Probabilistic selection and design of concrete using machine learning
نویسندگان
چکیده
Development of robust concrete mixes with a lower environmental impact is challenging due to natural variability in constituent materials and multitude possible combinations mix proportions. Making reliable property predictions machine learning can facilitate performance-based specification concrete, reducing material inefficiencies improving the sustainability construction. In this work, we develop algorithm that utilize intermediate target variables their associated noise predict final variable. We apply methodology specify has high resistance carbonation, another low impact. Both also fulfill targets on strength, density, cost. The specified are experimentally validated against predictions. Our generic enables exploitation learning, which broad range applications structural engineering beyond.
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ژورنال
عنوان ژورنال: Data-centric engineering
سال: 2023
ISSN: ['2632-6736']
DOI: https://doi.org/10.1017/dce.2023.5