Prediction of in-situ strain sensing efficiency self-sensing cementitious composites using machine learning (ML) requires a large, representative, consistent, and accurate dataset. However, such large experimental dataset is not readily available. Moreover, the success ML approach depends on its ability to abide by fundamental laws physics. To address these challenges this paper synergistically...

© 2012 IBRACON This paper aims to present the experimental results involving the use of nanoindentation measurements and prediction of macroscale elastic properties of high performance cementitious composites (HPCC). The elastic properties of HPCC mixture were evaluated at different length scales by nanoindentation (microscale), and elastic moduli and compressive strength tests (macroscale). Th...

Advanced engineered matrix composites (EMCs) require that the coefficient of thermal expansion (CTE) of the engineered matrix (EM) matches those of the fiber reinforcements as closely as possible in order to reduce thermal compatibility strains during heating and cooling of the composites. The present paper proposes a general concept for designing suitable matrices for long fiber reinforced com...

Thermal insulating composites help to reduce the total power consumption in a building by creating a barrier between external and internal environment. Such composites can be used in the roofing tiles or wall panels for exterior surfaces. This study purposes to develop lightweight cement-based composites for thermal insulating applications. Waste materials like silica fume (an industrial by-pro...