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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.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Discrete Wavelength-Locked External Cavity Laser

A prototype improved external cavity laser (ECL) was demonstrated in the second phase of a continuing effort to develop wavelength-agile lasers for fiber-optic communications and trace-gas-sensing applications. This laser is designed to offer next-generation performance for incorporation into fiber-optic networks. By eliminating several optical components and simplifying others used in prior designs, the design of this laser reduces costs, making lasers of this type very competitive in a price-sensitive market. Diode lasers have become enabling devices for fiber optic networks because of their cost, compactness, and spectral properties. ECLs built around diode laser gain elements further enhance capabilities by virtue of their excellent spectral properties with significantly increased (relative to prior lasers) wavelength tuning ranges. It is essential to exploit the increased spectral coverage of ECLs while simultaneously insuring that they operate only at precisely defined communication channels (wavelengths). Heretofore, this requirement has typically been satisfied through incorporation of add-in optical components that lock the ECL output wavelengths to these specific channels. Such add-in components contribute substantially to the costs of ECL lasers to be used as sources for optical communication networks. Furthermore, the optical alignment of these components, needed to attain the required wavelength precision, is a non-trivial task and can contribute substantially to production costs. The design of the present improved ECL differs significantly from the designs of prior ECLs. The present design relies on inherent features of components already included within an ECL, with slight modifications so that these components perform their normal functions while simultaneously effecting locking to the required discrete wavelengths. Hence, add-in optical components and the associated cost of alignment can be eliminated. The figure shows the locking feedback signal, and the frequency locking achieved by use of this signal, as a mirror is tilted through a range of angles to tune the ECL through 48 channels. The data for the frequency plot were obtained, simultaneously with the data for the locking-signal plot, by using a scanning Michelson interferometer to precisely determine the ECL wavelength (and, hence, frequency). Given the ability of the Michelson interferometer to obtain highly precise readings, the frequency plot can be taken to be a reliable indication of single-mode operation. The discontinuities in the frequency plot signify the switching of the ECL between channels; in other words, they indicate tuning with locking to discrete frequencies. The peaks of the feedbacklocking signal correspond to the centers, or near centers, of the mirror angle scan through the corresponding channels. Thus, it is clear that when the feedback-locking signal is at a local maximum, the ECL is operating at single frequency at or near the middle frequency of the selected channel. This is all that is required for precisely locking the ECL output wavelength. The locking is achieved without additional external optical components.

Pilgrim, Jeffrey S.↗
NASA NTRS1983

v-representability and density functional theory

It is shown that if n(r) is the discrete density on a lattice (enclosed in a finite box) associated with a nondegenerate ground state in an external potential v(r) (i.e., is 'v-representable'), then the density n(r) + mu(r), with m(r) arbitrary (apart from trivial constraints) and mu small enough, is also associated with a nondegenerate ground state in an external potential v'(r) near v(r); i.e., n(r) + m(r) is also v-representable. Implications for the Hohenberg-Kohn variational principle and the Kohn-Sham equations are discussed.

Kohn, W.↗
NASA NTRS2008

Discrete Gust Model for Launch Vehicle Assessments

Analysis of spacecraft vehicle responses to atmospheric wind gusts during flight is important in the establishment of vehicle design structural requirements and operational capability. Typically, wind gust models can be either a spectral type determined by a random process having a wide range of wavelengths, or a discrete type having a single gust of predetermined magnitude and shape. Classical discrete models used by NASA during the Apollo and Space Shuttle Programs included a 9 m/sec quasi-square-wave gust with variable wavelength from 60 to 300 m. A later study derived discrete gust from a military specification (MIL-SPEC) document that used a "1-cosine" shape. The MIL-SPEC document contains a curve of non-dimensional gust magnitude as a function of non-dimensional gust half-wavelength based on the Dryden spectral model, but fails to list the equation necessary to reproduce the curve. Therefore, previous studies could only estimate a value of gust magnitude from the curve, or attempt to fit a function to it. This paper presents the development of the MIL-SPEC curve, and provides the necessary information to calculate discrete gust magnitudes as a function of both gust half-wavelength and the desired probability level of exceeding a specified gust magnitude.

Leahy, Frank B.↗
NASA NTRS1979

Multi-level adaptive finite element methods. 1: Variation problems

A general numerical strategy for solving partial differential equations and other functional problems by cycling between coarser and finer levels of discretization is described. Optimal discretization schemes are provided together with very fast general solvers. It is described in terms of finite element discretizations of general nonlinear minimization problems. The basic processes (relaxation sweeps, fine-grid-to-coarse-grid transfers of residuals, coarse-to-fine interpolations of corrections) are directly and naturally determined by the objective functional and the sequence of approximation spaces. The natural processes, however, are not always optimal. Concrete examples are given and some new techniques are reviewed. Including the local truncation extrapolation and a multilevel procedure for inexpensively solving chains of many boundary value problems, such as those arising in the solution of time-dependent problems.

Brandt, A.↗
NASA NTRS1998

Aircraft/Air Traffic Management Functional Analysis Model: User's Guide - Version 2.0

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) a National Aeronautics and Space Administration (NASA) contract. This document provides a guide for using the model in analysis. Those interested in making enhancements or modification to the model should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Technical Description.

Etheridge, Melvin↗
DOE OSTI2026

Neural entropy-stable conservative flux form neural networks for learning hyperbolic conservation laws

We propose a neural entropy-stable conservative flux form neural network (NESCFN) for learning hyperbolic conservation laws and their associated entropy functions directly from solution trajectories, without requiring any predefined numerical discretization. While recent neural network architectures have successfully integrated classical numerical principles into learned models, most rely on prior knowledge of the governing equations or assume a fixed discretization. Our approach removes this dependency by embedding entropy-stable design principles into the learning process itself, enabling the discovery of physically consistent dynamics in a fully data-driven setting. By jointly learning both the flux function and a corresponding entropy, NESCFN promotes conservation and entropy dissipation, which is critical for long-term stability and fidelity in the system of hyperbolic conservation laws. Furthermore, numerical results demonstrate that the method achieves stability and conservation over extended time horizons and accurately captures shock propagation speeds, even without oracle access to future-time solution profiles in the training data.

Conservative flux form↗
NASA NTRSDate not supplied

Development of Buffet Forcing Functions Using Frequency-Dependent Coherence Factors

The current accepted approach to modeling launch vehicle transonic buffet environments is to acquire time-correlated unsteady pressure measurements at discrete locations on a model-scale wind-tunnel model and use these measurements to develop buffet forcing functions (BFFs).Part of the BFF development process is the application of coherence factors to account for the discrete nature of the pressure measurement used in the development of the BFFs. Presently, the Space Launch System (SLS) program divides the launch vehicle into distinct aerodynamic regions, within which, the coherence lengths are assumed to be constant. The coherence factors are computed by averaging the coherence function between sensors within the region over a specified frequency range. The present work validates and examines the impact of two proposed changes to the development of longitudinal coherence factors used in the development of launch vehicle BFFs. One change is to employ frequency-dependent coherence factors instead of coherence factors based on the mean of the coherence function. The second proposed change replaces the aerodynamic regions with a moving-segment approach that varies the calculated coherence lengths as a function of longitudinal location of the transducers. The impact of these approaches is examined using data from two rigid buffet model wind-tunnel tests: (1)a notional launch vehicle geometry through the comparison of discrete measurement-basedBFFs to loads developed by continuous integration of unsteady pressure sensitive paint data and (2) the SLS Block 1 Cargo vehicle configuration for which BFFs have been previously developed using less-mature methods. The trends from this examination of updated coherence factor approaches ultimately result in more intuitive results than currently-accepted coherence methods.

buffet, unsteady aerodynamics, launch vehicle, win↗
NASA NTRSDate not supplied

Development of Buffet Forcing Functions Using Frequency-Dependent Coherence Factors

The current accepted approach to modeling launch vehicle transonic buffet environments is to acquire time-correlated unsteady pressure measurements at discrete locations on a model-scale wind-tunnel model and use these measurements to develop buffet forcing functions (BFFs). Part of the BFF development process is the application of coherence factors to account for the discrete nature of the pressure measurement used in the development of the BFFs. Presently, the Space Launch System (SLS) program divides the launch vehicle into distinct aerodynamic regions, within which, the coherence lengths are assumed to be constant. The coherence factors are computed by averaging the coherence function between sensors within the region over a specified frequency range. The present work validates and examines the impact of two proposed changes to the development of longitudinal coherence factors used in the development of launch vehicle BFFs. One change is to employ frequency-dependent coherence factors instead of coherence factors based on the mean of the coherence function. The second proposed change replaces the aerodynamic regions with a moving-segment approach that varies the calculated coherence lengths as a function of longitudinal location of the transducers. The impact of these approaches is examined using data from two rigid buffet model wind-tunnel tests: (1) a notional launch vehicle geometry through the comparison of discrete measurement-based BFFs to loads developed by continuous integration of unsteady pressure sensitive paint data and (2) the SLS Block 1 Cargo vehicle configuration for which BFFs have been previously developed using less-mature methods. The trends from this examination of updated coherence factor approaches ultimately result in more intuitive results than currently-accepted coherence methods.

buffet↗
NASA NTRS1987

Some numerical calculations by using linear classical sonic theories approached from sub- or supersonic speeds

The unsteady aerodynamics of a two-dimensional wing at sonic speed are studied by using so-called classical sonic theories (linear), approached from supersonic flow (M=1+0) or subsonic flow (M=1-0). In the former approach, the exact expressions of lift and lift distribution are obtained in terms of Fresnel integrals, while in the latter approach an integral equation must be solved, the kernel function of which is obtained from the subsonic Possio's equation and has a root singularity. The discrete analysis is adopted on the basis of the semicircle method (SCM) and the weighting function for subsonic-flow-Gauss-quadrature, as well as modified characteristics obtained from both approaches agree quite well with each other. The results obtained by the present computations are compared with those of DLM-C (subsonic 2D code) developed by ANDO et al, and are found to give a reasonable outer boundary for subsonic unsteady aerodynamics.

Yamamoto, Y.↗
DOE OSTI2026

A robust framework for frictional fault contact in geological formations using a stabilized augmented Lagrangian approach

Numerical simulations are essential to evaluate the performance and safety of engineered subsurface systems such as geological carbon storage sites, enhanced geothermal fields, and oil and gas reservoirs. A key challenge lies in accurately modeling the frictional contact behavior along fault surfaces. This problem involves inequality constraints that arise from the physics of frictional slip, requiring specialized numerical methods to handle the resulting highly nonlinear and path-dependent behavior. Here, in this work, we address this challenge using an Augmented Lagrangian Method (ALM) implemented via the Uzawa algorithm. The formulation employs mixed finite element spaces, combining low-order piecewise linear displacements within the 3D domain cells with piecewise constant tractions defined on the fault surfaces. Furthermore, to ensure stability and satisfy the inf-sup condition, the discrete displacement space is enriched with face bubble functions on both sides of the contact interfaces. This approach offers several advantages over other stabilization techniques that rely on additional terms, and it integrates naturally in the Uzawa framework.

58 GEOSCIENCES↗
DOE OSTI2024

Targeted materials discovery using Bayesian algorithm execution

Rapid discovery and synthesis of future materials requires intelligent data acquisition strategies to navigate large design spaces. A popular strategy is Bayesian optimization, which aims to find candidates that maximize material properties; however, materials design often requires finding specific subsets of the design space which meet more complex or specialized goals. We present a framework that captures experimental goals through straightforward user-defined filtering algorithms. These algorithms are automatically translated into one of three intelligent, parameter-free, sequential data collection strategies (SwitchBAX, InfoBAX, and MeanBAX), bypassing the time-consuming and difficult process of task-specific acquisition function design. Our framework is tailored for typical discrete search spaces involving multiple measured physical properties and short time-horizon decision making. We demonstrate this approach on datasets for TiO 2 nanoparticle synthesis and magnetic materials characterization, and show that our methods are significantly more efficient than state-of-the-art approaches. Overall, our framework provides a practical solution for navigating the complexities of materials design, and helps lay groundwork for the accelerated development of advanced materials.

42 ENGINEERING↗
DOE OSTI2026

Predicting the dark matter-baryon abundance ratio

We discuss relaxation solutions to the dark matter-baryon coincidence problem in the context of QCD axion dark matter. In relaxation solutions, a moduli dynamically adjusts the mass of dark matter and baryons until their energy densities are 𝒪⁡(1) the same. Because the QCD axion is heavily connected to QCD, scanning the QCD axion mass inherently also scans the proton mass. In the context of relaxation solutions, this implies that the ratio of dark matter to baryon abundances (Ω DM /Ω B ) is a ratio of beta functions showing that these models can only accommodate discrete values of ΩDM/ΩB thereby “predicting” the ratio of the dark matter to baryon abundances. The original composite axion model has only a single integer degree of freedom 𝑁, the size of the gauge group, and we show that when 𝑁 =8 the observed value of Ω DM /Ω B =5.36 is reproduced to within its percent level error bars. Novel tests of this model include more precise measurements of Ω DM /Ω B , a better lattice determination of the dependence of the proton mass on the high energy QCD gauge coupling, as well as more traditional tests such as fifth force experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Moment extraction using an unfolding protocol without binning

Deconvolving (“unfolding”) detector distortions is a critical step in the comparison of cross-section measurements with theoretical predictions in particle and nuclear physics. However, most existing approaches require histogram binning while many theoretical predictions are at the level of statistical moments. We develop a new approach to directly unfold distribution moments as a function of another observable without having to first discretize the data. Our moment unfolding technique uses machine learning and is inspired by Boltzmann weight factors and generative adversarial networks (GANs). We demonstrate the performance of this approach using jet substructure measurements in collider physics. With this illustrative example, we find that our moment unfolding protocol is more precise than bin-based approaches and is as or more precise than completely unbinned methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Lattice QCD Benchmark of Proton Helicity and Flavor-Dependent Unpolarized Transverse Momentum-Dependent Parton Distribution Functions at Physical Quark Masses

We present the first lattice QCD calculations of the isovector helicity transverse momentum-dependent parton distribution function (TMDPDF) and the flavor-dependent unpolarized TMDPDFs for up and down quarks in the proton. Our computations utilize domain-wall fermion discretization with physical quark masses. Employing Coulomb-gauge-fixed quark correlation functions within the large-momentum effective theory framework, we access nonperturbative transverse quark separations 𝑏 𝑇 up to approximately 1 fm, corresponding to transverse momenta as low as 200 MeV. Based on the quasi-TMD factorization theorem, we construct renormalization-group–invariant ratios that are equal to the corresponding light-cone TMDPDF ratios. At moderate 𝑥, our results reveal that the isovector helicity and unpolarized TMDPDFs exhibit nearly identical transverse structure up to a normalization factor, and the unpolarized distributions display only mild flavor dependence. These findings not only support key trends observed in recent global analyses but also provide robust, nonperturbative constraints that can distinguish between different parameterizations. This Letter establishes a first-principles benchmark for TMDPDFs, offering valuable input for ongoing and future experimental efforts to map the proton’s three-dimensional structure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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↗
DOE OSTI2024

Development and Experimental Optimization of High-Temperature Modeling Tools and Methods for Concentrated Solar Power Particle - Systems

A novel, open-source radiative modeling toolset was developed to extend the functionality of particle-based modeling software (e.g. discrete element method (DEM)) to environmental conditions relevant to concentrated solar power applications. This toolset was optimized for deployment on desktop workstations instead of high-performance computing systems, to render such tools more accessible to the research community. Both particle-based modeling and radiative exchange modeling are computationally expensive and often require specialized programming expertise, making these methods cumbersome to use. Recent developments in DEM software by DCS Computing have greatly reduced these challenges, providing a graphical-user-interface based platform and modeling optimization for desktop workstations, HPCs, and cloud computing. The University of Dayton leveraged the experience of DCS Computing in developing a user-friendly, open-source radiative heat transfer expansion for DEM modeling. The University of Dayton DEM+ radiative modeling toolset was developed using a combination of fundamental experimental measurements, modeling, and simplified flow experiments over a range of temperatures and flow conditions. The toolset provides researchers with access to multiple radiative models including an accelerated Monte-Carlo Ray Tracing (application agnostic, highly computationally expensive), an expanded database of distance-based approximations (application limited, computationally light), and a weighted blending of the two methods capable of achieving over 90% reduction in computation time with equivalent accuracy compared to Monte-Carlo Ray Tracing. Through a graphical user interface, users can customize the radiative models to match their desired accuracy and available computational resources, improving access to particle based modeling for the research community. Ceramic sintered bauxite proppants were used in modeling and experimentally as a baseline. Both the radiative heat transfer and flow properties for particulate systems were investigated at elevated temperatures up to 800 °C. The major accomplishments for this work include a verified, open-source radiative modeling toolset to be distributed amongst the research community and the fabrication of three small-scale test facilities to investigate particle behavior and tune DEM flow properties for operation up to 800 °C. The findings have been shared with the research community via conference modeling workshops, deployment of the tools in DCS Computing Aspherix®, and open-source access to the developed radiative modeling tool. The development of next-generation CSP facilities and thermal energy storage systems based on ceramic particles requires providing access to computationally efficient and accurate modeling tools. Particles will experience a wide range of environments (20-800 °C) and handling conditions (dilute curtains or dense packing), requiring specially designed and optimized equipment. Optimizing solid particle physics models and establishing best-practices for particle modeling in CSP environments will assist researchers with designing optimized equipment, accelerating the deployment of more economically-competitive CSP facilities.

14 SOLAR ENERGY↗