Thermal Conductivity of Coconut Shell-Incorporated Concrete: A Systematic Assessment via Theory and Experiment

To minimize the energy consumption and adverse impact of excessive waste accumulation on environment, coconut shell (CA) became a potential (partial) replacement agent for fine aggregates in structural concrete production. Thus, systematic experimental theoretical studies are essential to determine thermal properties such containing optimum level CA. In this view, an artificial neural network (ANN) model, gene expression programming (GEP) response surface method (RS) were used predict optimize desired engineering characteristics some mixes designed with various levels CA inclusion. Furthermore, proposed model’s performance was assessed terms different statistical parameters calculated using ANOVA. The results revealed that mix made 53% as partial aggregate achieved density 2246 kg/m3 conductivity 0.5952 W/mK, which lower than control specimen (0.79 W/mK). p-value less 0.0001 F-value over 147.47, indicating significance all models. It is asserted ANN, GEP, RSM accurate reliable, can further be strong structural–thermal correlation minimal error. brief, composed may beneficial develop environmentally amiable green concrete.