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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17

Hybrid Modeling of Unmanned Aerial Vehicle Electric Powertrain for Fault Detection and Diagnostics

This paper shows the application of hybrid physics-informed machine learning to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived principles and empirical equations, as well as fully connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage. It has already been applied to Li-ion batteries in the past, and in this work, we extend the applications to other components of an electric powertrain, namely electronic speed controller with pulse-width modulation, and brushless DC motor with connected propeller. Training and testing of the model is carried out using experimental data from Li-ion battery discharge and powertrain testing in a laboratory environment.

Physics-Informed Machine Learning↗

Local and long-range atomic/magnetic structure of non-stoichiometric spinel iron oxide nanocrystallites

Spinel iron oxide nanoparticles of different mean sizes in the range 10–25 nm have been prepared by surfactant-free up-scalable near- and super-critical hydrothermal synthesis pathways and characterized using a wide range of advanced structural characterization methods to provide a highly detailed structural description. The atomic structure is examined by combined Rietveld analysis of synchrotron powder X-ray diffraction (PXRD) data and time-of-flight neutron powder-diffraction (NPD) data. The local atomic ordering is further analysed by pair distribution function (PDF) analysis of both X-ray and neutron total-scattering data. It is observed that a non-stoichiometric structural model based on a tetragonal γ-Fe 2 O 3 phase with vacancy ordering in the structure (space group P 4 3 2 1 2) yields the best fit to the PXRD and total-scattering data. Detailed peak-profile analysis reveals a shorter coherence length for the superstructure, which may be attributed to the vacancy-ordered domains being smaller than the size of the crystallites and/or the presence of anti-phase boundaries, faulting or other disorder effects. The intermediate stoichiometry between that of γ-Fe 2 O 3 and Fe 3 O 4 is confirmed by refinement of the Fe/O stoichiometry in the scattering data and quantitative analysis of Mössbauer spectra. The structural characterization is complemented by nano/micro-structural analysis using transmission electron microscopy (TEM), elemental mapping using scanning TEM, energy-dispersive X-ray spectroscopy and the measurement of macroscopic magnetic properties using vibrating sample magnetometry. Notably, no evidence is found of a Fe 3 O 4 /γ-Fe 2 O 3 core-shell nanostructure being present, which had previously been suggested for non-stoichiometric spinel iron oxide nanoparticles. Finally, the study is concluded using the magnetic PDF (mPDF) method to model the neutron total-scattering data and determine the local magnetic ordering and magnetic domain sizes in the iron oxide nanoparticles. The mPDF data analysis reveals ferrimagnetic collinear ordering of the spins in the structure and the magnetic domain sizes to be ∼60–70% of the total nanoparticle sizes. The present study is the first in which mPDF analysis has been applied to magnetic nanoparticles, establishing a successful precedent for future studies of magnetic nanoparticles using this technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Representing Complex Systems as Graphs for Debugging and Predictive Maintenance-Preliminary Thoughts

Representing complex systems as graphs enables use of mathematical tools to identify faults or predict failures. Graph nodes correspond to individual modules or subsystems, and edges link coupled system parts. ‘Probes’ measure the node outputs, monitoring the system health for unexpected behavior. Assuming one cannot probe every point, within a system, the fault correlates to a region—not necessarily the specific location. Bayesian networks trained to understand fault patterns can accurately identify the source. The diagnostic tool described aides debugging by pinpointing system failure causes. For predictive maintenance, probe data develop probability distribution functions describing subsystem mean time to failure. Unit lifetime can be estimated through these probability distributions. Two approaches include using Bayesian classifiers to infer the system failure source and developing maintenance schedules by treating systems as collections of random variables. When failure behavior does not follow a closed form function, use of similarity models is proposed.

97 MATHEMATICS AND COMPUTING↗

NASA Tech Briefs, October 2007

Topics covered include; Wirelessly Interrogated Position or Displacement Sensors; Ka-Band Radar Terminal Descent Sensor; Metal/Metal Oxide Differential Electrode pH Sensors; Improved Sensing Coils for SQUIDs; Inductive Linear-Position Sensor/Limit-Sensor Units; Hilbert-Curve Fractal Antenna With Radiation- Pattern Diversity; Single-Camera Panoramic-Imaging Systems; Interface Electronic Circuitry for an Electronic Tongue; Inexpensive Clock for Displaying Planetary or Sidereal Time; Efficient Switching Arrangement for (N + 1)/N Redundancy; Lightweight Reflectarray Antenna for 7.115 and 32 GHz; Opto-Electronic Oscillator Using Suppressed Phase Modulation; Alternative Controller for a Fiber-Optic Switch; Strong, Lightweight, Porous Materials; Nanowicks; Lightweight Thermal Protection System for Atmospheric Entry; Rapid and Quiet Drill; Hydrogen Peroxide Concentrator; MMIC Amplifiers for 90 to 130 GHz; Robot Would Climb Steep Terrain; Measuring Dynamic Transfer Functions of Cavitating Pumps; Advanced Resistive Exercise Device; Rapid Engineering of Three-Dimensional, Multicellular Tissues With Polymeric Scaffolds; Resonant Tunneling Spin Pump; Enhancing Spin Filters by Use of Bulk Inversion Asymmetry; Optical Magnetometer Incorporating Photonic Crystals; WGM-Resonator/Tapered-Waveguide White-Light Sensor Optics; Raman-Suppressing Coupling for Optical Parametric Oscillator; CO2-Reduction Primary Cell for Use on Venus; Cold Atom Source Containing Multiple Magneto- Optical Traps; POD Model Reconstruction for Gray-Box Fault Detection; System for Estimating Horizontal Velocity During Descent; Software Framework for Peer Data-Management Services; Autogen Version 2.0; Tracking-Data-Conversion Tool; NASA Enterprise Visual Analysis; Advanced Reference Counting Pointers for Better Performance; C Namelist Facility; and Efficient Mosaicking of Spitzer Space Telescope Images.

Source record↗

A workflow to assess the efficacy of brine extraction for managing injection-induced seismicity potential using data from a CO 2 injection site near Decatur, Illinois

Injection of CO 2 for storage in a geologic formation increases pore pressure and alters in situ stresses. Depending on the orientation of any existing fault and fracture planes, such as critically stressed planes, this stress alteration will modify normal stresses acting on planes and could result in frictional sliding and release stored energy in the form of seismicity. Brine extraction (BE) is a technique that can be applied prior to, or during, CO 2 injection to reduce pore pressure for increasing storage capacity and, potentially, for reducing the likelihood of frictional sliding. Here a workflow is described to assess the efficacy of BE for mitigating frictional sliding (i.e., seismicity) during injection and entails: site characterization, stress calculations and failure assessment, static and dynamic modeling, and BE operational planning. Site characterization describes the stress field used to calculate the Coulomb Failure Function (CFF) that constrains allowable pore pressure changes and injection rates in the numerical simulation of CO 2 injection scenarios. The inclusion of BE in the workflow allows for determination of the potential need for pressure reduction, and evaluation of the effectiveness of this operation. Example application of the workflow using an injection field dataset near Decatur, IL, provides insight on fracture planes and stresses at the site, formation properties and the impact of variable CO 2 injection-rate targets on whether BE plans are required. The study workflow indicates that BE could enhance CO 2 injection rate by 39% and correspondingly reduce the potential for injection-induced seismicity as indicated by a reduction in CFF.

58 GEOSCIENCES↗

Hardware-in-the-loop Testing of Network Protectors for Low-Voltage Networks with Distributed Energy Resources

In this report, we developed and validated a network protector relay digital twin model and interfaced a commonly used network protector relay hardware with our real-time simulation system. Hardware-in-the-loop protection studies are performed to assess the impact of distributed energy resources (DER) and benchmark a rate-of-change-based mitigation strategy. Simulation results suggest that the network protector reverse trip and auto-reclose functions are negatively impacted by the high distributed energy resource penetration. To accommodate DER backfeed while remaining secure and reliable for faults on primary feeders, we recommend options for a rate-of-change-based blocking scheme and a protection setting change. Finally, future mitigation ideas and standard revisions are discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Study of fault tolerant software technology for dynamic systems

The major aim of this study is to investigate the feasibility of using systems-based failure detection isolation and compensation (FDIC) techniques in building fault-tolerant software and extending them, whenever possible, to the domain of software fault tolerance. First, it is shown that systems-based FDIC methods can be extended to develop software error detection techniques by using system models for software modules. In particular, it is demonstrated that systems-based FDIC techniques can yield consistency checks that are easier to implement than acceptance tests based on software specifications. Next, it is shown that systems-based failure compensation techniques can be generalized to the domain of software fault tolerance in developing software error recovery procedures. Finally, the feasibility of using fault-tolerant software in flight software is investigated. In particular, possible system and version instabilities, and functional performance degradation that may occur in N-Version programming applications to flight software are illustrated. Finally, a comparative analysis of N-Version and recovery block techniques in the context of generic blocks in flight software is presented.

Caglayan, A. K.↗

A demonstration of an intelligent control system for a reusable rocket engine

An Intelligent Control System for reusable rocket engines is under development at NASA Lewis Research Center. The primary objective is to extend the useful life of a reusable rocket propulsion system while minimizing between flight maintenance and maximizing engine life and performance through improved control and monitoring algorithms and additional sensing and actuation. This paper describes current progress towards proof-of-concept of an Intelligent Control System for the Space Shuttle Main Engine. A subset of identifiable and accommodatable engine failure modes is selected for preliminary demonstration. Failure models are developed retaining only first order effects and included in a simplified nonlinear simulation of the rocket engine for analysis under closed loop control. The engine level coordinator acts as an interface between the diagnostic and control systems, and translates thrust and mixture ratio commands dictated by mission requirements, and engine status (health) into engine operational strategies carried out by a multivariable control. Control reconfiguration achieves fault tolerance if the nominal (healthy engine) control cannot. Each of the aforementioned functionalities is discussed in the context of an example to illustrate the operation of the system in the context of a representative failure. A graphical user interface allows the researcher to monitor the Intelligent Control System and engine performance under various failure modes selected for demonstration.

Musgrave, Jeffrey L.↗

Robustness of Vacancy-Bound Non-Abelian Anyons in the Kitaev Model in a Magnetic Field

Non-Abelian anyons in quantum spin liquids (QSLs) provide a promising route to fault-tolerant topological quantum computation. In the exactly solvable Kitaev honeycomb model, such anyons of the QSL state can be bound to nonmagnetic spin vacancies and endowed with non-Abelian statistics by an infinitesimal magnetic field. Here, we investigate how this approach for stabilizing non-Abelian anyons extends to a finite magnetic field represented by a proper Zeeman term. Through large-scale density-matrix renormalization group simulations, we compute the vacancy-anyon binding energy as a function of magnetic field for both the ferromagnetic and antiferromagnetic Kitaev models. Here, we find that anyon binding remains robust within the entire QSL phase for the ferromagnetic Kitaev model but breaks down already inside this phase for the antiferromagnetic Kitaev model. To compute a binding energy several orders of magnitude below the magnetic energy scale, we introduce both a refined definition and an extrapolation scheme based on carefully tailored perturbations.

Xiao, Bo [Oak Ridge National Laboratory (ORNL), Oa↗

Cybersecurity for Distance Relay Protection

This project is a DOE follow-up effort on the CREDC workshop held on September 13, 2018 in Cambridge, MA to discuss cybersecurity of distance relays, which considered the benefits, vulnerabilities and risk mitigations for the use of communication systems in power system protection. The objectives of this project are to define the taxonomy of relay protection and associated communications; define use cases describing approaches to reduce the cyber-attack surface on those protective relays; and evaluate the loss of operational functional capability from changes to communication coverage. Mitigating controls will also be evaluated to understand if there are other approaches to reduce attack surfaces while maintaining communications or partial communications. Distance relays are used to protect transmission lines of approximately 10 to 300 miles in length, by detecting short circuits (i.e., faults) on the lines and then tripping circuit breakers in the substation. Such protection systems are a subset of the power system and they incorporate sensing, logic and communication functions. Protection system exposure to cyberattack could be drastically limited by disconnecting relays from all vulnerable communication systems, but this may adversely impact overall power system performance in the absence of cyberattack. This project began with a use case analysis of protection systems with communications, as summarized in this report. It continued with modeling, testing and evaluation in a miniature power system (MPS), located in the Western Area Power Administration (WAPA) Electric Power Training Center (EPTC). The project also incorporated feedback from two industry meetings held in February and September 2019. The suggested next steps account for and complement the work already underway with DOE/CESER funding: 1. Study the performance of LCD and PC vs. PUTT, which is less reliant on communication system performance and GPS timing references. The PUTT scheme could prove to be more resilient to cyberattack or communications-related disruption. It could also be more tolerant of message re-routing with SDN/SDR communication systems. On the other hand, it will be more vulnerable to false tripping during dynamic events or to loss of the voltage signal. The optimum choice of scheme may depend on the specific power system and risk assessment. This study could provide a new template for evaluation based on business functions. 2. Research and develop new methods to detect and monitor distributed physical attacks, possibly using drones, video sensors, thermal sensors, machine learning and other advanced techniques. This will help mitigate the impact of cyberattack on the protection system, and will also help mitigate the impact of wild fires. 3. Implement a scalable PKI for use in electric utility protection systems. This will encourage widespread adoption of secure authentication methods that are already available, but not widely used at present. This will help secure engineering access to the relays. 4. Investigate the use of SDN in combination with SDR to achieve better cybersecurity and electromagnetic security of the network, incorporating path variability. This would help secure both engineering access and peer-to-peer GOOSE messaging. 5. Perform additional testing, with operator evaluation of “red button” scenarios, PUTT vs. LCD, relay mis-operations, and other cyberattacks in the EPTC. This is an important advantage of testing in the EPTC rather than by computer simulation or even hardware-in-the-loop simulation; the EPTC is already dedicated to managing the situational awareness, operator response times and other human impacts. One of the project objectives was to settle on a common nomenclature for this problem space. We have concluded that the OSI layer model, supplemented by ANSI device numbers and other IEEE standards, is already well-accepted by the industry. The IEEE PSRC knowledge base provides a great deal of public information

24 POWER TRANSMISSION AND DISTRIBUTION↗

A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings

In recent years, there has been a growing trend toward the development of smart buildings that rely on cyber-physical systems (CPS) to optimize occupant comfort, safety, and energy efficiency. To ensure the reliable and efficient operation of CPS with designed control strategies, it is important to evaluate their performance under various scenarios before deploying them in the real world. This is where a Hardware-in-the-loop (HIL) testbed designed for studying sensor and control-related studies in smart buildings can be highly valuable. With the growing threat of cyber-attacks and physical faults targeting smart buildings, it is essential to ensure the security of building operations. A HIL testbed can emulate cyber-attack and physical fault scenarios, allowing researchers to develop and test threat detection and mitigation algorithms. This enables researchers to identify potential issues and optimize the algorithms in a safe and controlled environment before they are deployed in real-world settings, reducing the risk of failures that can negatively impact occupant comfort, safety, and energy efficiency. Therefore, this paper developed a HIL testbed designed for cyber-physical energy systems (e.g. buildings automation system (BAS)) in smart commercial buildings. The HIL testbed is comprised of a real-time building and Heating, Ventilation, and Air-Conditioning (HVAC) emulator using Modelica-based dynamic models, a set of BAS controllers, and a BAS computer server. The data generation capability of the HIL testbed is demonstrated by tracking normal and faulty operating data in the BAS, as well as monitoring detailed network traffic in the local BAS network. Here, this study further demonstrates the HIL testbed’s capability by conducting case studies on real-time physical fault and cyber-attack experiments using a Department of Energy (DOE) prototype commercial building. It is anticipated that the fully functional HIL testbed will be utilized for a variety of sensor and control-related studies, including but not limited to testing, developing, validating of different HVAC control strategies, fault detection & diagnosis, energy monitoring and analysis, cyber security study, etc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ERSAP: Toward Better NP Data-Stream Analytics With Flow-Based Programming

This paper presents an reactive, actor-model and FBP paradigm based framework that we develop to design data-stream processing applications for HEP and NP. This framework encourages a functional decomposition of the overall data processing application into small mono-functional artifacts. Artifacts that are easy to understand, develop, deploy and debug. The fact that these artifacts (actors) are programmatically independent they can be scaled and optimized independently, which is impossible to do for components of the monolithic application. One of the important advantages of this approach is fault tolerance where independent actors can come and go on the data-stream without forcing the entire application to crash. Furthermore, it also makes it is easy to locate the faulty actor in the data pipeline. Due the fact that the actors are loosely coupled, and that the data (inevitably) carries the context, they can run on heterogeneous environments, utilizing different accelerators. This paper describes the main design concepts of the framework and presents a ?proof of concept? application design and deployment results obtain processing on-beam calorimeter streaming data.

Gyurjyan, V.↗

Fault-Tolerant, Real-Time, Multi-Core Computer System

A document discusses a fault-tolerant, self-aware, low-power, multi-core computer for space missions with thousands of simple cores, achieving speed through concurrency. The proposed machine decides how to achieve concurrency in real time, rather than depending on programmers. The driving features of the system are simple hardware that is modular in the extreme, with no shared memory, and software with significant runtime reorganizing capability. The document describes a mechanism for moving ongoing computations and data that is based on a functional model of execution. Because there is no shared memory, the processor connects to its neighbors through a high-speed data link. Messages are sent to a neighbor switch, which in turn forwards that message on to its neighbor until reaching the intended destination. Except for the neighbor connections, processors are isolated and independent of each other. The processors on the periphery also connect chip-to-chip, thus building up a large processor net. There is no particular topology to the larger net, as a function at each processor allows it to forward a message in the correct direction. Some chip-to-chip connections are not necessarily nearest neighbors, providing short cuts for some of the longer physical distances. The peripheral processors also provide the connections to sensors, actuators, radios, science instruments, and other devices with which the computer system interacts.

Gostelow, Kim P.↗

In Situ Velocity‐Strain Sensitivity Near the San Jacinto Fault Zone Analyzed Through Train Tremors

Abstract We utilize train tremors as P‐wave seismic sources to investigate velocity‐strain sensitivity near the San Jacinto Fault Zone. A dense nodal array deployed at the Piñon Flat Observatory is used to detect and identify repeating train energy emitted from a railway in the Coachella valley. We construct P‐wave correlation functions across the fault zone and estimate the spatially averaged dt / t versus strain sensitivity to be 6.25 × 10 4 . Through numerical simulations, we explore how the sensitivity decays exponentially with depth. The optimal solution reveals a subsurface sensitivity of 1.2 × 10 5 and a depth decay rate of 0.05 km −1 . This sensitivity aligns with previous findings but is toward the higher end, likely due to the fractured fault‐zone rocks. The depth decay rate, previously unreported, is notably smaller than assumed in empirical models. This raises the necessity of further investigations of this parameter, which is crucial to study stress and velocity variations at seismogenic depth.

Geology↗

Study of fault-tolerant software technology

Presented is an overview of the current state of the art of fault-tolerant software and an analysis of quantitative techniques and models developed to assess its impact. It examines research efforts as well as experience gained from commercial application of these techniques. The paper also addresses the computer architecture and design implications on hardware, operating systems and programming languages (including Ada) of using fault-tolerant software in real-time aerospace applications. It concludes that fault-tolerant software has progressed beyond the pure research state. The paper also finds that, although not perfectly matched, newer architectural and language capabilities provide many of the notations and functions needed to effectively and efficiently implement software fault-tolerance.

Slivinski, T.↗

Development of a methodology for assessing the safety of embedded software systems

A Dynamic Flowgraph Methodology (DFM) based on an integrated approach to modeling and analyzing the behavior of software-driven embedded systems for assessing and verifying reliability and safety is discussed. DFM is based on an extension of the Logic Flowgraph Methodology to incorporate state transition models. System models which express the logic of the system in terms of causal relationships between physical variables and temporal characteristics of software modules are analyzed to determine how a certain state can be reached. This is done by developing timed fault trees which take the form of logical combinations of static trees relating the system parameters at different point in time. The resulting information concerning the hardware and software states can be used to eliminate unsafe execution paths and identify testing criteria for safety critical software functions.

Garrett, C. J.↗

Analysis of Sample Acquisition Dynamics Using Discrete Element Method

The analysis presented in this paper is conducted in the framework of the Ocean Worlds Autonomy Testbed for Exploration Research and Simulation (OceanWATERS) project, currently under development at NASA Ames Research Center. OceanWATERS aims at designing a simulation environment which allows for testing autonomy of scientific lander missions to the icy moons of our solar system. Mainly focused on reproducing the end effector interaction with the inherent terrain, this paper introduces a novel discrete element method (DEM)-based approach to determine forces and torques acting on the lander’s scoop during the sample acquisition process. An accurate force feedback from the terrain on the scoop is required by fault-detection and autonomous decision-making algorithms to identify when the requested torque on the robotic arm’s joints exceeds the maximum available torque. Knowledge of the terrain force feedback significantly helps evaluating the arm’s links structural properties and properly selecting actuators for the joints. Models available in literature constitute a partial representation of the dynamics of the interaction. As an example, Balovnev derived an analytical expression of the vertical and horizontal force acting on a bucket while collecting a sample as a function of its geometry and velocity, soil parameters and reached depth. Although the model represents an adequate approximation of the two force components, it ignores the direction orthogonal to the scoop motion and neglects the torque. This work relies on DEM analysis to compensate for analytical models’ deficiencies and inaccuracies, i. e. provide force and torque 3D vectors, defined in the moving reference (body) frame attached to the scoop, at each instant of the sample collection process. Results from the first presented analysis relate to the specific OceanWATERS sampling strategy, which consists of collecting the sample through five consecutive passes with increasing depth, each pass following the same circularlinear- circular trajectory. Data is collected given a specific scoop design interacting with two types of bulk materials, which may characterize the surface of icy planetary bodies: snow and ice. Although specifically concerned with the OceanWATERS design, this first analysis provides the expected force trends for similar sampling strategies and allows to deduce phenomenological information about the general scooping process. In order to further instruct the community on the use of DEM tools as a solution to the sampling collection problem, two more analyses have been carried out, mainly focused on reducing the DEM computation time, which increases with a decrease in particle size. After running a set of identical simulations, where the only changing parameter is the size of the spherical particle, it is observed that the resulting force trajectories, starting from a given particle size, converge to the true trend. It is deducible that a further decrease in size yields negligible improvements in the accuracy, while it sensibly increases computation time. A final analysis aims at discussing limitations of approximating bulk material particles having a complex shape, e. g. ice fragments, with spheres, by comparing force trends resulting in the two cases for the same simulation scenario.

Catanoso, Damiana↗

On the Language of Reliability: A System Engineer Perspective

In its classical definition, risk is defined by three elements: what can go wrong, what are its consequences, and how likely is it to occur? While this definition makes sense in a regulatory-based framework where for the current fleet of operating light water reactors (LWRs), the risks associated with nuclear power plants typically are characterized in terms of core damage and large early release frequency (LERF), this approach does not provide a useful snapshot of the health of the plant from a broader perspective. This is due to the very narrow context in which the term “risk” typically is defined as nuclear safety aspects that have the potential to impact public health. In this paper, we take the viewpoint of nuclear safety that is reflective of the current fleet of operating LWRs for which core damage frequency and LERF are appropriate metrics. For other advanced reactor designs, other more applicable technology neutral metrics of reactor safety metrics would be specified. A possible alternate path would start by redefining the word risk with a broader meaning that better reflects the needs of a system health and asset management decision-making process. Rather than asking how likely an event could occur (in probabilistic terms), we can ask how far this event is from occurring. Our approach starts by defining and quantifying component and system health in terms of a “distance” between its actual and limiting conditions, i.e., determination of the margin that exists between the current state/condition and the state where the component/system is no longer capable of achieving its intended function. A margin is a measure that is more reflective of the current state or performance of a component, and therefore more closely tied to decisions that are made on an ongoing basis. Further, we will show how, given the data available from plant equipment reliability and monitoring (e.g., pump vibration data) and prognostic (e.g., component remaining useful life estimation) data, a margin can be described and determined for all types of maintenance approaches (e.g., corrective or predictive maintenance). We show how classical reliability models (e.g., fault trees) can be used to quantify the system margin provided component margin values. In the approach described in this paper, the propagation of margin values through classical reliability models are not performed using classical probabilistic calculations applied to sets (as performed in a typical plant probabilistic risk assessment). Instead, we show how it is possible to propagate margin values through Boolean logic gates (i.e., AND and OR operators) through distance-based operations.

97 MATHEMATICS AND COMPUTING↗