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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A new APDS approach - alarm processing based on alarm prioritization - 201

We take for granted that the advances in technology bring improvements to the conditions in which humans perform activities associated to them. Is that the case for digital alarm systems in nuclear power plants? The answer is not that simple. A review of the related literature, shows that still, the single most significant problem with alarm systems, is the large number of alarm messages presented to the operator at once. This is an issue that affects analog I and C control rooms with conventional annunciators and gets aggravated in digital I and C based control rooms. Digital alarm systems present the alarms in the form of lists in computer screens. This kind of presentation forces the operator to scroll or navigate pages to review the active alarms. Also, the alarm lists do not allow the operator to apply the pattern recognition practices acquired during training when using with fixed position alarm systems. An Alarm Processing and Diagnostic System (APDS) facilitates the alarm monitoring task by applying alarm reduction techniques based on alarm priorities. It allows the operators to focus on the most important alarms during plant upsets. A new generation of APDS should be based in an improved alarm analysis methodology. To develop such methodology, Tecnatom reviewed applicable standards and our own alarm analysis experiences. This paper documents the process and conclusions of the methodology development. (authors)

42 ENGINEERING↗
DOE OSTI2016

Retrospective analysis of pulse oximeter alarm settings in an intensive care unit patient population

Background: The cacophony of alerts and alarms in a hospital produced by medical devices results in alarm fatigue. The pulse oximeter is one of the most common sources of alarms. One of the ways to reduce alarm rates is to adjust alarm settings at the bedside. This study is aimed to retrospectively examine individual pulse oximeter alarm settings on alarm rates and inter- and intra- patient variability. Methods: Nine hundred sixty-two previously collected intensive care unit (ICU) patient records were obtained from the Multiparameter Intelligent Monitoring in Intensive Care II Database (Beth Israel Deaconess Medical Center, Boston, MA). Inclusion criteria included patient records that contained SpO 2 trend data sampled at 1 Hz for at least 1 h and a matching clinical record. SpO 2 alarm rates were simulated by applying a range of thresholds (84, 86, 88, and 90 %) and delay times (10 to 60 s) to the SpO 2 data. Patient records with at least 12 h of SpO 2 data were examined for the variability in alarm rate over time. Results: Decreasing SpO 2 thresholds and increasing delay times resulted in decreased alarm rates. A limited number of patient records accounted for most alarms, and this number increased as alarm settings loosened (the top 10 % of patient records were responsible for 57.4 % of all alarms at an SpO 2 threshold of 90 % and 15 s delay and 81.6 % at an SpO 2 threshold of 84 % and 45 s delay). Alarm rates were not consistent over time for individual patients with periods of high and low alarms for all alarm settings. Conclusion: Pulse oximeter SpO 2 alarm rates are variable between patients and over time, and the alarm rate and the extent of inter- and intra-patient variability can be affected by the alarm settings. Personalized alarm settings for a patient’s current status may help to reduce alarm fatigue for nurses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Employing Eye Trackers to Reduce Nuisance Alarms

When process operators anticipate an alarm prior to its annunciation, that alarm loses information value and becomes a nuisance. This study investigated using eye trackers to measure and adjust the salience of alarms with three methods of gaze-based acknowledgement (GBA) of alarms that estimate operator anticipation. When these methods detected possible alarm anticipation, the alarm’s audio and visual salience was reduced. A total of 24 engineering students (male = 14, female = 10) aged between 18 and 45 were recruited to predict alarms and control a process parameter in three scenario types (parameter near threshold, trending, or fluctuating). The study evaluated whether behaviors of the monitored parameter affected how frequently the three GBA methods were utilized and whether reducing alarm salience improved control task performance. The results did not show significant task improvement with any GBA methods (F(3,69) = 1.357, p = 0.263, partial η 2 = 0.056). However, the scenario type affected which GBA method was more utilized (X 2 (2, N = 432) = 30.147, p < 0.001). Alarm prediction hits with gaze-based acknowledgements coincided more frequently than alarm prediction hits without gaze-based acknowledgements (X 2 (1, N = 432) = 23.802, p < 0.001, OR = 3.877, 95% CI 2.25–6.68, p < 0.05). Participant ratings indicated an overall preference for the three GBA methods over a standard alarm design (F(3,63) = 3.745, p = 0.015, partial η 2 = 0.151). This study provides empirical evidence for the potential of eye tracking in alarm management but highlights the need for additional research to increase validity for inferring alarm anticipation.

99 - GENERAL AND MISCELLANEOUS↗
NASA NTRS2016

Memo on Speech Alarms: Replication and Validation of Results

Caution and warning (C&W) alarms help people to quickly and efficiently identify situations that are of immediate danger or would escalate to a safety critical level. Tones are highly salient and have been traditionally used for caution and warning alarms. However, research shows that tone alarms can have an unwanted startle effect that hinders operator decision making. Speech alarms are good alternatives to tone alarms because they require less training and are less startling. They have been in use for decades for caution and warning systems in commercial airplanes and in buildings. Speech alarms have been considered for space flight use by the National Aeronautics and Space Administration’s (NASA) Astronaut Office and by its Orion Program. To investigate whether performance with various types of speech alarms was similar to performance with the currently used tone alarms, a study was conducted in 2010. The results showed faster identification times of speech alarms as well as higher acceptance rates from participants. However, the presentation of the alarms had a variable onset time due to software. The current research project was funded to address this issue by collecting new data with alarms having nonvariable onset time and to validate the alarms in the Human Exploration Research Analog (HERA). This report describes the two studies: a laboratory experiment comparing tone and speech alarms, and an evaluation in the HERA facility.

warning signals↗
DOE OSTI2019

Report for 2.2.1 Task 5: Develop and Document a State-Based Alarm System for a Nuclear Power Plant Control Room Using Machine Learning. Light Water Reactor Sustainability Program report

In legacy control rooms the operators might have 20 to 30 alarms to deal with on 12 control boards, during a reactor trip. The new digital alarm system in the upgraded control room will display between 150 and 200 alarm points on a single screen. This overload of information prevents the operators from identifying any abnormal alarms quickly without having to scroll through the alarm list looking for the abnormal alarms. One way to tackle this problem could be to attempt to create a state-based alarm system which would identify plant states and would identify which alarms are expected in those states and suppress them from the alarm screen so that any unexpected alarms would be displayed and easily identified to the operators. This can be done today but is very labor intensive in that an operator or training instructor would be required to run scenarios and log the alarms to be suppressed. The hope is that Machine Learning (ML) can provide an alternative solution with less manual effort required.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Central alarm station interface for situation awareness

A method for analyzing security alarms is provided. The method comprising receiving alarm data from a number of security sensors generating alarms, wherein the alarm data includes spatio-temporal data regarding where and when an alarm is triggered. The alarm data is displayed on a user interface. The alarm data is analyzed for spatio-temporal relationships among the alarms according to a number of pattern recognition algorithms. The alarms are identified as genuine alarms if a discernable pattern is recognized among the alarms.

Speed, Ann E.↗
NASA NTRS1996

Remote Monitor Alarm System

A remote monitor alarm system monitors discrete alarm and analog power supply voltage conditions at remotely located communications terminal equipment. A central monitoring unit (CMU) is connected via serial data links to each of a plurality of remote terminal units (RTUS) that monitor the alarm and power supply conditions of the remote terminal equipment. Each RTU can monitor and store condition information of both discrete alarm points and analog power supply voltage points in its associated communications terminal equipment. The stored alarm information is periodically transmitted to the CMU in response to sequential polling of the RTUS. The number of monitored alarm inputs and permissible voltage ranges for the analog inputs can be remotely configured at the CMU and downloaded into programmable memory at each RTU. The CMU includes a video display, a hard disk memory, a line printer and an audio alarm for communicating and storing the alarm information received from each RTU.

Stute, Robert A.↗
DOE OSTI2017

Unstated assumptions in alarm management - 202

Alarm management in the process industries has been an increasing area of activity since the first publications of EEMUA 191 in 1999 and ISA18.2 in 2008. Most major oil and chemical companies have adopted some or all of the metrics for alarm management presented in these documents. However, simply targeting for these metrics might not be the best course of action for a company. Many of the metrics involve assumptions or logic not explicitly stated in the guidelines, assumptions that might not be valid for a given console or plant. In other cases, metrics are the result of implied, rather than explicit, relationships between alarm guidelines. Again, the implied connection might not be true under certain circumstances. Understanding these unstated underpinnings of alarm management can facilitate the implementation of a useful and efficient alarm management program. This paper explores some of the key unstated assumptions in alarm management and how changes in those assumptions can alter both the interpretation of alarm metrics as well as what metrics are utilized. (authors)

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Analysis and Recommendation of Alpha-Beta Continuous Air Monitor Alarm Setpoints for the RPL Stack Exhaust

The Radiochemical Processing Laboratory (RPL) alpha-beta continuous air monitor (CAM) is used for real-time detection of “artificial” alpha-beta particulates from the stack exhaust. The CAM interfaces with software developed by the Pacific Northwest National Laboratory—called the “PNNL OS3300 Alpha-Beta Monitoring Software”—that provides real-time estimates of alpha-beta air concentrations and integrated activities that are calculated from measured CAM counts. The OS3300 software has alarm setpoints that can be used to provide an early indication of larger releases, that if allowed to persist, could approach defined dose limits. This report performs a detailed review of historical and current alarm setpoints used at RPL, including discussion of the technical basis used in their development, analysis of alarm frequencies using measured historical data, and performs a detailed dose assessment using more realistic release scenarios, meteorology, and adjustment factors used in estimating released stack activity. Based on the results, the alpha and beta air concentration alarm setpoints will remain 1.77 × 10 -8 µCi/ml and 3.47 × 10 -8 µCi/ml, respectively; and the alpha and beta integrated activity alarm setpoints will remain 70.22 µCi and 137.63 µCi, respectively. These setpoints achieve the right operational balance in identifying larger releases from planned radiological work at RPL, without being overly conservative so as to cause nuisance alarming. Furthermore, implied doses associated with these setpoints are below defined and regulatory limits.

325RPL↗
DOE OSTI2015

Incorporating realistic conservatism into criticality alarm placement and emergency response: a regulatory perspective - 14425

Review of historical process plant criticality accidents shows that their consequences vary widely and are extremely difficult to predict accurately. Because of the wide variability and inherent uncertainty in estimating consequences, criticality detector placement analysis and consequence estimation for emergency response typically utilize very conservative assumptions with regard to the total fissions, time-dependent fission rate, and intervening shielding. For detector placement, a 'minimum accident of concern' is typically defined, whereas emergency consequence evaluations typically define a maximum fission source term. These require different mindsets because what is conservative for one type of analysis may be non-conservative for the other. While some conservatism is commonly practiced in both cases, excessive conservatism can result in a net increase in risk, such as resulting from inadvertent alarm activations, that can be costly to operations and counterproductive to safety. Conversely, reliance on very detailed calculational models to reduce conservatism could increase the number and complexity of controls, such as shielding for dose mitigation. Deterministic regulatory criteria have also been applied for determining where criticality detectors are to be deployed and what areas must be evacuated in the event of an accident. This paper explores several issues associated with criticality alarm placement and emergency response from a regulatory perspective. This paper will discuss insights gained from historical fuel facility accidents and significant events regarding the inherent risk of criticality, the most likely locations for criticality to occur, and the most probable characteristics of a critical excursion. This will include discussion of the previously disputed relevance of the United States Nuclear Regulatory Commission's (USNRC's) longstanding model for a critical excursion. While USNRC regulations deterministically require dual alarm coverage in all areas having greater than a 'critical mass' of fissionable material, a process is provided to grant exemptions when a risk-informed argument is technically justified. Similar risk-informed considerations have been used to justify compensatory measures allowing limited operation during periods of alarm system outage due to component failure or maintenance. This paper will explore the application of risk information and performance history to address requirements for criticality alarm system coverage, granting exemptions from deterministic criteria, allowing compensatory measures during system outages, determining evacuation areas and routes, and assessing the significance associated with alarm system issues. Finally, the impact of shielding on the USNRC's regulatory risk basis and approved subcritical margin will be reviewed. (authors)

42 ENGINEERING↗
DOE OSTI2020

Report for 2.2.1 Task 5: Develop and Document a State-Based Alarm System for a Nuclear Power Plant Control Room Using Machine Learning

Idaho National Laboratory (INL) has contracted IFE to support human factors research and the development of leading-edge technology to support control room operators as the U.S. fleet undergoes modernization and digitalization in legacy plants and control rooms. As the nuclear industry starts to shift to more digital controls and systems, these upgrades provide more information to the main control room in the form of digital signals and values. Also, an increase in the number of alarms points is provided by the vendors. New digital control rooms shift from main control boards to soft controls, and alarm panels to a single display. This change to a single display has created a problem of alarm waterfall, a situation in which the addition of new alarm points causes an overload of information to the operator during either a plant disturbance or other than normal full power operations. IFE’s goal is to find a workable solution to assist operators in both handling and understanding incoming alarms during emergency situations under these waterfall conditions.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2007

Multiple-Parameter, Low-False-Alarm Fire-Detection Systems

Fire-detection systems incorporating multiple sensors that measure multiple parameters are being developed for use in storage depots, cargo bays of ships and aircraft, and other locations not amenable to frequent, direct visual inspection. These systems are intended to improve upon conventional smoke detectors, now used in such locations, that reliably detect fires but also frequently generate false alarms: for example, conventional smoke detectors based on the blockage of light by smoke particles are also affected by dust particles and water droplets and, thus, are often susceptible to false alarms. In contrast, by utilizing multiple parameters associated with fires, i.e. not only obscuration by smoke particles but also concentrations of multiple chemical species that are commonly generated in combustion, false alarms can be significantly decreased while still detecting fires as reliably as older smoke-detector systems do. The present development includes fabrication of sensors that have, variously, micrometer- or nanometer-sized features so that such multiple sensors can be integrated into arrays that have sizes, weights, and power demands smaller than those of older macroscopic sensors. The sensors include resistors, electrochemical cells, and Schottky diodes that exhibit different sensitivities to the various airborne chemicals of interest. In a system of this type, the sensor readings are digitized and processed by advanced signal-processing hardware and software to extract such chemical indications of fires as abnormally high concentrations of CO and CO2, possibly in combination with H2 and/or hydrocarbons. The system also includes a microelectromechanical systems (MEMS)-based particle detector and classifier device to increase the reliability of measurements of chemical species and particulates. In parallel research, software for modeling the evolution of a fire within an aircraft cargo bay has been developed. The model implemented in the software can describe the concentrations of chemical species and of particulate matter as functions of time. A system of the present developmental type and a conventional fire detector were tested under both fire and false-alarm conditions in a Federal Aviation Administration cargo-compartment- testing facility. Both systems consistently detected fires. However, the conventional fire detector consistently generated false alarms, whereas the developmental system did not generate any false alarms.

Hunter, Gary W.↗
DOE OSTI2026

Field-based AFDD for refrigerant undercharge in residential HVAC systems: enhancing reliability through false alarm mitigation

This study evaluated rule-based and machine learning (ML) based automated fault detection and diagnostics (AFDD) algorithms for detecting refrigerant undercharge faults in residential heating, ventilation, and air conditioning (HVAC) systems, using actual building data and a minimal set of features. The ML-based algorithms included Decision Tree (DT) and K-Nearest Neighbors (KNN). Both the rule-based and ML-based algorithms demonstrated the capability to detect refrigerant undercharge faults of -30% or more. Both types of algorithms exhibited false alarms before the implementation of a false alarm mitigation algorithm, which motivated the development of such a mitigation strategy. After applying the mitigation, false alarms were substantially reduced, with the rule-based algorithm decreasing to 0.6% and the ML-based algorithms reaching 0%, while maintaining strong detection performance. Although the rule-based algorithm initially showed lower performance compared to the ML-based algorithms, its detection accuracy improved after mitigation to a level comparable to the ML-based algorithms. These results confirm that combining false alarm mitigation with both rule-based and ML-based AFDD algorithms significantly enhances practical reliability while preserving robust fault detection capabilities. Furthermore, the findings demonstrate the potential for field deployment of these algorithms in residential HVAC systems and highlight the importance of minimizing false alarms.

False Alarm↗
DOE OSTI2017

Plan for IER-443 Testing of the Y-12 and AWE Criticality Accident Alarm System Detectors at the Godiva IV Burst Reactor

This document provides the scope and details of the “Plan for Testing the Y-12 and AWE Criticality Accident Alarm System Detectors at the Godiva IV Burst Reactor”. Due to the relative simplicity of the testing goals, scope, and methodology, the NCSP Manager approved execution of the test when ready. No preliminary CED-1 or final design CED-2 reports were required or issued. The test will subject Criticality Accident Alarm System (CAAS) detectors supplied by Y- 12 and AWE to very intense and short duration mixed neutron and gamma radiation fields. The goals of the test will be to (1) substantiate functionality, for both existing and newly acquired Y- 12 CAAS detectors, and (2) the ability of the AWE detectors to provide quality temporal dose information after a hypothetical criticality accident. ANSI/ANS-8.3.1997 states that the “system shall be sufficiently robust as to actuate an alarm signal when exposed to the maximum radiation expected”, which has been defined at Y-12, in Documented Safety Analyses (DSAs), to be a dose rate of 10 Rad/s. ANSI/ANS-8.3.1997 further states that “alarm actuation shall occur as a result of a minimum duration transient” which may be assumed to be 1 msec. The pulse widths and dose rates which will be achieved in this test will exceed these requirements. Pulsed radiation fields will be produced by the Godiva IV fast metal burst reactor at the National Criticality Experimental Research Center (NCERC) at the Nevada National Security Site (NNSS). The magnitude of the pulses and the relative distances to the detectors will be varied to afford a wide range of radiation fluence and pulse widths. The magnitude of the neutron and gamma fields will be determined by reactor temperature rise to fluence and dose conversions which have been previously established through extensive measurements performed under IER-147. The requirements for CAAS systems to detect and alarm under a “minimum accident of concern” as well as other functional requirements specified in ANSI/ANS-8.3.1997, are not included in the test. Routine and periodic maintenance and calibrations performed at Y-12 and AWE are intended to provide adequate confirmation for meeting these requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Analysis and Recommendation of Tritium Gas Continuous Air Monitor Alarm Setpoints for the RPL Stack Exhaust

The Radiochemical Processing Laboratory (RPL) tritium continuous air monitor (CAM) is used for near real-time detection of tritium gas (i.e., elemental tritium [HT] and tritiated water vapor [HTO]) in the stack exhaust. The CAM interfaces with software developed by the Pacific Northwest National Laboratory (PNNL)—called the “PNNL OS3700 Tritium Monitoring Software”—that provides near real-time estimates of tritium gas air concentrations and integrated daily activities that are calculated from measured CAM counts. The OS3700 software implements alarm setpoints to alert the facility of larger tritium gas releases that if allowed to persist, could begin to challenge permitted emission and established dose constraints. This report performs a detailed review of historical and current tritium alarm setpoints used at RPL, including discussion of the technical basis used in their development, analysis of alarm frequencies using measured historical data, and performs a detailed dose assessment using more realistic release scenarios and meteorology. Based on the results, the tritium air concentration and integrated daily tritium activity alarm setpoints will remain 2.0 × 10 -5 µCi/ml and 25 Ci/day, respectively. These setpoints achieve the right operational balance in identifying larger releases from planned tritium work at RPL, without being overly conservative so as to cause nuisance alarming. Furthermore, implied doses associated with these setpoints are well below defined and regulatory limits.

325RPL↗
DOE OSTI2017

Soda Pop: A Time-Series Clustering, Alarming and Disease Forecasting Application

To introduce Soda Pop, an R/Shiny application designed to be a disease agnostic time-series clustering, alarming, and forecasting tool to assist in disease surveillance “triage, analysis and reporting” workflows within the Biosurveillance Ecosystem (BSVE). In this poster, we highlight the new capabilities that are brought to the BSVE by Soda Pop with an emphasis on the impact of methodological decisions. The Biosurveillance Ecosystem (BSVE) is a biological and chemical threat surveillance system sponsored by the Defense Threat Reduction Agency (DTRA). BSVE is intended to be user-friendly, multi-agency, cooperative, modular and threat agnostic platform for biosurveillance. In BSVE, a web-based workbench presents the analyst with applications (apps) developed by various DTRA funded researchers, which are deployed on-demand in the cloud(e.g., Amazon Web Services). These apps aim to address emerging needs and refine capabilities to enable early warning of chemical and biological threats for multiple users across local, state, and federal agencies. Soda Pop is an app developed by Pacific Northwest National Laboratory (PNNL) to meet the current needs of the BSVE for early warning and detection of disease outbreaks. Aimed for use bya diverse set of analysts, the application is agnostic to data source and spatial scale enabling it to be generalizable across many diseases and locations. To achieve this, we placed a particular emphasis on clustering and alerting of disease signals within Soda Pop without strong prior assumptions on the nature of observed diseased counts. Although designed to be agnostic to the data source, Soda Pop was initially developed and tested on data summarizing Influenza-Like Illness in military hospitals from collaboration with the Armed Forces Health Surveillance Branch. Currently, the data incorporated also includes the CDC’s National Notifiable Diseases Surveillance System(NNDSS) tables and the WHO’s Influenza A/B Influenza Data(Flunet). These data sources are now present in BSVE’s Postgres data storage for direct access. Soda Pop is designed to automate time-series tasks of data summarization, exploration, clustering, alarming and forecasting. Built as an R/Shiny application, Soda Pop is founded on the powerful statistical tool R.. Where applicable, Soda Pop facilitates nonparametric seasonal decomposition of time-series; hierarchical agglomerative clustering across reporting areas and between diseases within reporting areas; and a variety of alarming techniques including Exponential Weighted Moving Average alarms and Early Aberration Detection. Soda Pop embeds these techniques within a user-interface designed to enhance an analyst’s understanding of emerging trends in their data and enables the inclusion of its graphical elements into their dossier for further tracking and reporting. The ultimate goal of this software is to facilitate the discovery of unknown disease signals along with increasing the speed of detection of unusual patterns within these signals. Soda Pop organizes common statistical disease surveillance tasks in a manner integrated with BSVE data source inputs and outputs. The app analyzes time-series disease data and supports a robust set of clustering and alarming routines that avoid strong assumptions on the nature of observed disease counts. This attribute allows for flexibility in the data source, spatial scale, and disease types making it useful to a wide range of analysts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Organic liquid scintillation detectors for on-the-fly neutron/gamma alarming and radionuclide identification in a pedestrian radiation portal monitor

Here, we present new experimental results from a radiation portal monitor based on the use of organic liquid scintillators. The system was tested as part of a 3 He-free radiation portal monitor testing campaign at the European Commission’s Joint Research Centre in Ispra, Italy, in February 2014. The radiation portal monitor was subjected to a wide range of test conditions described in ANSI N42.35, including a variety of gamma-ray sources and a 20,000 n/s 252 Cf source. A false alarm test tested whether radiation portal monitors ever alarmed in the presence of only natural background. The University of Michigan Detection for Nuclear Nonproliferation Group’s system triggered zero false alarms in 2739 trials. It consistently alarmed on a variety of gamma-ray sources travelling at 1.2 m/s at a 70 cm source to detector distance. The neutron source was detected at speeds up to 3 m/s and in configurations with up to 8 cm of high density polyethylene shielding. The success of on-the-fly radionuclide identification varied with the gamma-ray source measured as well as with which of two radionuclide identification methods was used. Both methods used a least squares comparison between the measured pulse height distributions to library spectra to pick the best match. The methods varied in how the pulse height distributions were modified prior to the least squares comparison. Correct identification rates were as high as 100% for highly enriched uranium, but as low as 50% for 241 Am. Lastly, both radionuclide identification algorithms produced mixed results, but the concept of using liquid scintillation detectors for gamma-ray and neutron alarming in radiation portal monitor was validated.

3He replacement technology↗