Effect of Using Copper Tailings as Replacement of Fine Aggregate for Concrete Pavement

2021 ◽  
pp. 91-101
Author(s):  
Meng-Yao Gao ◽  
Sung-Ching Chen ◽  
Wei-Ting Lin
Keyword(s):  
Concrete Pavement ◽  
Fine Aggregate ◽  
Copper Tailings

The impact of fine aggregate characteristics on asphalt concrete pavement design life

2011 ◽  
Vol 12 (2) ◽  
pp. 101-109 ◽  
Author(s):  
Tamer M. Breakah ◽  
Jason P. Bausano ◽  
R. Christopher Williams ◽  
Stan Vitton
Keyword(s):  
Asphalt Concrete ◽  
Concrete Pavement ◽  
Pavement Design ◽  
Fine Aggregate ◽  
Design Life ◽  
Asphalt Concrete Pavement ◽  
The Impact

scholarly journals Classification-Based Regression Models for Prediction of the Mechanical Properties of Roller-Compacted Concrete Pavement

2020 ◽  
Vol 10 (11) ◽  
pp. 3707 ◽  
Author(s):  
Ali Ashrafian ◽  
Mohammad Javad Taheri Amiri ◽  
Parisa Masoumi ◽  
Mahsa Asadi-shiadeh ◽  
Mojtaba Yaghoubi-chenari ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Regression Models ◽  
Mechanical Characteristics ◽  
Concrete Pavement ◽  
Supplementary Cementitious Materials ◽  
Fine Aggregate ◽  
Roller Compacted Concrete ◽  
Interaction Detection ◽  
Model Tree

In the field of pavement engineering, the determination of the mechanical characteristics is one of the essential processes for reliable material design and highway sustainability. Early determination of the mechanical characteristics of pavement is essential for road and highway construction and maintenance. Tensile strength (TS), compressive strength (CS), and flexural strength (FS) of roller-compacted concrete pavement (RCCP) are crucial characteristics. In this research, the classification-based regression models random forest (RF), M5rule model tree (M5rule), M5prime model tree (M5p), and chi-square automatic interaction detection (CHAID) are used for simulation of the mechanical characteristics of RCCP. A comprehensive and reliable dataset comprising 621, 326, and 290 data records for CS, TS, and FS experimental cases was extracted from several open sources in the literature. The mechanical properties are determined based on influential input combinations that are processed using principle component analysis (PCA). The PCA method specifies that volumetric/weighted content forms of experimental variables (e.g., coarse aggregate, fine aggregate, supplementary cementitious materials, water, and binder) and specimens’ age are the most effective inputs to generate better performance. Several statistical metrics were used to evaluate the proposed classification-based regression models. The RF model revealed an optimistic classification capacity of the CS, TS, and FS prediction of the RCCP in comparison with the CHAID, M5rule, and M5p models. Monte-Carlo simulation was used to verify the results in terms of the uncertainty and sensitivity of variables. Overall, the proposed methodology formed a reliable soft computing model that can be implemented for material engineering, construction, and design.

scholarly journals PENGGUNAAN ABU BATU KARANG SEBAGAI FILLER DAN PASIR BESI SEBAGAI AGREGAT HALUS TERHADAP PARAMETER MARSHALL PADA CAMPURAN ASPAL AC-BC

Teras Jurnal ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 179
Author(s):  
Said Jalalul Akbar ◽  
Wesli Wesli ◽  
Lis Ayu Widari
Keyword(s):  
Asphalt Concrete ◽  
Coarse Aggregate ◽  
Asphalt Mixture ◽  
Concrete Pavement ◽  
Fine Aggregate ◽  
Asphalt Content ◽  
The Difference ◽  
Asphalt Concrete Pavement

<p align="center"><strong>Abstrak</strong></p><p class="11daftarpustaka"> </p><p>Campuran beraspal panas adalah kombinasi antara agregat yang dicampur merata dan dilapisi oleh aspal. Bahan penyusun dari campuran AC-BC hampir sama dengan bahan penyusun campuran aspal beton lainnya yaitu agregat halus, agregat kasar, <em>filler </em>dan aspal, yang membedakan adalah komposisi gradasi masing-masing lapisan. Penelitian ini membahas mengenai pengaruh penggantian Filler pada perkerasan jalan aspal beton AC-BC. Adapun tujuan dari penelitian ini adalah untuk mengetahui bagaimana pengaruh penggunaan<em> </em>Abu batu karang<em> </em>sebagai <em>Filler </em>dan pasir besi sebagai agregat halus terhadap karakteristik Marshall terhadap campuran Aspal AC-BC (<em>Asphalt Concrete – </em><em>Binder Course</em>) terhadap stabilitas dengan metode Spesifikasi Umum Bina Marga 2010 Revisi 3, Benda uji yang didapatkan dari kadar aspal optimumnya adalah sebesar 6,2 % dan untuk benda uji penambahan variasi yang digunakan adalah abu batu karang dan pasir besi  25% - 50% -75% - 100%. Adapun Hasil dari pengujian di laboratorium di dapatkan hasil grafik yang naik turun, peningkatan nilai stabilitas didapat dari penambahan kadar variasi 25%, 50%, 75%, dan mengalami penurunan pada penambahan 100% variasi pasir besi dan abu batu karang, sedangkan nilai Density meningkat pada variasi 100%,  VMA , VIM dan FLOW dengan penambahan<em> </em>pasir besi dan abu batu karang menurun pada variasi 50%-100%, sedangkan VFA, MQ  terjadi Peningkatan yang tidak terlalu signifikan pada variasi 100%. Maka dapat disimpulkan variasi penambahan abu batu karang dan dan pasir besi  sebagai pengganti <em>filler</em> dan penganti agregat halus memenuhi spesifikasi bina marga 2010 revisi 3.</p><p><em> </em></p><p>Kata Kunci:<em> Spesifikasi 2010 rev 3, </em><em>Filler, Agregat halus,</em><em> </em><em>Parameter Marshall</em><em></em></p><p align="center"><strong> </strong></p><p align="center"><strong> </strong></p><p align="center"><strong>Abstract</strong></p><p class="11daftarpustaka"> </p><p class="11daftarpustaka">Hot asphalt mixture is a combination of aggregates that are mixed evenly and coated with asphalt. The composition of AC-BC mixture is almost the same as the composition of other concrete asphalt mixers, namely fine aggregate, coarse aggregate, filler and asphalt, the difference is the gradation composition of each layer. This study discusses the effect of Filler replacement on AC-BC asphalt concrete pavement. The purpose of this research is to find out how the influence of the use of coral ash as fillers and iron sand as fine aggregate on the Marshall characteristics of the Asphalt Concrete - Binder Course asphalt mixture against stability with the General Reinforcement 2010 Revised 3 General Specifications method, The specimens obtained from the optimum asphalt content is 6.2% and for specimens the addition of variations used is rock ash and iron sand 25% - 50% -75% - 100%. As for the results of testing in the laboratory graph results get up and down, increasing the value of stability obtained from adding levels of variation 25%, 50%, 75%, and decreased in the addition of 100% variation of iron sand and rock ash, while the Density value increased at variations of 100%, VMA, VIM and FLOW with the addition of iron sand and coral ash decreased at a variation of 50% -100%, while VFA, MQ occurred a not too significant increase at 100% variation. Then it can be concluded that variations in the addition of coral ash and iron sand as a substitute for filler and substitute for fine aggregate meet the specifications of the 2010 revision 3.</p><p class="11daftarpustaka">Keywords: 2010 rev 3 specification, filler, fine aggregate, Marshall parameters</p>

scholarly journals Classification-Based Regression Models for Prediction of Mechanical Properties of Roller Compacted Concrete Pavement

2020 ◽  
Author(s):  
Ali Ashrafian ◽  
Mohammad Javad Taheri Amiri ◽  
Mahsa Asadi-shiadeh ◽  
Isa Yaghoobi-chenari ◽  
Amir Mosavi ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Regression Models ◽  
Mechanical Characteristics ◽  
Concrete Pavement ◽  
Supplementary Cementitious Materials ◽  
Fine Aggregate ◽  
Roller Compacted Concrete ◽  
Interaction Detection ◽  
Model Tree

In the field of pavement engineering, the determination of the mechanical characteristics is one of the essential process for reliable material design and highway sustainability. Early determination of mechanical characteristics of pavement is highly essential for road and highway construction and maintenance. Tensile strength (TS), compressive strength (CS) and flexural strength (FS) of roller compacted concrete pavement (RCCP) are very crucial characteristics as they are necessitated for many data from mixture proportions as input variables. In this research, the classification-based regression models named Random Forest (RF), M5rule model tree (M5rule), M5prime model tree (M5p) and Chi-square Automatic Interaction Detection (CHAID) are developed for simulation of the mechanical characteristics of RCCP. A comprehensive and reliable dataset comprising 621, 326 and 290 data records for CS, TS and FS experimental cases extracted from several open sources over the literature. The mechanical properties are developed based on influential inputs combination that processed using Principle Component Analysis (PCA). The applied PCA method as feature selection is specified that volumetric/weighted content forms of experimental variables (e.g., coarse aggregate, fine aggregate, supplementary cementitious materials, water and binder) and specimens&rsquo; age are the most effective inputs to generate the better performances. Several statistical metrics are measured to evaluate proposed classification-based regression models. RF model revealed an optimistic classification capacity of the CS, TS and FS prediction of the RCCP in comparison with the CHAID, M5rule, and M5p models. The research is extended for the results verification using Monte-carlo model for the uncertainty and sensitivity of variables importance analysis. Overall, the proposed methodology indicated a reliable soft computing model that can be implemented for the material engineering construction and design.

Early Detection of Honeycombs in Concrete Pavement Using GPR

2021 ◽  
Vol 35 (1) ◽  
pp. 04020138
Author(s):  
Theresa McCabe ◽  
Ece Erdogmus ◽  
Antony Kodsy ◽  
George Morcous
Keyword(s):  
Early Detection ◽  
Concrete Pavement

Effect of Copper Slag as a Fine Aggregate on the Durability Characteristics of High-Performance Concrete (HPC) Containing Silica Fume

2020 ◽  
Vol 07 (02) ◽  
pp. 1-10
Author(s):  
Rizwan Ahmad Khan ◽  
Keyword(s):  
Silica Fume ◽  
High Performance ◽  
High Performance Concrete ◽  
Copper Slag ◽  
Chloride Penetration ◽  
Interfacial Transition Zone ◽  
Fine Aggregate ◽  
Fresh Properties ◽  
Fine Aggregates ◽  
Effect Of Copper

This paper investigates the fresh and durability properties of the high-performance concrete by replacing cement with 15% Silica fume and simultaneously replacing fine aggregates with 25%, 50%, 75% and 100% copper slag at w/b ratio of 0.23. Five mixes were analysed and compared with the standard concrete mix. Fresh properties show an increase in the slump with the increase in the quantity of copper slag to the mix. Sorptivity, chloride penetration, UPV and carbonation results were very encouraging at 50% copper slag replacement levels. Microstructure analysis of these mixes shows the emergence of C-S-H gel for nearly all mixes indicating densification of the interfacial transition zone of the concrete.

Surface Wear of Concrete Pavement

2018 ◽  
pp. 125-128
Author(s):  
Atul D. Runwal ◽  
Ankit P. Thakare ◽  
Parikshit P. Thakare ◽  
Sagar Jagatap ◽  
Abhijit Warudkar
Keyword(s):  
Concrete Pavement ◽  
Surface Wear
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