Waveform Shape Research Articles

Estimating differential penetration of green (532 nm) laser light over sea ice with NASA's Airborne Topographic Mapper: observations and models

Abstract. Differential penetration of green laser light into snow and ice has long been considered a possible cause of range and thus elevation bias in laser altimeters. Over snow, ice, and water, green photons can penetrate the surface and experience multiple scattering events in the subsurface volume before being scattered back to the surface and subsequently the instrument's detector, therefore biasing the range of the measurement. Newly formed sea ice adjacent to open-water leads provides an opportunity to identify differential penetration without the need for an absolute reference surface or dual-color lidar data. We use co-located, coincident high-resolution natural-color imagery and airborne lidar data to identify surface and ice types and evaluate elevation differences between those surfaces. The lidar data reveals that apparent elevations of thin ice and finger-rafted thin ice can be several tens of centimeters below the water surface of surrounding leads, but not over dry snow. These lower elevations coincide with broadening of the laser pulse, suggesting that subsurface volume scattering is causing the pulse broadening and elevation shift. To complement our analysis of pulse shapes and help interpret the physical mechanism behind the observed elevation biases, we match the waveform shapes with a model of scattering of light in snow and ice that predicts the shape of lidar waveforms reflecting from snow and ice surfaces based on the shape of the transmitted pulse, the surface roughness, and the optical scattering properties of the medium. We parameterize the scattering in our model based on the scattering length Lscat, the mean distance a photon travels between isotropic scattering events. The largest scattering lengths are found for thin ice that exhibits the largest negative elevation biases, where scattering lengths of several centimeters allow photons to build up considerable range biases over multiple scattering events, indicating that biased elevations exist in lower-level Airborne Topographic Mapper (ATM) data products. Preliminary analysis of ICESat-2 ATL10 data shows that a similar relationship between subsurface elevations (restored negative freeboard) and “pulse width” is present in ICESat-2 data over sea ice, suggesting that biased elevations caused by differential penetration likely also exist in lower-level ICESat-2 data products. The spatial correlation of observed differential penetration in ATM data with surface and ice type suggests that elevation biases could also have a seasonal component, increasing the challenge of applying a simple bias correction.

Adaptive design of experiments to fit surrogate Gaussian process regression models allows fast sensitivity analysis of the input waveform for patient-specific 3D CFD models of liver radioembolization

Background and objectivePatient-specific 3D computational fluid dynamics (CFD) models are increasingly being used to understand and predict transarterial radioembolization procedures used for hepatocellular carcinoma treatment. While sensitivity analyses of these CFD models can help to determine the most impactful input parameters, such analyses are computationally costly. Therefore, we aim to use surrogate modelling to allow relatively cheap sensitivity analysis. As an example, we compute Sobol's sensitivity indices for three input waveform shape parameters. MethodsWe extracted three characteristic shape parameters from our input mass flow rate waveform (peak systolic mass flow rate, heart rate, systolic duration) and defined our 3D input parameter space by varying these parameters within 75 %-125 % of their nominal values. To fit our surrogate model with a minimal number of costly CFD simulations, we developed an adaptive design of experiments (ADOE) algorithm. The ADOE uses 100 Latin hypercube sampled points in 3D input space to define the initial design of experiments (DOE). Subsequently, we re-sample input space with 10,000 Latin Hypercube sampled points and cheaply estimate the outputs using the surrogate model. In each of 27 equivolume bins which divide our input space, we determine the most uncertain prediction of the 10,000 points, compute the true outputs using CFD, and add these points to the DOE. For each ADOE iteration, we calculate Sobol's sensitivity indices, and we continue to add batches of 27 samples to the DOE until the Sobol indices have stabilized. ResultsWe tested our ADOE algorithm on the Ishigami function and showed that we can reliably obtain Sobol's indices with an absolute error <0.1. Applying ADOE to our waveform sensitivity problem, we found that the first-order sensitivity indices were 0.0550, 0.0191 and 0.407 for the peak systolic mass flow rate, heart rate, and the systolic duration, respectively. ConclusionsAlthough the current study was an illustrative case, the ADOE allows reliable sensitivity analysis with a limited number of complex model evaluations, and performs well even when the optimal DOE size is a priori unknown. This enables us to identify the highest-impact input parameters of our model, and other novel, costly models in the future.

A space marching method for sonic boom near field predictions

The conventional sonic boom propagation prediction method widely adopted in supersonic aircraft design involves a two-step procedure. In the first step, a compressible viscous or inviscid Computational Fluid Dynamics analysis is applied to the aircraft geometry at flight conditions to produce a flow field solution near the aircraft. Then in the second step, a one dimensional nonlinear Burgers’ equation model is used to propagate sonic boom signature traces from the near field solution at flight altitude to the ground along a ray path. For an accurate ground signature prediction the near field signature must be accurately modeled at a sufficient distance from the aircraft flight path in order to minimize errors in the one dimensional propagation model. This is a very challenging task for general purpose CFD tools in a design environment because the cost of maintaining highly accurate off-body solutions increases dramatically as the radial distance is enlarged in the computational domain. It is also particularly difficult to apply these tools for wave propagation because the algorithms are normally lower order and numerically dissipative and dispersive. In this work a space marching procedure based on an optimized higher order finite difference method is developed and applied in conjunction with a CFD solution concentrated in the close vicinity of the aircraft. This new approach is much more efficient, compared to previous methods, in providing highly accurate near field signatures for full carpet ground predictions. Results indicate that near field signatures retain more waveform shape information farther from the aircraft geometry while reducing the CFD cost significantly. The predicted ground signature is also shown to converge in shape as the radial distance of the near field signature grows, which is indicative of a more ideal initial condition being supplied to the one dimensional wave propagation to ground. This feature is very difficult to replicate in a tractable manner with common CFD approaches used in design.

Electro-dewatering performance of sewage sludge under interrupted pulsating voltage: A comparison between square shape and half-sine shape waveform

Electro-dewatering of sewage sludge with pulsating voltage was conducted under the two different wave shapes (square wave (SQW) and half-sine wave (HSW)) to investigate the influence of wave shape and duty cycle on sludge dewatering performance. The results indicated that, under the same average voltage, the moisture content of dewatered sludge with HSW was 10.3%–35.4% lower than that with SQW, suggesting the better dewatering performance of HSW. The optimal dewatering performance was achieved at duty cycle of 80% for SQW and 60% for SHW. The chemical oxygen demand of filtrate from HSW could be 13% higher than that from SQW, indicating the higher capacity of HSW in breaking sludge cells/floc structure. The applied voltage during electrochemical treatment promoted the hydrolysis of protein in filtrate, and the main components in the electro-dewatered filtrate were fulvic acid- and humic acid-like substances. The specific energy consumption for sludge electro-dewatering were 0.015–0.269 kWh/(kg removed water), and it was almost in linear relationship with duty cycle. By overall considering the energy consumption and electro-dewatering performance, the condition of 60% duty cycle with HSW was obviously better than other conditions, which provides a meaningful guidance for future application of sludge electro-dewatering technology with pulsating voltage.

Characterizing Liquid Water in Deep Martian Aquifers: A Seismo‐Electric Approach

AbstractDeep Martian aquifers harboring liquid water could hold vital insights for current and past habitability. We show that with seismo‐electric interface responses (IRs) we can quantitatively characterize subsurface water on Mars. Full‐waveform simulations and sensitivity analyses across diverse Martian aquifer scenarios demonstrate the technique's effectiveness. In contrast to how seismo‐electric signals often appear on Earth, Mars' desiccated surface naturally removes co‐seismic fields and exposes useful IRs that allow us to characterize several aquifer properties. Changing the aquifer depth, thickness, or quantity changes the IR arrival times or shape: aquifer depth is a strong control on evanescent IRs, thickness affects the relative timing of IRs, and increasing the number of aquifers introduces more dipole sources to the waveform. Other factors, such as aquifer saturation, chemistry, and salinity, strongly affect IR amplitude but have minimal or no effect on waveform shape. Notably, for a deep low‐porosity aquifer, the salinity and brine chemistry (perchlorate vs. chloride) are the strongest controls on signal amplitude. Analyzing the effects of epicentral distance shows that radiating and evanescent IRs separate at large source‐receiver offset, allowing analyses of both signals and accurate event distance derivation. From this numerical investigation of the sensitivity of IRs to deep Martian aquifers, we anticipate future analyses of electromagnetic data from the InSight lander or future missions to Mars and other planets.

Traditional and alternative grounding system's impedance and resistance measurements of a 138 kV transmission line tower

One of the main causes of outages in transmission lines is lightning. To mitigate this occurrence, grounding electrodes are used at the base of the towers that make up the transmission lines. Since lightning is a phenomenon with components of low and relatively high-frequency energy (approximately up to 2 MHz), there is a certain complexity in accurately characterizing grounding systems. The primary parameter used to model a grounding system is the grounding impedance, which can be obtained through measurement. This paper presents measurements conducted on a 138 kV transmission line's traditional and alternative grounding system. The measured traditional grounding system consists of two horizontally buried copper grounding conductors and the alternative system comprises an electrode with four conductors encapsulated in concrete and buried vertically. The measurements were carried out using a 25 kHz earth resistance meter and impulse generators with waveform shapes of 1.2/50 μs, 1/70 μs, and 8/70 μs. Different measurement configurations are employed. The obtained measurements are compared with similar systems found in the literature, and the contributions of the concrete electrode to the grounding system are discussed.

Optical Darboux Transformer.

The optical Darboux transformer for solitons is introduced as a photonic device that performs the Darboux transformation directly in the optical domain. This enables two major advances for optical signal processing based on the nonlinear Fourier transform: (i)the multiplexing of solitonic waveforms corresponding to different discrete eigenvalues of the Zakharov-Shabat system, and (ii)the selective filtering of an arbitrary number of individual solitons too. The optical Darboux transformer can be built using existing commercially available photonic technology components and constitutes a universal tool for signal processing, optical communications, optical rogue waves generation, and waveform shaping and control in the nonlinear Fourier domain.

GNSS gyroscopes: determination of angular velocity and acceleration with very high-rate GNSS

Although global navigation satellite systems (GNSS) have been routinely applied to determine attitudes, there exists no literature on determining angular velocity and/or angular acceleration from GNSS. Motivated by the invention of computerized accelerometers of the correspondence author and following the success of accurately recovering translational velocity and acceleration waveforms from very high-rate GNSS precise positioning by Xu and his collaborators in 2021, we propose the concept of GNSS gyroscopes and reconstruct angular velocity and acceleration from very high-rate GNSS attitudes by applying regularization under the criterion of minimum mean squared errors. The major results from the experiments can be summarized in the following: (i) angular velocity and acceleration waveforms computed by applying the difference methods to high-rate GNSS attitudes are too noisy and can be physically not meaningful and numerically incorrect. The same can be said about inertial measurement unit (IMU) attitudes, if IMU gyros are not of very high accuracy; (ii) regularization is successfully applied to reconstruct the high-rate angular velocity and acceleration waveforms from 50 Hz GNSS attitudes and significantly outperforms the difference methods, validating the proposed concept of GNSS gyroscopes. By comparing the angular velocity and acceleration results by using the difference methods and regularization, we find that the peak values of angular velocity and acceleration by regularization are much smaller by a maximum factor of 1.57 in the angular velocity to a maximum factor of 8662.53 times in the angular acceleration in the case of high-rate GNSS, and by a maximum factor of 1.26 in the angular velocity to a maximum factor of 2819.85 times in the angular acceleration in the case of IMU, respectively; and (iii) the IMU attitudes apparently lead to better regularized angular velocity and acceleration waveforms than the high-rate GNSS attitudes, which can well be explained by the fact that the former is of better accuracy than the latter. As a result, to suppress the significant amplification of noise in GNSS attitudes, larger regularization parameters have to be chosen for the high-rate GNSS attitudes, resulting in smaller peak angular accelerations by a maximum factor of 37.55 percent in the angular velocity to a maximum factor of 6.20 times in the angular acceleration in comparison of the corresponding IMU results. Nevertheless, the regularized angular acceleration waveforms for both GNSS and IMU look more or less similar in pattern or waveform shape.

Electromagnetics theory-based new equation to improve harmonically tuned power amplifier theory and design

ABSTRACT Power amplifiers (PA) are used to boost the power of signals. Recently, harmonically tuned power amplifiers (HTPA) offer high efficiency and wider bandwidth than conventional PA. HTPA achieves by shaping waveforms using varying drain terminal impedance conditions (open and short-circuited etc.), but this impedance creates reflected waves at the drain. Existing HTPA methods lack a foundation in Electromagnetic Theory (EM), leading them to miss reflected waves. As a result, the existing equations show problems Type I: generate unwanted and non-required higher-order harmonics (n > 3); and Type II: they cannot link with simulated/measured results properly. This paper proposes an alternative approach by applying EM theory to develop a general HTPA equation. This equation works for any HTPA class and overcomes problems (Type I & II). To validate the proposed theory and equation, continuous mode Class F PA is designed and fabricated. Theoretical, simulation and experimental results all showed good agreement.

Real-time, sample-by-sample estimation of multiple signal waveforms from acoustic array data using B-splines

This work presents a real-time signal processing algorithm that estimates time-domain waveforms of multiple plane wave signals on a sample-by-sample basis from data measured by an acoustic array. Moreover, the algorithm provides sample-by-sample estimates of the direction-of-arrival (DOA) of the waveforms. In this case sample-by-sample means that as each sample of data is measured by the array estimates of the waveforms and their directions-of-arrival are updated. While the basic idea can be based on almost any finite-dimensional approximation to a function space, this algorithm makes use of B-spline basis for the signal waveforms. Other features of the approach include no restrictions on signal waveform shape, automatic estimation of the number of signals present, automatic step-size adjustment for correction of signal waveform and direction-of-arrival parameters to achieve good performance while guaranteeing stability, and the use of circular (spherical) statistical models for 2-D (3-D) DOA estimates. The approach contrasts with blind source separation (BSS) methods that are based on non-Gaussian statistical assumptions and that do not assume a known array geometry nor a propagation model. This method is closely related to algorithms based on block-of-data by block-of-data processing but does not require stitching results from block processing to create time-domain waveform estimates.

Small attenuation negative group delay of spoof surface plasmon polaritons

Spoof surface plasmon polariton (SSPP) waveguides can be used to effectively construct on-chip microwave systems due to the single-side conductor structure. SSPP waveguides usually exhibit normal dispersion, which can introduce large group delays to transmission signal and impair waveform shapes. However, the negative group velocity (NGV) effect may occur in the split modes of coupled surface plasmon polariton waveguides. In this regard, the synthesis wave model of forward and backward transmission waves is applied, which generates a quadrupole vortex wave transmission. In this paper, the SSPP unit structure with folded multi-split rings is proposed to achieve anomalous dispersion with NGV feature in the fundamental mode. The SSPP unit can be equivalent to an epsilon-negative medium, and a maximum negative group delay (NGD) can be reached at the frequency where the NGV begins to appear. For the corresponding SSPP waveguide, a NGD band with lower attenuation can be achieved at the stopband edge. While the SSPP unit structures are loaded as dispersive materials in a microstip line, the similar NGD performance can be obtained. Clearly, the SSPP NGD with lower attenuation provides a new delay equalization method for ultra reliable and low latency communications (URLLC), and can also be used as an effective dispersion compensation means.

Waveform shaping in photonic time-crystals

This paper reports on the waveform shaped by a finite duration photonic time-crystal with its permittivity and permeability periodically varying in time. A Gaussian-modulated sinusoidal pulse is incident onto this photonic time-crystal to evaluate the backward- and forward-scattering waveforms. An analytical formulation, utilizing a cascade of temporal transfer matrices and the inverse fast Fourier transform, was employed to conduct time-domain waveform computations. Interestingly, the dispersion diagram of the temporal unit cell, which displays a momentum gap characterized by a complex effective angular frequency, plays a crucial role in shaping the incident waveform. Specifically, the presence of momentum gaps in the spectrum of the incident pulse determines the frequencies of the generated oscillation modes.

Development of Excess Pore Water Pressure in Sand during K0-Controlled Cyclic Loading

Understanding the characteristics of the development of excess pore water pressure during cyclic loading is important to evaluating the dynamic behavior of soils. Many researchers have proposed experimental models to estimate pore water pressure. However, existing experimental models are mainly based on experimental results obtained under isostatic and constant amplitude loading. In this study, K0-controlled cyclic loading is undertaken by simulating a horizontal stratified ground, and the development of excess pore water pressure is evaluated by measuring the accumulated shear strain; a modified accumulated shear strain is proposed based on these results. The results show that the excess pore water pressure can be predicted from the modified accumulated shear strain, regardless of soil type, initial soil pressure coefficient, initial shear stress, or the shape of input waveform.

Oscillatory Waveform Shape and Temporal Spike Correlations Differ across Bat Frontal and Auditory Cortex.

Neural oscillations are associated with diverse computations in the mammalian brain. The waveform shape of oscillatory activity measured in the cortex relates to local physiology and can be informative about aberrant or dynamically changing states. However, how waveform shape differs across distant yet functionally and anatomically related cortical regions is largely unknown. In this study, we capitalize on simultaneous recordings of local field potentials (LFPs) in the auditory and frontal cortices of awake, male Carollia perspicillata bats to examine, on a cycle-by-cycle basis, waveform shape differences across cortical regions. We find that waveform shape differs markedly in the fronto-auditory circuit even for temporally correlated rhythmic activity in comparable frequency ranges (i.e., in the delta and gamma bands) during spontaneous activity. In addition, we report consistent differences between areas in the variability of waveform shape across individual cycles. A conceptual model predicts higher spike-spike and spike-LFP correlations in regions with more asymmetric shapes, a phenomenon that was observed in the data: spike-spike and spike-LFP correlations were higher in the frontal cortex. The model suggests a relationship between waveform shape differences and differences in spike correlations across cortical areas. Altogether, these results indicate that oscillatory activity in the frontal and auditory cortex possesses distinct dynamics related to the anatomical and functional diversity of the fronto-auditory circuit.

A new modulation approach to decrease total harmonic distortion of the SPWM voltage waveform using genetic optimization technique

The pulse width modulated power inverters have been increasingly using to convert DC power to AC power in small wind plants. When these inverters are used for power conversion, the integrated output voltage waveform is inevitably distorted. Although increasing the switching frequency is one choice to achieve the smoother output voltage, it adds extra harmonics to the output. There are various techniques such as analogue filtering, harmonic elimination etc. to reduce the number of harmonics usually affecting the system performance. In this study, a simple but efficient modulation approach based on the optimization of the shape of the triangular voltage waveform is proposed. The results have shown that the total harmonic distortion of the optimized voltage waveform decreases gradually and thus helps improve on the power quality during the conversion.

Power Quality of PV Multilevel Inverters in Residential Environment

The aim of the paper is to perform a comparative analysis of power quality for several PV multilevel inverters operating in residential environments. Two cases are presented, namely a diode-clamped multilevel inverter and a cascaded H bridge multilevel inverter which are compared with the situation of a pure sinusoidal supply regarding the voltage, the current and the instantaneous power waveform shapes. The waveforms are synthesized and uploaded in a programmable power source and are applied to a 40 W / 459 lx LED luminaire load. The harmonic limits check according to the standard IEC 61000-3- 2:2018, Class C, regarding lighting equipment are also presented. The measurements revealed that a filter retrofitting method was needed in order to obtain compliance with the power quality standard requirements

Automatic classification of circuit topologies of appliances based on higher order statistic

Electronic devices have a non-linear characteristic and are sources of harmonic emission. Their massive use pollutes the network and consequently it is needed to measure and characterize those devices. Harmonic current emitted by electronic devices is closely linked to their circuit topology and the distortion of the supply voltage. Different circuit topologies have also different current waveforms. This paper proposes an automatic classification method of steady-state appliances based on current waveform characterization in the higher order statistics space. The translation from the time domain to a statistical space enables the automatic identification of individual devices. The algorithm has been applied to the current waveforms of a large set of household appliances measured under sinusoidal conditions. The classification analysis proves that clusters of circuit topologies can be clearly identified. In addition, authors show that kurtosis and variance of an individual cycle provide enough information about the distribution of a waveform shape with respect to its average value, while the skewness inform about the half cycle bias. The method can be a useful tool to identify prevailing circuit topologies in the market. It can also improve automatic load identification, e.g. part of the future intelligent measurement systems such as smart meters.

Efficiency improvement of pulse waveform shaping on high power laser facility using deep learning

Laser pulse shaping is one of the key and time-consuming processes for preparing a shot on a high power laser facility. The frequent shifts of laser pulse waveform between shots makes improving laser pulse shaping efficiency an urgency. By combining historical dataset accumulated by iterative way of pulse shaping system and prevailing deep learning method, a U-Net modal is trained and applied on our laser facility. Now the pulse waveform shaping system integrated with this modal is capable of shaping and qualifying most of laser pulse waveforms in less than 5 s. As for part of unqualified outputs, a strategy of first deep learning prediction and then iterative way is able to fix all the rest, which cuts down roughly 80 % percent of time consumption, comparing with the absolutely iterative way.

Multiformity of extracellular microelectrode recordings from Aδ neurons in the dorsal root ganglia: a computational modeling study.

Microelectrodes serve as a fundamental tool in electrophysiology research throughout the nervous system, providing a means of exploring neural function with a high resolution of neural firing information. We constructed a hybrid computational model using the finite element method and multicompartment cable models to explore factors that contribute to extracellular voltage waveforms that are produced by sensory pseudounipolar neurons, specifically smaller A-type neurons, and that are recorded by microelectrodes in dorsal root ganglia. The finite element method model included a dorsal root ganglion, surrounding tissues, and a planar microelectrode array. We built a multicompartment neuron model with multiple trajectories of the glomerular initial segment found in many A-type sensory neurons. Our model replicated both the somatic intracellular voltage profile of Aδ low-threshold mechanoreceptor neurons and the unique extracellular voltage waveform shapes that are observed in experimental settings. Results from this model indicated that tortuous glomerular initial segment geometries can introduce distinct multiphasic properties into a neuron's recorded waveform. Our model also demonstrated how recording location relative to specific microanatomical components of these neurons, and recording distance from these components, can contribute to additional changes in the multiphasic characteristics and peak-to-peak voltage amplitude of the waveform. This knowledge may provide context for research employing microelectrode recordings of pseudounipolar neurons in sensory ganglia, including functional mapping and closed-loop neuromodulation. Furthermore, our simulations gave insight into the neurophysiology of pseudounipolar neurons by demonstrating how the glomerular initial segment aids in increasing the resistance of the stem axon and mitigating rebounding somatic action potentials.NEW & NOTEWORTHY We built a computational model of sensory neurons in the dorsal root ganglia to investigate factors that influence the extracellular waveforms recorded by microelectrodes. Our model demonstrates how the unique structure of these neurons can lead to diverse and often multiphasic waveform profiles depending on the location of the recording contact relative to microanatomical neural components. Our model also provides insight into the neurophysiological function of axon glomeruli that are often present in these neurons.

Wide-Range Displacement Monitoring With Waveform Shaping and Doppler Feature Amelioration Algorithm Utilizing Four-Channel Phase-and Quadrature Self-Injection-Locked Radar

Wide-Range Displacement Monitoring With Waveform Shaping and Doppler Feature Amelioration Algorithm Utilizing Four-Channel Phase-and Quadrature Self-Injection-Locked Radar