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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

The double-nucleus galaxy IRAS 02580-1136 - A merging system

CCD imaging, infrared photometry, and optical spectroscopy lead to the conclusion that IRAS 02580-1136 consists of two colliding galaxies and is possibly an ongoing merger. Visually, the IRAS source displays two distinct brightness concentrations. These two nuclei, referred to as A and B, have a projected linear separation of 7 kpc and a radial-velocity difference of 180 km/s. Nucleus A belongs to a bulgelike structure and has an optical spectrum typical of a Seyfert 2. It is argued that it harbors a 99 percent dust-obscured low-luminosity Seyfert I source that powers most of the far-infrared radiation. Nucleus B is either a galactic bulge or a low-luminosity elliptical with a heavily reddened compact H II region at its center.

Heisler, Charlene A.↗
NASA NTRS1990

Small-scale structure in the diffuse interstellar medium

The initial results of a study to probe the small-scale structure in the diffuse interstellar medium (ISM) through IUE and optical observations of interstellar absorption lines toward both components of resolvable binary stars is reported. The binaries (Kappa CrA, 57 Aql, 59 And, HR 1609/10, 19 Lyn, and Theta Ser) observed with IUE have projected linear separations ranging from 5700 to 700 Au. Except for Kappa CrA, the strengths of the interstellar absorption lines toward both components of these binaries agree to within 10 percent. In the case of Kappa CrA, the optically thin interstellar Mg I and Mn II lines are about 50 percent stronger toward Kappa-2 CrA than Kappa-1 CrA. Higher resolution observations of interstellar Ca II show that this difference is concentrated in the main interstellar component at V(LSR) = 9 + or - 2 km/s. Interestingly, this velocity corresponds to an intervening cloud that may be associated with the prominent Loop I shell in the local ISM. Given the separation (23 arcsec) and distance (120 pc) of Kappa CrA, the line strength variations indicate that this cloud has structure on scales of 2800 AU or less.

Meyer, David M.↗
NASA NTRS1993

The frequency of T Tauri companion stars

We present the results of a magnitude-limited multiplicity survey of T Tauri stars in two nearby star-forming regions, Taurus-Auriga and Ophiuchus-Scorpius. Each of the 69 stars in the sample was observed at K with an infrared array camera on the Hale 5-m Telescope at Palomar Observatory and imaged using 2D speckle imaging techniques. Thirty-three companion stars were found of which 15 were new detections. One of the main results of this survey indicates that the binary star frequency in the projected linear separation range 14 to 225 AU for T Tauri stars is a factor of 3.5 greater than that of the solar-type main-sequence stars. Given the limited angular separation range of this survey, the rate at which binaries are detected suggests that most T Tauri stars have companions. We propose that the observed overabundance of companions to T Tauri stars relative to their older counterparts on the main sequence is an evolutionary effect; in this scheme, triple and higher order T Tauri star systems, which are observed at higher frequencies than for the solar-type main-sequence stars, are disrupted by close encounters with another star or system of stars.

Ghez, A. M.↗
NASA NTRS1993

The multiplicity of T Tauri stars in the star forming regions Taurus-Auriga and Ophiuchus-Scorpius: A 2.2 micron speckle imaging survey

We present the results of a magnitude limited (K less than = 8.5 mag) speckle imaging survey of 69 T Tauri stars in the star forming regions Taurus-Auriga and Ophiuchus-Scorpius. Thirty-three companion stars were found with separations ranging from 0.07 sec to 2.5 sec, nine are new detections. This survey reveals a distinction between the classical T Tauri stars (CTTS) and the weak-lined T Tauri stars (WTTS) based on the binary star frequency as a function of separation: the WTTS binary star distribution is enhanced at the closer separations (less than 50 AU) relative to the CTTS binary star distribution. We suggest that the nearby companion stars shorten the accretion time scale in multiple star systems, thereby accounting for the presence of WTTS that are coeval with many CTTS. The binary star frequency in the projected linear separation range 16 to 252 AU for T Tauri stars (60 (+/- 17)%) is a factor of 4 greater than that of the solar-type main-sequence stars (16(+/- 3)%). Given the limited separation range of this survey, the rate at which binaries are detected suggests that most, if not all, T Tauri stars have companions. We propose that the observed overabundance of companions of T Tauri stars is an evolutionary effect, in which triple and higher order T Tauri stars are disrupted by close encounters with another star or system of stars.

Ghez, A. M.↗
NASA NTRS2004

An [OIII] Study of the Narrow Line Regions of Seyfert Galaxies: Testing the Unified Model

We present the results of an HST [OIII] study of the narrow line regions (NLRs) of Seyfert galaxies. Our sample consists of Seyfert galaxies selected from nearly isotropic properties, their far-infrared fluxes and warm infrared colors. We discuss the luminosities, projected linear extents, and morphologies of the NLRs of these galaxies as well as the agreement of these properties with the Unified Model. We find that while the Unified Model accurately predicts many of the observed characteristics of the NLRs, certain observed morphologies can not be explained by simple models and require a more careful examination.

Donley, J.↗
NASA NTRS2012

Herschel Discovery of a New class of Cold, Faint Debris Discs

We present Herschel PACS 100 and 160 micron observations of the solar-type stars alpha Men, HD 88230 and HD 210277, which form part of the FGK stars sample of the Herschel Open Time Key Programme (OTKP) DUNES (DUst around NEarby Stars). Our observations show small infrared excesses at 160 micron for all three stars. HD 210277 also shows a small excess at 100 micron. while the 100 micron fluxes of a Men and HD 88230 agree with the stellar photospheric predictions. We attribute these infrared excesses to a new class of cold, faint debris discs. alpha Men and HD 88230 are spatially resolved in the PACS 160 micron images, while HD 210277 is point-like at that wavelength. The projected linear sizes of the extended emission lie in the range from approximately 115 to <= 250 AU. The estimated black body temperatures from the 100 and 160 micron fluxes are approximately < 22 K, while the fractional luminosity of the cold dust is L(dust)/ L(star) approximates 10(exp -6), close to the luminosity of the Solar-System's Kuiper belt. These debris discs are the coldest and faintest discs discovered so far around mature stars and cannot easily be explained by invoking "classical" debris disc models.

Eiroa, C.↗
NASA NTRS2011

Herschel Discovery of a New Class of Cold, Faint Debris Discs

We present Herschel PACS 100 and 160 micron observations of the solar-type stars alpha Men, HD 88230 and HD 210277, which form part of the FGK stars sample of the Herschel Open Time Key Programme (OTKP) DUNES (DUst around NEarby Stars). Our observations show small infrared excesses at 160 m for all three stars. HD 210277 also shows a small excess at 100 micron, while the 100 micron fluxes of alpha Men and HD 88230 agree with the stellar photospheric predictions. We attribute these infrared excesses to a new class of cold, faint debris discs. alpha Men and HD 88230 are spatially resolved in the PACS 160 m images, while HD 210277 is point-like at that wavelength. The projected linear sizes of the extended emission lie in the range from approx 115 to <= 250 AU. The estimated black body temperatures from the 100 and 160 micron fluxes are approx < 22 K, while the fractional luminosity of the cold dust is L(sub dust) / L(*) approx 10 (exp 6) close to the luminosity of the Solar-System's Kuiper belt. These debris discs are the coldest and faintest discs discovered so far around mature stars and cannot easily be explained by invoking "classical" debris disc models.

Eiroal, C.↗
DOE OSTI2025

Projection-based multifidelity linear regression for data-scarce applications

Surrogate modeling for systems with high-dimensional quantities of interest remains challenging, particularly when training data are costly to acquire. This work develops multifidelity methods for multiple-input multiple-output linear regression targeting data-limited applications with high-dimensional outputs. Multifidelity methods integrate many inexpensive low-fidelity model evaluations with limited, costly high-fidelity evaluations. We introduce two projection-based multifidelity linear regression approaches with linear and nonlinear features that leverage principal component basis vectors for dimensionality reduction and combine multifidelity data through: (i) a direct data augmentation using low-fidelity data, and (ii) a data augmentation incorporating explicit linear corrections between low-fidelity and high-fidelity data. The data augmentation approaches combine high-fidelity and low-fidelity data into a unified training set and train the linear regression model through weighted least squares with fidelity-specific weights. We introduce a proximity-based weighting scheme with automatic weight selection strategy through cross-validation. Here, the proposed multifidelity linear regression methods are demonstrated on approximating the surface pressure field of a hypersonic vehicle in flight and the temperature field on an aircraft disc braking system. In an ultra low-data regime of no more than twelve high-fidelity samples, multifidelity linear regression achieves approximately 2% – 12% improvement in median accuracy and a higher R 2 score relative to single-fidelity methods at comparable computational cost.

data augmentation↗
DOE OSTI2024

RandONets: Shallow networks with random projections for learning linear and nonlinear operators

Deep neural networks have been extensively used for the solution of both the forward and the inverse problem for dynamical systems. However, their implementation necessitates optimizing a high-dimensional space of parameters and hyperparameters. This fact, along with the requirement of substantial computational resources, pose a barrier to achieving high numerical accuracy, but also interpretability. Here, to address the above challenges, we present Random Projection-based Operator Networks (RandONets): shallow networks with random projections and tailor-made numerical analysis methods that learn accurately and fast linear and nonlinear operators. Building on previous works, we prove that RandOnets are universal approximators of linear and nonlinear operators. Due to their simplicity, RandONets provide a one-step transformation of the input space, facilitating interpretability. For the evaluation of their performance, we focus on operators of PDEs. We show, that RandONets outperform by several orders of magnitude, both in terms of numerical approximation accuracy and computational cost, the “vanilla” DeepONets. Hence, we believe that our method will trigger further developments in the field of scientific machine learning, for the development of new ‘’light”schemes that will provide high accuracy while reducing dramatically the computational cost. A MATLAB toolbox for RandONets, including demos, is available on GitHub at https://github.com/GianlucaFabiani/RandONets.

Interpretable machine learning↗
DOE OSTI2025

SAM Linear Fresnel Model, Project B (CRADA Final Report)

Objective performance and economic modeling of solar thermal plants is of keen interest to many EPRI funders. One solar thermal technology that is not currently available to model in any non-vendor, non-proprietary tool is linear Fresnel. This technology has garnered enough interest from EPRI funders to merit investing in a tool to objectively model its performance. Early in 2010, EPRI performed a comparison of modeling solar thermal power plants using the IPSEPRO, CNRS and Solar Advisor (SAM) tools. After completing this effort, EPRI decided to adopt NREL’s Solar Advisor Model as its default modeling tool based in part on user friendliness, flexibility, number of technologies covered, integrated financial model and ease of running sensitivities. Furthermore, it was recognized that NREL continues to invest considerable time and resources into improving capabilities and functionality of the model.

14 SOLAR ENERGY↗
DOE OSTI2022

Characterization and alignment of a resonant cavity beam position monitor for the Compact LInear Collider (CLIC) project at CERN

Beam diagnostic devices are essential tools to sense the properties of the beam in particle accelerators. Beam Position Monitors (BPMs) are used to detect the transverse beam spatial coordinates. A large number of high-resolution resonant cavity BPMs, operating at 14GHz, are proposed to monitor the orbit of the two main beam linacs of the CLIC project. This paper discusses innovative calibration techniques on a dedicated test bench in the frame of the PACMAN project. The particular location of the electromagnetic center of the resonant cavity BPM is detected utilizing a stretched-wire measurement approach. Measurements, RF characterization and final fiducialization of the BPM electrical offset are treated with details. Initial studies through EM simulations of the cavity BPM are covered. The presented experimental results prove the feasibility of the alignment methodology with nanometric resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1982

Nonlinear optimization with linear constraints using a projection method

Nonlinear optimization problems that are encountered in science and industry are examined. A method of projecting the gradient vector onto a set of linear contraints is developed, and a program that uses this method is presented. The algorithm that generates this projection matrix is based on the Gram-Schmidt method and overcomes some of the objections to the Rosen projection method.

Fox, T.↗
NASA NTRS1992

Identification of linear stochastic systems through projection filters

A novel method is presented for identifying a state-space model and a state estimator for linear stochastic systems from input and output data. The method is primarily based on the relationship between the state-space model and the finite-difference model of linear stochastic systems derived through projection filters. It is proved that least-squares identification of a finite difference model converges to the model derived from the projection filters. System pulse response samples are computed from the coefficients of the finite difference model.

Chen, Chung-Wen↗
DOE OSTI2021

Efficient Space–Time Reduced Order Model for Linear Dynamical Systems in Python Using Less than 120 Lines of Code

A classical reduced order model (ROM) for dynamical problems typically involves only the spatial reduction of a given problem. Recently, a novel space–time ROM for linear dynamical problems has been developed [Choi et al., Space–tume reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems, Journal of Computational Physics, 2020], which further reduces the problem size by introducing a temporal reduction in addition to a spatial reduction without much loss in accuracy. The authors show an order of a thousand speed-up with a relative error of less than 10−5 for a large-scale Boltzmann transport problem. In this work, we present for the first time the derivation of the space–time least-squares Petrov–Galerkin (LSPG) projection for linear dynamical systems and its corresponding block structures. Utilizing these block structures, we demonstrate the ease of construction of the space–time ROM method with two model problems: 2D diffusion and 2D convection diffusion, with and without a linear source term. For each problem, we demonstrate the entire process of generating the full order model (FOM) data, constructing the space–time ROM, and predicting the reduced-order solutions, all in less than 120 lines of Python code. We compare our LSPG method with the traditional Galerkin method and show that the space–time ROMs can achieve O(10−3) to O(10−4) relative errors for these problems. Depending on parameter–separability, online speed-ups may or may not be achieved. For the FOMs with parameter–separability, the space–time ROMs can achieve O(10) online speed-ups. Finally, we present an error analysis for the space–time LSPG projection and derive an error bound, which shows an improvement compared to traditional spatial Galerkin ROM methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Spline-based distributed system identification with application to large space antennas

A parameter and state estimation technique for distributed models is demonstrated through the solution of a problem generic to large space antenna system identification. Assuming the position of the reflective surface of the maypole (hoop/column) antenna to be approximated by the static two-dimensional, stretched-membrane partial differential equation with variable-stiffness coefficient functions, a spline-based approximation procedure is described that estimates the shape and stiffness functions from data set observations. For given stiffness functions, the Galerkin projection with linear spline-based functions is applied to project the distributed problem onto a finite-dimensional subspace wherein algebraic equations exist for determining a static shape (state) prediction. The stiffness functions are then parameterized by cubic splines and the parameters estimated by an output error technique. Numerical results are presented for data descriptive of a 100-m-diameter maypole antenna.

Banks, H. T.↗