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At least 181 records · Page 10

Double exponential approximation and inverse double exponential fit for Bell Labs and International-Military Standard EMP waveforms

We summarize here the double exponential and inverse double exponential approximations for two common EMP waveforms, the Bell Laboratories (Bell Labs) and the International- military standard (IEC-MIL-STD). Both models have been used frequently due to their relatively easy analytical expressions for both the time domain waveforms and their associated frequency domain spectra.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SWIFT - Shaped-Waveform Interrogation of Fluids Technique

Researchers at Los Alamos have developed the Shaped-Waveform Interrogation of Fluids Technique (SWIFT), a technology enabling unprecedented process control capability. This technology provides important composition, flow rate, and pipe thickness measurements in real-time, at an extremely low cost and maintenance cycle. By utilizing a specialized shaped-waveform, as well as state-of-the-art signal processing, this information can be gathered without any frequency-domain signal processing, allowing for simplified electronics compared to nearly any other meter on the market. Since this technology is in expensive and non-invasive, with the capability of measuring liquids in both flow pipes and sealed containers, it is perfect for several industrial applications in the oil and gas, beverage, chemical, and pharmaceutical spaces. We are seeking a commercialization partner to license the technology or fund us through a Cooperative Research and Development Agreement (CRADA) to a further develop a usable product for commercial purposes.

47 OTHER INSTRUMENTATION↗

Report on the LLNL Global Full-waveform Inversion Workflow and Progress

LLNL has developed the SPiRaL global seismic tomography model based upon millions of body wave travel times and surface wave dispersion curves in the period range of 25-200 seconds (Simmons et al., 2021). The motivation to construct the SPiRaL model (which stands for S-, P-, Rayleigh, and Love waves) is based upon the guidance provided by a 3-D model workshop held in Berkeley in 2007 and documented in a paper by Zucca et al. (2009). It was concluded in Zucca et al. (2009) that a “practical and obtainable” model is one that predicts body wave travel times for event location while also predicting surface wave velocities for moment tensor estimation. We have largely followed that guidance which has led to the construction of SPiRaL. Looking forward, we now seek to improve the global model through full waveform inversion (FWI). This necessitates the development/customization of an efficient and flexible modeling workflow to automate the process using LLNL’s supercomputing platforms. This report briefly outlines the work that being performed at LLNL to develop the necessary tools and framework to update the SPiRaL global model with full waveform information.

58 GEOSCIENCES↗

Challenges and Potential of Waveform Modeling for Crustal Scale Predictions

Waveform modeling is crucial to improving our understanding of observed seismograms. Forward simulation of wavefields provides quantitative methods of testing interactions between complicated source functions and the propagation medium. Here, we discuss three experiments designed to improve under standing of high frequency seismic wave propagation. First, we compare observed and predicted travel times of crustal phases for a set of real observed earthquakes with calculations and synthetic seismograms. Second, we estimate the frequency content of a series of nearly co-located earthquakes of varying magnitude for which we have a relatively well- known 1D velocity model. Third, we apply stochastic perturbations on top of a 3D tomographic model and qualitatively assess how those variations map to differences in the seismograms. While different in scope and aim, these three vignettes illustrate the current state of crustal scale waveform modeling and the potential for future studies to better constrain the structure of the crust.

58 GEOSCIENCES↗

Probing D-region globally using lightning waveforms detected by ENTLN [Slides]

This report includes research and data that the author's state demonstrates "the technique from [Shao et al., Nature Geoscience, 2012] can be used with ENTLN waveforms. Furthermore, an "automated processing has been developed to produce averaged waveforms and associated measurements." Ideas for future work is also presented.

54 ENVIRONMENTAL SCIENCES↗

Electrorefining Bismuth Using AC Superimposed DC Waveforms

Bismuth has been successfully electrorefined using both direct current (DC) and alternating current (AC) superimposed DC waveforms on a kilogram scale at Brigham Young University (BYU) in Provo, Utah. Finding a suitable surrogate for Pu Electrorefining has always been a technical challenge. This work allows the possibility to improve Pu electrorefining with nonradioactive material at universities, which greatly reduces the cost at Lawrence Livermore National Laboratory (LLNL) for improving Pu Electrorefining. Several possible surrogates (Ce, In, Sn, Zn, and Bi) were selected based on their ability to mimic the Pu electrorefining process. Ce and In electrorefining experiments were conducted at the same temperature as Pu electrorefining in CaCl 2 while Sn, Zn, and Bi, electrorefining experiments were conducted at a lower temperature in a eutectic molten salt composed of LiCl, KCl, and CaCl 2 . The electrorefining experiments using Ce with a Ga impurity did not produce a cathode ring. While the remaining Ce anode after electrorefining was significantly less than what was initially added, Scanning Electron Microscopy with Energy Dispersive X-Ray (SEM-EDX) analysis showed that the Ce had been oxidized and formed a colloid with the surrounding molten salt. This is supported in the literature by analysis of Ce-rich CaCl 2 mixtures. All the electrorefining experiments except for the Ce electrorefining experiments did not introduce an impurity to the system. Electrorefining experiments with In showed that the InCl 3 volatilized out of the molten salt to an extent that only a low current (<<1 A) could be supported without decomposing the molten salt. Zn electrorefining experiments had marginal success, however an easily separable product was not formed. The Zn had to be rinsed from the salt after the experiment. Of the identified potential surrogates. Investigated, only Bi and Sn yielded an easily separable product ring, which enables quantitative analysis of yields and coulombic efficiencies. Bismuth was first identified as a surrogate at BYU, while Sn was identified as a surrogate at LLNL later. Thus, the electrorefining experiments conducted at BYU using AC superimposed DC waveforms used Bi as the metal to be electrorefined.

36 MATERIALS SCIENCE↗

Adjoint Waveform Tomography for Next Generation Seismic Analyses and Monitoring

The development of methods and capabilities to compute complete waveform simulations in three-dimensional (3D) Earth models along with adjoint methods for computing the fully 3D sensitivity kernels in the 2000's set the stage for new advances in seismic imaging. I believe that the full benefits of adjoint waveform tomography (AWT) are not yet fully realized and this will be an important direction for the future of seismic tomography.

58 GEOSCIENCES↗

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↗

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↗

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↗

Elastic Stochastic Full Waveform Inversion (eSFWI)

This collaboration between Lawrence Livermore National Security, LLC (LLNS) as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Chevron USA Inc., acting through its Chevron Technical Center division, aimed at developing next-generation computational methods for the Elastic Stochastic Full Waveform Inversion (eSFWI). Seismic imaging is heavily used in the oil and gas industry for identifying and operating subsurface reservoirs. Improved seismic imaging methods can improve productivity, lower costs, and improve operational and environmental safety. This CRADA demonstrated that new high-performance computing (HPC) architectures being rolled out over the next five years can enable unprecedented seismic imaging resolution when using eSFWI techniques to process active seismic data. An open-source computational mini-application was developed, capable of demonstrating near-peak performance for eSFWI algorithms on CPU and GPU enabled HPC platforms. Performance was demonstrated on LLNL HPC systems such as Lassen, as well as on Chevron systems. This project benefited Chevron USA Inc. by demonstrating the potential computational efficiency of their full waveform inversion capabilities used to characterize oil/gas reservoirs, which in turn benefits the public through potential increases in capabilities to perform analysis of leasing sites.

04 OIL SHALES AND TAR SANDS↗

Waveform Simulation Framework: User Manual with Tutorials

This manuscript describes the Waveform Simulation Framework (WSF), a Python-based framework that provides a unified, programmable interface for generating synthetic seismograms for applications such as seismic array design, method development, and special event analysis. WSF standardizes how users define sources, receivers, and velocity models while abstracting simulator-specific configuration details, enabling workflows that are largely independent of the underlying numerical engine. The document provides installation guidance and tutorial-driven examples for three WSF simulator wrappers—WSF PyFK, WSF SW4, and WSF SPECFEM2D—illustrating end-to-end workflows from forward waveform simulation to common post-processing tasks (e.g., visualization and backprojection) using consistent data products (e.g., ObsPy Stream objects and SAC files).

97 MATHEMATICS AND COMPUTING↗

Complex Attosecond Waveform Synthesis at FEL FERMI

Free-electron lasers (FELs) can produce radiation in the short wavelength range extending from the extreme ultraviolet (XUV) to the X-rays with a few to a few tens of femtoseconds pulse duration. These facilities have enabled significant breakthroughs in the field of atomic, molecular, and optical physics, implementing different schemes based on two-color photoionization mechanisms. In this article, we present the generation of attosecond pulse trains (APTs) at the seeded FEL FERMI using the beating of multiple phase-locked harmonics. We demonstrate the complex attosecond waveform shaping of the generated APTs, exploiting the ability to manipulate independently the amplitudes and the phases of the harmonics. The described generalized attosecond waveform synthesis technique with an arbitrary number of phase-locked harmonics will allow the generation of sub-100 as pulses with programmable electric fields.

47 OTHER INSTRUMENTATION↗

A new MicroTCA-based waveform digitizer for the Muon g-2 experiment

We present the design of a new $\mu$TCA-based waveform digitizer, which will be deployed in the Muon g-2 experiment at Fermilab and will allow our pileup identification requirement to be met. This digitizer features five independent channels, each with 12-bit, 800-MSPS digitization and a 1-Gbit memory buffer. The data storage and readout along with configuration are handled by six Xilinx Kintex-7 FPGAs. In addition, the digitizer is equipped with a mezzanine card for analog signal conditioning prior to digitization, further widening its range of possible applications. The performance results of this design are also presented, highlighting its $0.51 \pm 0.13$ mV intrinsic noise level and $< 22$ ps intrinsic timing resolution between channels. We believe that its performance, together with its flexible design, could be of interest to future experiments in search of a cost-effective waveform digitizer.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Python Waveform Cross-Correlation

PyWCC is a tool to compute seismic waveform cross-correlation coefficients on single-component or multiple-component seismic data across a network of seismic sensors. PyWCC compares waveform data templates with continuous seismic data, associates the resulting detections, identifies the template with the highest cross-correlation coefficient, and outputs a catalog of detections above a user-defined absolute cross-correlation threshold value.

Templeton, Dennise↗

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques -- A proof of concept

We investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Method for determining a histogram of variable sample rate waveforms

A computer-implemented method comprises receiving a plurality of sampled data points, each data point including a y value and a t value; defining a plurality of bins; defining an array of elements; dividing the sampled data points into a plurality of sections; assigning a plurality of polynomial equations, one polynomial equation to each section, each polynomial equation having a waveform that fits the data points of the associated section; determining a plurality of section bin times, one section bin time for each bin in each section, each section bin time determined using the polynomial equation and indicating an amount of time that the waveform has values in the range of one of the bins; and adding the section bin time for each bin in each section to the histogram data in the array element pointed to by the number of the bin.

Tohlen, Michael Aaron↗

Contrasting Time-Frequency Representations for Unknown Waveform Detection

In real-world applications like spectrum management and interference detection, dealing with unseen electromagnetic waveforms is critical. Although some methods attempt to simulate open set data using generator models, they face challenges in generating synthetic samples for open set while simultaneously selecting an optimal discriminator for accurate classification. This results in difficulties capturing distinctive features across classes, especially in dynamic scenarios where new classes emerge. To detect unseen waveforms, we propose combining time and frequency domain features with cosine similarity loss to enhance feature distinctiveness and enabling more accurate predictions. This approach efficiently captures more comprehensive information than single-domain representations or approaches without cosine loss. Additionally, our model avoids generic feature vectors by extracting class-specific features during training, resulting in improved class representation. The experiment results show that this combined feature approach with cosine loss outperforms single-domain models and improves accuracy by 10\% over models without cosine loss.

99 - GENERAL AND MISCELLANEOUS↗