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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Recovery of Forest Structure Following Large-Scale Windthrows in the Northwestern Amazon

The dynamics of forest recovery after windthrows (i.e., broken or uprooted trees by wind) are poorly understood in tropical forests. The Northwestern Amazon (NWA) is characterized by a higher occurrence of windthrows, greater rainfall, and higher annual tree mortality rates (~2%) than the Central Amazon (CA). We combined forest inventory data from three sites in the Iquitos region of Peru, with recovery periods spanning 2, 12, and 22 years following windthrow events. Study sites and sampling areas were selected by assessing the windthrow severity using remote sensing. At each site, we recorded all trees with a diameter at breast height (DBH) ≥ 10 cm along transects, capturing the range of windthrow severity from old-growth to highly disturbed (mortality > 60%) forest. Across all damage classes, tree density and basal area recovered to >90% of the old-growth values after 20 years. Aboveground biomass (AGB) in old-growth forest was 380 (±156) Mg ha -1 . In extremely disturbed areas, AGB was still reduced to 163 (±68) Mg ha -1 after 2 years and 323 (± 139) Mg ha -1 after 12 years. This recovery rate is ~50% faster than that reported for Central Amazon forests. The faster recovery of forest structure in our study region may be a function of its higher productivity and adaptability to more frequent and severe windthrows. These varying rates of recovery highlight the importance of extreme wind and rainfall on shaping gradients of forest structure in the Amazon, and the different vulnerabilities of these forests to natural disturbances whose severity and frequency are being altered by climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification

Learning the representation of shape cues in 2D & 3D objects for recognition is a fundamental task in computer vision. Deep neural networks (DNNs) have shown promising performance on this task. Due to the large variability of shapes, accurate recognition relies on good estimates of model uncertainty, ignored in traditional training of DNNs, typically learned via stochastic optimization. This paper leverages recent advances in stochastic gradient Markov Chain Monte Carlo (SG-MCMC) to learn weight uncertainty in DNNs. It yields principled Bayesian interpretations for the commonly used Dropout/DropConnect techniques and incorporates them into the SG-MCMC framework. Extensive experiments on 2D & 3D shape datasets and various DNN models demonstrate the superiority of the proposed approach over stochastic optimization. Our approach yields higher recognition accuracy when used in conjunction with Dropout and Batch-Normalization.

convolutional neural network↗
DOE OSTI2021

Solid Phase Gradient Alloying Method via ShAPE

Alloying has been used to confer desirable properties to various metallic systems since the bronze age. For example, Ni, Mn, and Cr are alloyed into an Fe matrix to make steel, which has improved strength and corrosion resistance (as displayed in Fig. 1). In addition to the type of alloying elements, the amount of alloying elements added into a matrix is also very critical for a material’s mechanical property, physical property, machinability, and cost. Conventionally, new alloys are discovered by combining alloy precursors and elemental constituents into a mixture and melting them together. The solidified product or ingot represents a usually non-homogeneous combination of the chemistry with a microstructure dictated by the physics of solidification. It is time and energy intensive to optimize the alloying amounts via the casting process and hence, economically not conducive to rapid alloy discovery. In addition, the cast microstructure seen in the as-cast ingot is often not the ideal, nor even desired structure for optimized performance. Cast materials often need further processing such as homogenization, annealing, and deformation work put in through rolling, forging, extruding, etc. to have favorable microstructures and properties. A faster method to discover new alloy combinations and evaluate them in their worked or processed form is needed. Recently, Laser Engineered Net Shaping was applied to fabricate gradient compositional material for alloy designing. However, the mechanical properties of this gradient alloy were poor due to the existence of impurities, oxidation and cracks that are inherent in the melt-solidification process. Because of these limitations, we propose to use a solid-phase process (ShAPE) to create bulk materials (extrudates) that vary in composition from one end of the extruded solid to the other. Various manufacturing methods for alloy design including conventional casting method, laser based combinatorial method and current solid phase gradient alloying method are displayed and compared in Fig. 2. ShAPE machine and a schematic of ShAPE process are displayed in Fig. 3. Starting material is processed by a rotating and plunging die to form an extrudate. We are proposing through this methodology to invent a new, bulk-scale combinatorial technique. With this novel technique, alloying element can be dissolved into the matrix with a continued gradient without bulk melting. Formation of inter-metallics and defects originating from melt processing can be avoided. In addition, the ShAPE process creates the mixed alloy chemistry, and meanwhile subjects the material to severe plastic strain, which induces the favorable “worked” microstructure. Products from the ShAPE process can be tested in hardness directly providing a path to rapid evaluation of mechanical properties. The ability to create graded structures using friction stir processing (FSP) has been demonstrated, however using the ShAPE process we believe will lead to much faster and higher fidelity results. When combined with high throughput screening methods of physical, mechanical and microstructural property characterization, efficiency and accuracy of alloy design can be significantly improved.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Shape optimization using a NURBS-based interface-enriched generalized FEM

This study presents a gradient-based shape optimization over a fixed mesh using a non-uniform rational B-splines-based interface-enriched generalized finite element method, applicable to multi-material structures. In the proposed method, non-uniform rational B-splines are used to parameterize the design geometry precisely and compactly by a small number of design variables. An analytical shape sensitivity analysis is developed to compute derivatives of the objective and constraint functions with respect to the design variables. Subtle but important new terms involve the sensitivity of shape functions and their spatial derivatives. As a result, verification and illustrative problems are solved to demonstrate the precision and capability of the method.

42 ENGINEERING↗
DOE OSTI2019

Shape-preserving machining produces gradient nanolaminate medium entropy alloys with high strain hardening capability

A high density of grain boundaries can potentially increase structural materials' strength, but at the expense of losing the materials' strain hardening ability at high flow stress levels. However, endowing materials with grain size gradients and a high density of internal interfaces can simultaneously increase the strength and strain hardening ability. This applies particularly for through-thickness gradients of nanoscale interface structures. In this work, we apply a machining method that produces metals with nanoscale interface gradients. Conventional bulk plastic deformation such as rolling, a process applied annually to about 2 billion tons of material, aims to reduce the metal thickness. We have modified this process by introducing severe strain path changes, realized by leading the sheet through a U-turn while preserving its shape, an approach known as ‘hard turning’. Furthermore, we applied this process at both room temperature and 77 K to a NiCrCo medium entropy alloy. Micropillar compression was conducted to evaluate the mechanical response. After hard turning at room temperature, the surface microstructure obtained a ~50% increase in yield stress (0.9 GPa) over the original state with homogeneous grain size (0.4 GPa), but the initial strain hardening rate did not show significant improvement. However, after hard turning at 77 k, the gradient nanolaminate structure tripled in yield stress and more than doubled its initial strain hardening rate. The improvements were achieved by introducing a specific microstructure that consists of gradient nanolaminates in the form of nanospaced twins and martensite in the face center cubic (fcc) phase. This microstructure was formed only at cryogenic temperature. It was found after turning at room temperature that only nanospaced twins were present in the fcc phase inside nanolaminates that had formed at the surface. The origin of the enhanced strain hardening mechanism was studied. Joint density functional theory (DFT) and axial next nearest neighbor Ising (ANNNI) models were used to explain the temperature-dependent phase formation of the NiCrCo nanolaminate at the surface of the hard-turned material.

36 MATERIALS SCIENCE↗
DOE OSTI2023

MaNGA DynPop – II. Global stellar population, gradients, and star-formation histories from integral-field spectroscopy of 10K galaxies: link with galaxy rotation, shape, and total-density gradients

ABSTRACT This is the second paper of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) Dynamics and stellar Population (DynPop) series, which analyses the global stellar population, radial gradients, and non-parametric star-formation history of ∼10K galaxies from the MaNGA Survey final data release 17 and relates them with dynamical properties of galaxies. We confirm the correlation between the stellar population properties and the stellar velocity dispersion σe, but also find that younger galaxies are more metal-poor at fixed σe. Stellar age, metallicity, and mass-to-light ratio (M*/L) all decrease with increasing galaxy rotation, while their radial gradients become more negative (i.e. lower value at the outskirts). The exception is the slow rotators, which also appear to have significantly negative metallicity gradients, confirming the mass–metallicity gradient correlation. Massive disc galaxies in the green valley, on the $(\sigma _{\rm e},\rm age)$ plane, show the most negative age and metallicity gradients, consistent with their old central bulges surrounded by young star-forming discs and metal-poor gas accretion. Galaxies with high σe, steep total mass-density slope, low dark matter fraction, high M*/L, and high metallicity have the highest star-formation rate at earlier times, and are currently quenched. We also discover a population of low-mass star-forming galaxies with low rotation but physically distinct from the massive slow rotators. A catalogue of these stellar population properties is provided publicly.

Astronomy & Astrophysics↗
DOE OSTI2014

Semiautomatic segmentation of aortic valve from sequenced ultrasound image using a novel shape-constraint GCV model

Purpose: Effective and accurate segmentation of the aortic valve (AV) from sequenced ultrasound (US) images remains a technical challenge because of intrinsic factors of ultrasound images that impact the quality and the continuous changes of shape and position of segmented objects. In this paper, a novel shape-constraint gradient Chan-Vese (GCV) model is proposed for segmenting the AV from time serial echocardiography. Methods: The GCV model is derived by incorporating the energy of the gradient vector flow into a CV model framework, where the gradient vector energy term is introduced by calculating the deviation angle between the inward normal force of the evolution contour and the gradient vector force. The flow force enlarges the capture range and enhances the blurred boundaries of objects. This is achieved by adding a circle-like contour (constructed using the AV structure region as a constraint shape) as an energy item to the GCV model through the shape comparison function. This shape-constrained energy can enhance the image constraint force by effectively connecting separate gaps of the object edge as well as driving the evolution contour to quickly approach the ideal object. Because of the slight movement of the AV in adjacent frames, the initial constraint shape is defined by users, with the other constraint shapes being derived from the segmentation results of adjacent sequence frames after morphological filtering. The AV is segmented from the US images by minimizing the proposed energy function. Results: To evaluate the performance of the proposed method, five assessment parameters were used to compare it with manual delineations performed by radiologists (gold standards). Three hundred and fifteen images acquired from nine groups were analyzed in the experiment. The area-metric overlap error rate was 6.89% ± 2.88%, the relative area difference rate 3.94% ± 2.63%, the average symmetric contour distance 1.08 ± 0.43 mm, the root mean square symmetric contour distance 1.37 ± 0.52 mm, and the maximum symmetric contour distance was 3.57 ± 1.72 mm. Conclusions: Compared with the CV model, as a result of the combination of the gradient vector and neighborhood shape information, this semiautomatic segmentation method significantly improves the accuracy and robustness of AV segmentation, making it feasible for improved segmentation of aortic valves from US images that have fuzzy boundaries.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

SU-F-J-95: Impact of Shape Complexity On the Accuracy of Gradient-Based PET Volume Delineation

Purpose: Explore correlation of tumor complexity shape with PET target volume accuracy when delineated with gradient-based segmentation tool. Methods: A total of 24 clinically realistic digital PET Monte Carlo (MC) phantoms of NSCLC were used in the study. The phantom simulated 29 thoracic lesions (lung primary and mediastinal lymph nodes) of varying size, shape, location, and {sup 18}F-FDG activity. A program was developed to calculate a curvature vector along the outline and the standard deviation of this vector was used as a metric to quantify a shape’s “complexity score”. This complexity score was calculated for standard geometric shapes and MC-generated target volumes in PET phantom images. All lesions were contoured using a commercially available gradient-based segmentation tool and the differences in volume from the MC-generated volumes were calculated as the measure of the accuracy of segmentation. Results: The average absolute percent difference in volumes between the MC-volumes and gradient-based volumes was 11% (0.4%–48.4%). The complexity score showed strong correlation with standard geometric shapes. However, no relationship was found between the complexity score and the accuracy of segmentation by gradient-based tool on MC simulated tumors (R{sup 2} = 0.156). When the lesions were grouped into primary lung lesions and mediastinal/mediastinal adjacent lesions, the average absolute percent difference in volumes were 6% and 29%, respectively. The former group is more isolated and the latter is more surround by tissues with relatively high SUV background. Conclusion: The complexity shape of NSCLC lesions has little effect on the accuracy of the gradient-based segmentation method and thus is not a good predictor of uncertainty in target volume delineation. Location of lesion within a relatively high SUV background may play a more significant role in the accuracy of gradient-based segmentation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Deep learning assisted jet tomography for the study of Mach cones in QGP

Abstract Mach cones are expected to form in the expanding quark-gluon plasma (QGP) when energetic quarks and gluons traverse the hot medium at a velocity faster than the speed of sound in high-energy heavy-ion collisions. The shape of the Mach cone and the associated diffusion wake are sensitive to the initial jet production location and the propagation direction of the parton shower relative to the radial flow because of the distortion caused by the collective expansion of the QGP and the large density gradient. The shape of jet-induced Mach cones and their distortions in heavy-ion collisions provide a unique and direct probe of the dynamical evolution and the equation of state of QGP. However, it is difficult to identify the Mach cone and the diffusion wake in current experimental measurements of final hadron distributions because they are averaged over all possible initial jet production locations and parton-shower propagation directions. To overcome this difficulty, we develop a deep learning assisted jet tomography which uses the full information of the final hadrons from jets to localize the initial jet production positions. This method can help to constrain the initial regions of jet production in heavy-ion collisions and enable a differential study of Mach-cones with different path lengths and orientations relative to the radial flow of the QGP in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Constraining the shape of Milky Way satellites with distance gradients

We combine the Dark Energy Camera Legacy Survey DR8 photometry with Gaia photometry to study the 3D structure of Bootes I, Draco, Ursa Minor, Sextans, and Sculptor dwarf galaxies using blue horizontal branch (BHB) stars as distance indicators. We construct a new colour–absolute magnitude of BHB stars that we use to measure the distance gradients within the body of the dwarf galaxies. We detect a statistically significant non-zero gradient only in Sextans and Sculptor. Through modelling of the gradient and 2D density of the systems by triaxial Plummer models, we find that the distance gradients in both dwarf galaxies are inconsistent with prolate shape, but compatible with oblate or triaxial shapes. In order to explain the observed gradients, oblate models of Sextans and Sculptor need to have a significant intrinsic ellipticity larger than 0.47 for Sextans and 0.46 for Sculptor. Furthermore, the flattened oblate shape may imply a significant anisotropy in velocity distribution in order to be consistent with the lack of significant velocity gradients in these systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Surface Profile and Stress Field Evaluation using Digital Gradient Sensing Method

Shape and surface topography evaluation from measured orthogonal slope/gradient data is of considerable engineering significance since many full-field optical sensors and interferometers readily output accurate data of that kind. This has applications ranging from metrology of optical and electronic elements (lenses, silicon wafers, thin film coatings), surface profile estimation, wave front and shape reconstruction, to name a few. In this context, a new methodology for surface profile and stress field determination based on a recently introduced non-contact, full-field optical method called digital gradient sensing (DGS) capable of measuring small angular deflections of light rays coupled with a robust finite-difference-based least-squares integration (HFLI) scheme in the Southwell configuration is advanced here. The method is demonstrated by evaluating (a) surface profiles of mechanically warped silicon wafers and (b) stress gradients near growing cracks in planar phase objects.

42 ENGINEERING↗
DOE OSTI2011

Mixing and stabilization study of a partially premixed swirling flame using laser induced fluorescence

A laboratory-scale swirling burner, presenting many similarities with gas turbines combustors, has been studied experimentally using planar laser induced fluorescence (PLIF) on OH radical and acetone vapor in order to characterize the flame stabilization process. These diagnostics show that the stabilization point rotates in the combustion chamber and that air and fuel mixing is not complete at the end of the mixing tube. Fuel mass fraction decays exponentially along the mixing tube axis and transverse profiles show a gaussian shape. However, radial pressure gradients tend to trap the fuel in the core of the vortex that propagates axially in the mixing tube. As the mixing tube vortex enters the combustion chamber, vortex breakdown occurs through a precessing vortex core (PVC). The axially propagating vortex shows a helicoidal trajectory in the combustion chamber which trace is observed with transverse acetone PLIF. As a consequence, the stabilizing point of the flame in the combustion chamber rotates with the PVC structure. This phenomenon has been observed in the present study with a high speed camera recording spontaneous emission of the flame. The stabilization point rotation frequency tends to increase with mass flow rates. It was also shown that the coupling between the PVC and the flame stabilization occurs via mixing, explaining one possible coupling mechanism between acoustic waves in the flow and the reaction rate. This path may also be envisaged for flashback, an issue that will be more completely treated in a near future. (author)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Gradients of 50 MV/m in TESLA Shaped Cavities via Modified Low Temperature Bake

This paper will discuss the 75/120 C modified low temperature bake capable of giving unprecedented accel-erating gradients of above 50 MV/m for 1.3 GHz TESLA-shaped niobium SRF cavities in CW operation. A bifurca-tion in the Q₀ vs E_{acc} curve is observed after retesting cavities without disassembly in between, yielding per-formance that ranges from exceptional to above state-of-the-art. Atomic Force Microscopy studies on cavity cut-outs gives a possible mechanism responsible for this branching in performance, namely, the dissociation and growth of room temperature niobium nano-hydrides that exist near the RF surface, which are made superconduct-ing only through the proximity effect. In-situ low temper-ature baking of cavity cutouts reveals a dissociation of these room temperature nano-hydrides, which could ex-plain the higher performance of cavities subject to similar in-situ heating in the dewar.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Solid-Density Ion Temperature from Redshifted and Double-Peaked Stark Line Shapes

Heβ spectral line shapes are important for diagnosing temperature and density in many dense plasmas. This work presents Heβ line shapes measured with high spectral resolution from solid-density plasmas with minimized gradients. The line shapes show hallmark features of Stark broadening, including quantifiable redshifts and double-peaked structure with a significant dip between the peaks; these features are compared to models through a Markov chain Monte Carlo framework. Line shape theory using the dipole approximation can fit the width and peak separation of measured line shapes, but it cannot resolve an ambiguity between electron density n e and ion temperature T i , since both parameters influence the strength of quasistatic ion microfields. Here a line shape model employing a full Coulomb interaction for the electron broadening computes self-consistent line widths and redshifts through the monopole term; redshifts have different dependence on plasma parameters and thus resolve the n e – T i ambiguity. The measured line shapes indicate densities that are 80–100% of solid, identifying a regime of highly ionized but well-tamped plasma. This analysis also provides the first strong evidence that dense ions and electrons are not in thermal equilibrium, despite equilibration times much shorter than the duration of x-ray emission; cooler ions may arise from nonclassical thermalization rates or anomalous energy transport. Furthermore, the experimental platform and diagnostic technique constitute a promising new approach for studying ion-electron equilibration in dense plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Shaping Micro-Bunched Electron Beams for Compact X-ray Free-Electron Lasers with Transverse Gradient Undulators

Laser-modulator-based micro-bunching of electron beams has been applied to many novel operating modes of X-ray free-electron lasers from harmonic generation to attosecond pulse production. Recently, it was also identified as a key enabling technology for the production of a compact XFEL driven by a relatively low-energy beam. In traditional laser modulator schemes with low-energy and high-current bunches, collective effects limit the possible working points that can be employed, and thus it is difficult to achieve optimal XFEL performance. We propose to utilize transverse longitudinal coupling in a transverse gradient undulator (TGU) to shape micro-bunched electron beams so as to optimize their performance in a compact X-ray free-electron laser. We show that a TGU added to a conventional laser modulator stage enables much more flexibility in the design, allowing one to generate longer micro-bunches less subject to slippage effects and even lower the slice emittance of the micro-bunches. We present a theoretical analysis of laser-based micro-bunching with an added TGU, simulation of compression with collective effects in such systems, and finally XFEL simulations demonstrating the gains in peak power enabled by the TGU. Although we focus on the application to compact XFELs, what we propose is a general phase space manipulation that may find utility in other applications as well.

eSASE↗
DOE OSTI2020

Computational modeling and neutron imaging to understand interface shape and solute segregation during the vertical gradient freeze growth of BaBrCl:Eu

In this work we apply continuum models to analyze phase change, heat transfer, fluid flow, solute transport, and segregation in order to understand prior neutron imaging observations of the vertical gradient freeze growth of Eu-doped BaBrCl. The models provide a rigorous framework in which to understand the mechanisms that are responsible for the complicated evolution of interface shape and dopant distribution in the growth experiment. We explain how a transition in the solid/liquid interface shape from concave to convex is driven by changes in radial heat transfer caused by furnace design. We also provide a mechanistic explanation of how dynamic growth conditions and changes of the flow structure in the melt result in complicated segregation patterns in this system. A growth pause caused by controller lock-up is shown to result in a band of solute depletion in accordance with classical theory. However, changing flow patterns during growth result in a non-monotonic axial distribution of solute that cannot be explained by simple application of classical segregation models. We assert that the approach presented here, namely the use of rigorous models in conjunction advanced diagnostics, such as neutron imaging, provides an exciting path forward for process optimization and control, accelerating the incremental advances that have, in the past, typically relied on empiricism, experience, and intuition.

36 MATERIALS SCIENCE↗