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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 OSTI2016

SU-F-T-550: Radiochromic Plastic Thin Sheet Dosimeter: Initial Performance

Purpose: Thin sheets, of a high sensitivity formulation of radiochromic dosimeter, Presage were prepared and evaluated for optical readout. Methods: Sheets of radiochromic polyurethane, 12 cm long, 10 cm wide and 0.2 cm thick were prepared with leuco crystal violet as the reporter molecule. Sample transmission was evaluated at a wavelength of 590 nm with in-house constructed instruments: optical cone beam laser CT scanner, fixed and scanning spot densitometers. Sample sequential irradiations to a total dose of 40 Gy were conducted with a modified, Theratron 60, cobalt radiotherapy machine at dose rates of 1 or 0.25 Gy per minute. Exposure to ambient and readout light was minimized to limit background photochromic signals. Samples were stored at 4°C. Optical activity was assessed from linearly polarized transmission images. Comparison sensitivity measurements with EBT3 film were conducted. Results: Samples were transparent, smooth and pale purple before irradiation. Radiochromic reaction was completed in less than 5 minutes. A linear dose response with a sensitivity of 0.5 cm-1Gy-1 was observed. Micrometer measurements found sheet thickness variations up to 20%. Uniform dose, 2 Gy attenuation images, correlated with local sheet thicknesses. Comparable measurements with EBT3 film were 3 times more sensitive at 1 Gy but above 15 Gy, EBT3 film had lower sensitivity than 0.2 cm thick Presage sheet dosimeter due to its non-linear response. Conclusion: Dose sensitivity provided a 10% decrease in transmission for a 1 Gy dose. Improvements in mold design are expected to allow production of sheets with less than 5% variation in thickness. Above, 10 Gy, Presage sheet dosimeter performance expected to exceed EBT3 film based on linearity, sensitivity, transparency and smoothness of samples. J Adamovics is owner of Heuris Inc.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

MO-FG-CAMPUS-IeP2-04: Multiple Penalties with Different Orders for Structure Adaptive CBCT Reconstruction

Purpose: To combine total variation (TV) and Hessian penalty in a structure adaptive way for cone-beam CT (CBCT) reconstruction. Methods: TV is a widely used first order penalty with good ability in suppressing noise and preserving edges but leads to the staircase effect in regions with smooth intensity transition. The second order Hessian penalty can effectively suppress the staircase effect with extra cost of blurring object edges. To take the best of both penalties we proposed a novel method to combine both for CBCT reconstruction in a structure adaptive way. The proposed method adaptively determined the weight of each penalty according to the geometry of local regions. An specially-designed exponent term with image gradient involved was used to characterize the local geometry such that the weights for Hessian and TV were 1 and 0 respectively at uniform local regions and 0 and 1 at edge regions. For other local regions the weights varied from 0 to 1. The objective functional was minimized using the majorzationminimization approach. We evaluated the proposed method on a modified 3D shepp-logan and a CatPhan 600 phantom. The full-width-at-halfmaximum (FWHM) and contrast-to-noise (CNR) were calculated. Results: For 3D shepp-logan the reconstructed images using TV had an obvious staircase effect while those using the proposed method and Hessian preserved the smooth transition regions well. FWHMs of the proposed method TV and Hessian penalty were 1.75 1.61 and 3.16 respectively, indicating that both TV and the proposed method is able to preserve edges. For CatPhan 600 CNR values of the proposed method were similar to those of TV and Hessian. Conclusion: The proposed method retains favorable properties of TV like preserving edges and also has the ability in better preserving gradual transition structure as Hessian does. All methods performs similarly in suppressing noise. This work was supported in part by National Natural Science Foundation of China (NNSFC) under Grant Nos.60971112 and 61375018 grants from the Cancer Prevention and Research Institute of Texas (RP130109 and RP110562-P2) National Institute of Biomedical Imaging and Bioengineering (R01 EB020366) and a grant from the American Cancer Society (RSG-13-326-01-CCE).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-201-01: BEST IN PHYSICS (THERAPY): A Fast Multi-Target Inverse Treatment Planning Strategy Optimizing Dosimetric Measures for High-Dose-Rate (HDR) Brachytherapy

Purpose: Inverse treatment planning (ITP) for interstitial HDR brachytherapy of gynecologic cancers seeks to maximize coverage of the clinical target volumes (tumor and vagina) while respecting dose-volume-histogram related dosimetric measures (DMs) for organs at risk (OARs). Commercially available ITP tools do not support DM-based planning because it is computationally too expensive to solve. In this study we present a novel approach that allows fast ITP for gynecologic cancers based on DMs for the first time. Methods: This novel strategy is an optimization model based on a smooth DM-based objective function. The smooth approximation is achieved by utilizing a logistic function for the evaluation of DMs. The resulting nonconvex and constrained optimization problem is then optimized with a BFGS algorithm. The model was evaluated using the implant geometry extracted from 20 patient treatment plans under an IRB-approved retrospective study. For each plan, the final DMs were evaluated and compared to the original clinical plans. The CTVs were the contoured tumor volume and the contoured surface of the vagina. Statistical significance was evaluated with a one-sided paired Wilcoxon signed-rank test. Results: As did the clinical plans, all generated plans fulfilled the defined DMs for OARs. The proposed strategy showed a statistically significant improvement (p<0.001) in coverage of the tumor and vagina, with absolute improvements of related DMs of (6.9 +/− 7.9)% and (28.2 +/− 12.0)%, respectively. This was achieved with a statistically significant (p<0.01) decrease of the high-dose-related DM for the tumor. The runtime of the optimization was (2.3 +/− 2.0) seconds. Conclusion: We demonstrated using clinical data that our novel approach allows rapid DM-based optimization with improved coverage of CTVs with fewer hot spots. Being up to three orders of magnitude faster than the current clinical practice, the method dramatically shortens planning time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Enhanced nearfield acoustic holography for larger distances of reconstructions using fixed parameter Tikhonov regularization

This paper evaluates the performance of various regularization parameter choice methods applied to different approaches of nearfield acoustic holography when a very nearfield measurement is not possible. For a fixed grid resolution, the larger the hologram distance, the larger the error in the naive nearfield acoustic holography reconstructions. These errors can be smoothed out by using an appropriate order of regularization. In conclusion, this study shows that by using a fixed/manual choice of regularization parameter, instead of automated parameter choice methods, reasonably accurate reconstructions can be obtained even when the hologram distance is 16 times larger than the grid resolution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Molecular beam homoepitaxy of N-polar AlN: Enabling role of aluminum-assisted surface cleaning

N-polar aluminum nitride (AlN) is an important building block for next-generation high-power radio frequency electronics. We report successful homoepitaxial growth of N-polar AlN by molecular beam epitaxy (MBE) on large-area, cost-effective N-polar AlN templates. Direct growth without any in situ surface cleaning leads to films with inverted Al polarity. It is found that Al-assisted cleaning before growth enables the epitaxial film to maintain N-polarity. The grown N-polar AlN epilayer with its smooth, pit-free surface duplicates the structural quality of the substrate, as evidenced by a clean and smooth growth interface with no noticeable extended defects generation. Near band-edge photoluminescence peaks are observed at room temperature on samples with MBE-grown layers but not on the bare AlN templates, implying the suppression of nonradiative recombination centers in the epitaxial N-polar AlN.

42 ENGINEERING↗
DOE OSTI2017

Measurement of the small-scale structure of the intergalactic medium using close quasar pairs

Using quasar pairs to measure smoothness Space between galaxies is filled with a tenuous gas known as the intergalactic medium (IGM). The presence of hydrogen atoms in the IGM at different redshifts imprints a series of absorption lines in the spectra of background quasars. Rorai et al. studied pairs of closely spaced quasars and quantified how similar their absorption lines are as a function of transverse separation and redshift. They thus assessed the smoothness of the IGM on relatively small scales—several times the size of a galaxy. The results constrain interactions between galaxies and the IGM, such as heating by ultraviolet photons. Science , this issue p. 418

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Topological Defects in Helical Magnets

Helical magnets which violated space inversion symmetry have rather peculiar topological defects. In isotropic helical magnets with exchange and Dzyaloshinskii–Moriya interactions, there are only three types of linear defects: ±π and 2π-disclinations. Weak crystal anysotropy suppresses linear defects on large scale. Instead, planar defects appear: domain walls that separate domains with different preferential directions of helical wavevectors. The appearance of such domain walls in the bulk helical magnets and some of their properties were predicted in the work [1]. In a recent work by an international team of experimenters and theorists [2], the existence of new types of domain walls on crystal faces of helical magnet FeGe was discovered. They have many features predicted by theory [1], but display also unexpected properties, one of them is the possibility of arbitrary angle between helical wavevectors. Depending on this angle, the domain walls observed in [2] can be divided in two classes: smooth and zig-zag. This article contains a mini-review of the existing theory and experiment. It also contains new results that explain why in a system with continuous orientation of helical wavevectors domain walls are possible. We discuss why and at what conditions smooth and zig-zag domain walls appear, analyze spin textures associated with helical domain walls, and find the dependence of their width on the angle between helical wavevectors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

On the Mechanism of Turbulent Shear Flows

As a result of our analysis of some facts of turbulent flows, whose explanation is beyond the scope of existing semiempirical theories, in particular, our estimate of the effective roughness height in pipes with distributed roughness characterized by two or more length scales, we present a version of the theory of turbulent flows in channels with smooth and rough walls with a unified mechanism of the dynamic interaction (friction mechanism) of a turbulent flow with its boundaries—the channel walls or external laminar flow. We have derived the expressions for a generalized law of friction that describe a turbulent flow at all admissible Reynolds numbers from the regime of flow with smooth walls to the regime with a complete manifestation of roughness elements and for sand roughness consistent with Nikuradse’s experimental data. One of the conclusions of the theory is the assertion that the only source of turbulence for turbulent flows in channels and jets are the vortices forming near the walls of channels and at the free boundaries of turbulent jets, and only through these vortices is the kinetic energy from the mean flow converted to the energy of turbulent pulsations. The difference between the mechanisms of the laminar and turbulent flow regimes can be clearly represented by Eq. (24).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Can gluon spin contribute to that of nucleon?

The transformation of angular momentum to its Belinfante form requires the smooth behaviour of classical fields at infinity which for the case of quantum operators transforms to the smooth behaviour of matrix elements at small momentum transfers. For the case of quarks this provides the kinematical counterpart of U {sub A }(1) problem while for gluons there is a contradiction between kinematics and dynamics governed by Kogut-Susskind pole. This may result in the violation of Equivalence Principle for nucleons or in the stringent constraints to the strange quark polarization in nucleons, while the most likely outcome would be the impossibility to separate gluon angular momentum to spin and orbital parts in the meaningful way.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Mixed phase effects on high-mass twin stars

Recently it has been found that a certain class of hybrid star equations of state with a large latent heat (strong first order phase transition obtained by a Maxwell construction) between stiff hadronic and stiff quark matter phases allows for the appearance of a third family of compact stars (including “twins”) at high mass of ∼ 2M{sub ⊙} We investigate how robust this high-mass twin phenomenon is against a smoothing of the transition which would occur, e.g., due to pasta structures in the mixed phase. To this end we propose a simple construction of a pasta-like equation of state with a parameter that quantifies the degree of smoothing of the transition and could eventually be related to the surface tension of the pasta structures. It is interesting to note that the range of energy densities for the transition as well as the pressure at the onset of the transition of this class of hybrid star matter at zero temperature corresponds well to values of the same quantities found in finite temperature lattice QCD simulations for the 1 σ region at the pseudocritical temperature T{sub c} = 154 ± 9 MeV. The pattern of the speed of sound as a function of energy density is very different.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Biexciton Binding Energy in Spherical Quantum Dots with Γ{sub 8} Valence Band

The biexciton binding energy in spherical CdSe/ZnSe quantum dots is calculated variationally in the framework of kp-perturbation theory. Smooth and abrupt confining potentials with the same localization area of carriers are compared for two limiting cases of light hole to heavy hole mass ratio β = m{sub lh}/m{sub hh}: β = 1 and β = 0. Accounting for correlations between carriers results in their polarized configuration and significantly increases the biexciton binding energy in comparison with the first order perturbation theory. For β = 0 in smooth confining potentials there are three nearby biexciton states separated by small energy gap between 1S{sub 3/2} and 1P{sub 3/2} hole states.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Comparison of Classical and Aggregation-Based Algebraic Multigrid Preconditioners for High-Fidelity Simulation of Wind Turbine Incompressible Flows

This paper presents a comparison of parallel strong scaling performance of classical and aggregation algebraic multigrid (AMG) preconditioners in the context of wind turbine simulations. Fluid motion is governed by the incompressible Navier--Stokes equations, discretized in space with control-volume finite elements and in time with an inexact projection scheme using an implicit integrator. A discontinuous-Galerkin sliding-mesh algorithm captures rotor motion. The momentum equations are solved with iterative Krylov methods, preconditioned by symmetric Gauss--Seidel (SGS) in Trilinos and $\ell_1$ SGS in hypre. The mass-continuity equation is solved with GMRES preconditioned by AMG and can account for the majority of simulation time. Reducing this continuity solve time is crucial. Wind turbine simulations present two unique challenges for AMG preconditioned solvers: the computational meshes include strongly anisotropic elements, and mesh motion requires matrix reinitialization and computation of preconditioners at each time step. Detailed timing profiles are presented and analyzed, and best practices are discussed for both classical and aggregation-based AMG. Results are presented for simulations of two different wind turbines with up to 6 billion grid points on two different computer architectures. For moving mesh problems that require linear-system reinitialization, the well-established strategy of amortizing preconditioner setup costs over a large number of time steps to reduce the solve time is no longer valid. Instead, results show that faster time to solution is achieved by reducing preconditioner setup costs at the expense of linear-system solve costs. Standard smoothed aggregation with Chebyshev relaxation was found to perform poorly when compared with classical AMG in terms of solve time and robustness. However, plain aggregation was comparable to classical AMG.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Learning Optimal Multigrid Smoothers via Neural Networks

Multigrid methods are one of the most efficient techniques for solving large sparse linear systems arising from partial differential equations (PDEs) and graph Laplacians from machine learning applications. One of the key components of multigrid is smoothing, which aims at reducing high-frequency errors on each grid level. However, finding optimal smoothing algorithms is problem-dependent and can impose challenges for many problems. In this paper, we propose an efficient adaptive framework for learning optimized smoothers from operator stencils in the form of convolutional neural networks (CNNs). Here, the CNNs are trained on small-scale problems from a given type of PDEs based on a supervised loss function derived from multigrid convergence theories and can be applied to large-scale problems of the same class of PDEs. Numerical results on anisotropic rotated Laplacian problems and variable coefficient diffusion problems demonstrate improved convergence rates and solution time compared with classical hand-crafted relaxation methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

On a nonlocal Cahn–Hilliard model permitting sharp interfaces

A nonlocal Cahn–Hilliard model with a non-smooth potential of double-well obstacle type that promotes sharp interfaces in the solution is presented. To capture long-range interactions between particles, a nonlocal Ginzburg–Landau energy functional is defined which recovers the classical (local) model as the extent of nonlocal interactions vanish. In contrast to the local Cahn–Hilliard problem that always leads to diffuse interfaces, the proposed nonlocal model can lead to a strict separation into pure phases of the substance. In this work, the lack of smoothness of the potential is essential to guarantee the aforementioned sharp-interface property. Mathematically, this introduces additional inequality constraints that, in a weak formulation, lead to a coupled system of variational inequalities which at each time instance can be restated as a constrained optimization problem. We prove the well-posedness and regularity of the semi-discrete and continuous in time weak solutions, and derive the conditions under which pure phases are admitted. Moreover, we develop discretizations of the problem based on finite element methods and implicit–explicit time-stepping methods that can be realized efficiently. Finally, we illustrate our theoretical findings through several numerical experiments in one and two spatial dimensions that highlight the differences in features of local and nonlocal solutions and also the sharp interface properties of the nonlocal model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition

Over the past decade, the machine learning security community has developed a myriad of defenses for evasion attacks. An understudied question in that community is: for whom do these defenses defend? This work considers common approaches to defending learned systems and how security defenses result in performance inequities across different sub-populations. We outline appropriate parity metrics for analysis and begin to answer this question through empirical results of the fairness implications of machine learning security methods. We find that many methods that have been proposed can cause direct harm, like false rejection and unequal benefits from robustness training. The framework we propose for measuring defense equality can be applied to robustly trained models, preprocessing-based defenses, and rejection methods. We identify a set of datasets with a user-centered application and a reasonable computational cost suitable for case studies in measuring the equality of defenses. In our case study of speech command recognition, we show how such adversarial training and augmentation have non-equal but complex protections for social subgroups across gender, accent, and age in relation to user coverage. We present a comparison of equality between two rejection-based defenses: randomized smoothing and neural rejection, finding randomized smoothing more equitable due to the sampling mechanism for minority groups. This represents the first work examining the disparity in the adversarial robustness in the speech domain and the fairness evaluation of rejection-based defenses.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2020

Analysis of Electric Vehicle Charging Behavior Patterns with Function Principal Component Analysis Approach

This manuscript focused on analyzing electric vehicles’ (EV) charging behavior patterns with a functional data analysis (FDA) approach, with the goal of providing theoretical support to the EV infrastructure planning and regulation, as well as the power grid load management. 5-year real-world charging log data from a total of 455 charging stations in Kansas City, Missouri, was used. The focuses were placed on analyzing the daily usage occupancy variability, daily energy consumption variability, and station-level usage variability. Compared with the traditional discrete-based analysis models, the proposed FDA modeling approach had unique advantages in preserving the smooth function behavior of the data, bringing more flexibility in the modeling process with little required assumptions or background knowledge on independent variables, as well as the capability of handling time series data with different lengths or sizes. In addition to the patterns revealed in the EV charging station’s occupancy and energy consumption, the differences between EV driver’s charging time and parking time were analyzed and called for the needs for parking regulation and enforcement. The different usage patterns observed at charging stations located on different land-use types were also analyzed.

Engineering↗
DOE OSTI2021

Evaluation of KDP Estimation Algorithm Performance in Rain Using a Known-Truth Framework

Accurate estimation of specific differential phase ( K DP ) is necessary for rain rate estimation, attenuation correction, and hydrometeor classification algorithms. There are numerous published methods to process polarimetric radar observations of propagation differential phase shift (Φ DP ) and estimate K DP , but the corresponding K DP estimate uncertainty is unquantified. This study provides guidance on how commonly used K DP estimation algorithms perform in various environments. Here, we create numerous synthetic (“true”) K DP profiles, integrate over them to obtain “smoothed” Φ DP , and then add noise typical of S-band operational weather radar measurements. Each algorithm is applied to our noisy Φ DP profiles and compared to the true K DP profile such that the errors and uncertainty are quantified. The synthetic K DP profiles are Gaussian in shape, which allows systematic variations in their magnitude and width to determine how each algorithm performs in smooth, slowly changing K DP profiles, as well as steep profiles. Results demonstrate that algorithm performance is dependent on the Φ DP field received. These results are further supported by an error analysis of each algorithm for two more complicated synthetic K DP profiles. Some K DP algorithms allow users to change various tuning parameters; a subset of these tuning parameters is tested to provide guidance on how changing these parameters impacts algorithm performance. We then provide evidence that our known-truth framework provides insight into algorithm performance in observed data through two case studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Analyzing the Adaptive Mesh Refinement (AMR) Characteristics of a High-Order 2D Cubed-Sphere Shallow-Water Model

Adaptive mesh refinement (AMR) is a technique that has been featured only sporadically in atmospheric science literature. This study aims to demonstrate the utility of AMR for simulating atmospheric flows. Several test cases are implemented in a 2D shallow-water model on the sphere using the Chombo-AMR dynamical core. This high-order finite-volume model implements adaptive refinement in both space and time on a cubed-sphere grid using a mapped-multiblock mesh technique. The tests consist of the passive advection of a tracer around moving vortices, a steady-state geostrophic flow, an unsteady solid-body rotation, a gravity wave impinging on a mountain, and the interaction of binary vortices. Both static and dynamic refinements are analyzed to determine the strengths and weaknesses of AMR in both complex flows with small-scale features and large-scale smooth flows. The different test cases required different AMR criteria, such as vorticity or height-gradient based thresholds, in order to achieve the best accuracy for cost. The simulations show that the model can accurately resolve key local features without requiring global high-resolution grids. The adaptive grids are able to track features of interest reliably without inducing noise or visible distortions at the coarse–fine interfaces. Finally and furthermore, the AMR grids keep any degradations of the large-scale smooth flows to a minimum.

54 ENVIRONMENTAL SCIENCES↗