Search NASA⌕ Search

SEARCH · Search NASA

Results for “FOURIER SERIES”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Differences between seasonal and mean annual energy balance model calculations of climate and climate sensitivity

The paper extends a simple Budyko-Sellers mean annual energy balance climate model with diffusive transport to include a seasonal cycle. In the model the latitudinal distribution of the zonal average surface temperature is represented by Legendre polynomials and its time-dependence by a Fourier sine-cosine series, and it has three parameters adjusted so that the observed amplitudes of the Northern Hemisphere zonal mean surface temperature are recovered. The seasonal model is used to reveal how the annual mean climate and the sensitivity to changes in incident radiation differ from the predictions obtained with the corresponding mean annual model. The distribution of the incident solar radiation in the models is shown to be insensitive to changes in the eccentricity and the longitude of perihelion and sensitive only to changes in the obliquity of the earth, and for past orbital changes both the seasonal and the mean annual model fail to produce glacial advances of the magnitude that are thought to have occurred.

North, G. R.↗
NASA NTRS1980

A plane-polar approach for far-field construction from near-field measurements

The planar configuration with a probe scanning a polar geometry is discussed with reference to its usefulness in the determination of a far field from near-field measurements. The accuracy of the method is verified numerically, using the concept of probe compensation as a vector deconvolution. Advantages of the Jacobi-Bessel series over the fast Fourier transforms for the plane-polar geometry are demonstrated. Finally, the far-field pattern of the Viking high gain antenna is constructed from the plane-polar near-field measured data and compared with the previously measured far-field pattern.

Rahmat-Samii, Y.↗
NASA NTRS1986

VLSI Architectures for Computing DFT's

Simplifications result from use of residue Fermat number systems. System of finite arithmetic over residue Fermat number systems enables calculation of discrete Fourier transform (DFT) of series of complex numbers with reduced number of multiplications. Computer architectures based on approach suitable for design of very-large-scale integrated (VLSI) circuits for computing DFT's. General approach not limited to DFT's; Applicable to decoding of error-correcting codes and other transform calculations. System readily implemented in VLSI.

Truong, T. K.↗
NASA NTRS2013

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

Morelli, Eugene A.↗
NASA NTRS1974

Program for the analysis of time series

A digital computer program for the Fourier analysis of discrete time data is described. The program was designed to handle multiple channels of digitized data on general purpose computer systems. It is written, primarily, in a version of FORTRAN 2 currently in use on CDC 6000 series computers. Some small portions are written in CDC COMPASS, an assembler level code. However, functional descriptions of these portions are provided so that the program may be adapted for use on any facility possessing a FORTRAN compiler and random-access capability. Properly formatted digital data are windowed and analyzed by means of a fast Fourier transform algorithm to generate the following functions: (1) auto and/or cross power spectra, (2) autocorrelations and/or cross correlations, (3) Fourier coefficients, (4) coherence functions, (5) transfer functions, and (6) histograms.

Brown, T. J.↗
DOE OSTI2025

Enhancing Short-Range Weather Forecasts through Temporal Variation Encoding: A Multiperiod Embedding Approach

Machine learning (ML) techniques have emerged as promising approaches to improve regional weather forecast accuracy and reliability through data-driven methods. We propose a novel ML-based weather forecasting model, the Multiperiod Embed Net (MPENet). A key distinguishing feature of MPENet is its explicit utilization of the inherent cyclic nature in weather dynamics, unlike the autoregressive strategies commonly used in other ML weather forecasting approaches. Critical cyclic structures are identified via Fourier analyses of dynamic time series. Cyclicity in the convolutional representation is achieved by transforming one-dimensional time series of meteorological variables into two-dimensional tensors based on identified periods. This approach enables the model to leverage intrinsic weather patterns, enhancing regional forecast performance. To demonstrate the effectiveness of MPENet, we conduct a comparative analysis with Nvidia’s FourCastNet. Both models are trained on High-Resolution Rapid Refresh (HRRR) data from 2015 to 2022, over a 192 km × 192 km region in Tennessee. The comparisons are performed locally at two specific locations known to have different weather dynamics due to orographic effects: Crossville, on the relatively flat Cumberland Plateau with fewer topographic airflow disruptions, and Oak Ridge, in the ridge-and-valley region, where airflow is heavily influenced by surrounding valleys and mountains. Our results indicate that FourCastNet achieves strong accuracy at very short lead times, while MPENet maintains competitive skill and shows advantages in capturing temporal evolution over longer periods. Cross-correlation analyses of MPENet and FourCastNet predictions with the HRRR data suggest that encoding critical cyclicity into the network architecture leads to improvements in the forecasting skill.

Artificial intelligence↗
NASA NTRS1983

Persistent anomalies of the Southern Hemisphere circulation

The persistent features of large anomalies have been examined and the locations of blocking in the Southern Hemisphere were determined. The data set used here contains daily maps of 500 mb geopotential heights for 100 months (June 1, 1972 to Nov. 30, 1980) covering from 10S to 90S. The seasonal cycle was defined as a 8 year mean and the 8th (annual) and 16th (semiannual) Fourier components of the time series at each grid point. Anomalies were defined as the difference between the total field and the seasonal cycle for each grid point.

Mo, K. C.↗
NASA NTRS2003

RACE and Calculations of Three-dimensional Distributed Cavity Phase Shifts

The design for RACE, a Rb-clock flight experiment for the ISS, is described. The cold collision shift and multiple launching (juggling) have important implications for the design and the resulting clock accuracy and stability. We present and discuss the double clock design for RACE. This design reduces the noise contributions of the local oscillator and simplifies and enhances an accuracy evaluation of the clock. As we try to push beyond the current accuracies of clocks, new systematic errors become important. The best fountain clocks are using cylindrical TE(sub 011) microwave cavities. We recently pointed out that many atoms pass through a node of the standing wave microwave field in these cavities. Previous studies have shown potentially large frequency shifts for atoms passing through nodes in a TE(sub 013) cavity. The shift occurs because there is a small traveling wave component due to the absorption of the copper cavity walls. The small traveling wave component leads to position dependent phase shifts. To study these effects, we perform Finite Element calculations. Three-dimensional Finite Element calculations require significant computer resources. Here we show that the cylindrical boundary condition can be Fourier decomposed to a short series of two-dimensional problems. This dramatically reduces the time and memory required and we obtain (3D) phase distributions for a variety of cavities. With these results, we will be able to analyze this frequency shift in fountain and future space clocks.

Li, Ruoxin↗
DOE OSTI2025

Amplified Mesoscale and Submesoscale Variability and Increased Concentration of Precipitation under Global Warming over Western North America

Abstract Cold-season precipitation statistics in simulations from the storm-resolving WRF Model at 6-km and 1-h resolution over western North America are analyzed. Pseudo–global warming future simulations for the 2041–80 period, constrained by GCMs under the RCP8.5 scenario, are compared to the 1981–2020 historical simulation. The analysis focuses on the dynamical properties of precipitation time series at subdaily scales and on the morphology of storms. The statistical distribution of precipitation intensities in each pixel of the simulation domain is characterized through nonparametric statistical indicators: frequency of wet hours, mean wet-hour precipitation intensity, and Gini coefficient as a measure of the temporal concentration of the precipitation volume. Additionally, the temporal and spatial Fourier power spectra of precipitation time series and precipitation fields are analyzed. The half-power period (HPP) and half-power wavelength (HPW) are defined as spectral measures of the characteristic scales of precipitation’s temporal and spatial patterns. The results show statistically significant increases in the mean wet-hour precipitation intensity and in the Gini coefficient in 99% of the pixels, indicating that the seasonal precipitation volume becomes more concentrated within a smaller number of hours with higher precipitation intensity. The statistics of change in the frequency of wet hours are more contrasted across the simulation domain. The changes are also reflected in the power spectra, which show the spatial and temporal variability increasing proportionally more with finer spatial and temporal scales and the HPW and HPP decreasing. These projected changes are expected to have consequences, not only in terms of hydrologic impacts but also in terms of the predictability of precipitation patterns. Significance Statement The precipitation characteristics of winter storms over the western United States and southwestern Canada are analyzed in future climate simulations for the 2041–80 period. As compared to present-day climate, the most intense parts of the storms are projected to produce a higher rainfall volume, with increased concentration over smaller areas and shorter time intervals. The propensity of rainfall intensity to vary rapidly over time will be enhanced in the future according to the simulations. These model predictions imply an increased risk of rapid flooding in small basins. They also suggest that predicting several hours ahead the time and location at which a storm will produce maximum rainfall may become more challenging in the future.

Climate change↗
NASA NTRS1988

An efficient approach for statistical calculations with globally gridded filtered time series

The formulas for performing several statistical calculations based on Fourier coefficients are presented for use in atmospheric observational studies. The calculations discussed include a method for estimating the degree of temporal freedoms of two correlated time series and a method for performing seasonal analyses using a half-year summer/winter projection operator in the frequency domain. A modified lag-correlation calculation is proposed for obtaining lag correlations in the frequency domain. Also, a spectral approach for Empirical Orthogonal Function (EOF) and Extended EOF analysis is given which reduces the size of the matrix to be solved in the eigenproblem.

Gao, X. H.↗
NASA NTRS1958

Investigation of Aperiodic Time Processes with Autocorrelation and Fourier Analysis

Autocorrelation and frequency analyses of a series of aperiodic time events, in particular, filtered noises and sibilant sounds, were made. The position and band width of the frequency ranges are best obtained from the frequency analysis, but the energies contained in the several bands are most easily obtained from the autocorrelation function. The mean number of zero crossings of the time function was determined from the curvature of the latter function in the vicinity of the zero crossing, and also with the aid of a decimal counter. The second method was found to be more exact.

Exner, Marie Luise↗
NASA NTRS2008

Simulation of Ground Winds Time Series for the NASA Crew Launch Vehicle (CLV)

Simulation of wind time series based on power spectrum density (PSD) and spectral coherence models for ground wind turbulence is described. The wind models, originally developed for the Shuttle program, are based on wind measurements at the NASA 150-m meteorological tower at Cape Canaveral, FL. The current application is for the design and/or protection of the CLV from wind effects during on-pad exposure during periods from as long as days prior to launch, to seconds or minutes just prior to launch and seconds after launch. The evaluation of vehicle response to wind will influence the design and operation of constraint systems for support of the on-pad vehicle. Longitudinal and lateral wind component time series are simulated at critical vehicle locations. The PSD model for wind turbulence is a function of mean wind speed, elevation and temporal frequency. Integration of the PSD equation over a selected frequency range yields the variance of the time series to be simulated. The square root of the PSD defines a low-pass filter that is applied to adjust the components of the Fast Fourier Transform (FFT) of Gaussian white noise. The first simulated time series near the top of the launch vehicle is the inverse transform of the adjusted FFT. Simulation of the wind component time series at the nearest adjacent location (and all other succeeding next nearest locations) is based on a model for the coherence between winds at two locations as a function of frequency and separation distance, where the adjacent locations are separated vertically and/or horizontally. The coherence function is used to calculate a coherence weighted FFT of the wind at the next nearest location, given the FFT of the simulated time series at the previous location and the essentially incoherent FFT of the wind at the selected location derived a priori from the PSD model. The simulated time series at each adjacent location is the inverse Fourier transform of the coherence weighted FFT. For a selected design case, the equations, the process and the simulated time series at multiple vehicle stations are presented.

Adelfang, Stanley I.↗
DOE OSTI2024

Denoising Seismic Waveforms Using a Wavelet-Transform-Based Machine-Learning Method

Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency‐based filtering methods for waveform denoising do not result in desired outcomes when the targeted signal and noise occupy similar frequency bands. Recently, denoising techniques based on deep‐learning convolutional neural networks (CNNs), in which a recorded waveform is decomposed into signal and noise components, have led to improved results. These CNN methods, which use short‐time Fourier transform representations of the time series, provide signal and noise masks for the input waveform. These masks are used to create denoised signal and designaled noise waveforms, respectively. However, advancements in the field of image denoising have shown the benefits of incorporating discrete wavelet transforms (DWTs) into CNN architectures to create multilevel wavelet CNN (MWCNN) models. The MWCNN model preserves the details of the input due to the good time–frequency localization of the DWT. In this report we use a data set of over 382,000 constructed seismograms recorded by the University of Utah Seismograph Stations network to compare the performance of CNN and MWCNN‐based denoising models. Evaluation of both models on constructed test data shows that the MWCNN model outperforms the CNN model in the ability to recover the ground‐truth signal component in terms of both waveform similarity and preservation of amplitude information. Model evaluation of real‐world data shows that both the CNN and MWCNN models outperform standard band‐pass filtering (BPF; average improvement in signal‐to‐noise ratio of 9.6 and 19.7 dB, respectively, with respect to BPF). Evaluation of continuous data suggests the MWCNN denoiser can improve both signal detection capabilities and phase arrival time estimates.

58 GEOSCIENCES↗
NASA NTRS1980

Verification of interim simulated atmospheric turbulence

During horizontal and near-horizontal flight of the space shuttle orbiter, the effects of atmospheric turbulence on the vehicle are crucial in establishing the space shuttle design, control, and human pilot effects. The effects of both turbulent gusts and gust gradients (shears) must be taken into account. By means of a nonrecursive turbulence simulation model, twelve simulated turbulence time series for gusts and gust gradients were generated as part of a previous investigation. The current investigation was concerned with the spectral analysis of the time series based on the use of Fourier transform theory. A comparison between the computed spectra and the corresponding von Karman theoretical spectra is also included. A basic difference is explained between the computed and theoretical spectra which was identified as a result of the comparison. Conclusions and recommendations are presented.

Tatom, F. B.↗
NASA NTRSDate not supplied

Dynamic Mode Decomposition of Unsteady Pressure-Sensitive Paint Measurements for the NASA Unitary Plan Wind Tunnel Tests

This paper describes the Dynamic Mode Decomposition (DMD) of the pressures on the scale model of the Space Launch System (SLS) Block 1 cargo vehicle with the Unsteady Pressure-Sensitive Paint (uPSP) measurements, which were collected in the Ascent Transient Aerodynamics Tests with the Unitary Plan Wind Tunnel 11-by-11-foot Transonic Wind Tunnel in September 2019 at NASA Ames Research Center. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. The conventional DMD algorithm is based on the Singular Value Decomposition (SVD) of the data matrix. For the matrix of the uPSP measurements of the SLS ATAT, the number of rows is equal to the number of nodes in the grid of the scale model, and the number of columns is equal to the number of frames in the videos taken with 4 Phantom high-speed cameras. In this paper, it is verified that, for the time series with zero mean value, the DMD is equivalent to the decomposition with the Discrete Fourier Transform (DFT). Considering the uPSP is mainly used in the assessment of the unsteady, aerodynamic phenomena, the DMD of the uPSP measurements can be implemented in two steps: (1) subtract the mean value from the uPSP measurement on each of the grid nodes; (2) apply the Fast Fourier Transform (FFT) on the resulting zero-mean time series. The DMD of the uPSP measurements with FFT has two advantages: (1) the computational complexity of FFT is O(N*logN), where N is the length of the time series; (2) compared to the SVD-based DMD algorithm, the DMD with FFT can be easily implemented in parallel processing. A sample matrix of uPSP measurements, at the size of 341 grid nodes and 128 frames, is generated. Figures 1 and 2 show the eigenvalues and the ratios of the eigenvectors, respectively, of the sample matrix, without and with the mean value removed on each of the grid nodes, computed with the SVD-based DMD and the FFT. The figures demonstrate the equivalence of the SVD-based DMD and the decomposition with DFT/FFT for the time series with zero mean value. The results of DMD of the uPSP measurements of the SLS ATAT in September 2019 are presented in the paper. The DMD modes at different frequencies are shown, the aerodynamic phenomena (e.g. shockwave and vortex shedding) are demonstrated and the correlation of the DMD modes with the test configuration parameter (e.g., the Mach Number) is discussed. Figure 3 shows a software tool to visualize the DMD modes. The code to implement the algorithm described in this paper was written in C, with libraries of FFTW for FFT and MPI/OpenMP for parallel processing, and executed on the NASA Pleiades supercomputer. Funding for this research was provided by the NASA Aerosciences Evaluation and Test Capabilities Project.

Pressure-Sensitive Paint↗
NASA NTRS1985

Cosmic ray secular variations in terrestrial records and aurorae

The rediscovery that the Sun and the solar wind can undergo important changes on historical time scales has brought into question the stability of the cyclic behavior of past time series of solar and solar-terrestrial origin. It was found by Vector Fourier analysis that the solar 11 year cycle is present in the series of 10Be, delta 180, in ice cores and of thermoluminescence (TL) in sea sediments during the last Millennia with a frequency modulation, related to the Sun behavior, as tested by comparison with the Sunspot number R sub z series. It was shown that the cyclogram of the series of yearly Aurorae from 1721 to 1979 linear-regression-corrected-for-R sub z is straight for the periodicity zeta=11,1y, which indicates that such periodicity is constant in time corresponding to the only line present in the 11y band. The maxima of this component appear at the same time together with the high speed solar wind streams taking place in coronal holes situated in high heliolatitudes. It is evidenced that the 11 year cycle has undergone frequency oscillations on a time scale of two centuries, although it is very difficult to determine the periodicities with high accuracy.

Attolini, M. R.↗
NASA NTRS1985

The conjecture concerning time variations in the solar neutrino flux

The results of the Fourier transformation of the unequally-spaced time series of the recorded Ar-37 production rate of the solar neutrino experiment (runs 18 to 80, 1970 to 1983) are reviewed. Significance criteria for every period discovered by the harmonic analysis are determined. A Fourier synthesis of certain discovered harmonics are performed. It seems that the solar neutrino flux increases shock-like with a period of approximately 8.3 years and after that breaks down. Possible connections between the periods found by the harmonic analysis and several observed phenomena on the solar surface are indicated.

Haubold, H. J.↗
NASA NTRS2003

Short-period circumnutations found in sunflower hypocotyls in satellite orbit. A reappraisal of data from Spacelab-1

We have further analysed data from an experiment performed in satellite orbit, in Spacelab-1. In micro-gravity the hypocotyls of Helianthus annuus, cv. "Teddy Bear", showed short period circumnutations (periods around 30 minutes) as well as the already reported long period nutations (with an average period of about 115 minutes). We applied various types of signal analysis (Fourier and wavelet analysis) to the data series. The long period circumnutations have a larger amplitude than the short term circumnutations. Both short and long period circumnutations exist in one and the same hypocotyl. (This is in contrast to our ground control experiments, where were found only the long-period nutations.) The period of the nutations changed throughout the experiment. These results are extending the conclusions drawn after the Spacelab experiment (Brown et al. 1990). In particular they emphasize the existence of both short- and long-period circumnutations in micro-gravity.

short duration↗