Abstract
Strength is a major criterion for aggregates which are used in the design of a flexible pavement structure. So, an engineer assumes a certain degree of responsibility for each material to be used, so it is the duty of the engineers in the field to validate the materials by regular tests. The quality of the materials used plays a key role in determining the strength and durability of the infrastructure projects. As flexible pavement contains number of layers among them the surface course being the highest load-bearing layer in the flexible pavement, material like cinder coal is tested for the same. The representation of all the quality indicators added in a single form is called ‘quality index’ which makes it easy to obtain the composite influence of all the quality parameters in that system and also helps to compare the general quality of the aggregate with a unit value. The quality of aggregates was determined by using weighted arithmetic index method and fuzzy approach to judge its potentiality for the surface course. Crushed stone aggregate and cinder coal materials were been used to compare the feasibility for the desired application. Cinder coal is an industrial by-product which is obtained from combustion of coal. Tests were conducted to determine the physical properties of aggregates and cinder coal, and the obtained results were used for calculating the quality index. From this study, it was observed that cinder coal has a net fuzzy value of ‘86%’, which indicates ‘unfit’, whereas for conventional aggregate (crushed stone), it is ‘30.75%’, which indicates ‘good’ for the surface course. Fuzzy value is used to characterize and disseminate uncertainties and inaccuracies in data and functional relationships.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yang, J., Wang, S., Lu, Z., & Lou, S. (2009). Converter slag–coal cinder columns for the removal of phosphorous and other pollutants. Journal of Hazardous Materials, 168.
Smarzewski, P., & Barnat-Hunek, D. (2016). Mechanical and durability related properties of high-performance concrete made with coal cinder and waste foundry sand. Construction and Building Materials.
Khanna, D. R., Singh, S., Saxena, N., Bhutiani, R., Matta, G., & Kulkarni, D. B. (2011). Physico-chemical and microbiological characterization of the groundwater across the city Bareiley (U.P.), India. Journal of Applied and Natural Sciences.
Haque, E., Reza, S., & Ahmed, R. (2018). Assessing the vulnerability of groundwater due to open pit coal mining using DRASTIC model: A case study of Phulbari Coal Mine, Bangladesh. Geosciences Journal.
Zhang, J. C., & Styblinski, M. A. (1995). Yield and variability optimization of integrated circuits. Springer Nature.
Soncim, S. P., De Oliveira, I. C. S., & Santos, F. B. (2019). Development of fuzzy models for asphalt pavement performance. Acta Scientiarum. Technology.
Guo, H., Wang, Y. S., Yang, C., Wang, X. L., Liu, N. N., & Xu, Z. J. (2019). Vehicle interior noise active control based on piezoelectric ceramic materials and improved fuzzy control algorithm. Applied Acoustics.
Zehtabchi, A., Hashemi, S. A. H., & Asadi, S. (2018). Predicting the strength of polymer-modified thin-layer asphalt with fuzzy logic. Construction and Building Materials.
Turki, M., Zarrad, I., Quéneudec, M., & Bouaziz, J. (2017). Prediction performance of compressive strength of cementitious materials containing rubber aggregates and filler using fuzzy logic method. Multidiscipline Modeling in Materials and Structures.
Sadrossadat, E., Heidaripanah, A., & Osouli, S. (2016). Prediction of the resilient modulus of flexible pavement subgrade soils using adaptive neuro-fuzzy inference systems. Construction and Building Materials.
Bhutiani, R., Khanna, D. R., Kulkarni, D. B., & Ruhela, M. (2016). Assessment of Ganga river ecosystem at Haridwar, Uttarakhand, India with reference to water quality indices. Applied Water Science.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ramu, P., Shiva Bhushan, J.Y.V., Shravani, B., Nagarani, I. (2020). Cinder Coal-Aggregate Quality Index (AQI) Appraisal Based on Weighted Arithmetic Index Method and Fuzzy Logic. In: Saride, S., Umashankar, B., Avirneni, D. (eds) Advances in Geotechnical and Transportation Engineering . Lecture Notes in Civil Engineering, vol 71. Springer, Singapore. https://doi.org/10.1007/978-981-15-3662-5_13
Download citation
DOI: https://doi.org/10.1007/978-981-15-3662-5_13
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-3661-8
Online ISBN: 978-981-15-3662-5
eBook Packages: EngineeringEngineering (R0)