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Characterization of microstructure and property evolution in advanced cladding and duct: Materials exposed to high dose and elevated temperature
Designing materials for performance in high-radiation fields can be accelerated through a carefully chosen combination of advanced multiscale modeling paired with appropriate experimental validation. Here, the studies reported in this work, the combined efforts of six universities working together as the Consortium on Cladding and Structural Materials, use that approach to focus on improving the scientific basis for the response of ferritic–martensitic steels to irradiation. A combination of modern modeling techniques with controlled experimentation has specifically focused on improving the understanding of radiation-induced segregation, precipitate formation and growth under radiation, the stability of oxide nanoclusters, and the development of dislocation networks under radiation. Experimental studies use both model and commercial alloys, irradiated with both ion beams and neutrons. Lastly, transmission electron microscopy and atom probe are combined with both first-principles and rate theory approaches to advance the understanding of ferritic–martensitic steels.
Dissipation of radiation energy in concentrated solid-solution alloys: Unique defect properties and microstructural evolution
The effort to develop metallic alloys with increased structural strength and improved radiation performance has focused on the incorporation of either solute elements or microstructural inhomogeneities to mitigate damage. The recent discovery and development of single-phase concentrated solid-solution alloys (SP-CSAs) has prompted fundamental questions that challenge established theories and models currently applicable to conventional alloys. Here, the current understanding of electronic and atomic effects, defect evolution, and microstructure progression suggests that radiation energy dissipates in SP-CSAs at different interaction strengths via energy carriers (electrons, phonons, and magnons). Modification of electronic- and atomic-level heterogeneities and tailoring of atomic transport processes can be realized through tuning of the chemical complexity of SP-CSAs by the selection of appropriate elements and their concentrations. Fundamental understanding of controlling energy dissipation via site-to-site chemical complexity reveals new design principles for predictive discovery and guided synthesis of new alloys with targeted functionalities, including radiation tolerance.
Mechanical properties and microstructure evaluation of powder bed fused inconel 625 nickel alloy
The objectives of this report were to optimize and fabricate full density Inconel 625 samples using direct metal laser fusion, an additive manufacturing process; and to compare and evaluate precipitation and solid solution strengthening of Inconel 625 produced by PBF to conventional processed material.
U-50Zr Microstructure and Property Assessment for LWR Applications
This project provides an initial assessment and research recommendations of U-50 wt.%Zr (U-50Zr) for its use as a light water reactor (LWR) fuel. This work based on the outcome of a recently funded exercise on the failure mode effects and analysis (FMEA) and the phenomena identification and ranking table (PIRT) to investigate high level nuclear fuel qualification metrics as derived by the United States Nuclear Regulatory Commission.
Processing, Microstructure, and Properties of AM-Alloy ABD®900-AM
In this work the processability and properties of AM alloy ABD900 processed via laser and electron beam powder bed fusion are investigated. Both AM modalities are suitable for processing and the material exhibits good high temperature creep properties. This phase I CRADA demonstrates that ABD900 is a suitable allow for potential blade repair work using powder bed fusional AM technology.
Effect of thermal aging on mechanical properties and microstructural development of Hastelloy C and C276.
Abstract not provided.
Thermomechanical Properties of Microstructurally Tuned Phase-Separated Epoxies
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Microstructure & Mechanical Properties of Scaled Thermally Aged LPBF 316H SS Builds
As part of the US Department of Energy’s Advanced Materials and Manufacturing Technologies program’s mission to accelerate qualification of advanced manufacturing pathways for nuclear applications, laser powder bed fusion (LPBF) 316H stainless steel (SS) has been selected as a model system to develop a rapid code case framework. This effort directly addresses the grand challenges of (1)expanding the limited portfolio of materials currently codified for elevated-temperature nuclear structural service under Section III, Division 5of the American Society of Mechanical Engineers’ Boiler and Pressure Vessel Code; and (2) significantly reducing qualification timelines that traditionally exceed a decade. The strategic importance of LPBF 316H lies in its immediate industrial relevance, existing data foundation from wrought 316H, and alignment with ongoing code case development for LPBF 316L.Prior work revealed accelerated precipitation of deleterious secondary phases and reduced creep ductility in as-printed LPBF 316H. Building on that prior research, FY2025activities focused on establishing an understanding of the key failure mechanisms of crept 316H specimens to aid in code case development and on evaluating stress relief (SR) parameters on the high-temperature performance and thermal aging-induced degradation of tensile and fracture behavior in LPBF316H.
Cold Spray Additive Manufacturing: Spray Angles, Microstructure, and Properties
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Microstructure-Creep Property Modeling for LPBF 316H SS
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Tailoring microstructure and properties of B4C films for next-generation fusion targets
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Predicting Mechanical Properties from Microstructure Images in Fiber-Reinforced Polymers Using Convolutional Neural Networks
Evaluating the mechanical response of fiber-reinforced composites can be extremely time-consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input–output pairs and have exhibited success in composite research. This paper explores a fully convolutional neural network modified from StressNet, which was originally used for linear elastic materials, and extended here for a non-linear finite element (FE) simulation to predict the stress field in 2D slices of segmented tomography images of a fiber-reinforced polymer specimen. The network was trained and evaluated on data generated from the FE simulations of the exact microstructure. The testing results show that the trained network accurately captures the characteristics of the stress distribution, especially on fibers, solely from the segmented microstructure images. The trained model can make predictions within seconds in a single forward pass on an ordinary laptop, given the input microstructure, compared to 92.5 h to run the full FE simulation on a high-performance computing cluster. These results show promise in using ML techniques to conduct fast structural analysis for fiber-reinforced composites and suggest a corollary that the trained model can be used to identify the location of potential damage sites in fiber-reinforced polymers.
Predicting Microstructure and Properties of Laser Engineered Materials.
Abstract not provided.
Exploring Microstructure - Mechanical Property Relationship using Statistical Data Analysis and Multiscale Coupling.
Abstract not provided.