Digital Twin for Systems 4.0: Enhancing Reliability Assessment Modeling and Simulation
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A team directed by the NASA Engineering and Safety Center (NESC) collected methodologies for how best to develop safe and reliable human rated systems and how to identify the drivers that provide the basis for assessing safety and reliability. The team also identified techniques, methodologies, and best practices to assure that NASA can develop safe and reliable human rated systems. The results are drawn from a wide variety of resources, from experts involved with the space program since its inception to the best-practices espoused in contemporary engineering doctrine. This report focuses on safety and reliability considerations and does not duplicate or update any existing references. Neither does it intend to replace existing standards and policy.
A team directed by the NASA Engineering and Safety Center (NESC) collected methodologies for how best to develop safe and reliable human rated systems and how to identify the drivers that provide the basis for assessing safety and reliability. The team also identified techniques, methodologies, and best practices to assure that NASA can develop safe and reliable human rated systems. The results are drawn from a wide variety of resources, from experts involved with the space program since its inception to the best-practices espoused in contemporary engineering doctrine. This report focuses on safety and reliability considerations and does not duplicate or update any existing references. Neither does it intend to replace existing standards and policy.
Apollo gyro reliability covering guidance, navigation and control systems, stressing failure mode prediction
While SOFC systems are expected to operate reliably and with limited degradation in steady state or transient performance, SOFC stacks may ultimately fail due to the loss of structural integrity of one or several of the cells as a result of the weakening of the materials and interfaces due to physico-chemical changes that occur during continuous operation as a result of plastic and creep deformations, modification of the temperature profile, and/or degradation of the electrochemical performance of the cells. Degradation mechanisms originating from the cell components include coarsening of the microstructure over time; decomposition of materials; chemical reaction of electrode materials with electrolyte at the interface; delamination from each other; and for the anode, coking and sulfur poisoning. Of all the reliability issues that may occur for SOFCs, the main limitation for Ni-based cermet anodes (e.g., NiO-YSZ) is the poor stability during reduction-oxidation (red-ox) cycling. This project was aimed at the development of ceramic anode SOFCs based on SFCM (SrFe0.2Co0.4Mo0.4O3), which is a conductive perovskite that is red-ox stable. Additionally, the project involved the development of a red-ox robust stack. Scale up of SFCM-based cells to a large format (10 cm by 10 cm) cell size was achieved as well as a maximum power density of 0.9 W/cm 2 at 600 °C (>0.6 W/cm 2 at 0.6 V). Up to a 10-cell stack was successfully assembled and demonstrated, and cells showed similar performance in reformed, pipeline natural gas as in hydrogen. Finally, a 3-cell stack was red-ox cycled without degradation for 40 cycles at ~600 °C.
This report summarizes work performed by the Space Systems Laboratory (SSL) for NASA Langley Research Center in the field of performance optimization for systems subject to uncertainty. The objective of the research is to develop design methods and tools to the aerospace vehicle design process which take into account lifecycle uncertainties. It recognizes that uncertainty between the predictions of integrated models and data collected from the system in its operational environment is unavoidable. Given the presence of uncertainty, the goal of this work is to develop means of identifying critical sources of uncertainty, and to combine these with the analytical tools used with integrated modeling. In this manner, system uncertainty analysis becomes part of the design process, and can motivate redesign. The specific program objectives were: 1. To incorporate uncertainty modeling, propagation and analysis into the integrated (controls, structures, payloads, disturbances, etc.) design process to derive the error bars associated with performance predictions. 2. To apply modern optimization tools to guide in the expenditure of funds in a way that most cost-effectively improves the lifecycle productivity of the system by enhancing the subsystem reliability and redundancy. The results from the second program objective are described. This report describes the work and results for the first objective: uncertainty modeling, propagation, and synthesis with integrated modeling.
Spacecraft power supply system and component reliability, efficiency, weight factors, and electromagnetic compatibility
Despite the importance of reliability to the cost competitiveness of PV, large data sets enabling high-level investigation of the technology’s performance in the field are relatively scarce. Dirk C. Jordan, Chris Deline, Bill Marion and Teresa Barnes of the National Renewable Energy Laboratory, and Mark Bolinger of the Lawrence Berkeley National Laboratory study a unique data set of 100,000 PV systems in the US, drawing out tips for better reliability that have relevance to other parts of the world.
Equivalent System Mass (ESM) and reliability estimates were performed for different life support architectures based primarily on International Space Station (ISS) technologies. The analysis was applied to a hypothetical 1-year deep-space mission. High-level fault trees were initially developed relating loss of life support functionality to the Loss of Crew (LOC) top event. System reliability was then expressed as the complement (nonoccurrence) this event and was increased through the addition of redundancy and spares, which added to the ESM. The reliability analysis assumed constant failure rates and used current projected values of the Mean Time Between Failures (MTBF) from an ISS database where available. Results were obtained showing the dependence of ESM on system reliability for each architecture. Although the analysis employed numerous simplifications and many of the input parameters are considered to have high uncertainty, the results strongly suggest that achieving necessary reliabilities for deep-space missions will add substantially to the life support system mass. As a point of reference, the reliability for a single-string architecture using the most regenerative combination of ISS technologies without unscheduled replacement spares was estimated to be less than 1%. The results also demonstrate how adding technologies in a serial manner to increase system closure forces the reliability of other life support technologies to increase in order to meet the system reliability requirement. This increase in reliability results in increased mass for multiple technologies through the need for additional spares. Alternative parallel architecture approaches and approaches with the potential to do more with less are discussed. The tall poles in life support ESM are also reexamined in light of estimated reliability impacts.
Formulas for reliability extended to more general cases. Useful in analyses of reliabilities of practical systems and structures, especially of redundant systems of identical components, among which operating loads distributed equally.
The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.
The engineering process of Design for Reliability (DfR) is well established in the automotive and aerospace industries. DfR should be useful in the future development of space life support systems. DfR is a sequence of tasks that develop system requirements and plan reliability analysis and testing. First and fundamentally, the reliability requirement is defined. Next the system reliability model is developed, often using a reliability block diagram. The overall system reliability requirement is allocated to the subsystems and an estimate of the attainable reliability is made. This expected reliability can be improved by simplifying the design by removing components or by replacing less reliable components. Improving reliability can require difficult compromises, such as reducing performance requirements, increasing budget, or extending testing. The actual system reliability can be determined only by testing, which should continue long enough to provide the required confidence in the measured value. New systems often have unexpected design errors that cause failures in early testing. The usual reliability improvement process of testing, finding the failure modes, and redesigning to remove them reduces the failure rate and is referred to as “reliability growth.” After redesign has been completed, the system should be further tested to determine the actual achieved reliability more accurately. If the final system failure rate is too high, redundant systems can be used to improve overall operational reliability. Adding redundancy simply to increase the one- or two-fault tolerance metric may sometimes reduce reliability. Reliability can be improved in three ways: redesigning the system to include more reliable subsystems and components, reliability growth testing and failure mode removal, and by using parallel redundant systems. DfR should combine these approaches to achieve the required reliability while managing performance, cost, and schedule.
Human-system interfaces (HSIs) play an important role in enabling operators to communicate with the nuclear power plant (NPP) side. Getting the information required to understand a NPP’s current status or perform necessary actions for responding to a given operational context are representative operator tasks performed using HSIs. To date, HSIs have been mainly evaluated in the context of human reliability analysis (HRA). However, the current HSI evaluation that occurs during HRA may be challengeable on two fronts: (1) reflecting the unique characteristics of HSI systems and (2) considering situations in which HSIs are poorly operated due to software/hardware malfunctions. Accordingly, this study proposes an approach for specifically evaluating HSIs for digital instrumentation and controls (DI&C) systems, using Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) and HRA. RESHA is a method for analyzing DI&C systems with redundancy features. In this study, we investigate how HSIs are evaluated in existing HRA methods, and what challenges exist in the current approaches. To better evaluate HSIs for DI&C systems, this study modifies the existing HSI evaluation process by additionally modeling the HSI back- and front- ends. In this paper, a HSI fault tree for the APR1400 DI&C system is introduced through a piping and instrumentation diagram. It then touches upon what aspects of the suggested method must be further researched.
Robustness of reliability predictions for series systems with identical components, assuming exponential failure distribution
The SURE reliability analysis program is discussed as well as the ASSIST model generation program. It is found that semi-Markov modeling using model reduction strategies with the ASSIST program can be used to accurately solve problems at least as complex as other reliability analysis tools can solve. Moreover, semi-Markov analysis provides the flexibility needed for modeling realistic fault-tolerant systems.
Reliable and continuous meteorological data are crucial for modeling the responses of energy systems and their components to weather and climate conditions, particularly in densely populated urban areas. However, existing long-term datasets often suffer from spatial and temporal gaps and inconsistencies, posing great challenges for detailed urban energy system modeling and cross-city comparison under realistic weather conditions. Here we introduce the Historical Comprehensive Hourly Urban Weather Database (CHUWD-H) v1.0, a 23-year (1998-2020) gap-free and quality-controlled hourly weather dataset covering 550 weather station locations across all urban areas in the contiguous United States. CHUWD-H v1.0 synthesizes hourly weather observations from stations with outputs from a physics-based solar radiation model and a reanalysis dataset through a multi-step gap filling approach. A 10-fold Monte Carlo cross-validation suggests that the accuracy of this gap filling approach surpasses that of conventional gap filling methods. Designed primarily for urban energy system modeling, CHUWD-H v1.0 should also support historical urban meteorological and climate studies, including the validation and evaluation of urban climate modeling.
A reliable isotope heat source simulator was designed for use in a Brayton power system. This simulator is composed of an electrically heated tungsten wire which is wound around a boron nitride core and enclosed in a graphite jacket. Simulator testing was performed at the expected operating temperature of the Brayton power system. Endurance testing for 5012 hours was followed by cycling the simulator temperature. The integrity of this simulator was maintained throughout testing. Alumina beads served as a diffusion barrier to prevent interaction between the tungsten heater and boron nitride core. The simulator was designed to maintain a surface temperature of 1311 to 1366 K (1900 to 2000 F) with a power input of approximately 400 watts. The design concept and the materials used in the simulator make possible man different geometries. This flexibility increases its potential use.
Accurate analysis of reliability of system requires that it accounts for all major variations in system's operation. Most reliability analyses assume that the system configuration, success criteria, and component behavior remain the same. However, multiple phases are natural. We present a new computationally efficient technique for analysis of phased-mission systems where the operational states of a system can be described by combinations of components states (such as fault trees or assertions). Moreover, individual components may be repaired, if failed, as part of system operation but repairs are independent of the system state. For repairable systems Markov analysis techniques are used but they suffer from state space explosion. That limits the size of system that can be analyzed and it is expensive in computation. We avoid the state space explosion. The phase algebra is used to account for the effects of variable configurations, repairs, and success criteria from phase to phase. Our technique yields exact (as opposed to approximate) results. We demonstrate our technique by means of several examples and present numerical results to show the effects of phases and repairs on the system reliability/availability.