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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
DOE OSTI2024

Maximizing the Radar Generalized Image Quality Equation for Bistatic SAR Using Waveform Frequency Agility

The radar generalized image quality equation (RGIQE) is a metric used to measure both monostatic and bistatic synthetic aperture radar (BSAR) image quality, it is a function of signal-to-noise ratio (SNR) and 2-D bandwidth. The 2-D bandwidth is equal to the area of the transfer function’s (TF) passband region. With the exception of side-looking monostatic geometries, almost all monostatic and bistatic geometries have skewed passband shapes when waveform frequency parameters remain unchanged from pulse to pulse. Most synthetic aperture radar (SAR) applications require a rectangular-shaped passband region, this is achieved by inscribing a rectangular region within the skewed intrinsic passband region. Increasing skewness results in less inscription area reducing 2-D bandwidth, image SNR, and thus RGIQE capacity. In this article, a waveform with frequency agility is used to rectify the skewness that degrades RGIQE capacity. By changing the waveform’s center frequency and instantaneous bandwidth from pulse to pulse in a particular manner, the intrinsic passband region can be de-skewed. The de-skewed shape maximizes the inscription area thus maximizing 2-D bandwidth, image SNR, and RGIQE capacity. Here, three examples are given in this article, one monostatic geometry, and two bistatic geometries. RGIQE capacity is increased by 52.02%, 44.42%, and 79.09% for the three examples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Enhancing Unknown Waveform Detection by Learning Intra and Inter-domain Dependencies with Advanced Attention Fusion Mechanisms

Detection of unknown waveforms in mission-critical communications is a crucial area of interest for the Department of Energy (DoE). Traditional methods and recent deep learning-based approaches often assume that the training set includes all possible classes, which is impractical for detecting new waveforms. This limitation gives rise to the problem of open-set recognition (OSR), which involves correctly identifying known classes while detecting and rejecting unknown or unseen classes. To address this limitation, we propose a novel dual-domain complex-valued neural architecture that jointly processes time-domain and frequency-domain signal representations using transformer mechanisms. A transformer model is a deep learning architecture that uses self-attention mechanisms to process and learn relationships in sequential data. Our model employs a cosine similarity loss to extract domain-specific features and incorporates a transformer architecture in the latent space to weigh the importance of different features from the time and frequency domains. The transformer layer includes stacked self-attention and cross-attention modules to learn intra-domain and inter-domain dependencies, creating a more holistic signal representation. An attention-based fusion module intelligently combines the time and frequency-domain features using multi-head attention, enabling the network to learn the optimal feature for each domain in each input signal. Quantitative results demonstrate the impact of these architectural choices on overall performance, showing significant improvement after incorporating self and cross-attention modules and using complex attention fusion over simple weighted fusion. Our ongoing work will focus on addressing the limitations of threshold-based OSR methods by developing a novel generative framework that integrates a conditional diffusion probabilistic model (DPM). DPM is a generative framework that learns to synthesize complex data by reversing a gradual noising process using a neural network trained to denoise step-by-step. Our goal is to leverage the inherent strengths of DPMs for identifying unknown signals more robustly. One primary advantage of using a DPM is its ability to provide a more reliable anomaly score based on the model's reconstruction error, rather than relying solely on classifier confidence. Additionally, the iterative denoising process of DPMs makes this approach naturally resilient to low Signal-to-Noise Ratio (SNR) conditions, where traditional methods often fail. By implementing this generative framework, we aim to enhance the model's capability to accurately detect unknown waveforms and maintain performance in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Multi‐Scale Seismic Imaging of the Ridgecrest, CA, Region With Waveform Inversion of Regional and Dense Array Data

Abstract We develop an inversion procedure for deriving multi‐scale velocity models with waveform inversions of earthquake and ambient noise data at multi‐frequency bands recorded by regional and dense sensor configurations. The method is applied for the area around the 2019 Ridgecrest earthquake rupture zones, utilizing data recorded by regional stations and dense 2D and 1D arrays with station spacings of ∼5 km and ∼100 m, respectively. Starting with regional Vp, Vs models and locations of Ridgecrest aftershocks, the velocity models and event locations are improved iteratively by inversions of waveforms recorded by regional stations and the 2D array, using a minimum spectral element size of ∼600 m. Waveforms from local events recorded by dense 1D arrays across the M7.1 rupture zone with frequencies of up to 10 Hz are used to resolve small‐scale features of the rupture zone and shallow crust with a local spectral element size of 80 m. The refined models provide self‐consistent descriptions of the rupture zone and the shallow crust embedded in the regional structures. The results reveal pronounced low Vs and high Vp/Vs in the M6.4 and M7.1 rupture zones coinciding with concentrations of seismicity, and also around the Garlock fault and in several local basins. We also observe clear velocity contrasts across the Garlock fault with polarity reversals along strike and with depth. The obtained multi‐scale velocity models can be used to improve derivations of earthquake source properties, simulations of dynamic ruptures and ground motions, and the understanding of fault and tectonic processes in the region.

Geochemistry & Geophysics↗
DOE OSTI2026

Effects of Velocity on Radar Waveforms

A common assumption in pulse-Doppler radar is that when interrogating a point, or point-like target, the received echo waveform is an attenuated and time-delayed, but otherwise faithful facsimile of the transmitted waveform. The effects of a relative line-of-sight velocity between radar and target is often presumed to manifest only as a pulse-to-pulse time delay, usually simplified as a phase shift. However, a significant line-of-sight velocity will also in fact substantially perturb the received waveform even for a single pulse, and may need to be accounted for, and compensated during radar signal processing.

42 ENGINEERING↗
DOE OSTI2025

Designing Yield Grids for Airborne Nuclear Explosions to Maintain Decrements in Rayleigh Waveform Amplitudes

This document details a method for selecting grid points that sample the yields of airborne, low yield nuclear explosions that constrains the relative size of seismic waveforms sourced by explosions that are parameterized by this grid. In detail, we impose this constraint so that the vertical component of ground displacement that is sourced by explosions with a fixed height of burst (HoB) at grid point k change by a fixed factor of a when compared to the waveform amplitudes sourced by explosions at grid point k + 1, as observed at a fixed standoff distance. This gridding thereby preserves amplitude ratios along the grid so that they are agnostic to k. We assert that this method is useful in tests that apply algorithms against synthetic or augmented datasets for which the performance of the algorithm must be measured against source size, and waveform amplitudes must change uniformly (e.g., Berg et al, 2025).

58 GEOSCIENCES↗
DOE OSTI2025

Temporal resolution and fidelity enhancement of arbitrary waveforms

An apparatus, comprising: Mach-Zehnder modulators (MZMs) numbered MZM #1 to MZM #n that exhibit nonlinearity between an input electrical domain signal and an output optical domain signal; a waveform source for applying a first voltage waveform to a first optical arm of said MZM #1; a laser source configured to direct laser light into the two arms of at least said MZM #1 to produce a first output optical domain signal; the apparatus being provided for utilizing said first output optical signal and the nonlinearities of MZMs numbered MZM #2 to said MZM #n to produce a final output voltage waveform that, compared to said input voltage, comprises at least one of: a shorter rise time, a shorter fall time, an increased signal temporal resolution or small signal dynamic range, an increased vertical resolution for small signals or large signals, a reduced noise on small signals or large signals and an increased bandwidth.

Muir, Ryan D.↗
DOE OSTI2025

Nondestructive Evaluation of Concrete: Elastic Property Imaging Through Full Waveform Inversion

Concrete is a major construction material worldwide and plays a crucial role in the nuclear industry. The elastic properties of concrete are prone to change and degrade while in service, as it is often subjected to extreme operational and environmental conditions. An accurate evaluation of concrete's elastic properties is thus essential to ensure structural integrity and safety. This is especially true for concrete in nuclear power plants, where irradiation effects significantly impact concrete mechanical properties. There are various methods to assess these properties, with ultrasound-based techniques showing high potential due to their nondestructive nature, cost-effectiveness, and safety. While several nondestructive evaluation methods exist, most rely on idealizations such as assuming homogeneous material and plane wavefronts. In this work, we address these issues by introducing an ultrasound-based nondestructive method aimed at reconstructing spatially varying images of concrete mechanical properties. By accurately modeling wave physics, including scattering and reflection, we overcome several of the aforementioned idealizations and aim to utilize the full waveform for imaging material properties through depth, resulting in more reliable images. Full waveform inversion (FWI) was first introduced by geophysicists to reconstruct subsurface elastic property images. The goal is to minimize the difference between simulated and recorded wavefield signals, often through gradient-based optimization algorithms. While FWI is primarily conducted using the acoustic approximation of the wave equation, few works focus on elastic FWI, where the goal is to reconstruct images of not only the pressure wave speed but also the shear wave speed and density (or their equivalents). This work explores the potential of using elastic FWI to predict concrete mechanical properties as an initial effort for a more accurate monitoring of concrete conditions in service. Reconstructing images of different elastic parameters enables more specificity and accurate condition diagnosis. This paper will detail this approach and provide examples demonstrating the effectiveness of elastic FWI in reconstructing comprehensive maps of concrete mechanical properties.

42 - ENGINEERING↗
DOE OSTI2026

Open Set Recognition for Unknown Waveform Classification

This presentation applies open set recognition to classify unknown waveforms, enabling systems to not only identify known types but also reliably detect when waveforms fall outside the training distribution. This approach enhances robustness by avoiding forced misclassification of novel or anomalous signals.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Sequential Fracture Activation and Stress Evolution During EGS Stimulation at Utah FORGE Revealed by Waveform Cross‐Correlation

Mapping fracture networks in Enhanced Geothermal Systems (EGS) is essential for optimizing reservoir performance, yet complex fracture evolution during stimulation remains difficult to resolve. This study examines the evolution of microseismicity and fracture networks during stage 3 of the 2022 EGS stimulation at the Utah Frontier Observatory for Research in Geothermal Energy site. We map the fracture network represented by 20 clusters of seismic events identified by waveform similarities with cross-correlation. We characterize their geometric properties such as strike, dip, length, and width, and analyze the time evolution of activated fractures. The results reveal a systematic fracture evolution: early activation of pre-existing natural fractures, complex network development during peak injection, and continued activation of less favorably oriented fractures post-injection. Magnitude calibration using the Principal Component Analysis of cross-correlated waveforms improves relative amplitude measurements, refining estimations of the Gutenberg-Richter b-values with spatial variations in b-values suggesting stress re-distribution across the stimulated area. Analysis of the stress state of selected fractures further shows that fractures requiring higher excess pore pressure primarily activate at the end of injection and post-injection, highlighting stress transfer due to pore pressure as a dominant triggering mechanism. These findings provide insights into fracture propagation, stress evolution, and seismic hazard assessment in EGS reservoirs.

Asirifi, Richard [Texas A & M Univ., College Stati↗
DOE OSTI2025

Scanless laser waveform measurement in the near-infrared

Field-resolved measurements of few-cycle laser waveforms allow access to ultrafast electron dynamics in light–matter interactions and are key to future lightwave electronics. Recently, sub-cycle gating based on nonlinear excitation in active pixel sensors has allowed the first single-shot measurements of mid-infrared optical fields. Extending the techniques to shorter wavelengths, however, is not feasible using silicon-based detectors with bandgaps in the near-infrared. Here, we demonstrate an all-optical sampling technique for near-infrared laser fields, wherein an intense fundamental field generates a sub-cycle gate through nonlinear excitation of a wide-bandgap crystal, in this case, ZnO, which can sample the electric field of a weak perturbing pulse. By using a crossed-beam geometry, the temporal evolution of the perturbing field is mapped onto a transverse spatial axis of the nonlinear medium, and the waveform is captured in a single measurement of the spatially resolved fluorescence emission from the crystal. The technique is demonstrated through field-resolved measurements of the field reshaping during nonlinear propagation in the ZnO detection crystal.

Truong, Tran-Chau (ORCID:0000000348940635)↗
DOE OSTI2026

Error quantification and comparison of binary neutron star gravitational waveforms from numerical relativity codes

Future gravitational wave detections of merging binary neutron star systems have the possibility to tightly constrain the equation of state of dense nuclear matter. In order to extract such constraints, gravitational waveform models need to be calibrated to accurate numerical relativity simulations of the late inspiral and merger. In this work, we take an essential step toward classifying the error and potential systematics in current generation numerical relativity simulations of merging binary neutron stars. To this end, we perform a direct comparison of two codes (fil, spec), which differ in many aspects, including the numerical methods and discretizations used and equations solved. We find that despite these different approaches, the codes are—within current numerical resolution bounds—fully consistent, and broadly comparable in cost for a given accuracy level. Our results indicate that the error in the waveforms is primarily dominated by the hydrodynamic evolution, consistent with earlier findings in the literature. Finally, we also discuss current limitations and cost estimates for numerical relativity simulations to reach the accuracies required in the era of next-generation gravitational detectors.

gravitational waves↗
DOE OSTI2025

Stochastic Waveform Estimation at the Fundamental Quantum Limit

Although measuring the deterministic waveform of a weak classical force is a well-studied problem, estimating a random waveform, such as the spectral density of a stochastic signal field, is much less well understood despite it being a widespread task at the frontier of experimental physics. State-of-the-art precision sensors of random forces must account for the underlying quantum nature of the measurement but the optimal quantum protocol for interrogating such linear sensors is not known. We derive the fundamental precision limit: the extended-channel quantum Cramér-Rao bound. In the experimentally relevant regime in which losses dominate, we prove that non-Gaussian-state preparation and measurement are required to achieve this fundamental limit and we determine numerically the optimal non-Gaussian protocol. We discuss how this scheme could accelerate searches for signatures of quantum gravity, stochastic gravitational waves, and axionic dark matter.

Axions↗
DOE OSTI2024

Grid Edge Waveform Analytics Framework for Event Detection and Classification

This paper provides a grid edge waveform analytics framework for power system event detection and classification in the local as well as in the wide area. This framework overviews data excellence for event detection and classification. The data excellence describes the data acquisition process and requirements, data processing, data quality, and data integrity. Power system event detection in the local area based on different features such as energy-based, cyclostationary approach, template matching, and wavelet transform are also discussed. Furthermore, local area event detection and classification using approaches such as statistical, signal processing, artificial intelligence, and hybrid are also discussed. Moreover, an overview of wide-area event detection and classification along with several other aspects such as wide-area events, wide-area event detection approaches, event location and system performance, event pattern recognition, inter-area oscillation, and wide-area frequency response under variable deployment of inverter-based resources are also provided. The proposed framework is the first step toward the goal of developing appropriate tools and methodologies to detect and classify local as well as wide-area events using waveform analytics. The appropriate event detection and classification framework development is especially important now as more and more grid edge devices with communication capabilities are being deployed in the modern power grid than ever before.

Bhusal, Narayan↗
DOE OSTI2025

Full‐Waveform Simulation of Infrasound Propagation in the Atmosphere: A Case Study of the 2023 April 20 SpaceX Starship Explosion

Infrasound, low‐frequency sound below 20 Hz, has been a key technology to monitor explosion events in the atmosphere. The International Monitoring System (IMS) of the Comprehensive Nuclear‐Test‐Ban Treaty Organization provides the means for continuous monitoring of infrasonic events worldwide. Infrasonic techniques for event location and size estimation can also complement other observational techniques for the detection and characterization of the entry of asteroids or large meteoroids. In this study, we describe the detection capability of IMS infrasound stations for an explosive event in the middle of the atmosphere. Full‐waveform simulations are performed with the specification of atmospheric conditions and incorporated into the event location and explosion yield estimation. We applied it to the 2023 April 20 SpaceX Starship explosion at 29 km altitude. Starship is a super heavy‐lift space vehicle constructed by SpaceX and known as the largest and most powerful rocket ever built. The Starship explosion created huge pressure disturbances in the atmosphere, and its infrasound was detected by the IMS arrays in North America between 2000 and 4000 km. Independent observational data and available ground‐truth information provide a rare opportunity to evaluate the monitoring capability of the IMS network for elevated sources in the atmosphere. We also demonstrate the capability of full‐waveform simulation for infrasound wavefield characterization and prediction to improve event location and yield estimation.

Geosciences↗
DOE OSTI2024

Three phase spectral interferometry for recording high dynamic range optical waveforms with <1 ps resolution over >2 ns records applied to closed-loop pulse shaping

Herein we demonstrate, to our knowledge, a novel spectral interferometry technique that simultaneously captures three spectral interferograms of a signal waveform with a reference pulse. The measured performance is robust to nonidealities and ambient drifts by implementing a precisely calibrated 3 × 3 polarization maintaining (PM) splitter that provides three phase shift differences nominally spaced 120° apart. The system can achieve long record length by implementing three, high resolution, virtually imaged phase array (VIPA) spectrometers. Here, we experimentally implement this technique and demonstrate the measurement of waveforms with >2ns of record while maintaining <1ps resolution.

42 ENGINEERING↗
DOE OSTI2024

Report on the sensitivity kernel construction and updating the SPiRaL model with waveform data

The WAVEFORMS Initiative in the Ground-based Nuclear Detonation Detection (GNDD) program includes research leading towards the prediction of entire seismic and acoustic waveforms produced by natural and manmade events, including explosions. A key aspect of this research is the development of Earth (seismic) models at multiple scales including crustal, regional, and global. The work described here pertains to the global-scale seismic tomography effort led by LLNL.

58 GEOSCIENCES↗
DOE OSTI2024

Program to Operate Waveform Generator

This poster is about the project that I did this year as a CCI intern. The project is code to control a waveform generator as well as send custom waveform types.

Manzo, D'Angelo↗
DOE OSTI2024

Enhanced PDV waveform search and analysis method using parallel circular-convolution / cross-correlation for improved dynamic surface velocity extraction [Poster]

Previous work on exhaustive search methodologies for extracting best-match parameters pertaining to dynamic surface quantities from PDV was done by cross-correlating synthetically generated PDV waveforms with observed counterparts using the circular-convolution theorem. This work was further developed into an open-source PDV analysis toolkit called CCPDVANALYSIS which expands upon and enhances the previously tested methods by parallelizing serial algorithmic components and incorporating a comprehensive script library for different flavors of instantaneous frequency functions utilized in generating synthetic PDV waveforms. Results of these enhancements have been shown to markedly decrease execution times of exhaustive search and extraction algorithms and produce improved velocity recoveries for low-velocity and dynamically varying velocity signals. The CCPDVANALYSIS script library demonstrates an advanced method for extracting velocities from low-velocity and non-constant velocity signals further extending and improving the methods beyond capabilities of traditional frequency domain tools.

97 MATHEMATICS AND COMPUTING↗