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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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Neuroscience initiatives aim to develop new technologies and tools to measure and manipulate neuronal circuits. In this paper, to deal with the massive amounts of data generated by these tools, the authors envision the co-location of open data repositories in standardized formats together with high-performance computing hardware utilizing open source optimized analysis codes.
Purpose: Alanine dosimeters are often used for in-vivo dosimetry purposes in radiation therapy. In a Monte Carlo study the influence of 20 different surrounding/phantom materials for alanine dosimeters was investigated. The investigations were performed in high-energy photon beams, covering the whole range from {sup 60}Co up to 25 MV-X. The aim of the study is the introduction of a perturbation correction k{sub env} for alanine dosimeters accounting for the environmental material. Methods: The influence of different surrounding materials on the response of alanine dosimeters was investigated with Monte Carlo simulations using the EGSnrc code. The photon source was adapted with BEAMnrc to a {sup 60}Co unit and an Elekta (E{sub nom}=6, 10, 25 MV-X) linear accelerator. Different tissue-equivalent materials ranging from cortical bone to lung were investigated. In addition to available phantom materials, some material compositions were taken and scaled to different electron densities. The depth of the alanine detectors within the different phantom materials corresponds to 5 cm depth in water, i.e. the depth is scaled according to the electron density (n{sub e}/n{sub e,w}) of the corresponding phantom material. The dose was scored within the detector volume once for an alanine/paraffin mixture and once for a liquid water voxel. The relative response, the ratio of the absorbed dose to alanine to the absorbed dose to water, was calculated and compared to the corresponding ratio under reference conditions. Results: For each beam quality the relative response r and the correction factor for the environment kenv was calculated. k{sub env}=0.9991+0.0049 *((n{sub e}/n{sub e,w})−0.7659){sup 3} Conclusion: A perturbation correction factor k{sub env} accounting for the phantom environment has been introduced. The response of the alanine dosimeter can be considered independent of the surrounding material for relative electron densities (n{sub e}/n{sub e,w}) between 1 and 1.4. For denser materials such as bone or much less dense surroundings such as lung, a small correction would be appropriate.
Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and then optimizing the model parameters to deconvolute various resistance, capacitive, inductive, or diffusion responses. For small data sets, this procedure can be conducted manually; however, it is not feasible to manually define a proper ECM for extensive data sets with a wide range of EIS responses. Automatic identification of an ECM would substantially accelerate the analysis of large sets of EIS data. We showcase machine learning methods to classify the ECMs of 9,300 impedance spectra provided by QuantumScape for the BatteryDEV hackathon. The best-performing approach is a gradient-boosted tree model utilizing a library to automatically generate features, followed by a random forest model using the raw spectral data. A convolutional neural network using boolean images of Nyquist representations is presented as an alternative, although it achieves a lower accuracy. We publish the data and open source the associated code. The approaches described in this article can serve as benchmarks for further studies. A key remaining challenge is the identifiability of the labels, underlined by the model performances and the comparison of misclassified spectra.
GEOPHIRES v2.0 is a geothermal techno-economic simulation tool upgraded from GEOPHIRES v1.2. The name stands for "GEOthermal energy for Production of Heat and electricity (“IR”) Economically Simulated". GEOPHIRES combines reservoir, wellbore, and surface plant technical models with cost correlations and levelized cost models to estimate the capital and operation and maintenance costs, instantaneous and lifetime energy production, and overall levelized cost of energy of a geothermal plant. In addition to electricity generation, direct-use heat applications and combined heat and power or cogeneration can be modeled. Various upgrades have been implemented to develop GEOPHIRES v2.0, including: updating the built-in cost correlations, coupling to the external reservoir simulator TOUGH2, enhancing the built-in wellbore simulator, converting the programming language to Python, and making the code open-source. Users are encouraged to build upon the tool, e.g. by implementing their own correlations or coupling to other simulators.
The "Wrapper for the optimization of cross-section generation in OpenMC" is Python-based software that runs the open-source Monte Carlo code OpenMC (https://docs.openmc.org/en/stable/ ) to generate cross-sections for any reactor geometry. The wrapper then optimizes those cross sections. The optimization aims to choose an energy group structure and a scattering representation that maximize accuracy with respect to continuous-energy results while avoiding significant computational expense. It then outputs these cross-sections in an ISOXML format readable by the Idaho National Lab code suite MOOSE (Olin William Calvin, Mark D DeHart, “Architecture for the Performance of Nuclear Fuel Depletion Calculations”, Idaho National Laboratory report, November 2019). The expected use-cases of this software include: -finding the best group structure and scattering representation for a specific reactor -testing the appropriateness of energy group structures for different reactor types -comparing energy group structures and scattering representations to each other -generating cross sections for use in deterministic codes, including ones found in the MOOSE suite The example reactor geometry included in this release is a generic reactor design, not based on any reactor in existence or in development. It was fabricated for the sole purpose of being a “testbed-geometry” upon which to develop this tool. Since the tool is designed to be generic, the nature of the test geometry is not very important, however, it is valuable to include as an example for users who are unfamiliar with developing reactor geometries for OpenMC.
The MicroEleX code package contains a variety of models and algorithms for physical modeling of microelectronic circuitry, including electrostatics, electrodynamics, superconducting physics, micromagnetics, multi-ferroic systems, and quantum transport. MicroEleX leverages the AMReX software framework to provide scalability on GPU-based supercomputing architectures. The code is open source and designed to be algorithmically flexible so developers can incorporate enhanced or customized physics.
The compiled datasets include plot level observations of energy crops (miscanthus and switchgrass) from recent experimental field trials in the US including dry biomass yield, location, state, region, harvest year, growing season degree days (GDD), winter season heating degree days (HDD), growing season cumulative precipitation, annual nitrogen application rate, age of the pant when harvested, National Commodity Crop Productivity Index (NCCPI) values, and cultivar type (switchgrass) from various published and unpublished sources. The stata codes include estimation procedures for four different specifications, i.e., Model A includes deterministic effect without interaction terms; Model B includes deterministic effect with interaction terms (N2, age2, N × age, GDD2, precip2, N × NCCPI); Model C includes deterministic effect with interaction terms, study, and location random effect; Model D includes deterministic effect with interaction terms, harvest year augmented study, and location random effect.
Potential iodine gas release from failed fuel pins is a critical factor in the source term analysis of oxide fuel-loaded sodium fast reactors (SFRs). The accumulated iodine-containing gas mixtures inside pin plenums are expected to be ejected during pin failures and rise through sodium pool, with potential release of gaseous iodine to the cover gas region. Due to its potential radiological impacts, a proper assessment of iodine behavior is necessary for an accurate source term assessment. Throughout the bubble rise trajectory in the sodium pool, iodine gas is continuously removed or transformed at the bubble interface by diffusion, as the combining reaction between the iodine and sodium to form sodium iodide (NaI) is a chemically preferred process. As the final amount of iodine released from the facility is strongly influenced by the removal phenomenon inside the sodium pool, experiments were previously performed by PNC (Power Reactor and Nuclear Fuel Development Corporation) to provide insight into this phenomenon. To assess the accuracy of present methods for predicting iodine gas removal within sodium pools, several candidate approaches, available in source term analysis codes, have been summarized and evaluated in this study. Spherical cap bubbles and spherical bubbles are considered in accordance with the methods adopted in each approach, and different forms of correlations for major parameters have been implemented in accordance with the original adoptions. Based on the summarized results, important aspects to be considered have been derived.
The design of future aircraft must address the combined demands for fuel efficiency, reduced emissions and lower operating costs. One contribution to these goals is weight savings through the development of new alloys and design techniques for airframe structures. This research contributes to the light-weighting through fabrication of monolithic components from advanced aluminum alloys by making a link between alloy processing history and in-service performance. Specifically, this research demonstrates the link between growing cracks with features of the alloy microstructure that follow from thermo-mechanical processing. This is achieved through a computer model of crack deviation. The model is validated against experimental data from production scale aluminum alloy plate, and demonstration of the effect of changes in processing history on crack growth is made. The model is cast in the open-source finite element code WARP3D, which is freely downloadable and well documented. This project provides benefit along several avenues. First, the technical contribution of the computer model offers the materials engineer a critical means of providing guidance both upstream, to process tuning to achieve optimal properties, and downstream, to enhance fault tolerance. Beyond the fuel savings and emissions reduction inherent in the light-weighting of aircraft structures, improved fault tolerance addresses demands for longer inspection intervals over baseline, and a lower life cycle cost.
This project focused on developing high-performance software tools for First-Principles Molecular Dynamics (FPMD) simulations, and applying them in investigations of materials relevant to energy conversion processes. FPMD is an atomistic simulation method that combines a quantum-mechanical description of electronic structure with the statistical description provided by molecular dynamics (MD) simulations. This reliance on fundamental principles allows FPMD simulations to provide a consistent description of structural, dynamical and electronic properties of a material. This is particularly useful in systems for which reliable empirical models are lacking. FPMD simulations are increasingly used as a predictive tool for applications such as batteries, solar energy conversion, light-emitting devices, electro-chemical energy conversion devices and other materials. During the course of the project, several new features were developed and added to the open-source Qbox FPMD code. The code was further optimized for scalable operation of large-scale, Leadership-Class DOE computers. When combined with Many-Body Perturbation Theory (MBPT) calculations, this infrastructure was used to investigate structural and electronic properties of liquid water, ice, aqueous solutions, nanoparticles and solid-liquid interfaces. Computing both ionic trajectories and electronic structure in a consistent manner enabled the simulation of several spectroscopic properties, such as Raman spectra, infrared spectra, and sum-frequency generation spectra. The accuracy of the approximations used allowed for direct comparisons of results with experimental data such as optical spectra, X-ray and neutron diffraction spectra. The software infrastructure developed in this project, as applied to various investigations of solids, liquids and interfaces, demonstrates that FPMD simulations can provide a detailed, atomic-scale picture of structural, vibrational and electronic properties of complex systems relevant to energy conversion devices.
Computational modeling has become a very effective approach in predicting properties of materials, and in designing functional materials with targeted structural, thermal, or optical properties. Many electronic structure methods have been developed, including density functional theory. Among them, DFT has been widely used in physics and materials science because it is computationally cheaper than other methods but still gives desired accuracy. It also provides a good starting point for higher levels of theory, such as many-body perturbation theory and quantum Monte Carlo. In parallel to these electronic structure method developments, a dramatic increase in computing capabilities over the last decade has enabled large-scale electronic structure calculations to address leading-edge materials science problems. In particular, with Theta at the Argonne Leadership Computing Facility (ALCF), our early science project investigated large-scale nanostructured materials for energy conversion and storage using two open-source electronic structure codes Qbox (http://qboxcode.org) and WEST (http://west-code.org). Qbox is an ab-initio molecular dynamics code based on plane wave DFT, and WEST is a post-DFT code for excited state calculations within many-body perturbation theory.
We successfully verified in the following three aspects the feasibility of using a cryogenic scintillating crystal-based neutrino detector at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory, for the detection of low-mass dark matter particles and non-standard neutrino interactions (NSIs), as part of the detector R&D effort of the COHERENT experiment. First, we demonstrated the possibility of using silicon photomultipliers (SiPMs) at cryogenic temperatures to replace traditional photomultiplier tubes (PMTs) as light sensors. Second, we verified that the high light yield of undoped CsI crystals measured above 13 keVee at 77 K still holds down to 5.9 keVee. Third, we successfully measured nuclear quenching factor of undoped cryogenic CsI at the Triangle Universities Nuclear Laboratory with the help from our Duke collaborators. The first achievement resulted in a publication in European Physics Journal C. The second resulted in an arXiv pre-print, which is under journal review. The last one indicates that the performance of the proposed detector may be better than what was assumed in the literature. The analysis is in the final stage and will result in another journal publication. In addition, two graduate students involved in this project graduated with master’s degrees during the project period. Both decided to continue their research as PhD students. One open-source data analysis code package was created and is publicly available on GitHub. A set of tutorials about Monte Carlo simulation of radiation interacting with detectors were created on YouTube, receiving more than 100,000 views.
What is UME? UME extracts an important computational kernel from a large computational physics application, which is based on an unstructured mesh representation. The memory layout, indexing, data management, and communication patterns are as close to the original application as possible. The original application is a long-lived Fortran program, with ~750K source lines of code (sloc). UME is a C++17 implementation of a zone gradient operator, with about ~3K sloc.
Project summary, objectives, and outcomes for the Energy Resilience Performance tool are provided. The Energy Resilience Performance tool estimates the resilience benefits of solar energy when included in backup power systems. The code is open source and is integrated into NREL's existing REopt web tool.
Final report for the DOE Fusion Energy Sciences project titled "A Streamlined, Open Source Neutronics Toolkit for Fusion Reactor Design". This project developed unstructured mesh tracking capabilities in OpenMC as well as two shutdown dose rate methodologies, and performed extensive performance improvements and validation of the open source Monte Carlo code, OpenMC.
Tutorials for modeling of slot-die and slide-die coating flows with Goma 7, an open source finite element code, are presented. The tutorials cover the workflow to attaining steady state solutions for these flows, and continuation strategies for navigating the operating windows. Advanced topics of coating window prediction, automated multiparameter continuation, non-Newtonian rheology, dynamic contact line modeling, and some more solution strategies are also covered.
We explore a time-dependent energy dissipation of the energetic electrons in the inhomogeneous intergalactic medium (IGM) during the epoch of cosmic reionization. In addition to the atomic processes, we take into account the inverse Compton (IC) scattering of the electrons on the cosmic microwave background photons, which is the dominant channel of energy loss for electrons with energies above a few MeV. We show that: (1) the effect on the IGM has both local (atomic processes) and non-local (IC radiation) components; (2) the energy distribution between hydrogen and helium ionizations depends on the initial energy of an electron; (3) the local baryon overdensity significantly affects the fractions of energy distributed in each channel; and (4) the relativistic effect of the atomic cross-section becomes important during the epoch of cosmic reionization. We release our code as open source for further modification by the community.
Two digital video data compression systems directly applicable to the Space Shuttle TV Communication System were described: (1) For the uplink, a low rate monochrome data compressor is used. The compression is achieved by using a motion detection technique in the Hadamard domain. To transform the variable source rate into a fixed rate, an adaptive rate buffer is provided. (2) For the downlink, a color data compressor is considered. The compression is achieved first by intra-color transformation of the original signal vector, into a vector which has lower information entropy. Then two-dimensional data compression techniques are applied to the Hadamard transformed components of this last vector. Mathematical models and data reliability analyses were also provided for the above video data compression techniques transmitted over a channel encoded Gaussian channel. It was shown that substantial gains can be achieved by the combination of video source and channel coding.