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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Design and Development of a Custom Laser Powder Bed Fusion System

Additive manufacturing (AM) has gained great momentum both in industrial and research applications. Due to the ability to create custom and complex parts directly from a computer-aided design (CAD) file, AM is becoming a more reliable and efficient means to fabricate components. While being implemented throughout the aerospace, medical, automotive, and energy industries, the development of metal AM is still ongoing and presents many unique scientific challenges. For example, in laser powder bed fusion (PBF), intense localized heating of metal powder followed by rapid cooling leads to residual stresses and unique microstructures within a build. This may lead to cracking and a decrease in mechanical performance. In-situ diagnostics enable the laser-material interaction to be monitored as it occurs in order to optimize process parameters, and can be leveraged to develop tailored materials with specific microstructures that are more conducive for the complex thermal patterns encountered during laser PBF. Unfortunately, most commercial laser PBF machines are not suitable for research applications due to their large size, lack of diagnostics, and black box operation. A smaller system is better suited for using smaller quantities of powder to develop new tailored materials for AM, and a custom, modular design permits greater flexibility for incorporating in-situ diagnostics. Therefore, this project consisted of the design and construction of a custom, small scale, modular PBF system.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Tungsten Alloy Laser Track Cracking Analysis

Tungsten exhibits many favorable properties such as a high melting point and high density. However, the hard and brittle nature of the material makes it difficult to work and machine. Tungsten can be alloyed with other elements to lower the material’s ductile-to-brittle transition temperature, thereby making it more ductile and workable at room temperature. While helpful for conventional manufacturing methods, the alloy poses a problem for additive manufacturing (AM) applications. The lower melting and vaporization point of the solute leads to increased vaporization. This in combination with intense localized heating and rapid cooling that occurs during AM processes creates residual stress in parts that contributes to cracking and increased porosity.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Process Modeling for Additive Manufacturing

Additive Manufacturing (AM) provides a new avenue to design innovative materials and components that cannot be created using traditional machining operations. With current AM capabilities, complex designs (such as those required in weapon systems) can be readily manufactured with laser powder forming (or Laser-Engineered Net Shaping (LENSTM)) [1] that would be otherwise cost prohibitive or impossible to produce. However, before an AM product can be qualified for weapon applications, the characteristics of the metals produced by additive manufacturing processes need to be well understood. This work focuses on the development of computational simulation tools to model the metal additive manufacturing process. This work extends and integrates existing Sandia National Laboratories tools to accomplish the following: (i) be able to better predict residual stresses in AM product, (ii) extend high-fidelity material models to capture material evolution during the formation process, leading to prediction of end-state material properties, and (iii) provide a basis for engineering tools to propose improvements to additive manufacturing process variables, including those that minimize process variation. While this work in its current state is directly applicable to additive manufacturing processes, the tools developed may also help enable modeling welding processes such as gas tungsten arc (GTA), electron beam, and laser welding.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2019

Comparison of mechanical testing across micro- and meso- length scales

The present report summarizes the results from a variety of tests performed across different lengths scales used to evaluate the mechanical properties of a FeCrAl C26M weld. A variety of microscale and mesoscale mechanical tests were performed to evaluate a range of properties including nanoindentation hardness, compression and shear yield strengths, tensile strengths, and elongation. Using the mesoscale tensile testing as a baseline for comparison, micropillar compression was found to be the most sensitive to microstructural changes in the weld. Nanoindentation hardness testing, being high throughput, is recommended as a first step to identify major changes in the system and if residual stress is present.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Progress on Grizzly Development for Reactor Pressure Vessels and Reinforced Concrete Structures

The Grizzly code has been under development for the U.S. Department of Energy’s Light Water Reactor Sustainability program to provide predictive tools for the evolution of material degradation in critical light water reactor structural components due to long-term exposure to the environmental conditions of normal reactor operation, and for the effects of this degradation on the safety of these components. This development has primarily targeted reactor pressure vessels and reinforced concrete structures. Work performed during Fiscal Year 2019 added important features for both of these types of structures. For probabilistic fracture mechanics analysis of reactor pressure vessels, capabilities were added to account for the effects of warm prestressing and residual stresses, as well as to model crack initiation, growth, and arrest. For modeling microstructure evolution in reactor pressure vessels, a cluster dynamics model for evolution of Mn-Ni-Si phases has been implemented. For modeling degraded reinforced concrete structures, capabilities to consider the combined effects of damage and creep in the concrete constitutive model and model nonlinear behavior of reinforcing bars has been added. These newly-developed features fill important gaps in Grizzly’s feature set for engineering-scale analysis of degraded reactor pressure vessels and reinforced concrete structures. Grizzly development in both of these areas has reached a point where it is ready for extensive testing on relevant engineering problems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Development and Integration of Predictive Models for Manufacturing and Structural Performance of Carbon Fiber Composites in Automotive Applications (Final Report)

The goal of this project is to develop integrated, state-of-the-art, computational modeling tools based on an integrated computational materials engineering (ICME) methodology that are critically needed to enable structural carbon fiber (CF) applications in automobiles. These tools are designed to predict the manufacturing and structural performance of CF composites, including stochastic effects. During the first phase of the project, the manufacturing and structural performance tools, including a stochastic driver, were developed, calibrated, and validated against coupon and component level test results. For this project, from the manufacturing side, the development efforts were focused on high-pressure resin transfer molding (HP-RTM), a potentially game-changing manufacturing technology that is capable of reaching the 3-5-minute cycle time that is necessary for volume manufacturing of composites. On the structural performance side, the crashworthiness of CF structures was studied. Accordingly, computational tools were developed and validated. The resulting differences between the numerical predictions and the experimental results in the first phase of the project were required to be less than 15%. During the second phase of the project, the manufacturing and performance tools were integrated by mapping the manufacturing outcomes (e.g., fiber angles, residual stresses, degree of cure, and defects) into the structural models. Also, using the tools developed in this project, an automotive assembly currently manufactured in steel (2016 GM Malibu) was redesigned to be manufactured using advanced CF composites with the objective of comparing the performance of the CF assembly with the developed ICME model predictions. The weight, performance and cost of the CF assembly were compared with the baseline steel assembly as well. The CF underbody design was shown to be 30% lighter than the corresponding steel design. The CF underbody assembly withstood the side pole impact with less than half the intrusion for the steel assembly. Excellent correlations within 10% for both peak impact load and intrusion were observed between the numerical predictions and experimental results. Based on the cost models developed in the project, the cost increase per Kg saved was determined to be $22. The project team has prepared a total of 28 publications in various journals and conferences and broadly communicated the project results for the benefit of the composite industry. The project team has also prepared a total of 10 patent applications that were submitted to the US Patent and Trademark office.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Demonstration of the Coating Analysis Capabilities in BISON

In order to improve the accident tolerance of light water reactor (LWR) fuel, coated cladding materials have been proposed which exhibit much slower oxidation kinetics in high-temperature steam than Zr-alloys. This behavior should decrease the energy release due to oxidation and allow the cladding to remain integral longer in the presence of high-temperature steam, making accident mitigation more likely. In order to determine how these coating materials will adjust the behavior of the Zr-alloy cladding during normal reactor operation, simulations have been performed using the Bison fuel performance code. This analysis focused on modeling and comparing the integral thermo-mechanical performance of coated and uncoated zircaloy cladding with uranium dioxide fuel under normal operating conditions. This analysis demonstrates the ability to model a discrete meshed coating bonded to the cladding exterior and provides a comparison with an uncoated fuel rod. A generic range of coating material properties are implemented given the differences and unknowns regarding the proprietary coating properties used by the vendors. A main-effects analysis was performed to identify trends and sensitivities in how coating material properties affect key fuel performance metrics. Lastly, because residual stresses are expected to form in the coating, arising from the high temperature coating application process and application techniques, an additional analysis was performed to identify the impact of these stresses on the cladding behavior. Future analysis efforts will target more comprehensive documentation of this main effects analysis by sampling the results at the beginning and middle-of-life in order to capture important behavior before and during the onset of gap closure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Multiscale Approach to Fast ModSim for Laser Processing of Metals for Future Nuclear Deterrence Environments

Predicting performance of parts produced using laser-metal processing remains an out- standing challenge. While many computational models exist, they are generally too computationally expensive to simulate the build of an engineering-scale part. This work develops a reduced order thermal model of a laser-metal system using analytical Green's function solutions to the linear heat equation, representing a step towards achieving a full part performance prediction in an "overnight" time frame. The developed model is able to calculate a thermal history for an example problem 72 times faster than a traditional FEM method. The model parameters are calibrated using a non-linear solution and microstructures and residual stresses calculated and compared to a non-linear case. The calibrated model shows promising agreement with a non-linear solution.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Commissioning of a Cask Enabling Characterization of Irradiated Nuclear Fuels with Pulsed Neutrons

Irradiation tests are a key component of nuclear fuel development and identifying typical and atypical regions in the irradiated fuel volume relies on very few characterization techniques. The goal of the effort reported here is to provide complementary measurements adding to the available parameter space for post irradiation examination as well as to inform subsequent hot cell PIE examinations by identifying typical and atypical regions with respect to microstructure, tomographic data, or isotope densities. Pulsed neutrons, enabling diffraction as well as energy-resolved neutron imaging and neutron absorption resonance spectroscopy, offer unique capabilities for this purpose. Time-of-flight neutron diffraction has the potential to offer efficient, non-destructive and non-contact microstructural characterization of irradiated fuel pins with spatial resolution of 1 mm 3 to 1 cm 3 while for energy-resolved neutron imaging (and by extension tomography) a resolution of 100 μm was demonstrated. The potential results include crystallinity vs. amorphous volumes and microstructural information such as phase compositions, lattice strains (indicative of residual stresses or chemistry variations) and textures from the diffraction data as well as distances (e.g. pellet to cladding), cracks, and isotopic distributions of minor actinides, fission products as well as fission gas partial pressures e.g. in the plenum from energy resolved neutron imaging.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Integrated Computational Materials and Mechanical Modeling for Additive Manufacturing of Alloys with Graded Structure Used in Fossil Fuel Power Plants

Wire-arc additive manufacturing (WAAM) has demonstrated its unique capability of producing large-size alloy components with a significantly reduced fabrication time and enhanced geometry design freedom. In this project, the team has developed an ICME (Integrated Computational Materials Engineering) modeling framework, which supports the WAAM of the AUSC (Advanced Ultra-Supercritical) power plant components. The manufacturing design has been applied to Inconel 740H, steel P91, as well as the dissimilar alloy components between steel P91 and Inconel 740H. The ICME model framework is developed by considering two types of modeling. First, mechanistic modeling has been applied to control the printing quality and understand the sequence of the dissimilar printing of the wall structure. The following models have been included in the developed ICME framework: finite element thermal model, grain structure model, residual stress simulation, crystal plasticity model, CALPHAD-based precipitation kinetic model, phase stability prediction, thermal expansion predictive model, and heuristic creep model. Secondary, a physics-based machine learning model has also been developed based on the ICME model structure. The machine learning model development is based on the ICME model prediction with calibration of the experiments. In addition, the WAAM has been utilized as a high-throughput experimental tool rapidly generating a gradient of alloy composition to facilitate experimental database generation for process-structure-property relationships. Such a database directly supported the ICME-enhanced machine learning, which further assisted in intermediate composition block design between P91 and 740H. A high-throughput screening study of the oxidation resistance has been performed based on such high-throughput experimentation. Based on the computational design, several dissimilar alloy manufacturing with post-heat treatment have been performed with a comprehensive evaluation of mechanical performance, including hardness mapping, yield strength, creep resistance. In this project, the single component of P91 and 740H processed by WAAM after heat treatment designed by ICME has demonstrated higher performance in yield strength and creep resistance than the wrought materials. The P91 sample prepared by WAAM with ICME-designed heat treatment performs better than P92 in creep resistance. The designed graded alloy printing with intermediate block shows a promising performance that exceeds the traditional welding. Moreover, the current research indicates the high need for location-specific design analysis with uncertainty quantification, an important topic that deserves more dedicated research. The achievement of this project demonstrated the promising future of WAAM in structural alloy manufacturing for energy power plant development. Successful printing requires synergetic efforts made by manufacturing, mechanical, and materials sciences.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Material Characterization for Large Scale Additive Manufacturing (AM)

The objective of this project was to enable prediction of residual stresses and warpage for extrusion deposition additive manufacturing (EDAM) fabricated carbon fiber thermoplastic matrix parts with three different materials systems produced by Techmer. The materials selected include Polyphenylene sulfide reinforced with 50% by weight of carbon fiber (CF-PPS), Polyethersulfone reinforced with 25% by weight of carbon fiber (CF-PESU), Polysulfone reinforced with 25% by weight of carbon fiber (CF-PSU). ADDITIVE3D © , a physics-based simulation workflow for EDAM, provided the simulation capabilities required for this project. Simulation predictions were validated against measurements carried out during and after the printing process carried out in the CAMRI and LSAM systems . Predictions for temperature, degree of crystallinity and deformation were carried out for the three material systems and two different geometries. Predictions for temperature were correlated very well with the experimental measurements for the two geometries printed using the three-material systems. The crystallinity level was verified for CF-PPS. The predictions for part deformation were in good agreement with the experimental measurements. In the best-case, predictions were within 8% of the maximum displacement observed in the 3-direction whereas predictions were within 14% for the worst-case. The adoption of this technology in commercial large-scale EDAM production processes would dramatically reduce the costs associated with producing articles by that process. Many thousands of dollars in materials, energy, and machine time could be saved by utilizing this simulation technology to develop articles rather than iterative printings to arrive at the optimal or correct design. The avoidance of a single failed print has the possibility of saving tens of thousands of dollars involved in the cost of material, machine and operators’ time.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Progress Report on Mockup Irradiation Capsule Fuel Measurements at LANSCE

Irradiation tests are a key component of nuclear fuel development and identifying typical and atypical regions in the irradiated fuel volume relies on very few characterization techniques. The goal of the effort reported here is to provide complementary measurements adding to the available parameter space for post irradiation examination as well as to inform subsequent hot cell PIE examinations by identifying typical and atypical regions with respect to microstructure, tomographic data, or isotope densities. Pulsed neutrons, enabling diffraction as well as energy-resolved neutron imaging and neutron absorption resonance spectroscopy, offer unique capabilities for this purpose. Time-of-flight neutron diffraction has the potential to offer efficient, non-destructive and non-contact microstructural characterization of irradiated fuel specimen with spatial resolution of 1 mm 3 to 1 cm 3 while for energy-resolved neutron imaging (and by extension tomography) a resolution of 100 μm 3 was demonstrated. The potential results include crystallinity vs. amorphous volumes and microstructural information such as phase compositions, lattice strains (indicative of residual stresses or chemistry variations) and textures from the diffraction data as well as distances (e.g. pellet to cladding), cracks, and isotope densities of minor actinides, fission products as well as fission gas partial pressures e.g. in the plenum from energy resolved neutron imaging.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

The Effect of Rolling As-Cast and Homogenized U-10Mo Samples on the Microstructure Development and Recovery Curves

Over the past several years Pacific Northwest National Laboratory (PNNL) has been actively involved in supporting the U.S. Department of Energy National Nuclear Security Administration Office of Material Management and Minimization (formerly Global Threat Reduction Initiative). The U.S. High-Power Research Reactor (USHPRR) project is developing alternatives to existing highly enriched uranium alloy fuel to reduce the proliferation threat. One option for a high-density metal fuel is uranium alloyed with 10 wt% molybdenum (U-10Mo). Forming the U-10Mo fuel plates/foils via rolling is an effective technique and is actively being pursued as part of the baseline manufacturing process. The processing of these fuel plates requires systematic investigation/understanding of the pre- and post-rolling microstructure, end-state mechanical properties, residual stresses, and defects, their effect on the mill during processing, and eventually, their in-reactor performance. In the work documented herein, studies were conducted to determine the effect of cold and hot rolling the as-cast and homogenized U-10Mo on its microstructure and hardness. The samples were homogenized at 900°C for 48 h, then later annealed for several durations and temperatures to investigate the effect on the material’s microstructure and hardness. The rolling of the as-cast plate, both hot and cold, was observed to form a molybdenum-rich and -lean banded structure. The cold rolling was ineffective, and in some cases exacerbated the as-cast defects. The grains elongated along the rolling direction and formed a pancake shape, while the carbides fractured perpendicularly to the rolling direction and left porosity between fractured particles of UC. The subsequent annealing of these samples at sub-eutectoid temperatures led to rapid precipitation of the α + γ ' lamellar phase, mainly in the molybdenum-lean regions. Annealing the samples above the eutectoid temperature did not refine the grain size or the banded microstructure. However, annealing the samples led to quick recovery in hardness as evidenced by a drop in Vickers hardness of 20%. Hot rolling was performed at 650 and 800°C. The hot-rolling mill loads (load separation force) were approximately 40 to 50% less than the cold-rolling for the same reduction and thickness. It was observed that hot rolling the samples with 50% or more reduction in thickness were responsible for dynamic recrystallization in the hot-rolled samples and led to grain refinement. Unlike the cold-rolled samples, the hot-rolled samples did not fracture the carbides and appeared to heal the casting defects. The recovery phenomenon was similar to the cold-rolled samples above the eutectoid temperatures, but owing to the refined grain size, the precipitation of the lamellar phase was far more rapid in these samples and the hardness increased more rapidly than in the cold rolled sample when heated below the eutectoid temperature. The data generated from these rolling efforts has been used to make the process modeling efforts more robust and applicable to all USHPRR partner rolling mills. The flow stress for cold rolling the samples was determined to be between 170-190 ksi, with frictional forces between 0.2 and 0.4 for the PNNL mill. The measured roll separation forces and those simulated using finite element methods for hot and cold rolling for the PNNL rolling mill were in good agreement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Sparse Data Machine Learning Integration with Theory, Experiment and Uncertainty Quantification: Process-Structure-Property-Performance of Friction Deformation Processing

Computer vision and deep learning tools that advance the ability to establish processing-structure-property-performance (PSPP) relations are presented. The Bayesian binning method for image segmentation enables quantitative analysis of microstructural features in an automated way, while the analysis of shapes and relative orientation of these features reveals local deformation maps indicative of both, material flow and residual stresses due to materials processing. The deep learning method leads to the previous knowledge agnostic mapping of empirically observed microstructural zones in friction stir welding (FSW) process and synthetic microstructure generation capability that is statistically equivalent to experimentally collected data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Summary of Methodology for Mitigating Risks Associated with Licensing and Qualifying AM Nuclear Materials

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program focuses on accelerating the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. Laser powder bed fusion (LPBF) is one of the most popular additive manufacturing (AM) processes for fabricating components with intrinsically complex geometries. LPBF was extensively explored for nuclear applications under the previous Transformational Challenge Reactor program. Additionally, Oak Ridge National Laboratory developed and licensed the Peregrine software and larger digital platform that couples machine learning and in situ data collection during AM to detect anomalies and any evolved defects. The digital platform will be critical to (1) the qualification of AM components for nuclear applications that link location-specific data to macroscopic properties and (2) predict final component performance. Current in situ process monitoring tools are valuable for observing the formation of stochastic flaws, but additional data are needed to predict the resulting microstructures and associated material performance. Rapid cooling rates and large thermal gradients have caused large heterogeneities in the microstructure, which cause anisotropy in mechanical performance. The AMMT program is evaluating the best approaches for addressing these heterogeneities and their effect on component performance using a combination of multiscale modeling, enhanced in situ process monitoring, and high throughput experimental testing. This report summarizes strategies for mitigating the risks associated with qualifying AM components, including developing new sensing capabilities for in situ process monitoring and characterizing melt pool solidification and residual stresses to inform multiscale modeling efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Imaging Enhanced Simulation Validation for Directed Energy Deposition Additive Manufacturing (Final CRADA Report – NFE-22-09107)

Directed Energy Deposition (DED) is a welding-based metal Additive Manufacturing (AM) process that relies on the programmed rastering of an electric arc or laser induced weld pool to construct a component in a layerwise fashion. The induced complex thermal field and uneven thermal contraction depends on the printed geometry and scan pattern, and as such, accumulated residual stresses and distortions are complex and difficult to predict. Several prior works have resulted in tools to combat this issue; ANSYS has developed a thermoplastic simulation package targeting DED AM, and ORNL has developed an in-situ imaging sensor package ‘Stereo Correlated Optical and Pyrometric System’ (SCOPS) that can spatially monitor temperature and full field strain. In this CRADA, these tools are compared in order to validate the results and complimentarily address the weaknesses in each other.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Fatigue Testing and Characterization of Pre-hydrided Zircaloy-4 Cladding Tubes

The solubility of hydrogen in Zircaloy-4 (Zry-4) at the cladding operating temperature is near 100 wt. ppm. Above this solubility limit, excess hydrogen precipitates as δ-hydride platelets in the cladding material. Because of the effect of the thermal gradient across the cladding thickness on the migration and precipitation of hydrogen, hydride rims are often observed at the cladding outer surface; under excessive corrosion conditions hydride blisters are possible. It is well known that the fatigue of metal alloys, especially high cycle fatigue, is sensitive to the status of surface including the microstructure, roughness, and residual stress. Thus, the question considered herein, is whether excessive hydrogen pickup modifies the microstructure such that it has a degradation effect on the fatigue performance of cladding during operation. This report describes the evaluation of fatigue performance of a pre-hydrided Zry-4 cladding. A commercial Zry-4 was polished and pre-hydrided to 800 ppm and 1300 ppm H contents. The fatigue testing was conducted under strain control at 5 Hz with fully-reversed bending by using a cyclic integrated reversible bending fatigue tester (CIRFT). Six specimens with 1300 ppm and one specimen with 800 ppm were tested. Significant variation in test results were observed. While two of the 1300 ppm specimens failed with less than 1 ×10 5 cycles (at 0.32% and 0.41%), the four other samples did not fail over the strain amplitude range of 0.25% to 0.38%. Interestingly, the fracture initiation site of the failed samples was on the outside diameter (OD) surface rather than on the inside diameter (ID) surface as is typical for the as-polished cladding. This suggested a degrading effect of the hydriding process. Subsequently, three of the unfailed specimens were then further tested at ~0.43% to observe where failure initiation occurred. Significant variation was also observed in these three specimens. One specimen failed at ~9000 cycles while the two others failed at 43000 and 1.06 ×10 5 cycles. The performance here correlated to the location of failure initiation; failure initiated on the OD in the sample that failed after 9000 cycles while it initiated on the ID in the sample that failed after 43000 and 1.06 ×10 5 cycles. Flat features at the OD initiation sites suggest a brittle hydride feature on the surface of those samples was the cause of the degradation in fatigue performance, though the overall hydrogen levels in all samples was similar. A summary of all the observations is provided below: • The un-failed specimens with 1300 ppm H were cycled to failure with a higher amplitude near 0.43%. In addition, the fatigue-treated specimen tended to have a longer fatigue at the same induced amplitude. • Fractography revealed a mixed failure mode for the pre-hydrided specimen. Particularly, the specimen with fracture initiation site (FIS) located on the outer diameter surface of tube tended to have a shorter fatigue life than that of FIS on the inner diameter surface. • Etched cross section was shown to have hydride platelets aligned with tube longitudinal axis as expected, and the density of hydrides is at the similar level as in literature data. Meanwhile, a LECO procedure was applied for hydrogen concentration measurement, which showed the measured hydrogen contents are close to the nominal value. • With the polished cladding tube as baseline, O’Donnell-Lager (O-L) analysis showed that a decrease of about 50% in reduction-of-area (RA) would be needed for the O-L fitting to the fatigue data of 1300 ppm cladding. The suggestion for the next steps is provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗