Microbial induced calcium carbonate deposition (MICP) is currently a research hotspot in the field of self-healing concrete.
However, its healing process is influenced by multiple factors such as material ratio, bacterial carrier, crack width, and curing environment.
Traditional single model static prediction is difficult to balance accuracy, timeliness, and physical interpretability.
The team led by Liu Dejun from China University of Mining and Technology (Beijing) has developed an integrated prediction framework consisting of “static evaluation dynamic tracking formula estimation”, which not only achieves high-precision intelligent prediction, but also derives semi empirical formulas that can be directly used in engineering sites, providing a systematic solution for the mix design and full life cycle performance monitoring of microbial self-healing concrete.
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