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At least 73 records · Page 4

Application of Probabilistic Methods to Assess Risk Due to Resonance in the Design of J-2X Rocket Engine Turbine Blades

The LOX-Hydrogen J-2X Rocket Engine, which is proposed for use as an upper-stage engine for numerous earth-to-orbit and heavy lift launch vehicle architectures, is presently in the design phase and will move shortly to the initial development test phase. Analysis of the design has revealed numerous potential resonance issues with hardware in the turbomachinery turbine-side flow-path. The analysis of the fuel pump turbine blades requires particular care because resonant failure of the blades, which are rotating in excess of 30,000 revolutions/minutes (RPM), could be catastrophic for the engine and the entire launch vehicle. This paper describes a series of probabilistic analyses performed to assess the risk of failure of the turbine blades due to resonant vibration during past and present test series. Some significant results are that the probability of failure during a single complete engine hot-fire test is low (~1%) because of the small likelihood of resonance, but that the probability increases to around 30% for a more focused turbomachinery-only test because all speeds will be ramped through and there is a greater likelihood of dwelling at more speeds. These risk calculations have been invaluable for use by program management in deciding if risk-reduction methods such as dampers are necessary immediately or if the test can be performed before the risk-reduction hardware is ready.

Brown, Andrew M.↗

Risk management for the Space Exploration Initiative

Probabilistic Risk Assessment (PRA) is a quantitative engineering process that provides the analytic structure and decision-making framework for total programmatic risk management. Ideally, it is initiated in the conceptual design phase and used throughout the program life cycle. Although PRA was developed for assessment of safety, reliability, and availability risk, it has far greater application. Throughout the design phase, PRA can guide trade-off studies among system performance, safety, reliability, cost, and schedule. These studies are based on the assessment of the risk of meeting each parameter goal, with full consideration of the uncertainties. Quantitative trade-off studies are essential, but without full identification, propagation, and display of uncertainties, poor decisions may result. PRA also can focus attention on risk drivers in situations where risk is too high. For example, if safety risk is unacceptable, the PRA prioritizes the risk contributors to guide the use of resources for risk mitigation. PRA is used in the Space Exploration Initiative (SEI) Program. To meet the stringent requirements of the SEI mission, within strict budgetary constraints, the PRA structure supports informed and traceable decision-making. This paper briefly describes the SEI PRA process.

Buchbinder, Ben↗

Failure environment analysis tool applications

Understanding risks and avoiding failure are daily concerns for the women and men of NASA. Although NASA's mission propels us to push the limits of technology, and though the risks are considerable, the NASA community has instilled within, the determination to preserve the integrity of the systems upon which our mission and, our employees lives and well-being depend. One of the ways this is being done is by expanding and improving the tools used to perform risk assessment. The Failure Environment Analysis Tool (FEAT) was developed to help engineers and analysts more thoroughly and reliably conduct risk assessment and failure analysis. FEAT accomplishes this by providing answers to questions regarding what might have caused a particular failure; or, conversely, what effect the occurrence of a failure might have on an entire system. Additionally, FEAT can determine what common causes could have resulted in other combinations of failures. FEAT will even help determine the vulnerability of a system to failures, in light of reduced capability. FEAT also is useful in training personnel who must develop an understanding of particular systems. FEAT facilitates training on system behavior, by providing an automated environment in which to conduct 'what-if' evaluation. These types of analyses make FEAT a valuable tool for engineers and operations personnel in the design, analysis, and operation of NASA space systems.

Pack, Ginger L.↗

Failure environment analysis tool applications

Understanding risks and avoiding failure are daily concerns for the women and men of NASA. Although NASA's mission propels us to push the limits of technology, and though the risks are considerable, the NASA community has instilled within it, the determination to preserve the integrity of the systems upon which our mission and, our employees lives and well-being depend. One of the ways this is being done is by expanding and improving the tools used to perform risk assessment. The Failure Environment Analysis Tool (FEAT) was developed to help engineers and analysts more thoroughly and reliably conduct risk assessment and failure analysis. FEAT accomplishes this by providing answers to questions regarding what might have caused a particular failure; or, conversely, what effect the occurrence of a failure might have on an entire system. Additionally, FEAT can determine what common causes could have resulted in other combinations of failures. FEAT will even help determine the vulnerability of a system to failures, in light of reduced capability. FEAT also is useful in training personnel who must develop an understanding of particular systems. FEAT facilitates training on system behavior, by providing an automated environment in which to conduct 'what-if' evaluation. These types of analyses make FEAT a valuable tool for engineers and operations personnel in the design, analysis, and operation of NASA space systems.

Pack, Ginger L.↗

Bridging the Engineering and Medicine Gap

A primary challenge NASA faces is communication between the disparate entities of engineers and human system experts in life sciences. Clear communication is critical for exploration mission success from the perspective of both risk analysis and data handling. The engineering community uses probabilistic risk assessment (PRA) models to inform their own risk analysis and has extensive experience managing mission data, but does not always fully consider human systems integration (HSI). The medical community, as a part of HSI, has been working 1) to develop a suite of tools to express medical risk in quantitative terms that are relatable to the engineering approaches commonly in use, and 2) to manage and integrate HSI data with engineering data. This talk will review the development of the Integrated Medical Model as an early attempt to bridge the communication gap between the medical and engineering communities in the language of PRA. This will also address data communication between the two entities in the context of data management considerations of the Medical Data Architecture. Lessons learned from these processes will help identify important elements to consider in future communication and integration of these two groups.

Walton, M.↗

Analysis of the Honeywell Uncertified Research Engine with Ice Crystal Cloud Ingestion at Simulated Altitudes

The Honeywell Uncertified Research Engine (HURE), a research version of a turbofan engine that never entered production, was tested in the NASA Propulsion System Laboratory (PSL), an altitude test facility at the NASA Glenn Research Center. The PSL is a facility that is equipped with water spray bars capable of producing an ice cloud consisting of ice particles, having a controlled particle diameter and concentration in the air flow. To develop the test matrix of the HURE, numerical analysis of flow and ice particle thermodynamics was performed on the compression system of the turbofan engine to predict operating conditions that could potentially result in a risk of ice accretion due to ice crystal ingestion. The goal of the test matrix was to provide operating conditions such that ice would accrete in either the fan-stator through the inlet guide vane region of the compression system or within the first stator of the high pressure compressor. The predictive analyses were performed with the mean line compressor flow modeling code (COMDESMELT) which includes an ice particle model. The HURE engine was tested in PSL with the ice cloud over the range of operating conditions of altitude, ambient temperature, simulated flight Mach number, and fan speed with guidance from the analytical predictions. The engine was fitted with video cameras at strategic locations within the engine compression system flow path where ice was predicted to accrete, in order to visually confirm ice accretion when it occurred. In addition, traditional compressor instrumentation such as total pressure and temperature probes, static pressure taps, and metal temperature thermocouples were installed in targeted areas where the risk of ice accretion was expected. The current research focuses on the analysis of the data that was obtained after testing the HURE engine in PSL with ice crystal ingestion. The computational method (COMDES-MELT) was enhanced by computing key parameters through the fan-stator at multiple span wise locations, in order to increase the fidelity with the current mean-line method. The Icing Wedge static wet-bulb temperature thresholds were applied for determining the risk of ice accretion in the fan-stator, which is thought to be an adiabatic region. At some operating conditions near the splitter-lip region, other sources of heat (non-adiabatic walls) were suspected to be the cause of accretion, and the Icing Wedge was not applied to predict accretion at that location. A simple order-of-magnitude heat transfer model was implemented into the COMDES-MELT code to estimate the wall temperature minimum and maximum thresholds that support ice accretion, as observed by video confirmation. The results from this model spanned the range of wall temperatures measured on a previous engine that experienced ice accretion at certain operating conditions. The goal of this study is to show that the computational process developed on earlier engine icing tests can be used to provide an icing risk assessment in adiabatic regions for other engines.

Turbofan engine↗

Safe Human Expeditions Beyond Low Earth Orbit (LEO)

The NASA Engineering and Safety Center (NESC) conducted an interdisciplinary study and workshop focusing on capabilities needed for crew health and safety on long-duration deep space expeditions in support of the Artemis Program and missions to Mars. The study focused on integration among four disciplines: 1) space weather monitoring and forecasting, 2) shielding technologies, 3) human health research, and 4) human factors engineering tools. An integrated risk assessment was performed to inform characteristics of mission architecture and capabilities needed for safe, long-duration human expeditions beyond low Earth orbit. This report contains the outcome of the NESC assessment.

Low Earth Orbit↗

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.↗

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.↗

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.↗

An Example of Risk Informed Design

NASA Engineering requested a Probabilistic Risk Assessment (PRA) to compare the difference in the risk of Loss of Crew (LOC) and Loss of Mission (LOM) between different designs of a fluid assembly. They were concerned that the configuration favored by the design team was more susceptible to leakage than a second proposed design, but realized that a quantitative analysis to compare the risks between the two designs might strengthen their argument. The analysis showed that while the second design did help improve the probability of LOC, it did not help from a probability of LOM perspective. This drove the analysis team to propose a minor design change that would drive the probability of LOM down considerably. The analysis also demonstrated that there was another major risk driver that was not immediately obvious from a typical engineering study of the design and was therefore unexpected. None of the proposed alternatives were addressing this risk. This type of trade study demonstrates the importance of performing a PRA in order to completely understand a system's design. It allows managers to use risk as another one of the commodities (e.g., mass, cost, schedule, fault tolerance) that can be traded early in the design of a new system.

Banke, Rick↗

Humans vs Hardware: The Unique World of NASA Human System Risk Assessment

Understanding spaceflight risks to crew health and performance is a crucial aspect of preparing for exploration missions in the future. The research activities of the Human Research Program (HRP) provide substantial evidence to support most risk reduction work. The Human System Risk Board (HSRB), acting on behalf of the Office of Chief Health and Medical Officer (OCHMO), assesses these risks and assigns likelihood and consequence ratings to track progress. Unfortunately, many traditional approaches in risk assessment such as those used in the engineering aspects of spaceflight are difficult to apply to human system risks. This presentation discusses the unique aspects of risk assessment from the human system risk perspective and how these limitations are accommodated and addressed in order to ensure that reasonable inputs are provided to support the OCHMO's overall risk posture for manned exploration missions.

Anton, W.↗

International Space Station (ISS) Orbital Replaceable Unit (ORU) Wet Storage Risk Assessment

The International Space Station (ISS) Program requested the NASA Engineering and Safety Center (NESC) to evaluate the risks posed by the practice of long-term wet storage of ISS Environmental Control and Life Support (ECLS) regeneration system orbital replacement units (ORUs). The ISS ECLS regeneration system removes water from urine and humidity condensate and converts it into potable water and oxygen. A total of 29 ORUs are in the ECLS system, each designed to be replaced by the ISS crew when necessary. The NESC assembled a team to review the ISS ECLS regeneration system and evaluate the potential for biofouling and corrosion. This document contains the outcome of the evaluation.

Squire, Michael D.↗

NSTS Orbiter auxiliary power unit turbine wheel cracking risk assessment

The present investigation of turbine-wheel cracking problems in the hydrazine-fueled APU turbine wheel of the Space Shuttle Orbiter's Main Engines has indicated the efficacy of systematic probabilistic risk assessment in flight certification and safety resolution. Nevertheless, real crack-initiation and propagation problems do not lend themselves to purely analytical studies. The high-cycle fatigue problem is noted to generally be unsuited to probabilistic modeling, due to its extremely high degree of intrinsic scatter. In the case treated, the cracks appear to trend toward crack arrest in a low cycle fatigue mode, due to a detuning of the resonance model.

Cruse, T. A.↗

An Integrated Approach to Risk Assessment for Concurrent Design

This paper describes an approach to risk assessment and analysis suited to the early phase, concurrent design of a space mission. The approach integrates an agile, multi-user risk collection tool, a more in-depth risk analysis tool, and repositories of risk information. A JPL developed tool, named RAP, is used for collecting expert opinions about risk from designers involved in the concurrent design of a space mission. Another in-house developed risk assessment tool, named DDP, is used for the analysis.

defect detection and prevention (DDP)↗

Probabilistic/Fracture-Mechanics Model For Service Life

Computer program makes probabilistic estimates of lifetime of engine and components thereof. Developed to fill need for more accurate life-assessment technique that avoids errors in estimated lives and provides for statistical assessment of levels of risk created by engineering decisions in designing system. Implements mathematical model combining techniques of statistics, fatigue, fracture mechanics, nondestructive analysis, life-cycle cost analysis, and management of engine parts. Used to investigate effects of such engine-component life-controlling parameters as return-to-service intervals, stresses, capabilities for nondestructive evaluation, and qualities of materials.

Watkins, T., Jr.↗

A Model to Assess the Risk of Ice Accretion Due to Ice Crystal Ingestion in a Turbofan Engine and its Effects on Performance

The occurrence of ice accretion within commercial high bypass aircraft turbine engines has been reported under certain atmospheric conditions. Engine anomalies have taken place at high altitudes that were attributed to ice crystal ingestion, partially melting, and ice accretion on the compression system components. The result was one or more of the following anomalies: degraded engine performance, engine roll back, compressor surge and stall, and flameout of the combustor. The main focus of this research is the development of a computational tool that can estimate whether there is a risk of ice accretion by tracking key parameters through the compression system blade rows at all engine operating points within the flight trajectory. The tool has an engine system thermodynamic cycle code, coupled with a compressor flow analysis code, and an ice particle melt code that has the capability of determining the rate of sublimation, melting, and evaporation through the compressor blade rows. Assumptions are made to predict the complex physics involved in engine icing. Specifically, the code does not directly estimate ice accretion and does not have models for particle breakup or erosion. Two key parameters have been suggested as conditions that must be met at the same location for ice accretion to occur: the local wet-bulb temperature to be near freezing or below and the local melt ratio must be above 10%. These parameters were deduced from analyzing laboratory icing test data and are the criteria used to predict the possibility of ice accretion within an engine including the specific blade row where it could occur. Once the possibility of accretion is determined from these parameters, the degree of blockage due to ice accretion on the local stator vane can be estimated from an empirical model of ice growth rate and time spent at that operating point in the flight trajectory. The computational tool can be used to assess specific turbine engines to their susceptibility to ice accretion in an ice crystal environment.

Jorgenson, Philip C. E.↗

Simulation of Liquid Rocket Engine Failure Propagation Using Self-Evolving Scenarios

Traditional probabilistic risk assessment approaches often require failure scenarios to be explicitly defined through event sequences that are then quantified as part of the integrated analysis. This approach becomes difficult when failure propagation paths change as a function of the system operation. Additionally, if the propagation paths represent interactions among even a modest number of components, the scenario count becomes combinatorially intractable. This paper presents an alternate approach for quantifying the probability of failure propagation in such a case. Rather than explicitly defining scenario sequences, simple physical models are created for each of the components. In this way, only the physical states and rules of component interactions must be defined, rather than event sequences for each individual scenario. Initiating failures are introduced into the system, either randomly or as defined by relative likelihood, and the failures cascade through the system via the interaction rules. This process is repeated using Monte Carlo methods and, as a result, the most probable scenarios “self-evolve” in terms of both sequence path and frequency. This approach was applied to failures occurring in the engine compartment of a space launch vehicle with four liquid rocket engines and four high-pressure helium tanks. Each engine was modeled with key components, such as turbomachinery, combustion chamber, propellant lines, and additional support systems. Three test cases were conducted with different high-energy engine failures. End results of interest included an additional engine-out failure and tank burst, which represent the loss-of-mission (LOM) and loss-of-crew (LOC) failure environments, respectively. Observations show that almost every scenario outcome is unique and that many scenarios involve complex chain reactions that are difficult to predict. This validates the usefulness of the modeling approach in assessing the overall risks to the crew during a launch vehicle abort.

Rocket Engine↗