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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
DOE OSTI2014

SU-C-9A-02: Structured Noise Index as An Automated Quality Control for Nuclear Medicine: A Two Year Experience

Purpose: Flood-field uniformity evaluation is an essential element in the assessment of nuclear medicine (NM) gamma cameras. It serves as the central element of the quality control (QC) program, acquired and analyzed on a daily basis prior to clinical imaging. Uniformity images are traditionally analyzed using pixel value-based metrics which often fail to capture subtle structure and patterns caused by changes in gamma camera performance requiring additional visual inspection which is subjective and time demanding. The goal of this project was to develop and implement a robust QC metrology for NM that is effective in identifying non-uniformity issues, reporting issues in a timely manner for efficient correction prior to clinical involvement, all incorporated into an automated effortless workflow, and to characterize the program over a two year period. Methods: A new quantitative uniformity analysis metric was developed based on 2D noise power spectrum metrology and confirmed based on expert observer visual analysis. The metric, termed Structured Noise Index (SNI) was then integrated into an automated program to analyze, archive, and report on daily NM QC uniformity images. The effectiveness of the program was evaluated over a period of 2 years. Results: The SNI metric successfully identified visually apparent non-uniformities overlooked by the pixel valuebased analysis methods. Implementation of the program has resulted in nonuniformity identification in about 12% of daily flood images. In addition, due to the vigilance of staff response, the percentage of days exceeding trigger value shows a decline over time. Conclusion: The SNI provides a robust quantification of the NM performance of gamma camera uniformity. It operates seamlessly across a fleet of multiple camera models. The automated process provides effective workflow within the NM spectra between physicist, technologist, and clinical engineer. The reliability of this process has made it the preferred platform for NM uniformity analysis.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

Automated identification of retinal vessels using a multiscale directional contrast quantification (MDCQ) strategy

Purpose: A novel algorithm is presented to automatically identify the retinal vessels depicted in color fundus photographs. Methods: The proposed algorithm quantifies the contrast of each pixel in retinal images at multiple scales and fuses the resulting consequent contrast images in a progressive manner by leveraging their spatial difference and continuity. The multiscale strategy is to deal with the variety of retinal vessels in width, intensity, resolution, and orientation; and the progressive fusion is to combine consequent images and meanwhile avoid a sudden fusion of image noise and/or artifacts in space. To quantitatively assess the performance of the algorithm, we tested it on three publicly available databases, namely, DRIVE, STARE, and HRF. The agreement between the computer results and the manual delineation in these databases were quantified by computing their overlapping in both area and length (centerline). The measures include sensitivity, specificity, and accuracy. Results: For the DRIVE database, the sensitivities in identifying vessels in area and length were around 90% and 70%, respectively, the accuracy in pixel classification was around 99%, and the precisions in terms of both area and length were around 94%. For the STARE database, the sensitivities in identifying vessels were around 90% in area and 70% in length, and the accuracy in pixel classification was around 97%. For the HRF database, the sensitivities in identifying vessels were around 92% in area and 83% in length for the healthy subgroup, around 92% in area and 75% in length for the glaucomatous subgroup, around 91% in area and 73% in length for the diabetic retinopathy subgroup. For all three subgroups, the accuracy was around 98%. Conclusions: The experimental results demonstrate that the developed algorithm is capable of identifying retinal vessels depicted in color fundus photographs in a relatively reliable manner.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Balmer Filaments in Tycho’s Supernova Remnant: An Interplay between Cosmic-ray and Broad-neutral Precursors

We present Hα spectroscopic observations and detailed modeling of the Balmer filaments in the supernova remnant (SNR) Tycho (SN 1572). We used GH α FaS (Galaxy Hα Fabry–Pérot Spectrometer) on the William Herschel Telescope with a 3.′4 × 3.′4 field of view, 0.″2 pixel scale, and σ{sub instr}=8.1 km s{sup −1} resolution at 1″ seeing for ∼10 hr, resulting in 82 spatial−spectral bins that resolve the narrow Hα line in the entire SN 1572 northeastern rim. For the first time, we can therefore mitigate artificial line broadening from unresolved differential motion and probe Hα emission parameters in varying shock and ambient medium conditions. Broad Hα line remains unresolved within spectral coverage of 392 km s{sup −1}. We employed Bayesian inference to obtain reliable parameter confidence intervals and to quantify the evidence for models with multiple line components. The median Hα narrow-line (NL) FWHM of all bins and models is W{sub NL}=(54.8±1.8) km s{sup −1} at the 95% confidence level, varying within [35, 72] km s{sup −1} between bins and clearly broadened compared to the intrinsic (thermal) ≈20 km s{sup −1}. Possible line splits are accounted for, significant in ≈18% of the filament, and presumably due to remaining projection effects. We also find widespread evidence for intermediate-line emission of a broad-neutral precursor, with a median W{sub IL}=(180±14) km s{sup −1} (95% confidence). Finally, we present a measurement of the remnant’s systemic velocity, V{sub LSR}=−34 km s{sup −1}, and map differential line-of-sight motions. Our results confirm the existence and interplay of shock precursors in Tycho’s remnant. In particular, we show that suprathermal NL emission is near-universal in SN 1572, and that, in the absence of an alternative explanation, collisionless SNR shocks constitute a viable acceleration source for Galactic TeV cosmic-ray protons.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

SpaceNet 9—Cross-Sensor Alignment of Optical and SAR Imagery

Precise registration of high-resolution synthetic aperture radar (SAR) and optical imagery is necessary for realizing the full potential and benefits of multimodal image analysis. However, two significant challenges presently exist. First, there is a lack of annotated datasets and benchmarks available for high-resolution SAR–optical image registration. Second, an assessment of efficient and reliable image registration methods that can precisely align these modalities is lacking. Here, we present a holistic description of the SpaceNet 9 Challenge and its results. We present a description of the dataset and baseline algorithm along with the results of the challenge, including a description of the winning algorithms. We release the SpaceNet 9 dataset along with open-sourcing the winning algorithms and baseline. The objective of SpaceNet 9 was to compute a dense displacement map that indicates the shift needed to align pixels in an optical image to the pixels in a SAR image. The challenge launched in April 2025 and was active for approximately two months. The top five solutions reduced image alignment error from approximately 34 m to under 13 m for public and private test data, with the best results obtaining a registration error of only 8.5 and 6.7 m on the public testing and private testing dataset, respectively. Usage of pretrained image matching models, robust outlier rejection with RANSAC, and estimating local displacement were common among the top solutions. The results of this challenge provide insight into high-resolution SAR–optical image registration and offer opportunities for future benchmarking in this domain. The baseline algorithm, winning solutions, and datasets are available at https://spacenet.ai/sn9-challenge/.

benchmark datasets↗
DOE OSTI2025

Can We Rely on Satellite Visible/Infrared Microphysical Retrievals of Boundary Layer Clouds in Partially Cloudy Scenes? Implications for Climate Research

This study addresses the longstanding question of the reliability of gridded visible/infrared satellite cloud properties in partially cloudy scenes. By using in-situ cloud probes and airborne Research Scanning Polarimeter (RSP) observations, we analyze bias changes in satellite retrievals from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) geostationary sensor during the ORACLES campaign. Biases in cloud optical depth (τ) and droplet effective radius (r e ) modestly change for cloud area fraction greater than 35%. The agreement between SEVIRI and RSP r e substantially improves when the retrievals are averaged after removing pixels with τ < 3.0, yielding biases indistinguishable from overcast scenes. In addition, satellite and RSP show an excellent agreement for closed- and open-cell stratocumulus clouds, showing that the satellite retrievals capture spatial changes of r e , and confirming that satellites can faithfully reproduce real physical features for optically thick and partially cloudy scenes. We demonstrate that a simple methodology can minimize uncertainties in satellite-based climate studies.

Painemal, David [NASA Langley Research Center, Ham↗
DOE OSTI2023

Sensitivity of Optical Satellites to Estimate Windthrow Tree-Mortality in a Central Amazon Forest

Windthrow (i.e., trees broken and uprooted by wind) is a major natural disturbance in Amazon forests. Images from medium-resolution optical satellites combined with extensive field data have allowed researchers to assess patterns of windthrow tree-mortality and to monitor forest recovery over decades of succession in different regions. Although satellites with high spatial-resolution have become available in the last decade, they have not yet been employed for the quantification of windthrow tree-mortality. Here, we address how increasing the spatial resolution of satellites affects plot-to-landscape estimates of windthrow tree-mortality. We combined forest inventory data with Landsat 8 (30 m pixel), Sentinel 2 (10 m), and WorldView 2 (2 m) imagery over an old-growth forest in the Central Amazon that was disturbed by a single windthrow event in November 2015. Remote sensing estimates of windthrow tree-mortality were produced from Spectral Mixture Analysis and evaluated with forest inventory data (i.e., ground true) by using Generalized Linear Models. Field measured windthrow tree-mortality (3 transects and 30 subplots) crossing the entire disturbance gradient was 26.9 ± 11.1% (mean ± 95% CI). Although the three satellites produced reliable and statistically similar estimates (from 26.5% to 30.3%, p < 0.001), Landsat 8 had the most accurate results and efficiently captured field-observed variations in windthrow tree-mortality across the entire gradient of disturbance (Sentinel 2 and WorldView 2 produced the second and third best results, respectively). As expected, mean-associated uncertainties decreased systematically with increasing spatial resolution (i.e., from Landsat 8 to Sentinel 2 and WorldView 2). However, the overall quality of model fits showed the opposite pattern. We suggest that this reflects the influence of a relatively minor disturbance, such as defoliation and crown damage, and the fast growth of natural regeneration, which were not measured in the field nor can be captured by coarser resolution imagery. Our results validate the reliability of Landsat imagery for assessing plot-to-landscape patterns of windthrow tree-mortality in dense and heterogeneous tropical forests. Satellites with high spatial resolution can improve estimates of windthrow severity by allowing the quantification of crown damage and mortality of lower canopy and understory trees. However, this requires the validation of remote sensing metrics using field data at compatible scales.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Real-Time Cloud, Radiation, and Aircraft Icing Parameters from GOES over the USA

A preliminary new, physically based method for realtime estimation of the probability of icing conditions has been demonstrated using merged GOES-10 and 12 data over the continental United States and southern Canada. The algorithm produces pixel-level cloud and radiation properties as well as an estimate of icing probability with an associated intensity rating Because icing depends on so many different variables, such as aircraft size or air speed, it is not possible to achieve 100% success with this or any other type of approach. This initial algorithm, however, shows great promise for diagnosing aircraft icing and putting it at the correct altitude within 0.5 km most of the time. Much additional research must be completed before it can serve as a reliable input for the operational CIP. The delineation of the icing layer vertical boundaries will need to be improved using either the RUC or balloon soundings or ceilometer data to adjust the cloud base height, a change that would require adjustment of the cloud-top altitude also.

Minnis, Patrick↗
DOE OSTI2026

Segmentation method comparison for residual fiber length measurement across tiled microscopy images

Fiber length distribution (FLD), in part, governs mechanical properties in discontinuous fiber composites, yet manual measurement methods limit the high-throughput characterization needed for materials design optimization. This study compares deep learning segmentation approaches for automated FLD measurement in large-field microscopy, evaluating how method choice affects the microstructural descriptors used in structure-property-processing relationships. A critical challenge is that high-resolution microscopy images (10,000×10,000 pixels) must be tiled for deep learning analysis, fragmenting fibers at boundaries. We demonstrate that segmentation method proves crucial for measurement accuracy. For example, instance segmentation with Slicing Aided Hyper Inference (SAHI) preserves individual fiber integrity across tiles while semantic segmentation prioritizes speed. Comparing against manual measurement of extracted carbon fibers, YOLOv11-SAHI matched manual ground truth (238 μm weighted mean) with 40x speedup (4.5 vs 167 minutes per image). U-Net provides rapid quantification although it is at the cost of reduced accuracy due only reliably measuring stand-alone fibers. Our comparative analysis reveals that instance segmentation with SAHI better preserves length measurements while semantic segmentation prioritizes speed, providing empirical guidance for method selection. The characterization provides essential inputs for mechanical property prediction models and inverse design workflows, accelerating composite materials development cycles.

Additive manufacturing↗
NASA NTRS2015

Improving the Timeliness of Winter Wheat Production Forecast in the United States of America, Ukraine and China Using MODIS Data and NCAR Growing Degree Day Information

Wheat is themost important cereal crop traded on international markets and winter wheat constitutes approximately 80% of global wheat production. Thus, accurate and timely production forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) developed an empirical generalized model for forecasting winter wheat production. Their approach combined BRDF-corrected daily surface reflectance from Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop typemasks. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season, percent wheat within the CMG pixel (area within the CMG pixel occupied by wheat), and the final yields. This method predicts the yield approximately one month to six weeks prior to harvest. In this study, we include Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data in order to improve the winter wheat production forecast by increasing the timeliness of the forecasts while conserving the accuracy of the original model. We apply this modified model to three major wheat-producing countries: the Unites States (US), Ukraine and China from 2001 to 2012. We show that a reliable forecast can be made between one month to a month and a half prior to the peak NDVI (meaning two months to two and a half months prior to harvest), while conserving an accuracy of 10% in the production forecast.

Production↗
DOE OSTI2014

Development of three-wavelength CCD image pyrometer used for the temperature field measurements of continuous casting billets

This paper develops an imaging based three-color pyrometer for the monitoring of temperature distribution in a continuous casting billet. A novel optical device, together with an embedded electronic system, is designed to sequentially collect a dark image and three thermal images with specified wavelengths on a same monochromatic charge-coupled-device (CCD). The three thermal images provide the basis for the determination of target temperature, while the dark image is used to online eliminate the dark noise of CCD with a differential method. This image pyrometer is not only independent of target emissivity but also overcomes the dissimilarity of measuring accuracy between the micro-sensors of CCD resulted from the non-uniformity of pixels’ intensity response and the vignetting of optical system. Furthermore, a precise two-color temperature field measuring model on the CCD pyrometer is established, based on which a self-adaptive light-integration mechanism is presented. Compared with the traditional fixed light-integration method, the measuring range of the pyrometer is greatly extended and its sensitivity in low temperature segment is improved. The test results in a steel factory demonstrate that the pyrometer is capable of meeting the requirement of surface temperature measurements about casting billets. Reliability and accuracy of measurement results are also discussed herein.

42 ENGINEERING↗
DOE OSTI2015

SU-D-201-06: Random Walk Algorithm Seed Localization Parameters in Lung Positron Emission Tomography (PET) Images

Purpose: The objective of this study was to find the best seed localization parameters in random walk algorithm application to lung tumor delineation in Positron Emission Tomography (PET) images. Methods: PET images suffer from statistical noise and therefore tumor delineation in these images is a challenging task. Random walk algorithm, a graph based image segmentation technique, has reliable image noise robustness. Also its fast computation and fast editing characteristics make it powerful for clinical purposes. We implemented the random walk algorithm using MATLAB codes. The validation and verification of the algorithm have been done by 4D-NCAT phantom with spherical lung lesions in different diameters from 20 to 90 mm (with incremental steps of 10 mm) and different tumor to background ratios of 4:1 and 8:1. STIR (Software for Tomographic Image Reconstruction) has been applied to reconstruct the phantom PET images with different pixel sizes of 2×2×2 and 4×4×4 mm{sup 3}. For seed localization, we selected pixels with different maximum Standardized Uptake Value (SUVmax) percentages, at least (70%, 80%, 90% and 100%) SUVmax for foreground seeds and up to (20% to 55%, 5% increment) SUVmax for background seeds. Also, for investigation of algorithm performance on clinical data, 19 patients with lung tumor were studied. The resulted contours from algorithm have been compared with nuclear medicine expert manual contouring as ground truth. Results: Phantom and clinical lesion segmentation have shown that the best segmentation results obtained by selecting the pixels with at least 70% SUVmax as foreground seeds and pixels up to 30% SUVmax as background seeds respectively. The mean Dice Similarity Coefficient of 94% ± 5% (83% ± 6%) and mean Hausdorff Distance of 1 (2) pixels have been obtained for phantom (clinical) study. Conclusion: The accurate results of random walk algorithm in PET image segmentation assure its application for radiation treatment planning and diagnosis.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2011

Miniaturized Airborne Imaging Central Server System

In recent years, some remote-sensing applications require advanced airborne multi-sensor systems to provide high performance reflective and emissive spectral imaging measurement rapidly over large areas. The key or unique problem of characteristics is associated with a black box back-end system that operates a suite of cutting-edge imaging sensors to collect simultaneously the high throughput reflective and emissive spectral imaging data with precision georeference. This back-end system needs to be portable, easy-to-use, and reliable with advanced onboard processing. The innovation of the black box backend is a miniaturized airborne imaging central server system (MAICSS). MAICSS integrates a complex embedded system of systems with dedicated power and signal electronic circuits inside to serve a suite of configurable cutting-edge electro- optical (EO), long-wave infrared (LWIR), and medium-wave infrared (MWIR) cameras, a hyperspectral imaging scanner, and a GPS and inertial measurement unit (IMU) for atmospheric and surface remote sensing. Its compatible sensor packages include NASA s 1,024 1,024 pixel LWIR quantum well infrared photodetector (QWIP) imager; a 60.5 megapixel BuckEye EO camera; and a fast (e.g. 200+ scanlines/s) and wide swath-width (e.g., 1,920+ pixels) CCD/InGaAs imager-based visible/near infrared reflectance (VNIR) and shortwave infrared (SWIR) imaging spectrometer. MAICSS records continuous precision georeferenced and time-tagged multisensor throughputs to mass storage devices at a high aggregate rate, typically 60 MB/s for its LWIR/EO payload. MAICSS is a complete stand-alone imaging server instrument with an easy-to-use software package for either autonomous data collection or interactive airborne operation. Advanced multisensor data acquisition and onboard processing software features have been implemented for MAICSS. With the onboard processing for real time image development, correction, histogram-equalization, compression, georeference, and data organization, fast aerial imaging applications, including the real time LWIR image mosaic for Google Earth, have been realized for NASA fs LWIR QWIP instrument. MAICSS is a significant improvement and miniaturization of current multisensor technologies. Structurally, it has a complete modular and solid-state design. Without rotating hard drives and other moving parts, it is operational at high altitudes and survivable in high-vibration environments. It is assembled from a suite of miniaturized, precision-machined, standardized, and stackable interchangeable embedded instrument modules. These stackable modules can be bolted together with the interconnection wires inside for the maximal simplicity and portability. Multiple modules are electronically interconnected as stacked. Alternatively, these dedicated modules can be flexibly distributed to fit the space constraints of a flying vehicle. As a flexibly configurable system, MAICSS can be tailored to interface a variety of multisensor packages. For example, with a 1,024x1,024 pixel LWIR and a 8,984x6,732 pixel EO payload, the complete MAICSS volume is approximately 7x9x11 in. (=18x23x28 cm), with a weight of 25 lb (=11.4 kg).

Sun, Xiuhong↗
NASA NTRS2015

An Upgrade of the Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Software

The Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) code is used at NASA Langley Research Center to analyze global aeroheating data on wind tunnel models tested in the Langley Aerothermodynamics Laboratory. One-dimensional, semi-infinite heating data derived from IHEAT are used to design thermal protection systems to mitigate the risks due to the aeroheating loads on hypersonic vehicles, such as re-entry vehicles during descent and landing procedures. This code was originally written in the PV-WAVE programming language to analyze phosphor thermography data from the two-color, relativeintensity system developed at Langley. To increase the efficiency, functionality, and reliability of IHEAT, the code was migrated to MATLAB syntax and compiled as a stand-alone executable file labeled version 4.0. New features of IHEAT 4.0 include the options to batch process all of the data from a wind tunnel run, to map the two-dimensional heating distribution to a three-dimensional computer-aided design model of the vehicle to be viewed in Tecplot, and to extract data from a segmented line that follows an interesting feature in the data. Results from IHEAT 4.0 were compared on a pixel level to the output images from the legacy code to validate the program. The differences between the two codes were on the order of 10-5 to 10-7. IHEAT 4.0 replaces the PV-WAVE version as the production code for aeroheating experiments conducted in the hypersonic facilities at NASA Langley.

Mason, Michelle L.↗
NASA NTRS2016

Features of the Upgraded Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Software

The Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) software is used at the NASA Langley Research Center to analyze global aeroheating data on wind tunnel models tested in the Langley Aerothermodynamics Laboratory. One-dimensional, semi-infinite heating data derived from IHEAT are used in the design of thermal protection systems for hypersonic vehicles that are exposed to severe aeroheating loads, such as reentry vehicles during descent and landing procedures. This software program originally was written in the PV-WAVE(Registered Trademark) programming language to analyze phosphor thermography data from the two-color, relative-intensity system developed at Langley. To increase the efficiency, functionality, and reliability of IHEAT, the program was migrated to MATLAB(Registered Trademark) syntax and compiled as a stand-alone executable file labeled version 4.0. New features of IHEAT 4.0 include the options to perform diagnostic checks of the accuracy of the acquired data during a wind tunnel test, to extract data along a specified multi-segment line following a feature such as a leading edge or a streamline, and to batch process all of the temporal frame data from a wind tunnel run. Results from IHEAT 4.0 were compared on a pixel level to the output images from the legacy software to validate the program. The absolute differences between the heat transfer data output from the two programs were on the order of 10(exp -5) to 10(exp -7). IHEAT 4.0 replaces the PV-WAVE(Registered Trademark) version as the production software for aeroheating experiments conducted in the hypersonic facilities at NASA Langley.

Mason, Michelle L.↗
DOE OSTI2013

A method for removing arm backscatter from EPID images

Purpose: To develop a method for removing the support arm backscatter from images acquired using current Varian electronic portal imaging devices (EPIDs).Methods: The effect of arm backscatter on EPID images was modeled using a kernel convolution method. The parameters of the model were optimized by comparing on-arm images to off-arm images. The model was used to develop a method to remove the effect of backscatter from measured EPID images. The performance of the backscatter removal method was tested by comparing backscatter corrected on-arm images to measured off-arm images for 17 rectangular fields of different sizes and locations on the imager. The method was also tested using on- and off-arm images from 42 intensity modulated radiotherapy (IMRT) fields.Results: Images generated by the backscatter removal method gave consistently better agreement with off-arm images than images without backscatter correction. For the 17 rectangular fields studied, the root mean square difference of in-plane profiles compared to off-arm profiles was reduced from 1.19% (standard deviation 0.59%) on average without backscatter removal to 0.38% (standard deviation 0.18%) when using the backscatter removal method. When comparing to the off-arm images from the 42 IMRT fields, the mean {gamma} and percentage of pixels with {gamma} < 1 were improved by the backscatter removal method in all but one of the images studied. The mean {gamma} value (1%, 1 mm) for the IMRT fields studied was reduced from 0.80 to 0.57 by using the backscatter removal method, while the mean {gamma} pass rate was increased from 72.2% to 84.6%.Conclusions: A backscatter removal method has been developed to estimate the image acquired by the EPID without any arm backscatter from an image acquired in the presence of arm backscatter. The method has been shown to produce consistently reliable results for a wide range of field sizes and jaw configurations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Calibration of a single-point laser range finder and a camera

Laser and visual imagery have been broadly utilized in computer vision and mobile robotics applications because these sensors provide complementary information. Since the single-point laser range finder can provide depth information of a single pixel in the observed image, its price and size is very suitable for handheld devices or very lightweight robotic platforms. So the combination of a single-point laser range finder and a camera has become increasingly useful in recent report and industrial applications. In this paper, we propose two accurate calibration methods for determining the position and direction of the laser range finder relative to the camera. Furthermore, we can accomplish calibration even without observing the laser spot in camera image. We evaluate the two methods through experiments which demonstrate their efficiency and high reliability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

The sloan digital sky survey reverberation mapping project: velocity shifts of quasar emission lines

Quasar emission lines are often shifted from the systemic velocity due to various dynamical and radiative processes in the line-emitting region. The level of these velocity shifts depends both on the line species and on quasar properties. We study velocity shifts for the line peaks (not the centroids) of various narrow and broad quasar emission lines relative to systemic using a sample of 849 quasars from the Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project. The coadded (from 32 epochs) spectra of individual quasars have sufficient signal-to-noise ratio (S/N) to measure stellar absorption lines to provide reliable systemic velocity estimates, as well as weak narrow emission lines. The large dynamic range in quasar luminosity (∼2 dex) of the sample allowed us to explore potential luminosity dependence of the velocity shifts. We derive average line peak velocity shifts as a function of quasar luminosity for different lines, and quantify their intrinsic scatter. We further quantify how well the peak velocity can be measured as a function of continuum S/N, and demonstrate that there is no systematic bias in the velocity measurements when S/N is degraded to as low as ∼3 per SDSS pixel (∼69 km s{sup −1}). Based on the observed line shifts, we provide empirical guidelines on redshift estimation from [O ii] λ3727, [O iii] λ5007, [Ne v] λ3426, Mg ii, C iii], He ii λ1640, broad Hβ, C iv, and Si iv, which are calibrated to provide unbiased systemic redshifts in the mean, but with increasing intrinsic uncertainties of 46, 56, 119, 205, 233, 242, 400, 415, and 477 km s{sup −1}, in addition to the measurement uncertainties. These results demonstrate the infeasibility of measuring quasar redshifts to better than ∼200 km s{sup −1} with only broad lines.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Neutron fluence and energy reconstruction with the IRSN recoil detector μ-TPC at 27 keV, 144 keV and 565 keV

The French Institute for Radioprotection and Nuclear Safety (IRSN), associated to the French Metrology Institute (LNE), is developing a time projection chamber using a Micromegas anode: μ-TPC. This work is carried out in collaboration with the Laboratory of Subatomic Physics and Cosmology (LPSC). The aim is to characterize with a primary procedure the energy distribution of neutron fluence in the energy range 8 keV - 1 MeV. The time projection chambers are gaseous detectors, which are able to measure charged particles energy and to reconstruct their track if a pixelated anode is used. In our case, the gas is used as a (n, p) converter in order to detect neutrons down to few keV. Coming from elastic collisions with neutrons, recoil protons lose a part of their kinetic energy by ionizing the gas. The ionization electrons are drifted toward a pixelated anode (2D projection), read at 50 MHz by a self-triggered electronic system to obtain the third track dimension. The neutron energy is reconstructed event by event thanks to proton scattering angle and proton energy measurements. The scattering angle is deduced from the 3D track. The proton energy is obtained by charge collection measurements, knowing the ionization quenching factor (i.e. the part of proton kinetic energy lost by ionizing the gas). The fluence is calculated thanks to the detected events number and the simulated detector response. The μ-TPC is a new reliable detector which enables to measure energy distribution of the neutron fluence without deconvolution or neutron calibration contrary to usual gaseous counters. The μ-TPC is still being developed and measurements have been carried out at the AMANDE facility, with neutrons energies going from 8 keV to 565 keV. After the context and the μ-TPC working principle presentation, measurements of the neutron energy and fluence at 27.2 keV, 144 keV and 565 keV are shown and compared to the complete detector simulation. This work shows the first direct reconstruction of neutron energy and fluence, simultaneously, at 27.2 keV in a continuous irradiation mode. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗