Results for “Probabilistic Safety Assessment” — Page 3

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 NTRS2001

Overview of Probabilistic Risk Assessment at NASA: Past, Present and Future

PRA (Probabilistic Risk Assessment) adds the "probability" dimension to the traditional "deterministic" dimension of engineering and safety analyses. Although PRA, as a discipline, has been the evolutionary product of only the last couple of decades, much of the underlying methodology has been in use for a long time. In fact, the concept of probability for describing the likelihood that rare events happen is ancient and dates from Ancient Greece. Our vision is for NASA to achieve world-class state-of-the-art capability in performing and using PRA in technical and management decisions. Since NASA is a leader in many technical fields in which it is involved, we hope, before long, to see NASA become a leader in this field also.

Stamatelatos, Michael G.↗

NASA NTRS2009

Johnson Space Center's Risk and Reliability Analysis Group 2008 Annual Report

The Johnson Space Center (JSC) Safety & Mission Assurance (S&MA) Directorate s Risk and Reliability Analysis Group provides both mathematical and engineering analysis expertise in the areas of Probabilistic Risk Assessment (PRA), Reliability and Maintainability (R&M) analysis, and data collection and analysis. The fundamental goal of this group is to provide National Aeronautics and Space Administration (NASA) decisionmakers with the necessary information to make informed decisions when evaluating personnel, flight hardware, and public safety concerns associated with current operating systems as well as with any future systems. The Analysis Group includes a staff of statistical and reliability experts with valuable backgrounds in the statistical, reliability, and engineering fields. This group includes JSC S&MA Analysis Branch personnel as well as S&MA support services contractors, such as Science Applications International Corporation (SAIC) and SoHaR. The Analysis Group s experience base includes nuclear power (both commercial and navy), manufacturing, Department of Defense, chemical, and shipping industries, as well as significant aerospace experience specifically in the Shuttle, International Space Station (ISS), and Constellation Programs. The Analysis Group partners with project and program offices, other NASA centers, NASA contractors, and universities to provide additional resources or information to the group when performing various analysis tasks. The JSC S&MA Analysis Group is recognized as a leader in risk and reliability analysis within the NASA community. Therefore, the Analysis Group is in high demand to help the Space Shuttle Program (SSP) continue to fly safely, assist in designing the next generation spacecraft for the Constellation Program (CxP), and promote advanced analytical techniques. The Analysis Section s tasks include teaching classes and instituting personnel qualification processes to enhance the professional abilities of our analysts as well as performing major probabilistic assessments used to support flight rationale and help establish program requirements. During 2008, the Analysis Group performed more than 70 assessments. Although all these assessments were important, some were instrumental in the decisionmaking processes for the Shuttle and Constellation Programs. Two of the more significant tasks were the Space Transportation System (STS)-122 Low Level Cutoff PRA for the SSP and the Orion Pad Abort One (PA-1) PRA for the CxP. These two activities, along with the numerous other tasks the Analysis Group performed in 2008, are summarized in this report. This report also highlights several ongoing and upcoming efforts to provide crucial statistical and probabilistic assessments, such as the Extravehicular Activity (EVA) PRA for the Hubble Space Telescope service mission and the first fully integrated PRAs for the CxP's Lunar Sortie and ISS missions.

Valentine, Mark↗

NASA NTRS2014

Quantitative Risk Modeling of Fire on the International Space Station

The International Space Station (ISS) Program has worked to prevent fire events and to mitigate their impacts should they occur. Hardware is designed to reduce sources of ignition, oxygen systems are designed to control leaking, flammable materials are prevented from flying to ISS whenever possible, the crew is trained in fire response, and fire response equipment improvements are sought out and funded. Fire prevention and mitigation are a top ISS Program priority - however, programmatic resources are limited; thus, risk trades are made to ensure an adequate level of safety is maintained onboard the ISS. In support of these risk trades, the ISS Probabilistic Risk Assessment (PRA) team has modeled the likelihood of fire occurring in the ISS pressurized cabin, a phenomenological event that has never before been probabilistically modeled in a microgravity environment. This paper will discuss the genesis of the ISS PRA fire model, its enhancement in collaboration with fire experts, and the results which have informed ISS programmatic decisions and will continue to be used throughout the life of the program.

Castillo, Theresa↗

NASA NTRS1992

Risk-based Spacecraft Fire Safety Experiments

Viewgraphs on risk-based spacecraft fire safety experiments are presented. Spacecraft fire risk can never be reduced to a zero probability. Probabilistic risk assessment is a tool to reduce risk to an acceptable level.

Apostolakis, G.↗

NASA NTRS1995

Probabilistic risk assessment of the Space Shuttle. Phase 3: A study of the potential of losing the vehicle during nominal operation, volume 1

This document is the Executive Summary of a technical report on a probabilistic risk assessment (PRA) of the Space Shuttle vehicle performed under the sponsorship of the Office of Space Flight of the US National Aeronautics and Space Administration. It briefly summarizes the methodology and results of the Shuttle PRA. The primary objective of this project was to support management and engineering decision-making with respect to the Shuttle program by producing (1) a quantitative probabilistic risk model of the Space Shuttle during flight, (2) a quantitative assessment of in-flight safety risk, (3) an identification and prioritization of the design and operations that principally contribute to in-flight safety risk, and (4) a mechanism for risk-based evaluation proposed modifications to the Shuttle System. Secondary objectives were to provide a vehicle for introducing and transferring PRA technology to the NASA community, and to demonstrate the value of PRA by applying it beneficially to a real program of great international importance.

Fragola, Joseph R.↗

NASA NTRS1997

Studies Relating to EVA

In this session, Session JA1, the discussion focuses on the following topics: The Staged Decompression to the Hypobaric Atmosphere as a Prophylactic Measure Against Decompression Sickness During Repetitive EVA; A New Preoxygenation Procedure for Extravehicular Activity (EVA); Metabolic Assessments During Extra-Vehicular Activity; Evaluation of Safety of Hypobaric Decompressions and EVA From Positions of Probabilistic Theory; Fatty Acid Composition of Plasma Lipids and Erythrocyte Membranes During Simulation of Extravehicular Activity; Biomedical Studies Relating to Decompression Stress with Simulated EVA, Overview; The Joint Angle and Muscle Signature (JAMS) System - Current Uses and Future Applications; and Experimental Investigation of Cooperative Human-Robotic Roles in an EVA Work Site.

Source record↗

NASA NTRSDate not supplied

Confidence-Based Buffer for Strategic Deconfliction with Probabilistic Operational Intent

This paper presents a methodology to expand the 95% confidence level of the elliptical geometry given by Unmanned Aircraft System (UAS) operators planning to fly Beyond Visual Line of Sight (BVLOS) to any confidence level before being fed to the strategic deconfliction (SD) module, effectively increasing the separation buffer between Operational Intents (OIs). To assess the performance of this approach, it is integrated within an adaptation of the Rolling Horizon with K-Position Search volume-based strategic deconfliction approach, previously developed at NASA Ames, preventing the 4D overlapping of OIs shaped by ellipses instead of traditional blocks. Safety and efficiency metrics are evaluated through the deconfliction of four simulated package delivery route network structures across the San Francisco Metropolitan Area with increasing numbers of crossing waypoints (network complexity). Safety assessment entails the in-house creation of a metric to quantify collision occurrences per flight hour based on the frequency at which the probabilistic operational volume segments are sampled, whereas efficiency is measured using ground delay. Results indicate that the largest buffer growth occurs when increasing the confidence level beyond 99.9% and demonstrate the negative impact of network complexity on both metrics, regardless of the OI geometry. Further, the ellipse-based SD adaptation more accurately estimates temporal separation at crossings, allowing deconflicted vehicles to be closer together. It is concluded that the proposed methodology enables the desired confidence level to serve as an effective controller of buffer size.

safety↗

NASA NTRSDate not supplied

Confidence-Based Buffer for Strategic Deconfliction with Probabilistic Operational Intent

This paper presents a methodology to expand the 95% confidence level of the elliptical geometry given by Unmanned Aircraft System (UAS) operators planning to fly Beyond Visual Line of Sight (BVLOS) to any confidence level before being fed to the strategic deconfliction (SD) module, effectively increasing the separation buffer between Operational Intents (OIs). To assess the performance of this approach, it is integrated within an adaptation of the Rolling Horizon with K-Position Search volume-based strategic deconfliction approach, previously developed at NASA Ames, preventing the 4D overlapping of OIs shaped by ellipses instead of traditional blocks. Safety and efficiency metrics are evaluated through the deconfliction of four simulated package delivery route network structures across the San Francisco Metropolitan Area with increasing numbers of crossing waypoints (network complexity). Safety assessment entails the in-house creation of a metric to quantify collision occurrences per flight hour based on the frequency at which the probabilistic operational volume segments are sampled, whereas efficiency is measured using ground delay. Results indicate that the largest buffer growth occurs when increasing the confidence level beyond 99.9% and demonstrate the negative impact of network complexity on both metrics, regardless of the OI geometry. Further, the ellipse-based SD adaptation more accurately estimates temporal separation at crossings, allowing deconflicted vehicles to be closer together. It is concluded that the proposed methodology enables the desired confidence level to serve as an effective controller of buffer size.

strategic deconfliction↗

NASA NTRSDate not supplied

Spaceflight Over the Last Ten Years: Failures and Fix-ups 2013 - 2022 RAMS XV Conference

This project is an overview and analysis of the past ten years (2013 – present) in global spaceflight, highlighting the orbital launches of countries, particularly the failures that occurred, the reasons they occurred, and a breakdown of the related statistics and background information. The analysis is conducted from a perspective of reliability and maintainability engineering and Probabilistic Risk Assessment (PRA) to formulate a quantifiable understanding of the data and how it is pertinent to Safety and Mission Assurance (SMA) in spaceflight. There is a breakdown by country or group, timelines, and number of launches. The failures over the years are categorized, all given a broad analysis of subsystem failures and details of events. A few failures are given a more in-depth analysis of root causes and failure modes determined by their unique or common nature. The data is retrieved from online, publicly available sources.

Quinn Slaugenhoupt↗

NASA NTRS2016

Probabilistic Survivability Versus Time Modeling

This presentation documents Kennedy Space Center's Independent Assessment work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer during key programmatic reviews and provided the GSDO Program with analyses of how egress time affects the likelihood of astronaut and ground worker survival during an emergency. For each assessment, a team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedy's Vehicle Assembly Building.

Operational Hazards↗

NASA NTRS2016

[MaRS Project]

The Space Exploration Division of the Safety and Mission Assurances Directorate is responsible for reducing the risk to Human Space Flight Programs by providing system safety, reliability, and risk analysis. The Risk & Reliability Analysis branch plays a part in this by utilizing Probabilistic Risk Assessment (PRA) and Reliability and Maintainability (R&M) tools to identify possible types of failure and effective solutions. A continuous effort of this branch is MaRS, or Mass and Reliability System, a tool that was the focus of this internship. Future long duration space missions will have to find a balance between the mass and reliability of their spare parts. They will be unable take spares of everything and will have to determine what is most likely to require maintenance and spares. Currently there is no database that combines mass and reliability data of low level space-grade components. MaRS aims to be the first database to do this. The data in MaRS will be based on the hardware flown on the International Space Stations (ISS). The components on the ISS have a long history and are well documented, making them the perfect source. Currently, MaRS is a functioning excel workbook database; the backend is complete and only requires optimization. MaRS has been populated with all the assemblies and their components that are used on the ISS; the failures of these components are updated regularly. This project was a continuation on the efforts of previous intern groups. Once complete, R&M engineers working on future space flight missions will be able to quickly access failure and mass data on assemblies and components, allowing them to make important decisions and tradeoffs.

Aruljothi, Arunvenkatesh↗

NASA NTRS2015

Probabilistic Survivability Versus Time Modeling

This technical paper documents Kennedy Space Centers Independent Assessment team work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer (CSO) and GSDO management during key programmatic reviews. The assessments provided the GSDO Program with an analysis of how egress time affects the likelihood of astronaut and worker survival during an emergency. For each assessment, the team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedys Vehicle Assembly Building (VAB).Based on the composite survivability versus time graphs from the first two assessments, there was a soft knee in the Figure of Merit graphs at eight minutes (ten minutes after egress ordered). Thus, the graphs illustrated to the decision makers that the final emergency egress design selected should have the capability of transporting the flight crew from the top of LC 39B to a safe location in eight minutes or less. Results for the third assessment were dominated by hazards that were classified as instantaneous in nature (e.g. stacking mishaps) and therefore had no effect on survivability vs time to egress the VAB. VAB emergency scenarios that degraded over time (e.g. fire) produced survivability vs time graphs that were line with aerospace industry norms.

Joyner, James J., Sr.↗

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 NTRS1987

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system structural components

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Cruse, T. A.↗

NASA NTRS1988

Probabilistic Structural Analysis Methods for select space propulsion system structural components (PSAM)

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Cruse, T. A.↗

NASA NTRS1997

Fatigue Reliability of Gas Turbine Engine Structures

The results of an investigation are described for fatigue reliability in engine structures. The description consists of two parts. Part 1 is for method development. Part 2 is a specific case study. In Part 1, the essential concepts and practical approaches to damage tolerance design in the gas turbine industry are summarized. These have evolved over the years in response to flight safety certification requirements. The effect of Non-Destructive Evaluation (NDE) methods on these methods is also reviewed. Assessment methods based on probabilistic fracture mechanics, with regard to both crack initiation and crack growth, are outlined. Limit state modeling techniques from structural reliability theory are shown to be appropriate for application to this problem, for both individual failure mode and system-level assessment. In Part 2, the results of a case study for the high pressure turbine of a turboprop engine are described. The response surface approach is used to construct a fatigue performance function. This performance function is used with the First Order Reliability Method (FORM) to determine the probability of failure and the sensitivity of the fatigue life to the engine parameters for the first stage disk rim of the two stage turbine. A hybrid combination of regression and Monte Carlo simulation is to use incorporate time dependent random variables. System reliability is used to determine the system probability of failure, and the sensitivity of the system fatigue life to the engine parameters of the high pressure turbine. 'ne variation in the primary hot gas and secondary cooling air, the uncertainty of the complex mission loading, and the scatter in the material data are considered.

Cruse, Thomas A.↗

NASA NTRS2018

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↗