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At least 289 records · Page 16

Failure Evaluation of Savannah River Site High-Level Waste Evaporator 242-25H - Part II - 17353

The Department of Energy's Savannah River Site evaporators are essential to the site actively managing and reducing its liquid high level waste inventory. Since 1951, a series of dedicated evaporators have reduced the liquid waste inventory from 600 ML (160 Mgal) by about a factor of four. The evaporators predominantly have experienced steam tube bundle failures, due to corrosion or fatigue, within about a decade of entering service. To extend service life, recent evaporators have used nickel-based alloys, such as Alloy G-3 (UNS N06030), and have improved operational controls to prevent corrosion. In spite of this, the 242-25H Evaporator recently developed a slow shell leak (0.4 L/min) after sixteen years. An evaporator shell leak is unique in the site's operating history. Finding and characterizing the leak has been challenging because of conflicting information from leak rate data and the locations of externally visible waste. The approaches used to evaluate possible failure modes are described. Failure modes considered include but are not limited to: pressure, temperature, materials, corrosion, fatigue, erosion, and wear. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Reliability Model for Ni-BaTiO3-Based (BME) Ceramic Capacitors

The evaluation of multilayer ceramic capacitors (MLCCs) with base-metal electrodes (BMEs) for potential NASA space project applications requires an in-depth understanding of their reliability. The reliability of an MLCC is defined as the ability of the dielectric material to retain its insulating properties under stated environmental and operational conditions for a specified period of time t. In this presentation, a general mathematic expression of a reliability model for a BME MLCC is developed and discussed. The reliability model consists of three parts: (1) a statistical distribution that describes the individual variation of properties in a test group of samples (Weibull, log normal, normal, etc.), (2) an acceleration function that describes how a capacitors reliability responds to external stresses such as applied voltage and temperature (All units in the test group should follow the same acceleration function if they share the same failure mode, independent of individual units), and (3) the effect and contribution of the structural and constructional characteristics of a multilayer capacitor device, such as the number of dielectric layers N, dielectric thickness d, average grain size r, and capacitor chip size S. In general, a two-parameter Weibull statistical distribution model is used in the description of a BME capacitors reliability as a function of time. The acceleration function that relates a capacitors reliability to external stresses is dependent on the failure mode. Two failure modes have been identified in BME MLCCs: catastrophic and slow degradation. A catastrophic failure is characterized by a time-accelerating increase in leakage current that is mainly due to existing processing defects (voids, cracks, delamination, etc.), or the extrinsic defects. A slow degradation failure is characterized by a near-linear increase in leakage current against the stress time; this is caused by the electromigration of oxygen vacancies (intrinsic defects). The two identified failure modes follow different acceleration functions. Catastrophic failures follow the traditional power-law relationship to the applied voltage. Slow degradation failures fit well to an exponential law relationship to the applied electrical field. Finally, the impact of capacitor structure on the reliability of BME capacitors is discussed with respect to the number of dielectric layers in an MLCC unit, the number of BaTiO3 grains per dielectric layer, and the chip size of the capacitor device.

reliability↗

Development of STS/Centaur failure probabilities liftoff to Centaur separation

The results of an analysis to determine STS/Centaur catastrophic vehicle response probabilities for the phases of vehicle flight from STS liftoff to Centaur separation from the Orbiter are presented. The analysis considers only category one component failure modes as contributors to the vehicle response mode probabilities. The relevant component failure modes are grouped into one of fourteen categories of potential vehicle behavior. By assigning failure rates to each component, for each of its failure modes, the STS/Centaur vehicle response probabilities in each phase of flight can be calculated. The results of this study will be used in a DOE analysis to ascertain the hazard from carrying a nuclear payload on the STS.

Hudson, J. M.↗

Independent Orbiter Assessment (IOA): Analysis of the purge, vent and drain subsystem

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results corresponding to the Orbiter PV and D (Purge, Vent and Drain) Subsystem hardware. The PV and D Subsystem controls the environment of unpressurized compartments and window cavities, senses hazardous gases, and purges Orbiter/ET Disconnect. The subsystem is divided into six systems: Purge System (controls the environment of unpressurized structural compartments); Vent System (controls the pressure of unpressurized compartments); Drain System (removes water from unpressurized compartments); Hazardous Gas Detection System (HGDS) (monitors hazardous gas concentrations); Window Cavity Conditioning System (WCCS) (maintains clear windows and provides pressure control of the window cavities); and External Tank/Orbiter Disconnect Purge System (prevents cryo-pumping/icing of disconnect hardware). Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode. Four of the sixty-two failure modes analyzed were determined as single failures which could result in the loss of crew or vehicle. A possible loss of mission could result if any of twelve single failures occurred. Two of the criticality 1/1 failures are in the Window Cavity Conditioning System (WCCS) outer window cavity, where leakage and/or restricted flow will cause failure to depressurize/repressurize the window cavity. Two criticality 1/1 failures represent leakage and/or restricted flow in the Orbiter/ET disconnect purge network which prevent cryopumping/icing of disconnect hardware. Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode.

Bynum, M. C., III↗

MO-G-BRE-09: Validating FMEA Against Incident Learning Data: A Study in Stereotactic Body Radiation Therapy

Purpose: Though FMEA (Failure Mode and Effects Analysis) is becoming more widely adopted for risk assessment in radiation therapy, to our knowledge it has never been validated against actual incident learning data. The objective of this study was to perform an FMEA analysis of an SBRT (Stereotactic Body Radiation Therapy) treatment planning process and validate this against data recorded within an incident learning system. Methods: FMEA on the SBRT treatment planning process was carried out by a multidisciplinary group including radiation oncologists, medical physicists, and dosimetrists. Potential failure modes were identified through a systematic review of the workflow process. Failure modes were rated for severity, occurrence, and detectability on a scale of 1 to 10 and RPN (Risk Priority Number) was computed. Failure modes were then compared with historical reports identified as relevant to SBRT planning within a departmental incident learning system that had been active for two years. Differences were identified. Results: FMEA identified 63 failure modes. RPN values for the top 25% of failure modes ranged from 60 to 336. Analysis of the incident learning database identified 33 reported near-miss events related to SBRT planning. FMEA failed to anticipate 13 of these events, among which 3 were registered with severity ratings of severe or critical in the incident learning system. Combining both methods yielded a total of 76 failure modes, and when scored for RPN the 13 events missed by FMEA ranked within the middle half of all failure modes. Conclusion: FMEA, though valuable, is subject to certain limitations, among them the limited ability to anticipate all potential errors for a given process. This FMEA exercise failed to identify a significant number of possible errors (17%). Integration of FMEA with retrospective incident data may be able to render an improved overview of risks within a process.

60 APPLIED LIFE SCIENCES↗

SU-E-T-87: A TG-100 Approach for Quality Improvement of Associated Dosimetry Equipment

Purpose: Dosimetry protocols devote so much time to the discussion of ionization chamber choice, use and performance that is easy to forget about the importance of the associated dosimetry equipment (ADE) in radiation dosimetry - barometer, thermometer, electrometer, phantoms, triaxial cables, etc. Improper use and inaccuracy of these devices may significantly affect the accuracy of radiation dosimetry. The purpose of this study is to evaluate the risk factors in the monthly output dosimetry procedure and recommend corrective actions using a TG-100 approach. Methods: A failure mode and effects analysis (FMEA) of the monthly linac output check procedure was performed to determine which steps and failure modes carried the greatest risk. In addition, a fault tree analysis (FTA) was performed to expand the initial list of failure modes making sure that none were overlooked. After determining the failure modes with the highest risk priority numbers (RPNs), 11 physicists were asked to score corrective actions based on their ease of implementation and potential impact. The results were aggregated into an impact map to determine the implementable corrective actions. Results: Three of the top five failure modes were related to the thermometer and barometer. The two highest RPN-ranked failure modes were related to barometric pressure inaccuracy due to their high lack-of-detectability scores. Six corrective actions were proposed to address barometric pressure inaccuracy, and the survey results found the following two corrective actions to be implementable: 1) send the barometer for recalibration at a calibration laboratory and 2) check the barometer accuracy against the local airport and correct for elevation. Conclusion: An FMEA on monthly output measurements displayed the importance of ADE for accurate radiation dosimetry. When brainstorming for corrective actions, an impact map is helpful for visualizing the overall impact versus the ease of implementation.

07 ISOTOPE AND RADIATION SOURCES↗

Determination of Turbine Blade Life from Engine Field Data

It is probable that no two engine companies determine the life of their engines or their components in the same way or apply the same experience and safety factors to their designs. Knowing the failure mode that is most likely to occur minimizes the amount of uncertainty and simplifies failure and life analysis. Available data regarding failure mode for aircraft engine blades, while favoring low-cycle, thermal-mechanical fatigue (TMF) as the controlling mode of failure, are not definitive. Sixteen high-pressure turbine (HPT) T-1 blade sets were removed from commercial aircraft engines that had been commercially flown by a single airline and inspected for damage. Each set contained 82 blades. The damage was cataloged into three categories related to their mode of failure: (1) TMF, (2) Oxidation/erosion (O/E), and (3) Other. From these field data, the turbine blade life was determined as well as the lives related to individual blade failure modes using Johnson-Weibull analysis. A simplified formula for calculating turbine blade life and reliability was formulated. The L10 blade life was calculated to be 2427 cycles (11 077 hr). The resulting blade life attributed to O/E equaled that attributed to TMF. The category that contributed most to blade failure was Other. If there were no blade failures attributed to O/E and TMF, the overall blade L(sub 10) life would increase approximately 11 to 17 percent.

Zaretsky, Erwin V.↗

Determination of Turbine Blade Life from Engine Field Data

It is probable that no two engine companies determine the life of their engines or their components in the same way or apply the same experience and safety factors to their designs. Knowing the failure mode that is most likely to occur minimizes the amount of uncertainty and simplifies failure and life analysis. Available data regarding failure mode for aircraft engine blades, while favoring low-cycle, thermal mechanical fatigue as the controlling mode of failure, are not definitive. Sixteen high-pressure turbine (HPT) T-1 blade sets were removed from commercial aircraft engines that had been commercially flown by a single airline and inspected for damage. Each set contained 82 blades. The damage was cataloged into three categories related to their mode of failure: (1) Thermal-mechanical fatigue, (2) Oxidation/Erosion, and (3) "Other." From these field data, the turbine blade life was determined as well as the lives related to individual blade failure modes using Johnson-Weibull analysis. A simplified formula for calculating turbine blade life and reliability was formulated. The L(sub 10) blade life was calculated to be 2427 cycles (11 077 hr). The resulting blade life attributed to oxidation/erosion equaled that attributed to thermal-mechanical fatigue. The category that contributed most to blade failure was Other. If there were there no blade failures attributed to oxidation/erosion and thermal-mechanical fatigue, the overall blade L(sub 10) life would increase approximately 11 to 17 percent.

Zaretsky, Erwin V.↗

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Gaining Insights in Loading Events for Wind Turbine Drivetrain Prognostics

Wind energy is one of the largest sources of renewable energy in the world. To further reduce the operations and maintenance (O&M) costs of wind farms, it is essential to be able to accurately pinpoint the root causes of different failure modes of interest. An example of such a failure mode that is not yet fully understood is white etching cracks (WEC). This can cause the bearing lifetime to be reduced to 5–10% of its design value. Multiple hypotheses are available in literature concerning its cause. To be able to validate or disprove these hypotheses, it is essential to have historic high-frequency measurement data (e.g., load and vibration levels) available. In time, this will allow linking to the history of the turbine operating data with failure data. This paper discusses the dynamic loading on the turbine during certain events (e.g., emergency stops, run-ups, and during normal operating conditions). By combining the number of specific events that each turbine has seen with the severity of each event, it becomes possible to assess which turbines are most likely to show signs of damage.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Investigation of Spiral Bevel Gear Condition Indicator Validation Via AC-29-2C Using Damage Progression Tests

This report documents the results of spiral bevel gear rig tests performed under a NASA Space Act Agreement with the Federal Aviation Administration (FAA) to support validation and demonstration of rotorcraft Health and Usage Monitoring Systems (HUMS) for maintenance credits via FAA Advisory Circular (AC) 29-2C, Section MG-15, Airworthiness Approval of Rotorcraft (HUMS) (Ref. 1). The overarching goal of this work was to determine a method to validate condition indicators in the lab that better represent their response to faults in the field. Using existing in-service helicopter HUMS flight data from faulted spiral bevel gears as a "Case Study," to better understand the differences between both systems, and the availability of the NASA Glenn Spiral Bevel Gear Fatigue Rig, a plan was put in place to design, fabricate and test comparable gear sets with comparable failure modes within the constraints of the test rig. The research objectives of the rig tests were to evaluate the capability of detecting gear surface pitting fatigue and other generated failure modes on spiral bevel gear teeth using gear condition indicators currently used in fielded HUMS. Nineteen final design gear sets were tested. Tables were generated for each test, summarizing the failure modes observed on the gear teeth for each test during each inspection interval and color coded based on damage mode per inspection photos. Gear condition indicators (CI) Figure of Merit 4 (FM4), Root Mean Square (RMS), +/- 1 Sideband Index (SI1) and +/- 3 Sideband Index (SI3) were plotted along with rig operational parameters. Statistical tables of the means and standard deviations were calculated within inspection intervals for each CI. As testing progressed, it became clear that certain condition indicators were more sensitive to a specific component and failure mode. These tests were clustered together for further analysis. Maintenance actions during testing were also documented. Correlation coefficients were calculated between each CI, component, damage state and torque. Results found test rig and gear design, type of fault and data acquisition can affect CI performance. Results found FM4, SI1 and SI3 can be used to detect macro pitting on two more gear or pinion teeth as long as it is detected prior to progressing to other components or transitioning to another failure mode. The sensitivity of RMS to system and operational conditions limit its reliability for systems that are not maintained at steady state. Failure modes that occurred due to scuffing or fretting were challenging to detect with current gear diagnostic tools, since the damage is distributed across all the gear and pinion teeth, smearing the impacting signatures typically used to differentiate between a healthy and damaged tooth contact. This is one of three final reports published on the results of this project. In the second report, damage modes experienced in the field will be mapped to the failure modes created in the test rig. The helicopter CI data will then be re-processed with the same analysis techniques applied to spiral bevel rig test data. In the third report, results from the rig and helicopter data analysis will be correlated. Observations, findings and lessons learned using sub-scale rig failure progression tests to validate helicopter gear condition indicators will be presented.

gears↗

Membrane Accelerated Stress Test Development for Polymer Electrolyte Fuel Cell Durability Validated Using Field and Drive Cycle Testing

A combined chemical/mechanical accelerated stress test (AST) was developed for proton exchange membrane (PEM) fuel cells based on relative humidity cycling (RHC) between dry and saturated gases at open circuit voltage (OCV). Membrane degradation and failure were investigated using scanning electron microscopy and small- and wide-angle X-ray scattering. Changes to membrane thickness, hydrophilic domain spacing, and crystallinity were observed to be most similar between field-operated cells and OCV RHC ASTs, where local thinning and divot-type defects are the primary failure modes. While RHC in air also reproduces these failure modes, it is not aggressive enough to differentiate between different membrane types in >1,333 hours (55 days) of testing. Conversely, steady-state OCV tests result in significant ionomer morphology changes and global thinning, which do not replicate field degradation and failure modes. It is inferred that during the OCV RHC AST, the decay of the membrane's mechanical properties is accelerated such that materials can be evaluated in hundreds, instead of thousands, of hours, while replicating the degradation and failure modes of field operation; associated AST protocols are recommended as OCV RHC at 90°C for 500 hours with wet/dry cycle durations of 30s/45s and 2m/2m for automotive and bus operation, respectively.

25 ENERGY STORAGE↗

Failure detection system risk reduction assessment

A process includes determining a probability of a failure mode of a system being analyzed reaching a failure limit as a function of time to failure limit, determining a probability of a mitigation of the failure mode as a function of a time to failure limit, and quantifying a risk reduction based on the probability of the failure mode reaching the failure limit and the probability of the mitigation.

Aguilar, Robert B.↗

Analytical technique permits comparison of reliability of alternate mechanical designs

Failure Rate Index analysis permits comparison of reliability of alternate mechanical designs. All failure modes for a mechanical component are identified, and computed on an index which relates the failure mode to failure of the component. The summation of all failure mode indexes relates the potential reliability of the component.

Henning, F. W.↗

Mechanically fastened joints in woven fabric composites

Strength analysis for composite bolted joints involves the mating of a stress analysis with an appropriate mode specific failure criterion for each of the primary failure modes. The stress analysis and failure criteria are independent of each other and can be manipulated separately in order to optimize the strength analysis package formed by their coupling. Material properties tests were conducted on rubber toughened graphite-epoxy material to measure the basic strength and stiffness in the warp and fill directions and in shear. Test matrices are summarized for investigations of laminate configuration, stacking sequence, fastener diameter, edge distance, fastener half spacing, laminate thickness, and fastener torque. A three dimensional finite element analysis computer program was written and failure criteria for net tension, shearout, and bearing were determined.

Wilson, D. W.↗

Assessment of Cladding-Cladding Delamination Failures in U-Mo Fuel Plates

Monolithic fuel is a candidate fuel form for the conversion of high-performance research reactors. This plate-type fuel consists of a high-density, U-Mo alloy-based fuel in a monolithic form that is sandwiched between zirconium diffusion barriers and encapsulated in an aluminum cladding. To qualify this fuel system, the program must demonstrate that the fuel meets the safety standards, has a predictable behavior, and performs well in a reactor. Although many plates have shown satisfactory thermo-mechanical performance in reactor, a small number of experimental plates exhibited failures, rendering performance of these plates unacceptable. Post-irradiation examinations of failed plates have revealed that various failures modes are present, including pillowing, blistering, buckling, warping, delamination, fracture, rupture, oxide spallation, etc. Previous studies have implied that such various operational and loading conditions could generate a complex stress-strain state, facilitating distinct failure modes that could impact the structural integrity. To understand such various failure modes, a comprehensive set of studies focusing on failure modes is being performed. As a part of these studies, this work studies the cladding-cladding separation failures that were observed in some of previous irradiation tests. To understand the root cause of cladding separation failures, selected plates from previous irradiation experiments were simulated under comparable operational conditions. Stress-strain state of the plates at the interface were examined. The results were comparatively evaluated to understand possible effects of stress state of the bond-line on delamination failures. This paper presents these findings, discusses such failure modes, and examines the influence of various factors on previously observed cladding delamination failures.

42 ENGINEERING↗

Instrumentation Cables Test Plan

A fire at a nuclear power plant (NPP) has the potential to damage structures, systems, and components important to safety, if not promptly detected and suppressed. At Browns Ferry Nuclear Power Plant on March 22, 1975, a fire in the reactor building damaged electrical power and control systems. Damage to instrumentation cables impeded the function of both normal and standby reactor coolant systems, and degraded the operators’ plant monitoring capability. This event resulted in additional NRC involvement with utilities to ensure that NPPs are properly protected from fire as intended by the NRC principle design criteria (i.e., general design criteria 3, Fire Protection). Current guidance and methods for both deterministic and performance based approaches typically make conservative (bounding) assumptions regarding the fire-induced failure modes of instrumentation cables and those failure modes effects on component and system response. Numerous fire testing programs have been conducted in the past to evaluate the failure modes and effects of electrical cables exposed to severe thermal conditions. However, that testing has primarily focused on control circuits with only a limited number of tests performed on instrumentation circuits. In 2001, the Nuclear Energy Institute (NEI) and the Electric Power Research Institute (EPRI) conducted a series of cable fire tests designed to address specific aspects of the cable failure and circuit fault issues of concern1. The NRC was invited to observe and participate in that program. The NRC sponsored Sandia National Laboratories to support this participation, whom among other things, added a 4-20 mA instrumentation circuit and instrumentation cabling to six of the tests. Although limited, one insight drawn from those instrumentation circuits tests was that the failure characteristics appeared to depend on the cable insulation material. The results showed that for thermoset insulated cables, the instrument reading tended to drift and fluctuate, while the thermoplastic insulated cables, the instrument reading fell off-scale rapidly. From an operational point of view, the latter failure characteristics would likely be identified as a failure from the effects of fire, while the former may result in inaccurate readings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Independent Orbiter Assessment (IOA): Analysis of the electrical power distribution and control subsystem, volume 1

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results corresponding to the Orbiter Electrical Power Distribution and Control (EPD and C) hardware. The EPD and C hardware performs the functions of distributing, sensing, and controlling 28 volt DC power and of inverting, distributing, sensing, and controlling 117 volt 400 Hz AC power to all Orbiter subsystems from the three fuel cells in the Electrical Power Generation (EPG) subsystem. Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode. Of the 1671 failure modes analyzed, 9 single failures were determined to result in loss of crew or vehicle. Three single failures unique to intact abort were determined to result in possible loss of the crew or vehicle. A possible loss of mission could result if any of 136 single failures occurred. Six of the criticality 1/1 failures are in two rotary and two pushbutton switches that control External Tank and Solid Rocket Booster separation. The other 6 criticality 1/1 failures are fuses, one each per Aft Power Control Assembly (APCA) 4, 5, and 6 and one each per Forward Power Control Assembly (FPCA) 1, 2, and 3, that supply power to certain Main Propulsion System (MPS) valves and Forward Reaction Control System (RCS) circuits.

Schmeckpeper, K. R.↗