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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Postclosure assessment modelling of a deep geologic repository for low and intermediate level radioactive waste in Ontario, Canada - 15145

In 2011, Ontario Power Generation (OPG) submitted an Environmental Impact Statement and a Preliminary Safety Report (PSR) to the federal authorities in Canada to support an application for a site preparation and construction licence for a Deep Geologic Repository (DGR) for low and intermediate level radioactive waste (L and ILW). The DGR, which is proposed to be located close to the existing Western Waste Management Facility (WWMF) at the Bruce nuclear site, would receive L and ILW arising from the operation and refurbishment of OPG's nuclear reactors; the wastes are currently stored safely at the WWMF. The PSR is supported by postclosure safety assessment modelling, including a total-systems level model implemented in the AMBER compartment modelling software that draws directly on detailed groundwater and coupled groundwater and gas modelling using the FRA3DVS-OPG and TOUGH2 codes. A full suite of calculation cases is managed within a single AMBER model, which aided efficient management of the calculation files and quality assurance. Assessment of expected/normal evolution cases results in maximum calculated effective doses to humans that are more than five orders of magnitude below associated criteria. Assessment of conservative disruptive and 'what if' scenarios results in maximum calculated doses that are higher than those for the normal evolution cases, but which, when the low likelihood of occurrence is taken into account, remain significantly below the associated risk criterion. The assessment demonstrates that deep geologic repositories can provide a safe disposal option and provides an example of evaluating the safety of projects on long time scales. It shows how results from detailed groundwater and gas codes can be incorporated into assessment-level codes such as AMBER, thereby providing a single systems model that can be used to efficiently evaluate a wide range of scenarios and associated calculation cases. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

WE-G-9A-01: Radiation Oncology Outcomes Informatics

The construction of databases and support software to enable routine and systematic aggregation, analysis and reporting of patient outcomes data is emerging as an important area. “How have results for our patients been affected by the improvements we have made in our practice and in the technologies we use?” To answer this type of fundamental question about the overall pattern of efficacy observed, it is necessary to systematically gather and analyze data on all patients treated within a clinic. Clinical trials answer, in great depth and detail, questions about outcomes for the subsets of patients enrolled in a given trial. However, routine aggregation and analysis of key treatment parameter data and outcomes information for all patients is necessary to recognize emergent patterns that would be of interest from a public health or practice perspective and could better inform design of clinical trials or the evolution of best practice principals. To address these questions, Radiation Oncology outcomes databases need to be constructed to enable combination essential data from a broad group of data types including: diagnosis and staging, dose volume histogram metrics, patient reported outcomes, toxicity metrics, performance status, treatment plan parameters, demographics, DICOM data and demographics. Developing viable solutions to automate aggregation and analysis of this data requires multidisciplinary efforts to define nomenclatures, modify clinical processes and develop software and database tools requires detailed understanding of both clinical and technical issues. This session will cover the developing area of Radiation Oncology Outcomes Informatics. Learning Objectives: Audience will be able to speak to the technical requirements (software, database, web services) which must be considered in designing an outcomes database. Audience will be able to understand the content and the role of patient reported outcomes as compared to traditional toxicity measures. Audience will be understand approaches, clinical process changes, consensus building efforts and standardizations which must be addressed to succeed in a multi-disciplinary effort to aggregate data for all patients. Audience will be able to discuss technical and process issues related to pooling data among institutions in the context of collaborative studies among the presenting institutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

How open data and interdisciplinary collaboration improve our understanding of space weather: A risk and resiliency perspective

Space weather refers to conditions around a star, like our Sun, and its interplanetary space that may affect space- and ground-based assets as well as human life. Space weather can manifest as many different phenomena, often simultaneously, and can create complex and sometimes dangerous conditions. The study of space weather is inherently trans-disciplinary, including subfields of solar, magnetospheric, ionospheric, and atmospheric research communities, but benefiting from collaborations with policymakers, industry, astrophysics, software engineering, and many more. Effective communication is required between scientists, the end-user community, and government organizations to ensure that we are prepared for any adverse space weather effects. With the rapid growth of the field in recent years, the upcoming Solar Cycle 25 maximum, and the evolution of research-ready technologies, we believe that space weather deserves a reexamination in terms of a “risk and resiliency” framework. By utilizing open data science, cross-disciplinary collaborations, information systems, and citizen science, we can forge stronger partnerships between science and industry and improve our readiness as a society to mitigate space weather impacts. The objective of this manuscript is to raise awareness of these concepts as we approach a solar maximum that coincides with an increasingly technology-dependent society, and introduce a unique way of approaching space weather through the lens of a risk and resiliency framework that can be used to further assess areas of improvement in the field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Spectral proper orthogonal decomposition of active wake mixing dynamics in a stable atmospheric boundary layer

Recent advancements in the use of active wake mixing (AWM) to reduce wake effects on downstream turbines open new avenues for increasing power generation in wind farms. However, a better understanding of the fluid dynamics underlying AWM is still needed to make wake mixing a reliable strategy for wind farm flow control. In this work, a spectral proper orthogonal decomposition (SPOD) is used to analyze the dynamics of coherent flow structures that are induced in the wake through blade pitch actuation. The data are generated using the ExaWind software suite to perform large eddy simulations of an NREL 2.8 MW turbine operating in a stable atmospheric boundary layer. SPOD tracks the modal behavior of flow structures from their generation in the turbine induction field through their growth in the near-wake region and to their subsequent evolution and energy transfers in the far wake. SPOD is shown to be a useful tool in the context of AWM because it translates the wavenumber and frequency inputs to the turbine controller to structures in the wake. A decomposition of the radial shear stress flux in the wake is also developed using SPOD to measure the contribution of coherent flow structures to mean flow turbulent entrainment and wake recovery. The effectiveness of AWM is connected to its ability to excite inherent structures in the wake of the turbine that arise using baseline controls. The effects of AWM on blade loading are also analyzed by connecting the axial force along the blade to the SPOD analysis of the turbine induction field. Lastly, the performance of different AWM strategies is demonstrated in a two-turbine array.

17 WIND ENERGY↗
DOE OSTI2018

Phase-Field Modeling of Nugget Zone for a AZ31-Mg-Alloy Friction Stir Weld

This work presents simulation of microstructure evolution in the nugget zone (NZ) of a AZ31-Mg-alloy friction stir weld. The process parameters (tool geometrical characteristics, rotational speed, travel speed, applied load) have been correlated with the resulting microstructural features in the NZ of the weld (grain size and population) with the aid of the MICRESS software, which provides the ability to simulate both nucleation and grain growth during dynamic recrystallization phenomena evolving in the NZ during the weld thermal cycle. The input parameters of the developed model include the tool geometry, the welding conditions as well as the recrystallization energy, the grain boundary mobility and specific material properties. NZ microstructure obtained by simulation shows good agreement with experimental measurements for both grain population and size.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The CMS Data Acquisition - Architectures for the Phase-2 Upgrade

The upgraded High Luminosity LHC, after the third Long Shutdown (LS3), will provide an instantaneous luminosity of 7.5 × 10 34 cm -2 s -1 (levelled), at the price of extreme pileup of up to 200 interactions per crossing. In LS3, the CMS Detector will also undergo a major upgrade to prepare for the phase-2 of the LHC physics program, starting around 2025. The upgraded detector will be read out at an unprecedented data rate of up to 50 Tb/s and an event rate of 750 kHz. Complete events will be analysed by software algorithms running on standard processing nodes, and selected events will be stored permanently at a rate of up to 10 kHz for offline processing and analysis. Here in this paper we discuss the baseline design of the DAQ and HLT systems for the phase-2, taking into account the projected evolution of high speed network fabrics for event building and distribution, and the anticipated performance of general purpose CPU. Implications on hardware and infrastructure requirements for the DAQ “data center” are analysed. Emerging technologies for data reduction are considered. Novel possible approaches to event building and online processing, inspired by trending developments in other areas of computing dealing with large masses of data, are also examined. We conclude by discussing the opportunities offered by reading out and processing parts of the detector, wherever the front-end electronics allows, at the machine clock rate (40 MHz). This idea presents interesting challenges and its physics potential should be studied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

New compositional data on ancient mortars and plasters from Pompeii (Campania – Southern Italy): Archaeometric results and considerations about their time evolution

Highlights: • Mortar samples from Pompeii, with different constructive functions, were studied. • Characterization of the materials can be used for preparing compatible mortars. • Analogies and differences were highlighted to identify the constructive phases. • Preliminary statistic models were proposed to discriminate materials and constructive phases. Twenty-six samples of mortar used for various construction applications (joint mortars, floor mortars, filling mortars and plasters) were collected from different areas of the archaeological site of Pompeii (Campania - Sothern Italy). The mortar samples belong to various historical periods covering approximately 2000 years, from the 2nd century BC to the post excavation period (18–19th century). The samples were characterized employing Optical Microscopy (OM), X-ray Powder Diffraction (XRPD), X-ray Fluorescence (XRF), Electron Probe Micro Analysis (EPMA) and Raman Spectroscopy. Moreover, image analysis was carried out using JMicroVision software in order to determine the percentages of binder, macropores and aggregate, in terms of crushed ceramic fragments (cocciopesto), rock fragments and monocrystals. The application of these techniques allowed obtaining a complete chemical and minero-petrographic characterization of the samples, which may prove useful for preparing compatible repair mortars for future restoration works. The archaeometric study provided new data on the production technology of the mortars and the analogies and differences observed among the samples, enabled us to distinguish different constructive phases, thus confirming or rebutting the archaeological hypothesis on the dating of some samples. By combining compositional variables through the discriminant analysis, it was also possible to analyse the time evolution of the materials and to construct preliminary multivariate statistical models, helpful to identify the various typologies of mortars used in the different historical periods.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Requirements for a global data infrastructure in support of CMIP6

The World Climate Research Programme (WCRP)'s Working Group on Climate Modelling (WGCM) Infrastructure Panel (WIP) was formed in 2014 in response to the explosive growth in size and complexity of Coupled Model Intercomparison Projects (CMIPs) between CMIP3 (2005–2006) and CMIP5 (2011–2012). This article presents the WIP recommendations for the global data infrastructure needed to support CMIP design, future growth, and evolution. Developed in close coordination with those who build and run the existing infrastructure (the Earth System Grid Federation; ESGF), the recommendations are based on several principles beginning with the need to separate requirements, implementation, and operations. Other important principles include the consideration of the diversity of community needs around data – a data ecosystem – the importance of provenance, the need for automation, and the obligation to measure costs and benefits. This paper concentrates on requirements, recognizing the diversity of communities involved (modelers, analysts, software developers, and downstream users). Such requirements include the need for scientific reproducibility and accountability alongside the need to record and track data usage. One key element is to generate a dataset-centric rather than system-centric focus, with an aim to making the infrastructure less prone to systemic failure. With these overarching principles and requirements, the WIP has produced a set of position papers, which are summarized in the latter pages of this document. They provide specifications for managing and delivering model output, including strategies for replication and versioning, licensing, data quality assurance, citation, long-term archiving, and dataset tracking. They also describe a new and more formal approach for specifying what data, and associated metadata, should be saved, which enables future data volumes to be estimated, particularly for well-defined projects such as CMIP6. The paper concludes with a future facing consideration of the global data infrastructure evolution that follows from the blurring of boundaries between climate and weather, and the changing nature of published scientific results in the digital age.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Application of the SEGUE Stellar Parameter Pipeline to LAMOST Stellar Spectra

We describe an application of the SEGUE Stellar Parameter Pipeline (SSPP) to medium-resolution stellar spectra obtained by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), in order to determine estimates of the stellar atmospheric parameters (T{sub eff}, log g, and [Fe/H]) and the abundance ratios ([α/Fe] and [C/Fe]). By performing a coordinate match with the LAMOST stellar database, we selected stars with LAMOST spectra in common with stars having available spectroscopy from the Apache Point Observatory Galactic Evolution Experiment (APOGEE), the RAdial Velocity Experiment (RAVE), and the Sloan Extension for Galactic Understanding and Exploration (SEGUE). We ran the selected LAMOST stellar spectra from each survey through SSPP, and compared the stellar parameters down to signal-to-noise ratio (S/N) of 10 and chemical abundances down to S/N = 20 derived by SSPP with those determined by the APOGEE, RAVE, and SEGUE software pipelines. Our results show that the derived stellar parameters generally agree quite well, even though there exist some small systematic offsets with small scatter in T{sub eff}, log g, and [Fe/H], due to the use of different temperature scales, abundance scales, and calibrations adopted by each survey. Comparison of the [α/Fe] determinations for LAMOST spectra suggests no sign of significant systematic offsets (<–0.04 dex), with a small scatter (<0.08 dex) relative to stars in common with APOGEE and SEGUE. The [C/Fe] estimates determined for the LAMOST spectra also exhibit good agreement, with a very small offset (∼0.01 dex) and scatter (∼0.12 dex) relative to the SEGUE stars, while there exists about a –0.19 dex offset, with a small scatter of ∼0.13 dex, for the APOGEE sample. Due to the existence of small offsets in the stellar parameters and abundances among difference data sets, optimal results when combining the different data sets will be obtained by removing the offsets. Once accomplished, the stellar parameters and chemical abundances estimated by SSPP from the LAMOST stellar spectra should provide a reliable database for studies of the Galactic disk and halo systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Risk-based area of review estimation in overpressured reservoirs to support injection well storage facility permit requirements for CO 2 storage projects

This paper by the Energy & Environmental Research Center presents a workflow and modeling approach for delineating a risk-based area of review (AOR) to support a U.S. Environmental Protection Agency (EPA) Class VI permit for a carbon dioxide (CO 2 ) storage project. The approach combines semianalytical solutions for estimating formation fluid leakage through a hypothetical leaky wellbore with the results of numerical reservoir simulations to define the AOR. The modeling utilizes 1) semianalytical solutions from the peer-reviewed literature for formation fluid leakage through abandoned wellbores by Raven (1990) and Avci (1994), 2) a FORTRAN model compiled and described in Cihan et al. (2011, 2012) called ASLMA (Analytical Solution for Leakage in Multilayered Aquifers), and 3) a computational framework for estimating a risk-based AOR first proposed by Oldenburg et al. (2014, 2016). Therefore, the approach builds upon well-established research and underlying hydrogeological principles that have been upheld for nearly three decades. Moreover, the ASLMA model has been broadly applied to an array of storage projects. The work presented herein extends these earlier works using a custom wrapper written in the software environment, R (R Core Team, 2020), which was developed to perform multiple runs of the ASLMA model using given ranges for one or more input parameters. In addition, the current work simulates the pressure buildup within the storage reservoir in response to CO 2 injection using a compositional simulator to better accommodate the temporospatial evolution of pressure buildup within the storage reservoir that is more accurately modeled using a heterogeneous geologic model and a compositional simulator that accounts for the multiphase interactions. The workflow is demonstrated using a case study for a 180,000-metric-ton-per-year storage project located in the PCOR (Plains CO 2 Reduction) Partnership region. For the storage project evaluated here, under the scenario where the leaky wellbore is open to a saline aquifer (thief zone) between the overlying seal (cap rock) and the underground sources of drinking water (USDW), the risk-based AOR essentially collapses to the areal extent of the CO 2 plume in the storage reservoir because the pressure buildup in the storage reservoir beyond the CO 2 plume is insufficient to drive formation fluids up a hypothetical leaky wellbore into the USDW. However, even under the conservative assumption that the leaky wellbore is not open to a thief zone, beyond the areal extent of the CO 2 plume, the incremental leakage is less than 400 m 3 over 20 years, which represents ~0.0001% or less of the total volume of water contained within the USDW rock volume. As discussed in the text, the threshold criterion for defining the risk-based AOR is site-specific and should be informed by the results of the sensitivity analysis and available site characterization data. The approach outlined in this paper is designed to be protective of USDWs and, therefore, comply with the Safe Drinking Water Act requirements and provisions for the U.S. EPA Class VI Underground Injection Control (UIC) Program (Class VI Rule) and North Dakota Administrative Code Chapter 43-05-01.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

2019 Computing Sciences Strategic Plan

Computing has transformed nearly every aspect of scientific inquiry — across disciplines and across scales — from the behavior of subatomic particles to the formation of structures in the early universe, from the assembly of the human genome to the evolution of earth systems. Over the past two decades, computing has become an integral part of how Berkeley Lab is “Bringing Science Solutions to the World.” Advances in computing and mathematics have been key, with new mathematical models of complex physical phenomena, new methods for analyzing complex data, new algorithms for accuracy and scaling and sophisticated software systems that encapsulate these techniques into open, reusable tools. The performance of NERSC computers and the ESnet network have grown by several orders of magnitude, along with our understanding of how to map scientific computations and workflows onto these systems. From research to facility operations, the passion, talent and dedication of the Computing Sciences Area staff has been the cornerstone of our success. The plan outlined in this document describes the next step in a journey to expand the influence and impact of our efforts, building an increasingly connected global enterprise for science that places more powerful instruments in the hands of scientists, along with more powerful methods and tools for modeling, analysis and prediction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A Comprehensive Validation Approach Using The RAVEN Code

The RAVEN computer code , developed at the Idaho National Laboratory, is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is a multi-purpose probabilistic and uncertainty quantification platform, capable to communicate with any system code. A natural extension of the RAVEN capabilities is the imple- mentation of an integrated validation methodology, involving several different metrics, that represent an evolution of the methods currently used in the field. The state-of-art vali- dation approaches use neither exploration of the input space through sampling strategies, nor a comprehensive variety of metrics needed to interpret the code responses, with respect experimental data. The RAVEN code allows to address both these lacks. In the following sections, the employed methodology, and its application to the newer developed thermal-hydraulic code RELAP-7, is reported.The validation approach has been applied on an integral effect experiment, representing natu- ral circulation, based on the activities performed by EG&G Idaho. Four different experiment configurations have been considered and nodalized.

PRA↗
DOE OSTI2017

Variant profiling of evolving prokaryotic populations

Genomic heterogeneity of bacterial species is observed and studied in experimental evolution experiments and clinical diagnostics, and occurs as micro-diversity of natural habitats. The challenge for genome research is to accurately capture this heterogeneity with the currently used short sequencing reads. Recent advances in NGS technologies improved the speed and coverage and thus allowed for deep sequencing of bacterial populations. This facilitates the quantitative assessment of genomic heterogeneity, including low frequency alleles or haplotypes. However, false positive variant predictions due to sequencing errors and mapping artifacts of short reads need to be prevented. We therefore created VarCap, a workflow for the reliable prediction of different types of variants even at low frequencies. In order to predict SNPs, InDels and structural variations, we evaluated the sensitivity and accuracy of different software tools using synthetic read data. The results suggested that the best sensitivity could be reached by a union of different tools, however at the price of increased false positives. We identified possible reasons for false predictions and used this knowledge to improve the accuracy by post-filtering the predicted variants according to properties such as frequency, coverage, genomic environment/localization and co-localization with other variants. We observed that best precision was achieved by using an intersection of at least two tools per variant. This resulted in the reliable prediction of variants above a minimum relative abundance of 2%. VarCap is designed for being routinely used within experimental evolution experiments or for clinical diagnostics. The detected variants are reported as frequencies within a VCF file and as a graphical overview of the distribution of the different variant/allele/haplotype frequencies. The source code of VarCap is available at https://github.com/ma2o/VarCap . In order to provide this workflow to a broad community, we implemeted VarCap on a Galaxy webserver, which is accessible at http://galaxy.csb.univie.ac.at .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Improving DFIG performance under fault scenarios through evolutionary reinforcement learning based control

The double-fed induction generator (DFIG) usually experiences high rotor current and DC capacitor link voltage during system fault events. In this paper, a novel data-driven approach is proposed to enhance the DFIG performance under fault scenarios. An advanced reinforcement learning (RL) algorithm called guided surrogate-gradient-based evolution strategy (GSES) is used to control the DFIG power and capacitor DClink voltage by adjusting the optional reference signals. This controller is able to prevent the rotor of DFIG from overcurrent risk and maintain the grid-connected operation. The proposed GSES-based control algorithm was evaluated through simulations on a 3.6-MW DFIG in PSCAD/EMTDC software. Results have validated the effectiveness of the proposed GSESbased control algorithm in improving the DFIG performance under fault scenarios.

42 ENGINEERING↗
DOE OSTI2014

SU-E-T-407: Evaluation of Four Commercial Dosimetry Systems for Routine Patient-Specific Tomotherapy Delivery Quality Assurance

Purpose: The purpose of this project was to evaluate the performance of four commercially available dosimetry systems for Tomotherapy delivery quality assurance (DQA). Methods: Eight clinical patient plans were chosen to represent a range of treatment sites and typical clinical plans. Four DQA plans for each patient plan were created using the TomoTherapy DQA Station (Hi-Art version 4.2.1) on CT images of the ScandiDose Delta4, IBA MatriXX Evolution, PTW Octavius 4D and Sun Nuclear ArcCHECK phantoms. Each detector was calibrated following the manufacture-provided procedure. No angular response correction was applied. All DQA plans for each detector were delivered on the Tomotherapy Hi-Art unit in a single measurement session but on different days. The measured results were loaded into the vendor supplied software for each QA system for comparison with the TPS-calculated dose. The Gamma index was calculated using 3%/3mm, 2%/2mm with 10% dose threshold of maximum TPS calculated dose. Results: Four detector systems showed comparable gamma pass rates for 3%/3m, which is recommended by AAPM TG119 and commonly used within the radiotherapy community. The averaged pass rates ± standard deviation for all DQA plans were (98.35±1.97)% for ArcCHECK, (99.9%±0.87)% for Matrix, (98.5%±5.09)% for Octavius 4D, (98.7%±1.27)% for Delata4. The rank of the gamma pass rate for individual plans was consistent between detectors. Using 2%/2mm Gamma criteria for analysis, the Gamma pass rate decreased on average by 9%, 8%, 6.6% and 5% respectively. Profile and Gamma failure map analysis using the software tools from each dosimetry system indicated that decreased passing rate is mainly due to the threading effect of Tomo plan. Conclusion: Despite the variation in detector type and resolution, phantom geometry and software implementation, the four systems demonstrated similar dosimetric performance, with the rank of the gamma pass rate consistent for the plans considered.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Tempus v. 1.0

Tempus is a software framework for the time integration of ordinary differential equations (ODEs), partial differential equations (PDEs), and differential-algebraic equations (DAEs). Examples of time-integration methods available are Forward Euler, Backward Euler, Explicit Runge-Kutta and Implicit Runge-Kutta methods. Tempus can be used from small systems of equations (e.g., single ODEs for the time evolution of plasticity models) to large-scale transient simulations requiring exascale computing (e.g., flow fields around reentry vehicles and magneto-hydrodynamics). Tempus will be released as part of Trilinos under a BSD open source license.

Obert, CurtisC.↗
DOE OSTI2022

BLAST aka: BLAST-Py see also BLAST-Lite (Battery Lifetime Analysis and Simulation Tool Suite - Python) [SWR-22-69]

Battery Lifetime Analysis and Simulation Tool Suite (BLAST or BLAST-Py) developed in the Python programming language. BLAST-Py predicts the evolution of lithium-ion battery performance metrics over their lifetime, using models trained on lab-based accelerated aging data to predict battery performance in dynamic, real-world use. BLAST-Py contains existing models for a variety of lithium-ion battery chemistries (NMC/Gr and LFP/Gr). See also the open-source version of this software tool known as "BLAST-Lite" at: https://github.com/NREL/BLAST-Lite

Smith, Kandler↗