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Ring, Robert W.

Publications and source records attributed to Ring, Robert W..

Lognormal Uncertainty Estimation for Failure Rates

"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain. Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This presentation will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

Britton, Paul T.↗

Uncertainty Estimation Cheat Sheet for Probabilistic Risk Assessment

"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This paper will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

Britton, Paul T.↗

Source Data Applicability Impacts on Epistemic Uncertainty for Launch Vehicle Fault Tree Models

Launch vehicle systems are designed and developed using both heritage and new hardware. Design modifications to the heritage hardware to fit new functional system requirements can impact the applicability of heritage reliability data. Risk estimates for newly designed systems must be developed from generic data sources such as commercially available reliability databases using reliability prediction methodologies, such as those addressed in MIL-HDBK-217F. Failure estimates must be converted from the generic environment to the specific operating environment of the system where it is used. In addition, some qualification of applicability for the data source to the current system should be made. Characterizing data applicability under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This paper will demonstrate a data-source applicability classification method for assigning uncertainty to a target vehicle based on the source and operating environment of the originating data. The source applicability is determined using heuristic guidelines while translation of operating environments is accomplished by applying statistical methods to MIL-HDK-217F tables. The paper will provide a case study example by translating Ground Benign (GB) and Ground Mobile (GM) to the Airborne Uninhabited Fighter (AUF) environment for three electronic components often found in space launch vehicle control systems. The classification method will be followed by uncertainty-importance routines to assess the need to for more applicable data to reduce uncertainty.

Al Hassan, Mohammad↗

Reliability and Maintainability Analysis of a High Air Pressure Compressor Facility

This paper discusses a Reliability, Availability, and Maintainability (RAM) independent assessment conducted to support the refurbishment of the Compressor Station at the NASA Langley Research Center (LaRC). The paper discusses the methodologies used by the assessment team to derive the repair by replacement (RR) strategies to improve the reliability and availability of the Compressor Station (Ref.1). This includes a RAPTOR simulation model that was used to generate the statistical data analysis needed to derive a 15-year investment plan to support the refurbishment of the facility. To summarize, study results clearly indicate that the air compressors are well past their design life. The major failures of Compressors indicate that significant latent failure causes are present. Given the occurrence of these high-cost failures following compressor overhauls, future major failures should be anticipated if compressors are not replaced. Given the results from the RR analysis, the study team recommended a compressor replacement strategy. Based on the data analysis, the RR strategy will lead to sustainable operations through significant improvements in reliability, availability, and the probability of meeting the air demand with acceptable investment cost that should translate, in the long run, into major cost savings. For example, the probability of meeting air demand improved from 79.7 percent for the Base Case to 97.3 percent. Expressed in terms of a reduction in the probability of failing to meet demand (1 in 5 days to 1 in 37 days), the improvement is about 700 percent. Similarly, compressor replacement improved the operational availability of the facility from 97.5 percent to 99.8 percent. Expressed in terms of a reduction in system unavailability (1 in 40 to 1 in 500), the improvement is better than 1000 percent (an order of magnitude improvement). It is worthy to note that the methodologies, tools, and techniques used in the LaRC study can be used to evaluate similar high value equipment components and facilities. Also, lessons learned in data collection and maintenance practices derived from the observations, findings, and recommendations of the study are extremely important in the evaluation and sustainment of new compressor facilities.

Safie, Fayssal M.↗

Common Cause Failure Modeling: Aerospace Versus Nuclear

Aggregate nuclear plant failure data is used to produce generic common-cause factors that are specifically for use in the common-cause failure models of NUREG/CR-5485. Furthermore, the models presented in NUREG/CR-5485 are specifically designed to incorporate two significantly distinct assumptions about the methods of surveillance testing from whence this aggregate failure data came. What are the implications of using these NUREG generic factors to model the common-cause failures of aerospace systems? Herein, the implications of using the NUREG generic factors in the modeling of aerospace systems are investigated in detail and strong recommendations for modeling the common-cause failures of aerospace systems are given.

Stott, James E.↗

Modeling the Risk of Fire/Explosion Due to Oxidizer/Fuel Leaks in the Ares I Interstage

A significant flight hazard associated with liquid propellants, such as those used in the upper stage of NASA's new Ares I launch vehicle, is the possibility of leakage of hazardous fluids resulting in a catastrophic fire/explosion. The enclosed and vented interstage of the Ares I contains numerous oxidizer and fuel supply lines as well as ignition sources. The potential for fire/explosion due to leaks during ascent depends on the relative concentrations of hazardous and inert fluids within the interstage along with other variables such as pressure, temperature, leak rates, and fluid outgasing rates. This analysis improves on previous NASA Probabilistic Risk Assessment (PRA) estimates of the probability of deflagration, in which many of the variables pertinent to the problem were not explicitly modeled as a function of time. This paper presents the modeling methodology developed to analyze these risks.

Ring, Robert W.↗

Factors which Limit the Value of Additional Redundancy in Human Rated Launch Vehicle Systems

The National Aeronautics and Space Administration (NASA) has embarked on an ambitious program to return humans to the moon and beyond. As NASA moves forward in the development and design of new launch vehicles for future space exploration, it must fully consider the implications that rule-based requirements of redundancy or fault tolerance have on system reliability/risk. These considerations include common cause failure, increased system complexity, combined serial and parallel configurations, and the impact of design features implemented to control premature activation. These factors and others must be considered in trade studies to support design decisions that balance safety, reliability, performance and system complexity to achieve a relatively simple, operable system that provides the safest and most reliable system within the specified performance requirements. This paper describes conditions under which additional functional redundancy can impede improved system reliability. Examples from current NASA programs including the Ares I Upper Stage will be shown.

Anderson, Joel M.↗

Risk Assessment Challenges in the Ares I Upper Stage

NASA Marshall Space Flight Center (MSFC) is currently at work developing hardware and systems for the Ares I rocket that will send future astronauts into orbit. Built on cutting-edge launch technologies, evolved powerful Apollo and Space Shuttle propulsion elements, and decades of NASA spaceflight experience, Ares I is the essential core of a safe, reliable, cost-effective space transportation system -- one that will carry crewed missions back to the moon, on to Mars and out into the solar system. Ares I is an in-line, two-stage rocket configuration topped by the Orion crew vehicle and its launch abort system. In addition to the vehicle's primary mission -carrying crews of four to six astronauts to Earth orbit --Ares I may also use its 25-ton payload capacity to deliver resources and supplies to the International Space Station, or to "park" payloads in orbit for retrieval by other spacecraft bound for the moon or other destinations. Crew transportation to the International Space Station is planned to begin no later than 2014. The first lunar excursion is scheduled for the 2020 timeframe. This paper presents the challenges in designing the Ares I upper stage for reliability and safety while minimizing weight and maximizing performance.

Stott, James E.↗