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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 OSTI2023

Photothermal heterodyne imaging of micron-sized objects

Micron-sized dye-doped polymer beads were imaged using transmitted/reflected light microscopy and photothermal heterodyne imaging (PHI) measurements. The transmitted/reflected light images show distinct ring patterns that are attributed to diffraction effects and/or internal reflections within the beads. In the PHI experiments pump laser induced heating changes the refractive index and size of the bead, which causes changes in the diffraction pattern and internal reflections. This creates an analogous ring pattern in the PHI images. The ring pattern disappears in both the reflected light and PHI experiments when an incoherent light source is used as a probe. When the beads are imaged in an organic medium heat transfer changes the refractive index of the environment, and gives rise to a ring pattern external to the beads in the PHI images. This causes the beads to appear larger than their physical dimensions in PHI experiments. This external signal does not appear when the beads are imaged in air because the refractive index changes in air are very small.

Bhandari, Janak (ORCID:0000000188423259)↗
DOE OSTI2017

Color Me Intrigued: the Discovery of iPTF 16fnm, a Supernova 2002cx-like Object

Modern wide-field, optical time-domain surveys must solve a basic optimization problem: maximize the number of transient discoveries or minimize the follow-up needed for the new discoveries. Here, we describe the Color Me Intrigued experiment, the first from the intermediate Palomar Transient Factory (iPTF) to search for transients simultaneously in the $g_\mathrm{PTF}$- and $R_\mathrm{PTF}$-bands. During the course of this experiment we discovered iPTF$\,$16fnm, a new member of the 02cx-like subclass of type Ia supernovae (SNe). iPTF$\,$16fnm peaked at $M_{g_\mathrm{PTF}} = -15.09 \pm 0.17 \; \mathrm{mag}$, making it the second least-luminous known type Ia SN. iPTF 16fnm exhibits all the hallmarks of the 02cx-like class: (i) low luminosity at peak, (ii) low ejecta velocities, and (iii) a non-nebular spectra several months after peak. Spectroscopically, iPTF$\,$16fnm exhibits a striking resemblence to 2 other low-luminosity 02cx-like SNe: SNe 2007qd and 2010ae. iPTF$\,$16fnm and SN 2005hk decline at nearly the same rate, despite a 3 mag difference in brightness at peak. When considering the full subclass of 02cx-like SNe, we do not find evidence for a tight correlation between peak luminosity and decline rate in either the $g'$ or $r'$ band. We further examine the $g' - r'$ evolution of 02cx-like SNe and find that their unique color evolution can be used to separate them from 91bg-like and normal type Ia SNe. This selection function will be especially important in the spectroscopically incomplete Zwicky Transient Facility/Large Synoptic Survey Telescope era. We measure the relative rate of 02cx-like SNe to normal SNe Ia and find $r_{N_{02cx}/N_{Ia}} = 25^{+75}_{-18.5}\%$. Finally, we close by recommending that LSST periodically evaluate, and possibly update, its observing cadence to maximize transient science.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

De-biased populations of Kuiper belt objects from the deep ecliptic survey

The Deep Ecliptic Survey (DES) was a survey project that discovered hundreds of Kuiper Belt objects from 1998 to 2005. Extensive follow-up observations of these bodies has yielded 304 objects with well-determined orbits and dynamical classifications into one of several categories: Classical, Scattered, Centaur, or 16 mean-motion resonances with Neptune. The DES search fields are well documented, enabling us to calculate the probability on each frame of detecting an object with its particular orbital parameters and absolute magnitude at a randomized point in its orbit. The detection probabilities range from a maximum of 0.32 for the 3:2 resonant object 2002 GF {sub 32} to a minimum of 1.5 × 10{sup –7} for the faint Scattered object 2001 FU {sub 185}. By grouping individual objects together by dynamical classes, we can estimate the distributions of four parameters that define each class: semimajor axis, eccentricity, inclination, and object size. The orbital element distributions (a, e, and i) were fit to the largest three classes (Classical, 3:2, and Scattered) using a maximum likelihood fit. Using the absolute magnitude (H magnitude) as a proxy for the object size, we fit a power law to the number of objects versus H magnitude for eight classes with at least five detected members (246 objects). The Classical objects are best fit with a power-law slope of α = 1.02 ± 0.01 (observed from 5 ≤ H ≤ 7.2). Six other dynamical classes (Scattered plus five resonances) have consistent magnitude distribution slopes with the Classicals, provided that the absolute number of objects is scaled. Scattered objects are somewhat more numerous than Classical objects, while there are only a quarter as many 3:2 objects as Classicals. The exception to the power law relation is the Centaurs, which are non-resonant objects with perihelia closer than Neptune and therefore brighter and detectable at smaller sizes. Centaurs were observed from 7.5 < H < 11, and that population is best fit by a power law with α = 0.42 ± 0.02. This is consistent with a knee in the H-distribution around H = 7.2 as reported elsewhere. Based on the Classical-derived magnitude distribution, the total number of objects (H ≤ 7) in each class is: Classical (2100 ± 300 objects), Scattered (2800 ± 400), 3:2 (570 ± 80), 2:1 (400 ± 50), 5:2 (270 ± 40), 7:4 (69 ± 9), 5:3 (60 ± 8). The independent estimate for the number of Centaurs in the same H range is 13 ± 5. If instead all objects are divided by inclination into 'Hot' and 'Cold' populations, following Fraser et al., we find that α{sub Hot} = 0.90 ± 0.02, while α{sub Cold} = 1.32 ± 0.02, in good agreement with that work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Models for HEU objects in the NDSE IV and III series

A Neutron-Diagnosed Subcritical Experiment (NDSE) proof-of-principle setup exists at area-11 in Nevada. An exquisite set of gamma-ray flux die-away data has been obtained at this facility for a number of highly-enriched uranium (HEU) objects, including objects referred to as IV, IV', IV'' (the object IV series), IIIa, and IIIb (the object III series). These objects are constructed via a set of hemi-spherical concentric HEU shells (known as the Rocky Flats shells), surrounded by a sphere of aluminum (Al), encased in an outer sphere of high-density polyethylene (HDP). The “as built” detailed MCNP-calculated k eff values obtained by Goorley, for the object IV and III series, are listed in Table II. These model calculations contain detailed information about the inner and outer radii and masses of each hemi-shell used to make each of the objects. Objects IV', and IV'' were obtained by replacing inner HEU shells with Al. The low k eff of object IIIa was obtained by substituting a single HEU shell, with an inner radius of ~5 cm, with an Al shell. For object IIIb the substitution was a little further out but only in one hemi-shell. Except for the inner most shell (ball), all HEU shells have a thickness close to 0.333 cm. Previously the k eff of objects IV', IV'', IIIa, and IIIb, were determined from measured gamma ray die-away data via an analysis using a simple modification of the density of the HEU in our simple three layered model (HEU, Al, and HDP) of object IV including the outer safety can. This was done to see the quality of the inference and investigate any limitations associated with not using detailed information about the known perturbations used to make these objects. In this work, we built models (priors) of objects IV', IV'', IIIa, and IIIb that make use of our knowledge about the nature of the perturbations. With these models, instead of adjusting the density of the HEU in our object IV model to match the data from objects IV', IV'', IIIa, and IIIb, as done previously, we will be able to (in future studies) adjust r AL , and r i to infer the k eff of the corresponding objects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Data association algorithm for large-scale multi-object tracking with complex interactions

We present an online multi-object tracking algorithm to track multiple objects across a large number of image frames. Our work is motivated by the need to study evolution of nanoscale objects by transmission electron microscopy. The proposed approach is based on the existing multi-way data association tracking algorithm that is capable of tracking interacting objects with complex behaviors (i.e., merge, split, overlap, and appearance or disappearance). The multi-way data association is an offline algorithm to associate objects across all image frames at one step with a global optimization, which does not scale very well for large number of image frames. The proposed online tracking algorithm processes image frames as they arrive by detecting all objects in the newly arrived image frame and making the associations of the objects to those detected from the previous frame by the multi-way data association. This frameby-frame association scheme can cause fragmented traces of the objects that are occasionally misdetected for some image frames. We overcome this issue by allowing previously unassociated objects to be associated when the objects reappear within a fixed number of future image frames, namely the frame-delayed association. We combine the multi-way data association with the frame-delayed association to be able to track interacting objects with accurate handling of object disappearance events. The proposed method is validated through applications to simulated multi-object tracking problem and a real multi-object tracking problem. Here, the outcome of the proposed method is compared with four state-of-the-art algorithms.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Size-Dependent Characteristics of Surface-Rooted Three-Dimensional Convective Objects in Continental Shallow Cumulus Simulations

A segmentation algorithm is applied to high resolution simulations of shallow continental convection to identify individual convective 3D objects within the convective boundary layer, in order to investigate which properties of the objects vary with the object width. The study analyses the geometry of the objects, along with their profiles of vertical velocity and total water, to assess various assumptions often used in spectral mass-flux convection schemes. The methodology of this paper is unique in that we use (a) a novel application of the watershed algorithm to detect individual objects in the constantly evolving continental boundary layer efficiently, and (b) an unprecedentedly large number of simulations being analyzed. In total, 26 days of LASSO simulations at the Atmospheric Radiation Measurement Southern Great Plains site are analyzed, yielding roughly one million objects. Plume-like surface-rooted objects are found to be omnipresent, the vertical extent of which is strongly dependent on the object width. The vertical velocity and moisture anomaly profiles of the widest objects are roughly consistent with the classic buoyancy-driven rising plume model. The kinematic and thermodynamic properties of the objects vary with object width. This width dependence is strongest above cloud base, but much weaker below. Finally the impact of neglecting the contribution of covariances to the vertical moisture flux, which is commonly used in mass-flux parameterizations, is investigated. The average effect of neglecting covariances increases linearly with object width, leading to a 20% flux underestimation for 2 km wide objects. Implications of the results for spectral convection scheme development are briefly discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Foreign object detection and removal to improve automated analysis of chest radiographs

Purpose: Chest radiographs commonly contain projections of foreign objects, such as buttons, brassier clips, jewellery, or pacemakers and wires. The presence of these structures can substantially affect the output of computer analysis of these images. An automated method is presented to detect, segment, and remove foreign objects from chest radiographs.Methods: Detection is performed using supervised pixel classification with a kNN classifier, resulting in a probability estimate per pixel to belong to a projected foreign object. Segmentation is performed by grouping and post-processing pixels with a probability above a certain threshold. Next, the objects are replaced by texture inpainting.Results: The method is evaluated in experiments on 257 chest radiographs. The detection at pixel level is evaluated with receiver operating characteristic analysis on pixels within the unobscured lung fields and an A{sub z} value of 0.949 is achieved. Free response operator characteristic analysis is performed at the object level, and 95.6% of objects are detected with on average 0.25 false positive detections per image. To investigate the effect of removing the detected objects through inpainting, a texture analysis system for tuberculosis detection is applied to images with and without pathology and with and without foreign object removal. Unprocessed, the texture analysis abnormality score of normal images with foreign objects is comparable to those with pathology. After removing foreign objects, the texture score of normal images with and without foreign objects is similar, while abnormal images, whether they contain foreign objects or not, achieve on average higher scores.Conclusions: The authors conclude that removal of foreign objects from chest radiographs is feasible and beneficial for automated image analysis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Impact of bowtie filter and object position on the two-dimensional noise power spectrum of a clinical MDCT system

Purpose: Noise characteristics of clinical multidetector CT (MDCT) systems can be quantified by the noise power spectrum (NPS). Although the NPS of CT has been extensively studied in the past few decades, the joint impact of the bowtie filter and object position on the NPS has not been systematically investigated. This work studies the interplay of these two factors on the two dimensional (2D) local NPS of a clinical CT system that uses the filtered backprojection algorithm for image reconstruction. Methods: A generalized NPS model was developed to account for the impact of the bowtie filter and image object location in the scan field-of-view (SFOV). For a given bowtie filter, image object, and its location in the SFOV, the shape and rotational symmetries of the 2D local NPS were directly computed from the NPS model without going through the image reconstruction process. The obtained NPS was then compared with the measured NPSs from the reconstructed noise-only CT images in both numerical phantom simulation studies and experimental phantom studies using a clinical MDCT scanner. The shape and the associated symmetry of the 2D NPS were classified by borrowing the well-known atomic spectral symbols s, p, and d, which correspond to circular, dumbbell, and cloverleaf symmetries, respectively, of the wave function of electrons in an atom. Finally, simulated bar patterns were embedded into experimentally acquired noise backgrounds to demonstrate the impact of different NPS symmetries on the visual perception of the object. Results: (1) For a central region in a centered cylindrical object, an s-wave symmetry was always present in the NPS, no matter whether the bowtie filter was present or not. In contrast, for a peripheral region in a centered object, the symmetry of its NPS was highly dependent on the bowtie filter, and both p-wave symmetry and d-wave symmetry were observed in the NPS. (2) For a centered region-ofinterest (ROI) in an off-centered object, the symmetry of its NPS was found to be different from that of a peripheral ROI in the centered object, even when the physical positions of the two ROIs relative to the isocenter were the same. (3) The potential clinical impact of the highly anisotropic NPS, caused by the interplay of the bowtie filter and position of the image object, was highlighted in images of specific bar patterns oriented at different angles. The visual perception of the bar patterns was found to be strongly dependent on their orientation. Conclusions: The NPS of CT depends strongly on the bowtie filter and object position. Even if the location of the ROI with respect to the isocenter is fixed, there can be different symmetries in the NPS, which depend on the object position and the size of the bowtie filter. For an isolated off-centered object, the NPS of its CT images cannot be represented by the NPS measured from a centered object.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Digital Twin for Hydropower System Object Modeling: Alder Dam (FY2023)

Hydropower is the world's largest source of renewable electricity, and hydropower plants are distributed all over the world. Typical major components of a hydropower plant are the governor, excitation, generator, thrust bearing, hydraulic turbine, transformer, the main lead, metering and control, tailwater depression, and dissolved oxygen. For each component, various measures are taken. The measurements are acquired by various heterogeneous systems, including standalone sensors, programmable logic controllers (PLC), Supervisory control and data acquisition (SCADA), Internet of Things (IoT), and data acquisition and integration platforms such as OSI/PI. The measured data are often archived within the plant by a data management platform, and many institutions have cloud-based archive systems, such as Hydropower Research Institution (HRI), U.S. Army Corps of Engineers (USACE), and Columbia River Data Access in Real Time (DART). Object Modeling is a general framework for designing information systems. It focuses on objects, the actions they perform, and the messages they send to one another to cause those actions to be taken. The major differences among object modeling, network modeling, data modeling, and process modeling are that in the first we focus on the actions in response to information, objects which form the system, the actions they perform, and how they pass information to one another, while in the second we concentrate on where, when and how much information is moved, while in the third we focus on what information is moved and where it is moved, while in the last we focus on how it is moved and when it is moved. Object modeling was developed basically as a method to develop object-oriented systems and to support object-oriented programming. It describes the static structure of the system. The object Modeling Technique is easy to draw and use. That is why we choose object modeling to connect physical hydropower plants to Digital Twin. It recognizes the objects and the relationship between them. It identifies the attributes and functions of each class. Dynamic Modeling: It explains how objects respond to events. Functional Modeling indicates the processes executed in an object and how data changes when it moves to objects. It has been used in many applications like telecommunication, transportation, etc.

13 HYDRO ENERGY↗
DOE OSTI2021

Quantifying the Multi-Objective Cost of Uncertainty

Various real-world applications involve modeling complex systems with immense uncertainty and optimizing multiple objectives based on the uncertain model. Quantifying the impact of the model uncertainty on the given operational objectives is critical for designing optimal experiments that can most effectively reduce the uncertainty that affect the objectives pertinent to the application at hand. In this paper, we propose the concept of mean multi-objective cost of uncertainty (multi-objective MOCU) that can be used for objective-based quantification of uncertainty for complex uncertain systems considering multiple operational objectives. We provide several illustrative examples that demonstrate the concept and strengths of the proposed multi-objective MOCU. Furthermore, we present a real-world example based on the mammalian cell cycle network to demonstrate how the multi-objective MOCU can be used for quantifying the operational impact of model uncertainty when there are multiple, possibly competing, objectives.

42 ENGINEERING↗
DOE OSTI2014

Near-infrared (JHK) spectroscopy of young stellar and substellar objects in orion

We performed low-resolution (R ∼ 40) near-infrared (0.9-2.4 μm) multi-object spectroscopy of 240 isolated point sources having apparent H-band magnitudes between 9 and 18 in the central 5' × 6' of the Orion Trapezium cluster. The observations were performed over four nights at the Canada-France-Hawaii Telescope using the visiting instrument SIMON, an infrared imager and multi-object spectrograph. We present the spectra of 104 objects with accurately derived spectral types including 7 new objects having masses below the hydrogen-burning limit, and 6 objects with masses below the deuterium-burning limit. The spectral classification is performed by fitting previously classified spectral templates of dwarf stars (K4-M3) and optically classified young stellar and substellar objects (M4-L0), to the entire 0.9-2.4 μm spectral energy distribution in order to assign a spectral type and visual extinction for each object. Of the 104 objects studied, 44 have been previously classified spectroscopically using various techniques. We perform a rigorous comparison between the previous classifications and our own and find them to be in good agreement. Using the dereddened H-band magnitudes, the classified objects are used to create an Hertzsprung-Russell diagram for the cluster. We find that the previous age estimates of ∼1 Myr to be consistent with our results. Consistent with previous studies, numerous objects are observed to have luminosities several magnitudes above the 1 Myr isochrone. Numerous objects exhibiting emission features in the J band are also reported.

79 ASTRONOMY AND ASTROPHYSICS↗