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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Remotely sensed physical property estimation from powder contaminated surfaces

It is the intent of this paper to demonstrate the veracity of a method to estimate the total solid contaminant mass present on a sparsely coated surface encompassing a pixel from longwave infrared spectra. Sparsely coated surfaces create complex radiometry due to the interactions of electromagnetic energy between intimate materials. Current algorithms can be used on intimate mixtures to identify the abundances of materials in a pixel, but they cannot provide additional property information. Radiative transfer models can create mixture signatures, but only with a set of well-characterized physical parameters that are typically not known or are difficult to retrieve. Finally, the approach described here creates a parameter inversion model from a radiative transfer model and uses empirically measured mixture data to retrieve physical characteristics of the contaminated surface and derive a total contaminant mass present.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-D-213-05: Design, Evaluation and First Applications of a Off-Site State-Of-The-Art 3D Dosimetry System

Purpose: To design, construct and commission a prototype in-house three dimensional (3D) dose verification system for stereotatic body radiotherapy (SBRT) verification at an off-site partner institution. To investigate the potential of this system to achieve sufficient performance (1mm resolution, 3% noise, within 3% of true dose reading) for SBRT verification. Methods: The system was designed utilizing a parallel ray geometry instigated by precision telecentric lenses and an LED 630nm light source. Using a radiochromic dosimeter, a 3D dosimetric comparison with our gold-standard system and treatment planning software (Eclipse) was done for a four-field box treatment, under gamma passing criteria of 3%/3mm/10% dose threshold. Post off-site installation, deviations in the system’s dose readout performance was assessed by rescanning the four-field box irradiated dosimeter and using line-profiles to compare on-site and off-site mean and noise levels in four distinct dose regions. As a final step, an end-to-end test of the system was completed at the off-site location, including CT-simulation, irradiation of the dosimeter and a 3D dosimetric comparison of the planned (Pinnacle{sup 3}) to delivered dose for a spinal SBRT treatment(12 Gy per fraction). Results: The noise level in the high and medium dose regions of the four field box treatment was relatively 5% pre and post installation. This reflects the reduction in positional uncertainty through the new design. This At 1mm dose voxels, the gamma pass rates(3%,3mm) for our in-house gold standard system and the off-site system were comparable at 95.8% and 93.2% respectively. Conclusion: This work will describe the end-to-end process and results of designing, installing, and commissioning a state-of-the-art 3D dosimetry system created for verification of advanced radiation treatments including spinal radiosurgery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-A-304-02: Treatment Simulation, Planning and Delivery for SBRT

Increased use of SBRT and hypo fractionation in radiation oncology practice has posted a number of challenges to medical physicist, ranging from planning, image-guided patient setup and on-treatment monitoring, to quality assurance (QA) and dose delivery. This symposium is designed to provide updated knowledge necessary for the safe and efficient implementation of SBRT in various linac platforms, including the emerging digital linacs equipped with high dose rate FFF beams. Issues related to 4D CT, PET and MRI simulations, 3D/4D CBCT guided patient setup, real-time image guidance during SBRT dose delivery using gated/un-gated VMAT or IMRT, and technical advancements in QA of SBRT (in particular, strategies dealing with high dose rate FFF beams) will be addressed. The symposium will help the attendees to gain a comprehensive understanding of the SBRT workflow and facilitate their clinical implementation of the state-of-art imaging and planning techniques. Learning Objectives: Present background knowledge of SBRT, describe essential requirements for safe implementation of SBRT, and discuss issues specific to SBRT treatment planning and QA. Update on the use of multi-dimensional (3D and 4D) and multi-modality (CT, beam-level X-ray imaging, pre- and on-treatment 3D/4D MRI, PET, robotic ultrasound, etc.) for reliable guidance of SBRT. Provide a comprehensive overview of emerging digital linacs and summarize the key geometric and dosimetric features of the new generation of linacs for substantially improved SBRT. Discuss treatment planning and quality assurance issues specific to SBRT. Research grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-CD-304-11: Veritas 2.0: A Cloud-Based Tool to Facilitate Research and Innovation

Purpose: We introduce Veritas 2.0, a cloud-based, non-clinical research portal, to facilitate translation of radiotherapy research ideas to new delivery techniques. The ecosystem of research tools includes web apps for a research beam builder for TrueBeam Developer Mode, an image reader for compressed and uncompressed XIM files, and a trajectory log file based QA/beam delivery analyzer. Methods: The research beam builder can generate TrueBeam readable XML file either from scratch or from pre-existing DICOM-RT plans. DICOM-RT plan is first converted to XML format and then researcher can interactively modify or add control points to them. Delivered beam can be verified via reading generated images and analyzing trajectory log files. Image reader can read both uncompressed and HND-compressed XIM images. The trajectory log analyzer lets researchers plot expected vs. actual values and deviations among 30 mechanical axes. The analyzer gives an animated view of MLC patterns for the beam delivery. Veritas 2.0 is freely available and its advantages versus standalone software are i) No software installation or maintenance needed, ii) easy accessibility across all devices iii) seamless upgrades and iv) OS independence. Veritas is written using open-source tools like twitter bootstrap, jQuery, flask, and Python-based modules. Results: In the first experiment, an anonymized 7-beam DICOM-RT IMRT plan was converted to XML beam containing 1400 control points. kV and MV imaging points were inserted into this XML beam. In another experiment, a binary log file was analyzed to compare actual vs expected values and deviations among axes. Conclusions: Veritas 2.0 is a public cloud-based web app that hosts a pool of research tools for facilitating research from conceptualization to verification. It is aimed at providing a platform for facilitating research and collaboration. I am full time employee at Varian Medical systems, Palo Alto.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-D-204-06: An Open Source ImageJ CatPhan Analysis Tool

Purpose: The CatPhan is a popular QA device for assessing CT image quality. There are a number of software options which perform analysis of the CatPhan. However, there is often little ability for the user to adjust the analysis if it isn’t running properly, and these are all expensive options. An open source tool is an effective solution. Methods: To use the software, the user imports the CT as an image sequence in ImageJ. The user then scrolls to the slice with the lateral dots. The user then runs the plugin. If tolerance constraints are not already created, the user is prompted to enter them or to use generic tolerances. Upon completion of the analysis, the plugin calls pdfLaTex to compile the pdf report. There is a csv version of the report as well. A log of the results from all CatPhan scans is kept as a csv file. The user can use this to baseline the machine. Results: The tool is capable of detecting the orientation of the phantom. If the CatPhan was scanned backwards, one can simply flip the stack of images horizontally and proceed with the analysis. The analysis includes Sensitometry (estimating the effective beam energy), HU values and linearity, Low Contrast Visibility (using LDPE & Polystyrene), Contrast Scale, Geometric Accuracy, Slice Thickness Accuracy, Spatial resolution (giving the MTF using the line pairs as well as the point spread function), CNR, Low Contrast Detectability (including the raw data), Uniformity (including the Cupping Effect). Conclusion: This is a robust tool that analyzes more components of the CatPhan than other software options (with the exception of ImageOwl). It produces an elegant pdf and keeps a log of analyses for long-term tracking of the system. Because it is open source, users are able to customize any component of it.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-I-59: Quality Assurance Phantom for PET/CT Alignment and Attenuation Correction

Purpose: This study utilizes a commercial PET/CT phantom to investigate two specific properties of a PET/CT system: the alignment accuracy of PET images with those from CT used for attenuation correction and the accuracy of this correction in PET images. Methods: A commercial PET/CT phantom consisting of three aluminum rods, two long central cylinders containing uniform activity, and attenuating materials such as air, water, bone and iodine contrast was scanned using a standard PET/CT protocol. Images reconstructed with 2 mm slice thickness and a 512 by 512 matrix were obtained. The center of each aluminum rod in the PET and CT images was compared to evaluate alignment accuracy. ROIs were drawn on transaxial images of the central rods at each section of attenuating material to determine the corrected activity (in BQML). BQML values were graphed as a function of slice number to provide a visual representation of the attenuation-correction throughout the whole phantom. Results: Alignment accuracy is high between the PET and CT images. The maximum deviation between the two in the axial plane is less than 1.5 mm, which is less than the width of a single pixel. BQML values measured along different sections of the large central rods are similar among the different attenuating materials except iodine contrast. Deviation of BQML values in the air and bone sections from the water section is less than 1%. Conclusion: Accurate alignment of PET and CT images is critical to ensure proper calculation and application of CT-based attenuation correction. This study presents a simple and quick method to evaluate the two with a single acquisition. As the phantom also includes spheres of increasing diameter, this could serve as a straightforward means to annually evaluate the status of a modern PET/CT system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-258: Efficacy of Exit Fluence-Based Dose Calculation for Prostate Radiation Therapy

Purpose: To investigate the efficacy of exit-fluence-based dose computation for prostate radiotherapy by determining if it estimates true dose more accurately than the original planning dose. Methods: Virtual exit-fluencebased dose computation was performed for 19 patients, each with 9–12 repeat CT images. For each patient, a 78 Gy treatment plan was created utilizing 5 mm CTV-to-PTV and OAR-to-PRV margins. A Monte Carlo framework was used to compute dose and exit-fluence images for the planning image and for each repeat CT image based on boney-anatomyaligned and prostate-centroid-aligned CTs. Identical source particles were used for the MC dose-computations on the planning and repeat CTs to maximize correlation. The exit-fluence-based dose and image were computed by multiplying source particle weights by FC(x,y)=FP(x,y)/FT(x,y), where (x,y) are the source particle coordinates projected to the exit-fluence plane and we denote the dose/fluence from the plan by (DP,FP), from the repeat-CT as (DT,FT), and the exit-fluence computation by (DFC,FFC). DFC mimics exit-fluence backprojection through the planning image as FT=FFC. Dose estimates were intercompared to judge the efficacy of exit-fluence-based dose computation. Results: Boney- and prostate-centroid aligned results are combined as there is no statistical difference between them, yielding 420 dose comparisons per dose-volume metric. DFC is more accurate than DP for 46%, 33%, and 44% of cases in estimating CTV D98, D50, and D2 respectively. DFC improved rectum D50 and D2 estimates 54% and 49% respectively and bladder D50 and D2 47 and 49% respectively. While averaged over all patients and images DFC and DP were within 3.1% of DT, they differed from DT by as much as 22% for GTV D98, 71% for the Bladder D50, 17% for Bladder D2, 19% for Rectum D2. Conclusion: Exit-fluence based dose computations infrequently improve CTV or OAR dose estimates and should be used with caution. Research supported in part by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-D-BRB-02: SBRT Treatment Planning and Delivery

Increased use of SBRT and hypofractionation in radiation oncology practice has posted a number of challenges to medical physicist, ranging from planning, image-guided patient setup and on-treatment monitoring, to quality assurance (QA) and dose delivery. This symposium is designed to provide current knowledge necessary for the safe and efficient implementation of SBRT in various linac platforms, including the emerging digital linacs equipped with high dose rate FFF beams. Issues related to 4D CT, PET and MRI simulations, 3D/4D CBCT guided patient setup, real-time image guidance during SBRT dose delivery using gated/un-gated VMAT/IMRT, and technical advancements in QA of SBRT (in particular, strategies dealing with high dose rate FFF beams) will be addressed. The symposium will help the attendees to gain a comprehensive understanding of the SBRT workflow and facilitate their clinical implementation of the state-of-art imaging and planning techniques. Learning Objectives: Present background knowledge of SBRT, describe essential requirements for safe implementation of SBRT, and discuss issues specific to SBRT treatment planning and QA. Update on the use of multi-dimensional and multi-modality imaging for reliable guidance of SBRT. Discuss treatment planning and QA issues specific to SBRT. Provide a comprehensive overview of emerging digital linacs and summarize the key geometric and dosimetric features of the new generation of linacs for substantially improved SBRT. NIH/NCI; Varian Medical Systems; F. Yin, Duke University has a research agreement with Varian Medical Systems. In addition to research grant, I had a technology license agreement with Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

High Velocity AI Cache (HVAC)

HVAC is a high-performance caching system designed for large-scale AI training workloads.

Khan, Awais [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2025

olcf/hsi_xfer

A wrapper for the `hsi` tool that provides a simple user interface to allow the most efficient and least stressful (to the system) way to migrate data off of HPSS filesystems

Wynne, JamesRiley [Oak Ridge National Laboratory (↗
DOE OSTI2018

Accelerated Climate Modeling For Energy

This is the final report on the work of the New York University team to the DOE Accelerated Climate Modeling For Energy (ACME) project. NYU was one of the original developers of the UV-CDAT tool for climate data analysis, which is being used in ACME. NYU primarily focused on the analysis package graphical user interface, workflow and provenance functionality. The most significant activities in the last year of the grant were the development of the new plotting system in UVCMetrics package and the package EzLinePlot for 1D plots which are described in detail.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

ComPort: Rigorous Testing Methods to Safeguard Software Porting (Final UW Report)

This report summarizes the University of Washington’s contributions to the ComPort project, Rigorous Testing Methods to Safeguard Software Porting, funded under the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (ASCR), award number DE-SC0022081. UW’s work addressed numerics-driven correctness challenges arising in heterogeneous and rapidly evolving computing environments. Our efforts focused on developing interactive analysis tools, correctness-preserving rewriting systems, semantic-aware code-transformation infrastructure, and multi-language support for reproducible numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Digital Twin: Visualizing the Future of the Power Grid [Slides]

The energy systems are generating data at a scale and complexity that increasingly outpaces our ability to analyze it. This talk argues that rigorous, large-scale visualization is a critical tool for meeting that challenge. Drawing on recent work in the Computational Science Center at the National Laboratory of the Rockies, we trace a progression of visualization research culminating in an immersive digital twin of a real campus power grid. Along the way, we examine why visualization matters at all, where widely-used techniques quietly fail, and what becomes analytically possible when you match the display environment to the scale of the problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Managing autonomous materials labs with multi-agent AI and its implications for the science of science

Self-driving lab systems (aka, autonomous experimentation) accelerate research - letting scientists learn faster, spend less resources, and fail smarter in well defined, narrow studies. The next-generation materials lab combines self-driving systems to tackle broader challenges - orchestrating complex research campaigns while optimizing lab resources. We propose that agent-based and agentic artificial intelligence will be an integral part of next-generation lab management and discuss potential implementation scenarios. Additionally, digital and physical sandboxes will allow scientists to evaluate diverse and dynamic research and lab management strategies. Beyond the immediate benefit to lab optimization, such sandboxes will enable realistic computational studies of the philosophy of science (i.e., science of science) to achieve higher level scientific efficiencies.

Computer science↗
DOE OSTI2023

Predicting rare events using neural networks and short-trajectory data

Estimating the likelihood, timing, and nature of events is a major goal of modeling stochastic dynamical systems. When the event is rare in comparison with the timescales of simulation and/or measurement needed to resolve the elemental dynamics, accurate prediction from direct observations becomes challenging. In such cases a more effective approach is to cast statistics of interest as solutions to Feynman-Kac equations (partial differential equations). Here, we develop an approach to solve Feynman-Kac equations by training neural networks on short-trajectory data. Our approach is based on a Markov approximation but otherwise avoids assumptions about the underlying model and dynamics. This makes it applicable to treating complex computational models and observational data. Additionally, we illustrate the advantages of our method using a low-dimensional model that facilitates visualization, and this analysis motivates an adaptive sampling strategy that allows on-the-fly identification of and addition of data to regions important for predicting the statistics of interest. Finally, we demonstrate that we can compute accurate statistics for a 75-dimensional model of sudden stratospheric warming. This system provides a stringent test bed for our method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

ATDM LANL FleCSI: Topology and Execution Framework

FleCSI is a compile-time configurable C++ framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. This means that FleCSI is potentially useful to many different ECP projects. Current support includes multidimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures (to identify data dependencies between distributed-memory address spaces). FleCSI introduces a functional programming model with control, execution, and data abstractions that are consistent with state-of-the-art task-based runtimes such as Legion and Charm++. The model also provides support for fine-grained, data-parallel execution with backend support for runtimes such as OpenMP and C++17. The FleCSI abstraction layer provides the developer with insulation from the underlying runtimes, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. This project is essential to the ECP Ristra Next-Generation Code project, part of ASC ATDM, because it provides a hierarchically parallel programming model that is consistent with the design of modern system architectures, but which allows for the straightforward expression of algorithmic parallelism in a portably performant manner.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Generating HPC Job Profiles and Expectations with Time-Series Data - Showcase Presentation

Summary: Job Profiles and Expectations provide important insights into workloads (Job Profile: window into how a job is running; Job Expectation: Is that job behaving as expected; Provides us with actionable information). Machine learning can be used to group job runs into workload types (Identified groups can then be used for generate expectations); Profiles and Expectations also enable the study of: System-wide events, tracking system changes; System resource utilization and scheduling; Marking log data for further investigation or failures/anomalies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Performance Analysis, Modeling and Scaling of HPC Applications and Tools

E cient use of supercomputers at DOE centers is vital for maximizing system throughput, mini- mizing energy costs and enabling science breakthroughs faster. This requires complementary e orts along several directions to optimize the performance of scienti c simulation codes and the under- lying runtimes and software stacks. This in turn requires providing scalable performance analysis tools and modeling techniques that can provide feedback to physicists and computer scientists developing the simulation codes and runtimes respectively. The PAMS project is using time allocations on supercomputers at ALCF, NERSC and OLCF to further the goals described above by performing research along the following fronts: 1. Scaling Study of HPC applications; 2. Evaluation of Programming Models; 3. Hardening of Performance Tools; 4. Performance Modeling of Irregular Codes; and 5. Statistical Analysis of Historical Performance Data. We are a team of computer and computational scientists funded by both DOE/NNSA and DOE/ ASCR programs such as ECRP, XStack (Traleika Glacier, PIPER), ExaOSR (ARGO), SDMAV II (MONA) and PSAAP II (XPACC). This allocation will enable us to study big data issues when analyzing performance on leadership computing class systems and to assist the HPC community in making the most e ective use of these resources.

97 MATHEMATICS AND COMPUTING↗