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DOE OSTI2026

FY 2026 Midyear Report: Seismic Monitoring of Underground Vibration Sources Using Distributed Acoustic Sensing and Seismometers

Safeguards-relevant temporal changes in underground facilities can be observed using geophysical monitoring techniques. Seismic waves, in particular, provide valuable insights into subsurface activities and can serve as an important tool for detecting anomalous events that may indicate containment breaches at geological repositories. This midyear report summarizes ongoing efforts to automatically and rapidly detect and locate anomalous vibration signals that could be indicative of potential containment breaches. Previous work during FY25 focused on compiling continuous seismic datasets from two underground sites and developing a database of continuous waveforms and ground-truth event data derived from multiple sensing modalities. Building on this foundation, we are adapting anomaly detection and geolocation algorithms to explore methods for monitoring underground activities using two relatively low-maintenance sensing technologies: a dense surface geophone array deployed at the Pleasant Gap mine in Pennsylvania, and a three-dimensional fiber-optic cable array for distributed acoustic sensing (DAS) installed in the subsurface at the Sanford Underground Research Facility (SURF) in South Dakota. This report summarizes work conducted during the first two quarters of FY26, during which we refined a dynamic power spectral density (PSD)-based detector, applied it independently to each geophone station, and then combined the per‑station detections with density-based spatial clustering of applications with noise (DBSCAN) to cluster events and produce spatial maps over a nine‑day interval. In addition, we outline plans for a field trial at the Waste Isolation Pilot Plant (WIPP) in New Mexico to compare traditional seismic monitoring approaches with DAS techniques and to evaluate the benefits of combined data analysis. Activities during the past two quarters have included the preparation and submission of a Field Test Plan to WIPP for approval, as well as submission to headquarters for review and feedback.

58 GEOSCIENCES↗

NASA NTRS2019

No Clear, Direct Evidence for Multiple Protoplanets Orbiting LkCa 15: LkCa 15 bcd are Likely Inner Disk Signals

Two studies utilizing sparse aperture-masking (SAM) interferometry and Hα differential imaging have reported multiple Jovian companions around the young solar-mass star, LkCa 15 (LkCa 15 bcd): theﬁrst claimed direct detection of infant, newly formed planets (“protoplanets”). We present new near-infrared direct imaging/spectroscopy from the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system coupled with Coronagraphic High Angular Resolution Imaging Spectrograph (CHARIS) integral ﬁeld spectrograph and multi-epoch thermal infrared imaging from Keck/ NIRC2 of LkCa 15 at high Strehl ratios. These data provide the ﬁrst direct imaging look at the same wavelengths and in the same locations where previous studies identiﬁed the LkCa 15 protoplanets,and thus offer the ﬁrst decisive test of their existence.The data do not reveal these planets. Instead,we resolve extended emission tracing adust disk with a brightness and location comparable to that claimed for LkCa 15 bcd. Forward-models attributing this signal to orbiting planets are inconsistent with the combined SCExAO/CHARIS and Keck/NIRC2 data. An inner disk provides a more compelling explanation for the SAM detections and perhaps also the claimed Hα detection of LkCa 15 b. We conclude that there is currently no clear, direct evidence for multiple protoplanets orbiting LkCa 15, although the system likely contains at least one unseen Jovian companion. To identify Jovian companions around LkCa 15 from future observations, the inner disk should be detected and its effect modeled, removed, and shown to be distinguishable from planets. Protoplanet candidates identiﬁed from similar systems should likewise be clearly distinguished from disk emission through modeling.

Thayne Currie↗

DOE OSTI2023

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and “transduce” signals to adjust internal processes. We hypothesized that an ecosystem’s unique stimuli leave a sensor “fingerprint,” able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection’s nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient’s disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1990

Integrated Optoelectronic Interface

Proposed optoelectronic integrated-circuit device serves as "universal" or standard interface for transmission and reception of digital and analog signals in communication, data-processing, and control systems. Eliminates need for custom design of interface circuitry in sense that it embodies "master-chip" design easily adaptable to use with specific equipment. Includes directly modulated semiconductor laser to generate light signals for transmission along optical fiber; positive/intrinsic/negative, avalanche, or other photodiode to detect light signals received along another optical fiber;and driving, synchronizing, preamplifying, and signal-regenerating circuitry. Muliplexes electronic signals before transmission and/or demultiplexes electronic signals after reception.

Katz, Joseph↗

NASA NTRS2012

Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs

Crewmembers returning from long-duration space flight face significant challenges due to the microgravity-induced inappropriate adaptations in balance/ sensorimotor function. The Neuroscience Laboratory at JSC is developing a method based on stochastic resonance to enhance the brain s ability to detect signals from the balance organs of the inner ear and use them for rapid improvement in balance skill, especially when combined with balance training exercises. This method involves a stimulus delivery system that is wearable/portable providing imperceptible electrical stimulation to the balance organs of the human body. Stochastic resonance (SR) is a phenomenon whereby the response of a nonlinear system to a weak periodic input signal is optimized by the presence of a particular non-zero level of noise. This phenomenon of SR is based on the concept of maximizing the flow of information through a system by a non-zero level of noise. Application of imperceptible SR noise coupled with sensory input in humans has been shown to improve motor, cardiovascular, visual, hearing, and balance functions. SR increases contrast sensitivity and luminance detection; lowers the absolute threshold for tone detection in normal hearing individuals; improves homeostatic function in the human blood pressure regulatory system; improves noise-enhanced muscle spindle function; and improves detection of weak tactile stimuli using mechanical or electrical stimulation. SR noise has been shown to improve postural control when applied as mechanical noise to the soles of the feet, or when applied as electrical noise at the knee and to the back muscles.

Bloomberg, Jacob↗

NASA NTRS1997

Uncertain responses by humans and rhesus monkeys (Macaca mulatta) in a psychophysical same-different task

The authors asked whether animals, like humans, use an uncertain response adaptively to escape indeterminate stimulus relations. Humans and monkeys were placed in a same-different task, known to be challenging for animals. Its difficulty was increased further by reducing the size of the stimulus differences, thereby making many same and different trials difficult to tell apart. Monkeys do escape selectively from these threshold trials, even while coping with 7 absolute stimulus levels concurrently. Monkeys even adjust their response strategies on short time scales according to the local task conditions. Signal-detection and optimality analyses confirm the similarity of humans' and animals' performances. Whereas associative interpretations account poorly for these results, an intuitive uncertainty construct does so easily. The authors discuss the cognitive processes that allow uncertainty's adaptive use and recommend further comparative studies of metacognition.

NASA Discipline Space Human Factors↗

NASA NTRS2017

AI and Autonomy Initiatives for NASA’s Deep Space Network (DSN)

NASA’s Deep Space Network (DSN) consists of thirteen large (34- and 70-meter) antennas that are used to communicate with approximately 40 NASA and partner spacecraft, all at great distance from the earth (generally at Lunar distances and beyond). The DSN has a long history — over 50 years — and has evolved with cutting edge, often custom, telecommunications equipment and associated software systems. In recent years, and in preparation for an increasing future demand, there has been an effort to invest in initiatives that will result in significant cost savings in the future. These efforts are building on, or augmenting, the recent deployment of “Follow-the-Sun” operations (day shift remote operational control of the entire network from each of the three antenna complexes in turn) — which is being deployed in 2017. This paper focuses on Adaptive Demand Access: in a paradigm shift from completely pre-planned operations, this concept calls for spacecraft to signal their intent (or not) for near-future contacts, in case they have science results of interest, or have experienced an anomaly. This would take advantage of a beacon tone transmission, which can be detected using smaller antennas. When a connection request is received, the DSN ground systems would adaptively accommodate the request, inserting the contact into the plan as soon as possible, subject to constraints and priorities. The demand access concept incorporates onboard data analysis and science data processing, so that beacon tones can be generated with maximum information. This area is representative of several where infusing AI technologies can lead to improved effectiveness of the DSN as the network readies for support of expanded Mars exploration efforts in the 2020’s and beyond.

Wyatt, E. Jay↗

NASA NTRS2004

Planetary Transmission Diagnostics

This report presents a methodology for detecting and diagnosing gear faults in the planetary stage of a helicopter transmission. This diagnostic technique is based on the constrained adaptive lifting algorithm. The lifting scheme, developed by Wim Sweldens of Bell Labs, is a time domain, prediction-error realization of the wavelet transform that allows for greater flexibility in the construction of wavelet bases. Classic lifting analyzes a given signal using wavelets derived from a single fundamental basis function. A number of researchers have proposed techniques for adding adaptivity to the lifting scheme, allowing the transform to choose from a set of fundamental bases the basis that best fits the signal. This characteristic is desirable for gear diagnostics as it allows the technique to tailor itself to a specific transmission by selecting a set of wavelets that best represent vibration signals obtained while the gearbox is operating under healthy-state conditions. However, constraints on certain basis characteristics are necessary to enhance the detection of local wave-form changes caused by certain types of gear damage. The proposed methodology analyzes individual tooth-mesh waveforms from a healthy-state gearbox vibration signal that was generated using the vibration separation (synchronous signal-averaging) algorithm. Each waveform is separated into analysis domains using zeros of its slope and curvature. The bases selected in each analysis domain are chosen to minimize the prediction error, and constrained to have the same-sign local slope and curvature as the original signal. The resulting set of bases is used to analyze future-state vibration signals and the lifting prediction error is inspected. The constraints allow the transform to effectively adapt to global amplitude changes, yielding small prediction errors. However, local wave-form changes associated with certain types of gear damage are poorly adapted, causing a significant change in the prediction error. The constrained adaptive lifting diagnostic algorithm is validated using data collected from the University of Maryland Transmission Test Rig and the results are discussed.

Lewicki, David G.↗

DOE OSTI2023

A transfer learning approach for acoustic emission zonal localization on steel plate-like structure using numerical simulation and unsupervised domain adaptation

The detection and localization of damage in metallic structures using acoustic emission (AE) monitoring and artificial intelligence technology such as deep learning has been widely studied. However, a current challenge of this approach is the difficulty of obtaining sufficient labeled historical AE signals for the training process of deep learning models. This problem can be approached through the implementation of transfer learning. The innovation of this paper lies in the development of a transfer learning approach for AE source localization on a stainless-steel structure when no historical labeled AE signals are available for training. A finite element model is developed to generate numerical AE signals for the training. Unsupervised domain adaptation (UDA) technology is utilized to reduce the distribution difference between the numerical and the realistic AE signals and to derive the localization results of the unlabeled realistic AE signals. Finally, the results suggest that the proposed approach is capable of localizing AE signals with high accuracy in the absence of labeled training data.

42 ENGINEERING↗

DOE OSTI2024

Photon number resolving detection with a single-photon detector and adaptive storage loop

Abstract Photon number resolving (PNR) measurements are beneficial or even necessary for many applications in quantum optics. Unfortunately, PNR detectors are usually large, slow, expensive, and difficult to operate. However, if the input signal is multiplexed, photon ‘click’ detectors, that lack an intrinsic PNR capability, can still be used to realize photon number resolution. Here, we investigate the operation of a single click detector, together with a storage line with tunable outcoupling. Using adaptive feedback to adjust the storage outcoupling rate, the dynamic range of the detector can in certain situations be extended by up to an order of magnitude relative to a purely passive setup. An adaptive approach can thus allow for photon number variance below the quantum shot noise limit under a wider range of conditions than using a passive multiplexing approach. This can enable applications in quantum enhanced metrology and quantum computing.

Sullivan, Nicholas M. (ORCID:0000000248447296)↗

NASA NTRS1981

Entropy encoding applied to a video DM bit stream

This paper investigates bandwidth compression of delta modulated video signals using a variety of novel techniques. The video signal is encoded at 16 MHz with an adaptive delta modulator (ADM) using the Song video mode algorithm. One method of achieving bandwidth compression is through the detection and reduction of steady state patterns in the DM bit stream. Further reduction is obtained by deleting the horizontal and vertical drive information. Finally, a modified ADM algorithm is introduced to increase the frequency of steady state patterns. When the modified ADM is combined with entropy coding a 30-50% data compression can be realized.

Barba, J.↗

DOE OSTI2020

High-speed volumetric imaging of formaldehyde in a lifted turbulent jet flame using an acousto-optic deflector

The development of high-speed volumetric laser-induced fluorescence measurements of formaldehyde (CH 2 O-LIF) using a pulse-burst laser operated at a repetition rate of 100 kHz is presented here. A novel laser scanning system employing an acousto-optic deflector (AOD) enables quasi-4D CH 2 O-LIF imaging at a scan frequency of 10 kHz. The diagnostic capability of time-resolved volumetric imaging is demonstrated in a partially premixed DME/air lifted turbulent jet flame near the flame base. Simultaneous imaging of laser beam profiles is performed to account for the laser pulse energy fluctuation and laser sheet inhomogeneity. With the accurate registration of laser sheet positions, the volumetric reconstruction of CH 2 O-LIF signals is performed within a detection volume of 17.3 × 11.9 × 2.3 mm 3 with an average out-of-plane spatial resolution of 250μm. A surface detection algorithm with adaptive thresholding is used to determine the global maximum intensity gradient by calculating gradient percentiles. The flame topology characteristics are investigated by evaluating the 3D curvatures of CH 2 O surfaces. Curvatures calculated using 2D data systematically underestimate the full 3D curvature due to the lack of out-of-plane information. The inner surfaces near the turbulent fuel jet exhibit higher probabilities of large mean curvature than the outer surfaces. The saddle and cylindrical structures are dominant on both the inner and outer surfaces and the elliptic structures occur with lower probability. The results suggest that the damping of turbulent fluctuations by the temperature increase through the CH 2 O region reduces the curvature, but the local structure topology remains self-similar.

42 ENGINEERING↗

DOE OSTI2021

BICEP/ Keck XII: Constraints on axionlike polarization oscillations in the cosmic microwave background

Here, we present a search for axionlike polarization oscillations in the cosmic microwave background (CMB) with observations from the Keck Array . A local axion field induces an all-sky, temporally sinusoidal rotation of CMB polarization. A CMB polarimeter can thus function as a direct-detection experiment for axionlike dark matter. We develop techniques to extract an oscillation signal. Many elements of the method are generic to CMB polarimetry experiments and can be adapted for other datasets. As a first demonstration, we process data from the 2012 observing season to set upper limits on the axion-photon coupling constant in the mass range 10 – 21 – 10 – 18 eV , which corresponds to oscillation periods on the order of hours to months. We find no statistically significant deviations from the background model. For periods larger than 24 hr (mass m < 4.8 × 10 – 20 eV ), the median 95% confidence upper limit is equivalent to a rotation amplitude of 0.68°, which constrains the axion-photon coupling constant to g Φ γ < ( 1.1 × 10 – 11 GeV – 1 ) m / ( 10 – 21 eV ) , if axionlike particles constitute all of the dark matter. The constraints can be improved substantially with data already collected by the BICEP series of experiments. Current and future CMB polarimetry experiments are expected to achieve sufficient sensitivity to rule out unexplored regions of the axion parameter space.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1974

Threshold detection in an on-off binary communications channel with atmospheric scintillation

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-emperical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. Bit error probabilities for non-optimum threshold detection system were also investigated.

Webb, W. E.↗

NASA NTRS1975

Threshold detection in an on-off binary communications channel with atmospheric scintillation

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-empirical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. The bit error probabilities for nonoptimum threshold detection systems were also investigated.

Webb, W. E.↗

NASA NTRS1992

Signal processing methodologies for an acoustic fetal heart rate monitor

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Pretlow, Robert A., III↗

NASA NTRS1998

Modulated Source Interferometry with Combined Amplitude and Frequency Modulation

An improved interferometer is produced by modifying a conventional interferometer to include amplitude and/or frequency modulation of a coherent light source at radio or higher frequencies. The phase of the modulation signal can be detected in an interfering beam from an interferometer and can be used to determine the actual optical phase of the beam. As such, this improvement can be adapted to virtually any two-beam interferometer, including: Michelson, Mach-Zehnder, and Sagnac interferometers. The use of an amplitude modulated coherent tight source results in an interferometer that combines the wide range advantages of coherent interferometry with the precise distance measurement advantages of white light interferometry.

Gutierrez, Roman C.↗

NASA NTRS2011

Multiple-Beam Detection of Fast Transient Radio Sources

A method has been designed for using multiple independent stations to discriminate fast transient radio sources from local anomalies, such as antenna noise or radio frequency interference (RFI). This can improve the sensitivity of incoherent detection for geographically separated stations such as the very long baseline array (VLBA), the future square kilometer array (SKA), or any other coincident observations by multiple separated receivers. The transients are short, broadband pulses of radio energy, often just a few milliseconds long, emitted by a variety of exotic astronomical phenomena. They generally represent rare, high-energy events making them of great scientific value. For RFI-robust adaptive detection of transients, using multiple stations, a family of algorithms has been developed. The technique exploits the fact that the separated stations constitute statistically independent samples of the target. This can be used to adaptively ignore RFI events for superior sensitivity. If the antenna signals are independent and identically distributed (IID), then RFI events are simply outlier data points that can be removed through robust estimation such as a trimmed or Winsorized estimator. The alternative "trimmed" estimator is considered, which excises the strongest n signals from the list of short-beamed intensities. Because local RFI is independent at each antenna, this interference is unlikely to occur at many antennas on the same step. Trimming the strongest signals provides robustness to RFI that can theoretically outperform even the detection performance of the same number of antennas at a single site. This algorithm requires sorting the signals at each time step and dispersion measure, an operation that is computationally tractable for existing array sizes. An alternative uses the various stations to form an ensemble estimate of the conditional density function (CDF) evaluated at each time step. Both methods outperform standard detection strategies on a test sequence of VLBA data, and both are efficient enough for deployment in real-time, online transient detection applications.

Thompson, David R.↗