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DOE OSTI2021

Aerodynamic effects on outer ash deposition rates in second generation atmospheric pressure oxy-coal combustion systems

Recent measurements in scenarios representative of second generation atmospheric pressure oxy-coal combustion systems have shown a significant increase in ash deposition rates in comparison to combustion in air. However, the causative mechanisms behind this increase have not been well understood. To fill this void, well-characterized experiments including fuel and deposit particle size distributions (PSDs) were coupled with highly resolved numerical simulations to isolate the aerodynamic effects impacting the deposition process such that mechanisms could be hypothesized. Three combustion scenarios (AIR, OXY27, OXY70) spanning a factor of three variation in flue gas volumetric flow rates were simulated and the deposition characteristics (impaction rates, deposit PSD, temperature, residence times, capture rates) tracked/predicted using a customized deposition module. The measured deposit PSD was significantly different from the PSD of the parent fuel indicating significant physio-chemical transformations (coalescence and particle growth in particular) at play. The use of simplistic modeling approaches (swelling parameter variations) to model particle growth led to inaccurate deposit ash PSD and rate predictions. A more satisfactory agreement between the measurements and simulations was obtained when the functional form of the parent fuel PSD (spread parameter) was modified to conform closely to the deposit PSD while still ensuring the fidelity of temperature and velocity predictions. Based on the measured ash compositions, identical capture criteria were employed across all three scenarios. Here this study further supports the theory that the ash deposition rates in these systems are dominated by aerodynamic effects with the ash PSD playing a dominant role.

42 ENGINEERING↗

DOE OSTI2026

Development of an ultraprecise glue-free bimorph deformable mirror with a length of 460 mm

Lead zirconate titanate (PZT) bimorph mirrors are essential for performing multiple functions, such as beam shaping, wavefront correction, and dynamic focusing with adjustable beam sizes. They typically consist of a mirror substrate with PZT electrodes bonded to the substrate using a thin epoxy film. However, glue-bonded PZT mirrors exhibit low reproducibility in measurement results. One source of this variability is water absorption by the substrate’s epoxy adhesive during wet fabrication processes, such as elastic emission machining (EEM), which leads to swelling and deformation. Additionally, longer deformable bimorph mirrors require larger PZT electrodes, further complicating their design and fabrication, particularly during bonding and ultraprecise metrology. To address these challenges, silver nanoparticles were employed to bond PZT elements to the silicon (Si) mirror, eliminating the need for epoxy glue. Here, in this study, we developed an inorganic-glue-free PZT bimorph mirror with a length of 460 mm and 28 channels. The glue-free bonding method successfully ensured the high reproducibility of measurements after water immersion. This approach resulted in a shape error of only 0.41 nm root mean square after the figure correction process using an ultraprecise EEM process. Scanning acoustic tomography and basic response function tests confirmed the success of the bonding process, showing no critical voids. Furthermore, the shape changes induced by applying voltages to the PZT electrodes closely matched predictions obtained from simulations. These results demonstrate the reliability and precision of the proposed glue-free bonding technique, paving the way for improved performance of new PZT bimorph mirrors.

Ichii, Yoshio [SLAC National Accelerator Laborator↗

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 OSTI2021

Effects of sample bias on adhesion of magnetron sputtered Cr coatings on SiC

Swelling of SiC at 300 C due to in-service neutron irradiation causes tensile residual stresses in coatings which are expected to adversely affect the performance of coated SiC composite fuel cladding for light water reactors. Matching the coating swelling with the substrate, a solution common for thermal expansion, is not practical in the case of neutron irradiation. Biasing samples during magnetron sputtering deposition induces compressive residual stress which may counteract this. In this study, chromium coatings were deposited on SiC by DC magnetron sputtering with no external heating at bias voltages of –50V, –75V, and –100V. The effects of the bias voltage on morphology, residual stress, microstrain, texture, and adhesion are shown. The low deposition temperature resulted in the coating microstructure evolution following an energetic particle bombardment dominated trend. Additionally, at the two lower bias voltages knock-on implantation dominated increasing the residual stress and microstrain while at the highest bias voltage, thermal spike migration allowed for defect relaxation. When the knock-on induced compressive residual stress exceeded 0.8 GPa microcrack formation in the SiC substrate decreased coating adhesion. While no microcracks formed at the lowest bias voltage, insufficient atomic mobility during coating growth lead to voids forming in the coating. A balance is needed to form void-free coatings that have high compressive residual stress.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Application of a deep learning semantic segmentation model to helium bubbles and voids in nuclear materials

Imaging nanoscale radiation-induced defects using the transmission electron microscope (TEM) is a key factor in the successful implementation of materials for nuclear energy structural applications. Analyzing each defect in a TEM micrograph is currently a manual task. To identify the defects in a single image can take anywhere from 15 min to an hour and a project can require the analysis of anywhere from tens to ≥ 100 images. Here, we use artificial intelligence (AI) models to automate this task. For simplification, we evaluated images with only a single type of defect; helium bubbles. Additionally, we performed semantic segmentation of these helium bubble defects in electron microscopy images of irradiated FeCrAl alloys using a deep learning DefectSegNet model. This model, which was previously used to classify crystal defects, is inspired by the classic DenseNet and U-Net image segmentation models. It claims high spatial resolution, but has poor performance at object boundaries. Our paper improves the DefectSegNet model’s application by adding two new features. First, the DefectSegNet model is applied not only to perform calculation pixel-wise but also object (or feature) wise. Because object-wise metrics are directly relevant to our final goal of detecting bubbles, whereas pixel-wise classification is only an intermediate step, it is an important part of our study. Second, a distance map loss (DML) function has been added to increase its performance at object boundaries. It is crucial to accurately represent defects boundaries, especially bubbles, in order to track the bubble-induced swelling caused by irradiation. The boundary-focused DML function is also compared to other loss functions like Cross-entropy, Weighted Binary Cross Entropy (WBCE), Dice and Intersection over Union (IOU). Finally, by incorporating new features, we found a marked improvement on segmentation quality and better shape preservation at the boundaries and areas of the bubbles.

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