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At least 271 records · Page 15

Mass and Reliability System (MaRS)

The Safety and Mission Assurance (S&MA) Directorate is responsible for mitigating risk, providing system safety, and lowering risk for space programs from ground to space. The S&MA is divided into 4 divisions: The Space Exploration Division (NC), the International Space Station Division (NE), the Safety & Test Operations Division (NS), and the Quality and Flight Equipment Division (NT). The interns, myself and Arun Aruljothi, will be working with the Risk & Reliability Analysis Branch under the NC Division's. The mission of this division is to identify, characterize, diminish, and communicate risk by implementing an efficient and effective assurance model. The team utilizes Reliability and Maintainability (R&M) and Probabilistic Risk Assessment (PRA) to ensure decisions concerning risks are informed, vehicles are safe and reliable, and program/project requirements are realistic and realized. This project pertains to the Orion mission, so it is geared toward a long duration Human Space Flight Program(s). For space missions, payload is a critical concept; balancing what hardware can be replaced by components verse by Orbital Replacement Units (ORU) or subassemblies is key. For this effort a database was created that combines mass and reliability data, called Mass and Reliability System or MaRS. The U.S. International Space Station (ISS) components are used as reference parts in the MaRS database. Using ISS components as a platform is beneficial because of the historical context and the environment similarities to a space flight mission. MaRS uses a combination of systems: International Space Station PART for failure data, Vehicle Master Database (VMDB) for ORU & components, Maintenance & Analysis Data Set (MADS) for operation hours and other pertinent data, & Hardware History Retrieval System (HHRS) for unit weights. MaRS is populated using a Visual Basic Application. Once populated, the excel spreadsheet is comprised of information on ISS components including: operation hours, random/nonrandom failures, software/hardware failures, quantity, orbital replaceable units (ORU), date of placement, unit weight, frequency of part, etc. The motivation for creating such a database will be the development of a mass/reliability parametric model to estimate mass required for replacement parts. Once complete, engineers working on future space flight missions will have access a mean time to failures and on parts along with their mass, this will be used to make proper decisions for long duration space flight missions

Barnes, Sarah↗

Reliability of the Danish Aerospace Corporation Portable Pulmonary Function System

Metabolic gas analysis is a critical component of investigations that measure cardio-pulmonary exercise responses during and after long-duration spaceflight. The primary purpose of the current study was to determine the reliability and intra-subject repeatability of a metabolic gas analysis device, the Portable Pulmonary Function System (PPFS), designed for use on the International Space Station (ISS). The second objective of this study was to directly compare PPFS measurements of expired oxygen and carbon dioxide (FEO2 and FECO2) to values obtained from a well-validated clinical metabolic gas analysis system (ParvoMedics TrueOne (c) [PM]). Eight subjects performed four peak cycle tests to maximal exertion. The first test was used to prescribe work rates for the subsequent test sessions. Metabolic gas analysis for this test was performed by the PM, but samples of FEO2 and FECO2 also were simultaneously collected for analysis by the PPFS. Subjects then performed three additional peak cycle tests, consisting of three 5-min stages designed to elicit 25%, 50%, and 75% maximal oxygen consumption (VO2max) followed by stepwise increases of 25 W/min until subjects reached volitional exhaustion. Metabolic gas analysis was performed using the PPFS for these tests. Intraclass correlation coefficients (ICC), within-subject standard deviations (WS SD), and coefficients of variation (CV%) were calculated for the repeated exercise tests. Mixed model regression analysis was used to compare paired FEO2 and FECO2 values obtained from the PPFS and the PM during the initial test. The ICC values for oxygen consumption (VO2), carbon dioxide production (VCO2), and ventilation (VE) indicate that the PPFS is highly reliable (0.79 to 0.99) for all exercise levels tested; however, ICCs for respiratory exchange ratio (RER) were low ( 0.11 - 0.51), indicating poor agreement between trials during submaximal and maximal exercise. Overall, CVs ranged from 1.6% to 6.7% for all measurements, a finding consistent with reported values that were obtained using other metabolic gas analysis techniques. The PPFS and PM produced comparable FEO2 data; however, there was less agreement between measures of FECO2 obtained from the two devices, particularly at lower CO2 concentrations. The PPFS appears, in practically all respects, to yield highly reliable metabolic gas analysis data. Lower reliability of RER measurements reported in the literature and likely is not a function of the PPFS device. Further examination of PPFS CO2 data is warranted to better understand the limitations of these PPFS measurements. Overall, the PPFS when used for repeated measures of cardio-pulmonary exercise should provide accurate and reliable data for studies of human adaptation to spaceflight.

Portable Pulmonary Function System (PPFS)↗

Reliability-Based Design of Thermal Protection Systems with Support Vector Machines

The primary objective of this work was to develop a computationally efficient and accurate approach to reliability analysis of thermal protection systems using support vector machines. An adaptive sampling approach was introduced informs a iterative support vector machine approximation of the limit state function used for measuring reliability. The proposed sampling approach efficient adds samples along the limit state function until the reliability approximation is converged. This methodology is applied to two samples, mathematical functions to test and demonstrate the applicability. Then, the adaptive sampling-based support vector machine approach is applied to the reliability analysis of a thermal protection system. The results of all three problems highlight the potential capability of the new approach in terms of accuracy and computational saving in determining thermal protection system reliability.

White, Laura M.↗

Going beyond reliability to robustness and resilience in space systems

The words reliability, robustness, and resilience, are often used interchangeably to describe tough and dependable systems but the distinctions between them suggest how to design more serviceable space systems. Reliability is simply the quality of consistently performing well. A system that dependably meets its design requirements in the specified environments is reliable. The designers may not consider themselves responsible for failures under unanticipated conditions. Robustness is the capability of performing without failure under a wide range of conditions, which can go beyond the expected range to include possible off-nominal conditions. Resilience is the ability to recover from or adapt to damaging events, such as failures, accidents, external disruptions, and repurposing. Such changes are usually unanticipated. They often invalidate the usual operating assumptions and cause system failure. Reliability, robustness, and resilience describe dependable performance under increasingly difficult conditions, first the specified environment, then a wider possible environment, and finally unanticipated damaging events. These three are increasingly desirable and increasingly difficult to achieve. Engineering for resilience would design systems that can ignore or repair failures, survive accidents, and recover from disruptions. Increasing the resilience of space systems, the ability to perform after unanticipated events, would greatly increase space crew safety. Improving reliability and robustness can be done by dealing with known sources of problems, but improving resilience requires implementing a general approach to reducing the impact of unknown future events. Two contrasting approaches are reducing system complexity and adding supervisory control. The need for resilience has been claimed for decades but little has been accomplished. Systems designers assume that they understand requirements, technologies, designs, architectures, integration, testing, operations, and environments. The potential problems of changes, failures, accidents, unknown environments, and unknown unknowns are ignored. Systems designers are typically overconfident and ignore the need for robustness and resilience.

Harry W Jones↗

Reliability-Aware Requirements Development for Autonomy Software

Autonomy is the ability of a system to make decisions and take actions in the presence of uncertainty. Validating autonomy, therefore, is a matter of validating that the system makes intelligent decisions even when there might be discrepancies between the observed and the expected state of the world as well as when the possible outcome of each of the possible courses of action is uncertain. During the requirements engineering phase, the functions, including those that are required to be autonomous and their expected behavior are specified. However, in the case of autonomous software system, it is challenging to specify all possible scenarios that the software may encounter. Additionally, since autonomous behaviors cannot always be fully predetermined, it is difficult to reason about their completeness and correctness. While these challenges are also faced with non-autonomous system, they are more prevalent for autonomous system due to their complexity and emergent behavior. Our efforts have been three-fold. On one hand, we have developed a goal-based method for requirements decomposition. We have embedded this approach into a higher-level systems engineering framework and then developed methods for decision and reliability analysis within this framework. And finally, we use simulation analysis to validate the more theoretical methods and provide a feedback mechanism. The decision analysis approach (DA) helps in identifying and mitigating the run-time risks, by bringing to the forefront the uncertainties, decisions, interactions, and other factors that may cause autonomous software to make erroneous decisions. The DA framework is used to quantify, for each decision that the software can make, failure risk due to uncertainties. The information about the key decisions and circumstances that can cause autonomous system to make incorrect decisions are used to generate test scenarios to be run in a simulator to ensure that the system can handle error-prone circumstances. The results or outcomes from decisions, based on the simulated scenarios, can then be leveraged to further gain insight of the assured system. We combine a goal-based approach with simulation analysis to facilitate requirements development for autonomous systems and further provide a method for run-time systems level reliability considerations during the autonomous software development process. The DA and the reliability analysis methods provide a formalism for the consideration of uncertainty in the run time decision-making process for autonomous software. This formalism considers the uncertainty involved in the outcome of different courses of action, in terms of performance and cost, as well as a method to consider the system level reliability implications. System level reliability considerations for autonomous software decision making contribute to the satisfaction of the system level goals over the lifecycle of a given mission. We demonstrate our approach using a hypothetical rover path planning example. The requirements for our rover simulator are based on existing literature about Mars rovers and lessons learned from real world observations at JPL. The specifics of the autonomy design for the Mars rovers, that have not been previously cleared for external release, are not used for our demonstrations.

Lindvall, Mikael↗

Topics in Reliability

This talk will wind through the details of history of reliability in the agency, where things are today, and where we need to go tomorrow. It will provide many examples of reliability that are often discounted because they are not tied to some mantra from the past. Furthermore, it will separate us from the red herrings that are ever present based on the misuse of terms and practices in reliability. It will delve into several key subject matter areas that have long been considered the key reliability drivers, such as parts, printed circuit boards, radiation, and workmanship. Finally, it will highlight how the Center and Agency need to change our approach at learning lessons from past experiences to maintain a basis for reliability long into the future.

COTS↗

Reliable IR Line Lists for N2O and OCS Isotopologues for High Temperature Applications up to 2000 K

To address the needs of planetary and exoplanetary atmosphere studies towards JWST, HWO and future IR astronomy missions, theoretical IR line lists of Carbonyl Sulfide (OCS) and Nitrous Oxide (N2O) are generated to provide complete, reliable, and consistent IR reference data in the range of 0 - 15,000 cm-1, or wavelength longer than 0.67 Å, for temperature up to 2000 K. The line lists are quantum mechanically computed using spectroscopically accurate potential energy surfaces empirically refined with reliable high-resolution experimental data, and high-quality dipole moment surfaces constructed at CCSD(T) level with aug-cc-pVT/Q/5(+d)Z basis and extrapolations to complete basis set limit. The Ames N2O line list includes the primary isotopologue 14N2 16O (denoted "446") with J=0-210 and E' up to 25,000 cm-1, and 11 minor isotopologues of 15N and 17/18O with J=0-150 and lower E' cutoffs. For OCS, Ames "natural" 296 K line list includes 12 most abundant isotopologues. The intensity contribution of OCS minor isotopologues at higher temperature is non-negligible, e.g., 8.6 ± 4.9% at 1000 K. The 16O12C32S (93.7%) and 16O12C34S (4.2%) transitions are computed with J=0-240 and E'< 22,000 cm-1, plus J=0-150 and E' < 16,000 cm-1 for five more minor isotopologues. Reliable Effective Hamiltonian models (e.g., NOSL-296 for 14N2 16O), experimental data collections, and reliable HITRAN or MARVEL levels are combined with quantum rovibrational calculations to deliver accurate and consistent empirical corrections for line positions. The reliability and accuracy of our IR intensity predictions are demonstrated by comparison with available databases, line lists, and experiments, at both room temperature and at high temperature. The line lists will be freely available to public online at ZENODO and NAS data portal. We acknowledge the financial support from NASA XRP and APRA programs.

Planetary↗

Scaled CMOS Reliability and Considerations for Spacecraft Systems: Bottom-Up and Top-Down Perspective

New space missions will increasingly rely on more advanced technologies because of system requirements for higher performance, particularly in instruments and high-speed processing. Component-level reliability challenges with scaled CMOS in spacecraft systems from a bottom-up perspective have been presented. Fundamental Front-end and Back-end processing reliability issues with more aggressively scaled parts have been discussed. Effective thermal management from system-level to the componentlevel (top-down) is a key element in overall design of reliable systems. Thermal management in space systems must consider a wide range of issues, including thermal loading of many different components, and frequent temperature cycling of some systems. Both perspectives (top-down and bottom-up) play a large role in robust, reliable spacecraft system design.

Scaled CMOS↗

Time Distribution Analysis for Task Primitives to Support Dynamic Human Reliability Analysis

To support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method and Human Reliability data EXtraction (HuREX). GOMS-HRA was developed to provide cognition-based time and human error probability (HEP) information for dynamic HRA calculations within the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework, while HuREX is a comprehensive HRA data collection method developed by the Korea Atomic Energy Research Institute (KAERI). In this paper, we examine time distributions by using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which proposes an HRA data collection framework to complement full-scope simulator research and gather input data for dynamic HRA by using simplified simulators such as the Rancor Microworld simulator. This paper investigates whether the time required for GOMS-HRA and HuREX task primitives fits 13 statistical distributions. Additionally, we compare and discuss the time distributions obtained from both student operators and professional operators. The result was that this study identified several time distributions for five GOMS-HRA and four HuREX task primitives. In the future, the results of this study are expected to provide objective reference data on the elapsed time for task primitives and aid in realistically simulating scenarios within dynamic HRA.

Dynamic Human Reliability Analysis↗

Evaluating grid stress and reliability in future electricity grids across a range of demand, generation mix, and weather trends

The reliability of power grids in the future will depend on how system planners account for the integration of new technologies, extreme weather events, and uncertainties in demand growth from increased electrification and data centers. This study introduces an open-source, multisectoral, multiscale modeling framework that projects grid stress and reliability trends between 2020 and 2055 in the Western Interconnection of the United States. The framework integrates global to national energy-water-land dynamics with power plant siting and hourly grid operations modeling. We analyze future wholesale electricity price shocks and unserved energy events across eight scenarios spanning a range of population growth and economic change, generation mixes, and weather conditions. Our results show future grids with high percentage of non-renewable generation and strong economic growth are characterized by higher reliability and lower wholesale electricity prices than lower growth scenarios because of larger reliance on dispatchable generators and lower fossil fuel extraction costs. Scenarios with high percentage of renewable resources have lower median but more volatile wholesale electricity prices as well as more frequent and severe unserved energy events compared to scenarios relying more on dispatchable generators. These events occur because higher proportion of solar and wind energy causes net demand curves to deepen during midday (duck curves get progressively severe), exacerbating the challenge of meeting demand during summer evening peaks. This study suggests that robust and co-optimized transmission and energy storage planning could help maintain low wholesale electricity prices and high reliability levels in future electricity grids across uncertainties in generation mixes.

Electric grid reliability↗

Integrated multimodel analysis reveals achievable pathways toward reliable, 100% renewable electricity for Los Angeles

Climate change has prompted many communities to set targets for carbon-free power supplies, but they often lack data-driven strategies to achieve them. We present a comprehensive analysis of an entirely renewable electric power system that can maintain operating reliability and resource adequacy using detailed models of the city of Los Angeles power grid. In consultation with the operating utility, the Los Angeles Department of Water and Power (LADWP), and the local community, we develop four supply scenarios across three demand projections to analyze which types of infrastructure and operational changes would achieve reliable electricity at least cost. We find that a reliable, 100%-renewable power system yielding more than $1 billion annually in health and climate co-benefits is achievable. Solar can supply most future energy needs, while combustion turbines that use renewable, storable carbon-neutral fuels are key to maintaining reliability. This study provides a replicable methodology that other jurisdictions globally can follow.

14 SOLAR ENERGY↗

Assessing the Reliability Benefits of Energy Storage as a Transmission Asset

Utilizing energy storage solutions to reduce the need for traditional transmission investments has been recognized by system planners and supported by federal policies in recent years. This work demonstrates the need for detailed reliability assessment for quantitative comparison of the reliability benefits of energy storage and traditional transmission investments. First, a mixed-integer linear programming expansion planning model considering candidate transmission lines and storage technologies is solved to find the least-cost investment decisions. Next, operations under the resulting system configuration are simulated in a probabilistic reliability assessment which accounts for weather-dependent forced outages. The outcome of this work, when applied to TPPs, is to further equalize the consideration of energy storage compared to traditional transmission assets by capturing the value of storage for system reliability.

co-optimization↗

Inferring Reliability Model Parameters from Expert Opinion

Here, we propose a method for constructing bathtub models of reliability from opinion. The method is intended for reliability studies early in the design and prototyping of a new system, before data concerning reliability has become available. A stylized bathtub curve is presented for soliciting best engineering judgement from technical experts. By pooling these stylized curves, we produce data that can be used to infer parameters for a piece-wise Weibull model of reliability. A numerical example demonstrates the practicality of the method while also highlighting potential pitfalls when working with subjective data.

42 ENGINEERING↗

Generation and analysis of large reliability models

An effort has been underway for several years at NASA's Langley Research Center to extend the capability of Markov modeling techniques for reliability analysis to the designers of highly reliable avionic systems. This effort has been focused in the areas of increased model abstraction and increased computational capability. The reliability model generator (RMG), a software tool which uses as input a graphical, object-oriented block diagram of the system, is discussed. RMG uses an automated failure modes-effects analysis algorithm to produce the reliability model from the graphical description. Also considered is the ASSURE software tool, a parallel processing program which uses the ASSIST modeling language and SURE semi-Markov solution technique. An executable failure modes-effects analysis is used by ASSURE. The successful combination of the power of graphical representation, automated model generation, and parallel computation leads to the conclusion that large system architectures can now be analyzed.

Aerospace electronics↗

An Ultra Reliability for Project for NASA

NASA has embarked on a new program designed to improve the reliability of NASA systems. In this context, the goal for ultra reliability is to ultimately improve the systems by an order of magnitude. The approach outlined in this presentation involves five steps: 1. Divide NASA systems into seven sectors; 2. Establish sector champions and representatives from each NASA center; 3. Develop a challenge list for each sector using a team of NASA experts in each area with the sector champion facilitating the effort; 4. Develop mitigation strategies for each of the sectors' challenge lists and rank their importance by holding a workshop with area experts from government (NASA and non-NASA), universities and industry; 5. Develop a set of tasks for each sector in order of importance for improving the reliability of NASA systems. Several NASA-wide workshops have been held, identifying issues for reliability improvement and providing mitigation strategies for these issues.

ultra-reliability↗

Column Grid Array Rework for High Reliability

Due to requirements for reduced size and weight, use of grid array packages in space applications has become common place. To meet the requirement of high reliability and high number of I/Os, ceramic column grid array packages (CCGA) were selected for major electronic components used in next MARS Rover mission (specifically high density Field Programmable Gate Arrays). ABSTRACT The probability of removal and replacement of these devices on the actual flight printed wiring board assemblies is deemed to be very high because of last minute discoveries in final test which will dictate changes in the firmware. The questions and challenges presented to the manufacturing organizations engaged in the production of high reliability electronic assemblies are, Is the reliability of the PWBA adversely affected by rework (removal and replacement) of the CGA package? and How many times can we rework the same board without destroying a pad or degrading the lifetime of the assembly? To answer these questions, the most complex printed wiring board assembly used by the project was chosen to be used as the test vehicle, the PWB was modified to provide a daisy chain pattern, and a number of bare PWB s were acquired to this modified design. Non-functional 624 pin CGA packages with internal daisy chained matching the pattern on the PWB were procured. The combination of the modified PWB and the daisy chained packages enables continuity measurements of every soldered contact during subsequent testing and thermal cycling. Several test vehicles boards were assembled, reworked and then thermal cycled to assess the reliability of the solder joints and board material including pads and traces near the CGA. The details of rework process and results of thermal cycling are presented in this paper.

high reliability↗

Users Guide on Scaled CMOS Reliability: NASA Electronic Parts and Packaging (NEPP) Program Office of Safety and Mission Assurance

Reliability of advanced CMOS technology is a complex problem that is usually addressed from the standpoint of specific failure mechanisms rather than overall reliability of a finished microcircuit. A detailed treatment of CMOS reliability in scaled devices can be found in Ref. 1; it should be consulted for a more thorough discussion. The present document provides a more concise treatment of the scaled CMOS reliability problem, emphasizing differences in the recommended approach for these advanced devices compared to that of less aggressively scaled devices. It includes specific recommendations that can be used by flight projects that use advanced CMOS. The primary emphasis is on conventional memories, microprocessors, and related devices.

Scaled CMOS↗

Space Radiation Effects and Reliability Consideration for the Proposed Jupiter Europa Orbiter

The proposed Jupiter Europa Orbiter (JEO) mission to explore the Jovian moon Europa poses a number of challenges. The spacecraft must operate for about seven years during the transit time to the vicinity of Jupiter, and then endure unusually high radiation levels during exploration and orbiting phases. The ability to withstand usually high total dose levels is critical for the mission, along with meeting the high reliability standards for flagship NASA missions. Reliability of new microelectronic components must be sufficiently understood to meet overall mission requirements.The proposed Jupiter Europa Orbiter (JEO) mission to explore the Jovian moon Europa poses a number of challenges. The spacecraft must operate for about seven years during the transit time to the vicinity of Jupiter, and then endure unusually high radiation levels during exploration and orbiting phases. The ability to withstand usually high total dose levels is critical for the mission, along with meeting the high reliability standards for flagship NASA missions. Reliability of new microelectronic components must be sufficiently understood to meet overall mission requirements.

semiconductor devices↗