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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-P-08: Medical Physics Perspective On Radiation Therapy Quality and Safety Considerations in Low Income Settings

Purpose: The last few years have seen a significant growth of interest in the global radiation therapy crisis. Various organizations are quantifying the need and providing aid in support of addressing the shortfall existing in many low-to-middle income countries (LMICs). The Lancet Oncology Commission report (Lancet Oncol. Sep;16(10):1153-86, 2015) projects a need of 22,000 new medical physicists in LMICs by 2035 if there is to be equal access globally. With the tremendous demand for new facilities, equipment and personnel, it is very important to recognize quality and safety considerations and to address them directly. Methods: A detailed examination of quality and safety publications was undertaken. A paper by Dunscombe (Front. Oncol. 2: 129, 2012) reviewed the recommendations of 7 authoritative reports on safety in radiation therapy and found the 12 most cited recommendations, summarized in order of most to least cited: training, staffing, documentation/standard operating procedures, incident learning, communication/questioning, check lists, QC/PM, dosimetric audit, accreditation, minimizing interruptions, prospective risk assessment, and safety culture. However, these authoritative reports were generally based on input from high income contexts. In this work, the recommendations were analyzed with a special emphasis on issues that are significant in LMICs. Results: The review indicated that there are significant challenges in LMICs with training and staffing ranking at the top in terms quality and safety. Conclusion: With the recognized need for expanding global access to radiation therapy, especially in LMICs, and the backing by multiple support organizations, quality and safety considerations must be overtly addressed. While multidimensional, training and staffing are top priorities. The use of outdated systems with poor interconnectivity, coupled with a lack of systematic QA in high patient load settings are additional concerns. Any support provided to lower resourced settings must address the multiple facets associated with these quality and safety indicators.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-180: A Reference Data Set for Testing Two Dimension Registration Algorithms

Purpose: To create and characterize a reference data set for testing image registration algorithms that transform portal image (PI) to digitally reconstructed radiograph (DRR). Methods: Anterior-posterior (AP) and Lateral (LAT) projection and DRR image pairs from nine cases representing four different anatomical sites (head and neck, thoracic, abdominal, and pelvis) were selected for this study. Five experts will perform manual registration by placing landmarks points (LMPs) on the DRR and finding their corresponding points on the PI using computer assisted manual point selection tool (CAMPST), a custom-made MATLAB software tool developed in house. The landmark selection process will be repeated on both the PI and the DRR in order to characterize inter- and -intra observer variations associated with the point selection process. Inter and an intra observer variation in LMPs was done using Bland-Altman (B&A) analysis and one-way analysis of variance. We set our limit such that the absolute value of the mean difference between the readings should not exceed 3mm. Later on in this project we will test different two dimension (2D) image registration algorithms and quantify the uncertainty associated with their registration. Results: Using one-way analysis of variance (ANOVA) there was no variations within the readers. When Bland-Altman analysis was used the variation within the readers was acceptable. The variation was higher in the PI compared to the DRR.ConclusionThe variation seen for the PI is because although the PI has a much better spatial resolution the poor resolution on the DRR makes it difficult to locate the actual corresponding anatomical feature on the PI. We hope this becomes more evident when all the readers complete the point selection. The reason for quantifying inter- and -intra observer variation tells us to what degree of accuracy a manual registration can be done. Research supported by William Beaumont Hospital Research Start Up Fund.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Sci-Thur PM - Colourful Interactions: Highlights 06: Patient-specific calibration of cone-beam computed tomographic (CBCT) image sets for on-line dose tracking and plan assessment

Purpose: To develop a radiotherapy dose tracking and plan evaluation technique using cone-beam computed tomography (CBCT) images. Methods: We developed a patient-specific method of calibrating CBCT image sets for dose calculation. The planning CT was first registered with the CBCT using deformable image registration (DIR). A scatter plot was generated between the CT numbers of the planning CT and CBCT for each slice. The CBCT calibration curve was obtained by least-square fitting of the data, and applied to each CBCT slice. The calibrated CBCT was then merged with original planning CT to extend the small field of view of CBCT. Finally, the treatment plan was copied to the merged CT for dose tracking and plan evaluation. The proposed patient-specific calibration method was also compared to two methods proposed in literature. To evaluate the accuracy of each technique, 15 head-and-neck patients requiring plan adaptation were arbitrarily selected from our institution. The original plan was calculated on each method’s data set, including a second planning CT acquired within 48 hours of the CBCT (serving as gold standard). Clinically relevant dose metrics and 3D gamma analysis of dose distributions were compared between the different techniques. Results: Compared to the gold standard of using planning CTs, the patient-specific CBCT calibration method was shown to provide promising results with gamma pass rates above 95% and average dose metric agreement within 2.5%. Conclusions: The patient-specific CBCT calibration method could potentially be used for on-line dose tracking and plan evaluation, without requiring a re-planning CT session.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Eukaryotic genomes from a global metagenomic data set illuminate trophic modes and biogeography of ocean plankton

ABSTRACT Metagenomics is a powerful method for interpreting the ecological roles and physiological capabilities of mixed microbial communities. Yet, many tools for processing metagenomic data are neither designed to consider eukaryotes nor are they built for an increasing amount of sequence data. EukHeist is an automated pipeline to retrieve eukaryotic and prokaryotic metagenome-assembled genomes (MAGs) from large-scale metagenomic sequence data sets. We developed the EukHeist workflow to specifically process large amounts of both metagenomic and/or metatranscriptomic sequence data in an automated and reproducible fashion. Here, we applied EukHeist to the large-size fraction data (0.8–2,000 µm) from Tara Oceans to recover both eukaryotic and prokaryotic MAGs, which we refer to as TOPAZ (Tara Oceans Particle-Associated MAGs). The TOPAZ MAGs consisted of >900 environmentally relevant eukaryotic MAGs and >4,000 bacterial and archaeal MAGs. The bacterial and archaeal TOPAZ MAGs expand upon the phylogenetic diversity of likely particle- and host-associated taxa. We use these MAGs to demonstrate an approach to infer the putative trophic mode of the recovered eukaryotic MAGs. We also identify ecological cohorts of co-occurring MAGs, which are driven by specific environmental factors and putative host-microbe associations. These data together add to a number of growing resources of environmentally relevant eukaryotic genomic information. Complementary and expanded databases of MAGs, such as those provided through scalable pipelines like EukHeist, stand to advance our understanding of eukaryotic diversity through increased coverage of genomic representatives across the tree of life. IMPORTANCE Single-celled eukaryotes play ecologically significant roles in the marine environment, yet fundamental questions about their biodiversity, ecological function, and interactions remain. Environmental sequencing enables researchers to document naturally occurring protistan communities, without culturing bias, yet metagenomic and metatranscriptomic sequencing approaches cannot separate individual species from communities. To more completely capture the genomic content of mixed protistan populations, we can create bins of sequences that represent the same organism (metagenome-assembled genomes [MAGs]). We developed the EukHeist pipeline, which automates the binning of population-level eukaryotic and prokaryotic genomes from metagenomic reads. We show exciting insight into what protistan communities are present and their trophic roles in the ocean. Scalable computational tools, like EukHeist, may accelerate the identification of meaningful genetic signatures from large data sets and complement researchers’ efforts to leverage MAG databases for addressing ecological questions, resolving evolutionary relationships, and discovering potentially novel biodiversity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Confronting a set of Skyrme and $\chi _{EFT}$ predictions for the crust of neutron stars

With the improved accuracy of neutron star observational data, it is necessary to derive new equation of state where the crust and the core are consistently calculated within a unified approach. For this purpose we describe non-uniform matter in the crust of neutron stars employing a compressible liquid-drop model, where the bulk and the neutron fluid terms are given from the same model as the one describing uniform matter present in the core. We then generate a set of fifteen unified equations of state for cold catalyzed neutron stars built on realistic modelings of the nuclear interaction, which belongs to two main groups: the first one derives from the phenomenological Skyrme interaction and the second one from χEFT Hamiltonians. The confrontation of these model predictions allows us to investigate the model dependence for the crust properties, and in particular the effect of neutron matter at low density. Here, the new set of unified equations of state is available at the CompOSE repository.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Is the magnitude of the Peccei–Quinn scale set by the landscape?

Rather general considerations of the string theory landscape imply a mild statistical draw towards large soft SUSY breaking terms tempered by the requirement of proper electroweak symmetry breaking where SUSY contributions to the weak scale are not too far from m weak ~ 100 GeV. Such a picture leads to the prediction that m h ~ 125 GeV while most sparticles are beyond current LHC reach. Here we explore the possibility that the magnitude of the Peccei-Quinn (PQ) scale f a is also set by string landscape considerations within the framework of a compelling SUSY axion model. First, we examine the case where the PQ symmetry arises as an accidental approximate global symmetry from a more fundamental gravity-safe Z$R\atop{24}$$ symmetry and where the SUSY mu parameter arises from a Kim-Nilles operator. The pull towards large soft terms then also pulls the PQ scale as large as possible. Unless this is tempered by rather severe (unknown) cosmological or anthropic bounds on the density of dark matter, then we would expect a far greater abundance of dark matter than is observed. This conclusion cannot be negated by adopting a tiny axion misalignment angle θ i because WIMPs are also overproduced at large f a . Hence, we conclude that setting the PQ scale via anthropics is highly unlikely. Instead, requiring soft SUSY breaking terms of order the gravity-mediation scale m 3/2 ~ 10 -100 TeV places the mixed axion-neutralino dark matter abundance into the intermediate scale sweet zone where f a ~ 10 11 -10 12 GeV. We compare our analysis to the more general case of a generic SUSY DFSZ axion model with uniform selection on theta_i but leading to the measured dark matter abundance: this approach leads to a preference for f a ~ 10 12 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Extraction and validation of a new set of CMS pythia8 tunes from underlying-event measurements

New sets of CMS underlying-event parameters ("tunes") are presented for the PYTHIA8 event generator. These tunes use the NNPDF3.1 parton distribution functions (PDFs) at leading (LO), next-to-leading (NLO), or next-to-next-to-leading (NNLO) orders in perturbative quantum chromodynamics, and the strong coupling evolution at LO or NLO. Measurements of charged-particle multiplicity and transverse momentum densities at various hadron collision energies are fit simultaneously to determine the parameters of the tunes. Comparisons of the predictions of the new tunes are provided for observables sensitive to the event shapes at LEP, global underlying event, soft multiparton interactions, and double-parton scattering contributions. In addition, comparisons are made for observables measured in various specific processes, such as multijet, Drell-Yan, and top quark-antiquark pair production including jet substructure observables. The simulation of the underlying event provided by the new tunes is interfaced to a higher-order matrix-element calculation. For the first time, predictions from PYTHIA8 obtained with tunes based on NLO or NNLO PDFs are shown to reliably describe minimum-bias and underlying-event data with a similar level of agreement to predictions from tunes using LO PDF sets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Recognition Method of Vehicle Cluster Situation Based on Set Pair Logic considering Driver’s Cognition

The recognition of vehicle cluster situations is one of the critical technologies of advanced driving, such as intelligent driving and automated driving. The accurate recognition of vehicle cluster situations is helpful for behavior decision‐making safe and efficient. In order to accurately and objectively identify the vehicle cluster situation, a vehicle cluster situation model is proposed based on the interval number of set pair logic. The proposed model can express the traffic environment’s knowledge considering each vehicle’s characteristics, grouping relationships, and traffic flow characteristics in the target vehicle’s interest region. A recognition method of vehicle cluster situation is designed to infer the traffic environment and driving conditions based on the connection number of set pair logic. In the proposed model, the uncertainty of the driver’s cognition is fully considered. In the recognition method, the relative uncertainty and relative certainty of driver’s cognition, traffic information, and vehicle cluster situation are fully considered. The verification results show that the proposed recognition method of vehicle cluster situations can realize accurate and objective recognition. The proposed anthropomorphic recognition method could provide a basis for vehicle autonomous behavior decision‐making.

Liu, Shijie↗
DOE OSTI2020

Level set topology optimization in Firedrake

Lestofire is an academic software for the automated design of engineering components. It finds the optimal geometry of a system to minimize a given cost function while constrained by a given set of physics equations. Using a level set function to describe the geometry, lestofire uses shapes derivative to evolve the system until its optimal shape. It leverages the compilation of variational forms in Firedrake (https://www.firedrakeproject.org/) and the automated calculation of shape derivatives via pyadjoint (http://www.dolfin-adjoint.or/en/latest/) to allow fast prototyping of different physics, cost functions and design parametrizations.

Salazar De Troya, Miguel↗
DOE OSTI2023

NSO Processing Scripts (NSO wind loading data set processing scripts) [SWR-23-86]

NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One plant from October 2021 to June, 2023. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, NREL commissioned a lidar scanning the horizontal plane over the trough field. The high-resolution data set, characterizing the complex flow field and resulting structural loads, is available at https://data.openei.org/submissions/5938. The processing routines published here were used to create the data from the instruments' raw data.

Egerer, Ulrike↗
DOE OSTI2022

Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample

Accurate detection of somatic mutations is challenging but critical in understanding cancer formation, progression, and treatment. We recently proposed NeuSomatic, the first deep convolutional neural network-based somatic mutation detection approach, and demonstrated performance advantages on in silico data. In this study, we use the first comprehensive and well-characterized somatic reference data sets from the SEQC2 consortium to investigate best practices for using a deep learning framework in cancer mutation detection. Using the high-confidence somatic mutations established for a cancer cell line by the consortium, we identify the best strategy for building robust models on multiple data sets derived from samples representing real scenarios, for example, a model trained on a combination of real and spike-in mutations had the highest average performance. The strategy identified in our study achieved high robustness across multiple sequencing technologies for fresh and FFPE DNA input, varying tumor/normal purities, and different coverages, with significant superiority over conventional detection approaches in general, as well as in challenging situations such as low coverage, low variant allele frequency, DNA damage, and difficult genomic regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Uncertain of uncertainties? A comparison of uncertainty quantification metrics for chemical data sets

Abstract With the increasingly more important role of machine learning (ML) models in chemical research, the need for putting a level of confidence to the model predictions naturally arises. Several methods for obtaining uncertainty estimates have been proposed in recent years but consensus on the evaluation of these have yet to be established and different studies on uncertainties generally uses different metrics to evaluate them. We compare three of the most popular validation metrics (Spearman’s rank correlation coefficient, the negative log likelihood (NLL) and the miscalibration area) to the error-based calibration introduced by Levi et al. ( Sensors 2022 , 22 , 5540). Importantly, metrics such as the negative log likelihood (NLL) and Spearman’s rank correlation coefficient bear little information in themselves. We therefore introduce reference values obtained through errors simulated directly from the uncertainty distribution. The different metrics target different properties and we show how to interpret them, but we generally find the best overall validation to be done based on the error-based calibration plot introduced by Levi et al. Finally, we illustrate the sensitivity of ranking-based methods (e.g. Spearman’s rank correlation coefficient) towards test set design by using the same toy model ferent test sets and obtaining vastly different metrics (0.05 vs. 0.65).

Rasmussen, Maria H.↗
DOE OSTI2018

Quadri-joint inversion: Method and application to the Big Sky 9C 3D data set in northern Montana

The Kevin Dome [Formula: see text] storage project, located in northern Montana, attempted to characterize the Duperow Formation as a potential long-term storage zone for injected [Formula: see text]. A multicomponent (9C) seismic survey was acquired for the Big Sky Carbon Sequestration Partnership over a portion of the Kevin Dome using P- and S-wave sources. Prestack migrated PP, PS, SH, and SV data sets were generated. We then applied several stratigraphic inversion workflows using one or several kinds of seismic wavefield at the same time resulting in joint inversions of each data set. The aim of our study is to demonstrate the benefits of doing quadri-joint inversion of PP-, PS-, SH-, and SV-wavefields for the recovery of the elastic earth parameters, especially the S-wave impedance and density. These are crucial parameters because they can help determine lithology and porefill in the reservoir characterization workflow. Because the inversion workflow always uses the original seismic data recorded in its own time domain, it is necessary to compute registration laws between PP-PS-, PP-SH-, and PP-SV-wavefields using a time shift computation procedure (warping) based on inverted S-wave impedances from inversion of a single wavefield. This generated a significant improvement over methods that rely on attempting to match trace waveforms that may have a different phase, frequency content, and polarity. Finally, we wanted to investigate the reliability of the quadri-joint inversion results in the Bakken/Banff Formations, which have less lateral geologic variation than the underlying Duperow target. This interval shares many of the geophysical characterization challenges common to shale reservoirs in other North American basins. We computed geomechanical parameters, such as Poisson’s ratio and Young’s modulus, which are a proxy for brittleness. Comparison of these results with independent laboratory measurements in the Bakken interval demonstrates the superiority of the quadri-joint inversion method to the traditional inversion using P-wave data only.

Geochemistry & Geophysics↗
DOE OSTI2019

EGS Collab Testbed 1: Second Set Tracer Test Results

The EGS Collab project is developing ~10-20 m-scale field sites where fracture stimulation and flow models can be validated against controlled, small-scale, in-situ experiments. The first multi-well experimental site was established at the 4850 level in the Homestake Mine in Lead, South Dakota, where hydraulic fractures were created at an injection well drilled sub-horizontal from the drift. This file contains the second set of tracer data (also include the data uploaded previously, https://gdr.openei.org/submissions/1128) for the EGS Collab testbed. The tracer tests were conducted during October 2018 - November 2019. Injected tracers include DNA, C-dots (fluorescein nano particles), fluorescein, rhodamine-b, sodium chloride, lithium bromide and cesium iodine. The tracers have been detected in three flowing wells located about 7.5 to 9 meters away from the injection interval. The tracer breakthrough curves from these locations have been adjusted to account for the residence time in the injection and production tubing. The details about the tracer test can be found in Background and Methods of Tracer Tests (Mattson et al. (2019,a,b)) (also included in this package). References Mattson, E.D., Neupane, G., Plummer, M.A., Hawkins, A., Zhang, Y. and the EGS Collab Team 2019a. Preliminary Collab fracture characterization results from flow and tracer testing efforts. In Proceedings 44th Workshop on Geothermal Reservoir Engineering, edited, Stanford University, Stanford, California. Mattson, E.D., Neupane, G., Hawkins, A., Burghardt, J., Ingraham, M., Plummer, M., and the EGS Collab Team, 2019b. Fracture tracer injection response to pressure perturbations at an injection well. GRC Transactions, Vol. 43, 2019. Neupane, Ghanashyam, Earl Mattson, Adam Hawkins, Mitchell Plummer, and Yuran Zhang. EGS Collab Testbed 1: Tracer data sets. No. 1128. DOE Geothermal Data Repository; Idaho National Laboratory, 2019.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Enclosed Sydney Swirl Burner Experimental Data Set - Release 1.0

This submission includes a comprehensive data set for the NETL Enclosed Sydney Swirl Burner, generated between 2012 and 2014. The data set includes global parametric data and advanced diagnostic data for (3) flames of interest to CFD model validation. The submission includes a companion summary document describing the data and associated references.

Diagnostics↗
DOE OSTI2022

SPANet: Generalized permutationless set assignment for particle physics using symmetry preserving attention

The creation of unstable heavy particles at the Large Hadron Collider is the most direct way to address some of the deepest open questions in physics. Collisions typically produce variable-size sets of observed particles which have inherent ambiguities complicating the assignment of observed particles to the decay products of the heavy particles. Current strategies for tackling these challenges in the physics community ignore the physical symmetries of the decay products and consider all possible assignment permutations and do not scale to complex configurations. Attention based deep learning methods for sequence modelling have achieved state-of-the-art performance in natural language processing, but they lack built-in mechanisms to deal with the unique symmetries found in physical set-assignment problems. We introduce a novel method for constructing symmetry-preserving attention networks which reflect the problem's natural invariances to efficiently find assignments without evaluating all permutations. This general approach is applicable to arbitrarily complex configurations and significantly outperforms current methods, improving reconstruction efficiency between 19% - 35% on typical benchmark problems while decreasing inference time by two to five orders of magnitude on the most complex events, making many important and previously intractable cases tractable. A full code repository containing a general library, the specific configuration used, and a complete dataset release, are available at https://github.com/Alexanders101/SPANet

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

PMC$_\infty$: Infinite-Order Scale-Setting method using the Principle of Maximum Conformality and preserving the Intrinsic Conformality

We show results for Thrust and C-parameter in e^+ e^- e + e − annihilation to 3 jets obtained using the recently developed new method for eliminating the scale ambiguity and the scheme dependence in pQCD namely the Infinite-Order Scale-Setting method using the Principle of Maximum Conformality (PMC _\infty ∞ ). This method preserves an important underlying property of gauge theories: intrinsic Conformality (iCF). It leads to a remarkably efficient method to eliminate the conventional renormalization scale ambiguity at any order in pQCD. A comparison with Conventional Scale Setting method (CSS) is also shown.

Di Giustino, Leonardo↗
DOE OSTI2012

Radon in Soil Gas Above Bedrock Fracture Sets at the Shepley’s Hill Superfund Site

The Idaho National Laboratory (INL) recently provided technical support for ongoing environmental remediation activities at the Shepley’s Hill remediation site near Devens, MA (Figure 1). The technical support was requested as follow-on work to an initial screening level radiation survey conducted in 2008. The purpose of the original study was to assess the efficacy of the INL-developed Backpack Sodium Iodide System (BaSIS) for detecting elevated areas of natural radioactivity due to the decay of radon-222 gases emanating from the underlying fracture sets. Although the results from the initial study were mixed, the BaSIS radiation surveys did confirm that exposed bedrock outcrops have higher natural radioactivity than the surficial soils, thus a high potential for detecting elevated levels of radon and/or radon daughter products. (INL 2009) The short count times associated with the BaSIS measurements limited the ability of the system to respond to elevated levels of radioactivity from a subsurface source, in this instance radon gas emanating from fracture sets. Thus, it was postulated that a different methodology be employed to directly detect the radon in the soil gases. The CR-39 particle track detectors were investigated through an extensive literature and technology search. The relatively long deployment or “detection” time of several days, as well as the sensitivity of the measurement and robustness of the detectors made the CR-39 technology promising for deployment at the Shepley’s Hill site.

58 GEOSCIENCES↗