• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.3
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• pp.305-312
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• 2017

This paper presents a laboratory investigation into the effects of fillers using industrial by-product such as coal ash, IGCC slag on properties of hot-mixed asphalt concrete variation with filler content. For comparison, existing mixture with lime and dust have also been considered. Marshall and flow test has been considered for the purpose of mix design as well as evaluation of mixture. Other performance tests such as indirect tensile strength test, tensile strength ratio(moisture susceptibility), dynamic stability have also been carried out variation with filler content. It is observed that the mixes with industrial by-product exhibit conform with quality standard. Therefore, it has been recommended to utilize industrial by-product based on fly ash wherever available, not only reducing the produce cost but also partly solve the industrial by-product utilization and disposal problem.

• Smart Structures and Systems
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• v.22 no.4
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• pp.433-440
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• 2018

Pavements porous concrete is a noble structure design in the urban management development generally enabling water to be permeated within its structure. It has also capable in the same time to cater dynamic loading. During the technology development, the quality and quantity of waste materials have led to a waste disposal crisis. Using recycled materials (secondary) instead of virgin ones (primary) have reduced landfill pressure and extraction demanding. This study has reviewed the waste materials (Recycled crushed glass (RCG), Steel slag, Steel fiber, Tires, Plastics, Recycled asphalt) used in the pavement porous concretes and report their respective mechanical, durability and permeability functions. Waste material usage in the partial cement replacement will cause the concrete production cost to be reduced; also, the concretes' mechanical features have slightly affected to eliminate the disposal waste materials defects and to use cement in Portland cement (PC) production. While the cement has been replaced by different industrial wastes, the compressive strength, flexural strength, split tensile strength and different PC permeability mixes have depended on the waste materials' type applied in PC production.

• International Journal of Highway Engineering
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• v.17 no.1
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• pp.17-24
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• 2015

PURPOSES : Recently, crack, rutting, and stripping problems from the surface of asphalt pavements in National highway are observed and they affect the drivers to feel uncomfortable on the road. Surface treatments are recommended to use in distressed pavements due to cost-effective, and improvement of surface performance. The purpose of this study is to evaluate the performance of micro-surfacing and polymer slurry seal treatments for distressed asphalt pavements. METHODS : Surface conditions and friction resistance are evaluated for asphalt pavements treated with micro-surfacing and polymer slurry seal mixes in National highway 30 line and 34 line. Visual observation is conducted and surface performance is measured by PES (Performance Evaluation Surveyor) in terms of crack ratio, rutting and IRI(International Roughness Index). BPN(British Pendulum Number) is measured by BPT(British Pendulum Tester) to evaluate the friction resistance in the field. RESULTS : The surface evaluation results are presented for asphalt pavement treated with micro-surfacing and polymer slurry seal treatments in National highway 30 line and 34 line. Based on the visual observation, micro-surfacing and polymer slurry seal treatments show better improvements in terms of cracks and stripping. Based on the surface conditions measured by PES vehicle, the surface performance of micro-surfacing treatments improves from 53.3% to 54.2% and the surface performance of polymer slurry seal treatments improves from 21.6% to 59.7%. However, the friction resistance of both micro-surfacing and polymer slurry seal treatments decreases from 2.5% to 6.7%. Further, it should be verified to produce the surface exposed with aggregates during the construction process of both treatment methods in the field. CONCLUSIONS : Based on the performance evaluation results in the filed, the surface performance of asphalt pavement treated with micro-surfacing and polymer slurry seal treatments improves from 21.6% to 59.7%. While, the friction resistance of asphalt pavement treated with micro-surfacing and polymer slurry seal treatments does not improve. It can be concluded that current micro-surfacing and polymer slurry seal treatments would improve surface performance but would not improve the friction resistance.

• Advances in materials Research
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• v.13 no.1
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• pp.63-86
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• 2024

Asphalt concrete (AC), is a mixture of bitumen and aggregates, which is very sensitive in the design of flexible pavement. In this study, the Marshall stability of the glass and carbon fiber bituminous concrete was predicted by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and M5P Tree machine learning algorithms. To predict the Marshall stability, nine inputs parameters i.e., Bitumen, Glass and Carbon fibers mixed in 100:0, 75:25, 50:50, 25:75, 0:100 percentage (designated as 100GF:0CF, 75GF:25CF, 50GF:50 CF, 25GF:75CF, 0GF:100CF), Bitumen grade (VG), Fiber length (FL), and Fiber diameter (FD) were utilized from the experimental and literary data. Seven statistical indices i.e., coefficient of correlation (CC), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Scattering index (SI), and BIAS were applied to assess the effectiveness of the developed models. According to the performance evaluation results, Artificial neural network (ANN) was outperforming among other models with CC values as 0.9147 and 0.8648, MAE values as 1.3757 and 1.978, RMSE values as 1.843 and 2.6951, RAE values as 39.88 and 49.31, RRSE values as 40.62 and 50.50, SI values as 0.1379 and 0.2027 and BIAS value as -0.1 290 and -0.2357 in training and testing stage respectively. The Taylor diagram (testing stage) also confirmed that the ANN-based model outperforms the other models. Results of sensitivity analysis showed that the fiber length is the most influential in all nine input parameters whereas the fiber combination of 25GF:75CF was the most effective among all the fiber mixes in Marshall stability.