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European Journal of Applied Sciences – Vol. 9, No. 6

Publication Date: December 25, 2021

DOI:10.14738/aivp.96.11464. Dorcas, O. A., Aderenle, O. R., & Emmanuel, F. K. (2021). Modelling the Strength Properties of Concrete Containing Construction

Demolition Waste Using Response Surface Methodology and Artificial Neural Network. European Journal of Applied Sciences, 9(6).

646-661.

Services for Science and Education – United Kingdom

Modelling the Strength Properties of Concrete Containing

Construction Demolition Waste Using Response Surface

Methodology and Artificial Neural Network

Oluyemi-Bamitale Ayibiowu Dorcas

School of Engineering & Engineering Technology

Federal University of Technology, Akure, Nigeria

Okanlawon Rufus Aderenle

School of Engineering & Engineering Technology

Federal University of Technology, Akure, Nigeria

Falola Kayode Emmanuel

School of Engineering & Engineering Technology

Federal University of Technology, Akure, Nigeria

ABSTRACT

The study presents a comparative approach between Response Surface

Methodology (RSM) and Artificial Neural Network (ANN) in estimating the

compressive strength and flexural strength of concrete incorporating Construction

Demolition waste. The effects of factor variables such as %RCA (Recycle Concrete

Aggregate as replacement for granite), water-cement ratio, % RFA (Recycled Fine

Aggregate as replacement for sand) and Recycled Concrete Aggregate size were

investigated using the central composite design of response surface methodology.

This same experimental design results were used in training the artificial neural

network. The predicting ability of both methodologies was compared using theRoot

Mean Square Error (RMSE) and the Absolute Average Deviation (AAD). Response

Surface Methodology Model had a RMSE and AAD compressive strength score of

9.74 and 1.6 while the ANN had score of 14.76 and 2.6 for compressive strength.

When compared to Artificial Neural Network, Response Surface Methodology

showed lower predictive error functions for both tensile and compressive strength

predictions, and was found to be more accurate in its ability to predict the strength

properties of CDW concrete.

Keywords: Response surface methodology; Construction and demolition waste; Central

Composite Design; Artificial Neural Network; Strength properties.

INTRODUCTION

Construction and demolition waste (CDW) is waste made up of building materials, debris and

rubble that is generated during the construction, remodeling, restoration or demolition of any

civil structure. These wastes are big and dense, and they take up a lot of space in waste bins,

containers and landfills. Construction and Demolition activities generate massive amounts of

waste, and the accumulation of waste has negative consequences for both environment and

human life. According to research from around the world, C&D trash accounts for 20-30% of

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Dorcas, O. A., Aderenle, O. R., & Emmanuel, F. K. (2021). Modelling the Strength Properties of Concrete Containing Construction Demolition Waste

Using Response Surface Methodology and Artificial Neural Network. European Journal of Applied Sciences, 9(6). 646-661.

URL: http://dx.doi.org/10.14738/aivp.96.11464

solid waste, with concrete and masonry accounting for 70-80% of it. CDW (Construction and

Demolition Waste) is mostly a by-product of fast urbanization. CDW materials offer a high

recycling and reusability potential. Despite its potential, landfilling remains Nigeria

s most

popular waste disposal option. Recycling of building and demolition debris is regulated by law

and policy in industrialized countries, and recycling rates have approached 90%. In Australia,

about 90% of this garbage was recycled. In 2012, Japan

s recycling rate was 99.5%, while

Singapore had the highest recycling rate of 99.9%. Nigeria

s CDW recovery rate is still less than

50%, which is a very low figure.

Nigeria, Africa's most populous country, has a population of about 206 million people. Its

population grew by about 5.5 million people per year. Nigeria is the world's seventh most

populous country, accounting for 2.64 percent of the global population. Many construction

projects are underway in order to meet the rising population's housing needs. Construction

generally relies on the natural environment for raw materials such as wood, sand, timber, and

aggregates, and construction operations generates a considerable amount of garbage. Nigeria

now produces roughly 165-170 million tonnes (MT) of debris yearly, according to government

estimates, and 12-14.7 MT of C & D garbage annually, according to Ministry of Urban

Development estimates. According to Poon & Ng [20], trash generated during construction is

predicted to be between 40 and 60 kg per square meter. Waste generated during rehabilitation

and restoration operations was estimated to be 40-50kg per sqm on a comparable basis. The

destruction of the buildings adds a large amount of C & D trash to the mix. As a result of the

various studies, it can be concluded that a variety of factors influence C & D waste generation,

including demographic factors such as population, rate of urbanization, population density, and

people's socioeconomic status; city age; and construction and demolition patterns and

practices [22]. According to Dajadian and Koch [7], trash can come from a variety of operations

and procedures that occur prior to, during, and after construction.

LITERATURE REVIEW

Concrete is the most widely used construction material on the planet; the raw materials are

readily available in most regions of the world, and it does not require specialized or expensive

gear to make. However, due to the increasing demand, some of the components that make up

the product are becoming scarce and expensive, necessitating the usage of alternative

materials. [5]. In an attempt to aid development in construction materials technology that

provide economical building materials with good quality and standard, studies on the use of by- product waste, such as concrete demolished waste (CDW), as an alternative material for

construction is necessary [5]. Because CDW is made from building debris, it has qualities that

are similar to natural aggregates, such as high water absorption, which can be lowered by

adding tiny granular particles [16]. The use of CDW as a substitute aggregate for concrete

reduces natural aggregate usage as well as landfill difficulties. CDW has been classified as

Recycled Concrete Aggregate (RCA), Recycled Fine Aggregate (RFA), or Recycled Mixed

Aggregate based on its composition (RMA). RCA has been used extensively by studies to

determine its viability in concrete [6; 12].

RSM is a statistical analytic technique in which each response is linked to a collection of factors

in order to assess the influence, relationship, and interaction between the variables and the

response. RSM analysis comprises designing a series of experiments and collecting the

outcomes as responses, then assessing the accuracy and optimizing the variables to get the