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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Speech Alarms Pilot Study

Speech alarms have been used extensively in aviation and included in International Building Codes (IBC) and National Fire Protection Association's (NFPA) Life Safety Code. However, they have not been implemented on space vehicles. Previous studies conducted at NASA JSC showed that speech alarms lead to faster identification and higher accuracy. This research evaluated updated speech and tone alerts in a laboratory environment and in the Human Exploration Research Analog (HERA) in a realistic setup.

Sandor, Aniko↗
DOE OSTI2026

epics-alarm-push

Prototype IOC alarm pusher using Redis in a support module.

Bracey, Dave [Fermi National Accelerator Laborator↗
DOE OSTI2026

Alarms and Attention: UX Lessons from Safety-critical monitoring

UX lessons from designing the Alarms app (a tool operators rely on to track accelerator subsystems and respond to alerts). The talk focuses on how observation, empathy, and iterative design helped us balance information, attention, and safety.

Kim, Leah [Fermilab]↗
DOE OSTI2026

Red Noise–based False Alarm Thresholds for Astrophysical Periodograms via Whittle’s Approximation to the Likelihood

Astronomers who search for periodic signals using Lomb–Scargle periodograms rely on false alarm level (FAL) estimates to identify statistically significant peaks. Although FALs are often calculated from white noise models, many astronomical time series suffer from red noise. Prewhitening is a statistical technique in which a continuum model is subtracted from the log power spectrum estimate, after which the observer can proceed with a white-noise treatment. Here we present a prewhitening-based method of calculating frequency-dependent FALs. We fit power laws and autoregressive models of order 1 to each Lomb–Scargle periodogram by minimizing the Whittle approximation to the negative log-likelihood (NLL), then calculate FALs based on the best-fit model power spectrum. Our technique is a novel extension of the Whittle NLL to datasets with uneven time sampling. We demonstrate FAL calculations using observations of α Cen B, GJ 581, HD 192310, synthetic data from the radial velocity (RV) fitting challenge, and Kepler observations of a differential rotator. The Kepler data analysis shows that only true rotation signals are detected by red noise FALs, while white noise FALs suggest all spurious peaks in the low-frequency range are significant. A high-frequency sinusoid injected into α Cen B logR$'$ HK observations exceeds the 1% red noise FAL despite having only 8.9% of the power of the dominant rotation signal. In a periodogram of HD 192310 RVs, peaks associated with differential rotation and planets are detected against the 5% red noise FAL without iterative model fitting or subtraction. The software for calculating red noise–based FALs is available on GitHub.

Astrostatistics (1882)↗
NASA NTRS1966

Detection system ensures positive alarm activation in digital message loss

Lost Word Detection System /LOWDS/ provides special identification for each error detection message transmitted from receiver to transmitter. The message is identified as an original message or an n-times retransmitted message so the receiver can detect where a retransmission request was not fulfilled and activate an alarm.

Bokros, P.↗
NASA NTRS1972

Tornado detector and alarm

Automatic device which attaches to an active television set sounds an audible alarm when a tornado is within 29 km (18miles) of device.

Moss, A. R.↗
NASA NTRS1973

Detector for inspection of fire alarms

Portable detector tests rate-of-rise temperature devices. Incandescent light bulb is calibrated to produce rate of temperature rise necessary to activate properly functioning alarm.

Clawson, G. T.↗
NASA NTRS1972

The Global Rescue Alarm Net (GRAN) experiment

The OMEGA Position Location Experiment (OPLE) was performed in 1967 by the Goddard Space Flight Center in order to demonstrate a position location and data collection system. OMEGA navigation signals were received at a remote site and retransmitted via a synchronous satellite to a ground processing center where data collecting and position determination were performed. Recent technological advances have made it possible to develop an Advanced OPLE System towards a global search and rescue application. This application generated some new problem areas such as the OMEGA lane ambiguity, random access, location accuracy, real-time processing, and size and weight of the Search and Rescue Communications (SARCOM). This experiment demonstrates the feasibility of instantaneous alarm and position location by using a relatively inexpensive, battery operated, three-pound package.

Morakis, J. C.↗
NASA NTRS1977

Inexpensive low-voltage solid-state alarm

Monitor/alarm with audio and visual warning output can be used to warn when prescribed limits of temperature, liquid level, pressure, or similar properties are exceeded. Device is more compact, lighter, and less expensive to manufacture than typical alarm circuits.

Hardy, D. H.↗
NASA NTRS1975

ALARM: A highly efficient eigenvalue extraction routine for very large matrixes

A highly efficient computer program, called ALARM, for the determination of eigenvalues and eigenvectors of large symmetric matrices (over 10,000 degrees of freedom), was described. As such, it is highly useful for analyzing complex finite element and finite difference idealizations encountered in structural dynamics and acoustic probelms. The program is based upon a scheme which reduces a large matrix to an equivalent tridiagonal one of much smaller size. The main strength of the algorithm lies in its ability to retain all the information required to obtain the eigenvalues at either end of the original matrix spectrum.

Ojalvo, I. U.↗
NASA NTRSDate not supplied

Monte Carlo Simulations for Evaluating the Accuracy of GLM Detection Efficiency and False Alarm Rate Retrievals

The performance of the Geostationary Lightning Mapper has been evaluated through comparison with other satellite lightning sensors and ground-based networks. However, because the performance of these reference sensors is both imperfect and imperfectly known, the true performance of GLM can only be estimated through such a process. In particular, GLM performance metrics such as detection efficiency (DE) and false alarm rate (FAR) retrieved through comparison with reference networks are affected by those networks’ own DE, FAR, and spatiotemporal accuracy, as well as the selected flash matching criteria. This study presents follow-on results from an ongoing analysis that uses a Monte Carlo simulation-based inversion technique to quantify the effect on retrieved GLM performance of a reasonable range of reference network DE, FAR, spatiotemporal accuracy, and the associated geographic patterns of each. These results help quantify and bound the actual performance of GLM and the attendant uncertainties when comparing GLM to imperfect reference networks.

Katrina Virts↗
NASA NTRSDate not supplied

Probing ExoMiner for Effectiveness against False Alarms in Kepler Data

We present a study on the effectiveness of ExoMiner against False Alarms in Kepler data. ExoMiner is a deep learning model that was used to validate around 370 Kepler Objects of Interest. We follow the analysis conducted in Coughlin et al (2017) “DR25 Robovetter Completeness and Effectiveness” for Robovetter, a rule-based model used to vet TCEs for this data release and automatically generate the Q1-Q17 DR 25 KOI Table. The ExoMiner model is trained on observed transit data from Kepler Q1-Q17 DR25 and evaluated on Kepler inverted and scrambled data. The results provide a more comprehensive insight into the capacities and limitations of ExoMiner, especially the vetting of not-transit-like signals and, more generally, the use of deep learning models to model transit photometry data for vetting and validation purposes.

exoplanet↗