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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

R and DE Robotic Sensor Intern Team: Remote 3D Mapping Sensor Suite

The primary goal of the sensor suite is to provide an internal 3D map of the HCAEX tunnel. When looking for a sensor that would provide XYZ point cloud data for mapping the decision was between a stereo camera, a 3D Lidar, or a 2D Lidar that would need to be spun around. The issues with the stereo camera were that it does not have a large field-of-view and that its depth information was not nearly as accurate as even the baseline Lidars. The selection between Lidars is detailed. The Hokuyo UTM-30LX-EW shown provides a 270 deg. FOV with high accuracy and resolution while the largest FOV on a 3D Lidar is 40 deg.. This was the reason a 2D Lidar was chosen over the 3D Lidar. Even though the 2D Lidar requires additional components and software to generate a 3D map, its FOV advantage is too great given that the HCAEX tunnel is a relatively confined space. The rotating planar scan from the 2D Lidar can be stitched into a 3D scan as shown in the graphic below. Along with XYZ data, the Lidar provides return intensity data in color which can be used to distinguish between different materials within the tunnel. To provide visual feedback a camera system needed to be identified. The common solution for this is a high resolution camera with a small FOV mounted on a pan-tilt system. But, given the critical nature of the visual feedback we looked into solutions without the need for moving parts. Two panospheric cameras give a FOV large enough to get a full 360 deg. view.. Camera color data (RGB) can also be combined with the 3D mapping data from the Lidar and overlaid on the map to give the user the ability to see inside the entire length of the tunnel as if they were inside. Situational awareness is required for the crawler in the tunnel in order for it to be able to register the 3D scans to create a final map. For this we procured a Microstrain 3DM-GX5-25 Inertial Measurement Unit (IMU). To perform the Lidar rotation we have two servos driving the pan and tilt. The servo controls and most data processing will be performed via an onboard computer. The sensor components are to be packaged together using 3D printed mounts into a standalone unit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

A Scientific Data Provenance API for Distributed Applications

Data provenance has been an active area of research as a means to standardize how the origin of data, process event history, and what or who was responsible for influencing results is explained. There are two approaches to capture provenance information. The first approach is to collect observed evidence produced by an executing application using log files, event listeners, and temporary files that are used by the application or application developer. The provenance translated from these observations is an interpretation of the provided evidence. The second approach is called disclosed because the application provides a firsthand account of the provenance based on the anticipated questions on data flow, process flow, and responsible agents. Most observed provenance collection systems collect lot of provenance information during an application run or workflow execution. The common trend in capturing provenance is to collect all possible information, then attempt to find relevant information, which is not efficient. Existing disclosed provenance system APIs do not work well in distributed environment and have trouble finding where to fit the individual pieces of provenance information. This work focuses on determining more reliable solutions for provenance capture. As part of the Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows (IPPD) project, an API was developed, called Producer API (PAPI), which can disclose application targeted provenance, designed to work in distributed environments by means of unique object identification methods. The provenance disclosure approach used adds additional metadata to the provenance information to uniquely identify the pieces and connect them together. PAPI uses a common provenance model to support this provenance integration across disclosure sources. The API also provides the flexibility to let the user decide what to do with the collected provenance. The collected provenance can be sent to a triple store using REST services or it can be logged to a file.

Raju, Bibi↗
DOE OSTI2015

MapReduce SVM Game

Despite technological advances making computing devices faster, smaller, and more prevalent in today's age, data generation and collection has outpaced data processing capabilities. Simply having more compute platforms does not provide a means of addressing challenging problems in the big data era. Rather, alternative processing approaches are needed and the application of machine learning to big data is hugely important. The MapReduce programming paradigm is an alternative to conventional supercomputing approaches, and requires less stringent data passing constrained problem decompositions. Rather, MapReduce relies upon defining a means of partitioning the desired problem so that subsets may be computed independently and recom- bined to yield the net desired result. However, not all machine learning algorithms are amenable to such an approach. Game-theoretic algorithms are often innately distributed, consisting of local interactions between players without requiring a central authority and are iterative by nature rather than requiring extensive retraining. Effectively, a game-theoretic approach to machine learning is well suited for the MapReduce paradigm and provides a novel, alternative new perspective to addressing the big data problem. In this paper we present a variant of our Support Vector Machine (SVM) Game classifier which may be used in a distributed manner, and show an illustrative example of applying this algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A novel technique for real-time estimation of edge pedestal density gradients via reflectometer time delay data

A new model-based technique for fast estimation of the pedestal electron density gradient has been developed. The technique uses ordinary mode polarization profile reflectometer time delay data and does not require direct profile inversion. Because of its simple data processing, the technique can be readily implemented via a Field-Programmable Gate Array, so as to provide a real-time density gradient estimate, suitable for use in plasma control systems such as envisioned for ITER, and possibly for DIII-D and Experimental Advanced Superconducting Tokamak. The method is based on a simple edge plasma model with a linear pedestal density gradient and low scrape-off-layer density. By measuring reflectometer time delays for three adjacent frequencies, the pedestal density gradient can be estimated analytically via the new approach. Using existing DIII-D profile reflectometer data, the estimated density gradients obtained from the new technique are found to be in good agreement with the actual density gradients for a number of dynamic DIII-D plasma conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Thomson Scattering Diagnostic Data Acquisition Systems for Modern Fusion Systems

Uniquely designed complex data acquisition system for Thomson scattering diagnostic was developed. It allows recording short duration (3-5 ns) scattered pulses with 2 GHz sampling rate and 10-bit total resolution in oscilloscope mode. The system consists up to 48 photo detector modules with 0- 200 MHz bandwidth, 1-48 simultaneously sampling ADC modules and synchronization subsystem. The photo detector modules are based on avalanche photodiodes (APD) and ultra-low noise trans-impedance amplifiers. ADC modules include fast analog to digital converters and digital units based on the FPGA (Field- Programmable Gate Array) for data processing and storage. The synchronization subsystem is used to form triggering pulses and to organize the simultaneously mode of ADC modules operation. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Novel principal component analysis tool based on python for analysis of complex spectra of time-of-flight secondary ion mass spectrometry

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface analysis tool, which can simultaneously provide elemental, isotopic, and molecular information with part per million (ppm) sensitivity. However, each spectrum may be composed of hundreds of ion signals, which makes the spectra data complex. Principal component analysis (PCA) is a multivariate analysis technique that has been widely used to figure out the variances among samples in ToF-SIMS spectra data analysis and is showing great success in the explanation of complex ToF-SIMS spectra. So far, several software tools have been developed for PCA of ToF-SIMS spectra; however, none of them are freely available. Such a situation leads to some difficulties in extending applications of PCA to various research fields. More importantly, it has long been challenging for common researchers to understand PCA plots and extract chemical differences among samples. In this work, we developed a new and flexible software tool (named “advanced spectra pca toolbox”) based on python for PCA of complex ToF-SIMS spectra along with an easy-to-read manual. It can generate data analysis reports automatically to explain chemical differences among samples, allowing less experienced researchers to easily understand tricky PCA results. Moreover, it is expandable and compatible with artificial intelligence/machine learning functions. Pure goethite and different lignin adsorbed goethite samples were used as a model system to demonstrate our new software tool, proving that our software tool can be readily used in complex spectra data processing. Our new software tool is open-source, convenient, flexible, and expandable. We expect this open-source tool will benefit the ToF-SIMS community.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Molecular Characterization of High Molecular Weight Polyesters by Matrix-Assisted Laser Desorption/Ionization High-Resolution Time-of-Flight Mass Spectrometry Combined with On-plate Alkaline Degradation and Mass Defect Analysis

Matrix-assisted laser desorption ionization high-resolution time-of-flight mass spectrometry (MALDI HR TOF MS) is a powerful tool for the molecular characterization of industrial polymers. However, accurate mass determination and resolution of isobaric ions are possible for oligomer samples only typically below m/z 3000. To cut long polymer chains into oligomers suitable for high-resolution mass spectrometry, we propose a simple “on-plate” alkaline degradation of polyesters as a sample pretreatment technique prior to the MALDI TOF MS measurement. This pretreatment can be performed on a MALDI target using a small amount of sample (μg or less) and 1 μL of alkaline reagent by simple pipetting. Informative mass spectra in the oligomeric mass range are successfully recorded but complicated by the variation of end-groups and the copolymeric composition of the degradation products. Data processing is assisted by a series of advanced Kendrick mass defect (KMD) analyses recently proposed by the authors to plot visually understandable two-dimensional maps. On-plate degradation pretreatment, high-resolution MALDI TOF MS measurements, and advanced KMD analyses are innovatively combined for the compositional characterization of bacterial poly(3-hydroxybutyric acid-co-3-hydroxyvaleric acid) and industrial poly(ethylene terephthalate) samples. .

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Interactive Visualization of Multi-Group Cross Sections on High-Fidelity Spatial Meshes

Core simulation tools utilizing Monte Carlo transport methods represent the 'Holy Grail' for nuclear reactor analysis. However, deterministic transport methods pose a number of advantages to Monte Carlo from a computational perspective, which seems likely to make these methods more viable in the near to intermediate term. Deterministic methods almost universally discretize the energy domain in a few to hundreds of energy groups. One of the key challenges for deterministic transport-based methods to be viable is accurate, reactor agnostic multi-group cross section generation. This paper describes tools for data processing and visualization of multigroup cross sections generated on high-fidelity spatial meshes from the OpenMC Monte Carlo code. Next generation deterministic transport reactor core modeling tools will require multi-group cross section (MGXS) generation on high-fidelity spatial meshes. High-fidelity MGXS are necessary for the accurate simulation of neutron physics in nuclear reactors with a high degree of spectral heterogeneity - e.g., large localized neutron flux gradients throughout a reactor core. Although many local (e.g., pin cell) approximations have been developed to model the scalar flux to compute spectral-averaged MGXS, these techniques cannot account for complex intra-pin and intra-assembly spatial self-shielding effects. Monte Carlo presents the most accurate method for reactor agnostic multi-group cross section generation since it does not require the use of local approximations to the flux. Monte Carlo has been proposed as a highly desirable framework for reactor agnostic cross section generation for many years. Monte Carlo methods can effectively embed all of the relevant spectral effects into the MGXS through the random particle tracking and interaction sampling processes. Previous work has applied MCNP and Serpent to compute few-group constants for diffusion calculations, and OpenMC to compute multi-group cross sections for transport-based methods. The primary difficulty with using Monte Carlo for MGXS generation is the tremendous computational resources required to adequately converge multi-group cross sections in each spatial region and energy group. Recent development of the OpenMC Monte Carlo code for high-performance computing platforms has made multigroup cross section generation from Monte Carlo more tractable in the foreseeable future. The recent release of OpenMC v0.7.1 includes a new Python-based module for MGXS generation. The MGXS generation module leverages many of the algorithms and features for 'big data' analysis of large tally datasets on complex spatial meshes. This paper describes the data management workflow and visualization tools which have been developed to explore the plethora of MGXS data generated with OpenMC. It is the authors' hope that the development of the visualization tool described in this paper will ultimately enable the design of machine learning algorithms to accelerate the convergence rate of high-fidelity multi-group cross section generated with Monte Carlo. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

The second– and third– order nonlinear optical properties and electronic transition of a NLO chromophore: A DFT study

It is well known that the practical applications of second-order and third-order nonlinear optical (NLO) materials have been reported in modern technology, such as optical data processing, transmission and storage, etc. In this respect, the linear and nonlinear optical parameters (the molecular static polarizability (α), and the first–order static hyperpolarizability (β{sub 0}), the second–order static hyperpolarizability (γ)), UV-vis spectra and HOMO and LUMO energies of 2-(1′-(4’’’-Methoxyphenyl)-5′-(thien-2″-yl)pyrrol-2′-yl)-1,3-benzothiazole were investigated by using the HSEh1PBE/6–311G(d,p) level of density functional theory. The UV–vis spectra were simulated using TD/HSEh1PBE/6– 311G(d,p) level, and the major contributions to the electronic transitions were obtained. The molecular hardness (η) and electronegativity (χ) parameters were also obtained by using molecular frontier orbital energies. The NLO parameters of the title compound were calculated, and obtained data were compared with that of para-Nitroaniline (pNA) which is a typical NLO material and the corresponding experimental data. Obtained data of the chromosphere display significant molecular second-and third-nonlinearity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Two-Photon Absorption of Nonchain HF Laser Radiation in Germanium Single Crystals

Some results of experimental and numerical studies on the transmission of a nonchain high-frequency (HF) laser beam through germanium (Ge) single crystals of differing thickness and specific resistance are presented. Based on the experimental data for the HF(DF) lasing spectrum, the coefficient of two-photon absorption in germanium has been estimated as K{sub 2} = 55 ± 10 cm/GW at λ = 2.8 μm. The results are in good agreement with theory. The developed experimental data-processing software has enabled the numerical study of the transmission of a high-power beam with λ = 2.6–3 μm through Ge at any laser-pulse-impact moment. It has been shown that thin germanium coatings can efficiently smoothen the distribution of energy over the beam aperture for high-power laser radiation with λ = 2.6–4 μm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Adjusted Graphite Thermal Scattering Data Applied to Fluoride-Salt-Cooled Reactors

Thermal scattering data is a key component of fission reactor simulation. While most materials can be reasonably modeled with a free gas approximation, the moderators in thermal systems require a more rigorous treatment to sufficiently capture their specific neutron interaction physics. Graphite does not typically feature as a principle moderator in power reactors in service today, but remains an attractive prospect for a number of new reactor concepts currently in development. In comparison to light water, a material nearly ubiquitous in thermal reactors, graphite offers a better neutron economy by way of a small absorption cross section, high thermodynamic stability and can be incorporated into the structure of the core itself. Graphite in its purest form is a crystalline material composed of stacked layers of graphene, a hexagonal planar lattice of carbon atoms. In-plane, each carbon atom is covalently bonded to 3 neighbouring carbon atoms, creating a strong bond, while between planes only a weak van der Waals force exists. Pure graphite has a density of 2.26 g/cm{sup 3}. However, reactor-grade contains a significant amount of carbon binder, leading to a porous bulk medium with randomly oriented micro crystals. Densities of 1.5 - 1.9 g/cm{sup 3} are typical for reactor-grade graphite, corresponding to porosities on the order of 10-30%. This deviation from pure crystalline graphite should be accounted for in the thermal scattering data. When an incident neutron is in or near the thermal region, its de Broglie wavelength is the same order as the molecular bond lengths, leading to elastic scattering. At similar energies, the dynamics of the moderator lattice (in the case of solid moderators) can cause inelastic scattering. For these moderators, special cross sections should be calculated and used in reactor simulations. To generate this thermal scattering data, parameters pertaining to the properties and structure of the material in question are fed into a nuclear data processing code, such as NJOY. Within NJOY is a module called LEAPR which is used to generate the thermal scattering law S(α,β), which is in turn is fed into another module THERMR which is used to generate thermal cross sections that factor in the molecular-scale scattering phenomena. The core of the thermal scattering law is the phonon spectrum ρ(β) which describes the modes of excitation of the material lattice. An investigation into the phonon frequency spectrum was conducted at North Carolina State University (NCSU) for reactor-grade graphite which accounts for porosity. This phonon spectrum was calculated using the ab initio density functional theory (DFT) code VASP. The inelastic cross section calculated using this spectrum was found to have good agreement with relevant experimental data. The resulting spectra differed from the benchmark spectrum produced by Young and Koppel, the same data used in current nuclear data evaluations. The latter uses the lattice dynamics of perfect crystalline graphite with four force constants fitted to the model from thermodynamics data from reactor-grade (porous) graphite, which yields a reasonable approximation to the phonon spectrum of reactor-grade graphite.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

The First Data Release from SweetSpot: 74 Supernovae in 36 Nights on WIYN+WHIRC

SweetSpot is a 3 yr National Optical Astronomy Observatory (NOAO) survey program to observe Type Ia supernovae (SNe Ia) in the smooth Hubble flow with the WIYN High-resolution Infrared Camera (WHIRC) on the WIYN 3.5 m telescope. We present data from the first half of this survey, covering the 2011B–2013B NOAO semesters and consisting of 493 calibrated images of 74 SNe Ia observed in the rest-frame near-infrared (NIR) in the range 0.02 < z < 0.09. Because many observed supernovae require host-galaxy subtraction from templates taken in later semesters, this release contains only the 186 NIR (JHK {sub s}) data points for the 33 SNe Ia that do not require host-galaxy subtraction. The sample includes four objects with coverage beginning before the epoch of B-band maximum and 27 beginning within 20 days of B-band maximum. We also provide photometric calibration between the WIYN+WHIRC and Two Micron All-Sky Survey (2MASS) systems, along with light curves for 786 2MASS stars observed alongside the SNe Ia. This work is the first in a planned series of three SweetSpot Data Releases. Future releases will include the full set of images from all 3 yr of the survey, including host-galaxy reference images and updated data processing with host-galaxy reference subtraction. SweetSpot will provide a well-calibrated sample that will help improve our ability to standardize distance measurements to SNe Ia, examine the intrinsic optical–NIR colors of SNe Ia at different epochs, explore the nature of dust in other galaxies, and act as a stepping-stone for more distant, potentially space-based surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Watermarks in stream processing systems: semantics and comparative analysis of Apache Flink and Google cloud dataflow

Streaming data processing is an exercise in taming disorder: from oftentimes huge torrents of information, we hope to extract powerful and timely analyses. But when dealing with streaming data, the unbounded and temporally disordered nature of real-world streams introduces a critical challenge: how does one reason about the completeness of a stream that never ends? In this paper, we present a comprehensive definition and analysis of watermarks, a key tool for reasoning about temporal completeness in infinite streams.First, we describe what watermarks are and why they are important, highlighting how they address a suite of stream processing needs that are poorly served by eventually-consistent approaches:• Computing a single correct answer, as in notifications.• Reasoning about a lack of data, as in dip detection.• Performing non-incremental processing over temporal subsets of an infinite stream, as in statistical anomaly detection with cubic spline models.• Safely and punctually garbage collecting obsolete inputs and intermediate state.• Surfacing a reliable signal of overall pipeline health.Second, we describe, evaluate, and compare the semantically equivalent, but starkly different, watermark implementations in two modern stream processing engines: Apache Flink and Google Cloud Dataflow.

Akidau, Tyler↗
DOE OSTI2015

Digital Autoradiography as a novel complementary technique for the investigation of radioactive contamination in nuclear facilities under dismantlement

The detection (location and quantification) of nuclear facilities to be dismantled possible contamination with low-range particles emitters ({sup 3}H, other low-energy β emitters, a emitters) remains a tedious and expensive task. Indeed, usual remote counters show a too low sensitivity to these non-penetrating radiations, while conventional wipe tests are irrelevant for fixed radioactivity evaluation. The only method to accurately measure activity levels consists in sampling and running advanced laboratory analyses (spectroscopy, liquid scintillation counting, pyrolysis...). Such measurements generally induce sample preparation, waste production (destructive analyses, solvents), nuclear material transportation, long durations, and significant labor mobilization. Therefore, the search for the limitation of their number and cost easily conflicts with the necessity to perform a dense screening for sampling (to maximize the representativeness of the samples), in installations of thousands of square meters (floors, wells, ceilings), plus furniture, pipes, and other wastes. To overcome this contradiction, Digital Autoradiography (D. A.) was re-routed from bio molecular research to radiological mapping of nuclear installations under dismantling and to waste and sample analysis. After in-situ exposure to the possibly-contaminated areas to investigate, commercial reusable radiosensitive phosphor screens (of a few 100 cm{sup 2}) were scanned in the proper laboratory device and sharp quantitative images of the radioactivity could be obtained. The implementation of geostatistical tools in the data processing software enabled the exhaustive characterization of concrete floors at a rate of 2 weeks / 100 m{sup 2}, at lowest costs. Various samples such as drilled cores, or tank and wood pieces, were also successfully evaluated with this method, for decisive results. Thanks to the accurate location of potential contamination spots, this approach ensures relevant and representative sampling for further laboratory analyses and should be inserted in the range of common tools used in dismantling. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Fault diagnosis and severity estimation in nuclear power plants - 196

Signed Directed Graph (SDG) is a type of fault diagnosis method with a capability to display the complex relationship between plant parameters and reveal the potential danger and the propagation path when a fault occurs in a nuclear plant. However, the fault diagnosis method based on qualitative SDG model inevitably has a number of disadvantages, and some of these disadvantages include its inability to identify reoccurring faults; ambiguous reasoning that can result in low resolution; performance that relies on the accuracy of the model; slow diagnosis rate for large systems and poor real-time diagnosis, among others. In this paper, we propose an SDG fault diagnosis methodology based on Granular Computing Theory, referred to as Granular Computing Signed Directed Graph (GCSDG). This paper shows how knowledge reduction nature of granular computing based fault diagnosis can simplify the decision table, reduce the allocation of resources, scale-down the complexity of the problem and improve the efficiency of data processing. Then, we estimate the severity of the fault using Back Propagation (BP) neural network approach. The proposed methodology was verified by considering certain faults in the primary loop of a PWR, using PCTRAN. The result shows a considerable improvement in fault diagnosis and the severity estimated serves as a useful information for the operator, providing a firm foundation for further intervention. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Robot for Investigations and Assessments of Nuclear Areas

RIANA is a remote controlled Robot dedicated for Investigations and Assessments of Nuclear Areas. The development of RIANA is motivated by the need to have at disposal a proven robot, tested in hot cells; a robot capable of remotely investigate and characterise the inside of nuclear facilities in order to collect efficiently all the required data in the shortest possible time. It is based on a wireless medium sized remote carrier that may carry a wide variety of interchangeable modules, sensors and tools. It is easily customised to match specific requirements and quickly configured depending on the mission and the operator's preferences. RIANA integrates localisation and navigation systems. The robot will be able to generate / update a 2D map of its surrounding and exploring areas. The position of the robot is given accurately on the map. Furthermore, the robot will be able to autonomously calculate, define and follow a trajectory between 2 points taking into account its environment and obstacles. The robot is configurable to manage obstacles and restrict access to forbidden areas. RIANA allows an advanced control of modules, sensors and tools; all collected data (radiological and measured data) are displayed in real time in different format (chart, on the generated map...) and stored in a single place so that may be exported in a convenient format for data processing. This modular design gives RIANA the flexibility to perform multiple investigation missions where humans cannot work such as: visual inspections, dynamic localization and 2D mapping, characterizations and nuclear measurements of floor and walls, non destructive testing, samples collection: solid and liquid. The benefits of using RIANA are: - reducing the personnel exposures by limiting the manual intervention time, - minimizing the time and reducing the cost of investigation operations, - providing critical inputs to set up and optimize cleanup and dismantling operations. (authors)

42 ENGINEERING↗
DOE OSTI2017

Project 1640 Observations of Brown Dwarf GJ 758 B: Near-infrared Spectrum and Atmospheric Modeling

The nearby Sun-like star GJ 758 hosts a cold substellar companion, GJ 758 B, at a projected separation of ≲30 au, previously detected in high-contrast multi-band photometric observations. In order to better constrain the companion’s physical characteristics, we acquired the first low-resolution (R ∼ 50) near-infrared spectrum of it using the high-contrast hyperspectral imaging instrument Project 1640 on Palomar Observatory’s 5 m Hale telescope. We obtained simultaneous images in 32 wavelength channels covering the Y, J, and H bands (∼952–1770 nm), and used data processing techniques based on principal component analysis to efficiently subtract chromatic background speckle-noise. GJ 758 B was detected in four epochs during 2013 and 2014. Basic astrometric measurements confirm its apparent northwest trajectory relative to the primary star, with no clear signs of orbital curvature. Spectra of SpeX/IRTF observed T dwarfs were compared to the combined spectrum of GJ 758 B, with χ {sup 2} minimization suggesting a best fit for spectral type T7.0 ± 1.0, but with a shallow minimum over T5–T8. Fitting of synthetic spectra from the BT-Settl13 model atmospheres gives an effective temperature T {sub eff} = 741 ± 25 K and surface gravity logg=4.3±0.5 dex (cgs). Our derived best-fit spectral type and effective temperature from modeling of the low-resolution spectrum suggest a slightly earlier and hotter companion than previous findings from photometric data, but do not rule out current results, and confirm GJ 758 B as one of the coolest sub-stellar companions to a Sun-like star to date.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Improvements in optical metrology for high-performance variable-line-spacing x-ray gratings

Here, we discuss a project to develop a precision metrology system for variable-line-spacing x-ray gratings using interferometric microscopes. We are developing test standards and calibration techniques to measure and correct for geometrical distortion and blur, and data processing techniques to combine multiple measurements and measure line spacing with high accuracy.

Calibration methods↗