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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Gradient-based constrained optimization using a database of linear reduced-order models

A methodology grounded in model reduction is presented for accelerating the gradient-based solution of a family of linear or nonlinear constrained optimization problems where the constraints include at least one linear Partial Differential Equation (PDE). A key component of this methodology is the construction, during an offline phase, of a database of pointwise, linear, Projection-based Reduced-Order Models (PROM)s associated with a design parameter space and the linear PDE(s). A parameter sampling procedure based on an appropriate saturation assumption is proposed to maximize the efficiency of such a database of PROMs. A real-time method is also presented for interpolating at any queried but unsampled parameter vector in the design parameter space the relevant sensitivities of a PROM. The practical feasibility, computational advantages, and performance of the proposed methodology are demonstrated for several realistic, nonlinear, aerodynamic shape optimization problems governed by linear aeroelastic constraints.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Uncertainty Estimates for Fitting Zernike Polynomials to Discrete Data

Zernike polynomials are a widely used metric in modern optical analysis. They conveniently represent surfaces as a series of weighted terms corresponding to various optical aberrations. Ideally, each term is independent of others in the series, but Zernike polynomials lose this property when working with sets of discrete data. This gives rise to uncertainty in each polynomial’s actual contribution and affects metrology and simulation estimates of their relative weights. Several factors influencing these estimates are the number and arrangement of sample locations, the method for calculating the weights, and the total number of Zernike terms used in the calculation. Discussed is the uncertainty associated with linear regression using random sampling. Other topics reviewed are complex Zernike polynomials and vector spaces of functions.

Zernike Polynomials↗
DOE OSTI2022

Nucleon-pair truncation of the shell model for medium-heavy nuclei

Background: Establishing computationally tractable models of atomic nuclei is a long-time goal of nuclear structure physics. A flexible framework which easily includes excited states and many-body correlations is the configuration-interaction shell model (SM), but the exponential growth of the basis means one needs an efficient truncation scheme, ideally one that includes both deformation and pairing correlations. Purpose: Here, we propose an efficient truncation scheme of the SM: starting from a pair condensate variationally defined by Hartree-Fock single-particle states and the particle-number conserved Bardeen-Cooper-Schrieffer (NBCS) approximation, we carry out projection of states with good angular momentum. Methods: After generating Hartree-Fock single-particle states with Kramers degeneracy in a SM space, we optimize the pair amplitudes in the NBCS by minimizing the energy, and then use linear algebra projection (LAP) of states with good angular momentum. Both NBCS and LAP are computationally fast. Results: Our calculations yield good agreement with full configuration-interaction SM calculations for low-lying states of transitional and rotational nuclei with axially symmetric and triaxial deformation in medium- and heavy-mass regions: 44,46,48 Ti, 48,50 Cr, 52 Fe, 60,62,64 Zn, 66,68 Ge, 68 Se, and 108,110 Xe. We predict low-lying states of 112–114 Ba and 116–120 Ce, nuclei difficult to reach by large-scale SM calculations. Conclusions: Both pair correlation and the configuration mixing between different intrinsic states play a key role in reproducing collectivity and shape coexistence, demonstrating the utility of this truncation scheme of the SM to study transitional and deformed nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Manifold projection image segmentation for nano-XANES imaging

As spectral imaging techniques are becoming more prominent in science, advanced image segmentation algorithms are required to identify appropriate domains in these images. We present a version of image segmentation called manifold projection image segmentation (MPIS) that is generally applicable to a broad range of systems without the need for training because MPIS uses unsupervised machine learning with a few physically motivated hyperparameters. We apply MPIS to nanoscale x-ray absorption near edge structure (XANES) imaging, where XANES spectra are collected with nanometer spatial resolution. We show the superiority of manifold projection over linear transformations, such as the commonly used principal component analysis (PCA). Moreover, MPIS maintains accuracy while reducing computation time and sensitivity to noise compared to the standard nano-XANES imaging analysis procedure. Finally, we demonstrate how multimodal information, such as x-ray fluorescence data and spatial location of pixels, can be incorporated into the MPIS framework. We propose that MPIS is adaptable for any spectral imaging technique, including scanning transmission x-ray microscopy, where the length scale of domains is larger than the resolution of the experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Theory-Guided Autoencoders

Data assimilation is a Bayesian inference process that obtains an enhanced understanding of a physical system of interest by fusing information from an inexact physics-based model, and from noisy sparse observations of reality. The multifidelity ensemble Kalman filter (MFEnKF) recently developed by the authors combines a full-order physical model and a hierarchy of reduced order surrogate models in order to increase the computational efficiency of data assimilation. The standard MFEnKF uses linear couplings between models, and is statistically optimal in case of Gaussian probability densities. This work extends the MFEnKF into to make use of a broader class of surrogate model such as those based on machine learning methods such as autoencoders non-linear couplings in between the model hierarchies. We identify the right-invertibility property for autoencoders as being a key predictor of success in the forecasting power of autoencoder-based reduced order models. We propose a methodology that allows us to construct reduced order surrogate models that are more accurate than the ones obtained via conventional linear methods. Numerical experiments with the canonical Lorenz'96 model illustrate that nonlinear surrogates perform better than linear projection-based ones in the context of multifidelity ensemble Kalman filtering. We additionality show a large-scale proof-of-concept result with the quasi-geostrophic equations, showing the competitiveness of the method with a traditional reduced order model-based MFEnKF.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

WISE J233237.05-505643.5: A Double-Peaked Broad-Lined AGN with Spiral-Shaped Radio Morphology

We present radio continuum mapping, optical imaging and spectroscopy of the newly discovered double-peaked broad-lined AGN WISE J233237.05-505643.5 at redshift z = 0.3447. This source exhibits an FR-I and FR-II hybrid-morphology, characterized by bright core, jet, and Doppler-boosted lobe structures in ATCA continuum maps at 1.5, 5.6, and 9 GHz. Unlike most FR-II objects, W2332-5056 is hosted by a disk-like galaxy. The core has a projected 5" linear radio feature that is perpendicular to the curved primary jet, hinting at unusual and complex activity within the inner 25 kpc. The multi-epoch optical-near-IR photometric measurements indicate significant variability over a 3-20 year baseline from the AGN component. Gemini-South optical data shows an unusual double-peaked emission-line features: the centroids of the broad-lined components of H-alpha and H-beta are blueshifted with respect to the narrow lines and host galaxy by approximately 3800 km/s. We examine possible cases which involve single or double supermassive black holes in the system, and discuss required future investigations to disentangle the mystery nature of this system.

galaxies: individual↗
DOE OSTI2020

Long-Term Corrosion Studies Of Pine Derived Bio-Oil And Blends With Heavy Fuel Oil

Biomass derived liquid fuels offer a means to reduce greenhouse gas emissions compared to those produced by combustion of petroleum derived liquid fuels. However, the corrosivity of bio-oils toward the less expensive structural materials creates a material selection problem for designers of storage tanks and combustion systems. Samples of candidate structural materials are being exposed for thousands of hours in multiple fast pyrolysis bio-oils and conditions to evaluate the corrosion resistance of these materials. One method to mitigate the corrosivity of bio-oils and speed their adoption, while also decreasing the pollution issues associated with low quality petroleum derived fuels, is to utilize blends of bio-oil and heavy fuel oil in engines currently solely burning a petroleum-based fuel. In addition to the corrosion studies conducted in 100% bio-oil, studies were also conducted with blends of the fast pyrolysis bio-oil produced from pine tree components with a heavy fuel oil that is used in ocean-going ships. This bio-oil had a very high carboxylic acid content which made it very corrosive to carbon and 2¼ Cr-1 Mo steel and even 409 stainless steel. The heavy fuel oil was not corrosive to carbon steel, but its sulfur content makes it a significant pollution producer and particularly undesirable for use near coastlines. Corrosion tests were conducted with the individual components and with various blends of the two liquid fuels. Studies showed a significantly lower corrosivity of the blends than would be projected assuming linear mixing behavior. Adoption of such blends holds the potential to reduce production of sulfur-containing exhaust gases as well as carbon dioxide from non-renewable fuels.

Keiser, Jim↗
DOE OSTI2020

Long-Term Corrosion Studies of Pine Derived Bio-Oil and Blends with Heavy Fuel Oil

Biomass derived liquid fuels offer a means to reduce greenhouse gas emissions compared to those produced by combustion of petroleum derived liquid fuels. However, the corrosivity of bio-oils toward the less expensive structural materials creates a material selection problem for designers of storage tanks and combustion systems. Samples of candidate structural materials are being exposed for thousands of hours in multiple fast pyrolysis bio-oils and conditions to evaluate the corrosion resistance of these materials. One method to mitigate the corrosivity of bio-oils and speed their adoption, while also decreasing the pollution issues associated with low quality petroleum derived fuels, is to utilize blends of bio-oil and heavy fuel oil in engines currently solely burning a petroleum-based fuel. In addition to the corrosion studies conducted in 100% bio-oil, studies were also conducted with blends of the fast pyrolysis bio-oil produced from pine tree components with a heavy fuel oil that is used in ocean-going ships. This bio-oil had a very high carboxylic acid content which made it very corrosive to carbon and 2¼ Cr-1 Mo steel and even 409 stainless steel. The heavy fuel oil was not corrosive to carbon steel, but its sulfur content makes it a significant pollution producer and particularly undesirable for use near coastlines. Corrosion tests were conducted with the individual components and with various blends of the two liquid fuels. Studies showed a significantly lower corrosivity of the blends than would be projected assuming linear mixing behavior. Adoption of such blends holds the potential to reduce production of sulfur-containing exhaust gases as well as carbon dioxide from non-renewable fuels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

RPI LINAC refurbishment and upgrade project

The Electron Linear Accelerator at Rensselaer Polytechnic Institute (RPI) was constructed in the late 1950s and started operation in 1961 [1]. The facility was designed and used primarily for measurements of Nuclear Data (ND) with emphasis on the resonance energy region. As such it was designed to produce short pulses of neutrons (5-5000 ns) and equipped with detection stations at different neutron flight path distances from the source (15 m-250 m). When the LINAC started operation it was one of the most powerful accelerators in the world for high energy-resolution measurements in the resonance region. The original LINAC with some upgrades is still in operation but no longer provides world class capabilities for measurements with short pulses. In 2011 discussions between the RPI ND group, Naval Reactors, and the Nuclear Criticality Safety Program about the future of the LINAC concluded that maintaining the capability to perform world-class nuclear data measurements at RPI was desirable. To that end, it was decided to refurbish the facility and upgrade the accelerator capabilities to enable high accuracy measurement in the resonance region with narrow neutron pulse and high electron beam power. Located at a major US technical university, this project provides a needed US nuclear data capability for both research and education, and also includes external users and industrial applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Status of the International Linear Collider

This paper is not a proposal for a CERN future project but provides information on the International Linear Collider (ILC) considered for Japan in order to facilitate the European Strategy discussion in a global context. It describes progress to date, ongoing engineering studies, updated cost estimate for the machine at $\sqrt{s}=250~\rm GeV$ and the situation in Japan. The physics of the ILC is not presented here, but jointly for all Linear Collider projects in a separate document ``A Linear Collider Vision for the Future of Particle Physics'' submitted for the forthcoming European Strategy deliberations.

Abe, Y. [KEK, Tsukuba]↗
DOE OSTI2025

Gluon unpolarized, polarized, and transversity GPDs from lattice QCD: Lorentz-covariant parametrization

We identify the matrix elements necessary to determine the leading-twist gluon generalized parton distributions (GPDs) H g , E g , H ˜ g , E ˜ g , H g T , E g T , H ˜ g T , E ˜ g T in lattice QCD calculations. We present a method to achieve a Lorentz-covariant parameterization of the matrix elements in terms of a linearly independent basis of tensor structures. This parameterization is crucial for projecting lattice QCD matrix elements onto light cone distributions. For the first time, we determine the corresponding components that project onto the linear combinations of invariant amplitudes, which reduce to the different gluon GPDs in the light cone limit and enable their separation in a lattice QCD calculation for spin-0 and spin- 1 2 hadrons. Hence, this work lays the foundation for the numerical determination of the gluon GPDs from first-principle lattice QCD calculations, directly advancing our understanding of the mass and spin structures and mechanical properties of the nucleon, as well as the physics underlying deeply virtual Compton scattering and deeply virtual meson production in a range of experimental processes. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2002

Waves in Turbulent Stably Stratified Shear Flow

Two approaches for the identification of internal gravity waves in sheared and unsheared homogeneous stratified turbulence are investigated. First, the phase angle between the vertical velocity and density fluctuations is considered. It was found, however, that a continuous distribution of the phase angle is present in weakly and strongly stratified flow. Second, a projection onto the solution of the linearized inviscid equations of motion of unsheared stratified flow is investigated. It was found that a solution of the fully nonlinear viscous Navier-Stokes equations can be represented by the linearized inviscid solution. The projection yields a decomposition into vertical wave modes and horizontal vortical modes.

Jacobitz, F. G.↗
NASA NTRS2002

Waves in Turbulent Stably-Stratified Shear Flow

Two approaches for the identification of internal gravity waves in sheared and unsheared homogeneous stratified turbulence are investigated. First, the phase angle between the vertical velocity and density fluctuations is considered. It is found, however, that a continuous distribution of the phase angle is present in weakly and strongly stratified flow. Second, a projection onto the solution of the linearized inviscid equations of motion of unsheared stratified flow is investigated. It is found that a solution of the fully nonlinear viscous Navier-Stokes equations can be represented by the linearized inviscid solution. The projection yields a decomposition into vertical wave modes and horizontal vortical modes.

Jacobitz, F. G.↗
NASA NTRS2012

Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing

As imagery is collected from an airborne platform, an individual viewing the images wants to know from where on the Earth the images were collected. To do this, some information about the camera needs to be known, such as its position and orientation relative to the Earth. This can be provided by common inertial navigation systems (INS). Once the location of the camera is known, it is useful to project an image onto some representation of the Earth. Due to the non-smooth terrain of the Earth (mountains, valleys, etc.), this projection is highly non-linear. Thus, to ensure accurate projection, one needs to project onto a digital elevation map (DEM). This allows one to view the images overlaid onto a representation of the Earth. A code has been developed that takes an image, a model of the camera used to acquire that image, the pose of the camera during acquisition (as provided by an INS), and a DEM, and outputs an image that has been geo-rectified. The world coordinate of the bounds of the image are provided for viewing purposes. The code finds a mapping from points on the ground (DEM) to pixels in the image. By performing this process for all points on the ground, one can "paint" the ground with the image, effectively performing a projection of the image onto the ground. In order to make this process efficient, a method was developed for finding a region of interest (ROI) on the ground to where the image will project. This code is useful in any scenario involving an aerial imaging platform that moves and rotates over time. Many other applications are possible in processing aerial and satellite imagery.

Ansar, Adnan I.↗
DOE OSTI2025

Enabling Efficient Sparse Computations using Linear Algebra Aware Compilers

This project developed the LAPIS compiler framework, built on the Multilevel Intermediate Representation (MLIR), to optimize sparse linear algebra operations and support performance portability across diverse architectures. The main innovation of LAPIS is the Kokkos dialect, which allows for lowering codes from a high productivity language to different architectures in an elegant way. The dialect also allows the conversion of lower-level MLIR code to C++ Kokkos code, facilitating the integration of scientific machine learning (SciML) models into applications. To extend LAPIS for distributed memory architectures, a new partition dialect was created to manage the distribution of sparse tensors and express communication patterns for sparse linear algebra operations. This dialect also supports the distributed execution of operators and includes algorithmic optimizations to minimize communication to improve performance. The project also demonstrates that MLIR can enable effective linear algebra-level optimizations, improving performance on different GPUs for both sparse and dense linear algebra kernels. Key applications of LAPIS include sparse linear algebra and graph kernels, TenSQL, a relational database management solution built on GraphBLAS, and the development of subgraph isomorphism and monomorphism kernels, showcasing performance portability. In summary, the LAPIS framework supports productivity, performance, portability, and distributed memory execution, while also enabling linear algebra-level optimizations that are challenging in traditional programming languages, with successful applications ranging from simple sparse linear algebra to complex graph kernels.

97 MATHEMATICS AND COMPUTING↗