PSAM 16 - Session T21 Overview

PSAM 16 Conference Session T21 Overview

Session Chair: Lukasz Sokolowski (lukasz.sokolowski@kiwa.com)

Paper 1 NA280

Lead Author: Nancy Lindsey Co-author(s): Jeff Dawson, jeffrey.w.dawson@nasa.gov Doug Sheldon, douglas.j.sheldon@jpl.nasa.gov Anthony DiVenti, anthony.j.diventi@nasa.gov Lionel Sindjui, lionel-nobel.w.sindjui@nasa.gov

NASA Physics of Failure (PoF) for Reliability
NASA Physics of Failure (PoF) for Reliability Authors: Nancy Lindsey, Jeff Dawson, Doug Sheldon, Anthony DiVenti, Lionel Sindjui Abstract: An item’s reliability or longevity is dependent not only on its design but also on how it is used, manufactured, tested, and the stresses it has or will experience. Stresses include operational and environmental exposures to thermal, voltage, current, age/exposure, mechanical, and radiation mechanisms. Therefore, in reliability analysis, it is important to consider the contributions of all of these factors when predicting the failure rates of components. Historically, there has been a reliance on handbook data (e.g., MIL-HDBK-217), but experience has shown that these values and distributions are not representative of actual performance (1,2). Therefore, to make more credible reliability and risk assessments for its missions, NASA must transition to estimating likelihoods of failure based on an item’s reliability/longevity factors (or the physical susceptibilities and strengths impacting the design’s performance) has or will experience, whenever possible. To facilitate this transition a “Handbook on Methodology for Physics of Failure Based Reliability Assessments” has been developed by NASA to assist in applying physics experiences or experiment physics for empirical analysis and conceptualized physics exposures or theoretical physics for deterministic analysis, to develop and aggregate realistic likelihoods of failure leading to more credible forecasts of item performance and longevity. In addition, since it is NASA’s intention that this document continues to evolve based on community lessons learned and the introduction of new assessment methodologies, NASA is encouraging and appreciates the contributions of current and future authors to maintain and enhance this handbook and its supporting case studies. References: 1) REF MIL-HDBK-217 Secretary of the Army Memo, 1996 2) SCiTech - EXPL-09/NASA Webinar, Reliability of Systems for Long Duration Missions, 2021

NASA Physics of Failure (PoF) for Reliability

NASA Physics of Failure (PoF) for Reliability Authors: Nancy Lindsey, Jeff Dawson, Doug Sheldon, Anthony DiVenti, Lionel Sindjui Abstract: An item’s reliability or longevity is dependent not only on its design but also on how it is used, manufactured, tested, and the stresses it has or will experience. Stresses include operational and environmental exposures to thermal, voltage, current, age/exposure, mechanical, and radiation mechanisms. Therefore, in reliability analysis, it is important to consider the contributions of all of these factors when predicting the failure rates of components. Historically, there has been a reliance on handbook data (e.g., MIL-HDBK-217), but experience has shown that these values and distributions are not representative of actual performance (1,2). Therefore, to make more credible reliability and risk assessments for its missions, NASA must transition to estimating likelihoods of failure based on an item’s reliability/longevity factors (or the physical susceptibilities and strengths impacting the design’s performance) has or will experience, whenever possible. To facilitate this transition a “Handbook on Methodology for Physics of Failure Based Reliability Assessments” has been developed by NASA to assist in applying physics experiences or experiment physics for empirical analysis and conceptualized physics exposures or theoretical physics for deterministic analysis, to develop and aggregate realistic likelihoods of failure leading to more credible forecasts of item performance and longevity. In addition, since it is NASA’s intention that this document continues to evolve based on community lessons learned and the introduction of new assessment methodologies, NASA is encouraging and appreciates the contributions of current and future authors to maintain and enhance this handbook and its supporting case studies. References: 1) REF MIL-HDBK-217 Secretary of the Army Memo, 1996 2) SCiTech - EXPL-09/NASA Webinar, Reliability of Systems for Long Duration Missions, 2021

Paper NA280 | Download the paper file. | Download the presentation PowerPoint file.

Name: Nancy Lindsey (nancy.j.lindsey@nasa.gov)

Bio: Nancy J Lindsey has spent 37+ years in aviation and aerospace engineering performing a variety of Systems and Mission Assurance engineering tasks across the entire gamut of space vehicle life cycles and program types including Defense & Commercial Communications Missions, Space-based Astronomical Observatories, Ground Systems, and Earth Science Monitoring Systems with national/international partners. She is now the Reliability, Maintainability, and Availability subject matter expert at NASA's Goddard Space Flight Center and the deputy Reliability & Maintainability Technical Fellow at NASA Headquarters. Mrs. Lindsey has a Bachelor of Science degree in Computer Science & Aeronautical Engineering from Embry-Riddle Aero. University in Daytona Beach, Florida, was trained in Flight Medicine and F-14 flight by the US Navy, and has a Master’s of Science degree in Space Studies, from the University of North Dakota. Nancy’s independent research efforts can be viewed via website: www.rcktmom.com.

Country: USA
Company: NASA HQ/GSFC
Job Title: Deputy R&M Technical Fellow (OSMA) & GSFC Reliability, Maintainability, and

Paper 2 SC287

Lead Author: Scott Lawrence Co-author(s): Susie Go, susie.go@nasa.gov Scott Lawrence, scott.l.lawrence@nasa.gov Amir Levine, amir.levine02.gmail.com

Failure Propagation Simulation for Launch Vehicle Safety Estimates
Abstract An important component in the assessment of launch vehicle safety is the estimation of the likelihood of a large-scale explosion given the existence of a failure that manifests as a relatively localized energy release. Here, a model for simulating cascading failures of energetic components in proximity, where the primary modes of energy transfer are fragments/shrapnel and blast overpressure, is presented. This model is an extension of the model developed by Mathias and Motiwala (2015) [REF1] with enhancements that include the effects of fragment ricochet, fragment drag, ballistic limit equation fragment thresholds, and blast impulse thresholds. A series of sensitivity studies have been carried out for a generic launch vehicle engine section and results are presented that illustrate the effects of the model modifications. REF1: Mathias, D., & Motiwala, S. (2015). Simulation of Liquid Rocket Engine Failure Propagation Using Self-Evolving Scenarios. 2015 Annual Reliability and Maintainability Symposium (RAMS 2015) . Palm Harbor, FL: Institute of Electrical and Electronics Engineers ( IEEE ). Model Description The paper provides an overview of the method which has been developed to further the objective of a risk modeling and assessment approach capable of self-generating failure scenarios, removing the need to prescribe failure scenarios a priori. The aim of this paper is to detail the modifications of the model and their effect on overall performance and capability rather than providing quantitative results for a specific use case. The approach begins with a configuration definition, comprised of triangulated surfaces, that defines the component shapes and relative positions within the configuration. Also required are the component design parameters, such as material type, thicknesses, masses, and volumes, which provide the basis for determining the environments produced by failure of the component, as well as the material response to externally generated failure environments. Finally, component failure information that cannot be inferred directly from the component design information must be specified, e.g., the number of fragments produced and the vulnerability to blast overpressure of the component. The simulation begins with the assumed failure of a user-specified component. The failure produces high-speed debris and/or blast overpressure that is propagated to surrounding components. The incident environments (debris field and pressure wave) are compared against the target component failure thresholds to determine the failure status of the target. If failure occurs in the target component, the process is repeated until there are no additional failures observed. Monte Carlo sampling is used to determine the failure probabilities of each of the components in the configuration, given uncertainties in the input parameters. The debris propagation model consists of simple straight-line trajectory segments with ricochet direction changes. The initial imparted velocities are decremented by aerodynamic drag and by the ricochet events. Blast overpressure decay is modeled using a clipped TNT model with stationary wall reflection effects at the target. Failure criteria for debris strike is based on an FAA ballistic limit equation formula which accounts for the target material properties, thickness, and the orientation of the surface relative to the impact trajectory. The blast overpressure failure threshold has been augmented to include a test for the level of integrated impulse in addition to the peak overpressure. Application and Results The model is applied to a generic rocket engine section containing four engines and four composite overwrapped pressure vessels (COPVs). Each engine is comprised of seven components, as shown in Figure 1. A detailed description of the component inputs will be provided. Results are obtained in the form of a sensitivity analyses to variations of the input parameters with the objective of determining the effects of the current model enhancements on the failure probability predictions. The parameters assessed in the sensitivity analysis include: • Initiating component • Number of Monte Carlo samples • Ricochet o Number of ricochets allowed o Coefficient of restitution • Altitude, i.e., ambient pressure and density • Blast overpressure threshold parameters o Peak overpressure o Integrated impulse Results indicate moderate sensitivity to the initiating component. It should be noted that there is a high degree of symmetry in the current application configuration. The propagation appears to be reasonably well characterized using 2000-5000 Monte Carlo samples. The ricochet sensitivity indicates significant effects from the first ricochet and marginal effects from additional ricochets. The addition of the blast impulse threshold is significant, indicating that using a peak overpressure threshold alone will generate overly conservative results, i.e., too many failures. In addition, the peak overpressure threshold plays a significant role at certain altitudes, indicating the need for a reliable method for estimating these threshold parameters as shown in Figure 2. The full paper includes additional details on the method, the test configuration, as well as detailed results of the sensitivity studies.

Failure Propagation Simulation for Launch Vehicle Safety Estimates

Abstract An important component in the assessment of launch vehicle safety is the estimation of the likelihood of a large-scale explosion given the existence of a failure that manifests as a relatively localized energy release. Here, a model for simulating cascading failures of energetic components in proximity, where the primary modes of energy transfer are fragments/shrapnel and blast overpressure, is presented. This model is an extension of the model developed by Mathias and Motiwala (2015) [REF1] with enhancements that include the effects of fragment ricochet, fragment drag, ballistic limit equation fragment thresholds, and blast impulse thresholds. A series of sensitivity studies have been carried out for a generic launch vehicle engine section and results are presented that illustrate the effects of the model modifications. REF1: Mathias, D., & Motiwala, S. (2015). Simulation of Liquid Rocket Engine Failure Propagation Using Self-Evolving Scenarios. 2015 Annual Reliability and Maintainability Symposium (RAMS 2015) . Palm Harbor, FL: Institute of Electrical and Electronics Engineers ( IEEE ). Model Description The paper provides an overview of the method which has been developed to further the objective of a risk modeling and assessment approach capable of self-generating failure scenarios, removing the need to prescribe failure scenarios a priori. The aim of this paper is to detail the modifications of the model and their effect on overall performance and capability rather than providing quantitative results for a specific use case. The approach begins with a configuration definition, comprised of triangulated surfaces, that defines the component shapes and relative positions within the configuration. Also required are the component design parameters, such as material type, thicknesses, masses, and volumes, which provide the basis for determining the environments produced by failure of the component, as well as the material response to externally generated failure environments. Finally, component failure information that cannot be inferred directly from the component design information must be specified, e.g., the number of fragments produced and the vulnerability to blast overpressure of the component. The simulation begins with the assumed failure of a user-specified component. The failure produces high-speed debris and/or blast overpressure that is propagated to surrounding components. The incident environments (debris field and pressure wave) are compared against the target component failure thresholds to determine the failure status of the target. If failure occurs in the target component, the process is repeated until there are no additional failures observed. Monte Carlo sampling is used to determine the failure probabilities of each of the components in the configuration, given uncertainties in the input parameters. The debris propagation model consists of simple straight-line trajectory segments with ricochet direction changes. The initial imparted velocities are decremented by aerodynamic drag and by the ricochet events. Blast overpressure decay is modeled using a clipped TNT model with stationary wall reflection effects at the target. Failure criteria for debris strike is based on an FAA ballistic limit equation formula which accounts for the target material properties, thickness, and the orientation of the surface relative to the impact trajectory. The blast overpressure failure threshold has been augmented to include a test for the level of integrated impulse in addition to the peak overpressure. Application and Results The model is applied to a generic rocket engine section containing four engines and four composite overwrapped pressure vessels (COPVs). Each engine is comprised of seven components, as shown in Figure 1. A detailed description of the component inputs will be provided. Results are obtained in the form of a sensitivity analyses to variations of the input parameters with the objective of determining the effects of the current model enhancements on the failure probability predictions. The parameters assessed in the sensitivity analysis include: • Initiating component • Number of Monte Carlo samples • Ricochet o Number of ricochets allowed o Coefficient of restitution • Altitude, i.e., ambient pressure and density • Blast overpressure threshold parameters o Peak overpressure o Integrated impulse Results indicate moderate sensitivity to the initiating component. It should be noted that there is a high degree of symmetry in the current application configuration. The propagation appears to be reasonably well characterized using 2000-5000 Monte Carlo samples. The ricochet sensitivity indicates significant effects from the first ricochet and marginal effects from additional ricochets. The addition of the blast impulse threshold is significant, indicating that using a peak overpressure threshold alone will generate overly conservative results, i.e., too many failures. In addition, the peak overpressure threshold plays a significant role at certain altitudes, indicating the need for a reliable method for estimating these threshold parameters as shown in Figure 2. The full paper includes additional details on the method, the test configuration, as well as detailed results of the sensitivity studies.

Paper SC287 | Download the paper file. | Download the presentation PowerPoint file.

Name: Scott Lawrence (scott.l.lawrence@nasa.gov)

Bio: Scott Lawrence is an aerospace engineer in the Systems Analysis Office at NASA Ames Research Center. Scott began his career at Ames in 1986 working on hypersonic CFD. For the past 15+ years, his focus has been on the application of physics-based modelling and simulation to the estimation of launch vehicle crew risks. Currently, Scott is the Engineering Risk Assessment (ERA) point of contact to the Space Launch System Induced Environments discipline. The ERA group has been responsible for generating estimates of SLS failure consequences in terms of crew safety which is used in the assessment of loss of crew probabilities.

Country: USA
Company: NASA
Job Title: Aerospace Engineer