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At least 235 records · Page 13

Methodology for Designing Fault-Protection Software

A document describes a methodology for designing fault-protection (FP) software for autonomous spacecraft. The methodology embodies and extends established engineering practices in the technical discipline of Fault Detection, Diagnosis, Mitigation, and Recovery; and has been successfully implemented in the Deep Impact Spacecraft, a NASA Discovery mission. Based on established concepts of Fault Monitors and Responses, this FP methodology extends the notion of Opinion, Symptom, Alarm (aka Fault), and Response with numerous new notions, sub-notions, software constructs, and logic and timing gates. For example, Monitor generates a RawOpinion, which graduates into Opinion, categorized into no-opinion, acceptable, or unacceptable opinion. RaiseSymptom, ForceSymptom, and ClearSymptom govern the establishment and then mapping to an Alarm (aka Fault). Local Response is distinguished from FP System Response. A 1-to-n and n-to- 1 mapping is established among Monitors, Symptoms, and Responses. Responses are categorized by device versus by function. Responses operate in tiers, where the early tiers attempt to resolve the Fault in a localized step-by-step fashion, relegating more system-level response to later tier(s). Recovery actions are gated by epoch recovery timing, enabling strategy, urgency, MaxRetry gate, hardware availability, hazardous versus ordinary fault, and many other priority gates. This methodology is systematic, logical, and uses multiple linked tables, parameter files, and recovery command sequences. The credibility of the FP design is proven via a fault-tree analysis "top-down" approach, and a functional fault-mode-effects-and-analysis via "bottoms-up" approach. Via this process, the mitigation and recovery strategy(s) per Fault Containment Region scope (width versus depth) the FP architecture.

Barltrop, Kevin↗

Structured Light-Based Hazard Detection For Planetary Surface Navigation

This paper describes a structured light-based sensor for hazard avoidance in planetary environments. The system presented here can also be used in terrestrial applications constrained by reduced onboard power and computational complexity and low illumination conditions. The sensor is on a calibrated camera and laser dot projector system. The onboard hazard avoidance system determines the position of the projected dots in the image and through a triangulation process detects potential hazards. The paper presents the design parameters for this sensor and describes the image based solution for hazard avoidance. The system presented here was tested extensively in day and night conditions in Lunar analogue environments. The current system achieves over 97 detection rate with 1.7 false alarms over 2000 images.

Nefian, Ara↗

New Release Products: Combining the Relativistic Electron Alert System for Exploration With Other Early Indicators of Solar Energetic Particle Events

The Relativistic Electron Alert System for Exploration (“REleASE”) exploits the prompt arrival of near-relativistic electrons in the Earth/moon system to rapidly warn human explorers of the imminent arrival of hazardous energetic ions from solar energetic particle (SEP) events. Since 2008, the REleASE system has been implemented in near-real-time, initially with electron observations from SOHO, and since 2017 with additional observations from ACE as “HESPERIA REleASE”: upcoming opportunities will utilize IMAP and SWFO observations. REleASE is undergoing performance validation as part of the NASA/CCMC SEP scoreboarding process (https://ccmc.gsfc.nasa.gov/scoreboards/sep/). The ongoing return of STEREO-A to the vicinity of Earth provides observations of radio waves in near-real-time and allows REleASE to be combined with the identification of type-III radio bursts, which provide additional evidence of particle escape from the Sun (the use of type-III bursts for SEP forecasting was pioneered by “ESPERTA” developed by Laurenza et al., 2009). The aim of this planned “REleASE+” system is to further reduce the rate of false alarms. Another opportunity, facilitated by the CLEAR space weather center (PI L. Zhao, Univ. Michigan) will combine REleASE with “SEPSTER” (Richardson et al., 2018) to reduce the high rate of false alarms produced by SEPSTER, which is triggered by reports of CMEs, the vast majority of which do not result in detected SEP ion events. This presentation will give a status update on these objectives.

solar particle events↗

State Machine Operation of Complex Systems

Operation of complex systems which depend on one or more other systems with many process variables often operate in more than one state. For each state there may be a variety of parameters of interest, and for each of these, one may require different alarm limits, different archiving needs, and have different critical parameters. Relying on operators to reliably change 10s-1000s of parameters for each system for each state is unreasonable.Not changing these parameters results in alarms being ignored or disabled, critical changes missed, and/or possible data archiving problems.To reliably manage the operation of complex systems, such as cryomodules (CMs), Fermilab is implementing state machines for each CM and an over-arching state machine for the PIP-II superconducting linac (SCL). The state machine transitions and operating parameters are stored/restored to/from a configuration database. Proper implementation of the state machines will not only ensure safe and reliable operation of the CMs, but will help ensure reliable data quality. A description of PIP-II SCL, details of the state machines, and lessons learned from limited use of the state machines in recent CM testing will be discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

State Machine Operation of Complex Systems

Operation of complex systems which depend on one or more other systems with many process variables often operate in more than one state. For each state there may be a variety of parameters of interest, and for each of these, one may require different alarm limits, different archiving needs, and have different critical parameters. Relying on operators to reliably change 10s-1000s of parameters for each system for each state is unreasonable. Not changing these parameters results in alarms being ignored or disabled, critical changes missed, and/or possible data archiving problems. To reliably manage the operation of complex systems, such as cryomodules (CMs), Fermilab is implementing state machines for each CM and an over-arching state machine for the PIP-II superconducting linac (SCL). The state machine transitions and operating parameters are stored/restored to/from a configuration database. Proper implementation of the state machines will not only ensure safe and reliable operation of the CMs, but will help ensure reliable data quality. A description of PIP-II SCL, details of the state machines, and lessons learned from limited use of the state machines in recent CM testing will be discussed.

43 PARTICLE ACCELERATORS↗

Stochastic Template Bank for Gravitational Wave Searches for Precessing Neutron Star-Black Hole Coalescence Events

Gravitational wave searches to date have largely focused on non-precessing systems. Including precession effects greatly increases the number of templates to be searched over. This leads to a corresponding increase in the computational cost and can increase the false alarm rate of a realistic search. On the other hand, there might be astrophysical systems that are entirely missed by non-precessing searches. In this paper we consider the problem of constructing a template bank using stochastic methods for neutron star-black hole binaries allowing for precession, but with the restrictions that the total angular momentum of the binary is pointing toward the detector and that the neutron star spin is negligible relative to that of the black hole. We quantify the number of templates required for the search, and we explicitly construct the template bank. We show that despite the large number of templates, stochastic methods can be adapted to solve the problem. We quantify the parameter space region over which the non-precessing search might miss signals.

gravitational wave↗

Control System Upgrade for Battery State-of-Charge Indications

The Advanced Test Reactor (ATR) Complex at Idaho National Laboratory (INL) relies on Battery Backed Power (BBP) systems and Uninterruptible Power Supplies (UPS) to ensure continuous power supply to critical components. This project aims to enhance the reliability and functionality of the battery monitoring and control systems by updating the State-of-Charge (SOC) system, Programmable Logic Controller (PLC), and Human-Machine Interface (HMI) for the nuclear safety-related battery banks. The current system, while functional, has areas for improvement, particularly in recharging calculations and alarm functions. The project objectives include developing flow charts, programming the new PLC and HMI, conducting bench tests, and updating design documentation. Additionally, the project ensures compliance with safety standards, develops training materials, creates comprehensive documentation, and integrates seamlessly with existing ATR infrastructure. The new SOC system is designed to be scalable for future upgrades, improve efficiency, enhance data accuracy, implement redundancy features, and achieve project goals within budget constraints while considering environmental impact. The methodology involved familiarizing with BBP and UPS systems, collecting current readings, rescaling signals, learning ladder logic, and updating the HMI. The transition from SLC 5/03 PLC using RS Logix 500 to CompactLogix 5380 using Studio 5000 was a key step. Despite challenges in transferring outdated PLC ladder logic and HMI code, starting from scratch led to a more accurate and efficient monitoring system, contributing to improved safety and operational efficiency. The project is currently awaiting approval of the Engineering Calculation and Analysis Report (ECAR) before implementation.

42 - ENGINEERING↗

Speech-Enhanced and Context Dependent Alerts: Future Implications for Spacecraft Design

In the future, NASA missions will involve many different space vehicles, habitats, and surface assets working together to provide safe, productive environments for crew. Because these systems will be provided by multiple commercial companies working with NASA, it will be very different from missions of the past, bringing new challenges. One of the challenges is related to whether NASA should move beyond simple tone annunciation alerting systems, to more advanced systems that include speech. The other is related to determining the level of consistency required of safety-critical alert systems across spacecraft. Two studies were completed to address these important issues. The first study investigated the advantages and disadvantages of a tone+speech alert relative to the traditional tone-only alert. Results indicate that speech-enhanced alerts initially take longer to silence (the default action to which NASA personnel are trained), due to the need to listen to the entire message, but ultimately provided for faster understanding of the alert situation. Speech-enhanced alerts were also preferred by a large majority of crew-like study participants. An unexpected finding was that participants took longer to respond to tone-only alerts that were heard in the same session as speech-enhanced alerts. Participants waited to hear a speech message even for alerts they were trained to know did not contain speech components. This performance error is believed to be due to negative transfer of training. A second study focused on task and alert performance using a common set of tones across two contexts (e.g., vehicles, habitats, suits) versus performance with a different set of tones for each context. Participants were able to manage two different alert sets successfully; results indicate that discriminability of the two alert sets played a major role in their success. Implications for the design of spacecraft alerts are discussed, and future areas of research are identified.

alerts↗

Hidden Markov models and neural networks for fault detection in dynamic systems

Neural networks plus hidden Markov models (HMM) can provide excellent detection and false alarm rate performance in fault detection applications, as shown in this viewgraph presentation. Modified models allow for novelty detection. Key contributions of neural network models are: (1) excellent nonparametric discrimination capability; (2) a good estimator of posterior state probabilities, even in high dimensions, and thus can be embedded within overall probabilistic model (HMM); and (3) simple to implement compared to other nonparametric models. Neural network/HMM monitoring model is currently being integrated with the new Deep Space Network (DSN) antenna controller software and will be on-line monitoring a new DSN 34-m antenna (DSS-24) by July, 1994.

Smyth, Padhraic↗

Enhanced Bank of Kalman Filters Developed and Demonstrated for In-Flight Aircraft Engine Sensor Fault Diagnostics

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.

Kobayashi, Takahisa↗

Deliberate Motion Analytics Applied to CUAS Sensor Fusion

The Advanced Reactor Safeguards and Security (ARSS) program in the Department of Energy’s Office of Nuclear Energy (DOE-NE) seeks to identify new technology solutions for safeguards and security challenges associated with domestic deployment of advanced nuclear reactors. Research in the ARSS program is investigating alternative physical protection system (PPS) approaches that leverage new detection technologies. This report shows test results from a new form of artificial intelligence (AI) that is called deliberate motion analytics (DMA) when used to spatially and temporally fuse active radar and passive radio frequency (RF) detection that significantly improves detection of uncrewed aircraft systems (UASs). DMA is designed to filter out false positive alarms yet provide highly reliable intrusion detection at nuclear power plants (NPPs) and advanced small modular reactor (ASMR) perimeters. This form of AI is considered to be an enabling technology for security of the future and supports the ARSS investigation of alternative PPSs.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Performance evaluation of a Doppler radar system for wind shear detection

Nonlinear stochastic differential equations are used to model wind shear, and extended Kalman filters are used to generate state estimates from measurements received from a Doppler radar onboard an aircraft. Likelihood-ratio tests are then used to detect the presence of wind shear. The performance of the system is evaluated by deriving theoretical expressions for the false alarm and miss error probabiilties. The approach uses a Fokker-Planck equation. The overall methodology is general and should be of interest in other applications.

Khalaf, Camille S.↗

Off-the-shelf real-time monitoring of satellite constellations in a visual 3-D environment

The multimission spacecraft analysis system (MSAS) data monitor is a generic software product for future real-time data monitoring and analysis. The system represents the status of a satellite constellation through the shape, color, motion and position of graphical objects floating in a three dimensional virtual reality environment. It may be used for the monitoring of large volumes of data, for viewing results in configurable displays, and for providing high level and detailed views of a constellation of monitored satellites. It is considered that the data monitor is an improvement on conventional graphic and text-based displays as it increases the amount of data that the operator can absorb in a given period, and can be installed and configured without the requirement for software development by the end user. The functionality of the system is described, including: the navigation abilities; the representation of alarms in the cybergrid; limit violation; real-time trend analysis, and alarm status indication.

Schwuttke, Ursula M.↗

Personal Cabin Pressure Monitor and Warning System

A cabin pressure altitude monitor and warning system provides a warning when a detected cabin pressure altitude has reached a predetermined level. The system is preferably embodied in a portable, pager-sized device that can be carried or worn by an individual. A microprocessor calculates the pressure altitude from signals generated by a calibrated pressure transducer and a temperature sensor that compensates for temperature variations in the signals generated by the pressure transducer. The microprocessor is programmed to generate a warning or alarm if a cabin pressure altitude exceeding a predetermined threshold is detected. Preferably, the microprocessor generates two different types of warning or alarm outputs, a first early warning or alert when a first pressure altitude is exceeded. and a second more serious alarm condition when either a second. higher pressure altitude is exceeded, or when the first pressure altitude has been exceeded for a predetermined period of time. Multiple types of alarm condition indicators are preferably provided, including visual, audible and tactile. The system is also preferably designed to detect gas concentrations and other ambient conditions, and thus incorporates other sensors, such as oxygen, relative humidity, carbon dioxide, carbon monoxide and ammonia sensors, to provide a more complete characterization and monitoring of the local environment.

Jan A Zysko↗

Hideen Markov Models and Neural Networks for Fault Detection in Dynamic Systems

None given. (From conclusion): Neural networks plus Hidden Markov Models(HMM)can provide excellene detection and false alarm rate performance in fault detection applications. Modified models allow for novelty detection. Also covers some key contributions of neural network model, and application status.

space network↗

Automatic Monitoring Of Complicated Systems

Collection of computer programs developed for expert computer system performing complicated, tedious, and repetitive portions of analysis of telemetry data from spacecraft. Provides nonstop, accurate surveillance of incoming data, also frees operators to concentrate their expertise on unexpected abnormal operating conditions. When unable to explain discrepancies with certainty resulting from data out of synchronization or other falso-alarm conditions, triggers alarm devices to request assistance from designated individuals. Concept useful in such terrestrial systems as production lines, power-distribution networks, chemical processes, large airplanes, and other assemblies of interdependent equipment.

Schwuttke, Ursula M.↗

A critical review of existing and emerging technologies and systems to optimize solid waste management for feedstocks and energy conversion

Solid waste generation and its accumulation is increasing at an alarming pace due to population growth and urbanization posing severe risks to health, safety, and natural ecosystems. Herein this review strategically addresses the challenges and solutions to increasing the sustainability footprint of solid waste management (SWM) systems by revealing multipronged approaches that reduce solid waste and handling costs while generating revenue and reducing greenhouse gas and related emissions. For example, the United States sends ~150 million tons of waste to landfills, which is composed of over 75% organic and recyclable materials having a potential to be diverted to alternative scenarios. The emergence of an automated upstream and downstream sorting process for solid waste to increase material diversion from landfills is a promising approach for creating sustainable SWM. The utilization of artificial-intelligence-enabled smart and automated systems at the home and industrial scales, comprehensive public re-education including awareness of the adverse effects of landfilled waste on the ecosystem, and more eco-friendly product development are required to significantly reduce landfills and their negative footprint.

09 BIOMASS FUELS↗

An adaptive tracking observer for failure-detection systems

The design problem of adaptive observers applied to linear, constant and variable parameters, multi-input, multi-output systems, is considered. It is shown that, in order to keep the observer's (or Kalman filter) false-alarm rate (FAR) under a certain specified value, it is necessary to have an acceptable proper matching between the observer (or KF) model and the system parameters. An adaptive observer algorithm is introduced in order to maintain desired system-observer model matching, despite initial mismatching and/or system parameter variations. Only a properly designed adaptive observer is able to detect abrupt changes in the system (actuator, sensor failures, etc.) with adequate reliability and FAR. Conditions for convergence for the adaptive process were obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors and accurate and fast parameter identification, in both deterministic and stochastic cases.

Sidar, M.↗