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The objective of this presentation is to discuss the PRA process and the reliability engineering discipline, their differences and similarities, and how they are used as complimentary analyses to support design and flight decisions.
The overall goal of the 2nd Generation RLV Program is to substantially reduce technical and business risks associated with developing a new class of reusable launch vehicles. NASA's specific goals are to improve the safety of a 2nd generation system by 2 orders of magnitude - equivalent to a crew risk of 1-in-10,000 missions - and decrease the cost tenfold, to approximately $1,000 per pound of payload launched. Architecture definition is being conducted in parallel with the maturating of key technologies specifically identified to improve safety and reliability, while reducing operational costs. An architecture broadly includes an Earth-to-orbit reusable launch vehicle, on-orbit transfer vehicles and upper stages, mission planning, ground and flight operations, and support infrastructure, both on the ground and in orbit. The systems engineering approach ensures that the technologies developed - such as lightweight structures, long-life rocket engines, reliable crew escape, and robust thermal protection systems - will synergistically integrate into the optimum vehicle. To best direct technology development decisions, analytical models are employed to accurately predict the benefits of each technology toward potential space transportation architectures as well as the risks associated with each technology. Rigorous systems analysis provides the foundation for assessing progress toward safety and cost goals. The systems engineering review process factors in comprehensive budget estimates, detailed project schedules, and business and performance plans, against the goals of safety, reliability, and cost, in addition to overall technical feasibility. This approach forms the basis for investment decisions in the 2nd Generation RLV Program's risk-reduction activities. Through this process, NASA will continually refine its specialized needs and identify where Defense and commercial requirements overlap those of civil missions.
The overall goal of the 2nd Generation RLV Program is to substantially reduce technical and business risks associated with developing a new class of reusable launch vehicles. NASA's specific goals are to improve the safety of a 2nd-generation system by 2 orders of magnitude - equivalent to a crew risk of 1-in-10,000 missions - and decrease the cost tenfold, to approximately $1,000 per pound of payload launched. Architecture definition is being conducted in parallel with the maturating of key technologies specifically identified to improve safety and reliability, while reducing operational costs. An architecture broadly includes an Earth-to-orbit reusable launch vehicle, on-orbit transfer vehicles and upper stages, mission planning, ground and flight operations, and support infrastructure, both on the ground and in orbit. The systems engineering approach ensures that the technologies developed - such as lightweight structures, long-life rocket engines, reliable crew escape, and robust thermal protection systems - will synergistically integrate into the optimum vehicle. To best direct technology development decisions, analytical models are employed to accurately predict the benefits of each technology toward potential space transportation architectures as well as the risks associated with each technology. Rigorous systems analysis provides the foundation for assessing progress toward safety and cost goals. The systems engineering review process factors in comprehensive budget estimates, detailed project schedules, and business and performance plans, against the goals of safety, reliability, and cost, in addition to overall technical feasibility. This approach forms the basis for investment decisions in the 2nd Generation RLV Program's risk-reduction activities. Through this process, NASA will continually refine its specialized needs and identify where Defense and commercial requirements overlap those of civil missions.
Experience from tests and flights and engineering analysis represent the two sources of information on which to base conclusions on the reliability or failure risk of aerospace flight systems. It is rarely feasible to establish high reliability at high confidence by testing aerospace flight systems or components. The limitations of testing in evaluating failure risk are discussed and an alternate statistical approach which relies on both test experience and analysis to quantitatively assess reliability is outlined. The implementation of this methodology in the service life assessment of ion thrusters is discussed and examples of failure modes being addressed in the NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) program are given.
The service longevity of complex propulsion systems, such as the Space Shuttle Main Engine (SSME), can be at risk from several competing failure modes. Conventional life assessment practice focuses upon the most severely life-limited feature of a given component, even though there may be other, less severe, potential failure locations. Primary, secondary, tertiary failure modes, as well as their associated probabilities, must also be considered. Futhermore, these probabilities are functions of accumulated service time. Thus a component may not always succumb to the most severe, or even the most probable failure mode. Propulsion system longevity must be assessed by considering simultaneously the actions of, and interactions among, life-limiting influences. These include, but are not limited to, high frequency fatigue (HFF), low cycle fatigue (LCF), and subsequent crack propagation, thermal and acoustic loadings, and the influence of less-than-ideal nondestructive evaluation (NDE). An outline is provided for a probabilistic model for service life analysis, and the progress towards its implementation is reported.
Finite element models (FEM) are routinely developed and used during fabrication of high dollar-value hardware. NASA, as part of the pre-flight certification of launch vehicles, routinely conducts vibration and static tests to calibrate models used for flight-risk assessments. During model calibration, certain areas of the model are modified, using engineering judgment and sensitivity analysis, to match the test results. Unfortunately, tools to identify problem areas in the FEM using test data directly are scarce and infrequently applied. Over the years, error localization algorithms have been proposed with very limited success. Recently, the Analytical Dynamics Model Improvement (ADMI) algorithm, which computes closed-form mass and stiffness corrections to match the test data exactly, have been shown to be an effective Error Localization Algorithm (ELA). The paper discusses three examples where ELA is used with simulated test data to locate problem areas. To gain confidence in the approach, the exact answer is shown along with ELA results. Results show that ELA is able to identify general problem areas consistent with known problem areas. In all examples, the ELA identified area is larger than the exact problem area. Nonetheless, with proper optimization tools, calibration results using the ELA identified areas provide excellent results.
Maintenance of human health on long-duration exploration missions is a primary challenge to mission designers. Indeed, human health risks are currently the largest risk contributors to the risks of evacuation or loss of the crew on long-duration International Space Station missions. We describe a quantitative assessment of the relative probabilities of occurrence of the individual risks to human safety and efficiency during space flight to augment qualitative assessments used in this field to date. Quantitative probabilistic risk assessments will allow program managers to focus resources on those human health risks most likely to occur with undesirable consequences. Truly quantitative assessments are common, even expected, in the engineering and actuarial spheres, but that capability is just emerging in some arenas of life sciences research, such as identifying and minimize the hazards to astronauts during future space exploration missions. Our expectation is that these results can be used to inform NASA mission design trade studies in the near future with the objective of preventing the higher among the human health risks. We identify and discuss statistical techniques to provide this risk quantification based on relevant sets of astronaut biomedical data from short and long duration space flights as well as relevant analog populations. We outline critical assumptions made in the calculations and discuss the rationale for these. Our efforts to date have focussed on quantifying the probabilities of medical risks that are qualitatively perceived as relatively high risks of radiation sickness, cardiac dysrhythmias, medically significant renal stone formation due to increased calcium mobilization, decompression sickness as a result of EVA (extravehicular activity), and bone fracture due to loss of bone mineral density. We present these quantitative probabilities in order-of-magnitude comparison format so that relative risk can be gauged. We address the effects of conservative and nonconservative assumptions on the probability results. We discuss the methods necessary to assess mission risks once exploration mission scenarios are characterized. Preliminary efforts have produced results that are commensurate with earlier qualitative estimates of risk probabilities in this and other operational contexts, indicating that our approach may be usefully applied in support of the development of human health and performance standards for long-duration space exploration missions. This approach will also enable mission-specific probabilistic risk assessments for space exploration missions.
The Mini-Research Module-2 (MRM-2), a Russian module on the International Space Station, does not meet its requirements for micrometeoroid and orbital debris probability of no penetration (PNP). To document this condition, the primary Russian Federal Space Agency ISS contractor, S.P. Korolev Rocket and Space Corporation-Energia (RSC-E), submitted an ISS non-compliance report (NCR) which was presented at the 5R Stage Operations Readiness Review (SORR) in October 2009. In the NCR, RSC-E argued for waiving the PNP requirement based on several factors, one of which was the risk of catastrophic failure was acceptably low at 1 in 11,100. However, NASA independently performed an assessment of the catastrophic risk resulting in a value of 1 in 1380 and believed that the risk at that level was unacceptable. The NASA Engineering and Safety Center was requested to evaluate the two competing catastrophic risk values and determine which was more accurate. This document contains the outcome of the assessment.
The United States (U.S.) Vision for Space Exploration directs NASA to develop two new launch vehicles for sending humans to the Moon, Mars, and beyond. In January 2006, NASA streamlined its hardware development approach for replacing the Space Shuttle after it is retired in 2010. Benefits of this approach include reduced programmatic and technical risks and the potential to return to the Moon by 2020, by developing the Ares I Crew Launch Vehicle (CLV) propulsion elements now, with full extensibility to future Ares V Cargo Launch Vehicle (CaLV) lunar systems. This decision was reached after the Exploration Launch Projects Office performed a variety of risk analyses, commonality assessments, and trade studies. The Constellation Program selected the Pratt & Whitney Rocketdyne J-2X engine to power the Ares I Upper Stage Element and the Ares V Earth Departure Stage. This paper narrates the evolution of that decision; describes the performance capabilities expected of the J-2X design, including potential commonality challenges and opportunities between the Ares I and Ares V launch vehicles; and provides a current status of J-2X design, development, and hardware testing activities. This paper also explains how the J-2X engine effort mitigates risk by building on the Apollo Program and other lessons lived to deliver a human-rated engine that is on an aggressive development schedule, with its first demonstration flight in 2012.
Since the Space Shuttle Challenger accident in 1986, NASA has extensively used probabilistic analysis methods to assess, understand, and communicate the risk of space launch vehicles. Probabilistic Risk Assessment (PRA), used in the nuclear industry, is one of the probabilistic analysis methods NASA utilizes to assess Loss of Mission (LOM) and Loss of Crew (LOC) risk for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability distributions to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: 1) what can go wrong that would lead to loss or degraded performance (i.e., scenarios involving undesired consequences of interest), 2) how likely is it (probabilities), and 3) what is the severity of the degradation (consequences). Since the Challenger accident, PRA has been used in supporting decisions regarding safety upgrades for launch vehicles. Another area that was given a lot of emphasis at NASA after the Challenger accident is reliability engineering. Reliability engineering has been a critical design function at NASA since the early Apollo days. However, after the Challenger accident, quantitative reliability analysis and reliability predictions were given more scrutiny because of their importance in understanding failure mechanism and quantifying the probability of failure, which are key elements in resolving technical issues, performing design trades, and implementing design improvements. Although PRA and reliability are both probabilistic in nature and, in some cases, use the same tools, they are two different activities. Specifically, reliability engineering is a broad design discipline that deals with loss of function and helps understand failure mechanism and improve component and system design. PRA is a system scenario based risk assessment process intended to assess the risk scenarios that could lead to a major/top undesirable system event, and to identify those scenarios that are high-risk drivers. PRA output is critical to support risk informed decisions concerning system design. This paper describes the PRA process and the reliability engineering discipline in detail. It discusses their differences and similarities and how they work together as complementary analyses to support the design and risk assessment processes. Lessons learned, applications, and case studies in both areas are also discussed in the paper to demonstrate and explain these differences and similarities.
Human exploration-class launch vehicles are inherently prone to debris due to the extreme environments generated during pre-launch operations, liftoff, and flight. The use of cryogenic propellants often requires thermal protection system (TPS) coatings, typically foam, to maintain the propellant conditions in the tank and prevent an accumulation ice on the external surface of the vehicle. Some ice growth is to be expected at umbilical interfaces, vents, flanges, or brackets where it is difficult to apply TPS. This ice may come loose at any time due to wind on the launch pad, structural vibration and acoustics after rocket ignition, or aerodynamic forces during flight. This phenomena is especially apparent on vehicles with no TPS, such as the Saturn V rockets used in the Apollo Program, see Figure 1. During propellant tanking, the thermal contraction of the underlying substrate may generate cracks in the TPS (Figure 1). Chunks of TPS can release due to the expansion of ingested gas from cryopumping or from aerodynamic forces if the crack creates an offset surface. Most foams will also have a certain amount of “popcorning” where small pieces of foam will pop off during flight because of the differential between the static surface pressure and the pressure of the gas trapped in the foam cell structure. There are a number of other coating or closeout materials that may be shed from the vehicle and become debris. During pre-launch operations and liftoff, the vehicle may also be exposed to debris originating from the launch pad or ground support equipment. This debris is separate from foreign object debris, or FOD, which is not intended to be present and is strictly controlled through operations and maintenance procedures. In this case, debris is generated from hardware and materials that are necessary for launch and are subject to the intense vibration, acoustics, and direct plume impingement of the launch environment. Examples include ice from umbilicals, tape and tie wraps that protect cables, and rust or corrosion from the launch platform. While NASA has historically been aware of debris as a potential issue that could cause a failure resulting in loss of mission, loss of vehicle, or loss of crew, the likelihood and severity of that risk was not always well understood or given sufficient weight in program and flight decisions. After the Space Shuttle Columbia accident (STS-107), the investigation found that foam TPS debris shed from the external tank was the proximate cause of the damage to the orbiter wing. Six previous observations of debris released from the foam ramp that covered the bipod connecting the forward end of the orbiter to the external tank resulted in minor changes or were determined to be accepted flight risks. Two occurrences of bipod ramp foam loss were not identified until the STS-107 investigation. Despite the damage inflicted by these debris strikes, the Shuttle Program Requirements Control Board deemed the vehicle safe to fly. During the Return to Flight effort following the Columbia disaster, NASA Engineering developed a process for the assessment of debris transport, impact, and damage tolerance to support independent assessments of risk by NASA Safety and Mission Assurance (S&MA). Under this system, each element (vehicle or ground system) defines a catalog of all expected debris based on launch history, component testing, or analysis. Debris transport analysis (DTA) is conducted using the debris catalog characteristics and potential flow transport mechanisms (e.g., vehicle aerodynamics, gravity, wind, plume-driven). The predicted debris impact locations and velocities are provided to the hardware owners, who use available test data and analysis to determine whether each component can withstand the impacts. In cases where the element hardware may be severely damaged or fail, the options are to mitigate the debris source through some change in design or operation, or to work with S&MA to try to characterize the probability of the impact and damage for program risk acceptance. Because of the differences in debris characteristics and transport, the DTA has been divided between the Liftoff and Ascent regimes. The development and application of Liftoff DTA methodology from the Shuttle Program to the current Artemis Program is the subject of this paper. Liftoff DTA covers the time from the start of pre-launch operations at the launch pad, up until the vehicle clears the launch tower and there is no longer any interaction with ground systems. Debris transport during this period is broadly classified as either gravity, wind, and plume-entrained (GWPE) or plume driven (PD). GWPE debris is generally lower speed, travelling in a forward-to-aft direction. PD transport includes flow features from the rocket ignition transient, as well as plume impingement and recirculation that occur as the vehicle lifts off the launch platform. In these cases, the debris typically moves in an aft-to-forward direction at higher speeds. The applicable transport mechanisms must be considered for each piece of debris depending on the material, and release location and time. For example, rust or metallic debris from the tower could fall (GWPE) and impact the vehicle before landing on the launch platform deck where it could be also be transported by plume impingement (PD). However, falling ice (GWPE) from an umbilical is unlikely to survive impact with the vehicle or launch platform and be available for PD transport. Modeling of debris transport is accomplished using a set of DTA tools which simulate debris trajectories subject to a reference frame acceleration (i.e., gravity) and aerodynamic drag. Where the trajectory encounters a solid surface, the debris is allowed to rebound with a specified coefficient of restitution. The drag is calculated by interpolating the fluid state at each point in the debris trajectory from high-fidelity computational fluid dynamics (CFD) simulations of the launch vehicle and pad. The CFD data may either be static (steady state or time averaged), typically for GWPE transport, or dynamic (time-accurate) for PD flow features like the ignition transient. Examples of the CFD flow field solutions for the Space Launch System (SLS) rocket and launch pad are shown in Figure 2. Typical SLS debris trajectory predictions from DTA are illustrated in Figure 3. The final version of this paper will include a more detailed examination of the Liftoff DTA process developed during the Shuttle Program, and how it has been augmented and applied to the SLS rocket under the Artemis Program. Comparisons with debris observations from the Artemis I launch will demonstrate validation of the tools and methodology.
Boeing-Canoga Park (BCP) and NASA-Marshall Space Flight Center (NASA-MSFC) are developing an Advanced Health Management System (AHMS) for use on the Space Shuttle Main Engine (SSME) that will improve Shuttle safety by reducing the probability of catastrophic engine failures during the powered ascent phase of a Shuttle mission. This is a phased approach that consists of an upgrade to the current Space Shuttle Main Engine Controller (SSMEC) to add turbomachinery synchronous vibration protection and addition of a separate Health Management Computer (HMC) that will utilize advanced algorithms to detect and mitigate predefined engine anomalies. The purpose of the Shuttle AHMS is twofold; one is to increase the probability of successfully placing the Orbiter into the intended orbit, and the other is to increase the probability of being able to safely execute an abort of a Space Transportation System (STS) launch. Both objectives are achieved by increasing the useful work envelope of a Space Shuttle Main Engine after it has developed anomalous performance during launch and the ascent phase of the mission. This increase in work envelope will be the result of two new anomaly mitigation options, in addition to existing engine shutdown, that were previously unavailable. The added anomaly mitigation options include engine throttle-down and performance correction (adjustment of engine oxidizer to fuel ratio), as well as enhanced sensor disqualification capability. The HMC is intended to provide the computing power necessary to diagnose selected anomalous engine behaviors and for making recommendations to the engine controller for anomaly mitigation. Independent auditors have assessed the reduction in Shuttle ascent risk to be on the order of 40% with the combined system and a three times improvement in mission success.
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.
The probabilistic structural analysis method (PSAM) was developed to analyze the effects of fluctuating loads, variable material properties, and uncertain analytical models especially for high performance structures such as the Space Shuttle Main Engine turbopump blades. Risk is calculated after expensive service experience. However, probabilistic structural analysis provides a rational alternative method to quantify uncertainties in the structural performance and durability. NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a probabilistic structural analysis computer code which integrates finite element methods and reliability algorithms, capable to predicting the probability distributions of structural response variables such as stress, displacement, natural frequencies, and buckling loads. This computer code is detailed.
With the conclusion of the NASA/ESA partnership on the Laser Interferometer Space Antenna (LISA) Project, NASA initiated a study to explore mission concepts that will accomplish some or all of the LISA science objectives at lower cost. The Gravitational-Wave Mission Concept Study consisted of a public Request for Information (RFI), a Core Team of NASA engineers and scientists, a Community Science Team, a Science Task Force, and an open workshop. The RFI yielded were 12 mission concepts, 3 instrument concepts and 2 technologies. The responses ranged from concepts that eliminated the drag-free test mass of LISA to concepts that replace the test mass with an atom interferometer. The Core Team reviewed the noise budgets and sensitivity curves, the payload and spacecraft designs and requirements, orbits and trajectories and technical readiness and risk. The Science Task Force assessed the science performance by calculating the horizons. the detection rates and the accuracy of astrophysical parameter estimation for massive black hole mergers, stellar-mass compact objects inspiraling into central engines. and close compact binary systems. Three mission concepts have been studied by Team-X, JPL's concurrent design facility. to define a conceptual design evaluate kt,y performance parameters. assess risk and estimate cost and schedule. The Study results are summarized.
A Risk Management Process has been tailored for Cassini that not only satisfies the requirements of NASA and JPL, but also allows the Program to proactively identify and assess risks that threaten mission objectives. Cassini Risk Management is a team effort that involves both management and engineering staff. The process is managed and facilitated by the Mission Assurance Manager (MAM), but requires regular interactions with Program Staff and team members to instill the risk management philosophy into the day to day mission operations. While Risk Management is well defined for projects in the development phase, it is a relatively new concept for Mission Operations. The Cassini team has embraced this process and has begun using it in an effective, proactive manner, to ensure mission success. It is hoped that the Cassini Risk Management Process will form the basis by which risk management is conducted during MO&DA on future projects. proactive in identifying, assessing and mitigating risks before they become problems. Cost ehtiveness is achieved by: Comprehensively identifying risks Rapidly assessing which risks require the expenditure of pruject cewums Taking early actions to mitigate these risks Iterating the process frequently, to be responsive to the dynamic internal and external environments The Cassini Program has successfully implemented a Risk Management Process for mission operations, The initial SRL has been developed and input into he online tool. The Risk Management webbased system has been rolled out for use by the flight team and risk owners we working proactive in identifying, assessing and mitigating risks before they become problems. Cost ehtiveness is achieved by: Comprehensively identifying risks Rapidly assessing which risks require the expenditure of pruject cewums Taking early actions to mitigate these risks Iterating the process frequently, to be responsive to the dynamic internal and external environments The Cassini Program has successfully implemented a Risk Management Process for mission operations, The initial SRL has been developed and input into he online tool. The Risk Management webbased system has been rolled out for use by the flight team and risk owners we working put into place will become visible and will be illusmted in future papers.
A quantitative methodology is being developed for assessment of risk of failure of solid rocket motors. This probabilistic methodology employs best available engineering models and available information in a stochastic framework. The framework accounts for incomplete knowledge of governing parameters, intrinsic variability, and failure model specification error. Earlier case studies have been conducted on several failure modes of the Space Shuttle Main Engine. Work in progress on application of this probabilistic approach to large solid rocket boosters such as the Advanced Solid Rocket Motor for the Space Shuttle is described. Failure due to debonding has been selected as the first case study for large solid rocket motors (SRMs) since it accounts for a significant number of historical SRM failures. Impact of incomplete knowledge of governing parameters and failure model specification errors is expected to be important.
Topics discussed include: new debris from a decommissioned satellite with a nuclear power source; debris from the destruction of the Fengyun-1C meteorological satellite; quantitative analysis of the European Space Agency's Automated Transfer Vehicle 'Jules Verne' reentry event; microsatellite impact tests; solar cycle 24 predictions and other long-term projections and geosynchronus (GEO) environment for the Orbital Debris Engineering Model (ORDEM2008). Abstracts from the NASA Orbital Debris Program Office, examining satellite reentry risk assessments and statistical issues for uncontrolled reentry hazards, are also included.