Recent Atomistic Simulations at Sandia - Hydrogen Materials Consortium (H-Mat)
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Zhou, Xiaowang↗
SEARCH · Engineering Papers
Results for “materials simulations”
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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Modeling of materials supply, demand and prices
The societal, economic, and policy tradeoffs associated with materials processing and utilization, are discussed. The materials system provides the materials engineer with the system analysis required for formulate sound materials processing, utilization, and resource development policies and strategies. Materials system simulation and modeling research program including assessments of materials substitution dynamics, public policy implications, and materials process economics was expanded. This effort includes several collaborative programs with materials engineers, economists, and policy analysts. The technical and socioeconomic issues of materials recycling, input-output analysis, and technological change and productivity are examined. The major thrust areas in materials systems research are outlined.
Source record↗
Orbital foamed material extruder
This invention is a process for producing foamed material in space comprising the steps of: rotating the material to simulate the force of gravity; heating the rotating material until it is molten; extruding the rotating, molten material; injecting gas into the extruded, rotating, molten material to produce molten foamed material; allowing the molten foamed material to cool to below melting temperature to produce the foamed material. The surface of the extruded foam may be heated to above melting temperature and allowed to cool to below melting temperature. The extruded foam may also be cut to predetermined length. The starting material may be metal or glass. Heating may be accomplished by electrical heating elements or by solar heating.
Tucker, Dennis S.↗
Presentation material for Progress in Simulated Water Well Performance on Mars
This presentation reports on the results of some experimental work regarding the establishment and operation of water wells on Mars. These results were accomplished since this group reported on this concept at the AIAA Space conference in 2018. These experiments were conducted to improve the understanding of a Rodwell’s performance under Mars surface conditions. The motivation to improve this understanding results from the leverage that access to large quantities of water, already on Mars, gives to future human missions to that planet. Previous work by this group has described the likely location of these water deposits and the extensive history of terrestrial use of the Rodwell technique. The results reported in this presentation indicate several key points. First, it has been demonstrated that a stable pool of water can be maintained under Martian surface environmental conditions using an approach comparable to terrestrial Rodwells. Next, it was unexpectedly learned that the water pool exhibits some of the same structural characteristics – specifically an ice shelf just above the water pool – that are seen in terrestrial Rodwells. This finding directly affected the way in which test data was reduced. And finally the experimental data was used to generate equations for convection-driven evaporation and convective heat transfer. The evaporation results were found to follow the same trends as published results for experiments in terrestrial environments. But the results reported here have also extended the range of these trends into much smaller Rayleigh Number ranges than anything previously reported. It was also found that convective heat transfer does not following published results even in the same Rayleigh Number range. A suggested explanation for this result has been proposed based on phenomenon described in the literature, but this group continues to look at the results to see if a better explanation can be found.
Mars↗
Characterization of Modern Spacecraft Materials under Space-simulated Environment
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Elena Plis↗
Large-scale First Principles Atomistic Simulation of Plasma Facing Materials.
Abstract not provided.
Cusentino, Mary Alice↗
Insights from a Joint US/India Workshop on Modeling and Simulation for Improved Nuclear Material Accountancy.
Abstract not provided.
Shoman, Nathan↗
Phase-field modeling of crack growth under coupled creep-fatigue
Crack growth under coupled creep-fatigue strongly influences service life of metallic components operating at high temperatures. However, there lack numerical models that enable direct simulations of crack growth and plasticity development under coupled creep-fatigue. Here, in this study, a unified phase-field model is developed for simulating crack growth under fatigue, creep, and coupled creep-fatigue. This model is able to reproduce the Paris laws for both brittle and ductile materials in pure fatigue mode, which shows that the degradation rate due to cyclic stress in ductile materials is generally larger than that in brittle materials. Fatigue simulations with different yield strengths demonstrate that plasticity facilitates crack growth in typical ductile materials. High-throughput simulations are performed under coupled creep-fatigue conditions, with varying hold-stress levels and hold-time. By analyzing crack growth rate under different hold-time, a creep-fatigue interaction term is obtained. Simulation results demonstrate that the creep-fatigue interaction is caused by smaller stress gradient and enhanced degradation rate ahead of the crack tips under coupled creep-fatigue, compared to the situation of pure fatigue. This work reveals the origin of different Paris-law exponents in brittle and ductile materials and demonstrates how the interplay between creep and fatigue affects crack growth.
36 MATERIALS SCIENCE↗
Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems
Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.
Preconditioner, Nonlinear, Porous media, Multiphas↗
Towards simulation of the dynamics of materials on quantum computers
A highly anticipated application for quantum computers is as a universal simulator of quantum many-body systems, as was conjectured by Richard Feynman in the 1980s. The last decade has witnessed the growing success of quantum computing for simulating static properties of quantum systems, i.e., the ground state energy of small molecules. However, it remains a challenge to simulate quantum many-body dynamics on current-to-near-future noisy intermediate-scale quantum computers. In this work, we demonstrate successful simulation of nontrivial quantum dynamics on IBM's Q16 Melbourne quantum processor and Rigetti's Aspen quantum processor; namely, ultrafast control of emergent magnetism by THz radiation in an atomically-thin two-dimensional material. The full code and step-by-step tutorials for performing such simulations are included to lower the barrier to access for future research on these two quantum computers. As such, this work lays a foundation for the promising study of a wide variety of quantum dynamics on near-future quantum computers, including dynamic localization of Floquet states and topological protection of qubits in noisy environments.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design
The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques. JARVIS is motivated by the Materials Genome Initiative (MGI) principles of developing open-access databases and tools to reduce the cost and development time of materials discovery, optimization, and deployment. The major features of JARVIS are: JARVIS-DFT, JARVIS-FF, JARVIS-ML, and JARVIS-tools. To date, JARVIS consists of ≈40,000 materials and ≈1 million calculated properties in JARVIS-DFT, ≈500 materials and ≈110 force-fields in JARVIS-FF, and ≈25 ML models for material-property predictions in JARVIS-ML, all of which are continuously expanding. JARVIS-tools provides scripts and workflows for running and analyzing various simulations. We compare our computational data to experiments or high-fidelity computational methods wherever applicable to evaluate error/uncertainty in predictions. In addition to the existing workflows, the infrastructure can support a wide variety of other technologically important applications as part of the data-driven materials design paradigm. The JARVIS datasets and tools are publicly available at the website: https://jarvis.nist.gov .
36 MATERIALS SCIENCE↗
Materials Development and Advanced Process Simulation for Additive Manufacturing with Fiber-Reinforced Thermoplastics (Final Technical Report)
DuPont, Local Motors, and the Composites Manufacturing and Simulation Center (CMSC) at Purdue worked together to advance process simulation capabilities for Additive Manufacturing (AM) and develop printable short fiber reinforced semi-crystalline engineering thermoplastics suitable for vehicle components. DuPont provided one candidate thermoplastic material, which was evaluated against the following three criteria: 1) Printability using extrusion additive manufacturing processes. 2) Suitability for vehicle applications based on mechanical coupon screening tests. 3) Predictive capability of process simulations. Indiana Manufacturing Institute provided modeling and simulation technology and access to Purdue’s lab scale AM printer. Local Motors provided mechanical property requirements and printed demonstration prototype components using their Thermwood Large Scale Additive Manufacturing (LSAM) printer. To meet the performance and cost requirements of the automotive industry, high fiber content semi-crystalline engineering materials are required. Printing experience and property data for a 50% by weight short glass fiber reinforced material were gathered. Further, material properties required for simulating the printing process with the glass-fiber reinforced material were characterized. Knowledge was acquired with regards to the processability and performance of this thermoplastic material. Predictions of part deformation and crystallinity level were verified against experimental observations. Any significant results other than verification of simulation, e.g., novel material identified here would be impactful.
36 MATERIALS SCIENCE↗
Figures of Merit Software: Description, User's Guide, Installation Notes, Versions Description, and License Agreement
Figures of Merit (FoMs) and the FoM software provide a method for quantitatively evaluating the quality of a regolith simulant by comparing the simulant to a reference material. FoMs may be used for comparing a simulant to actual regolith material, specification by stating the value a simulant s FoMs must attain to be suitable for a given application and comparing simulants from different vendors or production runs. FoMs may even be used to compare different simulants to each other. A single FoM is conceptually an algorithm that computes a single number for quantifying the similarity or difference of a single characteristic of a simulant material and a reference material and provides a clear measure of how well a simulant and reference material match or compare. FoMs have been constructed to lie between zero and 1, with zero indicating a poor or no match and 1 indicating a perfect match. FoMs are defined for modal composition, particle size distribution, particle shape distribution, (aspect ratio and angularity), and density. This TM covers the mathematics, use, installation, and licensing for the existing FoM code in detail.
hoelzer, H. D.↗
Simulation and Modeling of Optical Properties of U, Th, Pb, and Co Nanoparticles of Interest to Nuclear Security Using Finite Element Analysis
In this work, the optical characteristics of uranium (U), lead (Pb), cobalt (Co), and thorium (Th) nanoparticles are fashioned and simulated employing the finite element analysis (FEA) approach concerning multiple particle sizes. Applying finite element analysis, it was found that the simulated absorption peaks of electronic excitations of nuclear nanoparticles are red-shifted from 365 nm to 555 nm for U; from 355 nm to 550 nm for Pb; from 415 nm to 610 nm for Co; and from 350 nm to 540 nm for Th, comparing expanding particle sizes from 60 nm to 100 nm (except for Co, which varied from 70 nm to 100 nm). The FEA-simulated optical band gap energies and far-field radiation patterns were also obtained for nuclear materials. The simulation approach in this research enables the prediction of optical properties and design of nuclear materials before manufacture for nuclear security applications.
36 MATERIALS SCIENCE↗
Lunar Simulants
Lunar simulants are terrestrial materials that mimic aspects of lunar regolith for testing of technology that would interact with lunar surface material. The goal of simulants is mission risk reduction by providing confidence, through testing with simulants, that a technology will perform as designed on the lunar surface. Lunar simulants are often used in education and outreach activities to increase public knowledge about lunar surface materials and to inspire the next generation of space explorers.
simulant↗
Influence of fuel ash on the recoverability of copper from the spent material of chemical looping combustion
Chemical looping combustion (CLC) is an advanced energy production technology that inherently separates the CO 2 generated. The oxygen needed for fuel conversion is supplied by the oxygen carrier. When using copper-based oxygen carriers, oxygen carrier attrition is a challenge to the process economics, unless the attrited copper that is mixed with fuel ash in the spent material can be recovered by, for instance, acid leaching. However, fuel ash may transform the attrited copper into certain complexes of low leachability (e.g., CuAl 2 O 4 ), hindering the copper recovery. In this study, the copper content in the spent material was first evaluated. The effects of ash composition and copper content on the occurrence mode of copper in spent material were predicted by thermodynamic modeling. Redox cycles of simulated spent materials based on various coal ashes were performed to reveal the characteristics of CuAl 2 O 4 /CuFe 2 O 4 formation. The CuO-Al 2 O 3 reaction was investigated under the temperatures and solid residence times experienced in CLC. The materials were analyzed by X-ray diffraction. The results suggest that the fuel ash with a high Al/Ca ratio may lower the recoverability of copper when the temperature is above 925 °C. The slow formation of CuFe 2 O 4 is not expected to affect the copper recovery.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Python Urban Deployment Model (PyUDM) v1.0.0
The Python Urban Deployment Model (PyUDM) is a simulation tool used to investigate networks of static radiation detectors in urban environments. PyUDM simulates traffic, stationary NaI gamma-ray detectors, and moving radioactive sources on simulated vehicles. The analyzed output of the simulations contain valuable insights into the performance of different configurations of urban radiological detector configurations such as their ability to detect sources moving through the environment. To accurately simulate radioactive material moving through urban environments, PyUDM combines Monte Carlo simulation tools, publicly available map and traffic data, and measured gamma-ray spectra from urban environments.
Rofors, Emil↗