Abstract:
Nowadays, lightweight aggregate concrete is becoming more popular due to its versatile properties. It mainly helps to reduce the dead loads of the structure, which ultimately reduces design load requirements. The widespread use of lightweight aggregate concrete in Pakistan poses a significant challenge in identifying an optimized mix that meets the necessary requirements while keeping costs manageable. As the concrete matrix typically comprises 50 to 60% aggregate, we opted to replace the traditional natural aggregate with artificial lightweight expanded clay aggregate to improve the performance of the concrete. To achieve this, we selected five prominent and largely untapped clay fields in Pakistan. The selected clay fields include Nandipur, Multan, Mirpur, Sibbi, and DIK. After essential geotechnical characterization, the collected soil samples of chosen fields were chemically analyzed using X-ray diffraction and X-ray fluorescence tests, whereas thermal stability was assessed using thermogravimetric analysis. The characterized soil was used in the synthesis of ALECA through 120 different mixes recipes designed by varying pellet sizes, and the dose of admixed fly ash and kerosene oil. Nandipur clay turned out to be ideal for bloating, with a bloating index of 33.33% and a loose bulk density of 0.39 g/cm3. To solve the problem of mix design for lightweight concrete, a Machine learning-based application was developed and tested on a dataset of 420 data points. The application reduced the need for time-consuming experimental trials and allowed for the selection of the three lightest mixes. The suitability of these mixes for non-structural panels was tested according to ASTM guidelines and they met all requirements specified by ASTM. Finally, a cost comparison study was conducted on a selected building using ALECA infill panels versus brick infill. The results showed that using ALECA infill panels reduced overall construction costs by 16% compared to a building constructed with brick infill. Furthermore, BIM-based modeling was performed to evaluate the heating and cooling load demands and environmental performance of the building. The results
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revealed that the use of ALECA infill panels not only provided a cost-effective solution but also resulted in sustainable environmental performance.