With growing environmental consequences from material consumption, there is increased
urgency to decarbonize the production of materials we consume frequently, including …

Uniaxial compressive strength (UCS) is of great importance for building stone. Index tests
have been widely used to quickly predict UCS due to the cumbersome and expensive …

Developing an accurate pavement prediction model plays a dominant role in pavement
M&R optimization. Despite employing different robust machine learning techniques to …

The accurate prediction of concrete carbonation depth is essential to prevent concrete from
cracking and corrosion. However, identifying the critical parameters affecting carbonation …

Additive manufacturing in construction demands an in-depth understanding of the
rheological properties of fresh concrete. However, the abundant data in this field remains …

In this study, four Artificial intelligence (AI)-based machine learning models were developed
to estimate the Residual compressive strength (RCS) value of concrete supported with nano …

The current global demand to minimize carbon dioxide (CO2 $) emissions from Portland
cement manufacturing processes has led to the use of environmentally friendly additives in …

This paper proposes a straightforward approach to characterize the fracture properties and
fatigue life of asphalt mixtures over the service time. Since the serviceability of flexible …

Bacterial concrete, an environmentally conscious innovation, has garnered significant
attention for its remarkable contributions to enhancing concrete durability and promoting self …

This study investigates the application of aggregate-based conductive additives, including
steel slag, Iron slag, and ferrosilicon, in asphalt concretes for induction heating and induced …