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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Electron-nuclear decoupling at a spin clock transition

The ability to design quantum systems that decouple from environmental noise sources is highly desirable for development of quantum technologies with optimal coherence. The chemical tunability of electronic states in magnetic molecules combined with advanced electron spin resonance techniques provides excellent opportunities to address this problem. Indeed, so-called clock transitions have been shown to protect molecular spin qubits from magnetic noise, giving rise to significantly enhanced coherence. Here we conduct a spectroscopic and computational investigation of this physics, focusing on the role of the nuclear bath. Away from the clock transition, linear coupling to the nuclear degrees of freedom causes a modulation and decay of electronic coherence, as quantified via electron spin echo signals generated experimentally and in silico. Meanwhile, the effective hyperfine interaction vanishes at the clock transition, resulting in electron-nuclear decoupling and an absence of quantum information leakage to the nuclear bath, providing opportunities to characterize other decoherence sources.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1995

Water vapor radiometer measurements of the tropospheric delay fluctuations at Goldstone over a full year

One year of near-continuous water vapor radiometer (WVR) measurements at DSS 13 has provided a database for characterizing the Goldstone tropospheric delay properties in a statistical sense. The results have been expressed in terms of the Allan standard deviation of delay and compared to a previous model for Goldstone fluctuations and the specifications of the Cassini Gravitational Wave Experiment (GWE). The new WVR data indicate that average fluctuation levels at hour time scales or less are approximately 30 percent lower than the earlier Goldstone model predictions. At greater than 1 h time scales, the WVR indicated fluctuation levels are in closer agreement with the model, although noise floor limitations may be artificially raising the average WVR-derived atmospheric fluctuation levels at the longer time scales. When scaled to two-way Doppler tracking at 20 deg elevation, as will occur for the GWE, these results indicate that Goldstone winter tropospheric delay fluctuations will typically be a factor of 10 larger than the GWE requirements at 1000 s and a factor of 4 larger at 10,000 s.

Keihm, S. J.↗
NASA NTRS2001

Infrared Communications for Small Spacecraft: From a Wireless Bus to Cluster Concepts

Nanosatellites operating singly or in clusters are anticipated for future space science missions. To implement this new communications paradigm, we are approaching cluster communications by first developing an infrared (IR) intra-craft wireless bus capability, following initially the MIL-STD-1553B protocol. Benefits of an IR wireless bus are low mass, size, power, and cost, simplicity of implementation, ease of use, minimum EMI, and efficient and reliable data transfer. Our goals are to maximize the reliable link margin in order to afford greater flexibility in receiver placement, which will ease technology insertion. We have developed a concept demonstration using a high-speed visible-band silicon PIN photodiode and a high-efficiency visible LED operating at a data rate up to 4 Mb/sec. In designing an internal IR wireless bus, we have characterized various candidate materials, emitters, and geometries, assuming a single reflection. Thus, we have measured the bidirectional reflectance distribution function (BRDF) for five different materials characteristic of typical spacecraft structures, which range from nearly Lambertian to highly specular. We have fit our data to empirical BRDF functions and modeled the detected irradiance anywhere in the plane of incidence for a divergent (LED) emitter. We have also determined the angular limits on the link geometry to remain within the required bit error rate by determining the received signal-to-noise ratio (SNR) for minimum values of irradiance received at the detector.

Webb, Suzanne C.↗
DOE OSTI2024

GaN-based W-band receiver chip development for fusion plasma diagnostics

Millimeter-wave diagnostics have proven effective on various magnetic fusion devices worldwide, yet the formidable challenges posed by the harsh environments of future burning plasma devices, characterized by extreme temperatures, pressures, and radiation levels, remain a significant hurdle. To address these challenges, the utilization of wide bandgap Gallium Nitride (GaN)-based millimeter-wave diagnostics is a most promising solution for fusion reactor safety monitoring and control. A noteworthy W-band GaN-based system-on-chip receiver has been the demonstrated by employing HRL T3 40 nm GaN technology. This receiver chip, compactly designed with dimensions of 3 × 5 mm 2 , incorporates essential components such as the 75–110 GHz RF Low-Noise Amplifier (LNA), mixer, Intermediate Frequency (IF) amplifier, and Local Oscillator (LO) chain. This receiver chip will be packaged as a millimeter-wave receiver module and applied on the DIII-D National Fusion Facility, for fusion plasma edge shape monitoring for operational safety and dangerous disruption prediction. The laboratory measurement results have demonstrated suitable performance. Furthermore, this advancement is pivotal for accurate analysis of plasma behavior in the extreme conditions of burning plasma devices, driving progress in fusion research and technology.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Deep learning-based spatio-temporal fusion for high-fidelity ultra-high-speed X-ray radiography

Full-field ultra-high-speed (UHS) X-ray imaging experiments have been well established to characterize various processes and phenomena. However, the potential of UHS experiments through the joint acquisition of X-ray videos with distinct configurations has not been fully exploited. In this paper, we investigate the use of a deep learning-based spatio-temporal fusion (STF) framework to fuse two complementary sequences of X-ray images and reconstruct the target image sequence with high spatial resolution, high frame rate and high fidelity. We applied a transfer learning strategy to train the model and compared the peak signal-to-noise ratio (PSNR), average absolute difference (AAD) and structural similarity (SSIM) of the proposed framework on two independent X-ray data sets with those obtained from a baseline deep learning model, a Bayesian fusion framework and the bicubic interpolation method. The proposed framework outperformed the other methods with various configurations of the input frame separations and image noise levels. With three subsequent images from the low-resolution (LR) sequence of a four times lower spatial resolution and another two images from the high-resolution (HR) sequence of a 20 times lower frame rate, the proposed approach achieved average PSNRs of 37.57 dB and 35.15 dB, respectively. When coupled with the appropriate combination of high-speed cameras, the proposed approach will enhance the performance and therefore the scientific value of UHS X-ray imaging experiments.

deep learning↗
NASA NTRS2000

Limits on Line Bisector Variability for Stars with Extrasolar Planets

We present an analysis of high-resolution synoptic spectra of ten F- and G-type stars, seven of which exhibit periodic radial velocity variations due to the presence of one or more substellar companions. We searched for subtle periodic variations in photospheric line asymmetry, as characterized by line bisectors. In principle, periodic variations in line asymmetry observed at lower spectral resolution could mimic the radial velocity signature of a companion, but we find no significant evidence of such behavior in our data. Observations were obtained from 1998 March to 1999 February using the National Solar Observatory (NSO) 1.52-m McMath-Pierce Solar Telescope Facility on Kitt Peak in conjunction with the solar-stellar spectrograph, achieving a resolving power of 1.2x10(exp5). To characterize line asymmetry, we first measured line bisectors for the unblended Fe I photospheric line at 625.26 nm. To improve sensitivity to small fluctuations, we then combined points in each bisector to form a velocity displacement with respect to the line core. We searched for periodic variations in this displacement, finding no substantial difference between stars with substellar companions and those without reported companions. We find no correlation between bisector velocity displacement and the known orbital phase of substellar companions around our target stars. Simulations of a periodic signal with noise levels that mimic our measurement errors suggest that we can exclude bisector variations with amplitudes greater than about 20 m/s. These results support the conclusion that extrasolar planets best explain the observed periodic variations in radial velocity.

Povich, M. S.↗
NASA NTRS2003

Active Control of High Frequency Combustion Instability in Aircraft Gas-Turbine Engines

Active control of high-frequency (greater than 500 Hz) combustion instability has been demonstrated in the NASA single-nozzle combustor rig at United Technologies Research Center. The combustor rig emulates an actual engine instability and has many of the complexities of a real engine combustor (i.e. actual fuel nozzle and swirler, dilution cooling, etc.) In order to demonstrate control, a high-frequency fuel valve capable of modulating the fuel flow at up to 1kHz was developed. Characterization of the fuel delivery system was accomplished in a custom dynamic flow rig developed for that purpose. Two instability control methods, one model-based and one based on adaptive phase-shifting, were developed and evaluated against reduced order models and a Sectored-1-dimensional model of the combustor rig. Open-loop fuel modulation testing in the rig demonstrated sufficient fuel modulation authority to proceed with closed-loop testing. During closed-loop testing, both control methods were able to identify the instability from the background noise and were shown to reduce the pressure oscillations at the instability frequency by 30%. This is the first known successful demonstration of high-frequency combustion instability suppression in a realistic aero-engine environment. Future plans are to carry these technologies forward to demonstration on an advanced low-emission combustor.

Corrigan, Bob↗
NASA NTRS2012

Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer

A multi-channel electrometer voltmeter that employs self-nulling lock-in detection electronics in conjunction with a mechanical resonator with noncontact voltage sensing electrodes has been developed for space-based measurement of an Internal Electrostatic Discharge Monitor (IESDM). The IESDM is new sensor technology targeted for integration into a Space Environmental Monitor (SEM) subsystem used for the characterization and monitoring of deep dielectric charging on spacecraft. Use of an AC-coupled lock-in amplifier with closed-loop sense-signal nulling via generation of an active guard-driving feedback voltage provides the resolution, accuracy, linearity and stability needed for long-term space-based measurement of the IESDM. This implementation relies on adjusting the feedback voltage to drive the sense current received from the resonator s variable-capacitance-probe voltage transducer to approximately zero, as limited by the signal-to-noise performance of the loop electronics. The magnitude of the sense current is proportional to the difference between the input voltage being measured and the feedback voltage, which matches the input voltage when the sense current is zero. High signal-to-noise-ratio (SNR) is achieved by synchronous detection of the sense signal using the correlated reference signal derived from the oscillator circuit that drives the mechanical resonator. The magnitude of the feedback voltage, while the loop is in a settled state with essentially zero sense current, is an accurate estimate of the input voltage being measured. This technique has many beneficial attributes including immunity to drift, high linearity, high SNR from synchronous detection of a single-frequency carrier selected to avoid potentially noisy 1/f low-frequency spectrum of the signal-chain electronics, and high accuracy provided through the benefits of a driven shield encasing the capacitance- probe transducer and guarded input triaxial lead-in. Measurements obtained from a 2- channel prototype electrometer have demonstrated good accuracy (|error| < 0.2 V) and high stability. Twenty-four-hour tests have been performed with virtually no drift. Additionally, 5,500 repeated one-second measurements of 100 V input were shown to be approximately normally distributed with a standard deviation of 140 mV.

Blaes, Brent R.↗
NASA NTRS2013

MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region

MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

MODIS↗
DOE OSTI2024

DeepUQ: Assessing the Aleatoric Uncertainties from two Deep Learning Methods

Assessing the quality of aleatoric uncertainty estimates from uncertainty quantification (UQ) deep learning methods is important in scientific contexts, where uncertainty is physically meaningful and important to characterize and interpret exactly. We systematically compare aleatoric uncertainty measured by two UQ techniques, Deep Ensembles (DE) and Deep Evidential Regression (DER). Our method focuses on both zero-dimensional (0D) and two-dimensional (2D) data, to explore how the UQ methods function for different data dimensionalities. We investigate uncertainty injected on the input and output variables and include a method to propagate uncertainty in the case of input uncertainty so that we can compare the predicted aleatoric uncertainty to the known values. We experiment with three levels of noise. The aleatoric uncertainty predicted across all models and experiments scales with the injected noise level. However, the predicted uncertainty is miscalibrated to $\rm{std}(\sigma_{\rm al})$ with the true uncertainty for half of the DE experiments and almost all of the DER experiments. The predicted uncertainty is the least accurate for both UQ methods for the 2D input uncertainty experiment and the high-noise level. While these results do not apply to more complex data, they highlight that further research on post-facto calibration for these methods would be beneficial, particularly for high-noise and high-dimensional settings.

Nevin, Rebecca↗
NASA NTRS2012

The Atacama Cosmology Telescope: Data Characterization and Map Making

We present a description of the data reduction and mapmaking pipeline used for the 2008 observing season of the Atacama Cosmology Telescope (ACT). The data presented here at 148 GHz represent 12% or the 90 TB collected by ACT from 2007 to 2010. In 2008 we observed for 136 days, producing a total of 142h of data (11 TB for the 148 GHz band only), with a daily average of 10.5 h of observation. From these, 108.5 h were devoted to 850 sq deg stripe (11.2 h by 9 deg.1) centered on a declination of -52 deg.7, while 175 h were devoted to a 280 square deg stripe (4.5 h by 4 deg.8) centered at the celestial equator. We discuss sources of statistical and systematic noise, calibration, telescope pointing and data selection. Out of 1260 survey hours and 1024 detectors per array, 816 h and 593 effective detectors remain after data selection for this frequency band, yielding a 38 % survey efficiency. The total sensitivity in 2008, determined from the noise level between 5 Hz and 20 Hz in the time-ordered data stream (TOD), is 32 muK square root of s in CMB units. Atmospheric brightness fluctuations constitute the main contaminant in the data and dominate the detector and noise covariance at low frequencies in the TOD. The maps were made by solving the lease squares problem using the Preconditioned Conjugate Gradient method, incorporating the details of the detector and noise correlations. Cross-correlation with WMAP sky maps as well as analysis from simulations reveal the our maps are unbiased at l > 300. This paper accompanies the public release of the 148 GHz southern stripe maps from 2008. The techniques described here will be applied to future maps and data releases.

Duenner, Rolando↗
DOE OSTI2022

Regularized inversion of aerosol hygroscopic growth factor probability density function: application to humidity-controlled fast integrated mobility spectrometer measurements

Abstract. Aerosol hygroscopic growth plays an important role in atmospheric particle chemistry and the effects of aerosol on radiation and hence climate. The hygroscopic growth is often characterized by a growth factor probability density function (GF-PDF), where the growth factor is defined as the ratio of the particle size at a specified relative humidity to its dry size. Parametric, least-squares methods are the most widely used algorithms for inverting the GF-PDF from measurements of the humidified tandem differential mobility analyzer (HTDMA) and have been recently applied to the GF-PDF inversion from measurements of the humidity-controlled fast integrated mobility spectrometer (HFIMS). However, these least-squares methods suffer from noise amplification due to the lack of regularization in solving the ill-posed problem, resulting in significant fluctuations in the retrieved GF-PDF and even occasional failures of convergence. In this study, we introduce nonparametric, regularized methods to invert the aerosol GF-PDF and apply them to HFIMS measurements. Based on the HFIMS kernel function, the forward convolution is transformed into a matrix-based form, which facilitates the application of the nonparametric inversion methods with regularizations, including Tikhonov regularization and Twomey's iterative regularization. Inversions of the GF-PDF using the nonparameteric methods with regularization are demonstrated using HFIMS measurements simulated from representative GF-PDFs of ambient aerosols. The characteristics of reconstructed GF-PDFs resulting from different inversion methods, including previously developed least-squares methods, are quantitatively compared. The result shows that Twomey's method generally outperforms other inversion methods. The capabilities of Twomey's method in reconstructing the pre-defined GF-PDFs and recovering the mode parameters are validated.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Raman Spectroscopy for Mineral Identification and Quantification for in situ Planetary Surface Analysis: A Point Count Method

Quantification of mineral proportions in rocks and soils by Raman spectroscopy on a planetary surface is best done by taking many narrow-beam spectra from different locations on the rock or soil, with each spectrum yielding peaks from only one or two minerals. The proportion of each mineral in the rock or soil can then be determined from the fraction of the spectra that contain its peaks, in analogy with the standard petrographic technique of point counting. The method can also be used for nondestructive laboratory characterization of rock samples. Although Raman peaks for different minerals seldom overlap each other, it is impractical to obtain proportions of constituent minerals by Raman spectroscopy through analysis of peak intensities in a spectrum obtained by broad-beam sensing of a representative area of the target material. That is because the Raman signal strength produced by a mineral in a rock or soil is not related in a simple way through the Raman scattering cross section of that mineral to its proportion in the rock, and the signal-to-noise ratio of a Raman spectrum is poor when a sample is stimulated by a low-power laser beam of broad diameter. Results obtained by the Raman point-count method are demonstrated for a lunar thin section (14161,7062) and a rock fragment (15273,7039). Major minerals (plagioclase and pyroxene), minor minerals (cristobalite and K-feldspar), and accessory minerals (whitlockite, apatite, and baddeleyite) were easily identified. Identification of the rock types, KREEP basalt or melt rock, from the 100-location spectra was straightforward.

Haskin, Larry A.↗
DOE OSTI2024

DASEventNet: AI‐Based Microseismic Detection on Distributed Acoustic Sensing Data From the Utah FORGE Well 16A (78)‐32 Hydraulic Stimulation

Abstract Distributed acoustic sensing (DAS) has emerged as a promising seismic technology for monitoring microearthquakes (MEQs) with high spatial resolution. Efficient algorithms are needed for processing large DAS data volumes. This study introduces a deep learning (DL) model based on a Residual Convolutional Neural Network (ResNet) for detecting MEQs using DAS data, named as DASEventNet. The test data were collected from the Utah FORGE 16A (78)‐32 hydraulic stimulation experiments conducted in April 2022. The DASEventNet model achieves a remarkable accuracy of 100% when discriminating MEQs from noise in the raw test set of 260 examples. Surprisingly, the model identified weak MEQ signatures that have been manually categorized as noise. The decision‐making process with the model is decoded by the classic activation map, which illuminates learning features of the DASEventNet model. These features provide clear illustrations of weak MEQs and varied noise types. Finally, we apply the trained model to the entire period (∼7 days) of continuous DAS recordings and find that it discovers >5,700 new MEQs, previously unregistered in the public Silixa DAS catalog. The DASEventNet model significantly outperforms the traditional seismic method Short‐Term Average/Long‐Term Average (STA/LTA), which detected only 1,307 MEQs. The DASEventNet detection threshold is M w −1.80 compared to the minimum magnitude of M w −1.14 detected by STA/LTA. The spatiotemporal distribution of the newly identified MEQs defines an extensive stimulation zone and more accurately characterizes fracture geometry. Our results highlight the potential of DL for long‐term, real‐time microseismic monitoring that can improve enhanced geothermal systems and other activities that include subsurface hydraulic fracturing.

15 GEOTHERMAL ENERGY↗
NASA NTRS1998

High Resolution Imaging of the Sun with CORONAS-1

We applied several image restoration and enhancement techniques, to CORONAS-I images. We carried out the characterization of the Point Spread Function (PSF) using the unique capability of the Blind Iterative Deconvolution (BID) technique, which recovers the real PSF at a given location and time of observation, when limited a priori information is available on its characteristics. We also applied image enhancement technique to extract the small scale structure imbeded in bright large scale structures on the disk and on the limb. The results demonstrate the capability of the image post-processing to substantially increase the yield from the space observations by improving the resolution and reducing noise in the images.

Karovska, Margarita↗
NASA NTRS2006

Edge Response and NIIRS Estimates for Commercial Remote Sensing Satellites

Spatial resolution of panchromatic imagery from commercial remote sensing satellites was characterized based on edge response measurements using edge targets and the tilted-edge technique. Relative Edge Response (RER) was estimated as a geometric mean of normalized edge response differences measured in two directions of image pixels at points distanced from the edge by -0.5 and 0.5 of ground sample distance. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale (NIIRS). By assuming a plausible range of signal-to-noise ratio and assessing the effects of Modulation Transfer Function compensation, the NIIRS estimates were made and then compared with vendor-provided values and evaluations conducted by the National Geospatial-Intelligence Agency.

Blonski, Slawomir↗
NASA NTRS2009

Aqua MODIS Thermal Emissive Band On-Orbit Calibration, Characterization, and Performance

The NASA's Earth Observing System Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) has continued to operate with satisfactory performance since its launch in May 2002, exceeding its nominal six-year design lifetime. Its continuous Earth observations have been used to generate many science data products for studies of the Earth's, system. MODIS has 36 spectral bands; 20 reflective solar bands and 16 thermal emissive bands (TEBs). All TEB observations are made at 1-km nadir spatial resolution with spectral wavelengths from 3.7 to 14.4 pm. Primary applications of MODIS TEB 'include surface, cloud, and atmospheric temperatures, water vapor, and cloud top altitude. MODIS TEB on-orbit calibration uses a quadratic algorithm with its calibration coefficients derived using an onboard blackbody (BB). This paper will present Aqua MODIS TEB on-orbit calibration, characterization, and performance over its six-year mission. Examples of instrument thermal behavior, BB temperature stability, detector short-term stability, and changes in long-term response (or system gain) will be presented. Comparisons will also be made with Terra MODIS, launched in December 1999. On-orbit results show that Aqua MODIS and its focal plane temperatures have behaved normally. BB temperature has remained extremely stable with typical scan -to-scan variations of less than +/-0.15 mK. Most TEB detectors continue to exceed their specified signal-to-noise ratio requirements, exhibiting excellent short-term stability and calibration accuracy. Excluding a few noisy detectors, either identified prelaunch or occurring postlaunch, on-orbit changes in TEB responses have been less than 0.5% on an annual basis. By comparison; the overall Aqua TEB performance has been better than that of Terra MODIS,

Xiong, Xiaoxiong↗
DOE OSTI2025

STILGAR End-of-Project Report

The Subsurface Tunnel Imaging LeveraGed by Analysis of Rayleigh wave ellipticity (STILGAR) project demonstrated an integrated geophysical approach for detecting, locating, and characterizing underground structural changes using dense seismic arrays and advanced inversion techniques. Field campaigns were conducted at two operational mines—the Redmond salt mine (Utah) and Graymont Pleasant Gap limestone mine (Pennsylvania)—providing real-world testbeds for monitoring anthropogenic subsurface activity. At the Redmond salt mine, seismic interferometry combined with back-projection inversion successfully identified continuous, low-amplitude signals from mining operations. The approach differentiated stationary from migrating anthropogenic sources, captured daily operational cycles, and validated the potential of passive seismic monitoring for remote detection of underground activity. At the Graymont Pleasant Gap mine, two dense seismic deployments in the spring and fall of 2023 generated over 4 TB of high-resolution data. Key outcomes included the relocation of 199 underground and 8 surface explosions with accuracies within tens of meters and the development of a 3D P-wave velocity model using the triple-difference tomography algorithm (tomoTD) that resolved major structural features such as the mine entrance, low-velocity tunnels, and roof-collapse areas. Ambient noise cross-correlation and back-projection analyses revealed persistent sources linked to ongoing mining activity, whereas horizontal-to-vertical spectral ratio (HVSR) and ellipticity studies confirmed stable site responses across seasons and identified soil thickness trends consistent with regional erosional and depositional processes. Checkerboard and sensitivity tests further validated the robustness of the tomographic results. Overall, the findings emphasize that although significant progress has been made in subsurface imaging, further work is needed to enhance the detection and localization of underground structures. Accurate imaging requires higher frequencies, yet anthropogenic sources tend to dominate the seismic record at those frequencies, and high-frequency surface waves are affected by higher modes that complicate interpretation. The improved detection and localization of human-induced signals enabled detailed temporal and spatial mapping of daily mine operations, demonstrating the feasibility of continuous anthropogenic source monitoring. Sensitivity to signals from nontraditional sources, such as fan operations, highlights the broader applicability of this approach to other industrial environments in which continuous and impulsive signals are present. The field campaigns produced a substantial volume of high-quality seismic data, supporting the development and testing of new methods for seismic source characterization and subsurface imaging. Future deployments should include sensors capable of recording lower frequencies to probe deeper structures, increase bandwidth to enhance resolution and sensitivity to both shallow and deep targets, and collect additional large-scale datasets to refine imaging and source characterization techniques. Moreover, conducting 3D modeling studies of seismic wavefields at higher frequencies will provide a better understanding of wave scattering and cavity–wavefield interactions in complex underground environments. In conclusion, the STILGAR project demonstrated that integrated seismic monitoring can effectively characterize underground operations, capturing both natural and anthropogenic signals. The approaches developed provide a foundation for improved detection, localization, and imaging of subsurface structures and are directly transferable to broader industrial monitoring applications.

58 GEOSCIENCES↗