Xuan Zhang

<p>Applications of X-ray computed tomography (CT) for porosity characterization of engineering materials often involve an extended data analysis workflow that includes CT reconstruction of raw projection data, binarization, labeling and mesh extraction. It is often desirable to map the porosity in larger samples but the computational challenge of reducing gigabytes of raw data to porosity information poses a critical bottleneck. In this work, we describe algorithms and implementation of an end-to-end porosity mapping code that processes raw projection data from a synchrotron CT instrument into a porosity map and visualization in the form of triangular face mesh. Towards this objective, we report the development of a novel subset reconstruction scheme for X-ray CT using filtered backprojection and a convolutional neural network that allows us to reconstruct arbitrarily-shaped subsets of a tomography object. We build upon this scheme to implement the complete code for porosity mapping. The code first detects possible voids by performing a coarse reconstruction on down-sampled projections and then improves the shape of those voids with higher detail offered by reconstructing selected subsets from the original raw data. We report measurements of the time taken by this code to perform complete processing from raw data to a triangular face mesh for several visualization scenarios on a single highperformance workstation equipped with GPU. We show that we can now visualize local porosity within a 8 gigavoxel CT volume (12 gigabytes raw data) within 1 to 2 minutes and a 64 gigavoxel CT volume (100 gigabytes of raw data) within 3 to 7 minutes.</p>

Cast austenitic stainless steels (CASSs) are used in the cooling system of light water reactors (LWRs) for components with complex shapes, such as pump casings, valve bodies, coolant piping, etc. The CF grades of CASS alloys are the cast equivalents of 300-series stainless steels (SSs) and show excellent mechanical properties and corrosion resistance. In contrast to the fully austenitic microstructure of wrought SSs, CASS alloys consist of a dual-phase microstructure of delta ferrite and austenite and are vulnerable to thermal aging embrittlement. The service performance of CASS alloys is of concern after long-term exposure to high-temperature coolant. In this work, we studied the effects of thermal aging and ferrite content on the fracture resistance of CASS alloys. Crack growth rate and fracture toughness J–R curve tests were performed on aged and unaged CASS alloys in simulated light water reactor environments. The impact of thermal aging on the cracking susceptibility was investigated and the effect of ferrite content was evaluated. Significant embrittlement was observed in the CASS alloys after aging at 400°C. To understand the embrittlement mechanism, microstructural characterizations were performed with transmission electron microscope. The thermal aging produced G-phase precipitates and phase separation in the ferrite, but did not affect the microstructure of austenite. Consequently, the ferrite was hardened considerably after thermal aging while the hardness of austenite phase remained unchanged. The difference in hardness created a high incompatible strain at the interface between ferrite and austenite, leading to fracture at phase boundaries.

We present an in situ Radiated Materials (iRadMat) experimental module designed to interface with a servo-hydraulic load frame for X-ray measurements at beamline 1-ID at the Advanced Photon Source. This new capability allows in situ studies of radioactive specimens subject to thermo-mechanical loading using a suite of high-energy X-ray scattering and imaging techniques. The iRadMat is a radiation-shielded vacuum heating system with the sample rotation-under-load capability. We describe the design features and performances of the iRadMat and present a dataset from a 300 °C uniaxial tensile test of a neutron-irradiated pure Fe specimen to demonstrate its capabilities.