Durability and protection of mass timber structures: A review

S Ayanleye, K Udele, V Nasir, X Zhang… - Journal of Building …, 2022 - Elsevier
Mass timber (MT), a group of large engineered structural wooden panels such as cross-
laminated timber (CLT), glue-laminated timber (Glulam), laminated veneer lumber (LVL) …

[HTML][HTML] Acoustic emission monitoring of wood materials and timber structures: A critical review

V Nasir, S Ayanleye, S Kazemirad, F Sassani… - … and Building Materials, 2022 - Elsevier
The growing interest in timber construction and using more wood for civil engineering
applications has given highlighted importance of develo** non-destructive evaluation …

Prediction of the mechanical properties of wood using guided wave propagation and machine learning

H Fathi, V Nasir, S Kazemirad - Construction and Building Materials, 2020 - Elsevier
Accurate nondestructive prediction of the mechanical properties of wood is a critical quality
control task for timber grading. Currently, the ultrasonic wave method is widely used for this …

Effect of wood surface roughness on prediction of structural timber properties by infrared spectroscopy using ANFIS, ANN and PLS regression

S Ayanleye, V Nasir, S Avramidis, J Cool - European Journal of Wood and …, 2021 - Springer
Predicting the properties of structural timber using a rapid and reliable non-destructive
method is a critical quality control task in production. This study investigates using infrared …

Combined machine learning–wave propagation approach for monitoring timber mechanical properties under UV aging

V Nasir, H Fathi, S Kazemirad - Structural Health Monitoring, 2021 - journals.sagepub.com
This study proposes a combined machine learning–wave propagation approach for
nondestructive prediction of the modulus of elasticity (MOE) and rupture (MOR) of timber …

Classification of thermally treated wood using machine learning techniques

V Nasir, S Nourian, S Avramidis, J Cool - Wood Science and Technology, 2019 - Springer
Classification of thermally modified wood is a critical assessment and control task that
assures the quality of thermally treated wood. Machine learning methods can be used for …

The non-enzymatic browning of pine bark during thermal treatment: Color and chemical changes, color kinetics and insights into mechanisms

GY Yao, XP Chen, ZY Long, XB Du, JZ Liang… - Industrial Crops and …, 2023 - Elsevier
Thermal treatment is an essential modification method for agroforestry biomass, and it
causes the most intuitive change in agroforestry biomass, a color change. But there is still a …

Stress wave evaluation for predicting the properties of thermally modified wood using neuro-fuzzy and neural network modeling

V Nasir, S Nourian, S Avramidis, J Cool - Holzforschung, 2019 - degruyter.com
This study investigated using the stress wave method to predict the properties of thermally
modified wood by means of an adaptive neuro-fuzzy inference system (ANFIS) and neural …

Prediction of mechanical properties of artificially weathered wood by color change and machine learning

V Nasir, H Fathi, A Fallah, S Kazemirad, F Sassani… - Materials, 2021 - mdpi.com
Color parameters were used in this study to develop a machine learning model for
predicting the mechanical properties of artificially weathered fir, alder, oak, and poplar wood …