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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

BASIN-3D: A brokering framework to integrate diverse environmental data

Diverse observational and simulation datasets are needed to understand and predict complex ecosystem behavior over seasonal to decadal and century time-scales. Integration of these datasets poses a major barrier towards advancing environmental science, particularly due to differences in the structure and formats of data provided by various sources. Here, we describe BASIN-3D (Broker for Assimilation, Synthesis and Integration of eNvironmental Diverse, Distributed Datasets), a data integration framework designed to dynamically retrieve and transform heterogeneous data from different sources into a common format to provide an integrated view. BASIN-3D enables users to adopt a standardized approach for data retrieval and avoid customizations for the data type or source. We demonstrate the value of BASIN-3D with two use cases that require integration of data from regional to watershed spatial scales. The first application uses the BASIN-3D Python library to integrate time-series hydrological and meteorological data to provide standardized inputs to analytical and machine learning codes in order to predict the impacts of hydrological disturbances on large river corridors of the United States. The second application uses the BASIN-3D Django framework to integrate diverse time-series data in a mountainous watershed in East River, Colorado, United States to enable scientific researchers to explore and download data through an interactive web portal. Thus, BASIN-3D can be used to support data integration for both web-based tools, as well as data analytics using Python scripting and extensions like Jupyter notebooks. The framework is expected to be transferable to and useful for many other field and modeling studies.

Varadharajan, C↗
DOE OSTI2017

A quantitative method for analyzing glycome profiles of plant cell walls

Glycome profiling allows for the characterization of plant cell wall ultrastructure via sequential extractions and subsequent detection of specific epitopes with a suite of glycan-specific monoclonal antibodies (mAbs). The data are often viewed as the amount of materials recovered and coinciding colored heatmaps of mAb binding are generated. Interpretation of these data can be considered qualitative in nature as it depends on detecting subtle visual differences in antibody binding strength. In this paper we report a mixed model-based quantitative approach for glycome profile analyses, which accounts for the amount of materials recovered and displays the normalized values in revised heatmaps and statistical heatmaps depicting significant differences. The utility of this methodology was demonstrated on a previously published dataset investigating the effects of moisture stress on the roots and needles of Pinus taeda. An annotated R script for the quantitative methodology is included to allow future studies to utilize the same approach.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗
DOE OSTI2015

FELIX-1.0: A finite element solver for the time dependent generator coordinate method with the Gaussian overlap approximation

In this study, we describe the software package FELIX that solves the equations of the time-dependent generator coordinate method (TDGCM) in NN-dimensions (N ≥ 1) under the Gaussian overlap approximation. The numerical resolution is based on the Galerkin finite element discretization of the collective space and the Crank–Nicolson scheme for time integration. The TDGCM solver is implemented entirely in C++. Several additional tools written in C++, Python or bash scripting language are also included for convenience. In this paper, the solver is tested with a series of benchmarks calculations. We also demonstrate the ability of our code to handle a realistic calculation of fission dynamics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

eqtools: Modular, extensible, open-source, cross-machine Python tools for working with magnetic equilibria

As plasma physics research for fusion energy transitions to an increasing emphasis on cross-machine collaboration and numerical simulation, it becomes increasingly important that portable tools be developed to enable data from diverse sources to be analyzed in a consistent manner. This paper presents eqtools, a modular, extensible, open-source toolkit implemented in the Python programming language for handling magnetic equilibria and associated data from tokamaks. eqtools provides a single interface for working with magnetic equilibrium data, both for handling derived quantities and mapping between coordinate systems, extensible to function with data from different experiments, data formats, and magnetic reconstruction codes, replacing the diverse, non-portable solutions currently in use. Moreover, while the open-source Python programming language offers a number of advantages as a scripting language for research purposes, the lack of basic tokamak-specific functionality has impeded the adoption of the language for regular use. Implementing equilibrium-mapping tools in Python removes a substantial barrier to new development in and porting legacy code into Python. In this paper, we introduce the design of the eqtools package and detail the workflow for usage and expansion to additional devices. Additionally, the implementation of a novel three-dimensional spline solution (in two spatial dimensions and in time) is also detailed. Finally, verification and benchmarking for accuracy and speed against existing tools are detailed. Wider deployment of these tools will enable efficient sharing of data and software between institutions and machines as well as self-consistent analysis of the shared data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

ESPResSo++ 2.0: Advanced methods for multiscale molecular simulation

We report that molecular simulation is a scientific tool used in many fields including material science and biology. This requires constant development and enhancement of algorithms within molecular simulation software packages. Here, we present computational tools for multiscale modeling developed and implemented within the ESPResSo++ package. These include the latest applications of the adaptive resolution scheme, the hydrodynamic interactions through a lattice Boltzmann solvent coupled to particle-based molecular dynamics, the implementation of the hierarchical strategy for equilibrating long-chained polymer melts and a heterogeneous spatial domain decomposition. The software design of ESPResSo++ has kept its highly modular C++ kernel with a Python user interface. Furthermore, it has been enhanced by automatic scripts that parse configurations from other established packages, providing scientists with the ability to rapidly set up their simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Python Multiscale Thermochemistry Toolbox (pMuTT) for thermochemical and kinetic parameter estimation

Estimating the thermochemical properties of systems is important in many fields such as material science and catalysis. The Python multiscale thermochemistry toolbox (pMuTT) is a Python software library developed to streamline the conversion of ab-initio data to thermochemical properties using statistical mechanics, to perform thermodynamic analysis, and to create input files for kinetic modeling software. Its open-source implementation in Python leverages existing scientific codes, encourages users to write scripts for their needs, and allows the code to be expanded easily. The core classes developed include a statistical mechanical model in which energy modes can be included or excluded to suit the application, empirical models for rapid thermodynamic property estimation, and a reaction model to calculate kinetic parameters or changes in thermodynamic properties. In addition, pMuTT supports other features, such as Brønsted–Evans–Polanyi (BEP) relationships, coverage effects, and ab-initio phase diagrams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

INGRID: An interactive grid generator for 2D edge plasma modeling

A fusion boundary-plasma domain is defined by axisymmetric magnetic surfaces where the geometry is often complicated by the presence of one or more X-points; and modeling boundary plasmas usually relies on computational grids that account for the magnetic field geometry. The new grid generator INGRID (Interactive Grid Generator) presented in this work is a Python-based code for calculating grids for fusion boundary plasma modeling, for a variety of configurations with one or two X-points in the domain. INGRID first performs partitioning over the domain consisting of a small number of patches conforming to the magnetic field and wall geometry; then it generates a subgrid on each of the patches and joins them into a global grid. This domain partitioning strategy makes possible a uniform treatment of various configurations with one or two X-points in the domain. This includes single-null, double-null, and other configurations with two X-points in the domain. The INGRID design allows generating grids either interactively, via a parameter-file driven GUI, or using a non-interactive script-controlled workflow. Results of testing demonstrate that INGRID is a flexible, robust, and user-friendly grid-generation tool for fusion boundary-plasma modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Dataset describing two reference models for full-spectral lighting and daylight simulations together with implementations for two software systems

A dataset of two spectral lighting simulation reference models - one office and one factory hall - is presented. It aims to demonstrate and support full-spectral daylight and electric lighting simulations and facilitate evaluation of non-visual effects of light. The dataset includes Rhino CAD geometry, comprehensive spectral material and light source data and window system BSDF data. Example implementations in the two software tools, Radiance and OWL, enable reproducible workflows and support adoption in other software. The dataset is openly available on Zenodo. The office model reproduces Room 518 at the University of Innsbruck, including a west-facing façade and interior furnishings. The factory hall model follows the proposed geometry in the European standard 15193 for building energy performance. Interior reflectances in the office were measured in-situ using a handheld spectrometer. Exterior spectra and factory hall materials matching specified reflectances were obtained from an online spectral materials database. Glazing transmittance was derived from IGDB data using LBNL Optics/WINDOW. BSDFs for venetian blinds at various tilt angles, and for a diffusing pane adapted from the Complex Glazing Database, were generated in WINDOW. Luminaires in both models are specified with photometric files (Eulumdat/IES) and lamp spectra (Fluorescent 840, 4000 K LED). The provided example implementations (Radiance, OWL) include prepared input data and scripts to run first spectral simulations; example results are also included. The dataset is prepared to support reuse by researchers, designers and software developers for method validation, software engineering and comparison, and development of spectral metrics and controls.

Geisler-Moroder, David↗
DOE OSTI2025

Determining the profitability of energy storage over its life cycle using levelized cost of storage

Levelized cost of storage (LCOS) can be a simple, intuitive, and useful metric for determining whether a new energy storage plant would be profitable over its life cycle and to compare the cost of different energy storage technologies. However, researchers and industry decision makers still use conflicting definitions of LCOS. For example, some include charging cost, while others only include round trip efficiency (RTE) losses. Additionally, inputs to the existing formulations are not specific enough to generate repeatable results across studies, which reduces trust in the metric. To push for standardization in economic assessment of batteries and other energy storage devices, the authors review existing definitions of LCOS and identify the desired characteristics for a standard. They then propose a new definition and demonstrate that it fits these characteristics very well relative to other prominent options. Unit analysis is applied to this proposed definition to provide a deeper understanding of the equations and to demonstrate its effectiveness. Finally, the sensitivity of LCOS to different input parameters is investigated to help users understand how to compare analyses from literature to their own. The authors also provide a spreadsheet and a Python script to streamline adoption of the proposed definition.

25 ENERGY STORAGE↗
DOE OSTI2025

A Comprehensive Chemistry Evaluation and Diagnostics Package for E3SM – ChemDyg Version 1.1.0

The Chemistry Evaluation and Diagnostics Package (ChemDyg) is an open-source tool designed for the Energy Exascale Earth System Model (E3SM) developed by the U.S. Department of Energy. ChemDyg facilitates routine evaluation, tailored development, and in-depth analysis of atmospheric chemistry through its modular architecture, allowing users to compare model outputs with observational data. Version 1.1.0 introduces a robust set of diagnostic capabilities, including climatology, time evolution of key tracers, diurnal and annual cycle analyses, and extensive budget diagnostics. These features help identify model discrepancies and enhance the representation of atmospheric chemistry in E3SM. Each self-contained diagnostic set includes dedicated scripts and documentation for ease of use. The interactive HTML output improves data accessibility, accelerating chemistry model development. Additionally, ChemDyg's flexible framework allows for customization, enabling users to create unique diagnostic sets for specific scientific contributions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Numerical analysis of modified Central Solenoid insert design

The United States ITER Project Office (USIPO) is responsible for fabrication of the Central Solenoid (CS) for ITER project. The ITER machine is currently under construction by seven parties in Cadarache, France. The CS Insert (CSI) project should provide a verification of the conductor performance in relevant conditions of temperature, field, currents and mechanical strain. The US IPO designed the CSI that will be tested at the Central Solenoid Model Coil (CSMC) Test Facility at JAEA, Naka. To validate the modified design we performed three-dimensional numerical simulations using coupled solver for simultaneous structural, thermal and electromagnetic analysis. Thermal and electromagnetic simulations supported structural calculations providing necessary loads and strains. According to current analysis design of the modified coil satisfies ITER magnet structural design criteria for the following conditions: (1) room temperature, no current, (2) temperature 4K, no current, (3) temperature 4K, current 60 kA direct charge, and (4) temperature 4K, current 60 kA reverse charge. Fatigue life assessment analysis is performed for the alternating conditions of: temperature 4K, no current, and temperature 4K, current 45 kA direct charge. Results of fatigue analysis show that parts of the coil assembly can be qualified for up to 1 million cycles. Distributions of the Current Sharing Temperature (TCS) in the superconductor were obtained from numerical results using parameterization of the critical surface in the form similar to that proposed for ITER. Lastly, special ADPL scripts were developed for ANSYS allowing one-dimensional representation of TCS along the cable, as well as three-dimensional fields of TCS in superconductor material. Published by Elsevier B.V.

42 ENGINEERING↗
DOE OSTI2016

MDSplus quality improvement project

MDSplus is a data acquisition and analysis system used worldwide predominantly in the fusion research community. Development began 29 years ago on the OpenVMS operating system. Since that time there have been many new features added and the code has been ported to many different operating systems. There have been contributions to the MDSplus development from the fusion community in the way of feature suggestions, feature implementations, documentation and porting to different operating systems. The bulk of the development and support of MDSplus, however, has been provided by a relatively small core developer group of three or four members. Given the size of the development team and the large number of users much more effort was focused on providing new features for the community than on keeping the underlying code and documentation up to date with the evolving software development standards. To ensure that MDSplus will continue to provide the needs of the community in the future, the MDSplus development team along with other members of the MDSplus user community has commenced on a major quality improvement project. The planned improvements include changes to software build scripts to better use GNU Autoconf and Automake tools, refactoring many of the source code modules using new language features available in modern compilers, using GNU MinGW-w64 to create MS Windows distributions, migrating to a more modern source code management system, improvement of source documentation as well as improvements to the www.mdsplus.org web site documentation and layout, and the addition of more comprehensive test suites to apply to MDSplus code builds prior to releasing installation kits to the community. This paper should lead to a much more robust product and establish a framework to maintain stability as more enhancements and features are added. Finally, this paper will describe these efforts that are either in progress or planned for the near future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Computing environments for reproducibility: Capturing the “Whole Tale”

The act of sharing scientific knowledge is rapidly evolving away from traditional articles and presentations to the delivery of executable objects that integrate the data and computational details (e.g., scripts and workflows) upon which the findings rely. This envisioned coupling of data and process is essential to advancing science but faces technical and institutional barriers. The Whole Tale project aims to address these barriers by connecting computational, data-intensive research efforts with the larger research process transforming the knowledge discovery and dissemination process into one where data products are united with research articles to create "living publications" or tales. The Whole Tale focuses on the full spectrum of science, empowering users in the long tail of science, and power users with demands for access to big data and compute resources. We report here on the design, architecture, and implementation of the Whole Tale environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Trajectory Modulated Arc Therapy: A Fully Dynamic Delivery With Synchronized Couch and Gantry Motion Significantly Improves Dosimetric Indices Correlated With Poor Cosmesis in Accelerated Partial Breast Irradiation

Purpose: To develop planning and delivery capabilities for linear accelerator–based nonisocentric trajectory modulated arc therapy (TMAT) and to evaluate the benefit of TMAT for accelerated partial breast irradiation (APBI) with the patient in prone position. Methods and Materials: An optimization algorithm for volumetrically modulated arc therapy (VMAT) was generalized to allow for user-defined nonisocentric TMAT trajectories combining couch rotations and translations. After optimization, XML scripts were automatically generated to program and subsequently deliver the TMAT plans. For 10 breast patients in the prone position, TMAT and 6-field noncoplanar intensity modulated radiation therapy (IMRT) plans were generated under equivalent objectives and constraints. These plans were compared with regard to whole breast tissue volume receiving more than 100%, 80%, 50%, and 20% of the prescription dose. Results: For TMAT APBI, nonisocentric collision-free horizontal arcs with large angular span (251.5 ± 7.9°) were optimized and delivered with delivery time of ∼4.5 minutes. Percentage changes of whole breast tissue volume receiving more than 100%, 80%, 50%, and 20% of the prescription dose for TMAT relative to IMRT were −10.81% ± 6.91%, −27.81% ± 7.39%, −14.82% ± 9.67%, and 39.40% ± 10.53% (P≤.01). Conclusions: This is a first demonstration of end-to-end planning and delivery implementation of a fully dynamic APBI TMAT. Compared with IMRT, TMAT resulted in marked reduction of the breast tissue volume irradiated at high doses.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Image Guided Radiation Therapy Using Synthetic Computed Tomography Images in Brain Cancer

Purpose: The development of synthetic computed tomography (CT) (synCT) derived from magnetic resonance (MR) images supports MR-only treatment planning. We evaluated the accuracy of synCT and synCT-generated digitally reconstructed radiographs (DRRs) relative to CT and determined their performance for image guided radiation therapy (IGRT). Methods and Materials: Magnetic resonance simulation (MR-SIM) and CT simulation (CT-SIM) images were acquired of an anthropomorphic skull phantom and 12 patient brain cancer cases. SynCTs were generated using fluid attenuation inversion recovery, ultrashort echo time, and Dixon data sets through a voxel-based weighted summation of 5 tissue classifications. The DRRs were generated from the phantom synCT, and geometric fidelity was assessed relative to CT-generated DRRs through bounding box and landmark analysis. An offline retrospective analysis was conducted to register cone beam CTs (n=34) to synCTs and CTs using automated rigid registration in the treatment planning system. Planar MV and KV images (n=37) were rigidly registered to synCT and CT DRRs using an in-house script. Planar and volumetric registration reproducibility was assessed and margin differences were characterized by the van Herk formalism. Results: Bounding box and landmark analysis of phantom synCT DRRs were within 1 mm of CT DRRs. Absolute planar registration shift differences ranged from 0.0 to 0.7 mm for phantom DRRs on all treatment platforms and from 0.0 to 0.4 mm for volumetric registrations. For patient planar registrations, the mean shift differences were 0.4 ± 0.5 mm (range, −0.6 to 1.6 mm), 0.0 ± 0.5 mm (range, −0.9 to 1.2 mm), and 0.1 ± 0.3 mm (range, −0.7 to 0.6 mm) for the superior-inferior (S-I), left-right (L-R), and anterior-posterior (A-P) axes, respectively. The mean shift differences in volumetric registrations were 0.6 ± 0.4 mm (range, −0.2 to 1.6 mm), 0.2 ± 0.4 mm (range, −0.3 to 1.2 mm), and 0.2 ± 0.3 mm (range, −0.2 to 1.2 mm) for the S-I, L-R, and A-P axes, respectively. The CT-SIM and synCT derived margins were <0.3 mm different. Conclusion: DRRs generated by synCT were in close agreement with CT-SIM. Planar and volumetric image registrations to synCT-derived targets were comparable with CT for phantom and patients. This validation is the next step toward MR-only planning for the brain.

62 RADIOLOGY AND NUCLEAR MEDICINE↗