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NASA NTRS2003

Space Shuttle Main Engine Implications for the Abort-to-Orbit Off-the-Pad Study

In 2001, the Space Shuttle Main Engine (SSME) project office was contacted by the Space Shuttle Ascent Guidance, Navigation, and Control group to provide the engine perspective for an Abort-to-Orbit (ATO) study. The purpose of the AT0 Off-the-Pad study was to determine the feasibility of eliminating the Return to Launch Site and Transatlantic abort modes by using a five-segment solid rocket booster and throttling the remaining SSMEs to a higher power level. This would enable all abort modes to be Abort-to-Orbit. The SSME project office at Marshall Space Flight Center collaborated with MSFC's Space Transportation Directorate and Rocketdyne Propulsion and Power to provide the AT0 Off-the-Pad study with the analysis required. Power levels at 109%, 1 11% and 1 13% of rated power level were studied as well as mixture ratio decreases down to 5.85. SSME was to evaluate and define the technical and programmatic impacts to certify the SSME to these abort power levels. The SSME systems analysis group performed a steady state analysis using the SSME power balance model to determine if there were any technical issues associated with higher power level, low mixture ratio operation. Based on each power level/mixture ratio combination, an engine certification plan was created and a preliminary probabilistic risk assessment was performed. The results showed favorable results for higher power 1evel/lower mixture ratio SSME operation. In nearly all performance and redline parameters, the traded engine operation was encompassed by nominal engine performance of a prior engine configuration.

Schoffstoll, Dayna L.↗
NASA NTRS2004

PSRP Approach to PRA

There have been two scenarios in which the Payload Safety Review Panel (PSRP) has considered a Probabilistic Risk Assessment (PRA) a viable tool. For use in considering trade-offs during the initial design. When in a waiver condition to explain rationale for acceptance. The PSRP would consider the use of PRA in other applications where credible.

Stewart, Christine↗
NASA NTRS2005

Knowledge Representation Standards and Interchange Formats for Causal Graphs

In many domains, automated reasoning tools must represent graphs of causally linked events. These include fault-tree analysis, probabilistic risk assessment (PRA), planning, procedures, medical reasoning about disease progression, and functional architectures. Each of these fields has its own requirements for the representation of causation, events, actors and conditions. The representations include ontologies of function and cause, data dictionaries for causal dependency, failure and hazard, and interchange formats between some existing tools. In none of the domains has a generally accepted interchange format emerged. The paper makes progress towards interoperability across the wide range of causal analysis methodologies. We survey existing practice and emerging interchange formats in each of these fields. Setting forth a set of terms and concepts that are broadly shared across the domains, we examine the several ways in which current practice represents them. Some phenomena are difficult to represent or to analyze in several domains. These include mode transitions, reachability analysis, positive and negative feedback loops, conditions correlated but not causally linked and bimodal probability distributions. We work through examples and contrast the differing methods for addressing them. We detail recent work in knowledge interchange formats for causal trees in aerospace analysis applications in early design, safety and reliability. Several examples are discussed, with a particular focus on reachability analysis and mode transitions. We generalize the aerospace analysis work across the several other domains. We also recommend features and capabilities for the next generation of causal knowledge representation standards.

Throop, David R.↗
NASA NTRS2007

Design for Reliability and Safety Approach for the New NASA Launch Vehicle

The United States National Aeronautics and Space Administration (NASA) is in the midst of a space exploration program intended for sending crew and cargo to the international Space Station (ISS), to the moon, and beyond. This program is called Constellation. As part of the Constellation program, NASA is developing new launch vehicles aimed at significantly increase safety and reliability, reduce the cost of accessing space, and provide a growth path for manned space exploration. Achieving these goals requires a rigorous process that addresses reliability, safety, and cost upfront and throughout all the phases of the life cycle of the program. This paper discusses the "Design for Reliability and Safety" approach for the NASA new launch vehicles, the ARES I and ARES V. Specifically, the paper addresses the use of an integrated probabilistic functional analysis to support the design analysis cycle and a probabilistic risk assessment (PRA) to support the preliminary design and beyond.

Safie, Fayssal M.↗
NASA NTRS2008

Designing a Composable Geometric Toolkit for Versatility in Applications to Simulation Development

Conceived and implemented through the development of probabilistic risk assessment simulations for Project Constellation, the Geometric Toolkit allows users to create, analyze, and visualize relationships between geometric shapes in three-space using the MATLAB computing environment. The key output of the toolkit is an analysis of how emanations from one "source" geometry (e.g., a leak in a pipe) will affect another "target" geometry (e.g., another heat-sensitive component). It can import computer-aided design (CAD) depictions of a system to be analyzed, allowing the user to reliably and easily represent components within the design and determine the relationships between them, ultimately supporting more technical or physics-based simulations that use the toolkit. We opted to develop a variety of modular, interconnecting software tools to extend the scope of the toolkit, providing the capability to support a range of applications. This concept of simulation composability allows specially-developed tools to be reused by assembling them in various combinations. As a result, the concepts described here and implemented in this toolkit have a wide range of applications outside the domain of risk assessment. To that end, the Geometric Toolkit has been evaluated for use in other unrelated applications due to the advantages provided by its underlying design.

Reed, Gregory S.↗
NASA NTRS2010

Estimating the Reliability of a Soyuz Spacecraft Mission

Once the US Space Shuttle retires in 2010, the Russian Soyuz Launcher and Soyuz Spacecraft will comprise the only means for crew transportation to and from the International Space Station (ISS). The U.S. Government and NASA have contracted for crew transportation services to the ISS with Russia. The resulting implications for the US space program including issues such as astronaut safety must be carefully considered. Are the astronauts and cosmonauts safer on the Soyuz than the Space Shuttle system? Is the Soyuz launch system more robust than the Space Shuttle? Is it safer to continue to fly the 30 year old Shuttle fleet for crew transportation and cargo resupply than the Soyuz? Should we extend the life of the Shuttle Program? How does the development of the Orion/Ares crew transportation system affect these decisions? The Soyuz launcher has been in operation for over 40 years. There have been only two loss of life incidents and two loss of mission incidents. Given that the most recent incident took place in 1983, how do we determine current reliability of the system? Do failures of unmanned Soyuz rockets impact the reliability of the currently operational man-rated launcher? Does the Soyuz exhibit characteristics that demonstrate reliability growth and how would that be reflected in future estimates of success? NASA s next manned rocket and spacecraft development project is currently underway. Though the projects ultimate goal is to return to the Moon and then to Mars, the launch vehicle and spacecraft s first mission will be for crew transportation to and from the ISS. The reliability targets are currently several times higher than the Shuttle and possibly even the Soyuz. Can these targets be compared to the reliability of the Soyuz to determine whether they are realistic and achievable? To help answer these questions this paper will explore how to estimate the reliability of the Soyuz Launcher/Spacecraft system, compare it to the Space Shuttle, and its potential impacts for the future of manned spaceflight. Specifically it will look at estimating the Loss of Mission (LOM) probability using historical data, reliability growth, and Probabilistic Risk Assessment techniques

Lutomski, Michael G.↗
NASA NTRS2010

JSC Safety and Mission Assurance Data Analysis Overview

These slides describe the data analysis methods that are used to determine inputs for probabilistic risk models supporting the Space Shuttle Program. Other applications can follow a similar path probably using different data sources. Statistical approaches are different and not addressed here. Topics included here: 1) Prior Distribution; 2) Likelihood Data; 3) Bayesian Updating; and 4) Uncertainty and Error. Note: This is a high-level discussion and is not intended to be a tutorial.

Roelant, Henk↗
NASA NTRS2011

Estimating the Loss of Crew and Loss of Mission for Crew Spacecraft

Once the US Space Shuttle retires in 2011, the Russian Soyuz Launcher and Soyuz Spacecraft will comprise the only means for crew transportation to and from the International Space Station (ISS). The U.S. Government and NASA have contracted for crew transportation services to the ISS with Russia. The resulting implications for the US space program including issues such as astronaut safety must be carefully considered. Are the astronauts and cosmonauts safer on the Soyuz than the Space Shuttle system? Is the Soyuz launch system more robust than the Space Shuttle? The Soyuz launcher has been in operation for over 40 years. There have been only two loss of life incidents and two loss of mission incidents. Given that the most recent incident took place in 1983, how do we determine current reliability of the system? Do failures of unmanned Soyuz rockets impact the reliability of the currently operational man-rated launcher? Does the Soyuz exhibit characteristics that demonstrate reliability growth and how would that be reflected in future estimates of success? NASA s next manned rocket and spacecraft development project will have to meet the Agency Threshold requirements set forth by NASA. The reliability targets are currently several times higher than the Shuttle and possibly even the Soyuz. Can these targets be compared to the reliability of the Soyuz to determine whether they are realistic and achievable? To help answer these questions this paper will explore how to estimate the reliability of the Soyuz Launcher/Spacecraft system, compare it to the Space Shuttle, and its potential impacts for the future of manned spaceflight. Specifically it will look at estimating the Loss of Crew (LOC) and Loss of Mission (LOM) probability using historical data, reliability growth, and Probabilistic Risk Assessment techniques used to generate these numbers.

Lutomski, Michael G.↗
NASA NTRS2004

NASA Tech Briefs, July 2004

Topics: Optoelectronic Sensor System for Guidance in Docking; Hybrid Piezoelectric/Fiber-Optic Sensor Sheets; Multisensor Arrays for Greater Reliability and Accuracy; Integrated-Optic Oxygen Sensors; Ka-Band Autonomous Formation Flying Sensor; CMOS VLSI Active-Pixel Sensor for Tracking; Lightweight, Self-Deploying Foam Antenna Structures; Electrically Small Microstrip Quarter-Wave Monopole Antennas; A 2-to-28-MHz Phase-Locked Loop; Portable Electromyograph; Open-Source Software for Modeling of Nanoelectronic Devices; Software for Generating Strip Maps from SAR Data; Calibration Software for use with Jurassicprok; Software for Probabilistic Risk Reduction; Software Processes SAR Motion-Measurement Data; Improved Method of Purifying Carbon Nanotubes; Patterned Growth of Carbon Nanotubes or Nanofibers; Lightweight, Rack-Mountable Composite Cold Plate/Shelves; SiC-Based Miniature High-Temperature Cantilever Anemometer; Inlet Housing for a Partial-Admission Turbine; Lightweight Thermoformed Structural Components and Optics; Growing High-Quality InAs Quantum Dots for Infrared Lasers; Selected Papers on Protoplanetary Disks; Module for Oxygenating Water without Generating Bubbles; Coastal Research Imaging Spectrometer; Rapid Switching and Modulation by use of Coupled VCSELs; Laser-Induced-Fluorescence Photogrammetry and Videogrammetry; Laboratory Apparatus Generates Dual-Species Cold Atomic Beam; Laser Ablation of Materials for Propulsion of Spacecraft; Small Active Radiation Monitor; Hybrid Image-Plane/Stereo Manipulation; Partitioning a Gridded Rectangle into Smaller Rectangles; Digital Radar-Signal Processors Implemented in FPGAs; Part 1 of a Computational Study of a Drop-Laden Mixing Layer; and Some Improvements in Signal-Conditioning Circuits.

Source record↗
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 NTRS2013

Practical Application of PRA as an Integrated Design Tool for Space Systems

This paper presents the application of the first comprehensive Probabilistic Risk Assessment (PRA) during the design phase of a joint NASA/NOAA weather satellite program, Geostationary Operational Environmental Satellite Series R (GOES-R). GOES-R is the next generation weather satellite primarily to help understand the weather and help save human lives. PRA has been used at NASA for Human Space Flight for many years. PRA was initially adopted and implemented in the operational phase of manned space flight programs and more recently for the next generation human space systems. Since its first use at NASA, PRA has become recognized throughout the Agency as a method of assessing complex mission risks as part of an overall approach to assuring safety and mission success throughout project lifecycles. PRA is now included as a requirement during the design phase of both NASA next generation manned space vehicles as well as for high priority robotic missions. The influence of PRA on GOES-R design and operation concepts are discussed in detail. The GOES-R PRA is unique at NASA for its early implementation. It also represents a pioneering effort to integrate risks from both Spacecraft (SC) and Ground Segment (GS) to fully assess the probability of achieving mission objectives. PRA analysts were actively involved in system engineering and design engineering to ensure that a comprehensive set of technical risks were correctly identified and properly understood from a design and operations perspective. The analysis included an assessment of SC hardware and software, SC fault management system, GS hardware and software, common cause failures, human error, natural hazards, solar weather and infrastructure (such as network and telecommunications failures, fire). PRA findings directly resulted in design changes to reduce SC risk from micro-meteoroids. PRA results also led to design changes in several SC subsystems, e.g. propulsion, guidance, navigation and control (GNC), communications, mechanisms, and command and data handling (C&DH). The fault tree approach assisted in the development of the fault management system design. Human error analysis, which examined human response to failure, indicated areas where automation could reduce the overall probability of gaps in operation by half. In addition, the PRA brought to light many potential root causes of system disruptions, including earthquakes, inclement weather, solar storms, blackouts and other extreme conditions not considered in the typical reliability and availability analyses. Ultimately the PRA served to identify potential failures that, when mitigated, resulted in a more robust design, as well as to influence the program's concept of operations. The early and active integration of PRA with system and design engineering provided a well-managed approach for risk assessment that increased reliability and availability, optimized lifecyc1e costs, and unified the SC and GS developments.

Kalia, Prince↗
NASA NTRS2010

Europa Planetary Protection for Juno Jupiter Orbiter

NASA's Juno mission launched in 2011 and will explore the Jupiter system starting in 2016. Juno's suite of instruments is designed to investigate the atmosphere, gravitational fields, magnetic fields, and auroral regions. Its low perijove polar orbit will allow it to explore portions of the Jovian environment never before visited. While the Juno mission is not orbiting or flying close to Europa or the other Galilean satellites, planetary protection requirements for avoiding the contamination of Europa have been taken into account in the Juno mission design.The science mission is designed to conclude with a deorbit burn that disposes of the spacecraft in Jupiter's atmosphere. Compliance with planetary protection requirements is verified through a set of analyses including analysis of initial bioburden, analysis of the effect of bioburden reduction due to the space and Jovian radiation environments, probabilistic risk assessment of successful deorbit, Monte-Carlo orbit propagation, and bioburden reduction in the event of impact with an icy body.

Juno↗
NASA NTRS2014

Exit Presentation Fall 2013

Our current International Space Station Probabilistic Risk Assessment (ISS PRA) model assumes all collisions between a visiting vehicle (VV) and the ISS result in worst case loss of the ISS crew and the vehicle (LOCV). Drawing results from the Mir-Progress collision, we know this assumption is inaccurate because that collision did not lead to LOCV. Therefore the PRA team is conducting a study to determine the likelihood of LOCV when a collision occurs between a VV and the ISS. Kinetic energy is calculated and converted to pounds of TNT for the moving VVs when they collide with the ISS. Different scenarios are evaluated to obtain collision related data such as translational kinetic energy and rotational kinetic energy. These calculated data are integrated into the results from the expert elicitation performed on the Mir- Progress collision. As a result of this study, the PRA model will now calculate the probability of a VV collision with ISS, the probability that collision will result in Loss of Soyuz Crew (LOC) or Loss of ISS Crew and Vehicle (LOCV).

Yang, Qi Rong↗
NASA NTRS2015

Common Cause Failure Modeling

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFS are a set of dependent type of failures that can be caused by: system environments; manufacturing; transportation; storage; maintenance; and assembly, as examples. Since there are many factors that contribute to CCFs, the effects can be reduced, but they are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and CCF (dependent) failure and data is limited, especially for launch vehicles. The Probabilistic Risk Assessment (PRA) of NASA's Safety and Mission Assurance Directorate at Marshall Space Flight Center (MFSC) is using generic data from the Nuclear Regulatory Commission's database of common cause failures at nuclear power plants to estimate CCF due to the lack of a more appropriate data source. There remains uncertainty in the actual magnitude of the common cause risk estimates for different systems at this stage of the design. Given the limited data about launch vehicle CCF and that launch vehicles are a highly redundant system by design, it is important to make design decisions to account for a range of values for independent and CCFs. When investigating the design of the one-out-of-two component redundant system for launch vehicles, a response surface was constructed to represent the impact of the independent failure rate versus a common cause beta factor effect on a system's failure probability. This presentation will define a CCF and review estimation calculations. It gives a summary of reduction methodologies and a review of examples of historical CCFs. Finally, it presents the response surface and discusses the results of the different CCFs on the reliability of a one-out-of-two system.

Hark, Frank↗
NASA NTRS2016

Addressing Uniqueness and Unison of Reliability and Safety for a Better Integration

Over time, it has been observed that Safety and Reliability have not been clearly differentiated, which leads to confusion, inefficiency, and, sometimes, counter-productive practices in executing each of these two disciplines. It is imperative to address this situation to help Reliability and Safety disciplines improve their effectiveness and efficiency. The paper poses an important question to address, "Safety and Reliability - Are they unique or unisonous?" To answer the question, the paper reviewed several most commonly used analyses from each of the disciplines, namely, FMEA, reliability allocation and prediction, reliability design involvement, system safety hazard analysis, Fault Tree Analysis, and Probabilistic Risk Assessment. The paper pointed out uniqueness and unison of Safety and Reliability in their respective roles, requirements, approaches, and tools, and presented some suggestions for enhancing and improving the individual disciplines, as well as promoting the integration of the two. The paper concludes that Safety and Reliability are unique, but compensating each other in many aspects, and need to be integrated. Particularly, the individual roles of Safety and Reliability need to be differentiated, that is, Safety is to ensure and assure the product meets safety requirements, goals, or desires, and Reliability is to ensure and assure maximum achievability of intended design functions. With the integration of Safety and Reliability, personnel can be shared, tools and analyses have to be integrated, and skill sets can be possessed by the same person with the purpose of providing the best value to a product development.

Huang, Zhaofeng↗
NASA NTRS2016

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk, and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results, and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods, such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty, are rendered obsolete, since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods. This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper describes how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components.

Novack, Steven D.↗
NASA NTRS2016

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty are rendered obsolete since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods.This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper shows how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components.

Novack, Steven D.↗
NASA NTRS2016

Common Cause Failure Modeling

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFS are a set of dependent type of failures that can be caused by: system environments; manufacturing; transportation; storage; maintenance; and assembly, as examples. Since there are many factors that contribute to CCFs, the effects can be reduced, but they are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and CCF (dependent) failure and data is limited, especially for launch vehicles. The Probabilistic Risk Assessment (PRA) of NASA's Safety and Mission Assurance Directorate at Marshal Space Flight Center (MFSC) is using generic data from the Nuclear Regulatory Commission's database of common cause failures at nuclear power plants to estimate CCF due to the lack of a more appropriate data source. There remains uncertainty in the actual magnitude of the common cause risk estimates for different systems at this stage of the design. Given the limited data about launch vehicle CCF and that launch vehicles are a highly redundant system by design, it is important to make design decisions to account for a range of values for independent and CCFs. When investigating the design of the one-out-of-two component redundant system for launch vehicles, a response surface was constructed to represent the impact of the independent failure rate versus a common cause beta factor effect on a system's failure probability. This presentation will define a CCF and review estimation calculations. It gives a summary of reduction methodologies and a review of examples of historical CCFs. Finally, it presents the response surface and discusses the results of the different CCFs on the reliability of a one-out-of-two system.

Hark, Frank↗