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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Accuracy, criteria, and clinical significance of visual assessment on diffusion-weighted imaging and apparent diffusion coefficient quantification for diagnosing acute appendicitis

Purpose: To assess the accuracy, criteria, and clinical significance of diffusion-weighted imaging (DWI) signal intensity and apparent diffusion coefficient (ADC) quantification for diagnosing acute appendicitis. Methods: Fifty-one patients with right lower abdominal pain [uncomplicated appendicitis (n = 25), complicated appendicitis (n = 10), and non-appendicitis (n = 16)] who underwent MR examination were enrolled in this retrospective study. Two radiologists independently measured appendiceal diameter and wall thickness. They assessed whether a wall defect, an abscess, extraluminal air, or an appendicolith was present on axial T2WI; evaluated intensity on DWI using a 5-point scale; and determined the ADC values of the appendix and peri-appendiceal tissue. Statistical analysis was performed to assess imaging findings for the diagnosis of appendicitis and complicated appendicitis. Cut-off values were determined using receiver operating characteristic analysis. Results: For diagnosing acute appendicitis, the accuracy improved from 78.4% using only T2WI to 86.3% using combined T2WI and DWI for reader 1 and from 82.4 to 86.3% for reader 2. For the appendix, the cut-off ADC values that diagnosed appendicitis were 1.41 × 10{sup −3} and 1.26 × 10{sup −3} mm{sup 2}/s with accuracies of 78.4% and 76.5%, respectively. For the peri-appendiceal tissue, these values of 1.03 × 10{sup −3} and 0.91 × 10{sup −3} mm{sup 2}/s differentiated between uncomplicated and complicated appendicitis with an accuracy of 97.1%. Conclusions: Combined DWI and T2WI provided high accuracy for diagnosing appendicitis. The inflamed appendix had lower ADC value than the normal appendix. The peri-appendiceal tissue presenting low ADC value was a notable finding of complicated appendicitis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Transforming microseismic clouds into near real-time visualization of the growing hydraulic fracture

SUMMARY Microseismic observations during unconventional reservoir stimulation are typically seen as a proxy for clusters of hydraulic fractures and the extent of the stimulated reservoir. Such straightforward interpretation is often misleading and fails to provide a physically reasonable image of the fracturing process. This paper demonstrates the application of a physics-based machine learning algorithm which enables a rapid and accurate fracture mapping from the microseismic data. Our training and validation data set relies on a history-matched geomechanical modelling workflow implemented in GEOS software for the Hydraulic Fracturing Test Site 1 (HFTS-1) project. For this study we augmented the simulated fracture growth through geostatistical modelling of induced seismicity, so that the synthetic microseismic catalogue matches the main statistical properties of the field observations. We formulated the problem of mapping the actual fracture in the clutter of events to parallel common video segmentation workflows: several past video frames (microseismic density snapshots) are passed through a deep convolutional network to classify whether a given voxel is associated with a fracture or intact rock. We found that for accurate fracture mapping, the network’s input and architecture must be augmented to incorporate the fluid injection parameters (pressure, rate, concentration of proppant, and location of the perforation within the cluster). The error rate for the network reached as little as 10 per cent of the fracture area, while a conventional microseismic interpretation approach yielded ∼300 per cent. Our approach also yields must faster predictions than conventional methods (minutes instead of weeks), and could enable engineers to make rapid decisions regarding engineering parameters (pumping rate, viscosity) in real time during stimulation.

58 GEOSCIENCES↗
DOE OSTI2022

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2020

Quantitative probing of the fast particle motion during the solidification of battery electrodes

Synchrotron x-ray tomography represents one of the most powerful imaging techniques that can visualize the three-dimensional microstructural complexity with a high spatial resolution. To date, however, the temporal resolution of this technique has been handicapped by the intrinsic limitations in the data acquisition speed and the lack of a suitable data processing method. The present study aims to fundamentally resolve this challenge by implementing a data analysis method that is based on differentiating discrete tomography reconstruction from a continuous scan reconstruction. With this methodological development, we capture and quantify the particle motion during the solidification of battery electrodes and reveal the statistics of the dynamically evolving motion in the drying process, which has been challenging to resolve. We discover that the particle motion exhibits a strong dependence on its geometric location within a drying electrode. Our results also imply that the final electrode quality can be controlled by balancing the solvent evaporation rate and the particle mobility in the region close to the drying surface.

25 ENERGY STORAGE↗
DOE OSTI2017

Detection theory for accurate and non-invasive skin cancer diagnosis using dynamic thermal imaging

Skin cancer is the most common cancer in the United States with over 3.5M annual cases. Presently, visual inspection by a dermatologist has good sensitivity (> 90%) but poor specificity (< 10%), especially for melanoma, which leads to a high number of unnecessary biopsies. Here we use dynamic thermal imaging (DTI) to demonstrate a rapid, accurate and non-invasive imaging system for detection of skin cancer. In DTI, the lesion is cooled down and the thermal recovery is recorded using infrared imaging. The thermal recovery curves of the suspected lesions are then utilized in the context of continuous-time detection theory in order to define an optimal statistical decision rule such that the sensitivity of the algorithm is guaranteed to be at a maximum for every prescribed false-alarm probability. The proposed methodology was tested in a pilot study including 140 human subjects demonstrating a sensitivity in excess of 99% for a prescribed specificity in excess of 99% for detection of skin cancer. To the best of our knowledge, this is the highest reported accuracy for any non-invasive skin cancer diagnosis method.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Extreme-Scale Distribution-Based Data Analysis

Scientists overview and identify regions of interest by transforming data into compact information descriptors that characterize simulation results and allow detailed analysis on demand. Among many existing feature descriptors, statistical information derived from data samples is a promising approach to taming the big data avalanche because data distributionscomputed from a population can compactly describe the presence and characteristics of salient data features with minimal data movement. The ability to computationally summarize and process data using distributions also provides an efficient and representative capture of information that can adjust to size and resource constraints, with the added benefit that uncertainty associated with results can be quantified and communicated. In this project, we have developed a distribution-based data analysis and visualization framework for optimizing in situ processing and analysis of extreme-scale scientific data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

FAST: Using Federal Fleet Data for Decision-Making

This presentation provides an overview of the information currently being collected by the US Department of Energy, US General Services Administration, and US Energy Information Administration about the federal government's fleet of motor vehicles. The recent transition to collecting this information at the individual vehicle level provides new ways of visualizing the fleet and its operation and of using the information to support new forms of data-driven decision-making about the fleet. This presentation provides three examples of the types of analysis and decision-making this dataset supports.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Machine-learning-enabled on-the-fly analysis of RHEED patterns during thin film deposition by molecular beam epitaxy

Thin film deposition is a fundamental technology for the discovery, optimization, and manufacturing of functional materials. Deposition by molecular beam epitaxy (MBE) typically employs reflection high-energy electron diffraction (RHEED) as a real-time in situ probe of the growing film. However, the state-of-the-art for RHEED analysis during deposition requires human observation. Here, we present an approach using machine learning (ML) methods to monitor, analyze, and interpret RHEED images on-the-fly during thin film deposition. In the analysis workflow, RHEED pattern images are collected at one frame per second and featurized using a pretrained deep convolutional neural network. The feature vectors are then statistically analyzed to identify changepoints; these changepoints can be related to changes in the deposition mode from initial film nucleation to a transition regime, smooth film deposition, and in some cases, an additional transition to a rough, islanded deposition regime. The feature vectors are additionally analyzed via graph analysis and community classification. The graph is quantified as a stabilization plot, and we show that inflection points in the stabilization plot correspond to changes in the growth regime. The full RHEED analysis workflow is termed RHAAPsody and includes data transfer and output to a visual dashboard. We demonstrate the functionality of RHAAPsody by analyzing the precaptured RHEED images from epitaxial depositions of anatase TiO2 on SrTiO3(001) and show that the analysis workflow can be executed in less than 1 s. Our approach shows promise as one component of ML-enabled real-time feedback control of the MBE deposition process.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Homogenization of time series from Portugal and its former colonies for the period from the late 19th to the early 21st century

Here, three homogenization software packages – AnClim, RhTestsV3 and HOMER – have been applied to monthly and annual temperature and pressure series from Portugal and its ex-colonies in Africa and Asia to detect non-climatic breaks. Homogenization tests in both absolute and relative mode were performed with an a posteriori statistical assessment to select the most probable breakpoints. Time series from neighbouring stations as well as reanalyses data were used as reference series. The reanalyses data sets were used due to lack of suitable neighbouring stations and also to test reanalyses as proxy data. A list of probable shifts is produced and will be used to support future global reanalyses. Moreover, temperature and pressure series were adjusted using adjustment factors that were obtained by calculating the difference between certain periods before and after the breaks. The accuracy of the adjusted series was verified subjectively (visually) and objectively using three verification techniques: correlation coefficient, central root-mean-square error and standard deviation. A positive impact of the applied adjustment in terms of all three scores was reflected in a majority of cases.

abrupt breaks↗
DOE OSTI2021

Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks

ABSTRACT The problem of anomaly detection in astronomical surveys is becoming increasingly important as data sets grow in size. We present the results of an unsupervised anomaly detection method using a Wasserstein generative adversarial network (WGAN) on nearly one million optical galaxy images in the Hyper Suprime-Cam (HSC) survey. The WGAN learns to generate realistic HSC-like galaxies that follow the distribution of the data set; anomalous images are defined based on a poor reconstruction by the generator and outlying features learned by the discriminator. We find that the discriminator is more attuned to potentially interesting anomalies compared to the generator, and compared to a simpler autoencoder-based anomaly detection approach, so we use the discriminator-selected images to construct a high-anomaly sample of ∼13 000 objects. We propose a new approach to further characterize these anomalous images: we use a convolutional autoencoder to reduce the dimensionality of the residual differences between the real and WGAN-reconstructed images and perform UMAP clustering on these. We report detected anomalies of interest including galaxy mergers, tidal features, and extreme star-forming galaxies. A follow-up spectroscopic analysis of one of these anomalies is detailed in the Appendix; we find that it is an unusual system most likely to be a metal-poor dwarf galaxy with an extremely blue, higher-metallicity H ii region. We have released a catalogue with the WGAN anomaly scores; the code and catalogue are available at https://github.com/kstoreyf/anomalies-GAN-HSC; and our interactive visualization tool for exploring the clustered data is at https://weirdgalaxi.es.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Monte Carlo study for designing a dedicated “D”-shaped collimator used in the external beam radiotherapy of retinoblastoma patients

Purpose: Retinoblastoma is the most common intraocular malignancy in the early childhood. Patients treated with external beam radiotherapy respond very well to the treatment. However, owing to the genotype of children suffering hereditary retinoblastoma, the risk of secondary radio-induced malignancies is high. The University Hospital of Essen has successfully treated these patients on a daily basis during nearly 30 years using a dedicated “D”-shaped collimator. The use of this collimator that delivers a highly conformed small radiation field, gives very good results in the control of the primary tumor as well as in preserving visual function, while it avoids the devastating side effects of deformation of midface bones. The purpose of the present paper is to propose a modified version of the “D”-shaped collimator that reduces even further the irradiation field with the scope to reduce as well the risk of radio-induced secondary malignancies. Concurrently, the new dedicated “D”-shaped collimator must be easier to build and at the same time produces dose distributions that only differ on the field size with respect to the dose distributions obtained by the current collimator in use. The scope of the former requirement is to facilitate the employment of the authors' irradiation technique both at the authors' and at other hospitals. The fulfillment of the latter allows the authors to continue using the clinical experience gained in more than 30 years. Methods: The Monte Carlo codePENELOPE was used to study the effect that the different structural elements of the dedicated “D”-shaped collimator have on the absorbed dose distribution. To perform this study, the radiation transport through a Varian Clinac 2100 C/D operating at 6 MV was simulated in order to tally phase-space files which were then used as radiation sources to simulate the considered collimators and the subsequent dose distributions. With the knowledge gained in that study, a new, simpler, “D”-shaped collimator is proposed. Results: The proposed collimator delivers a dose distribution which is 2.4 cm wide along the inferior-superior direction of the eyeball. This width is 0.3 cm narrower than that of the dose distribution obtained with the collimator currently in clinical use. The other relevant characteristics of the dose distribution obtained with the new collimator, namely, depth doses at clinically relevant positions, penumbrae width, and shape of the lateral profiles, are statistically compatible with the results obtained for the collimator currently in use. Conclusions: The smaller field size delivered by the proposed collimator still fully covers the planning target volume with at least 95% of the maximum dose at a depth of 2 cm and provides a safety margin of 0.2 cm, so ensuring an adequate treatment while reducing the irradiated volume.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Statistical and clustering analysis for disturbances: A case study of voltage dips in wind farms

This study proposes and evaluates an alternative statistical methodology to analyze a large number of voltage dips. For a given voltage dip, a set of lengths is first identified to characterize the root mean square (rms) voltage evolution along the disturbance, deduced from partial linearized time intervals and trajectories. Principal component analysis and K-means clustering processes are then applied to identify rms-voltage patterns and propose a reduced number of representative rms-voltage profiles from the linearized trajectories. This reduced group of averaged rms-voltage profiles enables the representation of a large amount of disturbances, which offers a visual and graphical representation of their evolution along the events, aspects that were not previously considered in other contributions. The complete process is evaluated on real voltage dips collected in intense field-measurement campaigns carried out in a wind farm in Spain among different years. The results are included in this paper.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Search of the Full Six Years of the Dark Energy Survey for Outer Solar System Objects

We present a search for outer solar system objects in the 6 yr of data from the Dark Energy Survey (DES). The DES covered a contiguous 5000 deg 2 of the southern sky with ≈80,000 3 deg 2 exposures in the grizY filters between 2013 and 2019. This search yielded 812 trans-Neptunian objects (TNOs), one Centaur and one Oort cloud comet, 458 reported here for the first time. We present methodology that builds upon our previous search on the first 4 yr of data. All images were reprocessed with an optimized detection pipeline that leads to an average completeness gain of 0.47 mag per exposure, as well as improved transient catalog production and algorithms for linkage of detections into orbits. All objects were verified by visual inspection and by the “sub-threshold significance,” the signal-to-noise ratio in the stack of images in which its presence is indicated by the orbit, but no detection was reported. This yields a pure catalog complete to r ≈ 23.8 mag and distances 29 < d < 2500 au. The TNOs have minimum (median) of 7 (12) nights’ detections and arcs of 1.1 (4.2) yr, and will have grizY magnitudes available in a further publication. We present software for simulating our observational biases for comparisons of models to our detections. Initial inferences demonstrating the catalog’s statistical power are: the data are inconsistent with the CFEPS-L7 model for the classical Kuiper Belt; the 16 “extreme” TNOs (a > 150 au, q > 30 au) are consistent with the null hypothesis of azimuthal isotropy; and nonresonant TNOs with q > 38 au, a > 50 au show a significant tendency to be sunward of major mean-motion resonances.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-E-I-91: Quantitative Assessment of Early Hepatocellular Carcinoma and Cavernous Hemangioma of Live Using In-Line Phase-Contrast X-Ray Imaging

Purpose: To investigate the potential utility of in-line phase-contrast imaging (ILPCI) technique with synchrotron radiation in detecting early hepatocellular carcinoma and cavernous hemangioma of live using in vitro model system. Methods: Without contrast agents, three typical early hepatocellular carcinoma specimens and three typical cavernous hemangioma of live specimens were imaged using ILPCI. To quantitatively discriminate early hepatocellular carcinoma tissues and cavernous hemangioma tissues, the projection images texture feature based on gray level co-occurrence matrix (GLCM) were extracted. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, difference average, difference entropy and inverse difference moment, were obtained respectively. Results: In the ILPCI planar images of early hepatocellular carcinoma specimens, vessel trees were clearly visualized on the micrometer scale. Obvious distortion deformation was presented, and the vessel mostly appeared as a ‘dry stick’. Liver textures appeared not regularly. In the ILPCI planar images of cavernous hemangioma of live specimens, typical vessels had not been found compared with the early hepatocellular carcinoma planar images. The planar images of cavernous hemangioma of live specimens clearly displayed the dilated hepatic sinusoids with the diameter of less than 100 microns, but all of them were overlapped with each other. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, and difference average, showed a statistically significant between the two types specimens image (P<0.01), except the texture parameters of difference entropy and inverse difference moment(P>0.01). Conclusion: The results indicate that there are obvious changes in morphological levels including vessel structures and liver textures. The study proves that this imaging technique has a potential value in evaluating early hepatocellular carcinoma and cavernous hemangioma of live.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-AB-207A-08: BEST IN PHYSICS (IMAGING): Advanced Scatter Correction and Iterative Reconstruction for Improved Cone-Beam CT Imaging On the TrueBeam Radiotherapy Machine

Purpose: To improve CBCT image quality for image-guided radiotherapy by applying advanced reconstruction algorithms to overcome scatter, noise, and artifact limitations Methods: CBCT is used extensively for patient setup in radiotherapy. However, image quality generally falls short of diagnostic CT, limiting soft-tissue based positioning and potential applications such as adaptive radiotherapy. The conventional TrueBeam CBCT reconstructor uses a basic scatter correction and FDK reconstruction, resulting in residual scatter artifacts, suboptimal image noise characteristics, and other artifacts like cone-beam artifacts. We have developed an advanced scatter correction that uses a finite-element solver (AcurosCTS) to model the behavior of photons as they pass (and scatter) through the object. Furthermore, iterative reconstruction is applied to the scatter-corrected projections, enforcing data consistency with statistical weighting and applying an edge-preserving image regularizer to reduce image noise. The combined algorithms have been implemented on a GPU. CBCT projections from clinically operating TrueBeam systems have been used to compare image quality between the conventional and improved reconstruction methods. Planning CT images of the same patients have also been compared. Results: The advanced scatter correction removes shading and inhomogeneity artifacts, reducing the scatter artifact from 99.5 HU to 13.7 HU in a typical pelvis case. Iterative reconstruction provides further benefit by reducing image noise and eliminating streak artifacts, thereby improving soft-tissue visualization. In a clinical head and pelvis CBCT, the noise was reduced by 43% and 48%, respectively, with no change in spatial resolution (assessed visually). Additional benefits include reduction of cone-beam artifacts and reduction of metal artifacts due to intrinsic downweighting of corrupted rays. Conclusion: The combination of an advanced scatter correction with iterative reconstruction substantially improves CBCT image quality. It is anticipated that clinically acceptable reconstruction times will result from a multi-GPU implementation (the algorithms are under active development and not yet commercially available). All authors are employees of and (may) own stock of Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Visual Fixations in Basketball Shooting: Differences between Shooting Conditions

Basketball is a sport where shooting is one of the most important factors that determines the success or failure of the teams. Therefore, basketball players need to shoot the ball accurately. The present study aimed to evaluate whether different shooting conditions influence the visual behavior of athletes. For this, the Tobbi Pro Glasses 3 equipment was used to evaluate the time of the first fixation, the number of fixations, and the total time of fixations in the basket, during the shooting movement. Different distances to the basket, simulated gym audience noise, and shooting with opposition were considered. A group of 18 athletes with an average age of 22 ± 3.72 years and an average basketball practice experience of 12.5 ± 4.52 years performed 10 valid shots from different distances and different shooting angles, with different restrictions, namely, shooting with simulated opposition and gym audience noise. Statistically significant differences between shooting with opposition and baseline, in terms of the number of fixations and the total time of fixation, were found. Regarding shooting with gym audience noise, differences only occur for the total time of fixations in one position. Despite this, in all variables and positions, the values were lower in shooting with constraints compared to the baseline.

Amaro, Catarina M. (ORCID:0000000303343503)↗
DOE OSTI2025

Collaborative: in situ visual analytics technologies for extreme scale combustion simulations

This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Vertebral Augmentation with Nitinol Endoprosthesis: Clinical Experience in 40 Patients with 1-Year Follow-up

Purpose: This study was designed to assess the clinical outcomes of patients treated by vertebral augmentation with nitinol endoprosthesis (VNE) to treat painful vertebral compression fractures. Methods: Forty patients with one or more painful osteoporotic VCF, confirmed by MRI and accompanied by back-pain unresponsive to a minimum 2 months of conservative medical treatment, underwent VNE at 42 levels. Preoperative and postoperative pain measured with Visual Analog Scale (VAS), disability measured by Oswestry Disability Index (ODI), and vertebral height restoration (measured with 2-dimensional reconstruction CT) were compared at last follow-up (average follow-up 15 months). Cement extravasation, subsequent fractures, and implant migration were recorded. Results: Long-term follow-up was obtained in 38 of 40 patients. Both VAS and ODI significantly improved from a median of 8.0 (range 5–10) and 66 % (range 44–88 %) to 0.5 (range 0–8) and 6 % (range 6–66 %), respectively, at 1 year (p < 0.0001). Vertebral height measurements comparing time points increased in a statistically significant manner (ANOVA, p < 0.001). Overall cement extravasation rate was 9.5 %. Discal and venous leakage rates were 7.1 and 0 % respectively. No symptomatic extravasations occurred. Five of 38 (13.1 %) patients experienced new spontaneous, osteoporotic fractures. No device change or migration was observed. Conclusions: VNE is a safe and effective procedure that is able to provide long-lasting pain relief and durable vertebral height gain with a low rate of new fractures and cement leakages.

62 RADIOLOGY AND NUCLEAR MEDICINE↗