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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Application of a Density Law via Python for Aqueous Plutonium Nitrate

A predictive density tool has been developed in Python to reduce bias and uncertainty in nuclear criticality safety calculations for plutonium nitrate systems. The Pitzer Method and an empirical method were implemented into the tool, allowing for plutonium nitrate density calculations. Additionally, the Python tool can generate atom densities for a MCNP6.2 material card using the density from the selected method and directly the densities into a prepared MCNP6 input text file. The material card and density are calculated based on customizable user inputs of plutonium content, nitric acid content, temperature, plutonium isotope weight percentages and impurity concentrations. The Python tool has been validated and verified against the International Handbook of Evaluated Criticality Safety Benchmark Experiments to predict densities within a root mean square error of 1.0% for the Pitzer method and 1.8% for the empirical method. These errors in density were shown to lead to a ±0.5% error in MCNP6.2 calculated k effective for the Pitzer method and a ±1.7% error for the Empirical method. Simultaneous work is also being done at the University of New Mexico and Los Alamos National Laboratory to create a similar tool for plutonium chloride solutions, which aims to provide the accreditation of the chlorine absorption. These capabilities will not only provide more accurate models but also lead the way towards a better understanding of solution systems and potential relaxation in the conservatism of the current aqueous plutonium processing limits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

IER 441: Experiments to Measure the Effect of Tantalum on Critical Systems (SNL/ORNL) [Slides]

This presentation provides information on the experiments to measure the effect of Tantalum (Ta) on critical systems. This talk presents details on the Sandia Critical Experiments Program with the Seven Percent Critical Experiment (7uPCX) and the Burnup Credit Critical Experiment (BUCCX). The presentation highlights motivations, experiment design, and evaluations and publications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project to develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the Comprehensive Test Ban Treaty of 1996 which banned surface testing of nuclear devices [1]. This had the effect that experimental work was reduced from large scale tests to multiscale experiments to provide material models with validation at different length scales. In the subsequent years industry realized that multi-scale modeling and simulation-based design were transferable to the design optimization of any structural system. Horstemeyer [1] lists a number of advantages of the use of multiscale modeling. Among these are: the reduction of product development time by alleviating costly trial-and-error iterations as well as the reduction of product costs through innovations in material, product and process designs. Multi-scale modeling can reduce the number of costly large scale experiments and can increase product quality by providing more accurate predictions. Research tends to be focussed on each particular length scale, which enhances accuracy in the long term. This paper serves as an introduction to the LS-OPT and LS-DYNA methodology for multi-scale modeling. It mainly focuses on an approach to integrate material identification using material models of different length scales. As an example, a multi-scale material identification strategy, consisting of a Crystal Plasticity (CP) material model and a homogenized State Variable (SV) model, is discussed and the parameter identification of the individual material models of different length scales is demonstrated. The paper concludes with thoughts on integrating the multi-scale methodology into the overall vehicle design.

Stander, Nielen↗
DOE OSTI2011

Streamline Integration Using MPI-Hybrid Parallelism on a Large Multicore Architecture

Streamline computation in a very large vector field data set represents a significant challenge due to the nonlocal and data-dependent nature of streamline integration. In this paper, we conduct a study of the performance characteristics of hybrid parallel programming and execution as applied to streamline integration on a large, multicore platform. With multicore processors now prevalent in clusters and supercomputers, there is a need to understand the impact of these hybrid systems in order to make the best implementation choice. We use two MPI-based distribution approaches based on established parallelization paradigms, parallelize over seeds and parallelize over blocks, and present a novel MPI-hybrid algorithm for each approach to compute streamlines. Our findings indicate that the work sharing between cores in the proposed MPI-hybrid parallel implementation results in much improved performance and consumes less communication and I/O bandwidth than a traditional, nonhybrid distributed implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Advanced Hydrogen Turbine Development

Under the sponsorship of the U.S. Department of Energy (DOE) National Energy Technology Laboratories, Siemens has completed the Advanced Hydrogen Turbine Development Program to develop an advanced gas turbine for incorporation into future coal-based Integrated Gasification Combined Cycle (IGCC) plants. All the scheduled DOE Milestones were completed and significant technical progress was made in the development of new technologies and concepts. Advanced computer simulations and modeling, as well as subscale, full scale laboratory, rig and engine testing were utilized to evaluate and select concepts for further development. Program Requirements of: A 3 to 5 percentage point improvement in overall plant combined cycle efficiency when compared to the reference baseline plant; 20 to 30 percent reduction in overall plant capital cost when compared to the reference baseline plant; and NOx emissions of 2 PPM out of the stack. were all met. The program was completed on schedule and within the allotted budget

42 ENGINEERING↗
DOE OSTI2024

teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Prediction of stability constants of metal–ligand complexes by machine learning for the design of ligands with optimal metal ion selectivity

The new LOGKPREDICT program integrates HostDesigner molecular design software with the machine learning (ML) program Chemprop. By supplying HostDesigner with predicted log K values, LOGKPREDICT enhances the computer-aided molecular design process by ranking ligands directly by metal–ligand binding strength. Harnessing reliable experimental data from a historic National Institute of Standards and Technology (NIST) database and data from the International Union of Pure and Applied Chemistry (IUPAC), we train message passing neural net algorithms. The multi-metal NIST-based ML model has a root mean square error (RMSE) of 0.629 ± 0.044 (R 2 of 0.960 ± 0.006), while two versions of lanthanide-only IUPAC-based ML models have, respectively, RMSE of 0.764 ± 0.073 (R 2 of 0.976 ± 0.005) and 0.757 ± 0.071 (R 2 of 0.959 ± 0.007). For relative log K predictions on an out-of-sample set of six ligands, demonstrating metal ion selectivity, the RMSE value reaches a commendably low 0.25. Here we showcase the use of LOGKPREDICT in identifying ligands with high selectivity for lanthanides in aqueous solutions, a finding supported by recent experimental evidence. We also predict new ligands yet to be verified experimentally. Therefore, our ML models implemented through LOGKPREDICT and interfaced with the ligand design software HostDesigner pave the way for designing new ligands with predetermined selectivity for competing metal ions in an aqueous solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

E3SMFC

SAND2025-01123O E3SMFC is a software tool that integrates a feedback controller algorithm into the E3SM climate model to regulate sulfur dioxide injection, aiming to achieve specific climate outcomes. The program uses proportional-integral-derivative feedback control to adjusts sulfur dioxide levels in both spatial and temporal dimensions. It will only operate on computers that can run the DOE climate model E3SM. 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.

Ojetola, Samuel↗
DOE OSTI2022

Estimating Energy Market Schedules using Historical Price Data

The global climate crisis is expected to reshape the energy generation landscape in the coming decades. Increasing integration of non-dispatchable renewable energy resources into energy infrastructures and markets creates uncertainty as well as new opportunities for flexible energy systems. To conduct proper economic evaluation of flexible energy systems, such as integrated energy systems (IES), advancements in modelling of market interactions, such as bidding, is crucial. This work presents a shortcut algorithm which uses two mixed integer linear programs to compute dispatch schedules (e.g., hourly power production targets) that are constrained by the resource's bid information and characteristics (e.g., minimum up and down times) based on historical locational marginal price (LMP) data. The proposed algorithm is approximately 100 times faster and uses orders of magnitude less data than a full production cost model (PCM). We find the shortcut simulator recapitulates generator dispatch signals for the Prescient PCM with approximately 4% error for the RTS-GMLC test system.

electricity generation↗
DOE OSTI2025

An Integral-based Technique to Accelerate the Monte Carlo Radiative Transfer Computation for Supernovae

We present an integral-based technique (IBT) algorithm to accelerate supernova (SN) radiative transfer calculations. The algorithm utilizes “integral packets,” which are calculated by the path integral of the Monte Carlo (MC) energy packets, to synthesize the observed spectropolarimetric signal at a given viewing direction in a 3D time-dependent radiative transfer program. Compared to the event-based technique (EBT) proposed by M. Bulla et al., our algorithm significantly reduces the computation time and increases the MC signal-to-noise ratio (S/N). Using a 1D spherical symmetric Type Ia SN ejecta model DDC10 and its derived 3D model, the IBT algorithm has successfully passed the verification of spherical symmetry and cross comparison on a 3D SN model with the direct-counting technique and EBT. Notably, with our algorithm implemented in the 3D MC radiative transfer code SEDONA, the computation time is faster than EBT by a factor of 10−30, and the S/N is better by a factor of 1.5−3, with the same number of MC quanta.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Creation of the VADER Code in SCALE [Slides]

This presentation details the creation of Validation Analysis Data Evaluation Resource (VADER) code in SCALE. This lecture highlights the USLSTATS program written in JAVA and its history. Additionally, it covers the integration of VADER with SCALE along with features and background information.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

IRIS-MASH: Efficient Multi-device Asynchronous Multi-Stream Heterogeneous Computing

In the rapidly evolving field of high-performance computing (HPC), effectively leveraging heterogeneous devices through asynchronous task programming is paramount. This paper presents a robust asynchronous task programming model tailored for a multi-device, multi-stream execution environment that incorporates a diverse array of heterogeneous computing units, including GPUs from various vendors and other accelerators. Current state-of-the-art task programming models provide methodologies to support asynchronous task executions, but they typically handle homogeneous devices using native programming languages, while support for heterogeneous devices is limited to frameworks like OpenCL. This gap presents significant challenges in abstracting heterogeneous devices to harness their true asynchronous capabilities effectively using their native programming languages. By implementing asynchronous task execution, our model significantly boosts the performance of tiled algorithm task graphs through overlapping data transfers with computation and enabling the simultaneous execution of multiple kernels. We integrate this approach into a heterogeneous Intelligent Runtime System (IRIS) and assess its performance using a suite of tiled algorithm benchmarks from the heterogeneous math kernels library (MatRIS) based on IRIS. Experimental results demonstrate a performance improvement ranging from 1.6 × to 2 × over IRIS without asynchronous support, and a notable 22% performance enhancement compared to established runtime systems such as StarPU and PaRSEC. This approach significantly improves computation efficiency of HPC workflows and provides a solid base for future exploration and development in the area of asynchronous task programming in heterogeneous systems.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗
DOE OSTI2022

Estimating Energy Market Schedules Using Historical Price Data: Preprint

The global climate crisis is expected to reshape the energy generation landscape in the coming decades. Increasing integration of non-dispatchable renewable energy resources into energy infrastructures and markets increases uncertainty and creates new opportunities for flexible energy systems. To conduct proper economic evaluation of flexible energy systems, such as integrated energy systems (IES), advancements in modelling of market interactions, such as bidding, is crucial. This work presents a shortcut algorithm which uses two mixed integer linear programs to compute dispatch schedules (e.g., hourly power production targets) that are constrained by the resource's bid information and characteristics (e.g., minimum up and down times) based on historical locational marginal price (LMP) data. This is orders of magnitude less data than required for a market clearing calculation with a full production cost model (PCM). We find the shortcut simulator recapitulates generator dispatch signals for the Prescient PCM with approximately 4% error for the RTS-GMLC test system.

electricity generation↗
DOE OSTI2013

Linear-scaling calculation of Hartree-Fock exchange energy with non-orthogonal generalised Wannier functions

We present a method for the calculation of four-centre two-electron repulsion integrals in terms of localised non-orthogonal generalised Wannier functions (NGWFs). Our method has been implemented in the ONETEP program and is used to compute the Hartree-Fock exchange energy component of Hartree-Fock and Density Functional Theory (DFT) calculations with hybrid exchange-correlation functionals. As the NGWFs are optimised in situ in terms of a systematically improvable basis set which is equivalent to plane waves, it is possible to achieve large basis set accuracy in routine calculations. The spatial localisation of the NGWFs allows us to exploit the exponential decay of the density matrix in systems with a band gap in order to compute the exchange energy with a computational effort that increases linearly with the number of atoms. We describe the implementation of this approach in the ONETEP program for linear-scaling first principles quantum mechanical calculations. We present extensive numerical validation of all the steps in our method. Furthermore, we find excellent agreement in energies and structures for a wide variety of molecules when comparing with other codes. We use our method to perform calculations with the B3LYP exchange-correlation functional for models of myoglobin systems bound with O{sub 2} and CO ligands and confirm that the same qualitative behaviour is obtained as when the same myoglobin models are studied with the DFT+U approach which is also available in ONETEP. Finally, we confirm the linear-scaling capability of our method by performing calculations on polyethylene and polyacetylene chains of increasing length.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Solar Living House Final Technical Report

The Solar Living House is a high-performance solar-powered dwelling designed by a team of faculty and students from the University of Florida, in collaboration with Santa Fe College, the National University of Singapore, and Alachua Habitat for Humanity. The project was designed in accordance with the Solar Decathlon 2015, a research, design, education, and outreach program developed by the U.S. Department of Energy (DOE). The Solar Living House is fundamentally a house for living, centered on people and the activities of daily life while quietly introducing advanced design, construction, and engineering technologies. The 993 square-foot two-bedroom one-bath home was designed to embrace and frame an exterior courtyard space. This courtyard acts as an extension of the interior living spaces, maximizing the spatial potentials of a modest building footprint and introducing natural light into the primary living spaces of the house. Research Outcomes: The Solar Living House advances work on high-performance buildings through three principal technological innovations: wet/dry modular construction, a building automation system, and solar dehumidification systems. Wet / Dry Modular Construction: The house is designed as a series of five modules, including one that is designated as the “wet core.” The wet core consolidates the mechanical systems and bathroom into a single module to reduce plumbing runs, efficiency losses, and on-site construction time. The other four modules are designed to eliminate interior load bearing walls to allow for maximum flexibility in the reconfiguring of the space over time. The modules are designed to meet the structural challenges of both Florida’s hurricanes and California’s earthquakes. Building Automation System: The house is equipped with an integrated building automation system, allowing the houses environmental systems, lights, security systems, and smoke detectors to be programmed, monitored, and controlled through any mobile or computing device. These systems allow for more precise calibrations of temperature/humidity/lighting to correspond with user needs and preferences, minimizing energy losses with economical night- or day-time setbacks. Solar Dehumidification System: The most significant technological innovation in the Solar Living House is the solar thermal dehumidification system. This system generates hot water through two rooftop-mounted evacuated tube solar thermal collectors. The hot water is used to continually dry a regenerative solid desiccant material, typically white silica gel. The solid desiccant is used to adsorb moisture and humidity from the air without additional mechanical cooling. This strategy allows humidity to be modulated independently of air temperature, providing greater thermal comfort and reducing the opportunity for the growth of mold spores within the house while also reducing the overall energy consumption of the HVAC system. Economic Feasibility: The team set aggressive goals for affordability, targeting a construction cost of $138,710. An independent professional cost estimator determined the overall project costs, as designed, would be $333,799, or $336.15 per square foot of finished floor area. This is more than 2.4 times the target construction cost. By comparison, the average construction cost for a home in the United States in 2015 was $289,415, or $103.29 per square foot of finished floor area. Following work on the Solar Living House, team leaders incorporated many of its objectives into a net-zero energy home on a site in Gainesville, Florida. This site-built home avoided many of the constraints and complications of modular construction necessitated by the Solar Decathlon, allowing it to be built for a much more modest budget. This two-bedroom two bath 1,800 square foot home was constructed for $135.39 per square foot, including active photovoltaic solar systems, careful attention to continuous air barriers, increased insulation levels, and permanent site constructions. This project suggest that high-performance buildings can be realized for more modest budgets. Public Benefits: Work on the Solar Living House and Solar Decathlon 2015 offered our student team unparalleled learning opportunities. Because of the duration of the project, a number of students participated at different points in their education, from first year undergraduates all the way through to advanced graduate students. The opportunity for collaboration with students and faculty from the National University of Singapore was also extraordinary, allowing for a sharing of technical knowledge and cultural exchange. The wider public has benefited from this work as its findings have been shared through public presentations and publications. It serves as a useful stepping stone along the path towards affordable, high-performance buildings.

14 SOLAR ENERGY↗
DOE OSTI2019

l3d2vtk: An MCNPTools Utility to Enable LNK3DNT File Visualization & Post-processing [Slides]

This presentation discusses the objective of the project which is to provide a utility (among other utilities) that improves MCNP analysis post-processing and visualization capabilities. Much recent work has been done to improve MCNP post-processing and visualization. It also discusses the goals of the project, which are to create a product that is portable, open, easily interrogated by a user, no dependencies, including a mesh tally-to-VTK conversion, an EEOUT-to-VTK conversion, and an interactive, 3-D, visualization environments (e.g., ParaView). The presentation also discusses the reasons regarding why this is being done, which are to provide physical insight into behaviors and trends, to facilitate error mitigation (easier to “see” errors than “read” them), and to improve communication with collaborators. It also discusses why this is being done now as analyses are getting ever-more complicated and are more flexible in terms of build, test, and deployment capabilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Data Assimilation using Non-invasive Monte Carlo Sensitivity Analysis of Reactor Kinetics Parameters [Slides]

Sensitivity coefficients of prompt neutron decay constant (α) and effective delayed neutron fraction (β eff ) to Pu-239 nuclear data were calculated using a newly available tool (ACEtk). Uncertainty calculations showed the following trends: (1) The prompt neutron decay constant can be used to reduce nuclear data-induced uncertainty in Pu-239(n,f) and (2) the effective delayed neutron fraction can be used to effectively reduce nuclear data-induced uncertainty in Pu-239 total fission $\tilde{v}$. Sensitivity/uncertainty analysis can be used to determine optimal experiment/detector setup to identify compensating errors in nuclear data. Upcoming work includes investigating other nuclide-reaction pairs and response sensitivities, such as Δ$\rho$, neutron leakage spectra, and reaction rate measurements to constrain nuclear data of interest.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗