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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

CASTING DEFECT MODELING IN AN INTEGRATED COMPUTATIONAL MATERIALS ENGINEERING APPROACH

To accelerate the introduction of new cast alloys, the simultaneous modeling and simulation of multiphysical phenomena needs to be considered in the design and optimization of mechanical properties of cast components. The required models related to casting defects, such as microporosity and hot tears, are reviewed. Three aluminum alloys are considered A356, 356 and 319. The data on calculated solidification shrinkage is presented and its effects on microporosity levels discussed. Examples are given for predicting microporosity defects and microstructure distribution for a plate casting. Models to predict fatigue life and yield stress are briefly highlighted here for the sake of completion and to illustrate how the length scales of the microstructure features as well as porosity defects are taken into account for modeling the mechanical properties. Thus, the data on casting defects, including microstructure features, is crucial for evaluating the final performance-related properties of the component. ACKNOWLEDGEMENTS This work was performed under a Cooperative Research and Development Agreement (CRADA) with the Nemak Inc., and Chrysler Co. for the project "High Performance Cast Aluminum Alloys for Next Generation Passenger Vehicle Engines. The author would also like to thank Amit Shyam for reviewing the paper and Andres Rodriguez of Nemak Inc. Research sponsored by the U. S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, as part of the Propulsion Materials Program under contract DE-AC05-00OR22725 with UT-Battelle, LLC. Part of this research was conducted through the Oak Ridge National Laboratory's High Temperature Materials Laboratory User Program, which is sponsored by the U. S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Program.

Sabau, Adrian S↗
DOE OSTI2018

Linking process and structure in the friction stir scribe joining of dissimilar materials: A computational approach with experimental support

We present that friction stir welding (FSW) is a popular technique to join dissimilar materials in numerous applications. The solid state nature of the process enables joining materials with strikingly different physical properties. For welds in lap configuration, an enhancement to this technology is made by introducing a short, hard insert, referred to as a cutting-scribe, at the bottom of the tool pin. The cutting-scribe induces deformation in the bottom plate which leads to the formation of mechanical interlocks or hook like structures at the interface of two materials. A thermo-mechanical computational model employing a coupled Eulerian-Lagrangian approach is developed to quantitatively capture the morphology of these interlocks during the FSW process. Simulations using this model are validated by experimental observations. In conclusion, the identified interface morphology coupled with the predicted temperature field from this process–structure model can be used to estimate the post-weld microstructure and joint strength.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Green’s function fast multipole method for computation of micromechanical fields in heterogeneous materials

Computation of micromechanical fields in heterogeneous materials is usually performed using either the finite element method or the Green’s function method based on FFTs. The finite element method allows for accurate discretization and for non-periodic boundary conditions but is computationally expensive. On the other hand, the FFT-based method is computationally efficient but requires discretization on a regular grid of hexahedral voxels. In this paper, a Green’s function method allowing for accurate discretization using tetrahedral elements and for non-periodic boundary conditions is proposed. The convolution is computed using the fast multipole method, which provides good accuracy even for low-order expansion due to the fast decay of interactions between elements. The proposed Green’s function fast multipole method is verified by comparison with analytical and FFT-based solutions. Furthermore, the computational time is analyzed and compared to the FFT-based method for non-periodic convolution. Finally, effective properties of an elastic polycrystalline microstructure containing thin intergranular cracks are computed and analyzed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Many Body Methods from Chemistry to Physics: Novel Computational Techniques for Materials-Specific Modelling: A Computational Materials Science and Chemistry Network

Understanding the behavior of interacting electrons in molecules and solids so that one can predict new superconductors, catalysts, light harvesters, energy and battery materials and optimize existing ones is the ``quantum many-body problem’’. This is one of the scientific grand challenges of the 21 st century. A complete solution to the problem has been proven to be exponentially hard, meaning that straightforward numerical approaches fail. New insights and new methods are needed to provide accurate yet feasible approximate solutions. This CMSCN project brought together chemists and physicists to combine insights from the two disciplines to develop innovative new approaches. Outcomes included the Density Matrix Embedding method, a new, computationally inexpensive and extremely accurate approach that may enable first principles treatment of superconducting and magnetic properties of strongly correlated materials, new techniques for existing methods including an Adaptively Truncated Hilbert Space approach that will vastly expand the capabilities of the dynamical mean field method, a self-energy embedding theory and a new memory-function based approach to the calculations of the behavior of driven systems. The methods developed under this project are now being applied to improve our understanding of superconductivity, to calculate novel topological properties of materials and to characterize and improve the properties of nanoscale devices.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges

The production of metal parts via laser powder bed fusion additive manufacturing is growing exponentially. However, the transition of this technology from production of prototypes to production of critical parts is hindered by a lack of confidence in the quality of the part. Confidence can be established via a fundamental understanding of the physics of the process. It is generally accepted that this understanding will be increasingly achieved through modeling and simulation. However, there are significant physics, computational, and materials challenges stemming from the broad range of length and time scales and temperature ranges associated with the process. In this study, we review the current state of the art and describe the challenges that need to be met to achieve the desired fundamental understanding of the physics of the process.

36 MATERIALS SCIENCE↗
NASA NTRS1996

Computer-Aided Process Model For Carbon/Phenolic Materials

Computer program implements thermochemical model of processing of carbon-fiber/phenolic-matrix composite materials into molded parts of various sizes and shapes. Directed toward improving fabrication of rocket-engine-nozzle parts, also used to optimize fabrication of other structural components, and material-property parameters changed to apply to other materials. Reduces costs by reducing amount of laboratory trial and error needed to optimize curing processes and to predict properties of cured parts.

Letson, Mischell A.↗
DOE OSTI2021

Materials challenges and opportunities for quantum computing hardware

Combatting noise on the platform The potential of quantum computers to solve problems that are intractable for classical computers has driven advances in hardware fabrication. In practice, the main challenge in realizing quantum computers is that general, many-particle quantum states are highly sensitive to noise, which inevitably causes errors in quantum algorithms. Some noise sources are inherent to the current materials platforms. de Leon et al. review some of the materials challenges for five platforms for quantum computers and propose directions for their solution. Science , this issue p. eabb2823

Science & Technology - Other Topics↗
DOE OSTI2015

Materials Data on Fe3(O2F)2 (SG:1) by Materials Project

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

36 MATERIALS SCIENCE↗