Results for “Waveform sampling” — Page 3

DOE OSTI2025

Setup and Testing of PSEC5 ASIC Boards

The PSEC5 ASIC is a high-speed waveform sampling chip developed for precise measurements. This report presents the design review, test board configurations, and results from functional validation of the PSEC5 device. Key aspects examined include power integrity, voltage-controlled oscillator (VCO) behavior, SPI register functionality, clock division characteristics, readout performance, and analog biasing response. Tests were conducted across two boards under varied voltage conditions and signal configurations. Notable observations include robust VCO output, SPI communication irregularities, and anomalous readout conditions. The findings support design iterations for improved ASIC operability and firmware integration.

Fahey, Alexander [North Central Coll.]↗

NASA NTRS2009

Modulation Based on Probability Density Functions

A proposed method of modulating a sinusoidal carrier signal to convey digital information involves the use of histograms representing probability density functions (PDFs) that characterize samples of the signal waveform. The method is based partly on the observation that when a waveform is sampled (whether by analog or digital means) over a time interval at least as long as one half cycle of the waveform, the samples can be sorted by frequency of occurrence, thereby constructing a histogram representing a PDF of the waveform during that time interval.

Williams, Glenn L.↗

NASA NTRS1973

Digital second-order phase-locked loop

A digital second-order phase-locked loop is disclosed in which a counter driven by a stable clock pulse source is used to generate a reference waveform of the same frequency as an incoming waveform, and to sample the incoming waveform at zero-crossover points. The samples are converted to digital form and accumulated over M cycles, reversing the sign of every second sample. After every M cycles, the accumulated value of samples is hard limited to a value SGN = + or - 1 and multiplied by a value delta sub 1 equal to a number of n sub 1 of fractions of a cycle. An error signal is used to advance or retard the counter according to the sign of the sum by an amount equal to the sum.

Holes, J. K.↗

DOE OSTI2024

Detuned synchronized waveform averaging for reducing distortions due to sample interleaving

This invention introduces a method for optimally detuning the ratio of analog-to-digital (ADC) sample rate and trigger rate during waveform averaging to minimize the deleterious effects from sample interleaving. A prescription is described for determining the optimal detuning factor for the ADC or trigger rate in any scenario, depending on the number of ADC cores used and the limited tuning resolution of the clock rates for a specific implementation.

42 ENGINEERING↗

NASA NTRS1995

Shuttle Laser Altimeter (SLA): A pathfinder for space-based laser altimetry and lidar

The Shuttle Laser Altimeter (SLA) is a Hitchhiker experiment now being integrated for first flight on STS-72 in November 1995. Four Shuttle flights of the SLA are planned at a rate of about a flight every 18 months. They are aimed at the transition of the Goddard Space Flight Center airborne laser altimeter and lidar technology to low Earth orbit as a pathfinder for operational space-based laser remote sensing devices. Future alser altimeter sensors such as the Geoscience Laser Altimeter System (GLAS), an Earth Observing System facility instrument, and the Multi-Beam Laser Altimeter (MBLA), the land and vegetation laser altimeter for the NASA TOPSAT (Topography Satellite) Mission, will utilize systems and approaches being tested with SLA. The SLA Instrument measures the distance from the Space Shuttle to the Earth's surface by timing the two-way propagation of short (approximately 10 na noseconds) laser pulses. laser pulses at 1064 nm wavelength are generated in a laser transmitter and are detected by a telescope equipped with a silicon avalanche photodiode detector. The SLA data system makes the pulse time interval measurement to a precision of about 10 nsec and also records the temporal shape of the laser echo from the Earth's surface for interpretation of surface height distribution within the 100 m diam. sensor footprint. For example, tree height can be determined by measuring the characteristic double-pulse signature that results from a separation in time of laser backscatter from tree canopies and the underlying ground. This is accomplished with a pulse waveform digitizer that samples the detector output with an adjustable resolution of 2 nanoseconds or wider intervals in a 100 sample window centered on the return pulse echo. The digitizer makes the SLA into a high resolution surface lidar sensor. It can also be used for cloud and atmospheric aerosol lidar measurements by lengthening the sampling window and degrading the waveform resolution. Detailed test objectives for the STS-72 mission center on the acquisition of sample data sets for land topography and vegetation height, waveform digitizer performance, and verification of data acquisition algorithms. The operational concept of SLA is illustrated in Fig. 1 where a series of 100 m footprints stretch in a profile of Earth surface topography along the nadir track of the Space Shuttle. The location of SLA as a dual canister payload on the Hitchhiker Bridge Assembly in Bay 12 of the Space Shuttle Endeavor can also be noted in this figure. Full interpretation of the SLA range measurement data set requires a 1 m knowledge of the Orbiter trajectory and better than 0.1 deg knowledge of Orbiter pointing angle. These ancillary data sets will be acquired during the STS-72 mission with an on-board Global Positioning System (GPS) receiver, K-band range and range-rate tracking of the Orbiter through TDRSS, and use of on-board inertial measurement units and star trackers. Integration and interpretation of all these different data sets as a pathfinder investigation for accurate determination of Earth surface elevation is the overall science of the SLA investigation.

Bufton, Jack↗

DOE OSTI2019

PERLE: A High Power Energy Recovery Facility

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab is the first large high power CW recirculating electron accelerator to make use of SRF accelerating structures. The structures are configured in two anti-parallel linacs connected by arcs. Each linac consists of twenty C20/C50 cryomodules each containing eight 5-cell cavities and five C100 upgrade cryomodules each containing eight 7-cell cavities. Accurately classifying the source of cavity faults is critical for improving accelerator performance. A cavity fault triggers a waveform acquisition process where 17 waveform records sampled at 5 kHz are recorded for each of the 8 cavities in the affected cryomodule. The waveform record length is sufficiently long for transient microphonic effects to be observable. This data combined with archived signals sampled at 10 Hz are used to classify faults. Significant time is required for a subject matter expert to analyze and identify the intra-cavity signatures of imminent faults. This paper describes a path forward that utilizes machine learning for automatic fault classification. Post-training identification of the physical origins of faults are discussed, as are potential machine-trained model-free implementations of trip avoidance procedures. These methods should provide new insights into cavity fault mechanisms and facilitate intelligent optimization of cryomodule performance

Kaabi, W.↗

DOE OSTI2019

SRF Cavity Fault Classification Using Machine Learning At CEBAF

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab is the first large high power CW recirculating electron accelerator to make use of SRF accelerating structures. The structures are configured in two anti-parallel linacs connected by arcs. Each linac consists of twenty C20/C50 cryomodules each containing eight 5-cell cavities and five C100 upgrade cryomodules each containing eight 7-cell cavities. Accurately classifying the source of cavity faults is critical for improving accelerator performance. A cavity fault triggers a waveform acquisition process where 17 waveform records sampled at 5 kHz are recorded for each of the 8 cavities in the affected cryomodule. The waveform record length is sufficiently long for transient microphonic effects to be observable. This data combined with archived signals sampled at 10 Hz are used to classify faults. Significant time is required for a subject matter expert to analyze and identify the intra-cavity signatures of imminent faults. This paper describes a path forward that utilizes machine learning for automatic fault classification. Post-training identification of the physical origins of faults are discussed, as are potential machine-trained model-free implementations of trip avoidance procedures. These methods should provide new insights into cavity fault mechanisms and facilitate intelligent optimization of cryomodule performance

Solopova, A.↗

DOE OSTI2019

SRF Cavity Fault Classification Using Machine Learning At CEBAF

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab is the first large high power CW recirculating electron accelerator to make use of SRF accelerating structures. The structures are configured in two anti-parallel linacs connected by arcs. Each linac consists of twenty C20/C50 cryomodules each containing eight 5-cell cavities and five C100 upgrade cryomodules each containing eight 7-cell cavities. Accurately classifying the source of cavity faults is critical for improving accelerator performance. A cavity fault triggers a waveform acquisition process where 17 waveform records sampled at 5 kHz are recorded for each of the 8 cavities in the affected cryomodule. The waveform record length is sufficiently long for transient microphonic effects to be observable. This data combined with archived signals sampled at 10 Hz are used to classify faults. Significant time is required for a subject matter expert to analyze and identify the intra-cavity signatures of imminent faults. This paper describes a path forward that utilizes machine learning for automatic fault classification. Post-training identification of the physical origins of faults are discussed, as are potential machine-trained model-free implementations of trip avoidance procedures. These methods should provide new insights into cavity fault mechanisms and facilitate intelligent optimization of cryomodule performance

Solopova, A.↗

DOE OSTI2021

AC losses of Roebel and CORC ® cables at higher AC magnetic fields and ramp rates

We have measured ReBCO coated conductor-based conductor on round core (CORC ® ) and Roebel cables at 77 K in a spinning magnet calorimeter, which subjected the tapes in the samples to a radial magnetic field of 566 mT (peak) at frequencies up to 120 Hz (272 T s -1 , cyclic average) with an approximately sinusoidal waveform. The samples were oriented such that the field applied to the tapes within the cables was entirely radial, simplifying subsequent analysis. An expression for loss which included hysteretic, flux creep and eddy current losses was fit to both the CORC ® and the Roebel cables. This expression allowed easy comparison of the relative influence of eddy currents and flux creep (or power-law behavior) effects. The loss of both the CORC ® and Roebel cables measured here were seen to be essentially the sum of the hysteretic loss, flux creep effects, and the normal metal eddy current losses of the individual tapes. The losses of these cables were measured at high B × d B /d t with no coupling current loss observed under the present preparation conditions. The influence of flux creep effects on loss were not negligible. The losses of the CORC ® cable per meter of tape were seen to be reduced from the case of a flat tape because of the helical geometry of the tapes.

Physics↗

DOE OSTI2024

Waveform resampling with LMN method

In this article, resampling is a common technique applied in digital signal processing. Based on the Fast Fourier Transformation (FFT), we apply an optimization called here the LMN method to achieve fast and robust re-sampling. In addition to performance comparisons with some other popular methods, we illustrate the effectiveness of this LMN method in a particle physics experiment: re-sampling of waveforms from Liquid Argon Time Projection Chambers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRSDate not supplied

Uncertainty Quantification of CFD Model Assumptions Against Sonic Boom Noise Prediction of a Commercial Supersonic Transport

This paper presents the results of uncertainty modeling of sonic boom noise generation from commercial supersonic transport considering the Spalart-Allmaras (SA) turbulence modeling parameters as well as Mach number, angle of attack and altitude. Sample generation and analysis for this uncertainty model was performed by UQPCE, which is a software package developed at the NASA Langley Research Center. To build the uncertainty model, 42 cases of sonic boom noise calculation were performed. Computation of the ground noise can be briefly summarized in two steps. First, the near field pressure waveforms are sampled from CFD calculation using the NASA Langley’s FUN3D solver. Second, this information is passed to an atmospheric propagation code, sBOOM, which solves an augmented Burger’s equation and simulates how the near field waveforms will change while passing through the atmosphere. The ground signature is further processed to obtain the perceived loudness, PLdB. Having a high spatial resolution near the shockwave in the CFD calculation is critical in sonic boom noise prediction. Because the variation in the input parameters for the current uncertainty quantification (UQ) study is likely to lead to change in shock location, angle and strength, the grid adaptation for shock capturing is independently applied for each condition. The final mesh used in the CFD calculation consists of approximately 420 million cells. The pressure signatures are sampled at three, four and five body lengths away from the aircraft to make sure the three dimensional effects around the aircraft are resolved. The results of the UQ analysis shows that within the three aleatory variables, the angle of attack had the most impact against ground noise, followed by the altitude and the Mach number. Between the two SA model parameters, the Kármán constant (𝜅) was significantly more important than the turbulent Prandtl number (𝜎), but these two parameters were only marginally significant in the overall prediction variance in ground noise. The UQ procedure explained in this paper can be widely applied to other model parameters.

Uncertainty Quantification↗

NASA NTRSDate not supplied

Uncertainty Quantification of CFD Model Assumptions Against Sonic Boom Noise Prediction of a Commercial Supersonic Transport

This paper presents the results of uncertainty modeling of sonic boom noise generation from commercial supersonic transport considering the Spalart-Allmaras (SA) turbulence modeling parameters as well as Mach number, angle of attack and altitude. Sample generation and analysis for this uncertainty model was performed by UQPCE, which is a software package developed at the NASA Langley Research Center. To build the uncertainty model, 42 cases of sonic boom noise calculation were performed. Computation of the ground noise can be briefly summarized in two steps. First, the near field pressure waveforms are sampled from CFD calculation using the NASA Langley’s FUN3D solver. Second, this information is passed to an atmospheric propagation code, sBOOM, which solves an augmented Burger’s equation and simulates how the near field waveforms will change while passing through the atmosphere. The ground signature is further processed to obtain the perceived loudness, PLdB. Having a high spatial resolution near the shock wave in the CFD calculation is critical in sonic boom noise prediction. Because the variation in the input parameters for the current uncertainty quantification (UQ) study is likely to lead to change in shock location, angle and strength, the grid adaptation for shock capturing is independently applied for each condition. The final mesh used in the CFD calculation consists of approximately 420 million cells. The pressure signatures are sampled at three, four and five body lengths away from the aircraft to make sure the three dimensional effects around the aircraft are resolved. The results of the UQ analysis shows that within the three aleatory variables, the angle of attack had the most impact against ground noise, followed by the altitude and the Mach number. Between the two SA model parameters, the Kármán constant (𝜅) was significantly more important than the turbulent Prandtl number (𝜎), but these two parameters were only marginally significant in the overall prediction variance in ground noise. The UQ procedure explained in this paper can be widely applied to other model parameters.

Uncertainty Quantifications↗

DOE OSTI2014

Delta Modulation Technique for Improving the Sensitivity of Monobit Subsamplers in Radar and Coherent Receiver Applications

This paper introduces a technique for improving the sensitivity of RF subsamplers in radar and coherent receiver applications. The technique, referred to herein as “delta modulation” (DM), feeds the time-average output of a monobit analog-to-digital converter (ADC) back to the ADC input, but with opposite polarity. Assuming pseudo-stationary modulation statistics on the sampled RF waveform, the feedback signal corrects for aggregate DC offsets present in the ADC that otherwise degrade ADC sensitivity. Two RF integrated circuits (RFICs) are designed to demonstrate the approach. One uses analog DM to create the feedback signal; the other uses digital DM to achieve the same result. A series of tests validates the designs. The dynamic time-domain response confirms the feedback loop’s basic operation. Measured output quantization imbalance, under noise-only input drive, significantly improves with the use of the DM circuit, even for large, deliberately induced DC offsets and wide temperature variation from -55°C to +85 °C. Examination of the corrected vs. uncorrected baseband spectrum under swept input signal-tonoise ratio (SNR) conditions demonstrates the effectiveness of this approach for realistic radar and coherent receiver applications. In conclusion, two-tone testing shows no impact of the DM technique on ADC linearity.

47 OTHER INSTRUMENTATION↗

NASA NTRS1994

Fine structure of Langmuir waves observed upstream of the bow shock at Venus

Highly structured Langmuir waves, also known as electron plasma oscillations, have been observed in the foreshock of Venus using the plasma wave experiment on the Galileo spacecraft during the gravity assist flyby on February 10, 1990. The Galileo wideband sampling system provides digital electric field waveform measurements at sampling rates up to 201,600 samples per second, much higher than any previous instrument of this type. The main Langmuir wave emission band occurs near the local electron plasma frequency, which was approximately 43 kHz. The Langmuir waves are observed to shift above and below the plasma frequency, sometimes by as much as 20 kHz. The shifts in frequency are closely correlated with the downstream distance from the tangent field line, implying that the shifts are controlled by the electron beam velocity. Considerable fine structure is also evident, with timescales as short as 0.15 ms, corresponding to spatial scales of a few tens of Debye lengths. The frequency spectrum often consists of beat-type waveforms, with beat frequencies ranging from 0.2 to 7 kHz, and in a few cases, isolated wave packets. The peak electric field strengths are approximately 1 mV/m. These field strengths are too small for strongly nonlinear processes to be important. The beat-type waveforms are suggestive of a parametric decay process.

Hospodarsky, G. B.↗

NASA NTRS1994

The fine structure of Langmuir waves observed upstream of the bow shock at Venus

Highly structured Langmuir waves, also known as electron plasma oscillations, have been observed in the foreshock of Venus using the plasma wave experiment on the Galileo spacecraft during the gravity assist flyby on February 10, 1990. The Galileo wideband sampling system provides digital electric field waveform measurements at sampling rates up to 201,600 samples per second, much higher than any previous instrument of this type. The main Langmuir wave emission band occurs near the local electron plasma frequency, which was approximately 43 kHz. The Langmuir waves are observed to shift above and below the plasma frequency, sometimes by as much as 20 kHz. The shifts in frequency are closely correlated with the downstream distance from the tangent field line, implying that the shifts are controlled by the electron beam velocity. Considerable fine structure is also evident, with time scales as short as 0.15 milliseconds, corresponding to spatial scales of a few tens of Debye lengths. The frequency spectrum often consists of beat-type waveforms, with beat frequencies ranging from 0.2 to 7 kHz, and in a few cases, isolated wavepackets. The peak electric field strengths are approximately 1 mV/m. These field strengths are too small for strongly nonlinear processes to be important. The beat-type waveforms are suggestive of a parametric decay process.

Hospodarsky, G. B.↗

DOE OSTI2017

Diamond detectors for the TOTEM timing upgrade

This paper describes the design and the performance of the timing detector developed by the TOTEM Collaboration for the Roman Pots (RPs) to measure the Time-Of-Flight (TOF) of the protons produced in central diffractive interactions at the LHC . The measurement of the TOF of the protons allows the determination of the longitudinal position of the proton interaction vertex and its association with one of the vertices reconstructed by the CMS detectors. The TOF detector is based on single crystal Chemical Vapor Deposition (scCVD) diamond plates and is designed to measure the protons TOF with about 50 ps time precision. This upgrade to the TOTEM apparatus will be used in the LHC run 2 and will tag the central diffractive events up to an interaction pileup of about 1. A dedicated fast and low noise electronics for the signal amplification has been developed. The digitization of the diamond signal is performed by sampling the waveform. In conclusion, after introducing the physics studies that will most profit from the addition of these new detectors, we discuss in detail the optimization and the performance of the first TOF detector installed in the LHC in November 2015.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Fast Neutron Detection using Pixelated CdZnTe Spectrometers

One important important signature of special nuclear materials (SNM) are fast neutrons. Fast neutrons have a low natural background rate and readily penetrate high atomic number materials which easily shield gamma-ray signatures. Thus, fast neutrons provide a complementary signal to gamma rays for detecting shielded SNM. Scattering kinematics dictate that a large nucleus (such as Cd or Te) will recoil with small kinetic energy after an elastic collision with a fast neutron. Charge carrier recombination and quenching further reduce the recorded energy deposited. Thus, the energy threshold of CdZnTe detectors must be very low in order to sense the small signals from these recoils. Here, the threshold was reduced to less than 5 keVee to demonstrate that the 5.9 keV x-ray line from 55 Fe could be separated from electronic noise. Elastic scattering neutron interactions were observed as small energy depositions (less than 20 keVee) using digitally-sampled pulse waveforms from pixelated CdZnTe detectors. Characteristic gamma-ray lines from inelastic neutron scattering were also observed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

The Readout Electronics of the Mu2e Electromagnetic Calorimeter

The Mu2e electromagnetic calorimeter has been designed to measure ~100 MeV electrons with energy resolution σE/E <10%, time resolution σt < 500ps and position resolution σx < 1cm. The detector is composed of 1348 un-doped CsI crystals coupled to two large area Silicon Photomultipliers (SiPMs). Each SiPM is connected to a Front End Electronics (FEE) chip which hosts the shaping amplifier and the high voltage linear regulator. A group of 20 FEE is controlled by one Mezzanine Board (MB) which transmits the amplified signals to one Digitizer ReAdout Controller board (DiRAC). The DiRAC samples the waveforms at 200 MHz with 12-bit ADCs, packs the data according to the Mu2e custom format and transmits them to the event builder through an optical transceiver. To limit the number of pass-through connectors and the length of the cables, the readout and digitization electronics is located inside the detector cryostat and close to the interaction target. The boards will have to sustain a neutron fluence of about 5x10 10 n/cm 2 @ 1 MeVeq (Si)/y and a Total Ionizing Dose of about 12 krad, while working into a 1T magnetic field and a vacuum of 10 (-4) Torr. This harsh operational environment has made the electronics design challenging and required an extended campaign of tests to select and qualify the employed electronic components. In this paper we report on the board architecture and design, on the qualification of the prototypes, as well as on the results of the first vertical slice test of the Mu2e calorimeter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗