Porosity Analysis and Thermal Conductivity Prediction of Non-Autoclaved Aerated Concrete Using Convolutional Neural Network and Numerical Modeling

Porosity Analysis and Thermal Conductivity Prediction of Non-Autoclaved Aerated Concrete Using Convolutional Neural Network and Numerical Modeling

Currently, the visual study of the structure of building materials and products is gradually supplemented by intelligent algorithms based on computer vision technologies. These algorithms are powerful tools for the visual diagnostic analysis of materials and are of great importance in analyzing the...

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Bibliographic Details
Main Authors: Alexey N. Beskopylny, Evgenii M. Shcherban’, Sergey A. Stel’makh, Diana Elshaeva, Andrei Chernil’nik, Irina Razveeva, Ivan Panfilov, Alexey Kozhakin, Emrah Madenci, Ceyhun Aksoylu, Yasin Onuralp Özkılıç
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Buildings
Subjects:
aerated concrete
pore analysis
computer vision
convolutional neural network
thermal conductivity
Online Access:https://www.mdpi.com/2075-5309/15/14/2442
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