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NASA NTRSDate not supplied

Green Propulsion : A NASA GSFC Assessment

In the ever-changing paradigm of efficient and capable spacecraft design, scientific missions continue pushing spacecraft subsystems to deliver effective solutions to meet challenging new mission/spacecraft applications. From an in-space storable liquid chemical propulsion perspective, monopropellant hydrazine is a dependable propellant. Bi-propellant architectures offer even superior performance, but add the complexity of a hypergolic fuel (hydrazine/ mono-methyl hydrazine) and oxidizer (Nitrogen Tetroxide/ mixed oxides of nitrogen) dual tank combination. These propulsion system designs (mono-propellant and bi-propellant) have high heritage, high propellant throughput qualified engines, widely tested material compatibility, qualified fluid delivery commercial-off-the-shelf components, known handling practices, and repeatable performance in successfully delivering on mission requirements. NASA and the broader propulsion community have historically selected hypergolic propellants for most mission applications. The space propulsion community has learned to successfully handle these highly toxic and hazardous materials, navigate the regulated use and the associated safety protocols, personnel protective equipment, and unique training standards – all requisite for loading spacecraft propulsion systems with hypergolic propellants. The question now arises as to what is next for in-space chemical propulsion? Is there an alternative, or even replacement, to the reliable hypergolic fluids, or propellant alternatives that promise increased mission benefits? With the evolution and proven advancements in innovative in-space green propellant technologies capable of delivering benefits to scientific missions, concern over the reliability and infusibility of this higher performing and safer to handle class of propellants is waning. As NASA science missions move forward with the potential flight infusion of green propulsion, NASA and the broader propulsion community are working to address remaining gaps in hardware development, reliability, performance, unique operational considerations, and risk mitigations for high value scientific assets.

Henry W. Mulkey↗
NASA NTRS2014

How HRP Research Results Contribute to Human Space Exploration Risk Mitigation

In addition to the scientific value of publications derived from research, results from Human Research Program (HRP) research also support HRP’s goals of mitigating crew health and performance risks in space flight. Research results are used to build the evidence base characterizing crew health and performance risks, to support risk research plan development, to inform crew health and performance standards, and to provide technologies to programs for meeting those standards and optimizing crew health and performance in space. This talk will describe examples of how research results support these efforts. For example, HRP research results are used to revise or even create new standards for human space flight, which have been established to protect crew health and performance during flight, and prevent negative long-term health consequences due to space flight. These standards are based on the best available clinical and scientific evidence, as well as operational experience from previous space flight missions, and are reviewed as new evidence emerges. Research results are also used to update the HRP evidence base, which is comprised of a set of reports that provide a current record of the state of knowledge from research and operations for each of the defined human health and performance risks for future NASA exploration missions. A discussion of the role of evidence within the HRP architecture will also be presented. The scope of HRP research results extends well beyond publications, as they are used in several capacities to support HRP deliverables and, ultimately, the advancement of human space exploration beyond low-Earth orbit.

Lumpkins, S. B.↗
NASA NTRS2014

How HRP Research Results Contribute to Human Space Exploration Risk Mitigation

In addition to the scientific value of publications derived from research, results from Human Research Program (HRP) research also support HRP's goals of mitigating crew health and performance risks in space flight. Research results are used to build the evidence base characterizing crew health and performance risks, to support risk research plan development, to inform crew health and performance standards, and to provide technologies to programs for meeting those standards and optimizing crew health and performance in space. This talk will describe examples of how research results support these efforts. For example, HRP research results are used to revise or even create new standards for human space flight, which have been established to protect crew health and performance during flight, and prevent negative long-term health consequences due to space flight. These standards are based on the best available clinical and scientific evidence, as well as operational experience from previous space flight missions, and are reviewed as new evidence emerges. Research results are also used to update the HRP evidence base, which is comprised of a set of reports that provide a current record of the state of knowledge from research and operations for each of the defined human health and performance risks for future NASA exploration missions. A discussion of the role of evidence within the HRP architecture will also be presented. The scope of HRP research results extends well beyond publications, as they are used in several capacities to support HRP deliverables and, ultimately, the advancement of human space exploration beyond low-Earth orbit.

Lumpkins, Sarah↗
NASA NTRS2018

International Space Station Operational Experience and Its Impacts on Future Mission Supportability

Operational experience gained on the International Space Station (ISS) has enabled significant improvements in failure rate estimates for various Orbital Replacement Units (ORUs). These improved estimates, in turn, allow more efficient and accurate spare parts allocations for future missions, enabling significant reductions in both logistics mass and risk. This paper examines the value of ISS experience to date in terms of its impact on supportability for future missions. A supportability model is presented that assesses the spares required as a function of mission endurance and risk, taking into account uncertainty in failure rate estimates. Changes in ISS Environmental Control and Life Support (ECLSS) ORU failure rate estimates are described and discussed, both in terms of the overall population of ORUs and the evolution of failure rate estimates over time for a particular item. The value of those updated failure rate estimates is assessed by calculating the estimated spares mass requirements for two cases, using the initial, pre-ISS estimates and using the estimates informed by on-orbit experience. Hidden risk resulting from underestimated failure rates is also assessed. These results indicate that, for a 1,200-day Mars mission, ISS experience has enabled a 3.9 t to 6.0 t reduction in ECLSS spares mass required and uncovered failure rate underestimates that would have resulted in an order of magnitude increase in risk had they not been discovered and corrected. The implications of these results for system development and mission planning are discussed, including approaches to accelerate the rate of failure rate refinement and the risks associated with making changes or introducing new systems. Overall, test time is a critical factor that must be carefully considered in system development, and new systems must budget appropriate time for testing in a relevant environment or accept higher risk and logistics requirements on future missions.

Owens, Andrew C.↗
NASA NTRS2015

Common Cause Failure Modeling in Space Launch Vehicles

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 for example by system environments, manufacturing, transportation, storage, maintenance, and assembly. Since there are many factors that contribute to CCFs, they can be reduced, but are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and dependent CCF. Because common cause failure data is limited in the aerospace industry, the Probabilistic Risk Assessment (PRA) Team at Bastion Technology Inc. is estimating CCF risk using generic data collected by the Nuclear Regulatory Commission (NRC). Consequently, common cause risk estimates based on this database, when applied to other industry applications, are highly uncertain. Therefore, it is important to account for a range of values for independent and CCF risk and to communicate the uncertainty to decision makers. There is an existing methodology for reducing CCF risk during design, which includes a checklist of 40+ factors grouped into eight categories. Using this checklist, an approach to produce a beta factor estimate is being investigated that quantitatively relates these factors. In this example, the checklist will be tailored to space launch vehicles, a quantitative approach will be described, and an example of the method will be presented.

Hark, Frank↗
NASA NTRS2010

Control of Risks Through the Use of Procedures: A Method for Evaluating the Change in Risk

This paper considers how procedures can be used to control risks faced by an organization and proposes a means of recognizing if a particular procedure reduces risk or contributes to the organization's exposure. The proposed method was developed out of the review of work documents and the governing procedures performed in the wake of the Columbia accident by NASA and the Space Shuttle prime contractor, United Space Alliance, LLC. A technique was needed to understand the rules, or procedural controls, in place at the time in the context of how important the role of each rule was. The proposed method assesses procedural risks, the residual risk associated with a hazard after a procedure's influence is accounted for, by considering each clause of a procedure as a unique procedural control that may be beneficial or harmful. For procedural risks with consequences severe enough to threaten the survival of the organization, the method measures the characteristics of each risk on a scale that is an alternative to the traditional consequence/likelihood couple. The dual benefits of the substitute scales are that they eliminate both the need to quantify a relationship between different consequence types and the need for the extensive history a probabilistic risk assessment would require. Control Value is used as an analog for the consequence, where the value of a rule is based on how well the control reduces the severity of the consequence when operating successfully. This value is composed of two parts: the inevitability of the consequence in the absence of the control, and the opportunity to intervene before the consequence is realized. High value controls will be ones where there is minimal need for intervention but maximum opportunity to actively prevent the outcome. Failure Likelihood is used as the substitute for the conventional likelihood of the outcome. For procedural controls, a failure is considered to be any non-malicious violation of the rule, whether intended or not. The model used for describing the Failure Likelihood considers how well a task was established by evaluating that task on five components. The components selected to define a well established task are: that it be defined, assigned to someone capable, that they be trained appropriately, that the actions be organized to enable proper completion and that some form of independent monitoring be performed. Validation of the method was based on the information provided by a group of experts in Space Shuttle ground processing when they were presented with 5 scenarios that identified a clause from a procedure. For each scenario, they recorded their perception of how important the associated rule was and how likely it was to fail. They then rated the components of Control Value and Failure Likelihood for all the scenarios. The order in which each reviewer ranked the scenarios Control Value and Failure Likelihood was compared to the order in which they ranked the scenarios for each of the associated components; inevitability and opportunity for Control Value and definition, assignment, training, organization and monitoring for Failure Likelihood. This order comparison showed how the components contributed to a relative relationship to the substitute risk element. With the relationship established for Space Shuttle ground processing, this method can be used to gauge if the introduction or removal of a particular rule will increase or decrease the .risk associated with the hazard it is intended to control.

Praino, Gregory T.↗
NASA NTRS1992

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Moore, N. R.↗
NASA NTRS1992

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 2: Software documentation

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes, These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Moore, N. R.↗
NASA NTRS1992

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 3: Structure and listing of programs

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Moore, N. R.↗
NASA NTRS1992

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 1: Methodology and applications

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for designs failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

Moore, N. R.↗
NASA NTRS1992

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 2: Software documentation

An improved methodology for quantitatively evaluating failure risk of spaceflights systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for design, failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

Moore, N. R.↗
NASA NTRS1986

Cost Risk Analysis Based on Perception of the Engineering Process

In most cost estimating applications at the NASA Langley Research Center (LaRC), it is desirable to present predicted cost as a range of possible costs rather than a single predicted cost. A cost risk analysis generates a range of cost for a project and assigns a probability level to each cost value in the range. Constructing a cost risk curve requires a good estimate of the expected cost of a project. It must also include a good estimate of expected variance of the cost. Many cost risk analyses are based upon an expert's knowledge of the cost of similar projects in the past. In a common scenario, a manager or engineer, asked to estimate the cost of a project in his area of expertise, will gather historical cost data from a similar completed project. The cost of the completed project is adjusted using the perceived technical and economic differences between the two projects. This allows errors from at least three sources. The historical cost data may be in error by some unknown amount. The managers' evaluation of the new project and its similarity to the old project may be in error. The factors used to adjust the cost of the old project may not correctly reflect the differences. Some risk analyses are based on untested hypotheses about the form of the statistical distribution that underlies the distribution of possible cost. The usual problem is not just to come up with an estimate of the cost of a project, but to predict the range of values into which the cost may fall and with what level of confidence the prediction is made. Risk analysis techniques that assume the shape of the underlying cost distribution and derive the risk curve from a single estimate plus and minus some amount usually fail to take into account the actual magnitude of the uncertainty in cost due to technical factors in the project itself. This paper addresses a cost risk method that is based on parametric estimates of the technical factors involved in the project being costed. The engineering process parameters are elicited from the engineer/expert on the project and are based on that expert's technical knowledge. These are converted by a parametric cost model into a cost estimate. The method discussed makes no assumptions about the distribution underlying the distribution of possible costs, and is not tied to the analysis of previous projects, except through the expert calibrations performed by the parametric cost analyst.

Dean, Edwin B.↗
NASA NTRS2005

Shuttle-Derived Launch Vehicles' Capablities: An Overview

Shuttle-Derived Launch Vehicle (SDLV) concepts have been developed by a collaborative team comprising the Johnson Space Center, Marshall Space Flight Center, Kennedy Space Center, ATK-Thiokol, Lockheed Martin Space Systems Company, The Boeing Company, and United Space Alliance. The purpose of this study was to provide timely information on a full spectrum of low-risk, cost-effective options for STS-Derived Launch Vehicle concepts to support the definition of crew and cargo launch requirements for the Space Exploration Vision. Since the SDLV options use high-reliability hardware, existing facilities, and proven processes, they can provide relatively low-risk capabilities to launch extremely large payloads to low Earth orbit. This capability to reliably lift very large, high-dollar-value payloads could reduce mission operational risks by minimizing the number of complex on-orbit operations compared to architectures based on multiple smaller launchers. The SDLV options also offer several logical spiral development paths for larger exploration payloads. All of these development paths make practical and cost-effective use of existing Space Shuttle Program (SSP) hardware, infrastructure, and launch and flight operations systems. By utilizing these existing assets, the SDLV project could support the safe and orderly transition of the current SSP through the planned end of life in 2010. The SDLV concept definition work during 2004 focused on three main configuration alternatives: a side-mount heavy lifter (approximately 77 MT payload), an in-line medium lifter (approximately 22 MT Crew Exploration Vehicle payload), and an in-line heavy lifter (greater than 100 MT payload). This paper provides an overview of the configuration, performance capabilities, reliability estimates, concept of operations, and development plans for each of the various SDLV alternatives. While development, production, and operations costs have been estimated for each of the SDLV configuration alternatives, these proprietary data have not been included in this paper.

Rothschild, William J.↗
NASA NTRS2012

Hazard Analysis for Pneumatic Flipper Suitport/Z-1 Manned Evaluation, Chamber B, Building 32

One of the characteristics of an effective safety program is the recognition and control of hazards before mishaps or failures occur. Conducting potentially hazardous tests necessitates a thorough hazard analysis in order to protect our personnel from injury and our equipment from damage. The purpose of this hazard analysis is to define and address the potential hazards and controls associated with the Z1 Suit Port Test in Chamber B located in building 32, and to provide the applicable team of personnel with the documented results. It is imperative that each member of the team be familiar with the hazards and controls associated with his/her particular tasks, assignments, and activities while interfacing with facility test systems, equipment, and hardware. The goal of this hazard analysis is to identify all hazards that have the potential to harm personnel and/or damage facility equipment, flight hardware, property, or harm the environment. This analysis may also assess the significance and risk, when applicable, of lost test objectives when substantial monetary value is involved. The hazards, causes, controls, verifications, and risk assessment codes have been documented on the hazard analysis work sheets in appendix A of this document. The preparation and development of this report is in accordance with JPR 1700.1, JSC Safety and Health Handbook.

Source record↗
NASA NTRS2014

Hazard Analysis for Building 34 Vacuum Glove Box Assembly

One of the characteristics of an effective safety program is the recognition and control of hazards before mishaps or failures occur. Conducting potentially hazardous tests necessitates a thorough hazard analysis in order to prevent injury to personnel, and to prevent damage to facilities and equipment. The primary purpose of this hazard analysis is to define and address the potential hazards and controls associated with the Building 34 Vacuum Glove Box Assembly, and to provide the applicable team of personnel with the documented results. It is imperative that each member of the team be familiar with the hazards and controls associated with his/her particular tasks, assignments and activities while interfacing with facility test systems, equipment and hardware. In fulfillment of the stated purposes, the goal of this hazard analysis is to identify all hazards that have the potential to harm personnel, damage the facility or its test systems or equipment, test articles, Government or personal property, or the environment. This analysis may also assess the significance and risk, when applicable, of lost test objectives when substantial monetary value is involved. The hazards, causes, controls, verifications, and risk assessment codes have been documented on the hazard analysis work sheets in Appendix A of this document. The preparation and development of this report is in accordance with JPR 1700.1, "JSC Safety and Health Handbook" and JSC 17773 Rev D "Instructions for Preparation of Hazard Analysis for JSC Ground Operations".

Meginnis, Ian↗
NASA NTRS2016

Tailoring a Human Reliability Analysis to Your Industry Needs

Companies at risk of accidents caused by human error that result in catastrophic consequences include: airline industry mishaps, medical malpractice, medication mistakes, aerospace failures, major oil spills, transportation mishaps, power production failures and manufacturing facility incidents. Human Reliability Assessment (HRA) is used to analyze the inherent risk of human behavior or actions introducing errors into the operation of a system or process. These assessments can be used to identify where errors are most likely to arise and the potential risks involved if they do occur. Using the basic concepts of HRA, an evolving group of methodologies are used to meet various industry needs. Determining which methodology or combination of techniques will provide a quality human reliability assessment is a key element to developing effective strategies for understanding and dealing with risks caused by human errors. There are a number of concerns and difficulties in "tailoring" a Human Reliability Assessment (HRA) for different industries. Although a variety of HRA methodologies are available to analyze human error events, determining the most appropriate tools to provide the most useful results can depend on industry specific cultures and requirements. Methodology selection may be based on a variety of factors that include: 1) how people act and react in different industries, 2) expectations based on industry standards, 3) factors that influence how the human errors could occur such as tasks, tools, environment, workplace, support, training and procedure, 4) type and availability of data, 5) how the industry views risk & reliability, and 6) types of emergencies, contingencies and routine tasks. Other considerations for methodology selection should be based on what information is needed from the assessment. If the principal concern is determination of the primary risk factors contributing to the potential human error, a more detailed analysis method may be employed versus a requirement to provide a numerical value as part of a probabilistic risk assessment. Industries involved with humans operating large equipment or transport systems (ex. railroads or airlines) would have more need to address the man machine interface than medical workers administering medications. Human error occurs in every industry; in most cases the consequences are relatively benign and occasionally beneficial. In cases where the results can have disastrous consequences, the use of Human Reliability techniques to identify and classify the risk of human errors allows a company more opportunities to mitigate or eliminate these types of risks and prevent costly tragedies.

DeMott, D. L.↗
NASA NTRS2003

Schedule Risk Assessment

Schedule risk assessments determine the likelihood of finishing on time. Each task in a schedule has a varying degree of probability of being finished on time. A schedule risk assessment quantifies these probabilities by assigning values to each task. This viewgraph presentation contains a flow chart for conducting a schedule risk assessment, and profiles applicable several methods of data analysis.

Smith, Greg↗