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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A description of structured waves in shock compressed particulate composites

Dynamic compression of composite materials is of scientific interest because the mechanical mismatch between internal phases challenges continuum theories. Typical assumptions about steady wave propagation and quasi-instantaneous state changes require reexamination along with the need for time-dependent models. To that end, data and models are presented here for the shock compression of an idealized particulate composite. To serve as a generic representative of this material class, a polymer matrix was filled with tungsten particles, ranging from 1 to 50 vol. %. This creates a simple microstructure containing randomly scattered particles with an extreme impedance mismatch to the binding matrix. These materials were parallel plate impact loaded by Al flyers traveling at 1.8–5.0 km/s. Velocimetry provided records of the equilibrium state and the compression wave structure for each case with trends quantified by an empirical fit. The same quantities were also studied as a function of the wave's propagation distance. A homogenized viscoelastic model then made it possible to progress from cataloging trends to making predictions. Starting from a Mie–Gruneisen equation of state, additional time varying terms were added to capture the transient response. After calibration, accurate predictions of the steady wave structure were possible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Surrogate Model Integration with MOOSE XFEM for Creep Crack Growth

Ferritic-martensitic steels are key structural materials for advanced reactors but experience time-dependent deformation and damage under prolonged high temperature and irradiation, leading to creep-driven crack initiation and growth. High-fidelity models—crystal plasticity with irradiation mechanisms, phase-field for microstructural evolution, and continuum-damage viscoplasticity—capture the underlying physics but are too computationally intensive for broad design-space exploration and uncertainty quantification. This milestone advances a scalable alternative by integrating a microstructure-sensitive surrogate creep model into the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework and extending it to fracture via the extended finite element method (XFEM). The surrogate model, developed with collaborators at Sandia and Los Alamos National Laboratories, maps relevant microstructural descriptors to the viscoplastic response of HT9. We embed this surrogate within a coupled deformation-damage workflow in MOOSE/XFEM to simulate creep-driven crack initiation and propagation. Implementation enhancements include updates to the material interface, a plastic correction phase involving microstructure evolution, and fracture criteria to ensure numerical robustness and compatibility with the surrogate structure. Demonstrations on canonical creep benchmarks spanning uniaxial and multiaxial states show that the surrogate reproduces key trends of high-fidelity models while substantially reducing computational cost. The resulting capability bridges physics fidelity and performance, providing a practical path to a predictive, microstructure-aware assessment of creep and fracture in reactor materials.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗
DOE OSTI2025

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗
DOE OSTI2021

A novel physics-based and data-supported microstructure model for part-scale simulation of laser powder bed fusion of Ti-6Al-4V

The elasto-plastic material behavior, material strength and failure modes of metals fabricated by additive manufacturing technologies are significantly determined by the underlying process-specific microstructure evolution. In this work a novel physics-based and data-supported phenomenological microstructure model for Ti-6Al-4V is proposed that is suitable for the part-scale simulation of laser powder bed fusion processes. The model predicts spatially homogenized phase fractions of the most relevant microstructural species, namely the stable β-phase, the stable α s -phase as well as the metastable Martensite α m -phase, in a physically consistent manner. In particular, the modeled microstructure evolution, in form of diffusion-based and non-diffusional transformations, is a pure consequence of energy and mobility competitions among the different species, without the need for heuristic transformation criteria as often applied in existing models. The mathematically consistent formulation of the evolution equations in rate form renders the model suitable for the practically relevant scenario of temperature- or time-dependent diffusion coefficients, arbitrary temperature profiles, and multiple coexisting phases. Due to its physically motivated foundation, the proposed model requires only a minimal number of free parameters, which are determined in an inverse identification process considering a broad experimental data basis in form of time-temperature transformation diagrams. Subsequently, the predictive ability of the model is demonstrated by means of continuous cooling transformation diagrams, showing that experimentally observed characteristics such as critical cooling rates emerge naturally from the proposed microstructure model, instead of being enforced as heuristic transformation criteria. Eventually, the proposed model is exploited to predict the microstructure evolution for a realistic selective laser melting application scenario and for the cooling/quenching process of a Ti-6Al-4V cube of practically relevant size. Numerical results confirm experimental observations that Martensite is the dominating microstructure species in regimes of high cooling rates, e.g., due to highly localized heat sources or in near-surface domains, while a proper manipulation of the temperature field, e.g., by preheating the base-plate in selective laser melting, can suppress the formation of this metastable phase.

Inverse parameter identification↗
DOE OSTI2024

Multiscale simulation of spatially correlated microstructure via a latent space representation

When deformation gradients act on the scale of the microstructure of a part due to geometry and loading, spatial correlations and finite-size effects in simulation cells cannot be neglected. We propose a multiscale method that accounts for these effects using a variational autoencoder to encode the structure–property map of the stochastic volume elements making up the statistical description of the part. In this paradigm the autoencoder can be used to directly encode the microstructure or, alternatively, its latent space can be sampled to provide likely realizations. Furthermore, we demonstrate the method on three examples using the common additively manufactured material AlSi10Mg in: (a) a comparison with direct numerical simulation of the part microstructure, (b) a push forward of microstructural uncertainty to performance quantities of interest, and (c) a simulation of functional gradation of a part with stochastic microstructure.

Elastoplasticity↗
DOE OSTI2023

In-situ and ex-situ characterization of ion-irradiated AM materials

Additive manufacturing (AM) has attracted increasing attention in recent years as a new way of making high-quality components for nuclear reactors. While AM materials are compositionally similar to their conventionally produced counterparts, they do possess different microstructures, such as dislocation cells and chemical inhomogeneity, that can lead to different mechanical properties and performance behavior. In this study, the irradiation response of AM materials was investigated. In-situ and ex-situ ion irradiations were performed on AM316L and AM316H stainless steels (SS) at 300 and 600°C. The influence of the dislocation cell structure on the evolution of irradiation-induced dislocation loops was evident at 600ºC, but was much weaker at 300ºC. No voids were observed with the in-situ ion irradiation up to 10 dpa at both temperatures. Post-irradiation energy dispersive spectroscopy showed radiation-induced segregation (RIS) near grain boundaries and the formation of Cr-rich oxides throughout the matrix. The extent of segregation at dislocation cell walls varies with dose. Nanoindentation tests performed on the AM316L SS irradiated at 600ºC showed a complex dose dependence with softening at low doses and hardening at high doses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Mechanical Behavior of Additively Manufactured Molybdenum and Fabrication of Microtextured Composites

Refractory metals are a class of high-melting-temperature materials suitable for use in extreme environment applications. Interestingly, during additive manufacturing many pure refractory metals exhibit a switch from (001) to (111) build direction fiber preference with increasing surface energy density. Here we exploit this solidification physics to fabricate material with “mesoscale composite” engineered structures consisting of features with contrasting (001) and (111) build direction microtextures. Separately, elevated temperature tensile testing of EBM fabricated material with a randomized distribution of mixed (001)/(111)-fiber grains is shown to exhibit excellent properties. These results are utilized to build a crystal plasticity model for evaluating the local inelastic response of the composite mesoscale structures. Analysis of printed microstructures and microstructure-scale simulations indicate that both macro-scale and localized material behavior may be tailored. This strategy can be potentially used to synthesize materials with optimized performance for high-temperature applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dislocation Loops in Proton Irradiated Uranium-Nitrogen-Oxygen System

Here in this study, we investigated the dislocation loop types formed in the proton-irradiated uranium-nitrogen-oxygen (U-N-O) system, which involves uranium mononitride (UN), uranium sesquinitride (a-U2N3), and uranium dioxide (UO2) phases. The dislocation loop formation is examined using specimens irradiated at 400°C and 710°C. Based on the detailed transmission-based electron microscopy characterization with i) the morphology-based on-zone and ii) the invisibility-criterion based two-beam condition imaging techniques, only a single type of dislocation loop in each phase is found: a/2?110?, a/2?111?, or a/3?111? dislocation loops in UN, a-U2N3, and UO2 phases, respectively. Molecular statics calculations for the formation energy of perfect and faulted dislocation loops in UN phases indicate a critical loop size of ~ 6 nm, above which perfect loops are energetically favorable. This could explain the absence of faulted loops in the experimental observation of the irradiated UN phase at two temperatures. This work will enhance the understanding of irradiation induced microstructural evolution for uranium nitrides as advanced nuclear fuels for the next-generation nuclear reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Radiation-Induced Modifications in Copper Oxide Growth

Radiation-induced effects and their influence on oxidation processes were evaluated for their use as a forensic tool for special nuclear material (SNM). A beam of 10 MeV Au³⁺ ions was used to mimic the accumulation of microstructural damage from self-irradiation through the decay of radionuclides. Several copper samples were irradiated as suitable surrogate materials at 200 °C with a flux of 1x10¹² ions/cm·s to damage levels of 5, 10, and 15 displacements per atom (dpa). This corresponds to about 50, 100, and 150 years, respectively, of accumulated α-decay damage in a PuGa alloy assuming a damage rate of 0.1 dpa/year. After irradiation, all samples were exposed to an accelerated aging process induced by thermal treatment at 350 °C for 1 hour in air. This resulted in the growth of a mixed oxide layer (Cu₂O and CuO) which was characterized in detail using several complementary analytical techniques: Scanning Electron Microscopy, Raman spectroscopy, Synchrotron X-ray diffraction (transmission mode), and Grazing Incidence X-ray diffraction. The oxide layer growth of irradiated Cu at 350°C is distinctly modified as a result of the ion irradiation. Most notably, the growth of the CuO phase is suppressed with increasing radiation damage on the Cu substrate, and structural changes occurred in the Cu₂O phase. These results indicate that damage from self-irradiation over time can cause quantifiable modifications in the oxidation process of metals that could be harnessed for their use as a novel forensic tool.

36 MATERIALS SCIENCE↗
DOE OSTI2024

AOI [1] Advanced Manufacturing of Ceramic Anchors with Embedded Sensors for Process and Health Monitoring of Coal Boilers

Researchers at West Virginia University (WVU) developed methods to fabricate and test ceramic anchors with an embedded sensor technology for monitoring the health and processing conditions within pulverized coal (PC) and fluidized-bed combustion (FBC) boiler systems. The technology included the development of advanced manufacturing processes for 2D/3D printing electroceramic (conductive ceramic) sensor designs within the ceramic anchor microstructure during the manufacturing process. This advanced manufacturing process would allow for the precise control of local microstructure and composition in order to engineer layer-by-layer any protective and electrically active materials within the refractory anchor. This 3D printing technology would permit the rapid and controlled design of the refractory microstructure and embedded sensor design throughout the volume of the ceramic anchor. The work also included a method to interconnect the sensors to boiler shell through the anchor clamp, where the sensor signals will be processed by low-power electronics and transmitted wirelessly to a central processing hub. The end-goal of the program was to produce a ceramic anchor sensor system which would be ready for implementation within a coal boiler, and/or other similar refractory liner systems (such as that in the glass and metal manufacturing areas). The project objectives were to: 1) Define the chemical and microstructural stability, in addition to the electrical properties, of oxide and non-oxide ceramic composites to be embedded within the ceramic anchor compositions that may operate up to 1400ºC; 2) Develop and implement the 2D/3D printing technology to pattern and control the microstructure of the ceramic anchor and embedded sensor circuits; 3) Develop an interconnect technology which will permit easy installation of the ceramic anchors and signal collection at the boiler shell; 4) Develop low power analog electronics and wireless communication hardware to efficiently collect the sensor signal at each processing unit and transmit data to a central hub for data analysis; 5) Demonstrate the smart ceramic anchor system for temperature and liner fracture within a high-temperature processing unit, such as a boiler furnace or glass melting furnace floor/wall liner.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Resolving crystallographic geometrically necessary dislocations in three dimensions in a hexagonal close packed titanium alloy

Abstract Geometrically necessary dislocation (GND) content is measured from mm 3 -scaled Ti7Al three-dimensional (3D) microstructural data using a theory extended for hexagonal close packed crystals, which accounts for basal, prismatic and pyramidal ⟨ c + a ⟩ type dislocation content. The Ti7Al samples have been mechanically pre-strained to two different strain levels, and will then be strained along the same axis in uniaxial tension during simulation. Both inter- and intragranular GNDs across the microstructures have been characterized, with a large contribution of pyramidal ⟨ c + a ⟩ GNDs, consistent with the relative slip activity involved in pre-straining. The spatially resolved crystallographic GND distributions within the 3D microstructures are used to instantiate a microstructure model for forward modeling deformation simulations by a dislocation density hardening elasto-viscoplastic fast Fourier transform framework. Coarsening the voxel resolution during the initial microstructure construction procedure is shown to strongly impact both the magnitude and spatial distribution of the GNDs and in turn the forward deformation response of the pre-strained material. This study indicates that the voxel resolution desired when transferring from measured to model microstructures need not only be proportionally scaled with the microstructure but also sufficiently fine to capture the subgranular orientation gradients that may already be present in the material.

Materials Science↗
DOE OSTI2023

Analysis of Deformation and Fracture Mechanisms in the Harvested Low-Dose Baffle Former Bolt via Advanced Mechanical Tests

This report details the production of tensile specimens from in-service irradiated baffle former bolts (BFBs) and presents the results of a pilot in-situ SEM/EBSD test conducted at Oak Ridge National Laboratory’s Low Activation Materials Development and Analysis (LAMDA) facility. The SEM/EDS results confirmed that the material is AISI 316L steel, not AISI 347, and that no Nb addition was detected in several analyzed locations. EBSD analysis of the microstructure revealed in-grain misorientation gradients indicative of cold work, likely caused by material processing, and no retained ferrite was identified. During straining, dislocation channel formation was the primary deformation mechanism, with twinning also observed in favorably oriented grains at local strains as small as ~1.5%. No strain-induced phase instability was observed, likely due to the fact that the Ni and Cr content reached the upper limits for the 316L steel specification. Multiple microfracture events were observed during the tensile test. Fine strain-induced pores formed at the channel-grain boundary intersection points, while coarser microcracks were associated with non-metallic inclusions. Data analysis is ongoing, and additional tests are planned in the near future to provide more statistics and details.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Under the microscope: Reduced activation ferritic martensitic steel Eurofer-97 following ion-Irradiation and high-temperature high-pressure water exposure

Here, this study is designed to characterise the microstructural behaviour of Eurofer-97 steel under ion irradiation and subsequent exposure to high-temperature high-pressure (HTHP) water. Eurofer-97, a ferritic-martensitic steel, has been developed to withstand the conditions of fusion reactors in the locations in contact with coolant with an elevated level of neutron flux, such as the breeder-wall blanket. The material has been studied after self-ion irradiation (using Fe ions) simulating the microstructural effects of neutron irradiation limited to the subsurface layer. The corrosion properties of the Eurofer-97 steel were studied by exposure to HTHP water up to 331 °C. Advanced microstructural characterisation using scanning, transmission electron and focused ion beam microscopy was performed on the as-received microstructure and after ion irradiation. This was then characterised after exposure for 240 h in high-temperature water. Eurofer-97 had a dense, columnar Cr-rich inner oxide, followed by a Fe-rich outer oxide layer. In the irradiated condition the grain structure and oxide itself was less ordered. No appreciable difference in oxide thickness was identified between the irradiated and unirradiated specimens after this short exposure time.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Irradiation-assisted cracking of SA508-304L weldments with 308L groove filler and 309L butter in hot water immersion constant rate extension tests

Low alloy SA508 bainitic steel is often welded to 300 series austenitic stainless steel in nuclear power plants. These dissimilar metal weldments use 309L butter applied to the low alloy steel and 308L groove filler material to join the 309L to austenite. High alloy steels (such as the 308L and 309L material used here) have been identified as having greater susceptibility to irradiation-assisted stress corrosion cracking (IASCC). Evidence is presented here of cracking under tensile loads in 309L weldment butter in LWR hydrothermal conditions that correlates irradiation induced changes at δ ferrite–γ austenite phase boundaries and γ–γ grain boundaries; specifically intergranular Cr 23 C 6 precipitates. Cracking is not observed in irradiated 308L groove filler under the same conditions. Both the 309L butter and 308L filler material have a duplex or mixed δ–γ phase microstructure due to solidification during the welding procedure. We have performed constant extension rate autoclave immersion tests in BWR normal water chemistry hot water (288 °C, 10 MPa, 2000 wt. ppb dissolved oxygen, <100 nS/cm conductivity, neutral pH) of proton irradiated (2 MeV, approximately 3 displacements per atom at a depth of 10 μm) tensile specimens. Proton irradiation to the dpa levels used here induced Cr 23 C 6 carbide precipitation at γ–γ grain boundaries and δ–γ phase boundaries in the 309L butter but not the 308L filler. Cracking was observed in the proton-irradiated volume of 309L at these interfaces in the vicinity of the Cr 23 C 6 precipitates. We hypothesis the SA508 is the source of carbon in the 309L butter. Cr depletion at γ–γ grain boundaries was also observed and may also be a root cause of cracking. Furthermore, the 309L butter is under significant tensile residual stress in the weldment that adds to applied tensile loads and this too may be a contributing factor.

309L weld butter↗
DOE OSTI2020

Characterization of paste microstructure for durability properties of concrete

In this study, paste samples from different cementitious systems were characterized by using X-Ray Micro Computed Tomography (µ-CT) and Fluorescence Microscopy techniques. Quantitative and qualitative aspects of defects from paste samples were investigated to develop indicators of durability related properties of corresponding concrete samples. In the first phase of this study, hour glass shaped 3D printed molds were used to investigate five cementitious combinations consisting of three cement types (Coarse Ground portland cement, Type IL Portland Limestone Cement and Type I/II ordinary portland cement) and fly ash as a supplementary cementitious material. In the second phase, metal molds were used to compare the results of Coarse Ground portland cement with Type I ordinary portland cement, 5% of which was replaced with colloidal nanosilica. Potential correlations between paste and concrete have been presented. This work was supported by US Department of Energy and North Dakota Department of Commerce.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Role of aggregates and microstructure of mixed-ionic–electronic-conductors on charge transport in electrochemical transistors

Synthetic efforts have delivered a library of organic mixed ionic–electronic conductors (OMIECs) with high performance in electrochemical transistors. The most promising materials are redox-active conjugated polymers with hydrophilic side chains that reach high transconductances in aqueous electrolytes due to volumetric electrochemical charging. Current approaches to improve transconductance and device stability focus mostly on materials chemistry including backbone and side chain design. However, other parameters such as the initial microstructure and microstructural rearrangements during electrochemical charging are equally important and are influenced by backbone and side chain chemistry. In this study, we employ a polymer system to investigate the fundamental electrochemical charging mechanisms of OMIECs. We couple in situ electronic charge transport measurements and spectroelectrochemistry with ex situ X-ray scattering electrochemical charging experiments and find that polymer chains planarize during electrochemical charging. Our work shows that the most effective conductivity modulation is related to electrochemical accessibility of well-ordered, interconnected aggregates that host high mobility electronic charge carriers. Electrochemical stress cycling induces microstructural changes, but we find that these aggregates can largely maintain order, providing insights on the structural stability and reversibility of electrochemical charging in these systems. Finally, this work shows the importance of material design for creating OMIECs that undergo structural rearrangements to accommodate ions and electronic charge carriers during which percolating networks are formed for efficient electronic charge transport.

36 MATERIALS SCIENCE↗