Study on concrete proportioning methods: a qualitative and economical perspective

2021 ◽  
Vol 12 (1) ◽  
pp. 20
Author(s):  
Shoib Bashir Wani ◽  
Tahir Hussain Muntazari ◽  
Nusrat Rafique
Keyword(s):  
Design Method ◽  
Concrete Strength ◽  
Performance Criteria ◽  
Mix Design ◽  
Design Parameters ◽  
Fine Aggregate ◽  
Aggregate Content ◽  
Concrete Mix Design ◽  
Concrete Mix ◽  
Moderate Climate

The various approaches, established for concrete mix design, are not universal because design mixes are explicit to local climate, available materials, and type of exposure. The new-generation mix design method should be developed based on the performance criteria. The concrete strength obtained from the designed concrete mix and optimum cement content should not be considered as the only parameter for the suitability of the concrete mix. This study was carried to compare the proportioning of concrete mixes obtained by following procedures of Indian Standard (IS), American Concrete Institute (ACI) and British Standard (BS) of concrete mix design without the use of admixtures to validate for use in a moderate climate like Kashmir, India. The concrete mixes have been prepared with the necessary 28 days resistance in compression as “15 MPa, 20 MPa, 25 MPa, 30 MPa and 35 MPa”. The assessment of water-cement (w/c) ratio; cement, water, fine aggregate (FA) and coarse aggregate (CA) proportion was carried. The w/c ratio among all formulated mixes is significantly high in the BS method and low for IS method. The BS method uses less quantity and IS method uses the maximum quantity of cement. In addition, the ratio of total aggregate content (TAC) and the aggregate-cement ratio is higher in BS design method as compared to IS and ACI design methods. The aggregate content in ACI mix design appears to be consistent and it added to the relative high compressive strength. The specimens cast following BS guidelines failed to attain the target mean strength (TMS) due to a higher volume of aggregate content, high w/c proportion, less quantity of cement in the mix. The specimens cast by ACI and IS mix design upon compression testing showed higher results than the calculated TMS. The cost analysis per cubic meter of concrete revealed that IS and ACI mix proportioning are expensive than BS method. The IS procedure results in dense concrete followed by ACI procedure. It is expected that with a comprehensive investigation on selected design parameters concentrating more on local challenges, the present study will floor the way for the development and adoption of performance-based design mix selection for moderate climate.

scholarly journals Decision Support Model for Design of High-Performance Concrete Mixtures Using Two-Phase AHP-TOPSIS Approach

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Mohd. Ahmed ◽  
M. N. Qureshi ◽  
Javed Mallick ◽  
Mohd. Abul Hasan ◽  
Mahmoud Hussain
Keyword(s):  
High Performance ◽  
High Performance Concrete ◽  
Design Method ◽  
Design Methods ◽  
Mix Design ◽  
Design Parameters ◽  
Two Phase ◽  
Concrete Mix Design ◽  
Concrete Mix ◽  
Topsis Approach

Concrete mix design is the science to obtain concrete proportions of cement, water, and aggregate, based on the particular concrete design method and their mix design parameters. However, the suitability of concrete proportion for high-performance concrete depends on resulting mix factors, namely, water, cement, fine aggregate, and coarse aggregate ratios. This paper implements the multicriteria decision-making techniques (MCDM) for ranking concrete mix factors and representative mix design methods. The study presents a framework to identify critical mix factors found from the concrete mix design methods for high-performance concrete using the two-phase AHP and TOPSIS approach. Three methods of concrete mix design, namely, American Concrete Institute (ACI) mix design method, Department of Energy (DOE) method, and Fineness Modulus (FM) method, are considered for ranking mix design methods and the resulting mix factors. Three hierarchy levels, having three criteria and seven subcriteria, and three alternatives are considered. The present research is attempted to provide MCDM framework to rank the concrete mix guidelines for any given environment such as concrete under sulphate and chloride attack and for evolving the performance-based concrete mix design techniques. Sensitivity and validation analysis is also provided to demonstrate the effectiveness of the proposed approach.

scholarly journals Concrete Mix Design for Completely Recycled Fine Aggregate by Modified Packing Density Method

Materials ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 3535
Author(s):  
Yibo Yang ◽  
Baixi Chen ◽  
Yan Su ◽  
Qianpu Chen ◽  
Zhiji Li ◽  
...  
Keyword(s):  
Packing Density ◽  
Unit Price ◽  
Mix Design ◽  
Concrete Mixture ◽  
Fine Aggregate ◽  
Density Method ◽  
Concrete Mix Design ◽  
Recycled Fine Aggregate ◽  
Concrete Mix ◽  
Aggregate System

The undesirable properties of conventional recycled fine aggregate (RFA) often limit its application in the construction industry. To overcome this challenge, a method for preparing completely recycled fine aggregate (CRFA), which crushes all concrete waste only into fine aggregate, was proposed. The obtained CRFA had high apparent density, and its water absorption was lower than that of the conventional RFA. To take advantage of the CRFA, this paper introduced the modified packing density method for the CRFA concrete mix design. The modified packing density method took account of the powder with a particle size of smaller than 75 μm in the CRFA and balanced both the void ratio and the specific surface area of the aggregate system. Concrete (grade C55) was prepared using the CRFA to validate the feasibility of the proposed method. The unit price of the prepared CRFA concrete was around 12.7% lower than that of the natural aggregate concrete. Additionally, the proposed procedure for the concrete mixture design could recycle all concrete waste into the new concrete and replace all the natural fine aggregate in the concrete mixture.

Study Strength of Recycled Concrete Mix Design

2013 ◽  
Vol 423-426 ◽  
pp. 1072-1075
Author(s):  
Xin Hua Zhang ◽  
Sai Tian ◽  
Huai Ru Dai ◽  
Wei Lin ◽  
Zhi Chun Yao ◽  
...  
Keyword(s):  
Concrete Strength ◽  
Recycled Concrete ◽  
Recycled Aggregate Concrete ◽  
Recycled Aggregate ◽  
Mix Design ◽  
Replacement Rate ◽  
Ordinary Concrete ◽  
Concrete Mix Design ◽  
Waste Production ◽  
Concrete Mix

This paper discusses waste production of recycled aggregate concrete is used as the recycled concrete, experiment with different recycled aggregate instead of natural aggregate, the ratio of recycled concrete workability and compressive strength etc performance compared with ordinary concrete, analyzing the change of the recycled aggregate replacement rate on the influence of concrete strength.

Development of Concrete Mix Design Nomograph Containing Polyethylene Terephtalate (PET) as Fine Aggregate

2013 ◽  
Vol 701 ◽  
pp. 12-16 ◽  
Author(s):  
Mohd Irwan Juki ◽  
Khairunnisa Muhamad ◽  
Mahamad Mohd Khairil Annas ◽  
Koh Heng Boon ◽  
Norzila Othman ◽  
...  
Keyword(s):  
Tensile Strength ◽  
Compressive Strength ◽  
Splitting Tensile Strength ◽  
Mix Design ◽  
Fine Aggregate ◽  
Cement Ratio ◽  
Water Cement Ratio ◽  
Concrete Mix Design ◽  
Mix Proportion ◽  
Concrete Mix

This paper describes the experimental investigation to develop the concrete mix design Nomograph for concrete containing PET as fine aggregate. The physical and mechanical properties were determined by using mix proportion containing 25%, 50% and 75% of PET with water cement ratio (w/c) 0.45, 0.55 and 0.65. The data obtained showed that the inclusion of PET aggregate reduce the strength performances of concrete. All the data obtained were combined into one single graph to develop a preliminary mix design nomograph for PET concrete. The nomograph consist of ; relationship between compressive strength and water cement ratio; relationship between splitting tensile strength water cement ratio; relationship between splitting tensile strength and PET percentage and relationship between compressive strength and PET percentage. The mix design nomograph can be used to assists in selecting the proper mix proportion parameters based on the criteria required.

scholarly journals SIFAT DAN KARAKTERISTIK CAMPURAN BETON MENGGUNAKAN BATU PECAH DAN BATU GULI DARI SUNGAI BINJAI

2021 ◽  
Vol 2 (2) ◽  
pp. 239-254
Author(s):  
Johan Oberlyn Simanjuntak ◽  
Ros Anita Sidabutar ◽  
Humisar Pasaribu ◽  
Yetty Riris R Saragi ◽  
Sriyanti Sitorus
Keyword(s):  
Coarse Aggregate ◽  
Construction Material ◽  
Mix Design ◽  
Crushed Stone ◽  
Fine Aggregate ◽  
Normal Concrete ◽  
Concrete Mix Design ◽  
Concrete Mix ◽  
Optimum Type ◽  
Compressive Strength Of Concrete

Concrete is a construction material consisting of a mixture of cement, aggregate, water and with or without admixture if needed. Coarse aggregate and fine aggregate serve as the main filler of concrete as well as reinforcement, while the cement and water mixtured serves as a binder between materials. To find out and study the behavior of each of these concrete constituents, it is necessary to know the characteristics of the materials made as constituents of the concrete. This study was conducted with the aim of comparing the most optimum type of coarse aggregate used and the comparison of the use of cement for coarse aggregate of crushed stone and coarse aggregate of gully originating from North Sumatera area, namely from the Wampu River in Binjai City as a concrete mixture to see its effect on compressive strength of concrete at the same concrete characteristics namely f’c 25 MPa. The results of the normal concrete mix design are obtained by using coarse aggregate of crushed stone and coarse aggregate of boulder in different amounts of cement. The coarse aggregate of crushed stone requires more cement with the amount of cement 411.1 kg/m3 than the coarse aggregate of gum with the amount of cement 388.9 kg/cm3.

scholarly journals Model-Based Adaptive Machine Learning Approach in Concrete Mix Design

Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1661
Author(s):  
Patryk Ziolkowski ◽  
Maciej Niedostatkiewicz ◽  
Shao-Bo Kang
Keyword(s):  
Machine Learning ◽  
Compressive Strength ◽  
Concrete Strength ◽  
Design Methods ◽  
Mix Design ◽  
Engineering Practice ◽  
Concrete Compressive Strength ◽  
Concrete Technology ◽  
Concrete Mix Design ◽  
Concrete Mix

Concrete mix design is one of the most critical issues in concrete technology. This process aims to create a concrete mix which helps deliver concrete with desired features and quality. Contemporary requirements for concrete concern not only its structural properties, but also increasingly its production process and environmental friendliness, forcing concrete producers to use both chemically and technologically complex concrete mixtures. The concrete mix design methods currently used in engineering practice are joint analytical and laboratory procedures derived from the Three Equation Method and do not perform well enough for the needs of modern concrete technology. This often causes difficulties in predicting the final properties of the designed mix and leads to precautionary oversizing of concrete properties for fear of not providing the required parameters. A new approach that would make it possible to predict the newly designed concrete mix properties is highly desirable. The answer to this challenge can be methods based on machine learning, which have been intensively developed in recent years, especially in predicting concrete compressive strength. Machine learning-based methods have been more or less successful in predicting concrete compressive strength, but they do not reflect well the variability that characterises the currently used concrete mixes. A new adaptive solution that allows estimating concrete compressive strength on the basis of the concrete mix main ingredient composition by including two observations for a given batch of concrete is proposed herein. In presented study, a machine learning model was built with a deep neural network architecture, trained on an extensive database of concrete recipes, and translated into a mathematical formula. Testing on four concrete mix recipes was performed, which were calculated according to contemporary design methods (Bolomey and Fuller method), and a comparative analysis was conducted. It was found out that the new algorithm performs significantly better than that without adaptive features trained on the same dataset. The presented algorithm can be used as a concrete strength checking tool for the concrete mix design process.

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