h i g h l i g h t sEngineered cementitious composite is proposed for spent nuclear fuel storage. High temperature effect on ECC uniaxial tension properties is characterized. ECC has high spalling resistance after 6 h of exposure to 600°C. ''Spider web'' nano-cracks are absent in ECC at temperatures up to 600°C. The change in ECC microstructure explains its mechanical properties deterioration. a b s t r a c tStrain-hardening engineered cementitious composite materials (ECC) is proposed to substitute quasibrittle concrete materials for building extended spent nuclear fuel (SNF) storage systems in nuclear power plants. While most of ECC properties have been established under normal temperature, the study aims at understanding ECC material behavior under elevated temperature that is expected in a SNF storage environment. On the composite level, ECC specimens were characterized at various temperature levels up to 600°C under both uniaxial tension and compression. The elevated temperature effect on tensile strength and strain capacity, compressive strength and failure mode, moisture loss, and spalling behavior was studied. On the microstructure level, optical microscopy and scanning electron microscopy were conducted to probe the degradation of components, and the change of pore structures due to fiber melting within ECC. The results will provide crucial data and insights for future studies of re-engineering ECC with robust properties specifically desired for nuclear engineering applications.

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Electrical resistance tomography (ERT) serves as a non-invasive, non-destructive, non-radioactive imaging technique. It has potential applications in industrial and biological imaging. This paper presents an optimized inverse algorithm, named Newton’s Constrained Reconstruction Method (NCRM), to detect damage in cementitious materials. Several constraints were utilized in the proposed algorithm to optimize initial parameters. The range and spatial distribution of conductivities within the sample were chosen as two main constraints. Two sets of numerical and a set of experimental voltage data were used to reconstruct conductivity distribution images based on this algorithm. To evaluate the quality of reconstructed images, two image quality evaluation indicators, correlation coefficient and position error were used. Results show that the proposed algorithm NCRM has the ability to enhance the reconstructed image quality with fewer artifacts and has better positioning accuracy.

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