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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 OSTI2018

Optimal Wind Power Uncertainty Intervals for Electricity Market Operation

It is important to select an appropriate uncertainty level of the wind power forecast for power system scheduling and electricity market operation. Traditional methods hedge against a predefined level of wind power uncertainty, such as a specific confidence interval or uncertainty set, which leaves the questions of how to best select the appropriate uncertainty levels. To bridge this gap, this paper proposes a model to optimize the forecast uncertainty intervals of wind power for power system scheduling problems, with the aim of achieving the best trade-off between economics and reliability. Then we reformulate and linearize the models into a mixed integer linear programming (MILP) without strong assumptions on the shape of the probability distribution. In order to invest the impacts on cost, reliability, and prices in a electricity market, we apply the proposed model on a twosettlement electricity market based on a six-bus test system and on a power system representing the U.S. state of Illinois. The results show that the proposed method can not only help to balance the economics and reliability of the power system scheduling, but also help to stabilize the energy prices in electricity market operation.

electricity market↗
DOE OSTI2016

Hourglass Dispersion and Resonance of Magnetic Excitations in the Superconducting State of the Single-Layer Cuprate HgBa 2 CuO 4 + δ Near Optimal Doping

Here, we use neutron scattering to study magnetic excitations near the antiferromagnetic wave vector in the underdoped single-layer cuprate HgBa 2 CuO 4 + δ (superconducting transition temperature T c ≈ 88 K , pseudogap temperature T* ≈ 220 K ). The response is distinctly enhanced below T* and exhibits a Y -shaped dispersion in the pseudogap state, whereas the superconducting state features an X -shaped (hourglass) dispersion and a further resonancelike enhancement. We also observe a large spin gap of about 40 meV in both states. This phenomenology is reminiscent of that exhibited by bilayer cuprates. The resonance spectral weight, irrespective of doping and compound, scales linearly with the putative binding energy of a spin exciton described by an itinerant-spin formalism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Microstructural Analysis of Severe Plastic Deformed Twin Roll Cast AZ31 for the Optimization of Superplastic Properties

In recent years magnesium alloys have attracted significant attention as potential candidates to replace many of the heavier metals used in some automotive applications. However, the limited formability of magnesium and its alloys at room temperature has driven interest in the superplastic forming magnesium as an alternative shaping method. Severe plastic deformation techniques have become a well studied method of refining the grain size and modifying the microstructural characteristics of many magnesium alloys to achieve greater superplastic properties. In this study twin roll cast (TRC) AZ31 magnesium alloy was subjected to equal channel angular pressing (ECAP) and friction stir welding (FSW). The influence of these severe plastic deformation processes on the grain size, texture and grain boundary character distribution was investigated to identify the optimum severe plastic deformation process for the superplastic forming of AZ31.

Young, John P.↗
DOE OSTI2025

BCARS Simulated Phantom Dataset for Evaluation of Processing Pipelines

Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy is a powerful label-free biological imaging technique, but the raw signal requires careful processing. The vibrationally resonant (Raman) fingerprint signal is usually small compared with instrumental noise sources and the nonresonant background (NRB) inherent in the BCARS signal. Fortunately, the NRB exhibits a systematic phase relationship with the coherent Raman response, acting as a heterodyne amplifier for the weak fingerprint signal. Due to this heterodyne effect, the Raman response can be recovered quantitatively and invariantly across different instruments, provided the NRB shape is known. Even with heterodyne amplification, the amplitudes of fingerprint signal components are often comparable to system noise. Singular value decomposition (SVD), which utilizes spatial information, is often employed for additional noise filtering. Consequently, finding optimal processing parameters to properly distinguish the NRB and Raman responses and suppress noise in the complex BCARS signal requires a reference system that realistically represents the spectral and spatial properties of BCARS signals obtained from biological samples. We present a digital tissue phantom that meets these criteria as a tool for testing candidate signal processing pipelines. The digital phantom is generated with simulated hyperspectral Raman images having system-specific noise and background characteristics. Here, we analyze phantom datasets with differing background and signal-to-noise conditions to evaluate their impact on the performance of multiple signal processing pipelines. Specifically, we investigate the application of a Butterworth filter-based routine to directly estimate the NRB from the BCARS signal. Additionally, we evaluate a Lorentzian wavelet transform as an alternative to the Hilbert transform for extracting the Raman spectrum from the BCARS signal. While we demonstrate this phantom for BCARS, it can be used for any spectroscopic Raman imaging approach.

Dixon, Jessica Z. [Georgia Institute of Technology↗
DOE OSTI2022

Co-Based superalloy morphology evolution: A phase field study based on experimental thermodynamic and kinetic data

Cobalt-based superalloys with two phase $\gamma$/$\gamma '$ microstructures offer great promise as candidates for next-generation high-temperature alloys for applications, such as turbine blades. It is essential to understand the thermodynamic and kinetic factors that influence the microstructural evolution of these alloys in order to optimize the alloy compositions and processing steps with a goal to improve their coarsening, creep and rafting behavior. We are using a continuum phase field approach to study the diffusion process and to predict the equilibrium shapes of Co-Al-W $\gamma '$ precipitates. In order to obtain quantitatively predictive capabilities, we extract chemical free energies for the $\gamma$/$\gamma '$ phases based on CALculation of PHAse Diagrams (CALPHAD) thermodynamic data and diffusion mobilities for Co alloys based on CALPHAD kinetic data. We also use experimental or first-principles data for other quantities, such as misfit strain and interface information, for the parameterization of our model. A particular focus of our study is to understand how different energy balances, misfit strain and kinetics affect the coarsening and rafting behavior of $\gamma '$ precipitates, and the sensitivity of the final precipitate shape to materials parameters. Here, we find that the equilibrium shape of the precipitate results from a delicate competition between chemical, interfacial, and elastic energies, and it is very sensitive to changes in model parameters. Here, we examine how modeling input parameters affect the equilibrium shape of precipitates and relate these parameters to experimentally available values.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A water-soluble precursor for efficient silica polymerization by silicateins

Highlights: • New water-soluble silica acid precursor was suggested. • New precursor was highly effective with silicatein A1. • Optimal conditions for the silicatein activity were determined. Silicateins, the spicule-forming proteins from marine demosponges capable to polymerize silica, are popular objects of biomineralization studies due to their ability to form particles varied in shape and composition under physiological conditions. Despite the occurrence of the many approaches to nanomaterial synthesis using silicateins, biochemical properties of this protein family are poorly characterized. The main reason for this is that tetraethyl orthosilicate (TEOS), the commonly used silica acid precursor, is almost insoluble in water and thus is poorly available for the protein. To solve this problem, we synthesized new water-soluble silica precursor, tetra(glycerol)orthosilicate (TGS), and characterized biochemical properties of the silicatein A1 from marine sponge Latrunculia oparinae. Compared to TEOS, TGS ensured much greater activity of silicatein and was less toxic for the mammalian cell culture. We evaluated optimum conditions for the enzyme - pH range, temperature and TGS concentration. We concluded that TGS is a useful silica acid precursor that can be used for silica particles synthesis and in vivo applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning

In this work we accomplished the monitoring and prediction of porosity in laser powder bed fusion (LPBF) additive manufacturing process. This objective was realized by extracting physics-informed meltpool signatures from an in-situ dual-wavelength imaging pyrometer, and subsequently, analyzing these signatures via computationally tractable machine learning approaches. Porosity in LPBF occurs despite extensive optimization of processing conditions due to stochastic causes. Hence, it is essential to continually monitor the process with in-situ sensors for detecting and mitigating incipient pore formation. In this work a tall cuboid-shaped part (10 mm × 10 mm × 137 mm, material ATI 718Plus) was built with controlled porosity by varying laser power and scanning speed. This test caused various types of porosity, such as lack-of-fusion and keyhole formation, with varying degrees of severity in the part. The meltpool was continuously monitored using a dual-wavelength imaging pyrometer installed in the machine. Physically intuitive process signatures, such as meltpool length, temperature distribution, and ejecta (spatter) characteristics, were extracted from the meltpool images. Subsequently, relatively simple machine learning models, e.g., K-Nearest Neighbors, were trained to predict both the severity and type of porosity as a function of these physics-informed meltpool signatures. These models resulted in a prediction accuracy exceeding 95% (statistical F1-score). The same analysis was carried out with a complex, black-box deep learning convolutional neural network which directly used the meltpool images instead of physics-informed features. The convolutional neural network produced a comparable F1-score in the range of 89–97%. Finally, these results demonstrate that using pragmatic, physics-informed meltpool signatures within a simple machine learning model is as effective for flaw prediction in LPBF as using a complex and computationally demanding black-box deep learning model.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Temperature dependent localized surface plasmon resonance properties of supported gold nanoparticles

The well known localized surface plasmon resonance (LSPR) of gold nanoparticles (AuNPs) supported on a dielectric substrate depends on the particle shape, size and type of dielectric material. The particle size and shape mainly vary with the method of preparation and the parameters involved there in. In this report, we show preparation of AuNPs supported on quartz substrate by direct current sputtering followed by thermal annealing at an optimized temperature of 400 °C. The samples were characterized using optical absorption spectra, scanning electron microscopy (SEM) and the energy dispersive x-ray spectrum. The LSPR position could be tuned by varying annealing temperature. The LSPR was found to be blue shifted up to 10 nm with annealing temperature varying from 400 °C to 800 °C. The change in LSPR was ascribed to the morphology of AuNPs over quartz.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Ultra-high wear resistance of ultra-nanocrystalline diamond film: Correlation with microstructure and morphology

Nanostructured diamond films are having numerous unique properties including superior tribological behavior which is promising for enhancing energy efficiency and life time of the sliding devices. High wear resistance is the principal criterion for the smooth functioning of any sliding device. Such properties are achievable by tailoring the grain size and grain boundary volume fraction in nanodiamond film. Ultra-nanocrystalline diamond (UNCD) film was attainable using optimized gas plasma condition in a microwave plasma enhanced chemical vapor deposition (MPECVD) system. Crystalline phase of ultra-nanodiamond grains with matrix phase of amorphous carbon and short range ordered graphite are encapsulated in nanowire shaped morphology. Film showed ultra-high wear resistance and frictional stability in micro-tribological contact conditions. The negligible wear of film at the beginning of the tribological contact was later transformed into the wearless regime for prolonged sliding cycles. Both surface roughness and high contact stress were the main reasons of wear at the beginning of sliding cycles. However, the interface gets smoothened due to continuous sliding, finally leaded to the wearless regime.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

SU-E-T-542: Comparison of Stereotactic Radiosurgery (SRS) of Brain Lesions Using Gamma Knife, VMAT, IMRT, and Conformal Arcs

Purpose: To compare dose distributions in stereotactic radiation surgery of brain lesions using gamma Knife, VMAT, conformal arcs, and IMRT in order to provide an optimal treatment. Methods: Dose distributions from single shot of 4C model of Gamma Knife at the helmet collimation sizes of 4, 8, 14, and 18 mm in diameter were compared with full arcs with the square shapes of 4×4 (or 5×5), 8×8 (or 10×10), and spherical shapes of 16 or 20 mm in diameter using EDR3 films in the same gamma knife QA phantom. Plans for ten SRS cases with single and multiple lesions were created in gamma knife plans and Pinnacle plans. The external beam plans had enlarged field size by 2-mm and used single conformal full circle arc for solitary lesion and none coplanar arcs/beams for multiple lesions. Coverage, conformity index, dose to critical organs, and integral dose to the brain and nearby critical structures were compared on all plans. Structures and dose matrices were registered in a Velocity deformable image registration system. Results: Single full circle arc from Elekta beam-modulate MLC (4-mm leaf thickness) and agility MLC (5-mm leaf thickness) have larger penumbra and less flatness than that of Gamma Knife single shot. None-coplanar arcs or beams were required to achieve similar dose distribution. In general, Gamma Knife plans provided significant less integral dose than that of linac-based plans. Benefits of IMRT and VMAT versus gamma Knife and conformal arcs were not significant. Conclusion: Our dose measurement and treatment planning evaluation clearly demonstrated dose distribution differences amount current popular SRS modalities for small solitary and multiple brain lesions. The trend of using MLC shape beams or arcs to replace conventional cones should be revisited in order to keep lower integral dose if the late correlates with some radiation-induced side effects. Pilot grant from Elekta LLC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Super-resolution within a one-dimensional phononic crystal of resonators using time reversal in an equivalent circuit model

An equivalent circuit model has been developed to model a one-dimensional waveguide with many side-branch Helmholtz resonators. This waveguide constitutes a phononic crystal that has been shown to have decreased phase speed below the resonance frequency of an individual resonator. This decreased phase speed can be exploited to achieve super-resolution using broadband time reversal focusing techniques. It is shown that the equivalent circuit model is capable of quantifying this change in phase speed of the crystal and also the small-scale wave-resonator interactions within the crystal. The equivalent circuit model enables the parameterization of the physical variables and the optimization of the focusing bandwidth by balancing the combination of increasing resolution and decreasing amplitude near the resonance frequency. It is shown that the quality factor—in this case, the quality factor determined by the geometric shape of each resonator—controls the range of frequencies that are strongly affected by the Helmholtz resonators.

Kingsley, Adam D.↗
DOE OSTI2021

INTEGRATE - Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design technology can capture complex non-linear aerodynamic effects while being 100 times faster than design approaches based on computational fluid dynamics. This project enables innovation in wind turbine design by accelerating time to market through higher-accuracy early design iterations to reduce the levelized cost of energy. INVERTIBLE NEURAL NETWORKS Researchers are leveraging a specialized invertible neural network (INN) architecture along with the novel dimension-reduction methods and airfoil/blade shape representations developed by collaborators at the National Institute of Standards and Technology (NIST) learns complex relationships between airfoil or blade shapes and their associated aerodynamic and structural properties. This INN architecture will accelerate designs by providing a cost-effective alternative to current industrial aerodynamic design processes, including: - Blade element momentum (BEM) theory models: limited effectiveness for design of offshore rotors with large, flexible blades where nonlinear aerodynamic effects dominate - Direct design using computational fluid dynamics (CFD): cost-prohibitive - Inverse-design models based on deep neural networks (DNNs): attractive alternative to CFD for 2D design problems, but quickly overwhelmed by the increased number of design variables in 3D problems AUTOMATED COMPUTATIONAL FLUID DYNAMICS FOR TRAINING DATA GENERATION - MERCURY FRAMEWORK The INN is trained on data obtained using the University of Marylands (UMD) Mercury Framework, which has with robust automated mesh generation capabilities and advanced turbulence and transition models validated for wind energy applications. Mercury is a multi-mesh paradigm, heterogeneous CPU-GPU framework. The framework incorporates three flow solvers at UMD, 1) OverTURNS, a structured solver on CPUs, 2) HAMSTR, a line based unstructured solver on CPUs, and 3) GARFIELD, a structured solver on GPUs. The framework is based on Python, that is often used to wrap C or Fortran codes for interoperability with other solvers. Communication between multiple solvers is accomplished with a Topology Independent Overset Grid Assembler (TIOGA). NOVEL AIRFOIL SHAPE REPRESENTATIONS USING GRASSMAN SPACES We developed a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation as an analytic generative model, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data , (ii) improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes. TECHNOLOGY TRANSFER DEMONSTRATION - COUPLING WITH NREL WISDEM Researchers have integrated the inverse-design tool for 2D airfoils (INN-Airfoil) into WISDEM (Wind Plant Integrated Systems Design and Engineering Model), a multidisciplinary design and optimization framework for assessing the cost of energy, as part of tech-transfer demonstration. The integration of INN-Airfoil into WISDEM allows for the design of airfoils along with the blades that meet the dynamic design constraints on cost of energy, annual energy production, and the capital costs. Through preliminary studies, researchers have shown that the coupled INN-Airfoil + WISDEM approach reduces the cost of energy by around 1% compared to the conventional design approach. This page will serve as a place to easily access all the publications from this work and the repositories for the software developed and released through this pr...

aerodynamics↗
DOE OSTI2013

Localized Overheating Phenomena and Optimization of Spark-Plasma Sintering Tooling Design

The present paper shows the application of a three-dimensional coupled electrical, thermal, mechanical finite element macro-scale modeling framework of Spark Plasma Sintering (SPS) to an actual problem of SPS tooling overheating, encountered during SPS experimentation. The overheating phenomenon is analyzed by varying the geometry of the tooling that exhibits the problem, namely by modeling various tooling configurations involving sequences of disk-shape spacers with step-wise increasing radii. The analysis is conducted by means of finite element simulations, intended to obtain temperature spatial distributions in the graphite press-forms, including punches, dies, and spacers; to identify the temperature peaks and their respective timing, and to propose a more suitable SPS tooling configuration with the avoidance of the overheating as a final aim. Electric currents-based Joule heating, heat transfer, mechanical conditions, and densification are imbedded in the model, utilizing the finite-element software COMSOL™, which possesses a distinguishing ability of coupling multiple physics. Thereby the implementation of a finite element method applicable to a broad range of SPS procedures is carried out, together with the more specific optimization of the SPS tooling design when dealing with excessive heating phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SU-F-T-347: An Absolute Dose-Volume Constraint Based Deterministic Optimization Framework for Multi-Co60 Source Focused Radiotherapy

Purpose: Treatment plan optimization in multi-Co60 source focused radiotherapy with multiple isocenters is challenging, because dose distribution is normalized to maximum dose during optimization and evaluation. The objective functions are traditionally defined based on relative dosimetric distribution. This study presents an alternative absolute dose-volume constraint (ADC) based deterministic optimization framework (ADC-DOF). Methods: The initial isocenters are placed on the eroded target surface. Collimator size is chosen based on the area of 2D contour on corresponding axial slice. The isocenter spacing is determined by adjacent collimator sizes. The weights are optimized by minimizing the deviation from ADCs using the steepest descent technique. An iterative procedure is developed to reduce the number of isocenters, where the isocenter with lowest weight is removed without affecting plan quality. The ADC-DOF is compared with the genetic algorithm (GA) using the same arbitrary shaped target (254cc), with a 15mm margin ring structure representing normal tissues. Results: For ADC-DOF, the ADCs imposed on target and ring are (D100>10Gy, D50,10, 0<12Gy, 15Gy and 20Gy) and (D40<10Gy). The resulting D100, 50, 10, 0 and D40 are (9.9Gy, 12.0Gy, 14.1Gy and 16.2Gy) and (10.2Gy). The objectives of GA are to maximize 50% isodose target coverage (TC) while minimize the dose delivered to the ring structure, which results in 97% TC and 47.2% average dose in ring structure. For ADC-DOF (GA) techniques, 20 out of 38 (10 out of 12) initial isocenters are used in the final plan, and the computation time is 8.7s (412.2s) on an i5 computer. Conclusion: We have developed a new optimization technique using ADC and deterministic optimization. Compared with GA, ADC-DOF uses more isocenters but is faster and more robust, and achieves a better conformity. For future work, we will focus on developing a more effective mechanism for initial isocenter determination.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-C-BRB-02: Symmetric and Asymmetric MLC Based Lung Shielding and Dose Optimization During Translating Bed TBI

Purpose: The primary aim was to introduce a dose optimization method for translating bed total body irradiation technique that ensures lung shielding dynamically. Symmetric and asymmetric dynamic MLC apertures were employed for this purpose. Methods: The MLC aperture sizes were defined based on the radiological depth values along the divergent ray lines passing through the individual CT slices. Based on these RD values, asymmetrically shaped MLC apertures were defined every 9 mm of the phantom in superior-inferior direction. Individual MLC files were created with MATLAB™ and were imported into Eclipse™ treatment planning system for dose calculations. Lungs can be shielded to an optimum level by reducing the MLC aperture width over the lungs. The process was repeated with symmetrically shaped apertures. Results: Dose-volume histogram (DVH) analysis shows that the asymmetric MLC based technique provides better dose coverage to the body and optimum shielding of the lungs compared to symmetrically shaped beam apertures. Midline dose homogeneity is within ±3% with asymmetric MLC apertures whereas it remains within ±4.5% with symmetric ones (except head region where it drops down to −7%). The substantial over and under dosage of ±5% at tissue interfaces has been reduced to ±2% with asymmetric MLC technique. Lungs dose can be reduced to any desired limit. In this experiment lungs dose was reduced to 80% of the prescribed dose, as was desired. Conclusion: The novel asymmetric MLC based technique assures optimum shielding of OARs (e.g. lungs) and better 3-D dose homogeneity and body-dose coverage in comparison with the symmetric MLC aperture optimization. The authors acknowledge the financial and infrastructural support provided by Pakistan Institute of Engineering & Applied Sciences (PIEAS), Islamabad and Aga Khan University Hospital (AKUH), Karachi during the course of this research project. Authors have no conflict of interest with any national / international body for the presented work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Electron choreography at the attosecond time scale

Abstract In this work, we report on coherent control of electron dynamics in atoms via attosecond pulse-shaping. We show that the photoelectron emission from argon gas produced by absorption of an attosecond pulse train (APT) made of odd and even harmonics can be manipulated along the direction of polarization of the light by tuning the spectral components (amplitude and phase) of the pulse. In addition, we show that APTs produced with a two-color (400- plus 800 nm) femtosecond driving field exhibit high temporal tunability, which is optimized for an intensity ratio between the two colors in the range of 0.1 to 5%.

74 ATOMIC AND MOLECULAR PHYSICS↗