The article presents laboratory tests on the impact of the mixing water content used in the preparation of fresh mortar on the flexural and compressive strength of one of the dry-mix mortars produced by a leading European producer and dedicated to bricklaying with clinker elements. The development of these parameters in relation to curing time was also analyzed. The mortar samples were prepared from a factory-made mortar mix using 4.0 L (the value recommended by the mortar manufacturer), 4.5 L, and 5 L of water per 25 kg bag of ready-made, pre-mixed dry mortar mix. All samples were tested in five series after 5, 9, 14, 21, and 28 days of sample curing. The results of these tests showed that the use of 6 and 18% more mixing water than recommended by the manufacturer (4.5 and 5 L per bag) adversely affected the basic mechanical parameters of the tested mortar. Moreover, it was found that the highest compressive strength values were obtained after 21 days of curing and not after 28 days as usual. It was also found that hardening time and higher than recommended water content adversely affected the bending strength of the mortar.
Prominence of concrete is characterized by its high mechanical properties and durability, combined with multifunctionality and aesthetic appeal. Development of alternative eco-friendly or multipurpose materials has conditioned improvements in concrete mix design to optimize concrete production speed and price, as well as carbon footprint. Artificial neural networks represent a new and efficient tool in achieving optimal concrete mixtures according to its intended function. This paper addresses concrete mix design and the application of artificial neural networks (ANNs) for self-sensing concrete. The authors review concrete mix design methods and the development of ANNs for prediction of properties for various types of concrete. Furthermore, the authors present developments and applications of ANNs for prediction of compressive strength and flexural strength of carbon nanotubes/carbon nanofibers (CNT/CNF) reinforced concrete using experimental results for the learning process. The goal is to bring the ANN approach closer to a variety of concrete researchers and possibly propose the implementation of ANNs in the civil engineering practice.
In typical technical applications, steel components are usually connected by welding or with mechanical connectors. An alternative solution, typical in the aviation and automotive industry, but not widespread in engineering structures, is to join thin sheet metal using adhesives. The article presents an experimental study of adhesive joints used in overlap connections subjected to static tension. A methacrylate adhesive, selected experimentally from a range of adhesives, which combines the optimum strength and strain properties, was tested. The laboratory tests were carried out on double-lap specimens made of high-strength Domex 700 steel. On the basis of the experimental results, the behavior of the specimens and their failure mechanism, depending on the anchorage lengths used (200, 300 and 400 mm), are described. The tests confirmed the effectiveness of the selected methacrylate adhesive in a practical application. It was shown that with the appropriate anchorage length (adequate to the type of steel components and the joint geometry) between 300 and 400 mm, the capacity of the adhesive joint is higher than the capacity of a single steel component. Two types of specimen behavior were recognized: Quasi-brittle, which occurs at the anchorage length of 200 mm, and ductile, observed for 300 mm and 400 mm anchoring. In addition, thanks to the optical measurement method used, a detailed strain distribution on the specimen surface was determined. The data will be used for subsequent validation of an analytical and numerical model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.