built by building a hierarchy, creating a mission timeline, quantifying failure modes, and building/editing event sequence diagrams. Multiplicities, dependencies, and redundancies of the system are included in the risk model. For analysis runs, a fixed baseline is first constructed and stored. This baseline contains the lowest level scenarios, preserved in event tree structure. The analysis runs, at any level of the hierarchy and below, access this baseline for risk quantitative computation as well as ranking of particular risks. A standalone Tool Box capability exists, allowing the user to store application programs within QRAS.

Weinstock, Robert M↗

NASA NTRS2019

NASA Conjunction Assessment Risk Analysis (CARA) Updated Requirements Architecture

The NASA Conjunction Assessment Risk Analysis (CARA) program has been performing routine on-orbit satellite conjunction risk analysis for unmanned NASA spacecraft since 2005, and has developed a robust operations procedure and set of recommended best practices for operational conjunction assessment. However, a number of recent developments in Space Situational Awareness and commercial space operations conduct, such as the immanent deployment of much more sensitive space sensing systems and the launching of much larger satellite constellations, have begun to challenge these standard collision risk parameters and calculations. In response CARA has pursued a multi-year evaluation initiative to re-examine risk assessment algorithms and techniques, to develop needed improvements, and to assemble analysis-based operational requirements. This paper gives an overview of the principal parts of the Conjunction Assessment (CA) risk assessment process used at CARA, outlines the technical challenges that each part presents, surveys the possible solutions, and then indicates which particular solution is being recommended for NASA.

Newman, L. K.↗

NASA NTRS2025

Single Integrated Flux Files to Account for Spacecraft Attitude Motion in Meteoroid Risk Assessments Using the NASA MEM3 and Bumper Codes

Spacecraft meteoroid risk assessments can be performed using NASA’s Meteoroid Engineering Model 3 (MEM3) and the Bumper risk assessment code. The MEM3 meteoroid flux is highly directional in heliocentric space. To represent the directionality, MEM3 outputs the flux in commonly used coordinate frames. For example, if a spacecraft attitude is fixed in the orbital tangential frame, a single Bumper run using the MEM3 flux file in the body-fixed frame can be performed. Cases exist in which the spacecraft does not remain fixed in one of these frames during a mission. This could be handled by performing a series of Bumper runs at points along the trajectory. For each trajectory point, the spacecraft has to be rotated into the frame in which the MEM3 flux file is defined. Another option presented here is to generate a single integrated flux (SIF) file. A SIF file is an average over a trajectory of the time varying MEM3 flux files rotated from their native frame into the spacecraft bus frame. A SIF file enables accounting for spacecraft rotation (coupled with flux variation over the trajectory) in a single Bumper run. An example of an application of SIF files is the meteoroid risk assessment for the Mars Sample Return (MSR) campaign Capture Containment and Return System (CCRS). This report discusses how SIF files were generated for the CCRS risk assessment and presents metrics on the accuracy of the impinging fluence that is generated when using the files. The results show a maximum difference per element in a finite element model within 1 percent for seven of the eight examined cases, with the outlier being less than 2 percent. The results also show that the maximum standard deviation of differences across all elements is within 0.275 percent. The maximum difference in the total fluence across all the elements is 0.0463 percent. The maximum difference in the mean fluence across all the elements is 0.0407 percent.

Meteoroids↗

NASA NTRSDate not supplied

Multi-Model Ensemble Risk Assessment (MERA) - Space Radiation Risk Modeling

Explore the source record for details and available documents.

Ryan B Norman↗

NASA NTRS2016

NASA Human System Risk Assessment Process

NASA utilizes an evidence based system to perform risk assessments for the human system for spaceflight missions. The center of this process is the multi-disciplinary Human System Risk Board (HSRB). The HSRB is chartered from the Chief Health and Medical Officer (OCHMO) at NASA Headquarters. The HSRB reviews all human system risks via an established comprehensive risk and configuration management plan based on a project management approach. The HSRB facilitates the integration of human research (terrestrial and spaceflight), medical operations, occupational surveillance, systems engineering and many other disciplines in a comprehensive review of human system risks. The HSRB considers all factors that influence human risk. These factors include pre-mission considerations such as screening criteria, training, age, sex, and physiological condition. In mission factors such as available countermeasures, mission duration and location and post mission factors such as time to return to baseline (reconditioning), post mission health screening, and available treatments. All of the factors influence the total risk assessment for each human risk. The HSRB performed a comprehensive review of all potential inflight medical conditions and events and over the course of several reviews consolidated the number of human system risks to 30, where the greatest emphasis is placed for investing program dollars for risk mitigation. The HSRB considers all available evidence from human research and, medical operations and occupational surveillance in assessing the risks for appropriate mitigation and future work. All applicable DRMs (low earth orbit for 6 and 12 months, deep space for 30 days and 1 year, a lunar mission for 1 year, and a planetary mission for 3 years) are considered as human system risks are modified by the hazards associated with space flight such as microgravity, exposure to radiation, distance from the earth, isolation and a closed environment. Each risk has a summary two-page assessment representing the state of knowledge/evidence of that risk, available risk mitigations, traceability to the Space Flight Human System Standards (SFHSS) and program requirements, and future work required. These data then can drive coordinated budgets across the Human Research Program, the International Space Station, Crew Health and Safety and Advanced Exploration System budgets to provide the most economical and timely mitigations. The risk assessments were completed for the 6 DRMs and serve as the baseline for which subsequent research and technology development and crew health care portfolios can be assessed. The HSRB reviews each risk at least annually or when new evidence/information is available that adds to the body of evidence. The current status of each risk can be reported to program management for operations, budget reviews and general oversight of the human system risk management program.

Francisco, D.↗

NASA NTRS1995

Probabilistic risk assessment of the Space Shuttle. Phase 3: A study of the potential of losing the vehicle during nominal operation. Volume 5: Auxiliary shuttle risk analyses

Volume 5 is Appendix C, Auxiliary Shuttle Risk Analyses, and contains the following reports: Probabilistic Risk Assessment of Space Shuttle Phase 1 - Space Shuttle Catastrophic Failure Frequency Final Report; Risk Analysis Applied to the Space Shuttle Main Engine - Demonstration Project for the Main Combustion Chamber Risk Assessment; An Investigation of the Risk Implications of Space Shuttle Solid Rocket Booster Chamber Pressure Excursions; Safety of the Thermal Protection System of the Space Shuttle Orbiter - Quantitative Analysis and Organizational Factors; Space Shuttle Main Propulsion Pressurization System Probabilistic Risk Assessment, Final Report; and Space Shuttle Probabilistic Risk Assessment Proof-of-Concept Study - Auxiliary Power Unit and Hydraulic Power Unit Analysis Report.

Fragola, Joseph R.↗

NASA NTRS2021

Risk Assessment Metrics for NASA Fission Reactor Applications

Risk assessment is an important part of many NASA activities. In August 2019, the White House issued NSPM-20, which defines acceptable levels of risk for nuclear launches, but does not prescribe the particular methodologies or metrics that are to be used for comparison to the defined acceptance criteria. There are a variety of metrics that are possible and can be readily generated by a probabilistic risk assessment (PRA). This paper will explore alternative metrics that can be provided, along with some discussion of their characteristics and important factors to consider during a space fission reactor risk analysis.

Probabilistic Risk Assessment↗

NASA NTRS2000

Probabilistic Risk Assessment: A Bibliography

Probabilistic risk analysis is an integration of failure modes and effects analysis (FMEA), fault tree analysis and other techniques to assess the potential for failure and to find ways to reduce risk. This bibliography references 160 documents in the NASA STI Database that contain the major concepts, probabilistic risk assessment, risk and probability theory, in the basic index or major subject terms, An abstract is included with most citations, followed by the applicable subject terms.

Source record↗

NASA NTRS2013

PRA (Probabilistic Risk Assessments) Participation versus Validation

Probabilistic Risk Assessments (PRAs) are performed for projects or programs where the consequences of failure are highly undesirable. PRAs primarily address the level of risk those projects or programs posed during operations. PRAs are often developed after the design has been completed. Design and operational details used to develop models include approved and accepted design information regarding equipment, components, systems and failure data. This methodology basically validates the risk parameters of the project or system design. For high risk or high dollar projects, using PRA methodologies during the design process provides new opportunities to influence the design early in the project life cycle to identify, eliminate or mitigate potential risks. Identifying risk drivers before the design has been set allows the design engineers to understand the inherent risk of their current design and consider potential risk mitigation changes. This can become an iterative process where the PRA model can be used to determine if the mitigation technique is effective in reducing risk. This can result in more efficient and cost effective design changes. PRA methodology can be used to assess the risk of design alternatives and can demonstrate how major design changes or program modifications impact the overall program or project risk. PRA has been used for the last two decades to validate risk predictions and acceptability. Providing risk information which can positively influence final system and equipment design the PRA tool can also participate in design development, providing a safe and cost effective product.

DeMott, Diana↗

NASA NTRS2013

Security Risk Assessment Process for UAS in the NAS CNPC Architecture

This informational paper discusses the risk assessment process conducted to analyze Control and Non-Payload Communications (CNPC) architectures for integrating civil Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS). The assessment employs the National Institute of Standards and Technology (NIST) Risk Management framework to identify threats, vulnerabilities, and risks to these architectures and recommends corresponding mitigating security controls. This process builds upon earlier work performed by RTCA Special Committee (SC) 203 and the Federal Aviation Administration (FAA) to roadmap the risk assessment methodology and to identify categories of information security risks that pose a significant impact to aeronautical communications systems. A description of the deviations from the typical process is described in regards to this aeronautical communications system. Due to the sensitive nature of the information, data resulting from the risk assessment pertaining to threats, vulnerabilities, and risks is beyond the scope of this paper

data links↗

NASA NTRS2012

GERMcode: A Stochastic Model for Space Radiation Risk Assessment

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and high charge and energy (HZE) particles that have been studied at the NASA Space Radiation Laboratory (NSRL) for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of HZE particles in tissue and shielding materials is made with a stochastic approach that includes both particle track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections. For NSRL applications, the GERMcode evaluates a set of biophysical properties, such as the Poisson distribution of particles or delta-ray hits for a given cellular area and particle dose, the radial dose on tissue, and the frequency distribution of energy deposition in a DNA volume. By utilizing the ProE/Fishbowl ray-tracing analysis, the GERMcode will be used as a bi-directional radiation transport model for future spacecraft shielding analysis in support of Mars mission risk assessments. Recent radiobiological experiments suggest the need for new approaches to risk assessment that include time-dependent biological events due to the signaling times for activation and relaxation of biological processes in cells and tissue. Thus, the tracking of the temporal and spatial distribution of events in tissue is a major goal of the GERMcode in support of the simulation of biological processes important in GCR risk assessments. In order to validate our approach, basic radiobiological responses such as cell survival curves, mutation, chromosomal aberrations, and representative mouse tumor induction curves are implemented into the GERMcode. Extension of these descriptions to other endpoints related to non-targeted effects and biochemical pathway responses will be discussed.

Kim, Myung-Hee Y.↗

NASA NTRS1993

The Application of Integrated Knowledge-based Systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through the Biomedical Risk Assessment Intelligent Network (BRAIN), an integrated network of both human and computer elements. The BRAIN will function as an advisor to flight surgeons by assessing the risk of in-flight biomedical problems and recommending appropriate countermeasures. This paper describes the joint effort among various NASA elements to develop BRAIN and an Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of the following: (1) knowledge acquisition; (2) integration of IDRA components; (3) use of expert systems to automate the biomedical prediction process; (4) development of a user-friendly interface; and (5) integration of the IDRA prototype and Exercise Countermeasures Intelligent System (ExerCISys). Because the C Language, CLIPS (the C Language Integrated Production System), and the X-Window System were portable and easily integrated, they were chosen as the tools for the initial IDRA prototype. The feasibility was tested by developing an IDRA prototype that predicts the individual risk of influenza. The application of knowledge-based systems to risk assessment is of great market value to the medical technology industry.

Loftin, Karin C.↗

NASA NTRS2014

Engineering Risk Assessment of Space Thruster Challenge Problem

The Engineering Risk Assessment (ERA) team at NASA Ames Research Center utilizes dynamic models with linked physics-of-failure analyses to produce quantitative risk assessments of space exploration missions. This paper applies the ERA approach to the baseline and extended versions of the PSAM Space Thruster Challenge Problem, which investigates mission risk for a deep space ion propulsion system with time-varying thruster requirements and operations schedules. The dynamic mission is modeled using a combination of discrete and continuous-time reliability elements within the commercially available GoldSim software. Loss-of-mission (LOM) probability results are generated via Monte Carlo sampling performed by the integrated model. Model convergence studies are presented to illustrate the sensitivity of integrated LOM results to the number of Monte Carlo trials. A deterministic risk model was also built for the three baseline and extended missions using the Ames Reliability Tool (ART), and results are compared to the simulation results to evaluate the relative importance of mission dynamics. The ART model did a reasonable job of matching the simulation models for the baseline case, while a hybrid approach using offline dynamic models was required for the extended missions. This study highlighted that state-of-the-art techniques can adequately adapt to a range of dynamic problems.

Assessment↗

NASA NTRS2013

Security Risk Assessment Process for UAS in the NAS CNPC Architecture

Iannicca, Dennis C.↗

NASA NTRS1991

Reliability and risk assessment of structures

Development of reliability and risk assessment of structural components and structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) the evaluation of the various uncertainties in terms of cumulative distribution functions for various structural response variables based on known or assumed uncertainties in primitive structural variables; (2) evaluation of the failure probability; (3) reliability and risk-cost assessment; and (4) an outline of an emerging approach for eventual certification of man-rated structures by computational methods. Collectively, the results demonstrate that the structural durability/reliability of man-rated structural components and structures can be effectively evaluated by using formal probabilistic methods.

Chamis, C. C.↗

NASA NTRS2025

Assessment of Model Outcomes Between the Integrated Medical Model (IMM) and the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT)

The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is a computational model that provides human health and medical risk predictions for crewed spaceflight missions. MEDPRAT utilizes discrete event modeling and dynamic probabilistic simulation to predict critical mission outcomes (total medical events, crew health index, quality time lost, loss of crew life, removal to definitive care), condition occurrences, and resource consumption. Input parameters for MEDPRAT include crew attributes (e.g., sex), types of mission activities (e.g., whether and where crew members perform an extravehicular activity (EVA)), available resources, treatment information, and probability distributions for medical conditions. As an evolution of the Integrated Medical Model (IMM), MEDPRAT provides enhanced capabilities and higher fidelity, and incorporates more appropriate assumptions for long-duration spaceflight. IMM is the currently accepted standard for quantifying spaceflight mission medical risk in NASA operations that uses a probabilistic risk assessment (PRA) approach. MEDPRAT builds on the same logical foundation as IMM but implements the model architecture through highly optimized Monte Carlo sampling methods. An analysis is performed comparing the outputs from IMM with those from MEDPRAT V1.0 and V2.0 for the same reference missions in order to quantify similarities and differences in the model outcomes. The juxtaposition between IMM and MEDPRAT V1.0 and 2.0 shown in this report demonstrates that these two models generate very similar results; where differences in outcomes are shown, these are in accordance with the underlying assumptions and differences in the model architectures. This validation effort further establishes the credibility and reliability of the MEDPRAT software.

Matthew T Prelich↗

NASA NTRSDate not supplied

Artemis Missions Probabilistic Risk Assessment (PRA) & Reliability Assessment Overview

To show how NASA’s Moon-to-Mars (M2M) program can use hardware reliability assessments and comprehensive Probabilistic Risk Assessments (PRAs) to estimate risk of future missions and manage risk via safety and mission success requirements from the top down, so that this risk can be balanced with other program metrics like cost and schedule. These PRAs and reliability assessments can be used during the concept, design, and operational phases of development. This presentation also provides some thoughts on how the NASA process can be utilized for a lunar surface power grid development.

PRA↗

NASA NTRS2017

Evaluating Micrometeoroid and Orbital Debris Risk Assessments Using Anomaly Data

The accuracy of micrometeoroid and orbital debris (MMOD) risk assessments can be difficult to evaluate. A team from the National Aeronautics and Space Administration (NASA) Engineering and Safety Center (NESC) has completed a study that compared MMOD-related failures on operational satellites to predictions of how many of those failures should occur using NASA's TM"s MMOD risk assessment methodology and tools. The study team used the Poisson probability to quantify the degree of inconsistency between the predicted and reported numbers of failures. Many elements go into a risk assessment, and each of those elements represent a possible source of uncertainty or bias that will influence the end result. There are also challenges in obtaining accurate and useful data on MMOD-related failures.

Squire, Michael↗