首页|Study Results from Cardiff University Provide New Insights into Ma- chine Learning (Microcapsule Triggering Mechanics in Cementitious Materials: A Modelling and Machine Learning Approach)

Study Results from Cardiff University Provide New Insights into Ma- chine Learning (Microcapsule Triggering Mechanics in Cementitious Materials: A Modelling and Machine Learning Approach)

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Researchers detail new data in artificial intelligence. According to news originating from Cardiff, United Kingdom, by NewsRx correspondents, research stated, "Self-healing cementitious materials containing microcapsules filled with healing agents can autonomously seal cracks and restore structural integrity." Financial supporters for this research include Epscr. Our news editors obtained a quote from the research from Cardiff University: "However, optimising the microcapsule mechanical properties to survive concrete mixing whilst still rupturing at the cracked interface to release the healing agent remains challenging. This study develops an integrated numerical modelling and machine learning approach for tailoring acrylate-based microcapsules for triggering within cementitious matrices. Microfluidics is first utilised to produce microcapsules with systematically varied shell thickness, strength, and cement compatibility. The capsules are characterised and simulated using a continuum damage mechanics model that is able to simulate cracking. A parametric study investigates the key microcapsule and interfacial properties governing shell rupture versus matrix failure. The simulation results are used to train an artificial neural network to rapidly predict the triggering behaviour based on capsule properties."

Cardiff UniversityCardiffUnited KingdomEuropeCyborgsEmerging TechnologiesMachine Learning

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.22)
  • 49