Prediction and optimization of hardened properties of concrete prepared with granite dust and scrapped copper wire using response surface methodology.

Urban growth in the developing world has prompted researchers to seek alternatives to fine aggregate due to the severe environmental impact of extensive natural sand depletion. On top of that, the accumulation of non-biodegradable dumps, solid trash such as scrapped copper wire (SCW), and industrial remnants like granite dust (GD) have reached alarming levels. Therefore, incorporating these two waste materials in concrete offers a potentially sustainable solution.

Prediction and optimization of properties of concrete containing crushed stone dust and nylon fiber using response surface methodology.

Over-extraction of aggregates from natural sources with rapid urbanization as well as massive waste generation in construction industry have imposed the need to utilize waste material as concrete constituent. Crushed Stone Dust (CSD) is such a supplementary material that can be utilized for the production of sustainable concrete. This study attempts to predict and optimize fresh and hardened properties of concrete utilizing CSD as a partial replacement of natural fine aggregate and Nylon Fiber (NF) as fiber reinforcement using Response Surface Methodology (RSM).

Predicting the strength of concrete made with stone dust and nylon fiber using artificial neural network.

Excessive demand of concrete is causing depletion of natural sand resources. Especially, the extraction of river sand negatively affects its surrounding environment. A sustainable solution to this problem can be the proper utilization of waste materials and by-products like stone dust (SD) as fine aggregate replacement in concrete.