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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PyMTensor 1.0.0

SAND2021-1654 O The Python Material Tensor code (PyMTensor) applies crystal symmetries to arbitrary material tensors. It uses symbolic algebra to exactly determine the zero tensor components and the relationships between the nonzero components for all crystallographic point groups. It is capable of computing components of higher-order material tensors needed when treating nonlinear effects. It has a simple and flexible interface for inputting tensor rank information and any known symmetries between tensor indices.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.

Jensen, DanielS↗
DOE OSTI2025

Virtual Engineering: Python framework for engineering process design

Virtual Engineering (VE) is a Python software framework designed to accelerate the research and development of engineering processes that are fundamentally defined by multiple unit operations executed in series. VE supports a wide variety of different multi-physics models and integrates them to simulate a complete end-to-end process. To automate the execution of this model sequence, VE provides (i) a robust method to communicate between models, (ii) a high-level, user-friendly interface to set model parameters and enable optimization, and (iii) an overall model-agnostic approach that allows new computational units to be swapped in and out of workflows. Although the VE framework was developed to support the biochemical conversion of biomass to fuel, we have designed each component to easily accommodate new domains and unit models.

09 BIOMASS FUELS↗
DOE OSTI2012

Summary of Alpha-Neutron Sources in GADRAS

A common source of neutrons for calibration and testing is alpha-neutron material, named for the alpha-neutron nuclear reaction that occurs within. This material contains a long-lived alpha-emitter and a lighter target element. When the alpha particle from the emitter is absorbed by the target, neutrons and gamma rays are released. Gamma Detector Response and Analysis Software (GADRAS) includes built-in alpha-neutron source definitions for AcC, AmB, AmBe, AmF, AmLi, CmC, and PuC. In addition, GADRAS users may create their own alpha-neutron sources by placing valid alpha-emitters and target elements in materials within their one-dimensional models (1DModel). GADRAS has the ability to use pre-built alpha-neutron sources for plotting or as trace-sources in 1D models. In addition, if any material (existing or user-defined) specified in a 1D model contains both an alpha emitter in conjunction with a target nuclide, or there is an interface between such materials, then the appropriate neutron-emission rate from the alpha-neutron reaction will be computed. The gamma-emissions from these sources are also computed, but are limited to a subset of nine target nuclides. If a user has experimental data to contribute to the alpha-neutron gamma emission database, it may be added directly or submitted to the GADRAS developers for inclusion. The gadras.exe.config file will be replaced when GADRAS updates are installed, so sending the information to the GADRAS developers is the preferred method for updating the database. This is also preferable because it enables other users to benefit from your efforts.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Final Technical Report

This document serves as the final report for United States Department of Energy Basic Energy Sciences Grant DE-FG02-08ER15929, “Computational and Spectroscopic Investigations of the Molecular Scale Structure and Dynamics of Geologically Important Fluids and Mineral-Fluid Interfaces” (R. James Kirkpatrick, P.I., A. O. Yazaydin, co-P.I.). The research under this grant was intimately tied to that supported by the parallel the grant of the same title at Alfred (DOE DE-FG02-10ER16128; Geoffrey M. Bowers, P.I.).

58 GEOSCIENCES↗
DOE OSTI2018

Petri Nets for Adversarial Models using Monte Carlo Simulation

We describe an object-oriented framework and user interface for developing models of adversarial scenarios, implemented as stochastic Petri nets. The framework is implemented using the statistical computing language R, and provides facilities for eliciting models from subject matter experts, displaying models graphically, simulating scenario execution, and presenting scenario outcomes and statistics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Optimization of Energy Flow Through Synthetic Metabolic Modules and Regulatory Networks in a Model Photosynthetic Eukaryotic Microbe

Diatoms are important oceanic photosynthetic microorganisms, responsible for approximately 20% of all carbon fixation on Earth. Additionally, diatoms are attractive metabolic engineering candidates. This investigation leveraged Systems Biology techniques to advance our understanding of and potential to engineer diatoms for bioproducts of societal interest, such as biofuels. Systems Biology combines computational and experimental techniques to understand an organism at the whole-cell level as well as characterize the interface between the organism and its environment. Our research resulted in major contributions to the understanding of systems-level light-driven metabolism. Diatoms have a unique evolutionary history. As a result, existing understanding of photosynthetic metabolism may not be applicable to diatom physiology. We generated, validated, and published a high-quality metabolic model of diatom metabolism facilitating novel insights into these unique organisms. Additionally, we overcame a consistent challenge in the modeling of photosynthetic organisms by integrating light into metabolic models. This result allows realistic assessments of how the light environment affects cell physiology and metabolism, a necessary advancement for bioengineering. Next, we generated several methodologies for integrating large-scale datasets with models of metabolism. These “big data” approaches begin to address a constant challenge in biology, which is translating data into information and understanding. Finally, we built web-based databases for housing, distributing, and visualizing systems-level biology data. These projects created an online ecosystem for sharing, analyzing, and characterizing metabolic information and is currently being used by public and private institutions. Photosynthetic bioengineering has the promise to create high-energy products with minimal inputs. Systems Biology has a long history of facilitating bioengineering of cellular metabolism. However, photosynthetic organisms are only sparsely present in this history. This project and its outputs have accelerated the application of proven Systems Biology techniques to light-driven metabolism. The resulting methodologies will accelerate public and private endeavors leveraging photosynthetic systems in the bioengineering of bioproducts such as biofuels or carbon sequestration.

09 BIOMASS FUELS↗
DOE OSTI2022

Machine learning approaches to streamline and enhance the analysis of multiscale imaging data for bioaerosol and soil particles

Bioaerosol and soil particles are ubiquitous in the environment. They are multicomponent and complex in nature displaying mixed inorganic and organic components. The way components are mixed in a bioaerosol sample is referred to as its mixing state. Soil particles are also a mixture of inorganic (mineral) and organic (soil organic matter) components. Bioaerosol particles contribute to a major fraction of coarse mode atmospheric particles, especially in the tropical areas, contributing up to 80 % of the particle mass concentration. The mixing state of particles is crucial to evaluate because it impacts several important environmental processes such as warm and cold cloud formation and radiation budget. Mixing states in aerosols are accompanied by chemical reactions across solid-liquid-gas interfaces. In this study, we utilized elemental compositions and microcopy images of thousands of atmospheric particles acquired by computer-controlled scanning electron microscope equipped with an energy-dispersive x-ray spectrometer to compute the mixing state of atmospheric particles. A 2D convolutional neural network (CNN), also known as convnet, was used to model the relationship between low resolution imaging data and higher resolution spectroscopy data, with the former as training input and the latter as target output. Two types of CNNs were implemented and tested; a basic CNN and an Inception-v3 network. For binary classification, the basic CNN achieved an accuracy of 84.29 % across all atom types, and the Inception-v3-like network achieved an accuracy 85.51 %. This study demonstrates the applicability of deep learning to handle large amounts of imaging/chemical spectroscopy data efficiently and evaluate particle mixing state from a range of environmental samples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Grid Optimization Competition Challenge 3 Problem Formulation

This report contains the problem formulation for the Grid Optimization (GO) Competition Challenge 3. The Grid Optimization Competition is run by a team of researchers from a number of organizations, including the sponsor Advanced Research Projects Agency - Energy (ARPA-E), lead organization Pacific Northwest National Laboratory (PNNL), and technical contributors from Los Alamos National Laboratory (LANL), National Renewable Energy Laboratory (NREL), Texas A&M University (TAMU), Georgia Institute of Technology (GT), University of Wisconsin (UW), and others. The GO Competition poses challenge problems in the field of power grid management, invites entrants to develop solvers for these problems, invokes the solvers on a set of problem instances using common hardware, ranks the solvers according to their performance, and awards prizes according to the rankings. The overall goal of the GO Competition is to spur innovative research on high impact and computationally challenging problems in power grid management from initial development through commercial deployment. Complete information about the GO Competition can be found online at [2]. The webpage covers previous Challenges, rules, timeline, registration information, data formats, scoring methods, computational platform information, information on supported solvers and languages, sponsor information, frequently asked questions, administrator contact information, publicly available problem instances, computer code for reading and evaluating problem and solution data, a sandbox for testing solvers, and a solver submission interface, results, and publications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

LHC Event Generation in the Exascale Era

MCFM is a dedicated Monte-Carlo simulation program for collider phenomenology at highest energies. Designed during the Tevatron era, it has successfully incorporated the latest developments needed for LHC precision calculations and remained on the forefront of collider phenomenology. The Fortran code includes interfaces to modern PDF and loop reduction libraries but has been unchanged structurally compared to the earlier versions. Parallel computing has been enabled using OpenMP and MPI. MCFM provides numerically highly stable one-loop amplitudes and superior phase-space efficiency, leading to excellent performance in NXLO calculations using jettiness or qT subtraction techniques for IR regularization.

Campbell, John [Fermilab]↗
DOE OSTI2016

Integrated circuit test-port architecture and method and apparatus of test-port generation

A method and apparatus are provided for generating RTL code for a test-port interface of an integrated circuit. In an embodiment, a test-port table is provided as input data. A computer automatically parses the test-port table into data structures and analyzes it to determine input, output, local, and output-enable port names. The computer generates address-detect and test-enable logic constructed from combinational functions. The computer generates one-hot multiplexer logic for at least some of the output ports. The one-hot multiplexer logic for each port is generated so as to enable the port to toggle between data signals and test signals. The computer then completes the generation of the RTL code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Hybrid multiphase CFD simulation for liquid-liquid interfacial area prediction in annular centrifugal contactors

Liquid-liquid contacting equipment used in solvent extraction processes has the dual purpose of mixing and separating two immiscible fluids. Consequently, such devices inherently encompass a wide variety of multiphase flow regimes. A hybrid multiphase computational fluid dynamics (CFD) solver which combines the Eulerian multi-fluid method with VOF (volume of fluid) sharp interface capturing has been developed for application to annular centrifugal contactors. This solver has been extended to enable prediction of mean droplet size and liquid-liquid interfacial area through a single moment population balance method. Simulations of liquid-liquid mixing in a simplified geometry and a model annular centrifugal contactor are reported with droplet breakup/coalescence models being calibrated versus available experimental data. Quantitative comparison is made for two different housing vane geometries and it is found that the predicted droplet size is significantly smaller for vane geometries which result in higher annular liquid holdup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Develop and Connect TRISO Failure Analysis and Uncertainty Quantification to Fission Product Release Calculation Capability

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. Stress-based failure probability has been developed and analyzed to assess the integrity of tri-structural isotropic (TRISO) fuel particles during fuel life cycles. While simple, stress-based approaches to failure probability leveraging the Weibull statistical distribution entails a number of drawbacks when stress concentration occurs near crack tips, including finite element mesh size dependency. In this report, we use an interaction integral approach to the computation of stress intensity factors in functionally graded materials (FGM) for axisymmetric models. The inner pyrolytic carbon (IPyC) cracking induced silicon carbide (SiC) failure is one of the dominated failure modes in TRISO failure analysis. In this study, we consider a crack in the IPyC layer perpendicular to the SiC layer. The interface between these two TRISO layers is considered to be porous, which we simulate considering a transition of mechanical properties over the porous length. These aspects are considered in the computation of stress intensity factor (SIF) from a fracture mechanics approach and compared with the known stress-based failure probability approach.

42 ENGINEERING↗
DOE OSTI2013

FAST: A Fast Full System Cycle Accurate Computer Simulator (Early Career Principal Investigator Award Final Report)

This project is researching FAST, a methodology to build very fast, cycle-accurate full system computer simulators and building the first set of such simulators and the first set of tools to help construct those simulators. The methodology relies on a functional model that is a fast, full-system but not cycle-accurate simulator coupled with a timing model that is models the micro-architectural structure and arbitration of a computer system, but not its functionality. The way FAST simulators differ from other simulators partitioned in the same way is that the interface between the functional and timing model is optimized to minimize the need for round-trip communication. The optimized communication enables FAST timing models to be implemented in an FPGA and the functional model in software while still achieving extremely high performance. Our general strategy is to design a methodology and then prototype an example using that methodology to ensure the methodology is sound before committing to it. This strategy ensures that the selected methodology has been tested and provides an early example of the output of that methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Emitter/absorber interface of CdTe solar cells

The performance of CdTe solar cells can be very sensitive to the emitter/absorber interface, especially for high-efficiency cells with high bulk lifetime. Performance losses from acceptor-type interface defects can be significant when interface defect states are located near mid-gap energies. Numerical simulations show that the emitter/absorber band alignment, the emitter doping and thickness, and the defect properties of the interface (i.e., defect density, defect type, and defect energy) can all play significant roles in the interface recombination. In particular, a type I heterojunction with small conduction-band offset (0.1 eV ≤ ΔE{sub C} ≤ 0.3 eV) can help maintain good cell efficiency in spite of high interface defect density, much like with Cu(In,Ga)Se{sub 2} (CIGS) cells. The basic principle is that positive ΔE{sub C}, often referred to as a “spike,” creates an absorber inversion and hence a large hole barrier adjacent to the interface. As a result, the electron-hole recombination is suppressed due to an insufficient hole supply at the interface. A large spike (ΔE{sub C} ≥ 0.4 eV), however, can impede electron transport and lead to a reduction of photocurrent and fill-factor. In contrast to the spike, a “cliff” (ΔE{sub C} < 0 eV) allows high hole concentration in the vicinity of the interface, which will assist interface recombination and result in a reduced open-circuit voltage. Another way to mitigate performance losses due to interface defects is to use a thin and highly doped emitter, which can invert the absorber and form a large hole barrier at the interface. CdS is the most common emitter material used in CdTe solar cells, but the CdS/CdTe interface is in the cliff category and is not favorable from the band-offset perspective. The ΔE{sub C} of other n-type emitter choices, such as (Mg,Zn)O, Cd(S,O), or (Cd,Mg)Te, can be tuned by varying the elemental ratio for an optimal positive value of ΔE{sub C}. These materials are predicted to yield higher voltages and would therefore be better candidates for the CdTe-cell emitter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Computational understanding of Li-ion batteries

Over the last two decades, computational methods have made tremendous advances, and today many key properties of lithium-ion batteries can be accurately predicted by first principles calculations. For this reason, computations have become a cornerstone of battery-related research by providing insight into fundamental processes that are not otherwise accessible, such as ionic diffusion mechanisms and electronic structure effects, as well as a quantitative comparison with experimental results. The aim of this review is to provide an overview of state-of-the-art ab initio approaches for the modelling of battery materials. Here, we consider techniques for the computation of equilibrium cell voltages, 0-Kelvin and finite-temperature voltage profiles, ionic mobility and thermal and electrolyte stability. The strengths and weaknesses of different electronic structure methods, such as DFT+U and hybrid functionals, are discussed in the context of voltage and phase diagram predictions, and we review the merits of lattice models for the evaluation of finite-temperature thermodynamics and kinetics. With such a complete set of methods at hand, first principles calculations of ordered, crystalline solids, i.e., of most electrode materials and solid electrolytes, have become reliable and quantitative. However, the description of molecular materials and disordered or amorphous phases remains an important challenge. We highlight recent exciting progress in this area, especially regarding the modelling of organic electrolytes and solid–electrolyte interfaces.

25 ENERGY STORAGE↗
DOE OSTI2014

Coupled Physics Environment (CouPE) library - Design, Implementation, and Release

Over several years, high fidelity, validated mono-­physics solvers with proven scalability on peta-­scale architectures have been developed independently. Based on a unified component-­based architecture, these existing codes can be coupled with a unified mesh-­data backplane and a flexible coupling-­strategy-­based driver suite to produce a viable tool for analysts. In this report, we present details on the design decisions and developments on CouPE, an acronym that stands for Coupled Physics Environment that orchestrates a coupled physics solver through the interfaces exposed by MOAB array-­based unstructured mesh, both of which are part of SIGMA (Scalable Interfaces for Geometry and Mesh-­Based Applications) toolkit. The SIGMA toolkit contains libraries that enable scalable geometry and unstructured mesh creation and handling in a memory and computationally efficient implementation. The CouPE version being prepared for a full open-­source release along with updated documentation will contain several useful examples that will enable users to start developing their applications natively using the native MOAB mesh and couple their models to existing physics applications to analyze and solve real world problems of interest. An integrated multi-­physics simulation capability for the design and analysis of current and future nuclear reactor models is also being investigated as part of the NEAMS RPL, to tightly couple neutron transport, thermal-­hydraulics and structural mechanics physics under the SHARP framework. This report summarizes the efforts that have been invested in CouPE to bring together several existing physics applications namely PROTEUS (neutron transport code), Nek5000 (computational fluid-dynamics code) and Diablo (structural mechanics code). The goal of the SHARP framework is to perform fully resolved coupled physics analysis of a reactor on heterogeneous geometry, in order to reduce the overall numerical uncertainty while leveraging available computational resources. The design of CouPE along with motivations that led to implementation choices are also discussed. The first release of the library will be different from the current version of the code that integrates the components in SHARP and explanation on the need for forking the source base will also be provided. Enhancements in the functionality and improved user guides will be available as part of the release. CouPE v0.1 is scheduled for an open-­source release in December 2014 along with SIGMA v1.1 components that provide support for language-agnostic mesh loading, traversal and query interfaces along with scalable solution transfer of fields between different physics codes. The coupling methodology and software interfaces of the library are presented, along with verification studies on two representative fast sodium-­cooled reactor demonstration problems to prove the usability of the CouPE library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Quantitative x ray phase contrast imaging of oblique shock wave–interface interactions

Oblique shock wave–interface interactions of gases and liquids have been extensively studied in shock tubes using optical methods to measure equation-of-state (EOS) parameters. However, this is difficult with solids due to their opaqueness to visible light. X ray phase contrast imaging (XPCI) has the penetrative strength to probe solids while still being sensitive to mass density and enhancing the visibility of material boundaries. We investigate the accuracy and repeatability of measuring the mean value of the average mass density (areal density divided by thickness) over region S (B S ) and flow deflection angle (θ) from XPCI images of a sample. To that end, a Hough transform-based method for measuring θ is developed. To measure B S , the XPCI image intensity probability density function (PDF) is modeled accounting for the spatial distribution of x ray energy, scintillator response, and pulse-to-pulse variation in the x ray intensity. In addition, a Monte Carlo-based algorithm for computing the B S PDF is developed. Both methods are validated on an impact-generated oblique shock wave interacting at a solid polymer-to-polymer interface. Furthermore this is accomplished through a comparison to hydrodynamic simulations using well-established EOS. Under the modeling framework for the XPCI image intensity, B S is computed with an accuracy of < 0.1% and precision of 3%–5%, while θ has an uncertainty of 0.2°, respectively. This shows that the XPCI-based model that is developed here could be an invaluable tool for high-fidelity testing of hydrodynamic models in shock polar configurations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Three-dimensional local ALE-FEM method for fluid flow in domains containing moving boundaries/objects interfaces

A three-dimensional finite element method for the numerical simulations of fluid flow in domains containing moving rigid objects or boundaries is developed. The method falls into the general category of Arbitrary Lagrangian Eulerian methods; it is based on a fixed mesh that is locally adapted in the immediate vicinity of the moving interfaces and reverts to its original shape once the moving interfaces go past the elements. The moving interfaces are defined by separate sets of marker points so that the global mesh is independent of interface movement and the possibility of mesh entanglement is eliminated. The results is a fully robust formulation capable of calculating on domains of complex geometry with moving boundaries or devises that can also have a complex geometry without danger of the mesh becoming unsuitable due to its continuous deformation thus eliminating the need for repeated re-meshing and interpolation. Moreover, the boundary conditions on the interfaces are imposed exactly. This work is intended to support the internal combustion engines simulator KIVA developed at Los Alamos National Laboratories. The model's capabilities are illustrated through application to incompressible flows in different geometrical settings that show the robustness and flexibility of the technique to perform simulations involving moving boundaries in a three-dimensional domain.

16 TIDAL AND WAVE POWER↗