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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

SAIL Field Campaign X-Band Precipitation Radar Seasonal Surface Hydrometeor Phase Classification Value-Added Product Report

The Surface Atmosphere Integrated Field Laboratory (SAIL) campaign generated an unprecedented, multisensory record of cold-season precipitation in the Upper Colorado River Basin (UCRB). To complement the Surface Quantitative Precipitation Estimation (SQUIRE) snow water equivalent (SWE) product derived from the Colorado State University (CSU) X-band radar, a hydrometeor phase classification data set was developed to systematically identify phase of the near-surface precipitation. The algorithm uses Corrected Moments in Antenna Coordinates (CMAC) fields with semi-supervised classification (SSC) and fuzzy-logic hydrometeor classification (FHC) methods and maps hydrometeor classes to a compact set of phase classes suitable for Quantitative Precipitation Estimation (QPE) and hydrologic applications. We used SQUIRE grid projections to mitigate beam-blockage issues by selecting the near-surface gates for each beam as well as to make it directly usable for the QPE products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Graph neural networks for mechanical property prediction of 2D fiber composites

This work investigates the ability of graph neural networks (GNNs) to homogenize 2D fiber composite microstructures. We use different inhomogeneity and anisotropy indices to motivate and show that the Volume Elements (VEs) used in ML methods should ideally be far from their Representative Volume Element (RVE) size limit and, consequently, are notably anisotropic. Hence, training only the isotropic limit properties may not be acceptable. Another aspect is the need to normalize elastic stiffness values for ML, especially when high elastic contrast ratios are encountered between composite phases or in the material set. We introduce a normalization technique based on the mean-field method (MFM) to handle such high contrast ratios and train for the entire stiffness tensor. We show that the proposed GNN approaches exhibit high accuracy and efficiency compared to traditional methods and convolutional neural networks, utilizing unstructured graphs constructed from microstructure topology. Our model successfully predicts the stiffness tensor, peak strength under bulk damage, and brittle fracture initiation strength across diverse microstructure configurations while maintaining high accuracy even for extreme material contrasts and volume fractions. We also present a method to improve prediction accuracy for small dataset sizes using Voronoi partitioning.

Brittle strength↗
NASA NTRS2012

Construction of Solar-Wind-Like Magnetic Fields

Fluctuations in the solar wind fields tend to not only have velocities and magnetic fields correlated in the sense consistent with Alfven waves traveling from the Sun, but they also have the magnitude of the magnetic field remarkably constant despite their being broadband. This paper provides, for the first time, a method for constructing fields with nearly constant magnetic field, zero divergence, and with any specified power spectrum for the fluctuations of the components of the field. Every wave vector, k, is associated with two polarizations the relative phases of these can be chosen to minimize the variance of the field magnitude while retaining the\random character of the fields. The method is applied to a case with one spatial coordinate that demonstrates good agreement with observed time series and power spectra of the magnetic field in the solar wind, as well as with the distribution of the angles of rapid changes (discontinuities), thus showing a deep connection between two seemingly unrelated issues. It is suggested that using this construction will lead to more realistic simulations of solar wind turbulence and of the propagation of energetic particles.

Roberts, Dana Aaron↗
NASA NTRS1995

A comparison of two algorithms for simulating collisionless systems

Two completely different simulation algorithms are compared by applying them to the same stellar dynamical problems: one is a self-consistent field (SCF) method for solving Poisson's equation and the other is a phase-space method for integrating the collisionless Boltzmann equation. We consider simulations of spherical stellar systems which are initially far from equilibrium and relax to their final states by gravitational collapse. The initial conditions consist of either uniform-density spheres or nonequilibrium models having Plummer density profiles, in which velocity dispersions are assigned according to given virial ratios. If a few tens of radial expansion terms with hundreds of thousands of particles are used in the SCF code, excellent agreement is found between the results it generates and those obtained with the phase-space solver, provided that a sufficiently large number of grid cells are employed with the latter. These findings imply that for simulating collisionless systmes over many dynamical times, the SCF approach based on sampling phase space is competitive with the approach treating phase space as a continuous fluid. The results of our tests make it possible to estimate the number of particles and basis functions required in situations like those modeled. Limitations of the SCF method and the choice of an optimal set of basis functions are also discussed.

Hozumi, Shunsuke↗
NASA NTRS2007

Closed Loop, DM Diversity-based, Wavefront Correction Algorithm for High Contrast Imaging Systems

High contrast imaging from space relies on coronagraphs to limit diffraction and a wavefront control systems to compensate for imperfections in both the telescope optics and the coronagraph. The extreme contrast required (up to 10(exp -10) for terrestrial planets) puts severe requirements on the wavefront control system, as the achievable contrast is limited by the quality of the wavefront. This paper presents a general closed loop correction algorithm for high contrast imaging coronagraphs by minimizing the energy in a predefined region in the image where terrestrial planets could be found. The estimation part of the algorithm reconstructs the complex field in the image plane using phase diversity caused by the deformable mirror. This method has been shown to achieve faster and better correction than classical speckle nulling.

Give'on, Amir↗
NASA NTRS1990

Development of advanced silicon solar cells for Space Station Freedom

This report describes the development of large area high efficiency wrapthrough solar cells for Space Station Freedom. The goal of this contract was the development and fabrication of 8 x 8 cm coplanar back contact solar cells with a minimum output of 1.039 watts/cell. The first task in this program was a modeling study to determine the optimum configuration of the cell and to study the effects of surface passivation, substrate resistivity, and back surface field on the BOL and EOL performance. In addition, the optical stack, including the cell cover, AR coatings, and Kapton blanket, was modeled to optimize 'on orbit' operation. The second phase was a manufacturing development phase to develop high volume manufacturing processes for the reliable production of low recombination velocity boron back surface fields, techniques to produce smooth, low leakage wrapthrough holes, passivation, photoresist application methods, and metallization schemes. The final portion of this program was a pilot production phase. Seven hundred solar cells were delivered in this phase. At the end of the program, cells with average efficiencies over 13 percent were being produced with power output in excess of 1.139 watts/cell, thus substantially exceeding the program goal.

Lillington, David R.↗
DOE OSTI2025

Insights into distorted lamellar phases with small-angle scattering and machine learning

Lamellar phases are essential in various soft matter systems, with topological defects significantly influencing their mechanical properties. In this report, we present a machine-learning approach for quantitatively analyzing the structure and dynamics of distorted lamellar phases using scattering techniques. By leveraging the mathematical framework of Kolmogorov–Arnold networks, we demonstrate that the conformations of these distorted phases – expressed as superpositions of complex waves – can be reconstructed from small-angle scattering intensities. Through the contour analysis of wave field phase singularities, we obtain the statistics of the spatial distribution of topological defects. Furthermore, we establish that the temporal evolution of these defects can be derived from the time-dependent traveling wave field, informed by the dispersion relation of spectral components. This method opens new avenues for investigating the dynamics of distorted lamellar phases using various dynamic scattering techniques such as neutron spin echo and X-ray photon correlation spectroscopy. These findings enhance our microscopic understanding of how defects influence the physical properties of lamellar materials, with implications for both equilibrium and non-equilibrium states in general lamellar systems.

36 MATERIALS SCIENCE↗
NASA NTRS2024

Crowd-Sourced Technology Challenge for Improving Visual Color Detection of Hydrazine and Monomethylhydrazine Vapors in Spacecraft Environments

NASA currently uses a visual colorimetric detection method for potential hydrazine, monomethylhydrazine (MMH), or unsymmetrical dimethylhydrazine (UDMH) contamination in the International Space Station. Astronauts exposed to propellants or their residues during extravehicular activities may transfer contaminants into the airlock. The colorimetric detection method employs the Contamination Detection Kit (CDK), which uses a potassium tetrachloroaurate redox reaction with the propellant hydrazine vapors and a color comparison card to determine airborne concentrations. Seeking ideas for improvement, the NASA Tournament Lab (NTL) crowdsourced a way to tackle the challenge of detecting hydrazine and MMH vapors using colorimetric detection methods. This Rid the Rocket competition drew over 200 participants and 20 submissions from around the world proposing innovative ways to develop a new chemical colorimetric detection method for hydrazine and MMH vapors on spacecraft. Using a phased approach to evaluate contestants, NASA eventually narrowed the field to five finalists from the United States, Romania, Taiwan, and India. Concept papers and hardware submissions were judged on feasibility, creativity, and ability to detect hydrazine and MMH vapors before being sent to the NASA White Sands Test Facility for laboratory evaluation. Finalists employed variations of sampling methods and color-detection chemistry using a variety of sampling pumps and indicator pads or solutions—including those employing potassium or hydrogen tetrachloroaurate, para -dimethylaminobenzaldehyde (PDAB), and modifiers including sodium metasilicate and cetyltrimethylammonium bromide—to enhance gold nanoparticle formation and surface plasmon resonance (SPR) resulting in visual blue to purple color development. This paper presents a summary of the crowdsourced submissions and results of laboratory testing.

Crowd-Sourced↗
NASA NTRS2020

Non-linear Least Square Fitting Technique for the Determination of Field Line Resonance Frequency in Ground Magnetometer Data: Application to Remote Sensing of Plasmaspheric Mass Density

The accurate determination of the Field Line Resonance (FLR) frequency of a resonating geomagnetic field line is necessary to remotely monitor the plasmaspheric mass density during geomagnetic storms and quiet times alike. Under certain assumptions the plasmaspheric mass density at the equator is inversely proportional to the square of the FLR frequency. The most common techniques to determine the FLR frequency from ground magnetometer measurements are the amplitude ratio and phase difference techniques, both based on geomagnetic field observations at two latitudinally separated ground stations along the same magnetic meridian. Previously developed automated techniques have used statistical methods to pinpoint the FLR frequency using the amplitude ratio and phase difference calculations. We now introduce a physics-based automated technique, using non-linear least square fitting of the ground magnetometer data to the analytical resonant wave equations, that reproduces the wave characteristics on the ground, and from those determine the FLR frequency. One of the advantages of the new technique is the estimation of physics-based errors of the FLR frequency, and as a result of the equatorial plasmaspheric mass density. We present analytical results of the new technique, and test it using data from the Inner-Magnetospheric Array for Geospace Science (iMAGS) ground magnetometer chain along the coast of Chile and the east coast of the United States. We compare the results with the results of previously published statistical automated techniques.

A. Boudouridis↗
DOE OSTI2025

An eigenvalue-based method for computing the relaxed pressure in compressible multiphase flow with N phases

The modeling of compressible multiphase flows is a decades-old area of study with many applications across various fields. Many of these application areas use stiff pressure relaxation. This process involves the solution of a nonlinear system with N + 1 equations and N + 1 unknowns, where N is the number of phases. The resolution of this system with general equations of state (EOSs) is difficult. Furthermore, nonlinear systems can admit multiple solutions, and current solution methods do not address this possibility. Very recently, a thermodynamic relaxation method was introduced, which effectively maps a relatively simple predictor equation of state onto a more complex target equation of state. In this context, the target EOSs are the chosen EOSs for the thermodynamic model. Furthermore, this thermodynamic relaxation has the benefit of simplifying the stiff pressure relaxation system of equations. In this article, we show this system reduces to a polynomial of degree N, which can be recast as an eigenvalue problem through the use of the associated companion matrix. We show that although this eigenvalue method is generally less efficient than Newton–Raphson iteration, it does not suffer from convergence issues and finds all N roots of the polynomial. Hence, the method provides a fail-safe for root-finding iterative methods and a way to address the issue of multiple solutions to the nonlinear system of equations in stiff pressure relaxation.

Eigenvalue algorithm↗
DOE OSTI2026

Enhanced coercivity in Fe5C2/SiO2 core/shell nanocrystals

Rod-shaped Fe5C2 and core/shell Fe5C2/SiO2 nanocrystals were synthesized via a solution-based chemical method. Structural analysis confirmed the monoclinic phase of Fe5C2 with space group C2/c. Zero-field-cooling (ZFC) and field-cooling (FC) magnetization curves revealed distinct magnetic behaviors: uncoated Fe5C2 exhibited a low-temperature FC plateau indicative of strong dipolar interactions, while Fe5C2/SiO2 showed a monotonic increase in FC magnetization, suggesting reduced dipolar interactions due to SiO2 surface passivation. Isothermal remanent magnetization (IRM) and DC demagnetization (DCD) measurements supported this trend, with δM plots confirming weaker dipolar interactions in the coated sample. Bloch’s law fitting of temperature-dependent saturation magnetization showed a smaller Bloch’s constant for pure Fe5C2 and a larger value for Fe5C2/SiO2, reflecting enhanced surface disorder and reduced exchange coupling in the latter. Notably, Fe5C2/SiO2 demonstrated increased coercivity, attributed to decreased dipolar interaction and elevated surface anisotropy. Kneller’s law fitting yielded higher blocking temperatures for Fe5C2 (476 K) than Fe5C2/SiO2 (456 K), highlighting the impact of dipolar interactions on magnetic relaxation. These findings illustrate how SiO2 coatings effectively modulate dipolar interactions and enhance coercivity in Fe5C2 nanocrystals.

Joshi, Pramanand [Department of Physics, Universit↗
NASA NTRS2006

Uplink Array Calibration via Far-Field Power Maximization

Uplink antenna arrays have the potential to greatly increase the Deep Space Network s high-data-rate uplink capabilities as well as useful range, and to provide additional uplink signal power during critical spacecraft emergencies. While techniques for calibrating an array of receive antennas have been addressed previously, proven concepts for uplink array calibration have yet to be demonstrated. This article describes a method of utilizing the Moon as a natural far-field reflector for calibrating a phased array of uplink antennas. Using this calibration technique, the radio frequency carriers transmitted by each antenna of the array are optimally phased to ensure that the uplink power received by the spacecraft is maximized.

Vilnrotter, V.↗
NASA NTRS2003

The Statistical Mechanics of Ideal MHD Turbulence

Turbulence is a universal, nonlinear phenomenon found in all energetic fluid and plasma motion. In particular. understanding magneto hydrodynamic (MHD) turbulence and incorporating its effects in the computation and prediction of the flow of ionized gases in space, for example, are great challenges that must be met if such computations and predictions are to be meaningful. Although a general solution to the "problem of turbulence" does not exist in closed form, numerical integrations allow us to explore the phase space of solutions for both ideal and dissipative flows. For homogeneous, incompressible turbulence, Fourier methods are appropriate, and phase space is defined by the Fourier coefficients of the physical fields. In the case of ideal MHD flows, a fairly robust statistical mechanics has been developed, in which the symmetry and ergodic properties of phase space is understood. A discussion of these properties will illuminate our principal discovery: Coherent structure and randomness co-exist in ideal MHD turbulence. For dissipative flows, as opposed to ideal flows, progress beyond the dimensional analysis of Kolmogorov has been difficult. Here, some possible future directions that draw on the ideal results will also be discussed. Our conclusion will be that while ideal turbulence is now well understood, real turbulence still presents great challenges.

Shebalin, John V.↗
NASA NTRS2001

Multifunctional Collaborative Modeling and Analysis Methods in Engineering Science

Engineers are challenged to produce better designs in less time and for less cost. Hence, to investigate novel and revolutionary design concepts, accurate, high-fidelity results must be assimilated rapidly into the design, analysis, and simulation process. This assimilation should consider diverse mathematical modeling and multi-discipline interactions necessitated by concepts exploiting advanced materials and structures. Integrated high-fidelity methods with diverse engineering applications provide the enabling technologies to assimilate these high-fidelity, multi-disciplinary results rapidly at an early stage in the design. These integrated methods must be multifunctional, collaborative, and applicable to the general field of engineering science and mechanics. Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple-method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized. The multifunctional methodology presented provides an effective mechanism by which domains with diverse idealizations are interfaced. This capability rapidly provides the high-fidelity results needed in the early design phase. Moreover, the capability is applicable to the general field of engineering science and mechanics. Hence, it provides a collaborative capability that accounts for interactions among engineering analysis methods.

Ransom, Jonathan B.↗
DOE OSTI2025

Large-𝑁 SU(4) Schwinger boson theory for coupled-dimer antiferromagnets

Here, we develop a systematic large-𝑁 expansion based on the Schwinger boson representation of SU(4) coherent states of dimers for the paradigmatic spin-1/2 bilayer square lattice Heisenberg antiferromagnet. This system exhibits a quantum phase transition between a quantum paramagnetic state and a Néel order state, driven by the coupling constant 𝑔 = 𝐽′/𝐽, which is defined as the ratio between the interdimer 𝐽′ and intradimer 𝐽 exchange interactions. We demonstrate that this approach accurately describes static and dynamic properties on both sides of the quantum phase transition. The critical coupling constant 𝑔 𝑐 ≈ 0.42 and the dynamic spin structure factor reproduce quantum Monte Carlo results with high precision. Notably, the 1/𝑁 corrections reveal the longitudinal mode of the magnetically ordered phase along with the overdamping caused by its decay into the two-magnon continuum. The present large-𝑁 SU(4) Schwinger boson theory can be extended to more general cases of quantum paramagnets that undergo a quantum phase transition into magnetically ordered states.

Schwinger boson method↗
DOE OSTI2026

Bootstrap embedding for interacting electrons in phonon coherent-state mean field

Here, we develop a Fermi–Bose bootstrap embedding framework for the ground state of interacting electrons coupled to a phonon mean field. The method combines bootstrap embedding for correlated electrons with a self-consistent coherent-state mean-field treatment for phonons. This method models the interacting electron–phonon problem as a system of correlated electrons traveling in a self-consistently specified potential landscape, allowing for efficient treatment of large lattice systems. Convergence of the methods for fragment size and total system size is demonstrated for the one-dimensional Hubbard–Holstein model for up to 350 sites. Finite-size scaling is performed to extrapolate to the infinite system size. Benchmarking against the density matrix renormalization group for a small 8-site system at half- and quarter-filling shows an orders-of-magnitude runtime advantage. The comparison further reveals that the method performs best in regimes dominated by localization, such as the Mott insulating phase and the strong-coupling tiny polaron regime, where the local embedding ansatz is still valid. However, due to the mean-field treatment for phonons, we find limitations of our methods in the weakly coupled delocalized region and at the Peierls transition, where quantum phonon fluctuations and long-range kinetic correlations become substantial.

Islam, Shariful [North Carolina State University, ↗
DOE OSTI2026

Causality-respecting adaptive refinement for PINNs: enabling precise interface evolution in phase field modeling

Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving physical systems described by partial differential equations (PDEs). However, their accuracy in dynamical systems, particularly those involving sharp moving boundaries with complex initial morphologies, remains a challenge. Here, this study introduces an approach combining residual-based adaptive refinement (RBAR) with causality-informed training to enhance the performance of PINNs in solving spatio-temporal PDEs. Our method employs a three-step iterative process: initial causality-based training, RBAR-guided domain refinement, and subsequent causality training on the refined mesh. Applied to the Allen-Cahn equation, a widely-used model in phase field simulations, our approach demonstrates significant improvements in solution accuracy and computational efficiency over traditional PINNs. Notably, we observe an ‘overshoot and relocate’ phenomenon in dynamic cases with complex morphologies, showcasing the method’s adaptive error correction capabilities. This synergistic interaction between RBAR and causality training enables accurate capture of interface evolution, even in challenging scenarios where traditional PINNs fail. Our framework not only resolves the limitations of uniform refinement strategies but also provides a generalizable methodology for solving a broad range of spatio-temporal PDEs. The enhanced performance of the RBAR–causality combined framework demonstrates its strong potential for advancing PINN-based modeling of physical systems characterized by complex, evolving interfaces.

Allen-Cahn equations↗
NASA NTRS2002

The International Intercomparison of 3-Dimensional Radiation Codes

I3RC (International Intercomparison of 3-dimensional Radiation Codes) has as its primary goal to compare a wide variety of three-dimensional (3D) radiative transfer methods applied to Earth's atmosphere, with a few selected cloud fields as input, and a few selected radiative quantities as output. Phases 1 and 2 are now complete, and participants represented institutions in Canada, France, Germany, Russia, the United Kingdom, and the USA, who met for two workshops in Tucson, Arizona USA, and compared results from 5 cloud fields of varying complexity, beginning with simplified atmosphere and surface, and proceeding to more realistic cases. Phase 3 is now underway, focusing on improvement and sharing of 3D radiation code, aided by working groups on "Approximations" and "Open Source". The "Approximations" group has so far focused on diffusive approximate methods in an attempt to gain advantages in execution time, and also to advance the understanding of 3D radiation processes. The "Open Source" subgroup is developing a Monte Carlo radiative transfer toolkit that makes state-of-the-art techniques available to a wide range of users. Activities of both subgroups are further explained at the I3RC website http://i3rc.gsfc.nasa.gov. Participants in 13RC are forming a 3D Working Group under the auspices of the International Radiation Commission, and will meet for this and related activities at a workshop in Tucson in November 2002.

Cahalan, R. F.↗