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Energy dependence of collisional time delay functions computed for H/1S/ atoms interacting via hydrogen potential, determining scattering cross sections
In this work we highlight a preliminary temporal source analysis of the six declared Democratic People's Republic of Korea (DPRK) nuclear tests. We use regional seismic data to estimate relative source time functions (RSTFs) via iterative time-domain deconvolution (Ammon, 2006; Pippin, 2022) of vertical-component ground motions recorded within 2000 km of the source region. Since RSTFs are ideally independent of site and propagation effects, their amplitude spectrum is equivalent to the source spectral ratio, but they also retain phase information. We compare observed RSTFs (in the time and frequency domains) with synthetic RSTFs derived from the Mueller & Murphy (1971) explosion source model. The resolution of these time functions varies, however, we generally obtain high-quality results within the limitations of the recording broadband instrumentation. The results indicate that this method effectively preserves source time-history information that can be used for temporal analysis of remote nuclear explosions. This preliminary analysis is intended to assess the viability of using time-domain deconvolution methods for extracting temporal source information.
Approximation of scattering resonance energies and widths of ground state of molecular hydrogen from energy dependence of atomic collisional time delay functions
The VLBI is a satellite tracking technique that to date was applied largely to the tracking of synchronous orbits. These orbits are favorable for VLBI in that the remote satellite range allows continuous viewing from widely separated stations. The primary observable, geometric time delay is the time difference for signal propagation between satellite and baseline terminals. Extraordinary accuracy in angular position data on the satellite can be obtained by observation from baselines of continental dimensions. In satellite tracking though the common objective is to derive orbital elements. A question arises as to how the baseline vector bears on the accuracy of determining the elements. Our approach to this question is to derive an analytic expression for the time delay function in terms of Kepler elements and station coordinates. The analysis, which is for simplicity based on elliptic motion, shows that the resolution for the inclination of the orbital plane depends on the magnitude of the baseline polar component and the resolution for in-plane elements depends on the magnitude of a projected equatorial baseline component.
Recent testing of the SRB/MLP Frangible Nut System (SOS Part Number 114850-9/Boosters P/N 114848-3) at NASA indicated a need to reduce the function time between boosters (2) within a single frangible nut. These boosters are initiated separately by electrical impulse(s). Coupling the output of each detonator with an explosive cross-over would reduce the function time between boosters (independent of electrical impulse) while providing additional redundancy to the system. The objectives of this program were to: provide an explosive cross-over between boosters, reduce function time between boosters to less than one (1) millisecond within a given nut, reduce cost of boosters, be compatible with the existing frangible nut system, and meet requirements of USBI Spec's (nut 10SPC-0030, booster 10SPC-0031).
A global survey of the low-frequency (1-21 mHz) source characteristics of large events are studied. We are particularly interested in events unusually enriched in low-frequency and in events with a short-term precursor. We model the source time function of 12 large earthquakes using teleseismic data at low frequency. For each event we retrieve the source amplitude spectrum in the frequency range between 1 and 21 mHz with the Silver and Jordan method and the phase-shift spectrum in the frequency range between 1 and 11 mHz with the Riedesel and Jordan method. We then model the source time function by fitting the two spectra. Two of these events, the 1980 Irpinia, Italy, and the 1983 Akita-Oki, Japan, are shallow-depth complex events that took place on multiple faults. In both cases the source time function has a length of about 100 seconds. By comparison Westaway and Jackson find 45 seconds for the Irpinia event and Houston and Kanamori about 50 seconds for the Akita-Oki earthquake. The three deep events and four of the seven intermediate-depth events are fast rupturing earthquakes. A single pulse is sufficient to model the source spectra in the frequency range of our interest. Two other intermediate-depth events have slower rupturing processes, characterized by a continuous energy release lasting for about 40 seconds. The last event is the intermediate-depth 1983 Peru-Ecuador earthquake. It was first recognized as a precursive event by Jordan. We model it with a smooth rupturing process starting about 2 minutes before the high frequency origin time superimposed to an impulsive source.
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Precise corrections of Landsat data are useful for generating land-use maps, detecting various crops and determining their acreage, and detecting changes. The paper discusses computer processing and visualization techniques for Landsat data so that users can get more information from the imagery. The elementary unit of data in each band of each scene is the integrated value of intensity of reflected light detected in the field of view by each sensor. To develop the basic mathematical approach for precision correction of the data, differences between positions of ground control points on the reference map and the observed control points in the scene are used to evaluate the coefficients of cubic time functions of roll, pitch, and yaw, and a linear time function of altitude deviation from normal height above local earth's surface. The resultant equation, termed a mapping function, corrects the warped data image into one that approximates the reference map. Applications are discussed relative to shade prints, extraction of road features, and atlas of cities.
In Fermilab's PIP-II machine protection system, beam loss signals from various detectors are digitized at 125 MS/s. Noise from both high-frequency sources and low-frequency 60 Hz AC power equipment can contaminate the data. To suppress noise across these ranges—especially 60 Hz and its harmonics, which overlap with beam loss signal frequencies—advanced digital processing beyond standard filtering is required. Several real-time functional blocks were simulated and tested on an FPGA: (1) a dual time-constant discharging integrator filter, (2) a de-ripple baseline extraction and storage block, and (3) a fast-recovery discharging integrator. The nonlinear IIR integrator filter removes high-frequency noise and feeds into the baseline extractor. Upon detecting abrupt beam loss, it switches to a longer time constant to prevent baseline distortion. The de-ripple block calculates a valid baseline by averaging over multiple 60 Hz periods, storing results in a 4096-word FPGA RAM. This baseline is subtracted from raw data before integration by the fast-recovery block, which resets quickly after use. All blocks achieved expected performance and were successfully implemented on a low-cost FPGA.
Recorded seismic data are generally contaminated by noise from different sources, which masks the signals of interest. In the seismology community, frequency filtering (FF) is the standard method for noise suppression. However, when the signal of interest and noise share the same frequency band, the latter cannot be filtered out without infringing on the former. We implemented a noise suppression approach based on the mathematical morphology theorem. The method involves compound operations of dilation and erosion using structuring elements of varying lengths and decomposes an input noisy waveform into several time functions with differing characteristics. Further, the filtered waveform is constructed from the time functions using a self-adaptive reconstruction technique. Application to a data set of >4700 local waveforms suggests that the implemented mathematical morphological filtering (MMF) approach is efficient for data with low signal-to-noise ratio (SNR) and significantly outperforms FF in that SNR range. For most of the dataset, FF, machine learning (ML) denoising, and continuous wavelet transform (CWT) thresholding result in higher SNR values compared with the MMF method. However, for ~42% of the waveforms, MMF outperforms FF, and the SNR gain achieved with MMF is as large as ~23 dB. Compared to ML denoising and CWT thresholding, this proportion drops to only ~10%–14%. Our results suggests that in an operational setting, MMF cannot replace the other noise suppression methods; however, signal detection can be improved if MMF is used to supplement them in some scenarios. MMF could help detect signals in problematic low-SNR data, which are currently being missed particularly when using FF alone.
Relationship of perigee motion of satellite orbit to latitude and local time
Improvements are made on IUE data reduction using corrected reseau positions and dispersion constants for temperature variations and secular effects. Models describing the motion of the high dispersion spectral format as a function of THDA alone reduce the scatter in the predicted position of a given wavelength, and scatter is further reduced when a linear dependence on time is also allowed. A correction technique is presented for early data which reduces errors in wavelength assignments from over 30 km/s to less than 3 km/s in high dispersion. The reseau temperature correction helps locate the minimum background signal, centered between the echelle orders. The residual uncertainty of 2 km/s for SWP and 2.7 km/s for LWR makes the wavelength accuracy of time and temperature corrected IUE spectra comparable to that of temperature corrected data from the Copernicus satellite.
Time-frequency signal representations combined with subspace identification methods were used to analyze aeroelastic flight data from the F/A-18 Systems Research Aircraft (SRA) and aeroservoelastic data from the F/A-18 High Alpha Research Vehicle (HARV). The F/A-18 SRA data were produced from a wingtip excitation system that generated linear frequency chirps and logarithmic sweeps. HARV data were acquired from digital Schroeder-phased and sinc pulse excitation signals to actuator commands. Nondilated continuous Morlet wavelets implemented as a filter bank were chosen for the time-frequency analysis to eliminate phase distortion as it occurs with sliding window discrete Fourier transform techniques. Wavelet coefficients were filtered to reduce effects of noise and nonlinear distortions identically in all inputs and outputs. Cleaned reconstructed time domain signals were used to compute improved transfer functions. Time and frequency domain subspace identification methods were applied to enhanced reconstructed time domain data and improved transfer functions, respectively. Time domain subspace performed poorly, even with the enhanced data, compared with frequency domain techniques. A frequency domain subspace method is shown to produce better results with the data processed using the Morlet time-frequency technique.
A task overload condition often leads to high stress for an operator, causing performance degradation and possibly disastrous consequences. Just as dangerous, with automated flight systems, an operator may experience a task underload condition (during the en-route flight phase, for example), becoming easily bored and finding it difficult to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, the disengaged operator may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss an approach for Operator Functional State (OFS) monitoring in a typical aviation environment. A systematic ground truth finding procedure has been designed based on subjective evaluations, performance measures, and strong physiological indicators. The derived OFS ground truth is continuous in time compared to a very sparse estimation of OFS based on an expert review or subjective evaluations. It can capture the variations of OFS during a mission to better guide through the training process of the OFS assessment model. Furthermore, an OFS assessment model framework based on advanced machine learning techniques was designed and the systematic approach was then verified and validated with experimental data collected in a high fidelity Boeing 737 simulator. Preliminary results show highly accurate engagement/disengagement detection making it suitable for real-time applications to assess pilot engagement.
This project focussed on two aspects of computational modeling with a view toward application for photovoltaic design: (i) increased reliability of exchange-correlation functionals in time-dependent density functional theory (TDDFT) (a method of choice of the calculation of electronic spectra and dynamics), especially for time-resolved non-perturbative dynamics, and (ii) the development of a practical but rigorously-based method for coupling electronic and nuclear motion via the exact-factorization (EF) approach (a relatively new framework for developing approximations).
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Cosmic radiation anisotropy variation with time and direction described on intensity contour map, noting application for neutron monitors data reduction
Rats adrenal corticosterone concentrations changes in response to ACTH, determining response sensitivity dependence on time after hypophysectomy