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AI-powered non-destructive testing for smart manufacturing of carbon-negative biopolymer-bound soil composite
Barney H Miao1, Yiwen Dong2, Andreas Theissler3,4
1Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford, CA, USA. barneym@stanford.edu.
None:
Biopolymer-bound soil composite (BSC) is a materials technology that uses nature-based polymers to form carbon-negative building materials that are as strong as concrete. For large-scale applications of this material, a quality control system is necessary to minimize defects and avoid wastage. To meet this need, we developed a non-destructive vibration-based sensing system that assesses initial material quality, while still wet, before hardening occurs. We developed a set of artificial intelligence (AI) algorithms that use a set of physics-based features to aid in the smart manufacture of BSC. Our system allows for defect detection early on in the manufacturing process, so that the wet material can be salvaged when defects are identified. Another benefit is that our sensing system enables the monitoring of moisture loss as the material dries out and gains strength. Both of these functions are essential for large-scale deployment of this building material.
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