Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Microstructural evolution”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Characterization of the Fe-Co-1.5V soft ferromagnetic alloy processed by Laser Engineered Net Shaping (LENS)

Processing of the low workability Fe-Co-1.5V (Hiperco® equivalent) alloy is demonstrated using the Laser Engineered Net Shaping (LENS) metals additive manufacturing technique. As an innovative and highly localized solidification process, LENS is shown to overcome workability issues that arise during conventional thermomechanical processing, enabling the production of bulk, near net-shape forms of the Fe-Co alloy. Bulk LENS structures appeared to be ductile with no significant macroscopic defects. Atomic ordering was evaluated and significantly reduced in as-built LENS specimens relative to an annealed condition, tailorable through selection of processing parameters. Fine equiaxed grain structures were observed in as-built specimens following solidification, which then evolved toward a highly heterogeneous bimodal grain structure after annealing. The microstructure evolution in Fe-Co is discussed in the context of classical solidification theory and selective grain boundary pinning processes. In conclusion, magnetic properties were also assessed and shown to fall within the extremes of conventionally processed Hiperco® alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Review of Computer-Aided Manufacturing (CAM) strategies for hybrid directed energy deposition

Hybrid additive manufacturing intertwines both additive and subtractive manufacturing layer by layer to digitally fabricate parts with complex geometries, improved surface finish and tight dimensional accuracies, the sum of which is difficult to obtain with any single process. Computer-Aided Manufacturing (CAM) software is required to orchestrate the machine toolpathing for both the deposition as well as the machining processes and is crucial for the successful fabrication of high quality structures. Additionally, CAM requires substantial operator input to account for challenging aspects of each fabricated structure. For example, deciding at which layer of deposition will the machining process continue to maintain access to complex cavities for finishing - internal features that would otherwise be unfinishable due to reach limitations or obstructions. Moreover, of the many commercially-available hybrid systems, each has a unique kinematic environment which can benefit from specific optimization of toolpath planning and substantial research has directly correlated toolpathing with the microstructure evolution, mechanical properties, porosity and residual stress state of the final fabricated part. This review explores the available strategies for CAM in the context of hybrid direct energy deposition, discusses the advantages and disadvantages of each and considers future CAM trends for this transformational digital manufacturing technology.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Improving fatigue performance of additively manufactured Ti-6Al-4V using sulfur-based self-terminating etching processes

The adoption of Additively Manufactured (AM) Ti-6Al-4V (Ti64) is continually increasing in the industry due to its benefits over the conventional manufacturing techniques. However, AM Ti64 parts are prone to poor surface finish, which significantly affects their fatigue performance. Therefore, AM Ti64 parts need post-processing to enhance surface finish and fatigue performance. Prior work with a sulfur-based self-terminating etching process for AM Ti64 demonstrated support removal and surface roughness reduction. To further this work, this manuscript details the impact of this sulfur-based post-processing technique on the mechanical properties and the fatigue life of AM Ti64 by characterizing the surface roughness, microstructural evolution, and fracture surfaces. Finally, this post-processing technique decreased the surface roughness parameter - S v by 55 % from 84 ± 11 µm to 38 ± 19 µm and increased the average fatigue life by 340 % from about 7000 cycles to 30,000 cycles.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Deformation behavior and phase transformation of nanotwinned Al/Ti multilayers

We report nanotwinned Al/Ti multilayers have exhibited size-dependent microstructure evolution and high strength. However, their deformation mechanisms are less well understood. In this work, we investigated the deformation mechanisms of nanotwinned Al/Ti multilayers with FCC/HCP layer interfaces by using in situ micropillar compression tests. Nanotwinned Al/Ti multilayers exhibit compressive strength up to 2.4 GPa and good work hardening capability. Post-compression TEM analyses reveal high-density stacking faults and the HCP-to-FCC phase transformations in Ti. Molecular dynamics simulations elucidate the mechanisms of deformation induced phase transformation in Ti and the influence of collective movement of partial dislocations on the deformability of Al/Ti multilayers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Properties of Nb3Sn films fabricated by magnetron sputtering from a single target

Superconducting Nb3Sn films were fabricated on sapphire and fine grain Nb substrates by magnetron sputtering from a single stoichiometric Nb3Sn target. The structural, morphological and superconducting properties of the films annealed for 24 h at temperatures of 800-1000 {\deg}C were investigated. The effect of the annealing time at 1000 {\deg}C was examined for 1, 12, and 24 h. The film properties were characterized by X-ray diffraction, scanning electron microscopy, atomic force microscopy, energy dispersive X-ray spectroscopy, and Raman spectroscopy. The DC superconducting properties of the films were characterized by a four-point probe measurement down to cryogenic temperatures. The RF surface resistance of films was measured over a temperature range of 6-23 K using a 7.4 GHz sapphire-loaded Nb cavity. As-deposited Nb3Sn films on sapphire had a superconducting critical temperature of 17.21 K, which improved to 17.83 K when the film was annealed at 800 {\deg}C for 24 h. For the films annealed at 1000 {\deg}C, the surface Sn content was reduced to ~11.3 % for an annealing time of 12 h and to ~4.1 % for an annealing time of 24 h. The Raman spectra of the films confirmed the microstructural evolution after annealing. The RF superconducting critical temperature of the as-deposited Nb3Sn films on Nb was 16.02 K, which increased to 17.44 K when the film was annealed at 800 {\deg}C for 24 h.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Integral boundary conditions in phase field models

Modeling the chemical, electric and thermal transport as well as phase transitions and the accompanying mesoscale microstructure evolution within a material in an electronic device setting involves the solution of partial differential equations often with integral boundary conditions. Employing the familiar Poisson equation describing the electric potential evolution in a material exhibiting insulator to metal transitions, we exploit a special property of such an integral boundary condition, and we properly formulate the variational problem and establish its well-posedness. Next, we compare our method with the commonly-used Lagrange multiplier method that can also handle such boundary conditions. Numerical experiments demonstrate that our new method achieves optimal convergence rate in contrast to the conventional Lagrange multiplier method. Furthermore, the linear system derived from our method is symmetric positive definite, and can be efficiently solved by Conjugate Gradient method with algebraic multigrid preconditioning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Phase field benchmark problems for dendritic growth and linear elasticity

We present the second set of benchmark problems for phase field models that are being jointly developed by the Center for Hierarchical Materials Design (CHiMaD) and the National Institute of Standards and Technology (NIST) along with input from other members in the phase field community. As the integrated computational materials engineering (ICME) approach to materials design has gained traction, there is an increasing need for quantitative phase field results. New algorithms and numerical implementations increase computational capabilities, necessitating standard problems to evaluate their impact on simulated microstructure evolution as well as their computational performance. We propose one benchmark problem for solidifiication and dendritic growth in a single-component system, and one problem for linear elasticity via the shape evolution of an elastically constrained precipitate. We demonstrate the utility and sensitivity of the benchmark problems by comparing the results of 1) dendritic growth simulations performed with different time integrators and 2) elastically constrained precipitate simulations with different precipitate sizes, initial conditions, and elastic moduli. As a result, these numerical benchmark problems will provide a consistent basis for evaluating different algorithms, both existing and those to be developed in the future, for accuracy and computational efficiency when applied to simulate physics often incorporated in phase field models.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Migration energy barriers and diffusion anisotropy of point defects on tungsten surfaces

We report tungsten is one of the most promising candidates for plasma-facing materials in future fusion devices, owing to its high performance under extreme irradiation conditions. However, irradiation-induced surface morphology varies significantly, depending on the irradiation type, fluence, and flux. Therefore, it is critical to examine the dynamics of point defects on tungsten (W) surfaces to understand how irradiation affects surface morphology. In this study, we employ the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) method to search for potential migration paths of point defects on W (1 0 0), (1 1 0) and (1 1 1) surfaces. The first-principles calculations are then used to accurately determine the migration energy barriers. The obtained paths and barriers are incorporated into a kinetic Monte Carlo (KMC) model to determine trajectories and diffusivities, which are described by diffusion tensors to demonstrate their anisotropic features. Multiple diffusion mechanisms have been identified on different surfaces, with various anisotropy factors. Particularly, point defects on the W (1 1 0) surface have the highest diffusivities, with anisotropy factors independent of temperatures. In comparison, the anisotropy of the W (1 0 0) surface decreases as temperature increases, while the W (1 1 1) surface is isotropic for point defects. This study provides insights into defect transport properties on different surfaces, which are essential for understanding the early stages of irradiation-induced microstructural evolutions and surface morphology of tungsten.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A finite element formulation for deformation twinning induced strain localization in polycrystal magnesium alloys

Deformation twinning induces shear strain localization in hexagonal close-packed crystals and is critical for the material’s ductility and failure. Cracks often occur at twin-twin or twin-grain boundary intersections and propagate along twin bands. However, most crystal plasticity models for deformation twinning are based on a “pseudo-slip” approach and do not capture the localized deformation associated with the formation of each discrete twin band. The few exceptions are discrete twin models that involve very complex numerical algorithms and are often compromised in accuracy due to the numerical convergence. These factors make the discrete twin models hard to adopt. This paper proposes a modification to the conventional finite element weak form, to fully incorporate a twin-induced heterogeneous deformation that does not depend on the “pseudo-slip” assumption. The model starts by splitting the deformation gradient into elastic-slip-twinning components. The twin-induced deformation gradient component is computed separately by solving a microstructural evolution problem and then implemented into finite element weak form by constructing a global “twin-force” vector. The constitutive update (e.g., in the user-defined material subroutine, or UMAT, for ABAQUS) therefore avoids dealing with the twinning and recovers to the form of a regular slip-based crystal plasticity model. The results presented here indicate that the twin-induced strain localization and the associated stress-reversal phenomena near the twin band were naturally captured in the model, which was validated against an in-situ synchrotron X-ray micro-diffraction experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The impact of anisotropic thermal expansion on the isothermal annealing of polycrystalline α -uranium

Although grain growth impacts microstructural evolution in a wide variety of materials systems, the effect of anisotropic thermal expansion on grain boundary mobility and texture evolution has not been widely studied. Anisotropic thermal expansion occurs in multiple non-cubic metals, and the thermomechanical processing behavior of these materials can be better understood with further study into the impact of thermal expansion on grain boundary mobility and texture evolution. In this work, we develop a mesoscale phase field model of grain growth that includes the effect of anisotropic thermal expansion, which is applied to study polycrystalline α-uranium, a highly anisotropic metal. Three-dimensional simulations on polycrystalline a-uranium with and without thermal expansion eigenstrains are performed to study the grain boundary mobility and texture evolution as a function of temperature. A strain-free temperature of 933 K is selected, and the system is studied at within the range of 873 – 933 K at intervals of ten degrees, resulting in increasing thermal eigenstrain with decreasing temperature. We also estimate a grain boundary mobility prefactor and activation energy based on existing experimental data of isothermal annealing of α-uranium. The grain boundary mobility is found to display significant deviation from Arrhenius behavior with the inclusion of thermal expansion eigenstrain as the amount of thermal eigenstrain (and thus elastic strain energy within the system) increases. This result explains an experimentally observed grain boundary mobility deviation from Arrhenius behavior. Furthermore, the texture evolution is affected, such that the grain orientations become less random with increasing thermal eigenstrain, which could explain experimentally observed texture behavior. These results indicate that the effect of thermal expansion should be considered when predicting the thermomechanical processing behavior of α-uranium and other materials with anisotropic thermal expansion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Massively parallel phase-field simulations targeting exascale

The interface thickness in the phase-field (PF) method limits its simulation scales. Consequently, large-scale PF simulations become prohibitively expensive for resolving the extremely fine microstructures that typically form during rapid solidification processing. This challenge is significant in predicting microstructure evolution in metal additive manufacturing and has been identified by the United States Department of Energy’s Exascale Computing Project. Here, to address this, we develop a multi-GPU and MPI-based massively parallel simulation code, utilizing state-of-the-art algorithms, software, and libraries, for large-scale three-dimensional (3D) PF simulations. We report the first GPU-parallel PF simulations on Frontier (currently the second TOP500 exascale cluster) and Summit machines, taking dendritic growth as an example problem. We evaluate the parallel performance of our implementation using scaling studies with more than 24 000 GPUs (among the largest known computations to date) and the acceleration performance using large-scale simulations of dendritic growth in 3D. Finally, massively parallel GPUs in these supercomputers enabled the first coupled multiscale simulations of laser melting and subsequent dendritic solidification on the scale of a full melt-pool, demonstrating the feasibility of performing PF simulations with a point total over 2 billion grid points within an acceptable time.

Exascale↗
DOE OSTI2025

Development of Predictive Model for Accurate Rupture Time from Multi-Axial Creep in Alloy 709 with Physics-Based Simulations

A physics-based model is developed to predict multiaxial creep behavior in Alloy 709 (A709), an advanced austenitic stainless steel intended for high-temperature applications such as Sodium Fast Reactors (SFRs). Compared to conventional stainless steels like 316H, A709 offers superior high-temperature performance; however, comprehensive data on its multiaxial creep response remain limited. To address this gap, a crystal plasticity finite element (CPFE) framework is used to simulate the deformation and failure mechanisms of A709 under multiaxial loading conditions. The model incorporates an extended Hu-Cocks dislocation creep formulation that accounts for precipitation effects, along with the Sham–Needleman model to capture grain boundary cavitation-driven failure. These advanced constitutive models enable a detailed understanding of the interplay between microstructural evolution and macroscopic creep response. Furthermore, the study evaluates the predictive accuracy of various effective stress measures in estimating creep rupture life, leveraging simulated multiaxial creep data. The findings provide critical insights into the applicability of different stress measures for engineering design and life prediction of A709 components operating under complex loading conditions. This work contributes to improving the reliability of high-temperature structural components by advancing predictive modeling capabilities for advanced austenitic steels.

Alloy 709↗
DOE OSTI2024

Supersonic hot jet ablative testing and analysis of boron nitride nanotube hybrid composites

Boron nitride nanotubes (BNNTs) are high-strength, high-modulus nanotubes with high thermal and oxidative stabilities. Two hybrid composites were prepared with satin weave carbon fiber (CF) and resole-type phenolic resin: one with surface layers of BNNTs and one with alternating interlayers of BNNTs. The samples were subjected to hot jet tests that simulate realistic high-pressure-temperature conditions to understand the behavior of BNNTs under high-pressure erosion. Adding BNNTs to CF/phenolic laminates enhanced the ablation resistance by reinforcing the char material and mitigated localized thermal damage. Hybrid laminates exhibited up to 14% lower weight loss, 55% increase in flexural modulus, higher thermal diffusivity, and improved char yield and microstructure compared to CF/phenolic samples. The surface layer hybrid had many surviving nanotubes reinforcing the char and crystalline oxide structures that could mitigate further oxygen diffusion. Further, various characterization methods were used to deduce possible mechanisms and their products, indicating that BNNTs could serve as growth templates for direct crystalline boron oxide formation. Overall, hybrid BNNT/CF/phenolic laminates displayed better ablation resistance and favorable microstructure evolution under high-pressure conditions.

42 ENGINEERING↗
DOE OSTI2019

Multi-scale observations of structure and chemical composition changes of portland cement systems during hydration

There is little agreement about the mechanisms and few direct observations of the transition of cement paste from a slurry to a solid. This paper uses four different imaging techniques at multiple length scales (from 15.6 nm to 1 μm) to follow the three-dimensional microstructural evolution of portland cement, and monoclinic tricalcium silicate (mC 3 S) paste over the first 16 h of hydration. Measurements of over 60,000 particles captured every 10 min were made at the micron scale. Nanoscale examinations of the structure and chemical composition are used to support this work. The results show that hydration products with an average Ca/Si > 3 form on and near the surface of the hydrating particles prior to the acceleration period that appears to control the reaction rate. These hydration products appear to change in chemical composition as more rapid dissolution of C 3 S and formation of hydration products occur during the acceleration period. The findings are used to provide insights into the origin of the induction and acceleration periods during hydration.

36 MATERIALS SCIENCE↗
DOE OSTI2019

High temperature oxidation of Ni alloys in CO 2 containing impurities

Next-generation power systems need structural alloys resistant to high-temperature oxidation in CO 2 containing combustion impurities. In this report we evaluate the oxidation performance of several commercial Ni alloys exposed to 95%CO 2 -4%H 2 O-1%O 2 , with/without 0.1% SO 2 , at 750°C and 1 atm. All alloys formed protective chromia layers and showed no signs of carburization or sulfidation, and minimal chromia volatilization. The microstructural evolution of the alloy surface, secondary oxidants, and minor alloy additions all played a part in promoting protective chromia formation/growth. The results show that Ni alloys are promising candidates for high-temperature portions of next-generation CO 2 -based power systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Using lifetime of point defects for dislocation bias in bcc Fe

The interaction between dislocations and point defects is key to deformation processes and microstructural evolution of structural materials. In this work, we compute the lifetime of point defects to describe their interaction with dislocations. This approach can accurately account for the effects of the dislocation core and anisotropic defect dynamics to accumulatively determine the capture efficiency, sink strength, and dislocation bias at different temperatures and dislocation densities. Particularly, the absorption of point defects by straight screw and edge dislocations in a model bcc iron system is studied. The maximum swelling rates based on the obtained bias factors are in close agreement with a variety of experimental measurements, including both neutron and ion-irradiation data, especially when considering the survival fraction for point defects from displacement cascades. Further, this approach applies to many other processes and sinks, such as dislocation loops and interfaces, providing a powerful means to develop fundamental insights critical for improving radiation resistance and mechanical properties of structural materials through controlling defect interaction and evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗