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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 OSTI2025

Advanced Polymer Characterization: Modular Operations for Spectral Alignment by Iterative Compression (MOSAIC)

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry encodes structural information across diverse homo- and copolymer ensembles, yet decrypting these spectra requires a systematic analytical approach. We introduce Modular Operations for Spectral Alignment by Iterative Compression (MOSAIC)─a general cipher algorithm that applies modular arithmetic to filter monomer-derived mass contributions and cluster MALDI peaks by nonconstitutional repeating units (non-CRUs). MOSAIC performs sequential modular operations using monomer mass differences as base units to compress complex spectral data, revealing end-group distributions and comonomer incorporation. As a demonstration, we applied MOSAIC to five copolymers formed by two different polymerization mechanisms. Furthermore, the resulting remainder–mass plots clearly resolve polymer homologs with distinct non-CRUs into visually apparent clusters, enabling intuitive assignment of mass spectral features.

Wang, Hanlin M. [University of Illinois at Urbana−↗
DOE OSTI2024

Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks

There has been much recent interest in designing symmetry-aware neural networks (NNs) exhibiting relaxed equivariance. Such NNs aim to interpolate between being exactly equivariant and being fully flexible, affording consistent performance benefits. In a separate line of work, certain structured parameter matrices -- those with displacement structure, characterized by low displacement rank (LDR) -- have been used to design small-footprint NNs. Displacement structure enables fast function and gradient evaluation, but permits accurate approximations via compression primarily to classical convolutional neural networks (CNNs). In this work, we propose a general framework -- based on a novel construction of symmetry-based structured matrices -- to build approximately equivariant NNs with significantly reduced parameter counts. Our framework integrates the two aforementioned lines of work via the use of so-called Group Matrices (GMs), a forgotten precursor to the modern notion of regular representations of finite groups. GMs allow the design of structured matrices -- resembling LDR matrices -- which generalize the linear operations of a classical CNN from cyclic groups to general finite groups and their homogeneous spaces. We show that GMs can be employed to extend all the elementary operations of CNNs to general discrete groups. Further, the theory of structured matrices based on GMs provides a generalization of LDR theory focussed on matrices with cyclic structure, providing a tool for implementing approximate equivariance for discrete groups. We test GM-based architectures on a variety of tasks in the presence of relaxed symmetry. We report that our framework consistently performs competitively compared to approximately equivariant NNs, and other structured matrix-based compression frameworks, sometimes with a one or two orders of magnitude lower parameter count.

Samudre, Ashwin↗
DOE OSTI2022

Fast increased fidelity samplers for approximate Bayesian Gaussian process regression

Gaussian processes (GPs) are common components in Bayesian non-parametric models having a rich methodological literature and strong theoretical grounding. The use of exact GPs in Bayesian models is limited to problems containing several thousand observations due to their prohibitive computational demands. We develop a posterior sampling algorithm using H-matrix approximations that scales at O(n log 2 n). We show that this approximation’s Kullback-Leibler divergence to the true posterior can be made arbitrarily small. Though multidimensional GPs could be used with our algorithm, d-dimensional surfaces are modeled as tensor products of univariate GPs to minimize the cost of matrix construction and maximize computational efficiency. We illustrate the performance of this fast increased fidelity approximate GP, FIFA-GP, using both simulated and non-synthetic data sets

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1979

Axial-flow compressor turning angle and loss by inviscid-viscous interaction blade-to-blade computation

A method for computation of the flow field around an arbitrary airfoil cascade on an axially symmetric blade-to-blade surface was developed which takes into account the development and separation of the blade surface boundary layers and mixing in the wake. The method predicts the overall fluid turning and total pressure loss in the context of an inviscid-viscous interaction scheme. The inviscid flow solution is obtained from a compressible flow matrix method. The viscous flow is obtained from a differential boundary layer method which calculates laminar, transitional and turbulent boundary layers. Provisions for the calculation of laminar and turbulent separation regions were added to the viscous scheme. The combined inviscid-viscous interaction scheme described yields results which are quantitatively consistent with experimental data. This suggests that the physical basis for the interactive system is correct and justifies continued exploration and use of the method.

Hansen, E. C.↗
NASA NTRS1992

A comparison of three SAR interference filters

Three interference filters are discussed and their ability to remove the interference while leaving target signal data is quantified. The filters are adaptive frequency-domain spike filtering; adaptive frequency-domain interference determination and masking; and interference-target correlation masking. Using Jet Propulsion Laboratory Airborne Synthetic Aperture Radar (JPL AIRSAR) data, the algorithms are applied to three data sets. The resultant compressed Stokes matrix data are compared with the normally processed interference-free image in a quantitative sense. The algorithms are evaluated by measuring the polarization signature, SNR, equivalent number of looks, and impulse response of the processed images.

Chapman, B.↗
NASA NTRS1993

Forest investigations by polarimetric AIRSAR data in the Harz mountains

The Harz Mountains in the North of Germany have been a study site for several remote sensing investigations since 1985, as the mountainous area is one of the forest regions in Germany heavily affected by forest decline, especially in the high altitudes above 800 m. In a research program at the University of Berlin, methods are developed for improving remote sensing assessment of forest structure and forest state by additional GIS information, using several datasets for establishing a forest information system. The Harz has been defined as a test site for the SIR-C/X-SAR mission which is going to deliver multifrequency and multipolarizational SAR data from orbit. In a pilot project let by DLR-DFD, these data are to be investigated for forestry and ecology purposes. In preparing a flight campaign to the SIR-C / X-SAR mission, 'MAC EUROPE 1991', performed by NASA/JPL, an area of about 12 km in the Northern Harz was covered with multipolarizational AIRSAR data in the C-, L- and P-band, including the Brocken, the highest mountain of the Harz, with an altitude of 1142 m. The multiparameter AIRSAR data are investigated for their information content on the forest state, regarding the following questions: (1) information on forest stand parameters like forest types, age classes and crown density, especially for the separation of deciduous and coniferous forest; (2) information on the storm damages (since 1972) and the status of regeneration; (3) information on the status of forest destruction because of forest decline; and (4) influence of topography, local incidence angle and soil moisture on the SAR data. Within the project various methods and tools have been developed for the investigation of multipolarimetric radar backscatter responses and for discrimination purposes, in order to use the multipolarization information of the compressed Stokes matrix delivered by JPL.

Keil, M.↗
NASA NTRS2000

BOREAS RSS-16 AIRSAR CM Images: Integrated Processor Version 6.1 Level-3b

The BOREAS RSS-16 team used satellite and aircraft SAR data in conjunction with various ground measurements to determine the moisture regime of the boreal forest. RSS-16 assisted with the acquisition and ordering of NASA JPL AIRSAR data collected from the NASA DC-8 aircraft. The NASA JPL AIRSAR is a side-looking imaging radar system that utilizes the SAR principle to obtain high resolution images that represent the radar backscatter of the imaged surface at different frequencies and polarizations. The information contained in each pixel of the AIRSAR data represents the radar backscatter for all possible combinations of horizontal and vertical transmit and receive polarizations (i.e., HH, HV, VH, and VV). Geographically, the data cover portions of the BOREAS SSA and NSA. Temporally, the data were acquired from 12-Aug-1993 to 31-Jul-1995. The level-3b AIRSAR CM data are in compressed Stokes matrix format, which has 10 bytes per pixel. From this data format, it is possible to synthesize a number of different radar backscatter measurements. The data are stored in binary image-format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
DOE OSTI2021

Compression molding of anisotropic NdFeB bonded magnets in a polycarbonate matrix

Anisotropic bonded Nd 2 Fe 14 B (NdFeB) magnets in a polycarbonate (PC) binder matrix are fabricated using a compression molding process. The weight fractions (w.f.) of NdFeB in PC on the batch mixer are 20, 50, 75, 85 and 95% compared to the twin screw extruder with 20, 50 and 75% respectively. The density of the 95% batch mixed magnets fabricated was 5.34 g/cm 3 and the magnetic properties are, intrinsic coercivity H ci = 942.99 kA/m, remanence B r = 0.86 T, and energy product (BH) max = 120.96 kJ/m 3 . Furthermore, the measured tensile properties are in the range of 27-59 MPa, comparable to that of polyamide (PA), polyphenylene sulfide (PPS) bonded magnets and demonstrating potential for bonded magnet applications. Scanning electron microscopy showed that the onset of failure occurs in the magnetic particle- matrix interface. This study demonstrates that compression additive molding technique can be used to fabricate high performance NdFeB polycarbonate composite magnets with improved mechanical properties.

36 MATERIALS SCIENCE↗
NASA NTRS1974

Matrix methods for the design of cascades to prescribed surface velocity distributions and for fully compressible flow

This paper describes matrix methods that have been developed for calculating compressible flow on a blade-to-blade surface of revolution. The methods have been fully tested to date only for the design of plane cascades to prescribed blade surface distributions; the methods will be illustrated here for that problem only. Similar methods are presently being applied to both the direct and indirect problems and for flow on arbitrary surfaces of revolution in annular cascades with stream sheet thickness variations. It is believed that by such methods, both the direct and indirect calculations can be reduced to about 60 to 90 seconds of computing.

Silvester, M. E.↗
NASA NTRS1994

Effects of fiber, matrix, and interphase on carbon fiber composite compression strength

The major goal of this project was to obtain basic information on compression failure properties of carbon fiber composites. To do this, we investigated fiber effects, matrix effects, and fiber/matrix interface effects. Using each of nine fiber types, we prepared embedded single-fiber specimens, single-ply specimens, and full laminates. From the single-fiber specimens, in addition to the standard fragmentation test analysis, we were able to use the low crack density data to provide information about the distribution of fiber flaws. The single-ply specimens provided evidence of a correlation between the size of kink band zones and the quality of the interface. Results of the laminate compression experiments mostly agreed with the results from single-ply experiments, although the ultimate compression strengths of laminates were higher. Generally, these experiments showed a strong effect of interfacial properties. Matrix effects were examined using laminates subjected to precracking under mixed-mode loading conditions. A large effect of precracking conditions on the mode 1 toughness of the laminates was found. In order to control the properties of the fiber/matrix interface, we prepared composites of carbon fiber and polycarbonate and subjected these to annealing. The changes in interfacial properties directly correlated with changes in compression strength.

Nairn, John A.↗
DOE OSTI2023

Compression of tokamak boundary plasma simulation data using a maximum volume algorithm for matrix skeleton decomposition

This report demonstrates satisfactory data compression of SOLPS-ITER simulation output ranging from 2D fields, 1D profiles, and 0D scalar variables with a novel matrix decomposition approach. The singular value decomposition (SVD) scales poorly for large matrix sizes and is unsuited to the application on high dimensional data common to fusion plasma physics simulation. In this work, we employ the columns-submatrix-rows (CUR) matrix factorization technique in order to compute a low-rank approximation up to two orders of magnitude faster than the SVD, but within a nominal L2-norm relative error of ε = 10 –2 . In addition, the CUR approach maintains the original format of the data, in its extracted columns and rows, allowing for interpretable data storage at the original resolution of the simulation. We utilize an iterative algorithm to compute the CUR decomposition of simulation output by maximizing the volume, or linearly independent information content, of a low-rank submatrix contained within the data. Experiments over $\textit{n} × \textit{n}$ randomized test matrices with embedded rank-deficient features show that this maximum volume implementation of CUR matrix approximation has reduced asymptotic computational complexity on the order of n compared to the SVD, which scales approximately as $n^3$. These results show that the CUR technique can be used to effectively select time step snapshots (columns) of over 140 SOLPS-ITER output variables and the associated discretized coordinate timeseries (rows) allowing for reconstruction of the complete simulation dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Data-Driven Compression of Electron-Phonon Interactions

First-principles calculations of electron interactions in materials have seen rapid progress in recent years, with electron-phonon ( e − ph ) interactions being a prime example. However, these techniques use large matrices encoding the interactions on dense momentum grids, which reduces computational efficiency and obscures interpretability. For e − ph interactions, existing interpolation techniques leverage locality in real space, but the high dimensionality of the data remains a bottleneck to balance cost and accuracy. Here we show an efficient way to compress e − ph interactions based on singular value decomposition (SVD), a widely used matrix and image compression technique. Leveraging (un)constrained SVD methods, we accurately predict material properties related to e − ph interactions—including charge mobility, spin relaxation times, band renormalization, and superconducting critical temperature—while using only a small fraction (1%–2%) of the interaction data. These findings unveil the hidden low-dimensional nature of e − ph interactions. Furthermore, they accelerate state-of-the-art first-principles e − ph calculations by about 2 orders of magnitude without sacrificing accuracy. Our Pareto-optimal parametrization of e − ph interactions can be readily generalized to electron-electron and electron-defect interactions, as well as to other couplings, advancing quantitative studies of condensed matter. Published by the American Physical Society 2024

Physics↗
NASA NTRS1993

Prestressed Composite Parts

Matrix/fiber structural components strengthened by prestressing, according to proposal, increasing effective tensile strengths of components and enabling components to function in applications in which they otherwise fail. Reinforcing fibers stretched while encapsulated in matrix. After encapsulation, fibers released, placing matrix in lengthwise compression. Variety of fiber/matrix combinations fabricated this way. Prestressed quartz fibers encapsulated in ceramic matrix. Resulting composite used to make blade for gas turbine. Ceramic, normally weak in tension, has high strength and endures high temperature.

Surls, Michael M.↗
DOE OSTI2024

A graphics processing unit accelerated sparse direct solver and preconditioner with block low rank compression

We present the GPU implementation efforts and challenges of the sparse solver package STRUMPACK. The code is made publicly available on github with a permissive BSD license. STRUMPACK implements an approximate multifrontal solver, a sparse LU factorization which makes use of compression methods to accelerate time to solution and reduce memory usage. Multiple compression schemes based on rank-structured and hierarchical matrix approximations are supported, including hierarchically semi-separable, hierarchically off-diagonal butterfly, and block low rank. Here, in this paper, we present the GPU implementation of the block low rank (BLR) compression method within a multifrontal solver. Our GPU implementation relies on highly optimized vendor libraries such as cuBLAS and cuSOLVER for NVIDIA GPUs, rocBLAS and rocSOLVER for AMD GPUs and the Intel oneAPI Math Kernel Library (oneMKL) for Intel GPUs. Additionally, we rely on external open source libraries such as SLATE (Software for Linear Algebra Targeting Exascale), MAGMA (Matrix Algebra on GPU and Multi-core Architectures), and KBLAS (KAUST BLAS). SLATE is used as a GPU-capable ScaLAPACK replacement. From MAGMA we use variable sized batched dense linear algebra operations such as GEMM, TRSM and LU with partial pivoting. KBLAS provides efficient (batched) low rank matrix compression for NVIDIA GPUs using an adaptive randomized sampling scheme. The resulting sparse solver and preconditioner runs on NVIDIA, AMD and Intel GPUs. Interfaces are available from PETSc, Trilinos and MFEM, or the solver can be used directly in user code. We report results for a range of benchmark applications, using the Perlmutter system from NERSC, Frontier from ORNL, and Aurora from ALCF. For a high frequency wave equation on a regular mesh, using 32 Perlmutter compute nodes, the factorization phase of the exact GPU solver is about 6.5× faster compared to the CPU-only solver. The BLR-enabled GPU solver is about 13.8× faster than the CPU exact solver. For a collection of SuiteSparse matrices, the STRUMPACK exact factorization on a single GPU is on average 1.9× faster than NVIDIA’s cuDSS solver.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

The influence of fiber waviness on the compressive behavior of unidirectional continuous fiber composites

The influence of fiber waviness and matrix nonlinearity on the compressive behavior of continuous fiber composites is studied. A micromechanics model based on the kinematics of the fibers has been developed to predict the behavior of unidirectional composites with initially wavy fibers under compressive loads. The initial waviness has been idealized as sinusoidal. Nonlinear shear behavior of the matrix has been included. Because the shear strain in the matrix is a function of position, the deformed shape of the fibers differs from the initial shape. Therefore, the deformed fiber shape is represented by a sine series. Fiber waviness and matrix shear properties have been determined experimentally for T650-42/Radel C under several conditions. These experimental data have been used as input into the analytical model. Predicted compressive response is in reasonable agreement with experimental data.

Highsmith, Alton L.↗
NASA NTRS2001

Thermal Analysis of a Carbon Fiber Rope Barrier for Use in the Reusable Solid Rocket Motor Nozzle Joint-2

This study provides for development and verification of analysis methods used to assess performance of a carbon fiber rope (CFR) thermal barrier system that is currently being qualified for use in Reusable Solid Rocket Motor (RSRM) nozzle joint-2. Modeled geometry for flow calculations considers the joint to be vented with the porous CFR barriers placed in the "open' assembly gap. Model development is based on a 1-D volume filling approach where flow resistances (assembly gap and CFRs) are defined by serially connected internal flow and the porous media "Darcy" relationships. Combustion gas flow rates are computed using the volume filling code by assuming a lumped distribution total joint fill volume on a per linear circumferential inch basis. Gas compressibility, friction and heat transfer are included in the modeling. Gas-to-wall heat transfer is simulated by concurrent solution of the compressible flow equations and a large thermal 2-D finite element (FE) conduction grid. The derived numerical technique loosely couples the FE conduction matrix with the compressible gas flow equations, Free constants that appear in the governing equations are calibrated by parametric model comparison to hot fire subscale test results. The calibrated model is then used to make full-scale motor predictions using RSRM aft dome environments. Model results indicate that CFR thermal barrier systems will provide a thermally benign and controlled pressurization environment for the RSRM nozzle joint-2 primary seal activation.

Clayton, J. Louie↗
NASA NTRS2002

Thermal Analysis of a Carbon Fiber Rope Barrier for Use in the Reusable Solid Rocket Motor Nozzle Joint-2

This study provides development and verification of analysis methods used to assess performance of a carbon fiber rope (CFR) thermal barrier system that is currently being qualified for use in Reusable Solid Rocket Motor (RSRM) nozzle joint-2. Modeled geometry for flow calculations considers the joint to be vented with the porous CFR barriers placed in the 'open' assembly gap. Model development is based on a 1-D volume filling approach where flow resistances (assembly gap and CFRs) are defined by serially connected internal flow and the porous media 'Darcy' relationships. Combustion gas flow rates are computed using the volume filling code by assuming a lumped distribution total joint fill volume on a per linear circumferential inch basis. Gas compressibility, friction and heat transfer are included in the modeling. Gas-to-wall heat transfer is simulated by concurrent solution of the compressible flow equations and a large thermal 2-D finite element (FE) conduction grid. The derived numerical technique loosely couples the FE conduction matrix with the compressible gas flow equations. Free constants that appear in the governing equations are calibrated by parametric model comparison to hot fire subscale test results. The calibrated model is then used to make full-scale motor predictions using RSRM aft dome environments. Model results indicate that CFR thermal barrier systems will provide a thermally benign and controlled pressurization environment for the RSRM nozzle joint-2 primary seal activation.

Clayton, J. Louie↗