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At least 1,405 records · Page 78

SU-F-T-316: A Model to Deal with Dosimetric and Delivery Uncertainties in Radiotherapy Treatment Planning

Purpose The conventional way of dealing with uncertainties resulting from dose calculation or beam delivery in IMRT, is to do verification measurements for the plan in question. Here we present an alternative based on recommendations given in the AAPM 142 report and treatment specific parameters that model the uncertainties for the plan delivery. Methods Basis of the model is the assignment of uncertainty parameters to all segment fields or control point sequences of a plan. The given field shape is analyzed for complexity, dose rate, number of MU, field size related output as well as factors for in/out field position and penumbra regions. Together with depth related uncertainties, a 3D matrix is generated by a projection algorithm. Patient anatomy is included as uncertainty CT data set as well. Therefore, object density is classified in 4 categories close to water, lung, bone and gradient regions with additional uncertainties. The result is then exported as a DICOM dose file by the software tool (written in IDL, Exelis), having the given resolution and target point. Results Uncertainty matrixes for several patient cases have been calculated and compared side by side in the planning system. The result is not quite always intuitive but it clearly indicates high and low uncertainties related to OARs and target volumes as well as to measured gamma distributions.ConclusionThe imported uncertainty datasets may help the treatment planner to understand the complexity of the treatment plan. He then might decide to change the plan to produce a more suited uncertainty distribution, e.g. by changing the beam angles the high uncertainty spots can be influenced or try to use another treatment setup, resulting in a plan with lower uncertainties. A next step could be to include such a model into the optimization algorithm to add a new dose uncertainty constraint.

60 APPLIED LIFE SCIENCES↗

fp-tools

The output of a molecular dynamics simulation is a data file containing properties of the motion of the simulated particles as a function of time (e.g., positions, velocities). From this output, scientists can extract various properties which give insight into the physics of the system; for example, the radial distribution function can be computed from the particle positions, which gives insight into how close the system is to melting or freezing. Many publicly available codes to perform molecular dynamics simulations exist and have been well adopted by the scientific community (e.g., LAMMPS, VASP). However, it remains standard practice for scientists to write their own post-processing scripts to extract various properties of interest from the molecular dynamics simulation data. Since in many cases scientists are interested in the same set of “textbook” properties, there is a large duplication of effort in writing these post-processing scripts. Our proposed code, FP-Tools, is a C++ toolkit designed to help scientists extract and analyze quantities of interest from the output of a molecular dynamics simulation, eliminating the need for them to write these codes themselves and thus reducing this duplication of effort. The quantities which are computed by our code are well documented in the literature (either in publications or textbooks), and the algorithms we implement to compute these properties are also well known in the field. We are not introducing new science or methods here; rather, our primary goal is to provide a useful tool to the community in the form of a well-documented, easy to use package.

Hartman, Leah↗

Hydroshear Simulation Lab Test 2

This data file is for test 2. In this test a sample of granite with a pre-cut (man made fracture) is confined, heated and differential stress is applied. The max temperature in this this system development test is 95C. More test details can be found on the spreadsheets--note that there are 2 spreadsheets

15 GEOTHERMAL ENERGY↗

Offloading Calculations to Computational Storage Devices: Spark and HDFS [Slides]

The objective is to evaluate the capabilities of multiple CSDs (provided by NDG Systems) using Hadoop Filesystem and Apache Spark. The independent variables are: number of CSDs, 0, 1, 2, 4, or 6; size of dataset, 1 GB, 5 GB, 10 GB; type of dataset, one large file with all of the data, 10 files, 100 files. The dependent variables are: job time; execution time. the constants are operations on the dataset.

97 MATHEMATICS AND COMPUTING↗

Engineering Assessment And Certification of Integrity Of the DWTF Waste Treatment Tanks At Lawrence Livermore National Laboratory

This Engineering Assessment and Certification of Integrity of the Building 695 (B-695) Decontamination and Waste Treatment Facility (DWTF) Waste Treatment Tanks has been prepared using the guidelines of CCR §66270.16(a) “Specific Part B Information Requirements for Tank Systems”, and the CCR §66264.192(b) requirements for the written assessment of tank systems that store hazardous waste and have secondary containment. The regulations require that this assessment be completed and certified by an independent, qualified, California-registered Professional Engineer. This document will be kept on file by the Lawrence Livermore National Laboratory (LLNL) Environmental Functional Area and is applicable for a maximum of five (5) years from the date of issue.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Retracted: Eddy-Covariance and Auxiliary Measurements, NGEE-Barrow, 2012-2013

Redirect - This dataset has been superseded and is no longer available to download but is available by contacting the archive. Users are now directed to "Flux Tower Eddy Covariance and Meteorological Measurements for Barrow, Alaska: 2012-2016" https://doi.org/10.5440/1362279. This record does include the three original files, two .xlsx files and one .docx, as well as three versions created for interoperability in csv and pdf. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Thermo-Hydrological Modeling of Thermal Energy Storage in a Depleted Oil Reservoir

Thermal energy storage in oil and gas reservoirs leverages the existing surface and subsurface infrastructure, which can pave the way for economic production of geothermal energy. Existing studies on geothermal energy storage are focused mostly on the use of aquifers with more homogeneous rock and fluid properties. Coupling of heat and fluid flow in a multiphase-multicomponent system, such as an oil reservoir, is imperative especially if existing oil field assets need to be repurposed as required for a sustainable energy transition. The objective is to model the subsurface thermo-hydrological processes associated with reservoir performance and operational sustainability. The model evaluates formation pressure and temperature within the reservoir and at the injection/production wells during multiple charge and discharge cycles. Hot water (approximately 200 degrees C) heated by Concentrating Solar Power (CSP) at high pressure is injected into the existing oil reservoir for storage and produced as thermal energy for power generation, which will be accompanied by enhanced oil recovery. To demonstrate the coupled fluid and heat flow during the injection/production cycle in the subsurface reservoir, TOUGH3 (developed by Berkeley Lab) is used to simulate the thermo-hydrological (TH) processes in a multiphase, multicomponent system. Two well geometries are considered within the reservoir grid: 1) a single-well huff-n-puff system (same well is used for injection and production), and 2) an isolated injection-production well doublet. Seasonal charge and discharge cycling are implemented based on the scheduling specified in the model input file. The model reports pressure, temperature, enthalpy, liquid fluxes, heat fluxes, pore velocities, and changes in porosity & permeability due to temperature and pressure variations during the cyclic Reservoir Thermal Energy Storage (RTES) operations. The results from the simulations can be used to optimize the operational parameters (such as well spacing and injection/production rates) and round-trip efficiency for surface power-plants coupled with thermal energy storage over time. They can also serve as important inputs for levelized cost of storage estimations. The research will help to design and integrate surface renewable energy sources, such as concentrating solar power (CSP), with RTES to help balance out power supply and demand on the grid.

CSP↗

Determination of Solar System R-Process Abundances using ENDF/B-VIII.0 and TENDL-2015 libraries

Recent multi-messenger detection of the binary neutron star merger (GW170817) energized the astrophysical community and encouraged further research for determination of nuclear physics observables. Comprehensive studies of atomic nuclei in the cosmos provide an opportunity for investigating these astrophysical phenomena and acquiring complementary information on stellar nucleosynthesis processes that can be verified using the latest nuclear data. Evaluated Nuclear Data File (ENDF) libraries contain complete collections of reaction cross sections over the energy range relevant to astrophysics, fission yields and decay data. These data collections have been used worldwide in nuclear science, industry and national security applications. There is great interest in exploring the ENDF/B-VIII.0 and TALYS Evaluated Nuclear Data Library (TENDL-2015) for nuclear astrophysics purposes and comparing findings with the Karlsruhe Astrophysical Database of Nucleosynthesis in Stars (KADoNiS). The Maxwellian-averaged cross sections (MACS) and astrophysical reaction rates have been calculated using the ENDF/B-VIII.0 and TENDL-2015 evaluated data sets. The calculated cross sections were combined with the solar system abundances and fitted using the classical model of stellar nucleosynthesis. Astrophysical rapid- and slow-neutron capture, r- and s-process, respectively, abundances were obtained from present data and compared with available values. Further analysis of MACS reveals potential evaluated libraries data deficiencies and a strong need for new measurements. The current results demonstrate a large nuclear astrophysics potential of evaluated libraries and mutually beneficial relations between nuclear industry and research e orts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2018

Leaf gas exchange measurements on Arctagrostis latifolia (R. Br.) Griseb. following a single season warming treatment. Data were collected in 2018 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5–25 °C. The data package includes 4 data files in .csv format, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017–2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2019

Leaf gas exchange measurements on Eriophorum angustifolium Honck. following a single season warming treatment. Data were collected in 2019 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5–25 °C. The data package includes 4 data files in .csv format,, and include 4 data files, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017–2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Changuinola peat soil characteristics and gas emission raw data October 2019

This dataset comprises radiocarbon and geochemical measurements from peat and porewater samples collected across various depths at a site in Bocas del Toro, Panama. The study focuses on carbon cycling dynamics in tropical peatlands by examining carbon isotopic signatures (¹⁴C and ¹³C) and elemental compositions of bulk peat, dissolved organic carbon (DOC), carbon dioxide (CO₂), and methane (CH₄). Key parameters include radiocarbon ages and isotopic ratios (δ¹³C) of bulk peat, concentrations of carbon (%C) and nitrogen (%N), and radiocarbon content of porewater gases and dissolved organic carbon (DOC). The data provide insights into the vertical and spatial distribution of carbon sources and possible preservation and decomposition processes within tropical peat profiles, offering critical information for understanding carbon storage and greenhouse gas emissions in these ecosystems.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) carbon isotopic signatures (¹⁴C and ¹³C); (5) concentrations of carbon (%C) and nitrogen (%N); (6) radiocarbon content of porewater carbon dioxide (CO₂), and methane (CH₄) ; (7) porewater DOC; (8) bulk peat sampling protocol; (9) porewater sampling protocol; (10) porewater gas collection methods; and (11) gas extraction methods. All files are in .csv format and can be opened with any software that supports this file types.

54 ENVIRONMENTAL SCIENCES↗

EXFOR-NSR PDF database: a system for nuclear knowledge preservation and data curation

Current needs of nuclear science and technology include complete, well-documented, and easily verifiable nuclear data. The complete data records require supporting nuclear bibliography, presently stored in dedicated libraries, in addition, to actual data. Additionally, experimental nuclear reaction data (EXFOR) and Nuclear Science References (NSR) databases contain compilations based on primary (journals) and secondary (conference proceedings, theses, preprints, etc.) publications, and data received from authors via private communications. The secondary library materials and private communications often represent a bottleneck for nuclear data verification, compilation, evaluation, and dissemination activities. To address this issue, bibliographic materials were scanned into PDF (Portable Document Format) files and uploaded in a relational database. The traditional scope of nuclear databases that includes meta-data and numbers derived from data in specialized formats was broadened to accommodate the large volumes of original nuclear data publications. The complete PDF publication files were stored in a relational database as Binary Large OBjects (BLOB). This unique collection of nuclear data compilations and supporting publications generate many opportunities for machine learning applications. The Web interfaces for authorized and public access to the EXFOR-NSR nuclear publications database were implemented at the U.S. National Nuclear Data Center, https://www.nndc.bnl.gov/ and IAEA Nuclear Data Section, https://www-nds.iaea.org/ . The current system is complementary to major nuclear libraries and narrowly focused on nuclear data compilation and evaluation procedures. The contents of the PDF database, details of implementation, and Web interface are described. New capabilities for data curation, knowledge preservation, worldwide dissemination, and natural language processing (NLP) applications are given.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

MPLBM-UT: Multiphase LBM library for permeable media analysis

MPLBM-UT is a specialized lattice-Boltzmann library that makes running single- and two-phase flow simulations in porous media accessible to everyone. We provide a suite of tools to pre-process computational domains for simulation, to set up custom boundary conditions, to run simulations, to post-process simulation outputs, and to visualize simulation results and data. All of these tools are easily accessible to users through the mplbm_utils Python package included in and automatically installed with MPLBM-UT. The high-performance, highly parallel library Palabos is used as the solver backend. MPLBM-UT is easily deployed in a variety of systems, from laptops to supercomputer clusters. MPLBM-UT also features multiple examples and benchmark templates that allow for fast prototyping of different porous media problems. We also provide an interface for reading in different file types and downloading domains from the Digital Rocks Portal to perform simulations.

97 MATHEMATICS AND COMPUTING↗

Distributed data management on Belle II

The Belle II experiment started taking physics data in April 2018 with an estimated total volume of all files including raw events, Monte-Carlo and skim statistics of 340 petabytes expected by the end of operations in the late-2020s. Originally designed as a fully integrated component of the BelleDIRAC production system, the Belle II distributed data management (DDM) software needs to manage data across about 29 storage elements worldwide for a collaboration of nearly 1000 physicists. By late 2018, this software required significant performance improvements to meet the requirements of physics data taking and was seriously lacking in automation. Rucio, the DDM solution created by ATLAS, was an obvious alternative but required tight integration with BelleDIRAC and a seamless yet non-trivial migration. This contribution describes the work done on both DDM options, the current status of the software running successfully in production and the problems associated with trying to balance long-term operations cost against short term risk. .

97 MATHEMATICS AND COMPUTING↗

Preparation and characterization of electrodeposited cobalt nanowires

Electrochemical deposition technique has been used to deposit cobalt nanowires into the nano sized channels of Anodized Aluminium Oxide (AAO) templates. CoCl{sub 2}М‡6H2O salt solution was used, which was buffered with H{sub 3}BO{sub 3} and acidified by dilute H{sub 2}SO{sub 4} to increase the plating life and control pH of the solution. Thin film of copper around 150 nm thick on one side of AAO template coated by e-beam evaporation system served as cathode to create electrical contact. FESEM analysis shows that the as-deposited nanowires are highly aligned, parallel to one another and have high aspect ratio with a reasonably high pore-filing factor. The TEM results show that electrodeposited cobalt nanowires are crystalline in nature. The Hysteresis loop shows the magnetization properties for in and out of plane configuration. The in plane saturation magnetization (Ms) is lower than out of plane configuration because of the easy axis of magnetization is perpendicular to nanowire axis. These magnetic nanowires could be utilized for applications such as spintronic devices, high density magnetic storage, and magnetic sensor applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Molecular dynamics simulation of water in and around carbon nanotubes: A coarse-grained description

In the present study, we intend to investigate behaviour of water in and around hydrophobic open ended carbon nanotubes (CNTs) using a coarse-grained, core-softened model potential for water. The model potential considered here for water has recently been shown to successfully reproduce dynamic, thermodynamic and structural anomalies of water. The epitome of the study is to understand the incarceration of this coarse-grained water in a single-file carbon nanotube. In order to examine the effect of fluid-water van der Waals interaction on the structure of fluid in and around the nanotube, we have simulated three different CNT-water systems with varying degree of solute-water dispersion interaction. The analyses of the radial one-particle density profiles reveal varying degree of permeation and wetting of the CNT interior depending on the degree of fluid-solute attractive van der Waals interaction. A peak in the radial density profile slightly off the nanotube axis signifies a zigzag chain of water molecule around the CNT axis. The average numbers of water molecules inside the CNT have been shown to increase with the increase in fluid-water attractive dispersion interaction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

AXEAP : a software package for X-ray emission data analysis using unsupervised machine learning

The Argonne X-ray Emission Analysis Package ( AXEAP ) has been developed to calibrate and process X-ray emission spectroscopy (XES) data collected with a two-dimensional (2D) position-sensitive detector. AXEAP is designed to convert a 2D XES image into an XES spectrum in real time using both calculations and unsupervised machine learning. AXEAP is capable of making this transformation at a rate similar to data collection, allowing real-time comparisons during data collection, reducing the amount of data stored from gigabyte-sized image files to kilobyte-sized text files. With a user-friendly interface, AXEAP includes data processing for non-resonant and resonant XES images from multiple edges and elements. AXEAP is written in MATLAB and can run on common operating systems, including Linux, Windows, and MacOS.

97 MATHEMATICS AND COMPUTING↗

COMPASS-FME Synoptic Sites Level 1 Sensor Data v1-2

This is the version 1-2 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems.L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds and out-of-service flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project**This dataset includes:- An overall dataset README file that describes the current version, gives citation and contact information, etc.- Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year.- Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site.- Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v1-2 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning.

54 ENVIRONMENTAL SCIENCES↗