Random forest incorporating ab-initio calculations for corrosion rate prediction with small sample Al alloys data

Corrosion jeopardizes the materials longevity and engineering safety, hence the corrosion rate needs to be forecasted so as to better guide materials selection. Although field exposure experiments are dependable, the prohibitive cost and their time-consuming nature make it difficult to obtain large dataset for machine learning. Here, we...

A comparison between alkali-activated slag/fly ash binders prepared with natural seawater and deionized water

In this research, the effects of natural seawater (SW) on the properties of alkali-activated slag/fly ash (AASF) are studied. AASF prepared with deionized water is set as the reference mixture. The results showed that the use of natural SW resulted in a prolonged setting time and lower heat release, but no obvious impact on the flowability of...

Experimental comparisons between one-part and normal (two-part) alkali-activated slag binders

One-part alkali-activated slag (AAS) binders are more promising in large-scale constructions because one-part mixing procedure is safer and easier to handle compared to normal two-part method. Thus, this study aims at investigating different properties of one-part AAS binders and control samples prepared using the two-part method. Experimental...

Multi-disciplinary and multi-objective optimization problem re-formulation in computational design exploration: A case of conceptual sports building design

The benefits of applying multi-objective optimization (MOO) in building design have been increasingly recognized in recent decades. The existing or traditional computational design optimization (CDO) approaches mostly focus on optimization problem solving (OPS), as they often conduct optimizations directly by assuming the optimization...