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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-T-580: New Tumor Modeling Using 3D Gel Dosimeter for Brain Stereoctactic Radiotherpy (SRT)

Purpose: The purpose of this study is to develop new tumor model using 3D printing with 3D dosimeter for brain stereoctactic radiotherpy (SRT). Methods: BANG{sup 3} polymer gel was prepared and the gel-filled glass vials were irradiated with a 6 MV photon beam to acquire the calibration curve that present the change of R2 (1/T{sub 2}) value with dose. Graded doses from 0 to 12 Gy with an interval of 2 Gy were delivered. A kit for calibration of gel dosimeter and an 2 tumor model phantoms with a spherical shape were produced using a 3D printer with a polylactic acid after its 3D images were created using Autodesk software. 3D printed tumor phantoms and EBT3 films were irradiated to compare with treatment plan. After irradiation, vials for calibration and tumor model phantoms were scanned at 9.4T MRI. The spin-spin relaxation times (T{sub 2}) according to the each dose were calculated to evaluate the dose response. Acquired images were analyzed using an ImageJ. Scanned MRI images of tumor models were transferred treatment planning system and these were registered to the CT images. In all treatment plans, two arc plans (CW and CCW) were designed to deliver 50 Gy for 10 fractions. For first PTV, treatment plan was accurately designed that 95% of dose to cover 100% of PTV. But 2nd PTV was not intentionally cover 100% of PTV to evaluate the intensity of delivered tumor phantom with polymer gel. We compared the 3D dose distributions obtained from measurements with the 3D printed phantom and calculated with the TPS. Results: 3D printed phantom with a polymer gel was successfully produced. The dose distributions showed qualitatively good agreement among gel, film, and RTP data. Conclusion: A hybrid phantom represents a useful to validate the 3D dose distributions for patient-specific QA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Detection of Local/Regional Events in Kuwait Using Next-Generation Detection Algorithms

Seismic networks around the world use conventional triggering algorithms to detect seismic signals in order to locate local/regional seismic events. Kuwait National Seismological Network (KNSN) of Kuwait Institute of Scientific Research (KISR) is operating seven broad-band and short-period three-component stations in Kuwait. The network is equipped with Nanometrics digitizers and uses Antelope and Guralp acquisition software for processing and archiving the data. In this study, we selected 10 days of archived hourly-segmented continuous data of five stations (Figure 1) and 250 days of continuous recording at MIB. For the temporary deployment our selection criteria was based on KNSN catalog intensity for the period of time we test the method. An autonomous event detection and clustering framework is employed to test a more complete catalog of this short period of time. The goal is to illustrate the effectiveness of the technique and pursue the framework for longer period of time.

58 GEOSCIENCES↗
DOE OSTI2022

Journal paper

Laser technology is being widely studied for controlled energy deposition for a range of applications, including flow control, ignition, combustion, and diagnostics. The absorption and scattering of laser radiation by liquid droplets in aerosols affects propagation of the laser beam in the atmosphere, while the ignition and combustion characteristics in combustion chambers are influenced by the evaporation rate of the sprayed fuel. In this work, we present a mathematical model built on OpenFOAM for laser heating and evaporation of a single droplet in the diffusion-dominated regime taking into account absorption of the laser radiation, evaporation process, and vapor flow dynamics. The developed solver is validated against available experimental and numerical data for heating and evaporation of ethanol and water droplets. The two main regimes—continuous and pulsed laser heating—are explored. For continuous laser heating, the peak temperature is higher for larger droplets. For pulsed laser heating, when the peak irradiance is close to transition to the boiling regime, the temporal dynamics of the droplet temperature does not depend on the droplet size. With the empirical normalization of time, the dynamics of the droplet shrinkage and cooling are found to be independent of droplet sizes and peak laser intensities.

42 ENGINEERING↗
DOE OSTI2026

BM3DORNL

BM3DORNL is a high-performance, open-source library for removing streak and ring artifacts from computed-tomography (CT) data, developed for neutron imaging at Oak Ridge National Laboratory's Spallation Neutron Source (VENUS beamline) and applicable to X-ray CT as well. Ring artifacts — concentric rings in reconstructed slices caused by detector pixel-to-pixel response non-uniformities — appear as vertical streaks in the sinogram and degrade both image quality and quantitative analysis. BM3DORNL operates in the sinogram domain using an adaptation of the BM3D (block-matching and 3D collaborative filtering) algorithm (Dabov et al., 2007). It provides a dedicated streak-removal mode, a true multi-scale BM3D variant (after Mäkinen et al., 2021) that suppresses wide streaks single-scale methods miss, and an alternative Fourier–SVD method (~2.6× faster) combining FFT-based energy detection with rank-1 SVD. The computationally intensive core is implemented in Rust with parallel (Rayon) block matching, integral-image pre-screening, and optimized transforms, and is exposed through a simple Python API (with an optional GUI) so it integrates directly into existing tomography reconstruction pipelines. It processes both 2D sinograms and 3D sinogram stacks, is pip-installable for Linux and macOS, and is documented at https://bm3dornl.readthedocs.io.

Zhang, Chen [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2015

Improving Data Mobility & Management for International Cosmology

In February 2015 the third workshop in the CrossConnects series, with a focus on Improving Data Mobility & Management for International Cosmology, was held at Lawrence Berkeley National Laboratory. Scientists from fields including astrophysics, cosmology, and astronomy collaborated with experts in computing and networking to outline strategic opportunities for enhancing scientific productivity and effectively managing the ever-increasing scale of scientific data. While each field has unique details which depend on the instruments employed, the type and scale of the data, and the structure of scientific collaborations, several important themes emerged from the workshop discussions. Findings, as well as a set of recommendations, are contained in their respective sections in this report.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Automated Labeling of Electron Microscopy Images Using Deep Learning

© 2018 IEEE. Searching for scientific data requires metadata providing a relevant context. Today, generating metadata is a time and labor intensive manual process that is often neglected, and important datasets are not accessible through search. We investigate the use of machine learning to generalize metadata from a subset of labeled data, thus increasing the availability of meaningful metadata for search. Specifically, we consider electron microscopy images collected at the National Center for Electron Microscopy (NCEM) at the Lawrence Berkeley National Laboratory (LBNL) and use deep learning to discern characteristics from a small subset of labeled images and transfer labels to the entire image corpus. Relatively small training set sizes and a minimum resolution of 512\times 512 pixels required by the application domain pose unique challenges. We overcome these challenges by using a simple yet powerful convolutional network architecture that limits the number of free parameters to lower the required amount of computational power and reduce the risk of overfitting. We achieve a classification accuracy of approximately 80% in discerning between images recorded in two operating modes of the electron microscope-transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM). We use transfer learning-i.e., re-using the pre-trained convolution layers from the TEM vs. STEM classification problem-to generalize labels and achieve an accuracy of approximately 70 % despite current experiments being limited to small training data sets. We present these predictions as suggestions to domain scientists through a web-based tool to accelerate the labeling process with the goal of further validating our approach and improving the accuracy of automatically created labels.

Weber, Gunther H↗
DOE OSTI2013

Summer Student Internship working on the GPU

This summer internship consisted of learning computer programming skills and languages including Thrust, CUDA, C++, C and Linux. The application of this programming is for use in GPU, graphics processing units, that are processors that perform math intensive calculations rapidly in three dimensions typically in advanced video games (“NVIDIA GeForce…”). Our goal is to apply this technology towards exa-scale computing on the LANL supercomputing infrastructure. My mentors use these machines to do computations. The completed algorithms include KD tree and Top K. In order to access the GPU, CUDA was used. CUDA is a parallel computer architecture for general computing on the GPUs. There are different means by which to access CUDA. The first approach uses libraries, like Thrust, Linear Algebra, and Signal and Image Processing. Another approach parallelizes loops in Fortran or C and in the last approach people develop custom parallel algorithms using familiar language (“What is CUDA”). The algorithms I worked on this summer use the first approach of using the thrust library of parallel algorithms and data structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (4th Annual Report)

Nuclear plant sites collect and store large volumes of data collected from various equipment and systems. These datasets typically include plant process parameters, maintenance records, technical logs, online monitoring data, and equipment failure data. The collection of such data affords an opportunity to leverage data-driven machine learning and artificial intelligence technologies to provide diagnostic and prognostic capabilities within the nuclear power industry to reduce operating and maintenance costs. In this way, nuclear energy can become more economically competitive with other energy sources, and premature closures can be avoided. From a maintenance standpoint, savings can be achieved by leveraging machine learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose and predict potential faults within the system. Improved model accuracy can lead to reductions in unnecessary maintenance and more efficient planning of future maintenance, thus lowering the costs associated with parts, labor, and unnecessary planned, forced, or extended outages. From an operations perspective, cost savings can be generated by shifting from route-based monitoring to wireless technologies for online monitoring, and by transitioning from onsite- to cloud-based computing and storage services. Wireless monitoring would reduce the operator manhours required for taking routine measurements, while cloud computing services would generate cost savings by reducing the amount of hardware needing to be purchased and maintained—all while scaling to both computational and storage demands. This report summarizes this project’s effort to shift from costly, labor-intensive preventative maintenance to cheaper predictive maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Line Ratios for Solar Wind Charge Exchange with Comets

Charge exchange (CX) has emerged in X-ray emission modeling as a significant process that must be considered in many astrophysical environments—particularly comets. Comets host an interaction between solar wind ions and cometary neutrals to promote solar wind charge exchange (SWCX). X-ray observatories provide astronomers and astrophysicists with data for many X-ray emitting comets that are impossible to accurately model without reliable CX data. Here, we utilize a streamlined set of computer programs that incorporate the multi-channel Landau–Zener theory and a cascade model for X-ray emission to generate cross sections and X-ray line ratios for a variety of bare and non-bare ion single electron capture (SEC) collisions. Namely, we consider collisions between the solar wind constituent bare and H-like ions of C, N, O, Ne, Na, Mg, Al, and Si and the cometary neutrals H{sub 2}O, CO, CO{sub 2}, OH, and O. To exemplify the application of this data, we model the X-ray emission of Comet C/2000 WM1 (linear) using the CX package in SPEX and find excellent agreement with observations made with the XMM-Newton RGS detector. Our analyses show that the X-ray intensity is dominated by SWCX with H, while H{sub 2}O plays a secondary role. This is the first time, to our knowledge, that CX cross sections have been implemented into a X-ray spectral fitting package to determine the H to H{sub 2}O ratio in cometary atmospheres. The CX data sets are incorporated into the modeling packages SPEX and Kronos .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Exploiting data representation for fault tolerance

Incorrect computer hardware behavior may corrupt intermediate computations in numerical algorithms, possibly resulting in incorrect answers. Prior work models misbehaving hardware by randomly flipping bits in memory. We start by accepting this premise, and present an analytic model for the error introduced by a bit flip in an IEEE 754 floating-point number. We then relate this finding to the linear algebra concepts of normalization and matrix equilibration. In particular, we present a case study illustrating that normalizing both vector inputs of a dot product minimizes the probability of a single bit flip causing a large error in the dot product's result. Moreover, the absolute error is either less than one or very large, which allows detection of large errors. Then, we apply this to the GMRES iterative solver. We count all possible errors that can be introduced through faults in arithmetic in the computationally intensive orthogonalization phase of GMRES, and show that when the matrix is equilibrated, the absolute error is bounded above by one.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

New estimates of extensive-air-shower energies on the basis of signals in scintillation detectors

New formulas for estimating the energy of inclined extensive air showers (EASs) on the basis of signals in detectors by means of an original method and detailed tables of signals induced in scintillation detectors by photons, electrons, positrons, and muons and calculated with the aid of the GEANT4 code package were proposed in terms of the QGSJETII-04, EPOS LHC, and GHEISHA models. The parameters appearing in the proposed formulas were calculated by employing the CORSIKA code package. It is shown that, for showers of zenith angles in the range of 20◦–45◦, the standard constant-intensity-cut method, which is used to interpret data from the Yakutsk EAS array, overestimates the shower energy by a factor of 1.2 to 1.5. It is proposed to employ the calculated VEM (Vertical Equivalent Muon) signal units of 10.8 and 11.4 MeV for, respectively, ground-based and underground scintillation detectors and to take into account the dependence of signals on the azimuthal angle of the detector position and fluctuations in the development of showers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

SU-F-T-256: 4D IMRT Planning Using An Early Prototype GPU-Enabled Eclipse Workstation

Purpose: True 4D IMRT planning, based on simultaneous spatiotemporal optimization has been shown to significantly improve plan quality in lung radiotherapy. However, the high computational complexity associated with such planning represents a significant barrier to widespread clinical deployment. We introduce an early prototype GPU-enabled Eclipse workstation for inverse planning. To our knowledge, this is the first GPUintegrated Eclipse system demonstrating the potential for clinical translation of GPU computing on a major commercially-available TPS. Methods: The prototype system comprised of four NVIDIA Tesla K80 GPUs, with a maximum processing capability of 8.5 Tflops per K80 card. The system architecture consisted of three key modules: (i) a GPU-based inverse planning module using a highly-parallelizable, swarm intelligence-based global optimization algorithm, (ii) a GPU-based open-source b-spline deformable image registration module, Elastix, and (iii) a CUDA-based data management module. For evaluation, aperture fluence weights in an IMRT plan were optimized over 9 beams,166 apertures and 10 respiratory phases (14940 variables) for a lung cancer case (GTV = 95 cc, right lower lobe, 15 mm cranio-caudal motion). Sensitivity of the planning time and memory expense to parameter variations was quantified. Results: GPU-based inverse planning was significantly accelerated compared to its CPU counterpart (36 vs 488 min, for 10 phases, 10 search agents and 10 iterations). The optimized IMRT plan significantly improved OAR sparing compared to the original internal target volume (ITV)-based clinical plan, while maintaining prescribed tumor coverage. The dose-sparing improvements were: Esophagus Dmax 50%, Heart Dmax 42% and Spinal cord Dmax 25%. Conclusion: Our early prototype system demonstrates that through massive parallelization, computationally intense tasks such as 4D treatment planning can be accomplished in clinically feasible timeframes. With further optimization, such systems are expected to enable the eventual clinical translation of higher-dimensional and complex treatment planning strategies to significantly improve plan quality. This work was partially supported through research funding from National Institutes of Health (R01CA169102) and Varian Medical Systems, Palo Alto, CA, USA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Powering Circularity Through Data Reporting and Collection

Sustainability and Circular Economy have many metrics for evaluation. Calculating mass intensity, energy return on investment, financial payback, and recycling rate for proposed technology changes and lifecycle management can support decision making. Robust data with modeling tools can perform these calculations, informing good decision making. Analyses show that reliability is more critical than recyclability. Improved data gathering and tool accessibility will support our industry to make more circular choices for PV lifecycle management.

14 SOLAR ENERGY↗
DOE OSTI2013

Integrating Online Compression to Accelerate Large-Scale Data Analytics Applications

Abstract—With growing dataset sizes, and as computing cycles are increasing faster than storage and wide-area bandwidths, compression appears like a promising approach for improving the performance of large-scale data analytics applications. In this context, this paper makes the following contributions. First, we develop a new compression methodology, which exploits the similarities between spatial and/or temporal neighbors in a simulation dataset, and enables high compression ratios and low decompression costs. Second, we have developed a framework that can be used to incorporate a variety of compression and decompression algorithms. This framework also supports a simple API to allow integration with an existing application or data processing middleware. Once a compression algorithm is implemented, this framework can allow multi-threaded retrieval, multi-threaded data decompression, and use of informed prefetching and caching. By integrating this framework with a data-intensive middleware, we have applied our compression methodology and framework to three applications over two datasets, including a GCRM climate model dataset. We obtained an average compression ratio of 51.68%, and up to 53.27% improvement in execution time of data analysis applications.

Big Data, I/O, HPC↗
DOE OSTI2013

Digital tomosynthesis (DTS) for verification of target position in early stage lung cancer patients

Purpose: The ability to verify intrafraction tumor position is clinically useful for hypofractionated treatments. Short arc kV digital tomosynthesis (DTS) could facilitate more frequent target verification. The authors used DTS combined with triangulation to determine the mean temporal position of small-volume lung tumor targets treated with stereotactic radiotherapy. DTS registration results were benchmarked against online clinical localization using registration between free-breathing cone-beam computed tomography (CBCT) and the average intensity projection (AvIP) of the planning 4DCT.Methods: In this retrospective study, 76 sets of kV-projection images from online CBCT scans of 13 patients were used to generate DTS image slices (CB-DTS) with nonclinical research software (DTS Toolkit, Varian Medical Systems). Three-dimensional tumor motion was 1.3–4 mm in six patients and 6.1–25.4 mm in seven patients on 4DCT (significant difference in the mean of the groups, P < 0.01). The 4DCT AvIP was used to digitally reconstruct the Reference-DTS. DTS registration and DTS registration combined with triangulation were investigated. Progressive shortening of total DTS arc lengths from 95° to 35° around 0° gantry position was evaluated for different scenarios: DTS registration using the entire arc; DTS registration plus triangulation using two nonoverlapping arcs; and for 55° and 45° total gantry rotation, DTS registration plus triangulation using two overlapping arcs. Finally, DTS registration plus triangulation performed at eight gantry angles, each separated by 45° was evaluated using full fan kV projection data for one patient with an immobile tumor and five patients with mobile tumors.Results: For DTS registration alone, shortening arc length did not influence accuracy in X- and Y-directions, but in Z-direction, mean deviations from online CBCT localization systematically increased for shorter arc length (P < 0.05). For example, using a 95° arc mean DTS-CBCT difference was 0.8 mm (1 SD = 0.6 mm) and for a 35° arc the mean was 2.4 mm (1 SD = 1.7 mm). DTS plus triangulation using nonoverlapping-arcs increased accuracy in Z-direction for tested arc lengths ≤55° (P < 0.01). Overlapping arcs increased accuracy in Y-direction for tumors with motion >4 mm (P < 0.02) but increased Z-direction accuracy was only observed with 55° total gantry rotation. The 95th percentile deviations with this overlapping technique in X-, Y-, and Z-directions were 1.3, 2.0, and 2.5 mm, respectively. For the five patients with mobile tumors where DTS + triangulation was performed with 45° intervals, the pooled deviation from online CBCT correction showed, for X-, Y-, and Z-directions, mean of 1.1 mm, standard deviations (SD) of 0.9, 1.0, and 0.9 mm, respectively. The mean + 2 SD was <3 mm for each direction.Conclusions: Short-arc DTS verification of time averaged lung tumor position is feasible using free-breathing kV projection data and the AvIP of the 4DCT as a reference. Observed differences between DTS and online CBCT registration with AvIP were ≤3 mm (mean + 2 SD), however, the increased temporal resolution of DTS + triangulation also identified short period deviations from the average target position on the CBCT. Short-arc DTS appears promising for intrafraction tumor position monitoring during stereotactic lung radiotherapy delivered with a rotational technique.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Peregrine Software Development: Report on the Code Conversion From Python to C++

This work package seeks to convert the Peregrine software tool from its original Python implementation to a production version based on the C++ language. Peregrine is a powerful research platform with a multitude of advanced data analytics and data visualization functionalities. Developed by scientists to explore multimodal and multidimensional data related to the production of components using powder bed additive manufacturing processes, the tool implements state-of-the-art algorithms to assist machine users in making build or part quality determinations. Given that Peregrine is data-intensive, the goal of this conversion is to enhance the tool’s flexibility and interactivity and reduce the number of code dependencies to facilitate its deployment as part of the ongoing technology transfer campaign. This brief document provides an overview of Peregrine’s functionalities and capabilities, along with a detailed description of the core functionalities that have been implemented to date in the new C++ version. This document serves as a development update at the end of the first year of the ongoing conversion and will be regularly updated as progress continues.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

District heating utilizing waste heat of a data center: High-temperature heat pumps

Data centers are energy-intensive facilities with substantial low-grade waste heat. High-temperature heat pumps can be critical in boosting the data center’s waste heat for district heating, improving the system-level energy efficiency of data centers, and reducing CO 2 emissions in district heating. This study built thermodynamic models to assess high-temperature heat pumps with six configurations using low global warming potential refrigerants to supply heat up to 120 °C. The heat pump configurations include single-stage or two-stage cycles with advanced components, such as internal heat exchanger, economizer, flash tank, or parallel compressor. The refrigerants include R1234ze(Z), R1233ed(E), R1224yd(Z), R600, and R600a, and R245fa is used as a reference. A case study was carried out to recover the waste heat from the Frontier high-performance computing data center and provide hot water for district heating at the US Department of Energy’s Oak Ridge National Laboratory campus. The optimized performance of high-temperature heat pumps is characterized with various effectiveness of internal heat exchangers, and the operating parameters of economizer or flash tank, as well as their combination. The results show that the configurations of two-stage cycles with internal heat exchanger + flash tank and internal heat exchanger + economizer/parallel-compressor provide the highest coefficient of performance under scenarios of the maximum allowable value and a fixed value (0.3) of the internal heat exchangers’ effectiveness, respectively. R1234ze(Z) and R600a are the most promising refrigerants, considering trade-offs between the coefficient of performance and the volumetric heating capacity. The single-stage cycle with internal heat exchanger + economizer/parallel-compressor using R1234ze(Z) is recommended for utilizing Fronter’s waste heat in district heating. A one mega-watt high-temperature heat pump will reduce 33,100–33,200 metric tons of CO2 emission annually, corresponding to 85.4 %–85.6 % of equivalent CO2 emissions from natural gas boilers. Here, this study provides good guidelines for designing and deploying high-temperature heat pumps to support sustainable data centers and decarbonize district heating in the US.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Water–Hydrocarbon Interactions in Anionic Pyrene Monohydrate

Interactions between water and polycyclic aromatic hydrocarbons are essential in many aspects of chemistry, from interstellar and atmospheric processes to interfacial hydrophobicity and wetting phenomena. Despite their growing importance, the intermolecular potentials of the water-hydrocarbon interactions are underdeveloped compared to water-water potentials, and there are similarly few experimental probes that are sensitive to the details of the water-hydrocarbon potential. We present a combined experimental and computational study of anionic pyrene monohydrate, one of the simplest water/hydrocarbon clusters. The action spectrum in the OH region of the mass-selected cluster ion provides a rigorous benchmark for intermolecular potentials and computational methodologies. We identify missing intermolecular interactions and shortcomings in conventional dynamics calculations by comparing experimental data to density functional theory and classical molecular dynamics calculations. Kinetic trapping is prevalent, even for one water molecule and one pyrene molecule, leading to slow equilibration in conventional molecular dynamics calculations, even on nanosecond timescales and at low temperatures (50 K). At constant energy, temperature fluctuations for the pair of molecules are substantial. Immersing the system in a bath of soft spheres and employing parallel tempering alleviates kinetic trapping and dampens temperature fluctuations, bringing the system closer to the thermodynamic limit. With such augmented sampling, a simple, flexible water model reproduces the linewidth and the asymmetric broadening of the symmetric OH stretching mode, which we assign to spectral diffusion. In the OH stretching region, dynamics calculations predict a more intense antisymmetric peak than experiments observe but do not predict the bimodal split symmetric peak that the experiments show. Furthermore, our work suggests that electronic polarization, missing in the empirical force field, is responsible for the first discrepancy and that quantum nuclear effects, captured neither in density functional theory nor in classical dynamics, may be responsible for the second.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗