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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Application of IR Thermography with Thermal Diffusivity Analysis for Detection of Plies Displacement in CFRP Composites

This paper presents an efficient nondestructive testing (NDT) method for detection of plies displacement in carbon fiber reinforced plastic (CFRP) composites using the active thermography technique. To assess the capability of the proposed technique for detection of plies displacement, the CFRP composite specimens with simulated fault were designed and manufactured. The IR thermography measurements were conducted using two-sided experimental arrangement. From recorded sequences of thermal images, the temperature variations versus time plots were extracted to obtain the maximum thermal contrasts. For quantitative interpretation of the results, the thermal diffusivity values for each composite material were determined and related to the fiber volume fraction. The experimental results showed that the thermal diffusivity increases with an increase of fiber volume fraction; further, the values of thermal diffusivity are specimen thickness dependent. The obtained values of thermal diffusivity varied from 1.5 × 10{sup −7} m{sup 2}/s (for 3.2 mm composite with 8.5 vol.% carbon fiber) to 2.6 × 10{sup −7} m{sup 2}/s (for 7.7 mm composite with 34.1 vol.% carbon fiber). On the basis of these results, it was concluded that the active thermography combined with thermal diffusivity analysis can be considered as a reliable NDT technique for detection of plies displacement in CFRP composites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning model combining convolutional deep neural network with a self-attention mechanism for AC optimal power flow

Alternating current optimal power flow (OPF) analysis is critical for efficient and reliable operation of power systems. For large systems or repetitive computations, the traditional methods such as the direct and gradient methods, or non-traditional methods, such as the genetic algorithm and simulating annealing, are time-consuming and unsuitable for real-time computing. The work in this paper proposes a novel framework to obtain the optimal solution of power flow in real-time using a combination of convolutional neural networks and a self-attention mechanism. All parameters of the power networks are rearranged in an image-like shape of a multi-channel image where each channel is a two-dimensional matrix. The proposed approach is adaptive with every input size of power systems as well as frequent variations of network topologies without intervention to the framework core. The encompassment of all power system contexts in which all parameters of internal elements, generation costs, and topology information are included, contributes to the higher accuracy of inference compared to other current machine-learning-based OPF-solving methods. Besides, the proposed framework established on ubiquitous platforms is effortlessly integrated into current infrastructures of power systems, and the great efficiency along with the computation speed may serve as a critical point for practical implications, such as enabling faster decision-making during real-time operations, predicting system contingencies, and remedial actions based on an offline pre-trained model. Furthermore, this supervised learning process is applied to the dataset of four case studies of meshed power systems: the IEEE 5-bus system (IEEE-5), the IEEE 30-bus system (IEEE-30), the IEEE 39-bus system (IEEE-39), and the IEEE 57-bus system (IEEE-57) to prove the efficacy of the proposed method.

42 ENGINEERING↗
DOE OSTI2014

Interrater Reliability of the Categorization of Late Radiographic Changes After Lung Stereotactic Body Radiation Therapy

Purpose: Radiographic changes after lung stereotactic body radiation therapy (SBRT) have been categorized into 4 groups: modified conventional pattern (A), mass-like fibrosis; (B), scar-like fibrosis (C), and no evidence of increased density (D). The purpose of this study was to assess the interrater reliability of this categorization system in patients with early-stage non-small cell lung cancer (NSCLC). Methods and Materials: Seventy-seven patients were included in this study, all treated with SBRT for early-stage (T1/2) NSCLC at a single institution, with a minimum follow-up of 6 months. Six experienced clinicians familiar with post-SBRT radiographic changes scored the serial posttreatment CT images independently in a blinded fashion. The proportion of patients categorized as A, B, C, or D at each interval was determined. Krippendorff's alpha (KA), Multirater kappa (M-kappa), and Gwet's AC1 (AC1) scores were used to establish interrater reliability. A leave-one-out analysis was performed to demonstrate the variability among raters. Interrater agreement of the first and last 20 patients scored was calculated to explore whether a training effect existed. Results: The number of ratings ranged from 450 at 6 months to 84 at 48 months of follow-up. The proportion of patients in each category was as follows: A, 45%; B, 16%; C, 13%; and D, 26%. KA and M-kappa ranged from 0.17 to 0.34. AC1 measure range was 0.22 to 0.48. KA increased from 0.24 to 0.36 at 12 months with training. The percent agreement for pattern A peaked at 12 month with a 54% chance of having >50% raters in agreement and decreased over time, whereas that for patterns B and C increased over time to a maximum of 20% and 22%, respectively. Conclusion: This post-SBRT radiographic change categorization system has modest interrater agreement, and there is a suggestion of a training effect. Patterns of fibrosis evolve after SBRT and alternative categorization systems should be evaluated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Machine learning-based optimization of air-cooled heat sinks

Machine learning-based models using Artificial Neural Network (ANN) and greedy search algorithm are used to optimize air-cooled parallel plate-finned heat sinks (PPFHSs) subjected to laminar flow over an extensive range of design parameters. Here, the thermal and hydraulic performances of PPFHSs are represented by heat transfer coefficient (h) and pressure drop (ΔP), respectively. Optimization objectives for PPFHS designs can vary from industry to industry depending on their design priorities. The present study proposes a novel and generalized optimization method that defines practical optimization objectives and provides an accurate optimization process to design effective PPFHSs for a wide range of industrial applications with different design requirements. Three optimization objectives are presented in this study: (i) the largest h PΔ, (ii) the largest h within a specified maximum allowed flow rate, and (iii) the lowest weight that maximizes h for operation within the maximum allowed flow rate. While the shortcoming of the first objective is demonstrated, the other two objectives are found to be suitable for designing effective heat sinks (HSs) across different applications. Results suggest a promising trend from the third objective to develop HSs with ~ 37-68% lower weight, 80-85% reduced ΔP, and negligible penalty in h compared with optimized HSs obtained from the second objective. However, since the third objective leads to HSs with thinner fins, structural analysis should be performed to ensure reliable operation of the HSs.

42 ENGINEERING↗
DOE OSTI2026

Accurate determination of chemical abundances near a supermassive black hole

The metal abundances in galactic nuclei carry key information on the history of star formation and mass transfer in central regions of galaxies. X-ray fluorescence analysis is a unique tool to reliably measure the abundances of various elements via simple physics. Here we present a new observation of the active nucleus in the Circinus galaxy with the XRISM satellite at unprecedented X-ray energy resolution. The fluorescent iron Kα line profile modified by Compton scattering indicates that the material responsible for its emission is cold and metal rich and is located ≳0.024 pc from the supermassive black hole, consistent with the dusty torus region. The abundance pattern derived from comparing fluorescent line intensities of different metals shows subsolar ratios of argon- and calcium-to-iron and a supersolar ratio of nickel-to-iron. This abundance pattern is best produced by a combination in number fraction of 92$^{+2}_{–4}$% core-collapse supernovae from progenitor stars less massive than 20$^{+3}_{–2}$ M ⊙ and 8$^{+4}_{–2}$% type Ia supernovae. This suggests that gas feeding the supermassive black hole was enriched by recent core-collapse supernovae. Our findings imply that in metal-rich environments stars more massive than about 20 M ⊙ directly collapse into black holes or make faint supernovae without ejecting heavy metals into the space.

Astronomy and AstroPhysics↗
DOE OSTI2023

Short-lead seasonal precipitation forecast in northeastern Brazil using an ensemble of artificial neural networks

This study assesses the deterministic and probabilistic forecasting skill of a 1-month-lead ensemble of Artificial Neural Networks (EANN) based on low-frequency climate oscillation indices. The predictand is the February-April (FMA) rainfall in the Brazilian state of Ceará, which is a prominent subject in climate forecasting studies due to its high seasonal predictability. Additionally, the study proposes combining the EANN with dynamical models into a hybrid multi-model ensemble (MME). The forecast verification is carried out through a leave-one-out cross-validation based on 40 years of data. The EANN forecasting skill is compared with traditional statistical models and the dynamical models that compose Ceará’s operational seasonal forecasting system. A spatial comparison showed that the EANN was among the models with the smallest Root Mean Squared Error (RMSE) and Ranked Probability Score (RPS) in most regions. Moreover, the analysis of the area-aggregated reliability showed that the EANN is better calibrated than the individual dynamical models and has better resolution than Multinomial Logistic Regression for above-normal (AN) and below-normal (BN) categories. It is also shown that combining the EANN and dynamical models into a hybrid MME reduces the overconfidence of the extreme categories observed in a dynamically-based MME, improving the reliability of the forecasting system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A symmetric organic-based nonaqueous redox flow battery and its state of charge diagnostics by FTIR

Redox flow batteries have shown outstanding promise for grid-scale energy storage to promote utilization of renewable energy and improve grid stability. Nonaqueous battery systems can potentially achieve high energy density because of their broad voltage window. In this paper, we report a new organic redox-active material for use in a nonaqueous redox flow battery, 2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (PTIO) that has high solubility (>2.6 M) in organic solvents. PTIO exhibits electrochemically reversible disproportionation reactions and thus can serve as both anolyte and catholyte redox materials in a symmetric flow cell. The PTIO flow battery has a moderate cell voltage of ~1.7 V and shows good cyclability under both cyclic voltammetry and flow cell conditions. Moreover, we demonstrate that FTIR can offer accurate estimation of the PTIO concentration in electrolytes and determine the state of charge of the PTIO flow cell, which suggests FTIR potentially as a powerful online battery status sensor. In conclusion, this study is expected to inspire more insights in this under-addressed area of state of charge analysis aiming at operational safety and reliability of flow batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Evaluation of Analytical and Numerical Techniques for Defining the Radius of Influence for an Open-Loop Ground Source Heat Pump System

In an open-loop groundwater heat pump (GHP) system, groundwater is extracted, run through a heat exchanger, and injected back into the ground, resulting in no mass balance changes to the flow system. Although the groundwater use is non-consumptive, the withdrawal and injection of groundwater may cause negative hydraulic and thermal impacts to the flow system. Because GHP is a relatively new technology and regulatory guidelines for determining environmental impacts for GHPs may not exist, consumptive use metrics may need to be used for permit applications. For consumptive use permits, a radius of influence is often used, which is defined as the radius beyond which hydraulic impacts to the system are considered negligible. In this paper, the hydraulic radius of influence concept was examined using analytical and numerical methods for a non-consumptive GHP system in southeastern Washington State. At this location, the primary hydraulic concerns were impacts to nearby contaminant plumes and a water supply well field. The results of this study showed that the analytical techniques with idealized radial flow were generally unsuited because they over predicted the influence of the well system. The numerical techniques yielded more reasonable results because they could account for aquifer heterogeneities and flow boundaries. In particular, the use of a capture zone analysis was identified as the best method for determining potential changes in current contaminant plume trajectories. The capture zone analysis is a more quantitative and reliable tool for determining the radius of influence with a greater accuracy and better insight for a non-consumptive GHP assessment.

GHPs↗
DOE OSTI2014

Molecular dynamics simulations of the amino acid-ZnO (10-10) interface: A comparison between density functional theory and density functional tight binding results

We investigate the adsorption behavior of four different amino acids (glutamine, glutamate, serine, cysteine) on the zinc oxide (101{sup ¯}0) surface, comparing the geometry and energy associated with a number of different adsorption configurations. In doing this, we highlight the benefits and limits of using density-functional tight-binding (DFTB) with respect to standard density functional theory (DFT). The DFTB method is found to reliably reproduce the DFT adsorption geometries. Analysis of the adsorption configurations emphasizes the fundamental role of the first hydration layer in mediating the interactions between the amino acids and the surface. Direct surface-molecule bonds are found to form predominantly via the carboxylate groups of the studied amino acids. No surface-mediated chemical reactions are observed, with the notable exception of a proton transfer from the thiol group of cysteine to a hydroxyl group of the surface hydration layer. The adsorption energies are found to be dominated both by the formation of direct or indirect surface-molecule hydrogen bonds, but also by the rearrangement of the hydrogen-bond network in surface proximity in a non-intuitive way. Energetic comparisons between DFTB and DFT are made difficult on one side by the long time necessary to achieve convergence of potential energy values in MD simulations and on the other side by the necessity of including higher-order corrections to DFTB to obtain a good description of the hydrogen bond energetics. Overall, our results suggest that DFTB is a good reference method to set the correct chemical states and the initial geometries of hybrid biomolecule/ZnO systems to be simulated with non-reactive force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: large-scale structure catalogues and measurement of the isotropic BAO between redshift 0.6 and 1.1 for the Emission Line Galaxy Sample

ABSTRACT We present the Emission Line Galaxy (ELG) sample of the extended Baryon Oscillation Spectroscopic Survey from the Sloan Digital Sky Survey IV Data Release 16. We describe the observations and redshift measurement for the 269 243 observed ELG spectra, and then present the large-scale structure catalogues, used for the cosmological analysis, and made of 173 736 reliable spectroscopic redshifts between 0.6 and 1.1. We perform a spherically averaged baryon acoustic oscillations (BAO) measurement in configuration space, with density field reconstruction: the data two-point correlation function shows a feature consistent with that of the BAO, the BAO model being only weakly preferred over a model without BAO (Δχ2 < 1). Fitting a model constrained to have a BAO feature provides a 3.2 per cent measurement of the spherically averaged BAO distance DV(zeff)/rdrag = 18.23 ± 0.58 at the effective redshift zeff = 0.845.

Raichoor, Anand↗
DOE OSTI2021

Inherent issues regarding the use of in situ x-ray diffraction measurements to determine temperature in shock-compressed metals

Temperature determination in shock compressed solids constitutes an important and long-standing scientific need. Since the reduction of Bragg diffracted peaks due to temperature increase, using the Debye-Waller factor, is well established, we examined the use of this approach to determine temperatures in shock compressed gold and platinum by representing the shocked state as a superposition of density and temperature changes. Comparison of the calculated and measured diffraction peaks did not show good agreement, because x-ray diffraction (XRD) profiles in the shock compressed state are not governed solely by density and temperature changes. XRD results are also influenced measurably by shock wave induced microstructural changes. Our results demonstrate that contributions from microstructural changes need to be incorporated and modeled in the theoretical analysis to use XRD measurements for reliable temperature determination in shock compressed solids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

SU-E-J-243: Reproducibility of Radiomics Features Through Different Voxel Discretization Levels in F18-FDG PET Images of Cervical Cancer

Purpose: Site-specific investigations of the role of Radiomics in cancer diagnosis and therapy are needed. We report of the reproducibility of quantitative image features over different discrete voxel levels in PET/CT images of cervical cancer. Methods: Our dataset consisted of the pretreatment PET/CT scans from a cohort of 76 patients diagnosed with cervical cancer, FIGO stage IB-IVA, age range 31–76 years, treated with external beam radiation therapy to a dose range between 45–50.4 Gy (median dose: 45 Gy), concurrent cisplatin chemotherapy and MRI-based Brachytherapy to a dose of 20–30 Gy (median total dose: 28 Gy). Two board certified radiation oncologists delineated Metabolic Tumor volume (MTV) for each patient. Radiomics features were extracted based on 32, 64, 128 and 256 discretization levels (DL). The 64 level was chosen to be the reference DL. Features were calculated based on Co-occurrence (COM), Gray Level Size Zone (GLSZM) and Run-Length (RLM) matrices. Mean Percentage Differences (Δ) of features for discrete levels were determined. Normality distribution of Δ was tested using Kolomogorov - Smirnov test. Bland-Altman test was used to investigate differences between feature values measured on different DL. The mean, standard deviation and upper/lower value limits for each pair of DL were calculated. Interclass Correlation Coefficient (ICC) analysis was performed to examine the reliability of repeated measures within the context of the test re-test format. Results: 3 global and 5 regional features out of 48 features showed distribution not significantly different from a normal one. The reproducible features passed the normality test. Only 5 reproducible results were reliable, ICC range 0.7 – 0.99. Conclusion: Most of the radiomics features tested showed sensitivity to voxel level discretization between (32 – 256). Only 4 GLSZM, 3 COM and 1 RLM showed insensitivity towards mentioned discrete levels.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-252: Reproducibility of Radiogenomic Image Features: Comparison of Two Semi-Automated Segmentation Methods

Purpose: Objective and reliable quantification of imaging phenotype is an essential part of radiogenomic studies. We compared the reproducibility of two semi-automatic segmentation methods for quantitative image phenotyping in magnetic resonance imaging (MRI) of glioblastoma multiforme (GBM). Methods: MRI examinations with T1 post-gadolinium and FLAIR sequences of 10 GBM patients were downloaded from the Cancer Image Archive site. Two semi-automatic segmentation tools with different algorithms (deformable model and grow cut method) were used to segment contrast enhancement, necrosis and edema regions by two independent observers. A total of 21 imaging features consisting of area and edge groups were extracted automatically from the segmented tumor. The inter-observer variability and coefficient of variation (COV) were calculated to evaluate the reproducibility. Results: Inter-observer correlations and coefficient of variation of imaging features with the deformable model ranged from 0.953 to 0.999 and 2.1% to 9.2%, respectively, and the grow cut method ranged from 0.799 to 0.976 and 3.5% to 26.6%, respectively. Coefficient of variation for especially important features which were previously reported as predictive of patient survival were: 3.4% with deformable model and 7.4% with grow cut method for the proportion of contrast enhanced tumor region; 5.5% with deformable model and 25.7% with grow cut method for the proportion of necrosis; and 2.1% with deformable model and 4.4% with grow cut method for edge sharpness of tumor on CE-T1W1. Conclusion: Comparison of two semi-automated tumor segmentation techniques shows reliable image feature extraction for radiogenomic analysis of GBM patients with multiparametric Brain MRI.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Community Energy by Design: A Simulation-Based Design Workflow Using Measured Data Clustering to Calibrate Urban Building Energy Models (UBEMs)

This paper presents a workflow that informs urban design decisions using measured data clustering to calibrate urban building energy models. The method's goal is to support urban design in terms of form, building systems configurations, as well as influencing user behavior aspects in the built environment through a systemic analysis of measured data to develop reliable future-case design scenario energy models. Detailed data on appliance-level electricity use are employed via data clustering to calibrate a urban building energy model for the Mueller community in Austin, TX, USA. The data were collected by the Pecan Street Institute for a year in 2014 from consumers in Austin and other surrounding cities. First, collected energy data were restructured and cleaned from corrupt and/or missing information. Second, in order to identify common energy use patterns, a model-based clustering algorithm for functional data was applied. Behavioral/usage profiles are determined through clustering and translated into usage schedules and behaviors. As a result, an urban building energy model built in the urban modeling interface (umi) was calibrated, with fully calibrated and semi-calibrated buildings, within a maximum calibration error margin of 14% for daily-scale averages. Finally, an illustration of calibrated-urban building energy model design case scenarios is presented, and implications on community energy potential effects are discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

High-performance End-to-End Integrity Verification on Big Data Transfer

The scale of scientific data generated by experimental facilities and simulations in high-performance computing facilities has been proliferating with the emergence of IoT-based big data. In many cases, this data must be transmitted rapidly and reliably to remote facilities for storage, analysis, or sharing, for the Internet of Things (IoT) applications. Simultaneously, IoT data can be verified using a checksum after the data has been written to the disk at the destination to ensure its integrity. However, this end-to-end integrity verification inevitably creates overheads (extra disk I/O and more computation). Thus, the overall data transfer time increases. In this article, we evaluate strategies to maximize the overlap between data transfer and checksum computation for astronomical observation data. Specifically, we examine file-level and block-level (with various block sizes) pipelining to overlap data transfer and checksum computation. We analyze these pipelining approaches in the context of GridFTP, a widely used protocol for scientific data transfers. Theoretical analysis and experiments are conducted to evaluate our methods. The results show that block-level pipelining is effective in maximizing the overlap mentioned above, and can improve the overall data transfer time with end-to-end integrity verification by up to 70% compared to the sequential execution of transfer and checksum, and by up to 60% compared to file-level pipelining.

data integrity↗
DOE OSTI2014

Noise estimation of beam position monitors at RHIC

Beam position monitors (BPM) are used to record the average orbits and transverse turn-by-turn displacements of the beam centroid motion. The Relativistic Hadron Ion Collider (RHIC) has 160 BPMs for each plane in each of the Blue and Yellow rings: 72 dual-plane BPMs in the insertion regions (IR) and 176 single-plane modules in the arcs. Each BPM is able to acquire 1024 or 4096 consecutive turn-by-turn beam positions. Inevitably, there are broadband noisy signals in the turn-by-turn data due to BPM electronics as well as other sources. A detailed study of the BPM noise performance is critical for reliable optics measurement and beam dynamics analysis based on turn-by-turn data.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

California Plug-In Electric Vehicle Infrastructure Projections: 2017-2025 - Future Infrastructure Needs for Reaching the State's Zero Emission-Vehicle Deployment Goals

This report analyzes plug-in electric vehicle (PEV) infrastructure needs in California from 2017 to 2025 in a scenario where the State's zero-emission vehicle (ZEV) deployment goals are achieved by household vehicles. The statewide infrastructure needs are evaluated by using the Electric Vehicle Infrastructure Projection tool, which incorporates representative statewide travel data from the 2012 California Household Travel Survey. The infrastructure solution presented in this assessment addresses two primary objectives: (1) enabling travel for battery electric vehicles and (2) maximizing the electric vehicle-miles traveled for plug-in hybrid electric vehicles. The analysis is performed at the county-level for each year between 2017 and 2025 while considering potential technology improvements. The results from this study present an infrastructure solution that can facilitate market growth for PEVs to reach the State's ZEV goals by 2025. The overall results show a need for 99k-130k destination chargers, including workplaces and public locations, and 9k-25k fast chargers. The results also show a need for dedicated or shared residential charging solutions at multi-family dwellings, which are expected to host about 120k PEVs by 2025. An improvement to the scientific literature, this analysis presents the significance of infrastructure reliability and accessibility on the quantification of charger demand.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Determing the Radiative Heat Transfer out of the Fireball of an Atmospheric Nuclear Detonation using Experimental Data

When Edgerton, Germeshausen and Grier, Inc. (EG&G) conducted the atmospheric nuclear tests in the 1950s, they made several continuous records of the light output over time with special "streak cameras." Once processed, these "streak films" contained long bands of varying optical density on black-and-white 35mm film. The purpose for creating them was to determine the time-dependent rate of radiative heat transfer out of the fireball. Back then, EG&G's manual examination methods were not precise enough to make complete analysis worthwhile, so the data was never fully analyzed. With the advent of new computer software, recently developed analysis techniques have reduced uncertainty in the data to where re-analysis is providing results far more reliable than anything EG&G published. Previously inaccessible information can now be accurately gathered from the original films. The method described here allows the streak films to be analyzed so a radiative power curve for an atmospheric nuclear detonation can be constructed using only experimental data. It was applied to five streak films here, though it may be applicable to other types of films as well. The data was plotted and compared to solutions generated with the Hybrid Chemistry (HYCHEM) software. The results are explained, and uncertainty values are provided. If the results from more films show consistency and the sources of uncertainty are mitigated, enough data may be discovered to create a correction factor for HYCHEM or to make more accurate yield determinations using G.I. Taylor's equations. Several other conclusions and recommendations are also posed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗