Predicting the Permeability of Pervious Concrete Based on the Beetle Antennae Search Algorithm and Random Forest Model

Jiandong Huang,Tianhong Duan,Jiandong Liu,Yi Zhang,Jia Zhang,Yawei Lei,Junfei Zhang

doi:10.1155/2020/8863181

Abstract

Pervious concrete is an environmentally friendly material that improves water permeability, skid resistance, and sound absorption characteristics. Permeability is the most important functional performance for the pervious concrete while limited studies have been conducted to predict permeability based on mix-design parameters. This study proposed a method to combine the beetle antennae search (BAS) and random forest (RF) algorithm to predict the permeability of pervious concrete. Based on the 36 samples designed in the laboratory and 4 key influencing variables, the permeability of pervious concrete can be obtained by varying mix-design parameters by RF. BAS algorithm was used to tune the hyperparameters of RF, which were then verified by the so-called 10-fold cross-validation. Furthermore, the model to combine the BAS and RF was validated by the correlation parameters. The results showed that the hyperparameters of RF can be tuned by the BAS efficiently; the BAS can combine the conventional RF algorithm to construct the evolved model to predict the permeability of pervious concrete; the cement/aggregate ratio was the most significant variable to determine the permeability, followed by the coarse aggregate proportions.

Highlights

Pervious concrete is similar to conventional concrete but designed without fine aggregates and has a porosity and median pore diameter in the range of 0.15–0.3 and 2–4 mm, respectively [1,2,3,4]
Permeability is the most important functional performance for the pervious concrete, and it has been confirmed to be closely related to the pore structure, which determines the permeation rate per unit area. e permeability is traditionally characterized by the so-called permeability coefficient, and its value is typically between 0.1 and 2 cm/s [12, 13]
Nonconnected related parameters include total porosity, pore diameter, and distribution, and connected related parameters include connected porosity and pore tortuosity [14,15,16]. e total porosity of pervious concrete can be defined as the ratio of the voids volume to the specimen volume, which mainly depends on the ratio of mortar to aggregate and the compactness degree of the concrete, usually between 15% and 25% [17]

Summary

Introduction

Pervious concrete is similar to conventional concrete but designed without fine aggregates (i.e., sand) and has a porosity and median pore diameter in the range of 0.15–0.3 and 2–4 mm, respectively [1,2,3,4]. E pore tortuosity increases with the decrease of aggregate size and the increase of mortar fluidity [22] It can be confirmed from the previous research that the parameters affecting the permeability of pervious concrete have been studied, including aggregate size and mortar content [14, 17, 19]. To plant the database applied to the proposed BRF method, varying mixes of pervious concrete were designed considering four parameters (aggregate proportion %: 9.5∼13.2 mm; aggregate proportion: 4.75∼9.5 mm; aggregate proportion %: 2.36∼4.75 mm; cement-aggregate ratio) that have significant effects on the permeability coefficient according to the investigation based on known literature.

Methodology

Experimental Testing and Model Validation

Model Validation

Results and Discussion