Search NASA⌕ Search

Engineering topics

Popovics, John S.

Publications and source records attributed to Popovics, John S..

Silicon ion radiation as a viable surrogate for emulating neutron radiation damage in silicates

Abstract Nuclear power plants are aging around the world, and a precise assessment of irradiation damage in their components is needed. One key component, concrete, and specifically the silicates in its aggregates, can undergo significant expansion upon neutron radiation, which can lead to cracking and, ultimately, structural failure. However, assessing and predicting the extent of damage via neutron radiation is challenging due to reasons such as residual radioactivity and, most importantly, the high time involved. Here, we evaluate whether ion radiation can be a viable surrogate. Specifically, by employing Si 2+ ion radiations and a comprehensive multi-modal imaging protocol, we report mineral-specific responses for key silicates such as quartz, albite, anorthite, and microcline. We find that 10 MeV Si 2+ ions result in mineral expansions that are remarkably comparable to neutron radiation equivalent expansions (R 2 = 0.86, RMSE = 1.29%), opening up pathways towards rapid assessment of silicates subject to irradiation.

36 MATERIALS SCIENCE↗

In situ detection and characterization of alkali-silica reaction damage in concrete using contactless ultrasonic wavefield imaging

Here we present work to characterize cracking damage in concrete caused by alkali-silica reactivity distress. We apply contactless ultrasonic scan inspection, exploiting Rayleigh wave scattering from concrete inhomogeneities. The scanning system utilizes a multi-channel MEMS sensor array to collect ultrasonic wavefield data from concrete subjected to ASR-promoting environments. The location and extent of ASR damage are established by internal expansion measurements from embedded strain gauges, scanning electron microscope images of cored samples, and expansion measurements from companion samples. A wavefield data processing method extracts oscillatory fields from the ultrasonic wavefield data to detect distinct zones of ASR damage. A damage index is proposed to further characterize the extent of ASR damage. The results confirm the feasibility and accuracy of the approach to characterize ASR damage in concrete. The fully contactless ultrasonic scanning measurement system does not require separate material samples and enables in situ characterization of ASR damage within concrete structures.

36 MATERIALS SCIENCE↗

Development of an MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete

Abstract Although contactless ultrasonic wavefield imaging shows potential for effective nondestructive inspection of various engineering materials, it has been rarely applied to concrete materials owing to technical challenges including low signal-to-noise ratio (SNR) caused by inherent heterogeneity of concrete. This paper presents development of a multi-channel MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete materials. The developed multi-channel MEMS ultrasonic microphone array system contains eight MEMS ultrasonic microphone elements and a signal conditioning circuit that enables measurements of ultrasonic signals with high SNR. A compressed sensing approach, based on the multiple measurement vector (MMV) concept, is applied to reconstruct a full dense ultrasonic wavefield data from sparsely sampled ultrasonic wavefield data. Experiments are carried out on a laboratory concrete sample to verify the performance of the developed MEMS microphone array system and proposed compressed sensing approach and then large-scale concrete samples to demonstrate practical application. The experimental results demonstrate that the developed MEMS microphone array system provides high-quality (SNR > 20 dB) ultrasonic data collected from concrete elements; furthermore, the proposed compressed sensing approach provides accurate reconstruction of dense wavefield data, as determined by peak signal-to-noise ratio (PSNR), from sparsely measured wavefield data with compression ratios up to 85% and PSNR above 25 dB in data collected form realistic large-scale concrete samples. By combining the MEMS array system and compressed sensing approach, the total ultrasonic data acquisition time needed to produce dense wavefield data can be significantly reduced.

Instruments & Instrumentation↗