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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Statistical Interpolation Code for Ocean Analysis and Forecasting

Abstract We present a data assimilation package for use with ocean circulation models in analysis, forecasting, and system evaluation applications. The basic functionality of the package is centered on a multivariate linear statistical estimation for a given predicted/background ocean state, observations, and error statistics. Novel features of the package include support for multiple covariance models, and the solution of the least squares normal equations either using the covariance matrix or its inverse—the information matrix. The main focus of this paper, however, is on the solution of the analysis equations using the information matrix, which offers several advantages for solving large problems efficiently. Details of the parameterization of the inverse covariance using Markov random fields are provided and its relationship to finite-difference discretizations of diffusion equations are pointed out. The package can assimilate a variety of observation types from both remote sensing and in situ platforms. The performance of the data assimilation methodology implemented in the package is demonstrated with a yearlong global ocean hindcast with a 1/4° ocean model. The code is implemented in modern Fortran, supports distributed memory, shared memory, multicore architectures, and uses climate and forecasts compliant Network Common Data Form for input/output. The package is freely available with an open source license from www.tendral.com/tsis/ .

Srinivasan, Ashwanth↗
NASA NTRS1990

Force user's manual: A portable, parallel FORTRAN

The use of Force, a parallel, portable FORTRAN on shared memory parallel computers is described. Force simplifies writing code for parallel computers and, once the parallel code is written, it is easily ported to computers on which Force is installed. Although Force is nearly the same for all computers, specific details are included for the Cray-2, Cray-YMP, Convex 220, Flex/32, Encore, Sequent, Alliant computers on which it is installed.

Jordan, Harry F.↗
NASA NTRS1994

Flexible Method for Inter-object Communication in C++

A method has been developed for organizing and sharing large amounts of information between objects in C++ code. This method uses a set of object classes to define variables and group them into tables. The variable tables presented here provide a convenient way of defining and cataloging data, as well as a user-friendly input/output system, a standardized set of access functions, mechanisms for ensuring data integrity, methods for interprocessor data transfer, and an interpretive language for programming relationships between parameters. The object-oriented nature of these variable tables enables the use of multiple data types, each with unique attributes and behavior. Because each variable provides its own access methods, redundant table lookup functions can be bypassed, thus decreasing access times while maintaining data integrity. In addition, a method for automatic reference counting was developed to manage memory safely.

Curlett, Brian P.↗
NASA NTRS2012

Climate Models

Climate models is a very broad topic, so a single volume can only offer a small sampling of relevant research activities. This volume of 14 chapters includes descriptions of a variety of modeling studies for a variety of geographic regions by an international roster of authors. The climate research community generally uses the rubric climate models to refer to organized sets of computer instructions that produce simulations of climate evolution. The code is based on physical relationships that describe the shared variability of meteorological parameters such as temperature, humidity, precipitation rate, circulation, radiation fluxes, etc. Three-dimensional climate models are integrated over time in order to compute the temporal and spatial variations of these parameters. Model domains can be global or regional and the horizontal and vertical resolutions of the computational grid vary from model to model. Considering the entire climate system requires accounting for interactions between solar insolation, atmospheric, oceanic and continental processes, the latter including land hydrology and vegetation. Model simulations may concentrate on one or more of these components, but the most sophisticated models will estimate the mutual interactions of all of these environments. Advances in computer technology have prompted investments in more complex model configurations that consider more phenomena interactions than were possible with yesterday s computers. However, not every attempt to add to the computational layers is rewarded by better model performance. Extensive research is required to test and document any advantages gained by greater sophistication in model formulation. One purpose for publishing climate model research results is to present purported advances for evaluation by the scientific community.

Druyan, Leonard M.↗
DOE OSTI2015

Impact of correlated data in validation procedures - 14483

The increasing demand on accuracy of criticality calculations leads to the question, how to treat correlated data of benchmark experiments correctly. Correlations in the process of validation arise for example if a configuration in a series of experiments shares certain components, e.g. fuel rods. Traditional methods of code validation do not treat correlations explicitly, but give a more conservative estimation of the bias. Including correlations can lead to a more precise estimation. In the work at hand, a method is discussed based on Bayes theorem to include correlations in the experimental data when estimating an application case k{sub eff}. After a short introduction to the applied method and the demonstration of the general capability of it to predict the k{sub eff} correctly, it is shown how the calculated k{sub eff} of an application case depends on correlations in experimental data for a simple Toy Model. The impact of ignoring correlations and taking to account lower and higher correlations is shown and discussed. Further results are shown using a database of correlated experimental data from the International Handbook of Criticality Safety Experiments to estimate the bias of two application cases. The experiments were chosen following the suggestion of the OECD/NEA EGUACSA Benchmark phase IV and consists of 21 experiments from the LEU-COMP-THERM series 007 and 039. With the extracted data results the calculated k{sub eff} values of the application cases are shown and discussed for different examples of correlations. The calculations were done by applying Monte-Carlo sampling methods with the GRS tool SUnCISTT, using ORNL's SCALE 6.1.2. This work discusses a possible way of treating correlations in the recalculation of critical experiments to get a more precise bias estimation of the used code system. It will be shown, that the presented method is capable to treat similarities in experimental setups of data used to calculate the bias correctly, independent of the size of similarities. The presented method is in principle capable of assessing regimes with little experimental data to estimate a bias. (authors)

42 ENGINEERING↗
NASA NTRS1969

Pulse-code-modulation baseline correction for low signal-to-noise ratios

Time-shared integrate-hold-dump circuits separate the dc level due to the signal /bit information/ from the dc signal due to the baseline error. The system detects the baseline error, filters it, and then algebraically adds enough voltage to a servo loop to reduce the error to zero.

Stephens, T. J.↗
DOE OSTI2024

Dynamic and Responsive Distributed Energy Resource Education Solutions for Building, Fire, and Safety Department Officials (Final Technical Report)

From April 2021 through March 2024, the Interstate Renewable Energy Council (IREC) led a collaborative project to develop a free online clearinghouse of educational resources about solar photovoltaics (PV), energy storage systems (ESS), electric vehicle supply equipment (EVSE), and grid-interactive efficient building (GEB) technologies. Two websites—the Clean Energy Clearinghouse and CleanEnergyTraining.org—housed over 70 educational resources. Over the course of the three-year project, 154,272 unique visitors accessed the learning materials. Learner feedback was overwhelmingly positive. Even through the end of the project, there was sustained demand for education and communication. A primary innovation of the project was to drive multiple complementary audiences to the same place. Building owners, designers, installation contractors and developers, authorities having jurisdiction (AHJs), and fire service personnel all benefit from a shared understanding of clean energy technologies, including safety and code-related requirements. When considering the impact on the target audience, the project team worked with partners and advisors to inform resource creation and delivery in such a way as to address key motivational factors of the target audience and compel each user to seek additional information on the topic and return to the Clean Energy Clearinghouse website as their central location for more information. Resources were intentionally developed to be concise—five to 15 minutes—and accessible, meaning not overly technical. Providing basic information demystified the technologies and invited the professional to explore additional learning opportunities. Awardee and partner collaboration was key to project success. IREC facilitated collaboration among the other Topic 2 awardees, Southface and New Buildings Institute (NBI). The three awardees shared relevant information gained through discovery and validation questionnaires that informed product development and reduced duplication of effort by coordinating the development of complementary, and not competing, educational resources. Inspired by this collaboration, IREC brought on additional partners even in the final year of the project. Five regional energy efficiency organizations were part of the project, which expanded the connection between efficiency and distributed energy resources. We also included resources on the Clearinghouse that were developed through other federally funded projects, such as the Buildings Energy Efficiency Frontiers & Innovation Technologies (BENEFIT) program. The website was developed with the learner in mind, and not solely the funding source. Feedback from stakeholders throughout the project, and especially in its final year, indicated the need for continued education and facilitated communication among stakeholders to further the safe and widespread adoption of clean energy.

14 SOLAR ENERGY↗
NASA NTRS1976

Shared memory for a fault-tolerant computer

A system is described for sharing a memory in a fault-tolerant computer. The memory is under the direct control and monitoring of error detecting and error diagnostic units in the fault-tolerant computer. This computer verifies that data to and from the memory is legally encoded and verifies that words read from the memory at a desired address are, in fact, actually delivered from that desired address. The means are provided for a second processor, which is independent of the direct control and monitoring of the error checking and diagnostic units of the fault-tolerant computer, and to share the memory of the fault-tolerant computer. Circuitry is included to verify that: (1) the processor has properly accessed a desired memory location in the memory; (2) a data word read-out from the memory is properly coded; and (3) no inactive memory was erroneously outputting data onto the shared memory bus.

Gilley, G. C.↗
NASA NTRS1992

Address tracing of parallel systems via TRAPEDS

Trace-driven simulation is an important aid in performance analysis of computer systems. Capturing address traces to use in these simulations, however, is a difficult problem for parallel processor architectures. A technique termed TRAPEDS modifies executable code (at the assembly language level) to dynamically collect the address trace from executing code. TRAPEDS has recently been implemented on both a hypercube multicomputer and a shared-memory multiprocessor. Particular attention is focused on strategies for efficiently and accurately collecting traces from both classes of parallel machines. The iPSC/2 hypercube multicomputer implementation traces both user and system code, and performs simulation on-the-fly to avoid large storage costs. Strategies are detailed for mitigating address trace distortion when collecting operating system traces. The Encore Multimax multiprocessor implementation uses a timer-based approach to reflect the interleaving of the processor traces and stores the traces to disc. Time and space overhead results are presented for both TRAPEDS implementations. Experimental cache simulation results derived from iPSC/2 address traces are presented to illustrate the importance of tracing operating system references.

Stunkel, Craig B.↗
DOE OSTI2023

MOSCATO Development and Integration in Fiscal Year 2023

In FY23, significant developments were made to the MOSCATO code package, enhancing its capabilities in many aspects. The improvements and advancements can be summarized as follows: Code Restructuring: The MOSCATO code underwent a restructuring process, enabling both Nek5000 and NekRS to share the same interface when using MOSCATO. This integration facilitates smoother interactions between the different modules and streamlines the overall simulation process. Automatic Domain Extension: To allow simulations to propagate over longer time frames, an automatic domain extension capability was added to the metal diffusion module. This enhancement enables more accurate and reliable simulations of diffusion processes, especially in scenarios with extended time requirements. Expanded Corrosion Reactions: The updated MOSCATO package now includes additional reactions that contribute to corrosion. This addition enhances the code’s ability to model corrosion effects more comprehensively, providing a more realistic representation of the systems being studied. Example Case Setup: To assist users and showcase MOSCATO’s capabilities, we developed example cases for various applications. Notably, we created example cases for thermal cells and corrosion loops. These pre-configured cases allow users to get started quickly and effectively with their simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

CYRANO3 the EDF fuel code performance: Global overview and recent developments on MOX fuel

CYRANO3 is the thermal mechanical industrial code developed and used by EDF to simulate the nuclear fuel rod performance in pile, and during the disposal storage period as well. This code has already been used successfully for the last ten years by the EDF engineering teams in justifying the overall reloading options covering various fuels: UO{sub 2}, UO{sub 2} + gadolinium, MOX, UO{sub 2} plus additives, and various cladding as well proposed by the nuclear fuel suppliers. Its particularity is related to a construction around a standard one-dimensional thermal and mechanical finite elements kernel with an appropriate architecture to plug in any new functionalities or models. Since the beginning it is developed as a module able integrating within a core calculation chain. Other constrain is to always guaranty a running time consistent with the calculation of a core within a reasonable time. The objective is to provide the EDF designers with a convivial and qualified code, with robust algorithms and able to quickly evolve with computer performances. Algorithms are able to account for adiabatic transients and are robust enough to avoid any undesirable overflows. The permanent challenge is indeed to provide with the more descriptive simulations not degrading to much the running time. Developments are obviously performed within the strict Quality Insurance rules. The code is then associated to a large documentation base, including model specification, realization, validation and test procedures. Maintenance is managed through a system of anomaly and improvement forms. Computers are still evolving quickly. Therefore, after an architecture adaptation, the CYRANO3 code is now integrated in the PLEIADES platform as a PWR industrial application. The platform is an exchange space allowing sharing functionalities, models and properties. In this paper, we will give a global overview of the capabilities of CYRANO3 code to simulate the thermomechanical behavior of fuel rods, and we will focus on recent developments realized on MOX fuel. In CYRANO3 code, heterogeneous models (neutronic model, micromechanical behavior law and fission gas model) are developed for MOX fuels and integrated in order to account for differential evolutions between phases under irradiation. The methodology and these models are presented in this paper. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Thermochemical Nonequilibrium Modeling in a Continuous-Galerkin, Finite-Element Framework

The presented work discusses the implementation, verification, and validation of Park's two-temperature model in a scalable, computational fluid dynamics (CFD) code developed at the US Department of Energy's Oak Ridge National Laboratory (ORNL). The implementation of Park's two-temperature model was verified through 0D test cases involving an adiabatic reactor and a nitrogen thermal bath. The implementation was then validated through comparisons with other validated CFD codes and experimental data on a hypersonic cylinder and double cones. These are standard benchmark test cases for thermochemical non-equilibrium (TCNE) modeling, and all data are shared publicly. The verification and validation results showed that ORNL's in-house CFD code could model complex, high-speed flow problems with and without TCNE modeling. This work is essential for future research involving 3D shock wave/boundary layer interactions (SBLIs).

Nutter, Nicole↗
DOE OSTI2019

Using excitation-energy dependent fission yields to identify key fissioning nuclei in r -process nucleosynthesis

The possibility that nucleosynthesis in neutron star mergers may reach fissioning nuclei introduces significant uncertainties in predicting the relative abundances of $r$-process material from such events. We evaluate the impact of using sets of fission yields given by the 2016 GEF code for spontaneous (sf), neutron-induced $((n, f))$, and $β$-delayed (βdf) fission processes which take into account the approximate initial excitation energy of the fissioning compound nucleus. We further explore energy-dependent fission dynamics in the $r$ process by considering the sensitivity of our results to the treatment of the energy sharing and de-excitation of the fission fragments using the FREYA code. We show that the asymmetric-to-symmetric yield trends predicted by GEF 2016 can reproduce the high-mass edge of the second $r$-process peak seen in solar data and examine the sensitivity of this result to the mass model and astrophysical conditions applied. We consider the effect of fission yields and barrier heights on the nuclear heating rates used to predict kilonova light curves. We find that fission barriers influence the contribution of 254 Cf spontaneous fission to the heating at ~100 d, such that a light curve observation consistent with such late-time heating would both confirm that actinides were produced in the event and imply the fission barriers are relatively high along the 254 Cf β-feeding path. We lastly determine the key nuclei responsible for setting the r-process abundance pattern by averaging over thirty trajectories from a 1.2–1.4 M ⊙ neutron star merger simulation. Finally, we show it is largely the odd-N nuclei undergoing $(Z, N)(n, f)$ and $(Z, N)β$df that control the relative abundances near the second peak. We find the 'hot spots' for β-delayed and neutron-induced fission given all mass models considered and show most of these nuclei lie between the predicted $N$ = 184 shell closure and the location of currently available experimental decay data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

MEUMAPPS (C++ Version)

Many materials, metal alloys in particular, have features on the on micrometer or nanometer scale that have a large impact on the properties of the material. These features are known as the microstructure of the material. Understanding why and how the microstructure forms in a material is of fundamental scientific interest as well as of significant technological interest. The capability to predict microstructure evolution in a material allows the intentional design of microstructures and hence the intentional design of material properties. The phase-field method is one of the leading methods for predicting microstructure evolution. One of the most significant problems for phase-field models is their computational expense. Even limited phase-field simulations can easily require thousands of CPU core-hours to complete, which significantly limits their use. This code provides both a general framework for creating scalable, GPU-accelerated phase-field model applications as well as several applications themselves. The code is capable of using hundreds of GPUs efficiently, which greatly reduces the time required to perform simulations. The code is written with an emphasis on performance portability, that is the ability for the code to run efficiently on a number of different computing architectures without modification of the source code. The performance portability of this code is primarily enabled through the use of two libraries, Kokkos (performance portable data structures and execution patterns) and heFFTe (performance portable distributed 3D fast Fourier transforms). The code consists of a core library, applications, and tests. The core library includes shared functionality between applications. This includes interfaces with fast Fourier transform (FFT) libraries such as heFFTe, data structures based on Kokkos, file input and output capabilities, and a solver for infinitesimal strain mechanical equilibrium problems. Five applications are included in the code. The flagship application is the MEUMAPPS-SS application, which implements the Kim-Kim-Suzuki phase-field model for precipitation for an arbitrary number of phases and components in a metal alloy. Five simpler applications are also included that solve the Eshelby inclusion problem, Allen-Cahn equation, the coupled Allen-Cahn and diffusion equations, and the Cahn-Hilliard equation. The code includes two applications to solve the Cahn-Hilliard equation, one with constant-step-size first-order time integration and the second with adaptive high-order time integration.

DeWitt, Stephen [Oak Ridge National Lab. (ORNL), O↗
DOE OSTI2018

Genome-Scale 13 C Fluxomics Modeling for Metabolic Engineering of Saccharomyces cerevisiae .

Synthetic biology is a rapidly developing field that pursues the application of engineering principles and development approaches to biological engineering. Synthetic biology is poised to change the way biology is practiced, and has important practical applications: for example, building genetically engineered organisms to produce biofuels, medicines, and other chemicals. Traditionally, synthetic biology has focused on manipulating a few genes (e.g., in a single pathway or genetic circuit), but its combination with systems biology holds the promise of creating new cellular architectures and constructing complex biological systems from the ground up. Enabling this merge of synthetic and systems biology will require greater predictive capability for modeling the behavior of cellular systems, and more comprehensive data sets for building and calibrating these models. The so-called "-omics" data sets can now be generated via high throughput techniques in the form of genomic, proteomic, transcriptomic, and metabolomic information on the engineered biological system. Of particular interest with respect to the engineering of microbes capable of producing biofuels and other chemicals economically and at scale are metabolomic datasets, and their insights into intracellular metabolic fluxes. Metabolic fluxes provide a rapid and easy to understand picture of how carbon and energy flow throughout the cell. Furthermore, we present a detailed guide to performing metabolic flux analysis and modeling using the open source JBEI Quantitative Metabolic Modeling (jQMM) library. This library allows the user to transform metabolomics data in the form of isotope labeling data from a 13 C labeling experiment into a determination of cellular fluxes that can be used to develop genetic engineering strategies for metabolic engineering.The jQMM library presents a complete toolbox for performing a range of different tasks of interest in metabolic engineering. Various different types of flux analysis and modeling can be performed such as flux balance analysis, 13 C metabolic flux analysis, and two-scale 13 C metabolic flux analysis (2S- 13 C MFA). 2S- 13 C MFA is a novel method that determines genome-scale fluxes without the need of every single carbon transition in the metabolic network. In addition to several other capabilities, the jQMM library can make model based predictions for how various genetic engineering strategies can be incorporated toward bioengineering goals: it can predict the effects of reaction knockouts on metabolism using both the MoMA and ROOM methodologies. In this chapter, we will illustrate the use of the jQMM library through a step-by-step demonstration of flux determination and knockout prediction in a complex eukaryotic model organism: Saccharomyces cerevisiae ( S. cerevisiae ). Included with this chapter is a digital Jupyter Notebook file that provides a computable appendix showing a self-contained example of jQMM usage, which can be changed to fit the user's specific needs. As an open source software project, users can modify and extend the code base to make improvements at will, allowing them to share their development work and contribute back to the jQMM modeling community.

-Omics data↗
DOE OSTI2020

pySMARTS: SMARTS Python Wrapper (Simple Model of the Atmospheric Radiative Transfer of Sunshine)

The pySMARTS module contains functions for calling SMARTS: Simple Model of the Atmospheric Radiative Transfer of Sunshine, from NREL, developed by Dr. Christian Gueymard. SMARTS software can be obtained from: https://www.nrel.gov/grid/solar-resource/smarts.html Users will be responsible to obtain a copy of SMARTS from NREL, honor it's license, and download the SMART files into their PVLib folder. This wrapper is shared under a BSD-3-Clause License, and was originally coded in Matlab by Juan Russo (2001), updated and ported to python by Silvana Ayala (2019-2020).

Ayala Pelaez, Silvana↗
DOE OSTI2023

KinCat v.1.0

SAND2024-02099O The software is designed to allow researchers to perform kinetic Monte Carlo (KMC) simulations of catalytic reactions on a 2D lattice. The code is written efficiently to run on a variety of shared memory computing architectures (e.g. GPU, multi-core) and to natively express the full complexity of lateral interactions on reaction rates. The software allows researchers to perform KMC simulations of catalytic reactions on a 2D lattice. It uses parallel shared-memory computing architectures to reduce run-times and allows for simultaneous simulation of multiple independent runs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Najm, Habib↗
DOE OSTI2025

VA Determinants of Health Data Curation Documentation FY25-Q2

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Determinants of Health (EDH) project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

97 MATHEMATICS AND COMPUTING↗