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At least 487 records · Page 27

System and method for high dynamic range waveform digitization

Diverse applications from particle physics experiments to lidar are driving cost and current reduction in giga-hertz sampling rate high-resolution data conversion. Multiple imagers captures a single pixel of data and require processing at very high speed. High-bandwidth high-rate signal sampling, analog-to-digital conversion, and transfer of large amounts of data to a digital data acquisition block are required in such systems. Dynamic range, power consumption, and transfer of high-speed, high-bit width data are key implementation challenges. Data acquisition architectures optimized for specific requirements of such systems may facilitate system implementation and reduce overall system cost.

Mostafanezhad, Isar↗

Temporal resolution and fidelity enhancement of arbitrary waveforms

Apparatuses comprising cascaded or series configurations of Mach-Zehnder electrooptic modulators, where the nonlinearities of the cascaded and series configurations of Mach-Zehnder electrooptic modulators increase signal bandwidth and boost signal fidelity in electronic digital to analog converters. The Mach-Zehnder electrooptic modulators are combined with photodiode detectors that are used to convert signals from the optical domain to the electrical domain.

Muir, Ryan D.↗

Impact of CT attenuation correction method on quantitative respiratory-correlated (4D) PET/CT imaging

Purpose: Respiratory-correlated positron emission tomography (PET/CT) 4D PET/CT is used to mitigate errors from respiratory motion; however, the optimal CT attenuation correction (CTAC) method for 4D PET/CT is unknown. The authors performed a phantom study to evaluate the quantitative performance of CTAC methods for 4D PET/CT in the ground truth setting. Methods: A programmable respiratory motion phantom with a custom movable insert designed to emulate a lung lesion and lung tissue was used for this study. The insert was driven by one of five waveforms: two sinusoidal waveforms or three patient-specific respiratory waveforms. 3DPET and 4DPET images of the phantom under motion were acquired and reconstructed with six CTAC methods: helical breath-hold (3DHEL), helical free-breathing (3DMOT), 4D phase-averaged (4DAVG), 4D maximum intensity projection (4DMIP), 4D phase-matched (4DMATCH), and 4D end-exhale (4DEXH) CTAC. Recovery of SUV{sub max}, SUV{sub mean}, SUV{sub peak}, and segmented tumor volume was evaluated as RC{sub max}, RC{sub mean}, RC{sub peak}, and RC{sub vol}, representing percent difference relative to the static ground truth case. Paired Wilcoxon tests and Kruskal–Wallis ANOVA were used to test for significant differences. Results: For 4DPET imaging, the maximum intensity projection CTAC produced significantly more accurate recovery coefficients than all other CTAC methods (p < 0.0001 over all metrics). Over all motion waveforms, ratios of 4DMIP CTAC recovery were 0.2 ± 5.4, −1.8 ± 6.5, −3.2 ± 5.0, and 3.0 ± 5.9 for RC{sub max}, RC{sub peak}, RC{sub mean}, and RC{sub vol}. In comparison, recovery coefficients for phase-matched CTAC were −8.4 ± 5.3, −10.5 ± 6.2, −7.6 ± 5.0, and −13.0 ± 7.7 for RC{sub max}, RC{sub peak}, RC{sub mean}, and RC{sub vol}. When testing differences between phases over all CTAC methods and waveforms, end-exhale phases were significantly more accurate (p = 0.005). However, these differences were driven by the patient-specific respiratory waveforms; when testing patient and sinusoidal waveforms separately, patient waveforms were significantly different between phases (p < 0.0001) while the sinusoidal waveforms were not significantly different (p = 0.98). When considering only the subset of 4DMATCH images that corresponded to the end-exhale image phase, 4DEXH, mean and interquartile range were similar to 4DMATCH but variability was considerably reduced. Conclusions: Comparative advantages in accuracy and precision of SUV metrics and segmented volumes were demonstrated with the use of the maximum intensity projection and end-exhale CT attenuation correction. While respiratory phase-matched CTAC should in theory provide optimal corrections, image artifacts and differences in implementation of 4DCT and 4DPET sorting can degrade the benefit of this approach. These results may be useful to guide the implementation, analysis, and development of respiratory-correlated thoracic PET/CT in the radiation oncology and diagnostic settings.

60 APPLIED LIFE SCIENCES↗

Alternate Null Hypothesis Correlation: A New Approach to Automatic Seismic Event Detection

This paper describes a new method of seismic signal detection that improves upon the conventional waveform correlation method. Recent studies suggested that a significant limiting factor in the application of waveform correlation to regional and global scale monitoring is the false alarm rate. The false alarms do not originate from detections on noise but rather from seismic arrivals with unrelated source locations. This article presents results from an approach to waveform correlation that exploits techniques from signal processing and machine learning to improve the accuracy of detecting seismic arrivals. We modify the detection model for waveform correlation such that transient signals from noncollocated seismicity are considered when designing the detectors. The new approach uses waveform templates from known catalog events to train a supervised machine learning algorithm that derives a new set of detectors to represent the unique characteristics of the template waveforms; these new detectors maximize the likelihood of detecting only the desired events, thereby minimizing false alarms. We train a waveform correlation template library for a single three-component seismic monitoring station. We then review results from applying the new detectors, known as alternate null hypothesis correlation (ANCorr) templates, to a test set of seismic waveforms. Finally, we compare ANCorr results with those from application of the conventional waveform correlation matched filter technique.

58 GEOSCIENCES↗

Protection and Restoration Solutions to Reliable and Resilient Integration of Grid-connected PV Installations and Distributed Energy Resources: Design, Testbed, Proof of Work and Impact Studies (Final Report)

To gain a better understanding of the complex transients in a utility grid with a large number of solar PV installations coupled by PWM inverters during the protection and restoration period of the power grid, in this project a kW-level experimental system with dominating inverter-based resources and a hardware-in-loop simulation system with transmission and distribution models, as well as several SEL protective relays have been built and used. The major research findings of the project are summarized below in two perspectives: Experimental research: A self-organized ultra-high frequency solitary waveform is discovered and demonstrated in the hardware experimental system. Despite the familiarities, such a solitary waveform is distinct from any harmonics, transient, or resonance waves in that, it is 1) non-dispersive over time and space, 2) not associated with any active source or the linear superposition of sources, 3) half-cycle asymmetric, 4) not responding to filters or change of system characteristic resonance frequency, 5) ubiquitous as it occurs simultaneously everywhere in the system from DC supply, power lines, and the utility grid, and 6) explosive through tripping the protection or damaging susceptible devices or circuits. Analytical study: The nature of such a new waveform and an analytical explanation of its formation are studied based on related physics and non-linear science principles, with the following highlights: 1) such a new waveform follows the solutions to the Non-linear Schrödinger equation, so the classic linear perturbation theory is unable to explain or predict such a unique waveform as confirmed with the research team of RTDS; 2) the critical condition of occurrence of such a waveform is derived, which indicates that the breakings of solitary wave is a system synchronous issue between the utility grid in the 60Hz phasor domain and duty-ratio modulation of DC sources in the inverter switching frequency domain; 3) such a waveform carries energy mass so it could be detrimental; 4) such a waveform is deceiving as it is not readily detectable in the energy propagation direction by the primary protection equipment, while it is detrimental in the perpendicular direction of energy propagation, i.e. voltage direction. Thus, it has more likely challenges to the second primary equipment and devices, particularly at the weakest link and point such as aging insulation and inappropriate setting of susceptible devices. Therefore, such a waveform can be easily ignored in the aftermath investigation. The intellectual merits: The experimental discovery reveals certain unfamiliar transient phenomena that could challenge the integration of large-scale grid-connected solar PV installation during the group ride-through period of solar PV installations, commissioning of large-solar farms, or dramatic change of solar radiation conditions. Particularly, the research findings suggest that the occurrence of the unfamiliar transient phenomena is uniquely associated with the inverter-based solar PV installation, which is less likely to happen for rotary energy systems. The physics and non-linear science-based research work laid down an analytical path to the challenging transient stability problems including those that have been observed currently and future calls. Both experimental and analytical research results explain the limitation of many current research effects including some DoE research undertakings as well as possible solutions. The broader impacts: The research outcome of the project advances the understanding of the possible transient problems for the integration of inverter-based solar PV installation. It also highlights the theoretical and technical barriers for applying the conventional theory and technology to design and implement countermeasures against their adverse impacts of the large-scale solar PV installation and operation on grid reliability and security. More broadly, the research outcomes have shed some light on the open, fundamental challenges in the integration of large-scale solar photovoltaic energy into current and next-generation power grids across the country, and worldwide. The advanced physics and non-linear science-based analysis open up a path to harmonization of the renewables for societal energy needs via building a resilient and sustainable electric power infrastructure.

14 SOLAR ENERGY↗

A comparison of earthquake backprojection imaging methods for dense local arrays

Backprojection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. While backprojection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed and simplified to overcome imaging challenges. Real data issues include aliased station spacing, inadequate array aperture, inaccurate velocity model, low signal-to-noise ratio, large noise bursts and varying waveform polarity. We compare the performance of backprojection with four previously used data pre-processing methods: raw waveform, envelope, short-term averaging/long-term averaging and kurtosis. Our primary goal is to detect and locate events smaller than noise by stacking prior to detection to improve the signal-to-noise ratio. The objective is to identify an optimized strategy for automated imaging that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the source images, preserves magnitude, and considers computational cost. Imaging method performance is assessed using a real aftershock data set recorded by the dense AIDA array following the 2011 Virginia earthquake. Our comparisons show that raw-waveform backprojection provides the best spatial resolution, preserves magnitude and boosts signal to detect events smaller than noise, but is most sensitive to velocity error, polarity error and noise bursts. On the other hand, the other methods avoid polarity error and reduce sensitivity to velocity error, but sacrifice spatial resolution and cannot effectively reduce noise by stacking. Of these, only kurtosis is insensitive to large noise bursts while being as efficient as the raw-waveform method to lower the detection threshold; however, it does not preserve the magnitude information. For automatic detection and location of events in a large data set, we therefore recommend backprojecting kurtosis waveforms, followed by a second pass on the detected events using noise-filtered raw waveforms to achieve the best of all criteria.

58 GEOSCIENCES↗

An explainable variational autoencoder model for three-dimensional acoustic emission source localization in hollow cylindrical structures

We introduce an explainable variational autoencoder for three-dimensional (3D) localization of acoustic emission sources in hollow cylindrical structures, with an unsupervised approach. This research capitalizes on multi-arrival waveforms generated by helical path propagation in cylindrical geometries to enable efficient two-receiver localization. By integrating the modal characteristics of Lamb modes under multi-path conditions, we demonstrate that two sets of time-of-arrival differences and peak amplitudes extracted from one receiver can serve as effective localization features. This initial approach identifies four potential source locations, highlighting the feasibility of two-receiver source localization using traditional feature extraction methods. However, direct extraction can be challenging when mode overlaps occur, complicating the localization process. To address this, our work proposes a novel waveform-based method. This method leverages the consistent dispersion characteristics within isotropic materials, where each unique combination of mode arrival times and peak amplitudes constructs a distinct waveform. This distinctiveness overcomes the ambiguities associated with mode overlaps, significantly enhancing the method’s precision and robustness. Our approach adopts a data-driven strategy for waveform-based localization using variational autoencoder (VAE). VAE discerns waveform patterns for localization, while also addressing data uncertainties. The VAE’s encoder and decoder networks capture the localization process and the source’s influence on waveform generation, respectively, guiding latent variables to segregate waveforms by source in the latent space. The design of the learning process focuses on specific localization characteristics to enhance result explainability. Localization predictions are generated by projecting test waveforms, not included in the training set, onto a trained latent space. The prediction is determined using a nearest-neighbor approach based on the closest latent representation of a source. Validation with pencil-lead-break tests on a metallic pipe confirmed our method’s effectiveness, achieving an averaged 3D localization accuracy of 0.84.

Lee, Guan-Wei↗

Electrochemical sensing using voltage-current time differential

A device for signal processing. The device includes a signal generator, a signal detector, and a processor. The signal generator generates an original waveform. The signal detector detects an affected waveform. The processor is coupled to the signal detector. The processor receives the affected waveform from the signal detector. The processor also compares at least one portion of the affected waveform with the original waveform. The processor also determines a difference between the affected waveform and the original waveform. The processor also determines a value corresponding to a unique portion of the determined difference between the original and affected waveforms. The processor also outputs the determined value.

99 GENERAL AND MISCELLANEOUS↗

Linear Seismic Source Equivalents in 3D Nonlinear Models: Effects of Embedded Small-Scale, Near-Source Structures

Gaining a proper understanding of how Earth structure and other near-source properties affect estimates of explosion yield is important to the nonproliferation mission. The yields of explosion sources are often based on seismic moment or waveform amplitudes. Quantifying how the seismic waveforms or estimates of the source characteristics derived from those waveforms are influenced by natural or man-made structures within the near-source region, where the wavefield behaves nonlinearly, is required to understand the full range of uncertainty in those yield estimates. We simulate tamped chemical explosions using a nonlinear, shock physics code and couple the ground motions beyond the elastic radius to a linear elastic, full waveform seismic simulation algorithm through 3D media. In order to isolate the effects of simple small-scale 3D structures on the seismic wavefield and linear seismic source estimates, we embed spheres and cylinders close to the fully- tamped source location within an otherwise homogenous half-space. The 3 m diameters spheres, given their small size compared to the predominate wavelengths investigated, not surprisingly are virtually invisible with only negligible perturbations to the far-field waveforms and resultant seismic source time functions. Similarly, the 11 m diameter basalt sphere has a larger, but still relatively minor impact on the wavefield. However, the 11 m diameter air-filled sphere has the largest impact on both waveforms and the estimated seismic moment of any of the investigated cases with a reduction of ~25% compared to the tamped moment. This significant reduction is likely due in large part to the cavity collapsing from the shock instead of being solely due to diffraction effects . Although the cylinders have the same diameters as the 3 m spheres, their length of interaction with the wavefield produces noticeable changes to the seismic waveforms and estimated source terms with reductions in the peak seismic moment on the order of 10%. Both the cylinders and 11 m diameter spheres generate strong shear waves that appear to emanate from body force sources.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Examining the Performance of Walsh-DSSS Against FBMC-SS in HF Channels

Abstract—Filter bank multicarrier spread spectrum (FBMCSS) has proven to be a robust and reliable waveform choice for communication over high frequency (HF) skywave links. However, the performance of this waveform has yet to be contextualized against typical robust HF waveforms, such as the Walsh-encoded waveform detailed in the MIL-STD-188-110D, Appendix D document. In this paper, we first outline the advantages of both the Walsh and FBMC-SS waveforms as well as present their developments. Simulation results are then presented for ideal, simulated HF, and HF with interference channel conditions. Lastly, skywave-HF results are presented for these two waveforms both with and without interference.

99 GENERAL AND MISCELLANEOUS↗

Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to advance geothermal exploration and safe geothermal energy production. As part of the project, this submission provides data arrays for 149 microearthquakes between the year 2012 and 2013 at the Newberry EGS Site for use with the Deep Learning Algorithm that has been developed. The data provided includes raw waveform data, location data, normalized waveform data, and processed waveform data. Penn State Geothermal Team has shared the following files from the project: - 149 microearthquakes (MEQs) between 2012 and 2013 at Newberry EGS sites, 'Normalized Waveform Inputs.npz' are normalized waveforms. - labels of 149 MEQs: Processed Waveform Inputs.npz - location labels of 149 MEQs: Location Data.npz Note: .npz is the python file format by NumPy that provides storage of array data.

15 GEOTHERMAL ENERGY↗

The geometry of signal space: a case study of direct mapping between seismic signals and event distribution

SUMMARY Under favourable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal-space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection and scaling, with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning and possible application to studies of repeating events in induced, volcanic and glacial seismicity. Our results place limits on the widely held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗