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Item Optimisation of recycled concrete aggregates for cement-treated bases by response surface method(Taylor and Francis Ltd., 2023) Chiranjeevi, K.; Kumar, D.H.; Srinivasa, A.S.; Ravi Shankar, A.U.Sustainability is a primary concern that needs to be addressed since infrastructure development requires significant natural resources. Using Recycled Concrete Aggregates (RCA) for road construction has numerous benefits in saving natural resources and the environment. In the present investigation, the demolition waste is being used for road construction, partially/fully replacing natural aggregates. The Cement Treated Recycled Concrete Aggregate (CTRCA) specimens were prepared at 3%, 5%, and 7% cement with various blends of RCA and Natural Coarse Aggregates (NCA) ranging from 0 to 100%. The strength characteristics in terms of Unconfined Compressive Strength (UCS), Flexural Strength (FS), Elastic Modulus, Indirect Tensile Strength (ITS) and durability tests were conducted on cured samples. Microstructural analysis using Scanning Electronic Microscope (SEM) revealed that the pores and cracks in the old mortar have a detrimental influence on the mechanical properties of CTRCA mixes. However, Energy Dispersive Spectroscopy (EDS) and durability tests have shown positive results. The Response Surface Method (RSM) was utilised to optimise the RCA and cement content in CTRCA mixes. The research resulted in the maximum possible RCA of up to 70% with a cement content of 5.8%, which met the Indian Road Congress (IRC) specifications for Cement Treated Bases (CTB). © 2023 Informa UK Limited, trading as Taylor & Francis Group.Item Processing of laboratory concrete demolition waste using ball mill(Elsevier Ltd, 2023) Rakesh Kumar Reddy, R.; Yaragal, S.C.; Sanjay, V.K.The demand for natural aggregates in the twenty-first century is at an all-time high due to rapid urbanisation and infrastructure development. Finding alternative aggregate materials is a challenge for achieving construction sustainability. Both the depletion of natural resources and the improper disposal of construction and demolition (C&D) waste can be ameliorated by the widespread use of recycled aggregates in construction. Due to the attached mortar, aggregates from C&D waste must be processed before using them in concrete. Various combinations of ball mill processing parameters were used to produce relatively higher-quality aggregates. Water absorption was used as the primary criterion for determining the quality of processed aggregates. The water absorption capacity of recycled coarse aggregate was found to be decreased from 5.8% to 1.5% as a result of effectively removing the attached mortar by employing ball mill processing. Specific gravity, impact, and crushing values are also improved after processing, as discussed and illustrated in this paper. © 2023Item A novel approach for optimizing the processing of recycled coarse aggregates(Elsevier Ltd, 2023) Rakesh Kumar Reddy, R.; Yaragal, S.C.This paper proposes an alternative method for processing the demolition waste into high-quality recycled coarse aggregate using the ball mill. Taguchi's design of experiments based on orthogonal array was used to minimize the number of trials for saving material and time. Experiments were carried out based on L25 orthogonal array with three processing parameters: charge, revolution duration, and aggregate weight with five levels. The revolution speed of the ball mill was set to 60 revolutions per minute. The Taguchi method was then combined with grey relational analysis to achieve the best combination of processing parameters for producing high-quality aggregate. Experimental studies on water absorption, specific gravity, impact value, and abrasion value were used to assess the quality of recycled coarse aggregates. The best combination for each performance characteristic was achieved by using the mean of Signal to Noise ratio graphs. The optimal combination of processing parameter levels to generate superior quality recycled aggregates and the most significant processing parameter were identified based on the response table of means of grey relation grade. © 2023 Elsevier Ltd