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Autonomous algorithms use energy detectors to find template waveforms for repeating sources. These template waveforms parameterize pattern matching detectors. Template extracting is upstream of all template matching efforts. Operations must adaptively quantify performance of template methods
SPE is a project in order to develop new, more physics-based, seismic models of explosions (see Nelson et al. 2013). One key component of this effort is numerical modeling enabled by modern state-of-art code/software. Accurate modeling of the shape and amplitude of seismic waves from their generation to their propagation to remote monitoring seismic stations is important to our ability to determine the origin and strength of the source from remote recording. In this project, the modeling is performed by coupling two codes HOSS and SPECFEM3D. HOSS models the dynamic nonlinear processes happening near the explosion. SPECFEM3D computes the propagation of seismic waves as they travel through 3D complex Earth models. SPECFEM3D was modified in order to be driven by a set of time-series calculated by HOSS in lieu of a seismic source. The goal of this summer project is the investigation of several questions pertinent to the establishment of a full end-to-end modeling capability from the high-rate strain regime area to remote distances where seismic station record seismic waves generated by explosions. The investigated questions are: (1) How to perform proper filtering? Direct-solution modeling only sustains a limited range of frequency depending on the grid size. As we go from one modeling domain to the other via coupling, the mesh size is getting coarser to allow modeling at large scale but also to account for the fact that high-frequency waves do not physically travel to large distances. So filtering of the time-series generated by the near-field hydrodynamic modeling is a current practice often employed but its effects on the modeled waveforms has to be investigated. (2) Quantitative assessment of the efficiency of attenuation to remove high-frequency content of the wavefield. This assessment will allow to create meshes with a grid size appropriate to the actual physics of wave propagation for a given explosion. (3) Checking that the coupling process and the two codes respect the cylindrical symmetry that is expected in the case of a pure explosion in a half-space. (4) The effect of the state-of-stress in the near-source area on the modeled seismic waveforms. These questions will be investigated through the modeling of SPE-4P, the fourth explosion of this series because it was designed to have little interaction with the geologic surrounding and the free surface of the Earth so that it is the most explosion-like experiment, with the most symmetries to be verified.
We examined the feasibility of using fiber-optic Distributed Acoustic Sensing (DAS) as an alternative to a traditional seismic array. Seismic arrays are used routinely globally to measure waveform propagation parameters and signal features including back-azimuth (BAZ) and apparent horizontal velocity through the process of beamforming or frequency-wavenumber (f-k) array analysis with the assumption that the signals travel across the array as a plane-wave. These measurements are useful for identifying signal detections as teleseismic, regional, or local distance seismic phases based on their velocities traveling across the array (e.g., Rost and Thomas, 2001). Signal enhancement is the main benefit of array processesing through the stacking of multiple channels as a phased array. This enhancement increases as the square root of the number of channels relative to a single seismic station (e.g., Rost and Thomas, 2001), which is a factor of 3 from a typical nine-channel array. DAS provides the potential of stacking waveforms from 100’s to 1000’s of channels. However, DAS is a novel technology designed for geophysical exploration and therefore has some limitations which we will explore. We started with the dataset from the PoroTomo project because of its unique experimental layout of colocated geophone array and DAS deployment so the two recording technologies can be compared side-by-side.
Denoising contaminated seismic signals for later processing is a fundamental problem in seismic signals analysis. The most straightforward denoising approach, using spectral filtering, is not effective when noise and seismic signal occupy the same frequency range. Neural network approaches have shown success denoising local signal when trained on short-time Fourier transform spectrograms (Zhu et al 2018; Tibi et al 2021). Scalograms, a wavelet-based transform, achieved ~15% better reconstruction as measured by dynamic time warping on a seismic waveform test set than spectrograms, suggesting their use as an alternative for denoising. We train a deep neural network on a scalogram dataset derived from waveforms recorded by the University of Utah Seismograph Stations network. We find that initial results are no better than a spectrogram approach, with additional overhead imposed by the significantly larger size of scalograms. A robust exploration of neural network hyperparameters and network architecture was not performed, which could be done in follow on work.
The TurboWave I and II infrasound campaigns were conducted to examine short term variability in acoustic propagation at local and regional distances. The tests were conducted in nearly co-located regions at the Energetic Materials Research and Testing Center in Socorro, NM between 2019 and 2020 and recorded across a variety of acoustic microbarometer sensors. This report details the waveform data recorded from the experiment and coincides with data archival at the Incorporated Research Institutions for Seismology. The report includes a description of the experiment along with the types of data and instruments. The data release includes raw waveform data as well as metadata information.
Sandia National Laboratories performed tests to address the potential vulnerability concerns of a coupled High-Altitude Electromagnetic Pulse (HEMP) inducing secondary coupling onto critical instrumentation and control cables in a nuclear power plant, with specific focus on early-time HEMP. Three types of receiving cables in nine configurations were tested to determine transfer functions between two electrically separated cables referenced to the common mode input current on the transmitting cable. One type of transfer function related the input short circuit current and resulting open circuit voltage on the receiving cable. The other transfer function related the input short circuit current and the resulting short circuit current on the receiving cable. A 500 A standard HEMP waveform was input into the transfer functions to calculate peak coupling values on the receiving cables. The highest level of coupling using the standard waveform occurred when cables were in direct contact, with a peak short circuit current of 85 A and open circuit voltage of 9.8 kV, while configurations with separated cables predicted coupling levels of less than 5 A or 500 V.
This report summarizes results from a 2 year effort to improve the current automated seismic event processing system by leveraging machine learning models that can operated over the inherent graph data structure of a seismic sensor network. Specifically, the GraphAlign project seeks to utilize prior information on which stations are more likely to detect signals originating from particular geographic regions to inform event filtering. To date, the GraphAlign team has developed a Graphical Neural Network (GNN) model to filter out false events generated by the Global Associator (GA) algorithm. The algorithm operates directly on waveform data that has been associated to an event by building a variable sized graph of station waveforms nodes with edge relations to an event location node. This builds off of previous work where random forest models were used to do the same task using hand crafted features. The GNN model performance was analyzed using an 8 week IMS/IDC dataset, and it was demonstrated that the GNN outperforms the random forest baseline. We provide additional error analysis of which events the GNN model performs well and poorly against concluded by future directions for improvements.
An innovative, compact 288GHz interferometer has been fabricated, tested, installed and successfully demonstrated on the LAPD-U magnetized plasma at UCLA. The system takes advantage of frequency modulated (FM) radar techniques to deliver a compact heterodyne system. In addition, the reflected power from the source is taken advantage of to eliminate the need for additional quasi-optical components. Electron density in LAPD-U plasma has recently been increased substantially thereby requiring a higher frequency/shorter wavelength interferometer to avoid deleterious refractive effects. This system satisfies those needs. The system uses a 96GHz varactor tuned Gunn oscillator which passes to a passive tripler. This tripler has ~3% conversion efficiency. The 288GHz radiation is then coupled to free space using a so-called dual-mode or Pickett horn. The output 288GHz beam is then coupled to an aspheric lens manufactured from low-loss, high-density polyethylene. This lens is employed to collimate the emerging beam. Small axial adjustment of the lens position can also be used to create a slowly focusing beam so as to optimize the measured signal. In addition, up-down or side-to-side adjustment of the lens can be utilized to steer the beam vertically or horizontally – again to optimize alignment. The propagating beam passes through a beam splitter and then through a water-free, bubble-free fused quartz window into the LAPD-U vacuum vessel. The beam-splitter is a thin sheet of G10 which reflects a small fraction of the incident power (~5 %) towards a zero-bias detector optimized for the frequency range from 220 to 300GHz. Note that waveguides at this frequency have dimensions of ~0.9mm x 0.45mm and so have very large conductive losses. This drives the use of quasi-optical propagation. The detector requires no DC bias and is very responsive (> 1V/mW into 1MΩ). Radiation is coupled to the detector via a similar lens-horn arrangement used for the launch. This reflected beam acts as the local oscillator or reference millimeter-wave beam for the detector. The remainder of the launched source beam then enters the LAPD-U vacuum vessel and passes through the plasma at the mid-plane until reaching the opposing port which is closed off with an aluminum flange. This flange is used as a mirror to retroreflect the incident 288GHz beam back along its path. The retroreflected beam exits the input port but does NOT couple directly into the zero-bias detector. Instead, the majority of the return power continues towards the 288GHz source. As mentioned above the transmitted beam enters the source a second time. This would appear undesirable. However, at these frequencies multipliers are highly non-linear elements which results in a significant portion of the return beam (~20%) re-emerging from the multiplier and horn and then coupling via the G10 beam-splitter to the zero-bias detector. This approach eliminated the need for a second quasi-optical beam-splitter. The system is extremely compact measuring approximately 28 inches x 20 inches. The above did not explain how heterodyne operation was achieved. As mentioned above the Gunn oscillator is able to be varactor tuned. This allows a low voltage to be applied to control the operating frequency of the Gunn oscillator. During heterodyne operation a sawtooth shaped voltage is applied to the varactor at 750kHz using an 80MHz Arbitrary Waveform Generator (AWG). This voltage changes the Gunn frequency linearly during the up-sweep which is then reset abruptly at the sawtooth crash to be immediately followed by another linear sweep. Passage through the 288GHz multiplier triples the frequency change experienced by the electromagnetic wave. These frequency changes are small – tens of megahertz. This FM radar approach results in the launched electromagnetic wave frequencies at the detector for the reference and plasma wave to be different. The approximately 10 ns delay propagation delay for the plasma beam results in the local oscillator and plasma beams NOT having an identical frequency – there is in fact a fixed difference frequency. The frequency tuning level of the Gunn oscillator is then adjusted so that there is ONE cycle of this difference frequency during each linear ramp. During the sawtooth crash or downward re-sweep this one cycle replays in reverse but on a very fast timescale. The process then repeats. Low-pass filtering eliminates the fast re-sweep to leave a pure sine wave heterodyne signal. When the plasma is present it introduces a phase delay in the sine wave (caused by the extremely small Doppler shift resulting from the optical path length change). Of course, to measure this phase change we need a reference. This is simply obtained from an arbitrary waveform generator which provides a synchronized output pulse train which again is low pass filtered to obtain a 750kHz sinusoidal voltage reference for the interferometer. The interferometer was installed on LAPD-U where it has worked reliably and has established that electron densities exceeding 1x10 13 cm -3 are routinely achieved. In addition, the system sensitivity was able to easily observe density fluctuation at frequencies up to 50kHz. FM Radar techniques have enabled a full demonstration of a compact, sensitive, high frequency (288GHz/1mm) heterodyne interferometer.
The goal of this project was to develop and demonstrate an advanced dielectric barrier discharge (DBD) plasma actuator technology. We set out to demonstrate the efficacy and impact of the new actuator technology as a key component of an active load control system for wind turbines. A DBD plasma actuator consists of a thin layer of dielectric material separating a pair of offset electrodes. One of those electrodes is embedded between the dielectric layer and a non-conductive substrate, while the other is exposed to air. When driven by an appropriate high voltage waveform, the device ionizes the air near the surface of the dielectric and adjacent to the exposed electrode. Collisions between the ions in the plasma and neutral air molecules result in a wall-jet – a region of induced air velocity that can be used to modify the flow around a lifting body. Use of the device near the trailing edge of a wind turbine blade, designed in such a way as to amplify the effects of the flow-modifying device, can result in large changes to the global forces experienced by the blade. Because of the fast response time of the device, it can allow the turbine to react in real time to changes in the wind associated with turbulence, wind shear, gusts, and the like, when paired with appropriate sensors and control algorithms. The goal of this project was to increase the capacity of the device to induce velocity on its surface at the levels required by large, utility-scale wind turbines. The first technical goal was to increase the induced velocity from the current industry-best of about 4 m/s to 10 m/s by modifying the electrical waveform used to drive the device and by introducing a semi-conductive surface coating to control electrostatic charge build-up on the surface. The second goal was to use the device to modify the lift on a representative airfoil in a wind tunnel, demonstrating a reduction in lift coefficient of 0.2 or better. The third goal was to produce an actuator-induced velocity of 20 m/s. Alongside our partners at the University of Texas at Dallas, we also applied modern, advanced design methods to optimize the impact of the technology on the design of wind turbines. We also had planned to install a segmented, active load control system on a test turbine to demonstrate the ability to reduce unsteady aerodynamic forces on the turbine associated with changes in the wind. The highest induced velocity achieved during this research was 11 m/s. However, practical design constraints limited the change in lift coefficient to about 0.12 for a representative airfoil in the wind tunnel at a Reynolds number of 400,000. The primary conclusion is that the plasma actuator control authority remains insufficient for practical purposes when extrapolated to Reynolds numbers over 1 million. The potential impact of the active lift control concept was evaluated through detailed simulations for three wind turbine sizes: a 3.4MW onshore turbine, a 10MW offshore turbine, and a 15MW offshore turbine. A feedback control system was designed for each turbine within two scenarios: one where the active lift control is used as a retrofit capability on the baseline design, and the other where the designers were permitted to “upscale” the turbines in order increase annual energy production. The levelized cost of energy was then evaluated for the range of turbine sizes and design configuration. It was found that the LCOE reduction associated with active lift control fell in the range of 0.7% to 7.2%, with the highest reduction associated with upscaling the 3.4MW turbine.
This project aims to improve field-scale Carbon Capture and Storage (CCS) assessments by enhancing petrophysical and geophysical log predictions through machine learning and neural networks. In our work during EY23, we applied Conditional Variational Autoencoders (CVAEs) to predict compressional velocity (Vp) and assess CO2 saturation levels in geological formations at the Illinois Basin Decatur Project (IBDP). In another task, we improved full-waveform inversion (FWI) methods with machine-learning approaches using lithological constraints. Full-waveform inversion (FWI) of seismic data estimates the elastic properties of subsurface rocks with high spatial resolution.
One of the most iconic of radar waveforms is the Linear FM chirp. It is well-behaved and well-understood, and has become the gold standard against which other radar waveforms are measured. It has a number of desirable attributes, but is not without some issues. It may be processed by a number of techniques with many variations. Details of the Linear FM chirp are presented and discussed in this report.
As nearly every aspect of the electric power grid undergoes rapid change, measurement technologies that support grid operation and planning must evolve as well. The rapid large-scale deployment of inverter-based resources (IBRs) vital to achieving the nation’s clean energy goals has in some cases led to negative impacts on the reliability and security of the bulk power system (BPS). Advanced power system measurements, including synchronized phasor and waveform measurements, are key to making IBR integration secure and reliable. To this end, the Department of Energy (DOE) initiated the PROGRESS MATRIX project to develop advanced measurement capabilities and analytics that will accelerate adoption of IBRs while improving the reliability and resilience of the BPS. This report discusses the outcomes of the project, which was a joint effort between the Pacific Northwest National Laboratory (PNNL), Oak Ridge National Laboratory (ORNL), the National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL). In the project’s first year, PNNL, NREL, and ORNL partnered with the Bonneville Power Administration (BPA), the Western Area Power Administration (WAPA), and Kauai Island Utility Cooperative (KIUC) to understand their existing measurement capabilities and the gaps limiting deployment of IBR-focused measurement systems and analytics. The other primary activity in the first year was deployment of GridSweep instruments, which provide unprecedented precision in waveform measurement while probing distribution systems. The instruments were deployed at Dominion Energy and the University of California, Riverside. In the project’s second year, the input from partner utilities and collected measurements were used to advance measurement capabilities. Twelve analytical methods spanning disturbance analysis, power plant evaluation, feeder evaluation, and modeling were developed. Two software tools were developed, one to analyze GridSweep measurements and another to automatically evaluate the control performance of power plants connected to the BPS. Testbeds at ORNL and NREL were augmented to better enable studies of IBR integration. The project culminated in demonstrations of these analytical methods, software tools, and testbeds, both in the field and in the laboratory. This report discusses these various accomplishments and documents the significant progress in developing advanced measurement capabilities to support the secure, reliable, and accelerated adoption of IBRs in the BPS.
We report the first demonstration of using the Quantum Instrumentation and Control Kit (QICK) system on RFSoC FPGA technology to drive an entangled photon pair source and to detect the photon signals. With the QICK system, we achieve high levels of performance metrics including coincidence-to-accidental ratio exceeding 150, and entanglement visibility exceeding 95%, consistent with performance metrics achieved using conventional waveform generators. We also demonstrate simultaneous detector readout using the digitization functional of QICK, achieving internal system synchronization time resolution of 3.2 ps. The work reported in this paper represents an explicit demonstration of the feasibility for replacing commercial waveform generators and time taggers with RFSoC-FPGA technology in the operation of a quantum network, representing a cost reduction of more than an order of magnitude.
To meet performance and reliability requirements necessary for broader adoption of electric drive vehicles, the Electrical and Electronics Technical Team of the U.S. Drive partnership has established aggressive design goals for next-generation electric vehicle drivetrains. Specifically, the 2025 roadmap stipulates a 100 kW/L power density target and a $\$$2.7/kW cost target for power electronics, in addition to high-voltage operation (i.e., greater than 800 VDC). The additional targets for traction motor and the overall system performance impose further challenges on the power electronics design. For example, many high specific power machines have reduced iron content, and therefore reduced intrinsic filtering, thus requiring the inverter to supply a low-distortion drive current. These machines also typically have a high pole count, thus requiring drive current at a higher electrical frequency. Other motors, such as brush-less dc and switch reluctance machines, require a carefully-shaped, non-sinusoidal drive current (Yang, Shang, Brown, & Krishnamurthy, 2015), (Zhang, Bowman, O'Connel, & Haran, 2018), (Anderson, et al., 2018). Two- and three-level inverter topologies are the conventional framework for the power electronics design of the drivetrain, and some demonstrations have shown recent progress towards addressing cost, power density and efficiency goals (Gurpinar & Ozpineci, 2018), (Zhu, Kim, Chen, Erickson, & Maksimović, 2018), (Deshpande, Chen, Narayanasamy, Sathyanarayanan, & Luo, 2018), (Alizadeh, et al., 2019). However, an unconventional approach may be necessary to take the dramatic leap in power density necessitated by the roadmap—while simultaneously addressing the other system needs. Therefore, this project leverages the flying capacitor multilevel (FCML) topology, together with a scalable, modular approach, to address these needs. This type of hybrid converter has several advantages: lower voltage (i.e., less than 300 V) transistors can be used, energy-dense capacitors process most of the power, and the output current waveform is multilevel and exhibits a frequency multiplying effect—in other words, the output has reduced dv/dt and filtering requirements for the same high voltage dc bus. For example, in an electric vehicle with an 800 V bus, a 10-level FCML could leverage 100 V, commercially available GaN devices switching at 115 kHz to produce a ~1 MHz switching waveform (modulated according to the motor drive requirements) with one ninth of the dv/dt of a two-level converter. Prior work has already demonstrated promising performance and gravimetric power density figures for more electric aircraft applications (Pallo, Foulkes, Modeer, Coday, & Pilawa-Podgurski, 2018). This project leverages lessons learned to achieve the volumetric power density of 100 kW/L by employing advanced liquid cooling, address the 300,000 mile reliability challenge with redundant design, topology failure studies and online health monitoring, and reduce costs to $\$$2.7/kW through the use of low-cost GaN devices, modular converter assemblies, and modest modifications to traditional manufacturing methods. The project involved several hardware designs, each achieving increasing performance. At the conclusion of the project, a volumetric power density of 380 kW/L was achieved, in a 800V dc-ac converter, greatly surpassing even the aggressive target goal.
This study used STEAD to train and evaluate this model because STEAD is among the best benchmark datasets available for local to regional data. STEAD is a global dataset with over 1 million 60 s long seismic waveforms that originated from approximately 450,000 earthquakes and background noise captured by more than 2,500 seismic stations. Each waveform in STEAD was attached with metadata such as earthquake locations, station locations, and signal arrival times when available
The Muon to Electron Experiment (\acrshort{Mu2e}) requires a uniform beam profile from the Muon Delivery Ring to meet their experimental needs. A specialized Spill Regulation System (\acrshort{SRS}) has been developed to help achieve consistent spill uniformity. The system is based on a custom-designed carrier board featuring an Arria 10 SoC, capable of executing real-time feedback control. The FPGA processes beam pulses of approximately 200 ns every 1.695 microseconds, allowing for continuous monitoring of the extracted spill intensity through fast bunch integration. The system directly controls three quadrupole magnets, which work in conjunction with sextupole magnets to achieve third-order resonant extraction. Furthermore, the board interfaces with Fermilab s Accelerator Control Network (ACNET), enabling operators to modify spill regulation settings in real-time via the control network while providing diagnostic waveforms. These waveforms help operators monitor the process and fine-tune the feedback mechanisms. This paper presents an overview of the board's architecture and its initial progress toward regulating beam extraction. This initial version of the regulation system aims to evaluate baseline performance to inform future system improvements.
X-ARAPUCA waveform data, collected at a test stand at the Noble Liquid Test Facility (NLTF) and the Short Baseline Near Detector (SBND), were analyzed via python scripts. For the ARARA system, various distributions and correlations were studied, including the area and amplitude distributions of the waveform peaks for identifying single photoelectron peaks, as well as characterizing the behavior of the baseline artifact. The ARARA system is being studied in order to be implemented into SBND, just as the APSAIA X-ARAPUCAs have been.
The ICARUS experiment is part of the Short-Baseline Neutrino (SBN) program at Fermilab. The main goal of the experiment is to investigate the possibility of sterile neutrinos in the O(1 eV) mass region and provide clarification of the anomaly detected from the Liquid Scintillator Neutrino Detector (LSND) and MiniBooNE experiments. The ICARUS-T600 detector is a Liquid Argon Time Projection Chamber (LAr-TPC), that can provide excellent 3D imaging and calorimetric reconstruction of any ionizing particles. This detection technique allows a detailed study of neutrino interactions, spanning a wide energy spectrum (from a few keV to several hundreds of GeV). The detector consists of two identical adjacent modules, filled with a total of 760 tons of ultra-pure liquid argon. Each module houses two LAr-TPCs separated by a common cathode with a maximum drift distance of 1.5 m, equivalent to about 1 ms drift time for the nominal $500$ V/m electric drift field. The anode is made of three parallel wire planes positioned 3 mm apart, where the stainless-steel wires are oriented on each plane at a different angle with respect to the horizontal direction ($+60^\degree$,$-60^\degree$,$0^\degree$). The first two planes (Induction 1 and Induction 2) provide a non-destructive charge measurement, whereas the ionization charge is fully collected by the last collection plane. In total, 53248 wires with a 3 mm pitch and length up to 9 m are installed in the detector. In the first stage of the reconstruction, segments of waveforms corresponding to physical signals (hits) are searched for in the deconvolved wire waveform with a threshold-based hit-finding algorithm. Each hit is then fitted with a Gaussian, whose area is proportional to the number of drift electrons generating the signal. In the second stage of the reconstruction, hits are passed as input to Pandora, a framework software composed of different pattern recognition algorithms, that performs a 3D reconstruction of the full image recorded in the collected event, including the identification of interaction vertices and tracks and showers inside the TPC. These are organized into a hierarchical structure (called slice) of particles generated starting from a primary interaction vertex. In some cases, related to the inefficiencies in the hit detection or excessive deflection of the particle trajectory, Pandora breaks the particle's track into two or more smaller pieces and considers each piece as an independent track. We studied this phenomenon focusing on primary muons from ν_μ CC interactions contained in a single module with a track at least 20 cm long, to exclude delta rays. The study determined that about $7-8\%$ of the muon tracks are broken. Approximately $80\%$ of the times, Pandora assigns all segments of the track to the same slice (intra-slice track split), while in the remaining $20\%$ of the cases, one of the segments is associated with another slice (extra-slice track split). To mitigate this phenomenon, we designed an algorithm that detects and stitches the tracks broken by Pandora for the intra-slice split. In Monte Carlo simulations, the algorithm showed an efficiency exceeding $80\%$ and a purity exceeding $93\%$.