NEPAG Developments to Improve Component Engineering and Reliability for Space
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Use of success and failure data in reliability engineering
Complex systems improvement by integration of reliability and systems engineering techniques
Solar energy, especially photovoltaics (PV), plays a significant role in the global energy transition required for decarbonization. Technological advancements in increasing efficiencies coupled with cost reductions through economies of scale made PV a cost-competitive energy source set to exceed the milestone of 1 TW globally deployed capacity in 2022. However, ongoing downward price pressure coupled with increasing service life expectations creates tremendous challenges for reliability engineers in ensuring the safe and reliable operation of PV modules and systems over the anticipated service life. Today's reliability research efforts aim for module lifetimes of up to 50 years. Still, our current tools fall short in accurately assessing degradation mechanisms and failure modes over such extended periods. We argue that the well-established PV reliability learning cycle needs to be accelerated to keep up with the rapid technological advancements and high expectations that are put on PV and its role in the global energy transition. In this article, we explore the evolution of the PV reliability learning cycle and highlight the significance that predictive modeling capabilities will have on future PV module reliability. We propose creating a unifying modeling framework - which once established will enable the holistic assessment of PV module reliability, accelerate the PV reliability learning cycle, and bring us closer to quantitative service life predictions of PV modules.
The problem of improving operational reliability of turbojet engines is studied in a series of papers. Failure statistics for this engine are presented, the theory and experimental evidence on how engine failures occur are described, and the methods available for avoiding failure in operation are discussed. The individual papers of the series are Objectives, Failure Statistics, Foreign-Object Damage, Compressor Blades, Combustor Assembly, Nozzle Diaphrams, Turbine Buckets, Turbine Disks, Rolling Contact Bearings, Engine Fuel Controls, and Summary Discussion.
The problem of improving operational reliability of turbojet engines is studied. Failure statistics for this engine are presented, the theory and experimental evidence on how engine failures occur are described, and the methods available for avoiding failure in operation are discussed.
During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.
Under the US Department of Energy's (DOEs) Solar Thermal Technology Program, Sandia National Laboratories is evaluating heat engines for solar distributed receiver systems. The final design is described of an engineering prototype advanced Stirling conversion system (ASCS) with a free-piston hydraulic engine output capable of delivering about 25 kW of electric power to a utility grid. The free-piston Stirling engine has the potential for a highly reliable engine with long life because it has only a few moving parts, has noncontacting bearings, and can be hermetically sealed. The ASCS is designed to deliver maximum power per year over a range of solar input with a design life of 30 years (60,000 h). The system includes a liquid Nak pool boiler heat transport system and a free-piston Stirling engine with high-pressure hydraulic output, coupled with a bent axis variable displacement hydraulic motor and a rotary induction generator.
A key technological concept for producing reliable engine diagnostics and prognostics exploits the benefits of fusing sensor data, information, and/or processing algorithms. This report describes the development of a hybrid engine model for a propulsion gas turbine engine, which is the result of fusing two diverse modeling methodologies: a physics-based model approach and an empirical model approach. The report describes the process and methods involved in deriving and implementing a hybrid model configuration for a commercial turbofan engine. Among the intended uses for such a model is to enable real-time, on-board tracking of engine module performance changes and engine parameter synthesis for fault detection and accommodation.
This viewgraph presentation reviews operational reliability and its role in achieving high reliability through design and process reliability. The topics include: 1) Reliability Engineering Major Areas and interfaces; 2) Design Reliability; 3) Process Reliability; and 4) Reliability Applications.
Design stage reliability analysis application to static inverter
NERVA nuclear rocket engine design technology program, discussing probabilistic techniques for reliability engineering
Hazard Analysis, Failure Modes and Effects Analysis (FMEA), the Limited-Life Items List (LLIL), and the Single Point Failure (SPF) List were applied by System Safety and Reliability engineers on NASA's Communications, Navigation, and Networking reConfigurable Testbed (CoNNeCT) Project. The integrated approach involving cross reviews of these reports by System Safety, Reliability, and Design engineers resulted in the mitigation of all identified hazards. The outcome was that the system met all the safety requirements it was required to meet.
Reliability is the ability of a product to properly function, within specified performance limits, for a specified period of time, under the life cycle application conditions. Failure analysis is a vital tool in the effort to ensure reliability of electronic products and systems throughout their product lifecycle. Today, organizations involved in activities within the electronics supply chain are facing new challenges, not just from complex assembly styles, harsher lifecycle environments, and sophisticated supply chains, but also from customers who are demanding a quicker turn-around. Unfortunately, root cause failure analysis is often performed incompletely, leading to a poor understanding of failure mechanisms and causes and, customer dissatisfaction due to recurring failures. The PDC starts with an introduction to reliability concepts, physics of failure and an overview of failure mechanisms that affect PCBs, PCBAs and components. The PDC then dives into root cause hypothesizing techniques (Pareto, FMEA, fishbone, FTA), non-destructive and destructive analysis and, materials characterization will be discussed. Numerous failure analysis case studies will be used to illustrate the techniques and analysis principles to arrive at the root cause(s) of field failures on printed circuit boards, active components, and assemblies. What Will You Learn: Topics include: Overview of Reliability Concepts Failure mechanisms of electronic products Root cause analysis Failure analysis techniques -Non-destructive techniques (optical, CSAM etc.) -Destructive analysis (DPA, Decap, FIB etc.) -Materials characterization (XRF, EDS, TMA/DSC etc.) Who Will Benefit: Reliability engineers, failure analysis engineers, engineering managers, design engineers, component engineers, quality assurance functions and, personnel involved with reliability activities within their company.
In-flight sensor fault detection and isolation (FDI) is critical to maintaining reliable engine operation during flight. The aircraft engine control system, which computes control commands on the basis of sensor measurements, operates the propulsion systems at the demanded conditions. Any undetected sensor faults, therefore, may cause the control system to drive the engine into an undesirable operating condition. It is critical to detect and isolate failed sensors as soon as possible so that such scenarios can be avoided. A challenging issue in developing reliable sensor FDI systems is to make them robust to changes in engine operating characteristics due to degradation with usage and other faults that can occur during flight. A sensor FDI system that cannot appropriately account for such scenarios may result in false alarms, missed detections, or misclassifications when such faults do occur. To address this issue, an enhanced bank of Kalman filters was developed, and its performance and robustness were demonstrated in a simulation environment. The bank of filters is composed of m + 1 Kalman filters, where m is the number of sensors being used by the control system and, thus, in need of monitoring. Each Kalman filter is designed on the basis of a unique fault hypothesis so that it will be able to maintain its performance if a particular fault scenario, hypothesized by that particular filter, takes place.