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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Modeling the direct sun component in buildings using matrix algebraic approaches: Methods and validation

Simulation tools that enable annual energy performance analysis of optically-complex fenestration systems have been widely adopted by the building industry for use in building design, code development, and the development of rating and certification programs for commercially-available shading and daylighting products. The tools rely on a three-phase matrix operation to compute solar heat gains, using as input low-resolution bidirectional scattering distribution function (BSDF) data (10–15° angular resolution; BSDF data define the angle-dependent behavior of light-scattering materials and systems). Measurement standards and product libraries for BSDF data are undergoing development to support solar heat gain calculations. Simulation of other metrics such as discomfort glare, annual solar exposure, and potentially thermal discomfort, however, require algorithms and BSDF input data that more accurately model the spatial distribution of transmitted and reflected irradiance or illuminance from the sun (0.5° resolution). This study describes such algorithms and input data, then validates the tools (i.e., an interpolation tool for measured BSDF data and the five-phase method) through comparisons with ray-tracing simulations and field monitored data from a full-scale testbed. Simulations of daylight-redirecting films, a micro-louvered screen, and venetian blinds using variable resolution, tensor tree BSDF input data derived from interpolated scanning goniophotometer measurements were shown to agree with field monitored data to within 20% for greater than 75% of the measurement period for illuminance-based performance parameters. The three-phase method delivered significantly less accurate results. We discuss the ramifications of these findings on industry and provide recommendations to increase end user awareness of the current limitations of existing software tools and BSDF product libraries.

14 SOLAR ENERGY↗
DOE OSTI2025

ExaCA v2.0: A versatile, scalable, and performance portable cellular automata application for additive manufacturing solidification

The previously established ExaCA software for performance portable alloy grain structure simulation has been updated to better represent the solidification behavior during complex alloy processing conditions, such as those encountered during metal additive manufacturing (AM), and for improved performance and scalability. Here, an extension to the time–temperature history input data format and the core ExaCA algorithm to include an arbitrary number of melting and solidification events yielded improved prediction of texture for various melt pool geometries, expanding the range of AM-relevant conditions that can be accurately simulated. Improved heat transport process simulation coupling, including the creation of large raster datasets from single track time–temperature history data and in-memory coupling with the new, performance portable finite difference code Finch, were also demonstrated in example studies on the effect of multilayer AM microstructure predictions on hatch spacing and cell size, respectively. Additional new features are detailed and demonstrated, including the ability to perform simulations using various interfacial response function forms, execute simulations on state-of-the-art hardware, improved usability through post-processing versatility, and improved strong and weak scaling performance. The performance, physics, and versatility improvements demonstrated here will further enable large-scale studies on AM process–microstructure relationships that were not previously possible. Furthermore, the usability improvements and ability to run coupled AM process–microstructure simulations using the Finch-ExaCA workflow will facilitate broader use of this open-source software by the computational materials community.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Building an open source software ecosystem for cross-disciplinary plasma research and education

Software is crucial to all areas of modern plasma science research. Laboratory plasma physicists use software to interpret plasma diagnostics, analyze experimental results, and glean insights using advanced techniques from data science. Space scientists use software to reduce and understand in situ observations. Numericists use software to simulate the behavior of laboratory, heliospheric, and astrophysical plasmas, and then analyze or visualize the results. Theorists use symbolic manipulation software to perform or check derivations. Cross-disciplinary research and cross-comparisons between experiments, observations, simulations, and theories all require software. Despite our heavy reliance on software, funding agencies have traditionally had few avenues available to support development of general purpose research software infrastructure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

The Integration of Plant Sample Analysis, Laboratory Studies, and Thermodynamic Modeling to Predict Slag-Matte Equilibria in Nickel Sulfide Converting

The Kalgoorlie Nickel Smelter (KNS) produces low Fe, low Cu nickel matte in its Peirce–Smith converter operations. To inform process development in the plant, new fundamental data are required on the effect of CaO in slag on the distribution of arsenic between slag and matte. A combination of plant sample analysis, high-temperature laboratory experiments, and thermodynamic modeling was carried out to identify process conditions in the converter and to investigate the effect of slag composition on the chemical behavior of the system. The high-temperature experiments involved re-equilibration of industrial matte-slag-lime samples at 1498 K (1225 °C) and P(SO{sub 2}) = 0.12 atm on a magnetite/quartz substrate, rapid quenching in water, and direct measurement of phase compositions using electron probe X-ray microanalysis (EPMA) and laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS). A private thermodynamic database for the Ca-Cu-Fe-Mg-Ni-O-S-Si-(As) system was used together with the FactSage software package to assist in the analysis. Thermodynamic predictions combined with plant sample characterization and the present experimental data provide a quantitative basis for the analysis of the effect of CaO fluxing on the slag-matte thermochemistry during nickel sulfide converting, in particular on the spinel liquidus and the distribution of elements between slag and matte as a function of CaO addition.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Correct Compilation of Concurrent C Code

The CompCert compiler represents a landmark effort in program verification as both a piece of verified software and as a compiler for verified C programs. A key shortcoming of CompCert however is that it does not support multithreaded programs. Prior work to add threads to CompCert has either required major rewrites of parts of the proof or only works for well synchronized programs. The problem is that CompCert’s backward simulation derives from a forward simulation via the determinism of the semantics of intermediate representation languages. This makes the proofs in CompCert easier but also makes them incompatible with standard models of multithreading which are non-deterministic. Here we propose an alternate formulation of CompCert’s proof structure that parameterizes the existing single threaded semantics with nondeterministic behavior generated at the multithreading level. While this is an old trick where program equivalence is concerned, performing it in the context of CompCert is quite subtle. Our approach allows for expressive concurrent semantics and does not require major proof rewrites but still results in a global backward simulation for multithreaded programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

ADAM: A web platform for graph-based modeling and optimization of supply chains

Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. Here, in this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

pysrim: Automation, Analysis, and Plotting of SRIM Calculations

The behavior of ions traveling through a material is of great interest to many fields. For instance, radiation damage in nuclear materials and ion beam modification of materials are most concerned with understanding the formation and evolution of defects along the ion path (Was 2016). Some of the important properties that can be gleaned from investigating the initial damage from the ion include: numbers of interstitials and vacancies produced, energy deposited per unit length to electrons and atomic nuclei, track diameter, and implanted ion profile. These properties enable further simulations and allow computing a common unit of radiation damage dose, displacements per atom (dpa), which can be used to compare irradiation experiments with different ions (Backman et al. 2013) (Stoller et al. 2013). Additionally, the ejection of materials near the surface due to incident ions is important to sputtering and ion-beam analysis techniques, such as elastic recoil detection analysis (ERDA) and secondary ion mass spectrometry (SIMS) (Vickerman and Gilmore 2011). The interaction of ions within a material can be broken into two parts: electronic and nuclear stopping. Electronic stopping is the energy lost from the ion due to inelastic collisions with electrons along its path. Nuclear stopping is the energy lost due to elastic collisions between the ion and atomic nuclei within the material. The Stopping and Range of Ions in Matter (SRIM) code is a well known software in the radiation damage and ion-beam communities that allows the simulation, via Monte Carlo, of ions through a material by modeling the energy transfer through electronic and nuclear stopping (J. F. Ziegler, Ziegler, and Biersack 2010). SRIM was originally developed in 1985 and has had numerous updates on the electronic stopping powers since then, with the nuclear stopping well explained by the ZBL potential (J. F. Ziegler 1988). The executable SRIM is free to use for non-commercial use but the source code is not available to the community despite requests. While SRIM is a scientifically accurate code it does not get updated frequently and has many bugs from a usability standpoint.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Effects of Zr Ion Implantation on Surface Mechanical Properties and Corrosion Resistance of Pure Magnesium

Zirconium (Zr) was implanted into pure Mg by metal vapor vacuum arc (MEVVA) at the dose of 2 × 10{sup 16} ions/cm{sup 2} at room temperature. The surface characteristics of Zr-implanted Mg were analyzed by the Stopping and Range of Ions in Matter software (SRIM) and x-ray photoelectron spectroscopy (XPS), the surface nanohardness and tribological behavior were measured through nanoindentation and a friction-abrasion testing machine, and the corrosion resistance of Zr-implanted Mg was evaluated by electrochemical measurement and immersion test in simulated body fluid (SBF). The results demonstrated that a gradient modified layer composed of MgO, Mg(OH){sub 2}, ZrO{sub 2} and Zr was formed on the near surface of pure Mg and the nanohardness of pure Mg was improved by 48%. Furthermore, the Zr-implanted Mg exhibited a more positive corrosion potential of − 1.43 V (versus SCE) and a lower corrosion current density of 19.9 μA/cm{sup 2}, and localized corrosion was effectively retarded during 24 h immersion in SBF, suggesting that the corrosion resistance of pure Mg was remarkably improved after Zr ion implantation. The mechanisms of surface strengthening and improved corrosion resistance were also discussed in this paper.

36 MATERIALS SCIENCE↗
DOE OSTI2019

FEAA90: Physics-based Creep Simulation of Thick Section Welds in High Temperature and Pressure Applications

Welded microstructures of ?’-strengthened, nickel-based alloy, 740H, contain significant microstructural heterogeneities that can have a strong influence on the dislocation dynamics, resulting in very different creep behavior compared to the base metal. Crystal plasticity-based finite element method (CPFEM) has been widely used to incorporate the effect of microstructural heterogeneities on deformation at the polycrystalline scale and is being utilized in this work to model the creep behavior of 740H GTA welds. Current model development is focused on secondary creep considering dislocation climb, glide, and, anti-phase boundary shearing or Orowan looping. A dislocation-density based CPFEM model addressing these mechanisms is currently being implemented in the Multi-Physics Object Oriented Simulation Environment (MOOSE: mooseframework.org) software that provides the ability to solve problems involving multiple physics concurrently and implicitly. Short term creep tests at 700-800°C of cross weld and all-weld metal samples from GTA welds in Alloy 740 will be used to determine input parameters for the model. Long term creep tests at 750°C on Alloy 740H GTA welds will be used to validate the results of modeling and simulation. The model will also be applied to welds with microstructures that develop during hybrid laser arc welding (HLAW) of Alloy 740H to evaluate the effect of weld microstructure on of the validity of the model.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Modeling Induction Stirring and Particle Tracking in Molten Uranium

Two independent numerical models have been developed to simulate the behavior of carbon impurities in molten uranium metal. Informed by experimental parameters, one model was created using the commercial software Star-CCM+ and compared with another developed using open-source codes, including OpenFOAM, Finite Element Method Magnetics (FEMM) and a First Passage Kinetic Monte Carlo (FPKMC) approach. The target experimental system features a 404g uranium metal charge containing an average carbon concentration of 139 ppm which was melted in a vacuum induction furnace at 1400° C then resolidified. The microstructures of the uranium and its impurities before and after melting have been characterized and reported separately. Prior to simulating the uranium-carbon system described, the numerical models were validated using a previously published nonradioactive experimental system to ensure agreement with expected output values. Focus has been placed on modeling velocity fields under induction stirring and impurity particle trajectories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Molecular dynamics study of mechanical properties of carbon nanotube reinforced aluminum composites

Atomistic simulations were conducted to estimate the effect of the carbon nanotube (CNT) reinforcement on the mechanical behavior of CNT-reinforced aluminum (Al) nanocomposite. The periodic system of CNT-Al nanocomposite was built and simulated using molecular dynamics (MD) software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator). The mechanical properties of the nanocomposite were investigated by the application of uniaxial load on one end of the representative volume element (RVE) and fixing the other end. The interactions between the atoms of Al were modeled using embedded atom method (EAM) potentials, whereas Adaptive Intermolecular Reactive Empirical Bond Order (AIREBO) potential was used for the interactions among carbon atoms and these pair potentials are coupled with the Lennard-Jones (LJ) potential. The results show that the incorporation of CNT into the Al matrix can increase the Young’s modulus of the nanocomposite substantially. In the present case, i.e. for approximately 9 with % reinforcement of CNT can increase the axial Young’s modulus of the Al matrix up to 77 % as compared to pure Al.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Development and Experimental Optimization of High-Temperature Modeling Tools and Methods for Concentrated Solar Power Particle - Systems

A novel, open-source radiative modeling toolset was developed to extend the functionality of particle-based modeling software (e.g. discrete element method (DEM)) to environmental conditions relevant to concentrated solar power applications. This toolset was optimized for deployment on desktop workstations instead of high-performance computing systems, to render such tools more accessible to the research community. Both particle-based modeling and radiative exchange modeling are computationally expensive and often require specialized programming expertise, making these methods cumbersome to use. Recent developments in DEM software by DCS Computing have greatly reduced these challenges, providing a graphical-user-interface based platform and modeling optimization for desktop workstations, HPCs, and cloud computing. The University of Dayton leveraged the experience of DCS Computing in developing a user-friendly, open-source radiative heat transfer expansion for DEM modeling. The University of Dayton DEM+ radiative modeling toolset was developed using a combination of fundamental experimental measurements, modeling, and simplified flow experiments over a range of temperatures and flow conditions. The toolset provides researchers with access to multiple radiative models including an accelerated Monte-Carlo Ray Tracing (application agnostic, highly computationally expensive), an expanded database of distance-based approximations (application limited, computationally light), and a weighted blending of the two methods capable of achieving over 90% reduction in computation time with equivalent accuracy compared to Monte-Carlo Ray Tracing. Through a graphical user interface, users can customize the radiative models to match their desired accuracy and available computational resources, improving access to particle based modeling for the research community. Ceramic sintered bauxite proppants were used in modeling and experimentally as a baseline. Both the radiative heat transfer and flow properties for particulate systems were investigated at elevated temperatures up to 800 °C. The major accomplishments for this work include a verified, open-source radiative modeling toolset to be distributed amongst the research community and the fabrication of three small-scale test facilities to investigate particle behavior and tune DEM flow properties for operation up to 800 °C. The findings have been shared with the research community via conference modeling workshops, deployment of the tools in DCS Computing Aspherix®, and open-source access to the developed radiative modeling tool. The development of next-generation CSP facilities and thermal energy storage systems based on ceramic particles requires providing access to computationally efficient and accurate modeling tools. Particles will experience a wide range of environments (20-800 °C) and handling conditions (dilute curtains or dense packing), requiring specially designed and optimized equipment. Optimizing solid particle physics models and establishing best-practices for particle modeling in CSP environments will assist researchers with designing optimized equipment, accelerating the deployment of more economically-competitive CSP facilities.

14 SOLAR ENERGY↗
DOE OSTI2023

Using Eye-Tracking to Quantify Reverse Engineering Expertise

Software reverse engineering (RE) requires analysts to closely read and make decisions about code. Little is known about what makes an analyst successful, making it difficult to train new analysts or design tools to augment existing ones. The goal of this project was to quantify the eye movement behaviors supporting RE and code comprehension more generally. We applied eye-tracking methods from the language comprehension literature to understand where analysts direct their attention over time when completing tasks (e.g., function identification, bug detection). Across three studies, we manipulated aspects of code hypothesized to impact comprehension (e.g., variable name meaningfulness, code complexity) and presentation methods (e.g., line-by-line, free viewing, gaze-contingent moving window) to understand effects on accuracy and gaze patterns. Results showed clear benefits of meaningful variable names, and effects of expertise on global and line-specific viewing patterns. Findings could inspire empirically-supported tool or analytic adaptations that help to reduce analyst workload.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

A Novel Method of Modeling the Deformation Resistance for Clad Sheet

Because of the excellent thermal conductivity, the clad sheet (3003/4004/3003) of aluminum alloy is extensively used in various heat exchangers, such as radiator, motorcar air conditioning, evaporator, and so on. The deformation resistance model plays an important role in designing the process parameters of hot continuous rolling. However, the complex behaviors of the plastic deformation of the clad sheet make the modeling very difficult. In this work, a novel method for modeling the deformation resistance of clad sheet was proposed by combining the finite element analysis with experiments. The deformation resistance model of aluminum 3003 and 4004 was proposed through hot compression test on the Gleeble-1500 thermo-simulation machine. And the deformation resistance model of clad sheet was proposed through finite element analysis using DEFORM-2D software. The relationship between cladding ratio and the deformation resistance was discussed in detail. The results of hot compression simulation demonstrate that the cladding ratio has great effects on the resistance of the clad sheet. Taking the cladding ratio into consideration, the mathematical model of the deformation resistance for clad sheet has been proved to have perfect forecasting precision of different cladding ratio. Therefore, the presented model can be used to predict the rolling force of clad sheet during the hot continuous rolling process.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Mesoscale Numerical Characterization of Kevlar and Carbon–Kevlar Hybrid Plain-Woven Fabric Compression Behavior

A mesoscale finite element model (FEM) of the plain-woven fabric representative elementary volume (REV/unit cell) is developed. The developed FEM is used to predict the nonlinear compaction behavior of monolithic and intraply hybrid fabric made of high-strength carbon and Kevlar fibers. For geometrical modeling of the fabric REV, TexGen, an open-source geometrical modeling software (developed at Nottingham University), is utilized, and for mechanical characterization, FE simulation tool Abaqus{sup ®} is used. Geometrical nonlinearity of the fabric, including periodic boundary conditions and yarn interactions, is incorporated in the REV FE model. Material nonlinearity caused by transversely isotropic behavior of fibrous yarns is implemented through the user material subroutine form in FE simulation along with local orientation assigned to each yarn in the REV. Material properties of fibers are extracted from the literature and supplier data. The compression behavior of monolithic Kevlar and hybrid carbon–Kevlar (carbon warp and Kevlar weft yarns, C–K) fabric is predicted using the proposed FE model. FEM-predicted results were found to have good agreement with the experimentally obtained ones. Results depict that C–K hybrid fabrics have improved compression strength. Hybridization effect is governed by yarns mutual interaction, yarn area at crossovers, and transverse in-plane properties of the interyarn hybridized fabric. The proposed FE model can be used to predict the mechanical behavior of woven fabrics with different weaving patterns, unit cell geometry, material properties, and loading conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Inter-Disciplinary Collaboration in Support of the Post-Standby TREAT Mission

Although analysis methods have advanced significantly in the last two decades, high fidelity multi- physics methods for reactors systems have been under development for only a few years and are not presently mature nor deployed. Furthermore, very few methods provide the ability to simulate rapid transients in three dimensions. Data for validation of advanced time-dependent multi- physics is sparse; at TREAT, historical data were not collected for the purpose of validating three-dimensional methods, let alone multi-physics simulations. Existing data continues to be collected to attempt to simulate the behavior of experiments and calibration transients, but it will be insufficient for the complete validation of analysis methods used for TREAT transient simulations. Hence, a 2018 restart will most likely occur without the direct application of advanced modeling and simulation methods. At present, the current INL modeling and simulation team plans to work with TREAT operations staff in performing reactor simulations with MAMMOTH, in parallel with the software packages currently being used in preparation for core restart (e.g., MCNP5, RELAP5, ABAQUS). The TREAT team has also requested specific measurements to be performed during startup testing, currently scheduled to run from February to August of 2018. These startup measurements will be crucial in validating the new analysis methods in preparation for ultimate application for TREAT operations and experiment design. This document describes the collaboration between modeling and simulation staff and restart, operations, instrumentation and experiment development teams to be able to effectively interact and achieve successful validation work during restart testing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-J-106: The Use of Deformable Image Registration with Cone-Beam CT for a Better Evaluation of Cumulative Dose to Organs

Purpose: The knowledge of dose accumulation in the patient tissues in radiotherapy helps in determining the treatment outcomes. This project aims at providing a workflow to map cumulative doses that takes into account interfraction organ motion without the need for manual re-contouring. Methods: Five prostate cancer patients were studied. Each patient had a planning CT (pCT) and 5 to 13 CBCT scans. On each series, a physician contoured the prostate, rectum, bladder, seminal vesicles and the intestine. First, a deformable image registration (DIR) of the pCTs onto the daily CBCTs yielded registered CTs (rCT) . This rCT combined the accurate CT numbers of the pCT with the daily anatomy of the CBCT. Second, the original plans (220 cGy per fraction for 25 fractions) were copied on the rCT for dose re-calculation. Third, the DIR software Elastix was used to find the inverse transform from the rCT to the pCT. This transformation was then applied to the rCT dose grid to map the dose voxels back to their pCT location. Finally, the sum of these deformed dose grids for each patient was applied on the pCT to calculate the actual dose delivered to organs. Results: The discrepancy between the planned D98 and D2 and these indices re-calculated on the rCT, are, on average, of −1 ± 1 cGy and 1 ± 2 cGy per fraction, respectively. For fractions with large anatomical motion, the D98 discrepancy on the re-calculated dose grid mapped onto the pCT can raise to −17 ± 4 cGy. The obtained cumulative dose distributions illustrate the same behavior. Conclusion: This approach allowed the evaluation of cumulative doses to organs with the help of uncontoured daily CBCT scans. With this workflow, the easy evaluation of doses delivered for EBRT treatments could ultimately lead to a better follow-up of prostate cancer patients.

60 APPLIED LIFE SCIENCES↗