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At least 451 records · Page 25

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NASA NTRS1995

Model studies of the beam-filling error for rain-rate retrieval with microwave radiometers

Low-frequency (less than 20 GHz) single-channel microwave retrievals of rain rate encounter the problem of beam-filling error. This error stems from the fact that the relationship between microwave brightness temperature and rain rate is nonlinear, coupled with the fact that the field of view is large or comparable to important scales of variability of the rain field. This means that one may not simply insert the area average of the brightness temperature into the formula for rain rate without incurring both bias and random error. The statistical heterogeneity of the rain-rate field in the footprint of the instrument is key to determining the nature of these errors. This paper makes use of a series of random rain-rate fields to study the size of the bias and random error associated with beam filling. A number of examples are analyzed in detail: the binomially distributed field, the gamma, the Gaussian, the mixed gamma, the lognormal, and the mixed lognormal ('mixed' here means there is a finite probability of no rain rate at a point of space-time). Of particular interest are the applicability of a simple error formula due to Chiu and collaborators and a formula that might hold in the large field of view limit. It is found that the simple formula holds for Gaussian rain-rate fields but begins to fail for highly skewed fields such as the mixed lognormal. While not conclusively demonstrated here, it is suggested that the notionof climatologically adjusting the retrievals to remove the beam-filling bias is a reasonable proposition.

Ha, Eunho↗

DOE OSTI2021

Closures and Simulation for Thermal Radiation Transport in Stochastic Media with Nonlinear Temperature Dependence

Because of the practical challenge of rendering very complex realistic spatial structures for numerical work, it is common practice to resort to characterizing such media as stochastic mixtures of materials, ideally parametrized with low order statistics such as the mean, variance, and correlation functions of the now random material properties. This enables realizations of the medium to be repeatedly generated and radiation transport computations to, in principle, be performed for a large ensemble of these realizations to obtain a statistically well-characterized radiation field. Statistical post-processing yields desired quantities such as conditional and unconditional mean radiation flux and probability distributions of transmitted radiation. However, such computations prove expensive for all but the simplest stochastic geometries and are most suited for benchmarking approximate models. The most common approximations lead to homogenized media so that transport computations are required only on a single medium realization but by construct provide only limited statistical information on the radiation field. Almost all approximate approaches to this problem attempt to develop equations for low order moments of the radiation intensity (mean, second moment, correlation function) but inevitably encounter a closure problem: the equation for any statistical moment will contain terms depending on unknown higher-order moments. Thus, the challenge shifts to one of developing closure relations that relate the unknown moments to the lower order moments. Under very special conditions, an exact closure can be derived but in general closures are heuristically stated constitutive relations. Also, closure approaches depend on whether the mixing statistics are spatially and/or temporally continuous as in fluctuating turbulent fields, or discontinuous as in randomly mixed solid chunks of material. Thus, unconditional averaging is generally applied in the former case but conditional averaging is more appropriate when the mixing is discontinuous. In this work, the emphasis is on binary statistical mixtures of immiscible fluids as as such the quantities of interest are averages (flux, temperature) conditioned on the material type.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1985

Forced MHD turbulence in a uniform external magnetic field

Two-dimensional dissipative MHD turbulence is randomly driven at small spatial scales and is studied by numerical simulation in the presence of a strong uniform external magnetic field. A behavior is observed which is apparently distinct from the inverse cascade which prevails in the absence of an external magnetic field. The magnetic spectrum becomes dominated by the three longest wavelength Alfven waves in the system allowed by the boundary conditions: those which, in a box size of edge 2 pi, have wave numbers (kx' ky) = (1, 1), and (1, -1), where the external magnetic field is in the x direction. At any given instant, one of these three modes dominates the vector potential spectrum, but they do not constitute a resonantly coupled triad. Rather, they are apparently coupled by the smaller-scale turbulence.

Hossain, M.↗

NASA NTRS1985

Forced magnetohydrodynamic turbulence in a uniform external magnetic field

Two-dimensional dissipative MHD turbulence is randomly driven at small spatial scales and is studied by numerical simulation in the presence of a strong uniform external magnetic field. A behavior is observed which is apparently distinct from the inverse cascade which prevails in the absence of an external magnetic field. The magnetic spectrum becomes dominated by the three longest wavelength Alfven waves in the system allowed by the boundary conditions: those which, in a box size of edge 2 pi, have wave numbers (kx, ky) = (1, 1), and (1, -1), where the external magnetic field is in the x direction. At any given instant, one of these three modes dominates the vector potential spectrum, but they do not constitute a resonantly coupled triad. Rather, they are apparently coupled by the smaller-scale turbulence.

Hossain, M.↗

NASA NTRS1979

Random harmonic analysis program, L221 (TEV156). Volume 2: Supplemental system design and maintenenace document

Volume 2 of a two volume document is presented. A computer program, L222 (TEV 156), available for execution on the CDC 6600 computer is described. The program is capable of calculating steady-state solutions for linear second-order differential equations due to sinusoidal forcing functions. From this, steady-state solutions, generalized coordinates, and load frequency responses may be determined. Statistical characteristics of loads for the forcing function spectral shape may also be calculated using random harmonic analysis techniques. The particular field of application of the program is the analysis of airplane response and loads due to continuous random air turbulence.

Graham, M. L.↗

DOE OSTI2026

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗

NASA NTRS1990

Particle image fields and partial coherence

The accuracy of Young's fringe method for reducing velocity field data is compromized by a spatially incoherent background field which originates in the random locations of the seeding particles. The probability density function for the spatial frequency cutoff of this background is derived as a function of the particle count, the distribution governing the power in each frequency interval is derived, and conditions are found under which the Van Cittert-Zernike theorem applies. The background field resembles the far field of a partially coherent source in the high particle count limit, but departs significantly at low and moderate counts.

Rubinstein, Robert↗

NASA NTRS1988

Magnetic fine structure of solar coronal loops

A numerical simulation of the effect of a random photospheric flow on the magnetic structure of a coronal loop is presented. An initially uniform field embedded in a perfectly conducting plasma is assumed, extending between two flat parallel plates representing the solar photosphere at both ends of the loop. The field is perturbed by a sequence of randomly phased, sinusoidal flow patterns applied at one of the boundary plates, and the corresponding sequence of force-free fields is determined. It is found that the electric currents generated by these flows develop a fine structure on a scale significantly smaller than the wavelength of the velocity patterns. This suggests that magnetic energy is transferred to smaller scale via a cascade process.

Van Ballegooijen, A. A.↗

DOE OSTI2023

Deterministic Current–Induced Perpendicular Switching in Epitaxial Co/Pt Layers without an External Field

Current–induced spin–orbit torques (SOTs) have emerged as a powerful tool to control magnetic elements and non–uniform magnetic textures such as domain walls and skyrmions. SOT–induced switching of perpendicular magnetization generally requires an external field to break the rotational symmetry of the spin–orbit effective fields responsible for the deterministic reversal. The proposed mechanisms to eliminate this requirement often rely on complex multilayer structures that necessitate laborious optimization in the material and spin transport properties, making them less attractive for applications. Herein, current–induced, external field–free switching of an epitaxial MgO/Pt/Co trilayer with an extremely large perpendicular anisotropy in excess of 3 Tesla is reported. It is found that switching occurs due to the interplay of strong SOTs, local anisotropy fluctuations, and the Dzyaloshinkii–Moriya interaction inherent to this epitaxial system. Finally, given that these layers constitute the base stack of a magnetic tunnel junction, this switching mechanism offers the most technologically viable path toward devices such as field–free SOT–based magnetic random–access memories.

36 MATERIALS SCIENCE↗

NASA NTRS1994

The nature of the dense obscuring material in the nucleus of NGC 1068

High spatial and spectral resolution observations of the distribution, physical parameters, and kinematics of the molecular interstellar medium toward the nucleus of the Seyfert 2 galaxy NGC 1068 are reported. The data consist of 2.4 by 3.4 arcseconds resolution interferometry of the 88.6 GHz HCN J = 1 towards 0 line at 17 km/s spectral resolution, single dish observations of several mm/submm isotopic lines of CO and HCN, and 0.85 arcseconds imaging spectroscopy of the 2.12 micron H2 S(1) line at a velocity resolution of 110 km/s. The central few hundred parsecs of NGC 1068 contain a system of dense (N(H2) approximately 10(exp 5) cm(exp -3)), warm (T greater than or equal to 70 K) molecular cloud cores. The low density molecular envelopes have probably been stripped by the nuclear wind and radiation. The molecular gas layer is located in the plane of NGC 1068's large scale disk (inclination approximately 35 deg) and orbits in elliptical streamlines in response to the central stellar bar. The spatial distribution of the 2 micron H2 emission suggests that gas is shocked at the leading edge of the bar, probably resulting in gas influx into the central 100 pc at a rate of a few solar mass per year. In addition to large scale streaming (with a solid body rotation curve), the HCN velocity field requires the presence of random motions of order 100 km/s. We interpret these large random motions as implying the nuclear gas disk to be very thick (scale height/radius approximately 1), probably as the result of the impact of nuclear radiation and wind on orbiting molecular clouds. Geometry and column density of the molecular cloud layer between approximately 30 pc to 300 pc from the nucleus can plausibly account for the nuclear obscuration and anisotropy of the radiation field in the visible and UV.

Tacconi, L. J.↗

DOE OSTI2024

Far-field speckle correlations as a function of object position for microscopically distinguishing objects hidden in a randomly scattering medium

Super-resolution optical sensing is of critical importance in science and technology and has required prior information about an imaging system or obtrusive near-field probing. Additionally, coherent imaging and sensing in heavily scattering media such as biological tissue has been challenging, and practical approaches have either been restricted to measuring the field transmission of a single point source, or to where the medium is thin. We present the concept of far-subwavelength spatial sensing with relative object motion in speckle as a means to coherently sense through heavy scatter. Experimental results demonstrate the ability to distinguish nominally identical objects with nanometer-scale translation while hidden in randomly scattering media, without the need for precise or known location and with imprecise replacement. The theory and supportive illustrations presented provide the basis for super-resolution sensing and the possibility of virtually unlimited spatial resolution, including through thick, heavily scattering media with relative motion of an object in a structured field. This work provides enabling opportunities for material inspection, security, and biological sensing.

Hastings, Ryan L. (ORCID:0009000095977807)↗

DOE OSTI2022

Spectral form factor of a quantum spin glass

It is widely expected that systems which fully thermalize are chaotic in the sense of exhibiting random-matrix statistics of their energy level spacings, whereas integrable systems exhibit Poissonian statistics. In this paper, we investigate a third class: spin glasses. These systems are partially chaotic but do not achieve full thermalization due to large free energy barriers. We examine the level spacing statistics of a canonical infinite-range quantum spin glass, the quantum p-spherical model, using an analytic path integral approach. We find statistics consistent with a direct sum of independent random matrices, and show that the number of such matrices is equal to the number of distinct metastable configurations — the exponential of the spin glass “complexity” as obtained from the quantum Thouless-Anderson-Palmer equations. We also consider the statistical properties of the complexity itself and identify a set of contributions to the path integral which suggest a Poissonian distribution for the number of metastable configurations. Our results show that level spacing statistics can probe the ergodicity-breaking in quantum spin glasses and provide a way to generalize the notion of spin glass complexity beyond models with a semi-classical limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1990

Numerical simulation of 3-D Benard convection with gravitational modulation

In this numerical study, randomly and sinusoidally modulated gravitational fields imposed on three-dimensional Rayleigh-Benard convection are investigated in an effort to understand the effects of vibration (G-Jitter) on fluid systems. The time-dependent, Navier-Stokes equations and the energy equation with Boussinesq approximations are solved by a semi-implicit, pseudospectral procedure. An analysis of energy balances indicates that with increasing modulation amplitude, transition from synchronous to relaxation oscillation goes through the subharmonic response. Random modulations are found to be less stabilizing than sinusoidal and are shown to impose three-dimensionality on the flow for some parameter ranges both at terrestrial and zero base gravity conditions.

Biringen, S.↗

NASA NTRS1974

Random-access technique for modular bathymetry data storage in a continental shelf wave refraction program

A study was conducted of an alternate method for storage and use of bathymetry data in the Langley Research Center and Virginia Institute of Marine Science mid-Atlantic continental-shelf wave-refraction computer program. The regional bathymetry array was divided into 105 indexed modules which can be read individually into memory in a nonsequential manner from a peripheral file using special random-access subroutines. In running a sample refraction case, a 75-percent decrease in program field length was achieved by using the random-access storage method in comparison with the conventional method of total regional array storage. This field-length decrease was accompanied by a comparative 5-percent increase in central processing time and a 477-percent increase in the number of operating-system calls. A comparative Langley Research Center computer system cost savings of 68 percent was achieved by using the random-access storage method.

Poole, L. R.↗

NASA NTRSDate not supplied

Nanoflare heating in coronal X-ray Bright Points

Understanding the heating of the non-flaring solar corona is an active topic of research in heliophysics. It is well accepted that magnetic fields are mainly responsible for coronal heating. The photospheric driver randomly moves the foot-points of the magnetic field lines, and either generates waves or the quasi-static buildup of magnetic energy, depending on the timescale of motion. Heating by the dissipation of the magnetic energy is termed as DC heating while the dissipation of wave is known as AC heating mechanism. Both the AC and DC heating mechanisms can lead to impulsive heating events, termed nanoflares. The magnitude and frequency of these nanoflares determine whether they can adequately satisfy the coronal heating budget. Thus it is of great importance to study the nanoflares properties to validate their role in coronal heating. Individual nanoflares are difficult to detect with the present generation instruments, however their presence can be inferred through indirect observational techniques combined with simulated nanoflare-heated plasma emissions. We combined the observed emission properties of coronal X-ray bright points (XBP) in EUV and X-ray wavelengths with the simulated nanoflare heated plasma to understand nanoflare properties and their contribution in coronal heating. Our results indicate that the heating of coronal XBPs could be explained by frequent nanoflares. Further we demonstrate that the sensitive spectroscopic observations in X-ray wavelength are crucial to diagnose the nanoflare properties.

Biswajit Mondal↗

DOE OSTI2025

Once-in-a-lifetime encounter models for neutrino media. II. Quasisteady states and miscidynamic flavor evolution

We extended the once-in-a-lifetime encounter (OILE) model to stochastic interactions among neutrinos. As in the original OILE model, the new model reproduces the mean-field behavior of a dense neutrino gas for time 𝑡 ≲ (𝜇⁢𝛾) −1 , where 𝜇 measures the strength of the mean-field neutrino self-interaction potential and is proportional to the neutrino density, and the dimensionless “impact parameter” 𝛾 is a measure of the change in the flavor quantum state of a neutrino during interaction with another neutrino when the wave packets of the two neutrinos overlap. As in the mean-field case, the OILE model with random neutrino velocities experiences kinetic flavor decoherence as the flavor quantum states of the neutrinos diverge from each other. Unlike the mean-field case, however, the OILE model has a “collision term” due to the quantum entanglement among neutrinos. For 𝛾 ≪ 1, this incoherent effect can drive the neutrinos into a quasisteady state that is similar to the collective precession mode in a homogeneous and isotropic neutrino gas in the mean-field approximation. Subsequently, the collision term drives the neutrino gas adiabatically through different quasisteady states and eventually to flavor equilibration. This process is an example of miscidynamic flavor evolution, with the mixing equilibria being the quasisteady precession states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2010

Coherent Eigenmodes in Homogeneous MHD Turbulence

The statistical mechanics of Fourier models of ideal, homogeneous, incompressible magnetohydrodynamic (MHD) turbulence is discussed, along with their relevance for dissipative magnetofluids. Although statistical theory predicts that Fourier coefficients of fluid velocity and magnetic field are zero-mean random variables, numerical simulations clearly show that certain coefficients have a non-zero mean value that can be very large compared to the associated standard deviation, i.e., we have coherent structure. We use eigenanalysis of the modal covariance matrices in the probability density function to explain this phenomena in terms of `broken ergodicity', which is defined to occur when dynamical behavior does not match ensemble predictions on very long time-scales. We provide examples from 2-D and 3-D magnetohydrodynamic simulations of homogeneous turbulence, and show new results from long-time simulations of MHD turbulence with and without a mean magnetic field

Shebalin, John V.↗

NASA NTRS1988

Nanoflares and the solar X-ray corona

Observations of the sun with high time and spatial resolution in UV and X-rays show that the emission from small isolated magnetic bipoles is intermittent and impulsive, while the steadier emission from larger bipoles appears as the sum of many individual impulses. We refer to the basic unit of impulsive energy release as a nanoflare. The observations suggest, then, that the active X-ray corona of the sun is to be understood as a swarm of nanoflares. This interpretation suggests that the X-ray corona is created by the dissipation at the many tangential discontinuities arising spontaneously in the bipolar fields of the active regions of the sun as a consequence of random continuous motion of the footpoints of the field in the photospheric convection. The quantitative characteristics of the process are inferred from the observed coronal heat input.

Parker, E. N.↗