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DOE OSTI2012

A new pulsed laser deposition technique: Scanning multi-component pulsed laser deposition method

The scanning multi-component pulsed laser deposition (PLD) method realizes uniform depositions of desired coatings by a modified pulsed laser deposition process, preferably with a femto-second laser-system. Multi-component coatings (single or multilayered) are thus deposited onto substrates via laser induced ablation of segmented targets. This is achieved via horizontal line-scanning of a focused laser beam over a uniformly moving target's surface. This process allows to deposit the desired composition of the coating simultaneously, starting from the different segments of the target and adjusting the scan line as a function of target geometry. The sequence and thickness of multilayers can easily be adjusted by target architecture and motion, enabling inter/intra layer concentration gradients and thus functional gradient coatings. This new, simple PLD method enables the achievement of uniform, large-area coatings. Case studies were performed with segmented targets containing aluminum, titanium, and niobium. Under the laser irradiation conditions applied, all three metals were uniformly ablated. The elemental composition within the rough coatings obtained was fixed by the scanned area to Ti-Al-Nb = 1:1:1. Crystalline aluminum, titanium, and niobium were found to coexist side by side at room temperature within the substrate, without alloy formation up to 600 deg. C.

36 MATERIALS SCIENCE↗

DOE OSTI2011

Smooth full field reconstruction of velocity and its gradients from noisy scattered velocimetry data in a cross-slot flow

We present a method combining generalized Tikhonov regularization with a finite element approximation for reconstructing smooth velocity and velocity gradient fields from spatially scattered and noisy velocity data in a two-dimensional complex flow domain. Synthetic velocity data for a cross-slot geometry are generated using the Oldroyd-B solution, subsequently perturbed by random noise. Performances of diverse finite element continuity-regularization criterion combinations are tested against noise-free data, while the optimum regularization parameter is determined using generalized cross-validation. The best performance is achieved for the velocity field and its gradients simultaneously by C{sup 2} continuous Hermite finite elements and minimization of a norm of the velocity's third derivative. The standard regularization criterion based on the second derivative is shown to lead to systematic distortions in boundary regions, allowing therefore a lower reduction in the statistical error. Furthermore, optical fields are calculated by applying a differential constitutive equation directly to the reconstructed flow kinematics; high quality velocity gradient fields are shown to be an essential prerequisite for their reliable prediction. Overall, the method is expedient to implement and does not require boundary conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Thermal dissipation sensors enter a new age: Navigating frontiers in transpiration and hydrologic function

Thermal dissipation (TD) sensors have been used extensively for a wide array of sap flow applications, and yet recently several limitations of this approach have been identified, including a tendency to underestimate absolute flows, especially in small stems with very high flows. However, when used properly, the TD method remains the most cost effective and reliable approach for determining relative flows in comparison studies. Major advantages of this method include the ability to replicate maximally within trees, across trees of different sizes, and across multiple species to capture the full range of natural variation in the study system. From early studies, such variation has been deemed a major challenge for representing stand-level dynamics. In a series of recent comparison studies, we determined mean sap flux density dynamics within and among groups of trees. These studies were conducted within temperate coniferous forest (n=46), temperate oak savanna (n=36), temperate pine forest (n=49), temperate bottomland hardwood forest (n=23), tropical premontane rainforest (n=43), semiarid subtropical shrubland (n=25), and tropical dry forest (n=15), with a total of 237 sensors. Two study sites were also equipped with eddy covariance systems for determination of stand-level evapotranspiration. Sites subject to high background thermal gradients used the transient thermal dissipation method. Comparisons varied between studies but tended to focus on relative flow differences between species, between wetter and drier microsites, between understory and overstory components, or between wetter and drier periods of the growing season. Except for the shrubland sites, study trees tended to be at least 15-cm diameter and frequently exceeded 50-cm diameter. Results of this cross-site comparison highlight the inherent variation in natural stands and the importance of using large sample sizes. The TD approach remains a valuable and preferred method for the future determination of water use in trees. However, sensor replication can fundamentally impact a study's outcomes and should be more carefully considered in study design. Customized error mitigation strategies are best to address the sources of variation most problematic for a particular study. In conclusion, the development of “smart” calibration approaches that correct for fundamental effects of radial variation inherent in thermal dissipation studies is discussed.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1987

Assimilation of scalar versus horizontal gradient information from the VAS into a mesoscale model

Comparisons are made between analyses and forecasts which incorporate VAS geopotential data as either scalar or horizontal gradient information for a case study on the AVE/VAS day of Mar. 6, 1982. On this day, incorporating the VAS information in analysis as a variational constraint on horizontal geopotential gradients significantly mitigated the effects of large data biases which made VAS assimilation by standard scalar methods very difficult. A subsequent forecast made from the gradient assimilation was superior to one made from the standard analysis and of comparable quality in geopotentials to a control forecast from synoptic data. Most impact was noted in the forecasts of vertical motion and precipitation in the gradient vs this control simulation.

Diak, George↗

DOE OSTI2018

Gradient-based optimization for regression in the functional tensor-train format

Predictive analysis of complex computational models, such as uncertainty quantification (UQ), must often rely on using an existing database of simulation runs. In this paper we consider the task of performing low-multilinear-rank regression on such a database. Specifically we develop and analyze an efficient gradient computation that enables gradient-based optimization procedures, including stochastic gradient descent and quasi-Newton methods, for learning the parameters of a functional tensor-train (FT). We compare our algorithms with 22 other nonparametric and parametric regression methods on 10 real-world data sets and show that for many physical systems, exploiting low-rank structure facilitates efficient construction of surrogate models. Here, we use a number of synthetic functions to build insight into behavior of our algorithms, including the rank adaptation and group-sparsity regularization procedures that we developed to reduce overfitting. Finally we conclude the paper by building a surrogate of a physical model of a propulsion plant on a naval vessel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2010

Shape measurement biases from underfitting and ellipticity gradients

With this study, precision weak gravitational lensing experiments require measurements of galaxy shapes accurate to <1 part in 1000. We investigate measurement biases, noted by Voigt and Bridle (2009) and Melchior et al. (2009), that are common to shape measurement methodologies that rely upon fitting elliptical-isophote galaxy models to observed data. The first bias arises when the true galaxy shapes do not match the models being fit. We show that this "underfitting bias" is due, at root, to these methods' attempts to use information at high spatial frequencies that has been destroyed by the convolution with the point-spread function (PSF) and/or by sampling. We propose a new shape-measurement technique that is explicitly confined to observable regions of k-space. A second bias arises for galaxies whose ellipticity varies with radius. For most shape-measurement methods, such galaxies are subject to "ellipticity gradient bias". We show how to reduce such biases by factors of 20–100 within the new shape-measurement method. The resulting shear estimator has multiplicative errors < 1 part in 10 3 for high-S/N images, even for highly asymmetric galaxies. Without any training or recalibration, the new method obtains Q = 3000 in the GREAT08 Challenge of blind shear reconstruction on low-noise galaxies, several times better than any previous method.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

SU-E-T-621: Analysis of Robustness of Proton Pencil Beam Scanning Technique for Delivery of Craniospinal Irradiation

Purpose: To investigate the robustness and safety of craniospinal irradiation (CSI) planned with a proton pencil beam scanning (PBS) technique which overcomes the complexity of the planning associated with feathering match lines. Methods: Six CSI patients were planned with gradient-dose matching using PBS technique. Uniform dose coverage to the entire target volumes was achieved with averaged junction lengths of 6.9±0.3 cm. Robustness of the plans was evaluated by shifting the isocenter of each treatment field by ±3 mm in longitudinal direction and compared with the original non-shifted plan with metrics of conformity number (CN) and homogeneity index (HI). An anthropomorphic phantom study using film measurements was also carried out on a plan with 5 cm junction length. Results: For a given junction length, the dose errors were directly proportional to the setup errors. Setup errors of 3 mm from each field caused on average 3.5% lower CN and 2.1% higher HI. Minimal D95% to PTV and D98% to CTV were reduced by 2.2%±1.5% and 2.8%±1.7% respectively. A drop of maximal 6.8%±5.5% on the minimal dose to the cribriform plate was also observed. When the junction length was 5cm or longer, these 3mm setup errors from each field resulted in up to 12% dose errors. Consistent results were reached between film measurements and planned dose profiles in the junction area. Due to near-zero exit doses beyond the target volume, sparing of anterior organs such as heart, liver, lung and kidney were observed. Conclusions: Longitudinal setup errors directly reduce the dosimetric accuracy of the CSI treatment with matched proton fields. The reported technique creates a slow dose gradient in the junction area, which makes the treatment more robust and safe to longitudinal setup errors compared to conventional feathering methods.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Adaptive Grid Redistribution for a 1D Model of Turbulence and Clouds

In global atmospheric models, resolving stratocumulus (Sc) in the vertical is computationally expensive. However, Sc appear only under special meteorological conditions. Therefore, there is motivation to refine the vertical grid levels adaptively. In order to facilitate the possibility of parallelization on graphical processing units, our grid adaptation method prescribes the number of vertical levels a priori. Then grid levels are relocated toward altitude ranges in need of refinement. Because the method relocates existing grid levels, rather than adding extra levels, there is a risk of creating regions with overly coarse grid spacing, that is, voids in the grid mesh. To prevent such voids from forming, a simple method is developed to impose a maximum grid spacing. To decide where to place enhanced resolution, the authors develop an empirical mesh refinement criterion. It refines grid spacing near the ground, near strong temperature gradients, and within clouds. Our grid adaptation method is implemented in a single-column model and evaluated on four test cases: decaying stratocumulus, developing shallow cumulus, a quasi-stationary stratocumulus deck, and the diurnal cycle of a dry boundary layer. In the stratocumulus cases, mesh refinement leads to improvements in both the time evolution of fields and their time averages. The other two cases show smaller differences.

Carstensen, Steffen [Univ. of Wisconsin, Milwaukee↗

DOE OSTI2013

Thermal transpiration through single walled carbon nanotubes and graphene channels

Thermal transpiration through carbon nanotubes (CNTs) and graphene channels is studied using molecular dynamics (MD) simulations. The system consists of two reservoirs connected by a CNT. It is observed that a flow is developed inside the CNT from the low temperature reservoir to the high temperature reservoir when the two reservoirs are maintained at different temperatures. The influence of channel size and temperature gradient on the mean velocity is analysed by varying the CNT diameter and the temperature of one of the reservoirs. Larger flow rate is observed in the smaller diameter CNTs showing an increase in the mean velocity with increase in the temperature gradient. For the flow developed inside the CNTs, slip boundaries occur and the slip length is calculated using the velocity profile. We examine the effect of fluid-wall interaction strength (ε{sub fw}), diffusivity (D), and viscosity of the fluid (μ) on the temperature induced fluid transport through the CNTs. Similar investigations are also carried out by replacing the CNT with a graphene channel. Results show that the mean velocity of the fluid atoms in the graphene channel is lower than that through the CNTs. This can be attributed to the higher degree of confinement observed in the CNTs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Magneto-electronic and Thermodynamic Properties of Quaternary NiFeMnZ (Z = In, Sn) New Spin Gapless Semiconductors

This paper deals with investigation of magneto-electronic and thermodynamic properties of new spin gapless semiconductor quaternary NiFeMnZ (Z = In, Sn) Heusler alloys. In addition, electronic properties such as band structure and density of states were studied in detail. The obtained results are based on first-principles calculations, using the full potential linearized augmented plane wave (FP-LAPW) method within well-known generalized gradient approximation (GGA) coupling with spin-orbit calculation (SOC) in framework of the density functional theory (DFT) implemented in the WIEN2k package. As results, the alloys were found to be new spin gapless semiconductors (SGSs), and both compounds in LiMgPdSn-type crystal structure are stable. The magnetic moment of NiFeMnIn and NiFeMnSn was 4.39 and 4.99 μ{sub B} per formula unit, respectively. This result is in agreement with the Slater-Pauling rule (M{sub tot} = 24 −Z{sub tot}). Furthermore, the thermodynamic properties were also predicted. All these multifunctionalities lead to crucial interest for developing future spintronics device generations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning

Residential heating, ventilation, and air conditioning (HVAC) has been considered as an important demand response resource. However, the optimization of residential HVAC control is no trivial task due to the complexity of the thermal dynamic models of buildings and uncertainty associated with both occupant-driven heat loads and weather forecasts. In this paper, we apply a novel model-free deep reinforcement learning (RL) method, known as the deep deterministic policy gradient (DDPG), to generate an optimal control strategy for a multi-zone residential HVAC system with the goal of minimizing energy consumption cost while maintaining the users’ comfort. Here, the applied deep RL-based method learns through continuous interaction with a simulated building environment and without referring to any prior model knowledge. Simulation results show that compared with the state-of-art deep Q network (DQN), the DDPG-based HVAC control strategy can reduce the energy consumption cost by 15% and reduce the comfort violation by 79%; and when compared with a rule-based HVAC control strategy, the comfort violation can be reduced by 98%. In addition, experiments with different building models and retail price models demonstrate that the well-trained DDPG-based HVAC control strategy has high generalization and adaptability to unseen environments, which indicates its practicability for real-world implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Multi‐Material Gradient Printing Using Meniscus‐enabled Projection Stereolithography (MAPS)

Light‐based additive manufacturing methods are widely used to print high‐resolution 3D structures for applications in tissue engineering, soft robotics, photonics, and microfluidics, among others. Despite this progress, multi‐material printing with these methods remains challenging due to constraints associated with hardware modifications, control systems, cross‐contamination, waste, and resin properties. Here, a new printing platform coined Meniscus‐enabled Projection Stereolithography (MAPS) is reported, a vat‐free method that relies on generating and maintaining a resin meniscus between a crosslinked structure and bottom window to print lateral, vertical, discrete, or gradient multi‐material 3D structures with no waste and user‐defined mixing between layers. MAPS is compatible with a wide range of resins shown and can print complex multi‐material 3D structures without requiring specialized hardware, software, or complex washing protocols. MAPS's ability to print structures with microscale variations in mechanical stiffness, opacity, surface energy, cell densities, and magnetic properties provides a generic method to make advanced materials for a broad range of applications.

bioprinting↗

DOE OSTI2011

Dosimetric evaluation for exposure of patient to a z-gradient coil in magnetic resonance imaging

In magnetic resonance imaging, time-varied gradient magnetic fields may stimulate nerves and muscles by inducing electric fields and currents in patients, which may potentially cause health problems. In this paper, a realistic z-gradient coil was numerically designed and the exposure level in a 3D real human man model was calculated by using the impedance method. It was found that the z-gradient coil produces a magnetic flux density (B-field) with two regions of good homogeneity along the coil length, separated by a very weak B-field in the middle of the coil. The spatially averaged B-field is 281 times greater than that of the International Commission on Non-Ionizing Radiation Protection's (ICNIRP) reference level. The 1-cm{sup 2}-averaged induced current density in the central nervous system is 87 times greater than that of the ICNIRP's basic restriction. The maximum current density in all of the body tissues is above the nerve stimulation threshold.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Accelerating gradient descent and Adam via fractional gradients

Here we propose a class of novel fractional-order optimization algorithms. We define a fractional-order gradient via the Caputo fractional derivatives that generalizes integer-order gradient. We refer it to as the Caputo fractional-based gradient, and develop an efficient implementation to compute it. A general class of fractional-order optimization methods is then obtained by replacing integer-order gradients with the Caputo fractional-based gradients. To give concrete algorithms, we consider gradient descent (GD) and Adam, and extend them to the Caputo fractional GD (CfGD) and the Caputo fractional Adam (CfAdam). We demonstrate the superiority of CfGD and CfAdam on several large scale optimization problems that arise from scientific machine learning applications, such as ill-conditioned least squares problem on real-world data and the training of neural networks involving non-convex objective functions. Numerical examples show that both CfGD and CfAdam result in acceleration over GD and Adam, respectively. We also derive error bounds of CfGD for quadratic functions, which further indicate that CfGD could mitigate the dependence on the condition number in the rate of convergence and results in significant acceleration over GD.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2011

MEASURING GRAVITATIONAL LENSING FLEXION IN A1689 USING AN ANALYTIC IMAGE MODEL

Measuring dark matter substructure within galaxy cluster halos is a fundamental probe of the {Lambda}CDM model of structure formation. Gravitational lensing is a technique for measuring the total mass distribution which is independent of the nature of the gravitating matter, making it a vital tool for studying these dark-matter-dominated objects. We present a new method for measuring weak gravitational lensing flexion fields, the gradients of the lensing shear field, to measure mass distributions on small angular scales. While previously published methods for measuring flexion focus on measuring derived properties of the lensed images, such as shapelet coefficients or surface brightness moments, our method instead fits a mass-sheet transformation invariant Analytic Image Model (AIM) to each galaxy image. This simple parametric model traces the distortion of lensed image isophotes and constrains the flexion fields. We test the AIM method using simulated data images with realistic noise and a variety of unlensed image properties, and show that it successfully reproduces the input flexion fields. We also apply the AIM method for flexion measurement to Hubble Space Telescope observations of A1689 and detect mass structure in the cluster using flexion measured with this method. We also estimate the scatter in the measured flexion fields due to the unlensed shape of the background galaxies and find values consistent with previous estimates.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

DEVELOPMENT AND APPLICATION OF RISK ANALYSIS TOOLKIT FOR PLANT RESOURCE OPTIMIZATION

This paper presents the development of methods and tools that are being designed to optimize plant operations (e.g., maintenance/replacement schedules and optimal maintenance postures for plant components) in a manner that is more cost effective than current approaches and makes better use of available component health and cost data. These methods include both data- and model-based optimization methods. Model-based optimization methods directly include reliability and cost models to determine an optimal plant operational strategy. We consider gradient-based and evolutionary (based on genetic algorithms) optimization methods. The second class of methods target more specific use cases (e.g., project schedule optimization) and are not based on reliability models directly, but they require specific component reliability and cost data. This class of methods is based on variants of the knapsack problem with an aim to determine an optimal project schedule that maximizes the overall NPV. This paper also presents multi-objective methods designed to identify an optimal maintenance posture based on a Pareto frontier analysis. Rather than dictating the “right” tradeoff (i.e., identify the absolute best posture), we show how it is possible to perform a trade space exploration approach (i.e., identify value and costs of several postures and let the analysis account for desired value and cost metrics). This is performed by identifying maintenance postures that maximize value (e.g., system availability) and minimize operational costs, i.e., the Pareto frontier in a value-cost trade space. For all these methods we present detailed applicative examples that show their validity from a decision-making perspective.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Forming high efficiency silicon solar cells using density-graded anti-reflection surfaces

A method (50) is provided for processing a graded-density AR silicon surface (14) to provide effective surface passivation. The method (50) includes positioning a substrate or wafer (12) with a silicon surface (14) in a reaction or processing chamber (42). The silicon surface (14) has been processed (52) to be an AR surface with a density gradient or region of black silicon. The method (50) continues with heating (54) the chamber (42) to a high temperature for both doping and surface passivation. The method (50) includes forming (58), with a dopant-containing precursor in contact with the silicon surface (14) of the substrate (12), an emitter junction (16) proximate to the silicon surface (14) by doping the substrate (12). The method (50) further includes, while the chamber is maintained at the high or raised temperature, forming (62) a passivation layer (19) on the graded-density silicon anti-reflection surface (14).

14 SOLAR ENERGY↗

DOE OSTI2015

Forming high-efficiency silicon solar cells using density-graded anti-reflection surfaces

14 SOLAR ENERGY↗