The Influence of Materials on the Mechanical Properties of Ultra-High-Performance Concrete (UHPC): A Literature Review.

Ultra-high-performance concrete (UHPC) is a cementitious composite combining high-strength concrete matrix and fiber reinforcement. Standing out for its excellent mechanical properties and durability, this material has been widely recognized as a viable choice for highly complex engineering projects. This paper proposes (i) the review of the influence exerted by the constituent materials on the mechanical properties of compressive strength, flexural tensile strength, and elastic modulus of UHPC and (ii) the determination of optimal quantities of the constituent materials based on simplified statistical analyses of the developed database.

Influence of the ANN Hyperparameters on the Forecast Accuracy of RAC's Compressive Strength.

The artificial neural networks (ANNs)-based model has been used to predict the compressive strength of concrete, assisting in creating recycled aggregate concrete mixtures and reducing the environmental impact of the construction industry. Thus, the present study examines the effects of the training algorithm, topology, and activation function on the predictive accuracy of ANN when determining the compressive strength of recycled aggregate concrete. An experimental database of compressive strength with 721 samples was defined considering the literature.

Flexural Strength Characteristics of Fiber-Reinforced Cemented Soil.

This work deals with the flexural performance of a soil-cement for pavement reinforced by polypropylene and steel fibers, and the main purpose is to evaluate the effect of different curing times. In this sense, three different curing times were employed to investigate the influence of fibers on the material's behavior at varying levels of strength and stiffness as the matrix became increasingly rigid. An experimental program was developed to analyze the effects of incorporating different fibers in a cemented matrix for pavement applications.