Results for “spectral density” — Page 9

DOE OSTI2024

Binary pseudo-random array standards for calibration of 3D optical surface profilers used for metrology with significantly curved x-ray optics

High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. The current capabilities and possibility for improvements in X-ray mirror manufacturing are limited by inherent imperfections of the integrated metrology tools. In the case of Fizeau interferometry, metrology tools are currently calibrated with super-polished flat test-standard/reference mirrors. This is acceptable for measuring slightly curved X-ray optics. However, for even moderately curved aspherical X-ray mirrors the flat-reference calibration is not sufficiently accurate and stitching Fizeau interferometer-based surface metrology is used to mitigate the problem. But still, the retrace and aberration errors, as well as the limited spatial resolution, described with the instrument transfer function (ITF), can be transferred into the optical surface topography of X-ray mirrors obtained in stitching metrology. For ITF calibration, we have developed an original technique, based on test standards structured as two-dimensional (2D) highly-randomized (HR) binary pseudo-random arrays (BPRAs). The technique employs the unique properties of the HR BPRA patterns in the spatial frequency domain., i.e. the inherent 2D power spectral density of the HR BPRA pattern has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. Here, we explore technological, metrological, and analytical aspects essential for calibration of the retrace and aberration errors of Fizeau interferometers using different types of tilted test samples, including a super-polished reference mirror for the re-trace calibration and the uniformly redundant array (URA) BPRA standards for the geometrical distortion (aberration) calibration. While the first method was previously demonstrated by researchers at DIAMOND Light Source, a method based on the URA BPRA is described and demonstrated here for the first time. We outline the design and fabrication process used in fabrication of URA BPRA test standards, and present the results of application of the URA BPRA standards demonstrating the high efficacy of our approach to geometrical distortion calibration of Fizeau interferometers. We also discuss the possible sources of unexpected peculiarities of the systematic errors, including an astigmatic character of the retrace error, observed with Fizeau interferometers at the Advanced Light Source X-Ray Optics Laboratory.

Munechika, Keiko↗

DOE OSTI2024

Binary pseudo-random array for calibration of interferometers with transmission spheres and cylinders

Binary pseudo-random array (BPRA) “white noise” artifacts are highly effective for characterizing the instrument transfer function (ITF) of surface topography metrology tools and wavefront measurement instruments. These BPRA artifacts feature all spatial frequencies within the instrument bandpass equally, resulting in a power spectral density with a white-noise-like character. This characteristic allows for direct ITF determination with uniform sensitivity across the entire spatial frequency range. We have developed a novel BPRA calibration standard that combines the diffractive pattern of a reflection computer-generated hologram (CGH) with the white noise generating BPRA pattern. By integrating these technologies using the same lithographic techniques, the resulting calibration sample enables ITF characterization of a Fizeau interferometer with a transmission sphere, or any nulling optic.

Munechika, K↗

DOE OSTI2024

Correlation Between Microscopic Current Fluctuations Observed at Ultra-Microelectrodes and Macroscopic Bulk Electrolysis Performance in Redox-Active Microemulsions

Microemulsions (μEs) have been proposed as redox flow battery (RFB) electrolytes that maximize ionic conductivity and charge capacity by synergizing two immiscible phases. However, charge transfer during electrolysis in μEs is poorly understood. Here, we show that ultramicroelectrode electrolysis of ferrocene-loaded μEs –20%, 60%, and 90% water - reveals stochastic current fluctuations. These are differentiated in the scanning electrochemical microscopy (SECM) geometry, where power spectral density analysis showed distinct changes in the frequency contributions. SECM in the substrate generation-tip collection mode showed that fluctuations arise under mass-transfer control. Significant differences in the diffusion coefficient of ferrocene species were deducted from SECM approach curves, suggesting phase transfer behavior. Using bulk electrolysis, we calculated the charge accessibility and cycling behavior in the μEs. A decrease in the stochastic behavior of the μEs seems to correlate to a higher accessibility and cycling performance, with the 90% water μE displaying the best reversibility and the 60% the lowest. Altogether, these results suggest that Marangoni-type convection driven by concentration gradients and/or μE restructuring during charge transfer play a role in the electrochemical performance of μEs. This presents opportunities for screening and diagnosing the performance of these emerging RFB electrolytes.

25 ENERGY STORAGE↗

DOE OSTI2022

RAFT (Response Amplitudes of Floating Turbines) [SWR-22-40]

RAFT is a Python code for frequency-domain analysis of floating wind turbines. RAFT works in the frequency domain to provide efficient computations of a floating wind system's response spectra accounting for platform hydrodynamics, quasi-static mooring reactions, rotor aerodynamics, and linearized control. It can be used to calculate response amplitude operators (RAO's), power spectral densities, mean/static properties, and response metrics based on mean and root-mean-square values of each output. RAFT serves as the Level 1 model in the WEIS (Wind Energy with Integrated Servo-control) toolkit, and features an OpenMDAO wrapper.

Hall, Matthew↗

DOE OSTI2023

Out of distribution evaluation for neural image compression

Official code for the NeurIPS 2023 paper "Neural Image Compression: Generalization, Robustness, and Spectral Biases". This code can be used to: - Computing spectral distortion errors of images compressed with traditional codes or neural image compression models (as proposed in the aformentioned paper) - Visualize power spectral densities and fourier heatmaps (as proposed in the aformentioned paper) - Train and test a variety of neural image compression models

Lieberman, KelseyA↗

DOE OSTI2023

Modeling Script

This script illustrates the advantages of loychikSD_NP, e.g. acts as a demonstration of the higher-order spectral density.

Loychik, Neil↗

DOE OSTI2023

Extract Bandwidth Statistical Properties

This is the script to calculate higher-order spectral densities.

Loychik, Neil↗

DOE OSTI2024

HiFiPDV2 v. 2

SAND2024-01061O The HiFiPDV-2 software is similar to other photonic Doppler velocimetry (PDV) analysis codes in that it converts signals from intensity-time space to frequency-time space using a short-time Fourier transform (STFT). It then analyzes peaks of the resulting power spectral density information to extract the velocity-time history. The unique aspects of HiFiPDV and HiFiPDV-2 are that this reduction process is repeated for an array of reasonable STFT input variables. The resulting population distribution of output velocity-time histories is evaluated to determine the most likely velocity history and its associated uncertainty. This uncertainty is defined as the systematic uncertainty of the PDV signal as it is a function of input values to the reduction process. The HiFiPDV-2 program brings new functionality and efficiency to these calculations—most notably significant reductions in memory usage and calculation times, the ability to evaluate frequency-shifted signals, and the ability to filter out baseline signals. Developers recommend that users have at least 2 GB of RAM per CPU core in their system. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Voorhees, Travis↗

DOE OSTI2020

Improving inverse Compton sources by avoiding non-linearities

We present a new, more nuanced understanding of non-linear effects in inverse Compton sources. Deleterious non-linear effects can arise even at low laser intensities, a regime previously viewed as linear. After laying out a survey of non-linear phenomena which degrade the effectiveness of inverse Compton sources, we discuss two powerful techniques designed to avoid these non-linearities. Starting with the known technique of non-linear longitudinal chirping of the laser pulse in the high laser field regime, we show that the simple stretching of the laser pulse, while keeping the energy constant, can significantly increase the spectral density of the scattered radiation in many operating regimes. Our numerical simulations show that combining these two techniques avoids detrimental non-linearities and improves the performance of inverse Compton sources over an order of magnitude.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Temporal contrast degradation from mid-spatial-frequency surface error on stretcher mirrors

Temporal contrast degradation due to mid-spatial-frequency error in chirped-pulse amplification stretcher optics is studied. Third-order cross-correlation measurements reveal a temporal peak that appears when using two different mirrors processed by magnetorheological finishing, despite an improvement in rms roughness compared to a third unprocessed mirror. Simulations based on measured power spectral density show how the actual impact on contrast is different from measurements using a typical bandwidth-limited third-order cross correlator. Furthermore, strategies are proposed to avoid this type of contrast degradation while exploiting computer numerically controlled polishing techniques for enhancement of surface figure and roughness.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Topography restoration in white-light interferometry using an instrument transfer function evaluated with binary pseudo-random arrays

Accurate knowledge of the instrument transfer function (ITF) is vital for topography measurements using white-light interferometry (WLI). To this end, we derive a complete set of analytical expressions for the power spectral density (PSD) of a discretely sampled binary pseudo-random array (BPRA) as a theoretical benchmark. We then determine the ITF by comparing this theoretical PSD with the measured PSD of the BPRA. For the Zygo ZeGage Pro HR with a objective, the determined ITF closely matches the nominal modulation transfer function (MTF). Accordingly, we integrate the nominal MTF into Fourier-domain restoration filters and apply them to practical WLI topography data, yielding restored topographies that show improved agreement with atomic force microscopy measurements. Overall, our integrated BPRA-based ITF measurement and filtering methodology offers a robust yet practical means of characterizing WLI performance and enhancing the accuracy of surface measurements.

Hirose, Shigenobu [Japan Agency for Marine Earth S↗

DOE OSTI2022

Memory and CPU efficient coherent mode decomposition of partially coherent synchrotron radiation with subtraction of common quadratic phase terms

Application examples of a memory and CPU efficient coherent mode decomposition (CMD) method for wave-optics based simulation of the partially coherent undulator radiation propagation through a hard X-ray beamline in a 3rd generation synchrotron radiation source are presented. The high efficiency of the method is achieved thanks to the analytical treatment of the common quadratic phase terms that are developed in the phase of cross-spectral density (CSD) of partially coherent radiation at a distance from source. This treatment allows for a considerable, several orders of magnitude, reduction of the 4D CSD mesh density (and the memory occupied by the CSD) required for ensuring sufficient accuracies of wavefront propagation simulations with the modes produced by the CMD at a beamline entrance. This method, implemented in the “Synchrotron Radiation Workshop” open-source software, dramatically increases the feasibility of the CMD of 4D CSD for producing 2D coherent modes for a large variety of applications at storage rings and other types of radiation sources.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Radar - 449MHz - North Bend, OR (OTH) - Reviewed Data

**Winds.** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and are combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature.** To measure atmospheric temperature, a radio acoustic sounding system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60 m up to 3.5 km for the 449 MHz. **Moments and Spectra.** The raw spectra and moments data are available for all dwells along each beam and are stored in daily files. For each day, there are files labeled "header" and "data." These files are generated by the radar data acquisition system (LAP-XM) and are encoded in a proprietary binary format. Values of spectral density at each Doppler velocity (FFT point), as well as the radial velocity, signal-to-noise ratio, and spectra width for the selected signal peak are included in these files. Attached zip files, *449mhz-spectra-data-extraction.zip* and *449mhz-moment-data-extraction.zip*, include executables to unpack the spectra, (GetSpectra32.exe) and moments (GetMomSp32.exe), respectively. Documentation on usage and output file formats also are included in the zip files.

17 WIND ENERGY↗

DOE OSTI2023

Radar - 449MHz - Forks, WA (FKS) - Reviewed Data

**Winds.** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and are combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature.** To measure atmospheric temperature, a radio acoustic sounding system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60 m up to 3.5 km for the 449 MHz. **Moments and Spectra.** The raw spectra and moments data are available for all dwells along each beam and are stored in daily files. For each day, there are files labeled "header" and "data." These files are generated by the radar data acquisition system (LAP-XM) and are encoded in a proprietary binary format. Values of spectral density at each Doppler velocity (FFT point), as well as the radial velocity, signal-to-noise ratio, and spectra width for the selected signal peak are included in these files. Attached zip files, *449mhz-spectra-data-extraction.zip* and *449mhz-moment-data-extraction.zip*, include executables to unpack the spectra, (GetSpectra32.exe) and moments (GetMomSp32.exe), respectively. Documentation on usage and output file formats also are included in the zip files.

17 WIND ENERGY↗

DOE OSTI2023

Radar - 449MHz - Astoria, OR (AST) - Reviewed Data

**Winds.** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and are combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature.** To measure atmospheric temperature, a radio acoustic sounding system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60 m up to 3.5 km for the 449 MHz. **Moments and Spectra.** The raw spectra and moments data are available for all dwells along each beam and are stored in daily files. For each day, there are files labeled "header" and "data." These files are generated by the radar data acquisition system (LAP-XM) and are encoded in a proprietary binary format. Values of spectral density at each Doppler velocity (FFT point), as well as the radial velocity, signal-to-noise ratio, and spectra width for the selected signal peak are included in these files. Attached zip files, *449mhz-spectra-data-extraction.zip* and *449mhz-moment-data-extraction.zip*, include executables to unpack the spectra, (GetSpectra32.exe) and moments (GetMomSp32.exe), respectively. Documentation on usage and output file formats also are included in the zip files.

17 WIND ENERGY↗

DOE OSTI2025

Anomaly Detection in Seismic Data with Deep Learning: Application for Instrument Failure Detection and Forecasting

Seismic data quality assessment (QA) is the first and one of the most important steps before conducting any further data analysis. Traditional methods involve checking various metrics, such as spike detection and power spectral density, by setting strict thresholds or comparing data against synthetic benchmarks. However, these approaches often rely on pre-existing knowledge and assumptions about data anomalies, leading to potential misclassification of unusual cases. Here, in this study, we propose a deep autoencoder model, an unsupervised learning approach that evaluates data quality without making assumptions about normal and anomalous data, which can be used to identify deviations in recorded data that may indicate nascent instrument failure. We test the model with the U.S. International Monitoring System (IMS) seismic stations and demonstrate the capability of detecting anomalies on a monthly scale. This could prompt station operators to examine potential problems early, allowing sufficient time for instrument maintenance to prevent data outages. In addition, we use a new manually selected testing dataset to compare our model performance against two supervised machine learning (ML) approaches and a standard QA package, as baseline models. When applied to the dataset containing known data anomalies, performance of the supervised and unsupervised ML approaches is similar, with an accuracy of 88.1% for our model compared to ∼90% for the supervised ML approach and 78.2% for the standard QA package. Our model outperforms the baseline models when applied to new stations, where new types of data anomalies can be station-specific and not included in the training dataset. Finally, we show model transferability by training the model with data from the Global Seismograph Network only and applying it to the IMS network data. The results suggest that our model is generalizable and can be applied to new stations with good accuracy.

Lin, Jiun-Ting [Lawrence Livermore National Labora↗

DOE OSTI2022

Joule heating in bad and slow metals

Heat supplied to a metal is absorbed by the electrons and then transferred to the lattice. In conventional metals energy is released to the lattice by phonons emitted from the Lindhard continuum. However in a 'bad' metal, with short mean free path, the low energy Lindhard continuum is destroyed. To describe energy transfer to the lattice in these cases we obtain a general Kubo formula for the energy relaxation rate in terms of the electronic density spectral weight \text{lm} \, G^R_{nn}(\omega_{k},k) lm G n n R ( ω k , k ) evaluated on the phonon dispersion \omega_k ω k . We apply our Kubo formula to the high temperature Hubbard model, using recent data from quantum Monte Carlo and experiments in ultracold atoms to characterize \text{lm} \, G^R_{nn}(\omega_{k},k) lm G n n R ( ω k , k ) . We furthermore use recent data from electron energy-loss spectroscopy to estimate the energy relaxation rate of the cuprate strange metal to a high energy optical phonon. As a second, distinct, application of our formalism we consider 'slow' metals. These are defined to have Fermi velocity less than the sound velocity, so that particle-hole pairs are kinematically unable to emit phonons. We obtain an expression for the energy relaxation rate of a slow metal in terms of the optical conductivity.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Critical and Californium Source-Driven Noise Analysis Subcritical Measurements with an Unreflected Cylindrical Tank of Mixed Uranium-Plutonium Nitrate Solution

The reported experiments were performed by Oak Ridge National Laboratory (ORNL) at the Battelle Northwest Laboratory’s (now Pacific Northwest National Laboratory) critical experiments facility at Hanford, Washington in 1981 and used 16 days of critical facility time, not including 10 days for setup and removal of ORNL equipment. These measurements were to assess the capability of the Cf source-driven noise analysis (CSDNA) method to measure the subcriticality (keff) of mixed U-Pu nitrate solutions. In addition to the CSNDA measurements, measurements were also performed near delayed criticality where CSDNA measurements cannot be performed. This report documents the experiments that were not reported at that time by presenting the ORNL experimental results and any online analysis performed during and shortly after the measurements. The mixed nitrate solution had a U concentration at 188 grams per liter (g/L), a Pu concentration of 280 g/L, free acid normality of 2.80, H ion molarity of 5.9 and a specific gravity of 1.754 g/cm 3 , a 240 Pu isotopic content of 7.981 wt. %, and a 235 U isotopic content of 0.724 wt. %. The stainless-steel tank for the solution had an inside diameter of 35.38 cm, an outside diameter of 35.53 cm, a height of 56.72 cm, and bottom thickness of 0.9525 cm. A Zircaloy pipe with a 3.1496 cm outside diameter, a 2.7788 cm inside diameter, and bottom thickness of 0.635 cm was available for insertion of the Cf source in the center of the fissile solution. The Cf source was also located at the outside surface of the tank (solution height varied from 10 to 53 cm) and in the center of the solution (solution height varied from 10 to 60.7 cm). The CSDNA measurements were not analyzed online to determine the subcritical neutron multiplication factors. At all subcritical states, the break frequency noise analysis data was fitted to obtain the prompt neutron decay constant. The neutron multiplication factors were determined for the two configurations of the measurements near delayed criticality. The subcritical neutron multiplication factors from the CNSDA measurements can be obtained with further analysis. However, the near delayed critical configuration, the prompt neutron decay constants, the count rates, and the measured cross and auto power spectral densities can be calculated directly for benchmarking. Much of data presented in this report are from ORNL notes—not in the ORNL logbooks. For the final benchmark analysis, the data from the Battelle Northwest Laboratory (which operated the critical facility in 1981) critical facility logbook should be consulted and be incorporated where appropriate. The purpose of this report is to document the experimental information for the measurements performed so that at a later date researchers could perform the required uncertainty and calculational analyses and documentation to use these data for an International Criticality Safety Benchmark Program (ICSBEP) or Nuclear Energy Agency benchmark. The data from these measurements are available from the ORNL Records Management Services Department, and the logbook is available from ICSBEP at Idaho National Laboratory. Preparation of the present report is part of a larger cooperative effort between Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) to document more than 15 undocumented critical and subcritical experiments enumerated in ORNL/TM-2019/18 and performed by ORNL at ORCEF and other USDOE critical experiments facilities using more than 500 operational days of critical facility time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗