The purpose of this qualification work is to study the physical and mechanical behavior of concrete with the addition of 0.5% and 1% coconut fiber, which has been subjected to two chemical treatments to reduce its degradation. The coconut fibers were extracted from the raw material and cut into pieces 4 cm long. Subsequently, the fibers were subjected to two chemical treatments. The first involved immersing the fibers in 4% sodium hydroxide (NaOH) solution, and the second treatment involved coating them with gum arabic and silica fume. A total of 50 samples of fibers were collected in their natural and post-treated state to be tested. The dosage was prepared for design strengths of 210 and 240 kg/cm² (20.59 and 23.54 MPa), so that the percentages of 0.5% and 1% volume of coconut fiber, for the two treatments selected, replaced the respective volume of coarse aggregates. The cylinders with 1% addition of fibers had the best performance for the design strength of 20.59 MPa, including the cylinders without fibers. Those with 0.5% addition of fibers presented better performance for the 23.54 MPa dosage, although this was lower than the cylinders without fibers. In all cases, the cylinders with NaOH-treated fibers outperformed their counterparts with fibers treated with gum arabic and silica fume. Finally, a CO₂ balance was determined, and an environmental gain up to 14 kg in CO₂ emissions was established for each cubic meter of composite concrete.

This study describes a slender reinforced concrete shear wall experimental test under in‐plane cyclic lateral load, and the development of an analytical model which uses the fiber method approach to consider hysteretic nonlinear constitutive material models behavior. The shear wall tested had bending behavior, since the amount of longitudinal reinforcing bars produced weak bending capacity compared to the shear strength. The analytical model tries to represent global and local behavior of the wall, and its calibration is based on reaching experimental parameters like area enclosed and secant stiffness on every loop. After the analytical model was calibrated, the relation between some performance points and damage states observed during the test is studied.

The objective of this work is to study the physical and mechanical behavior of concrete with the addition of 0.5% and 1.0% of coconut fibers subjected to two chemical treatments in order to reduce their degradation and optimize their use in the elaboration of concrete specimens, which must comply with the standards of the American Society for Testing of Materials (ASTM), the American Concrete Institute (ACI) and the Instituto Ecuatoriano de Normalización (INEN). The coconut fibers were obtained from the raw material by hand and cut to a length of 4 cm. Subsequently, the coconut fibers were subjected to two chemical treatments: The first treatment is the immersion of the coconut fibers in 4% sodium hydroxide (NaOH) solution and the second treatment, the coconut fibers were immersed in gum arabic to consequently coat them with silica fume. A particular dosage was carried out with a proportion of 0.5% and 1.0% volume of coconut fiber for the two chemical treatments, replacing the volume of coarse aggregate. Simple concrete joists were made without fiber and with the post-treatment coconut fibers, which were subjected to flexural tests. The results indicated that the best chemical treatment is sodium hydroxide with a concentration of 4% and 1.0% coconut fiber for strengths of 210 kg/cm² and 240 kg/cm². In general, the joists with coconut fiber treated with sodium hydroxide outperformed the fibers treated with gum arabic and silica fume.

This study introduces a general procedure to analyze the structural vulnerability of large areas applied to an unusual problem. Thus, the vulnerability of a whole neighborhood to two simultaneous extreme events has been analyzed. For this task, the Multi-Criteria Decision Making analysis based on experts' judgment has been an excellent option to be used, but it has some drawbacks. For example, it is difficult to make a judgment for every house, especially when there are uncommon problems. Then, freeware has been used for Machine Learning (ML) methods in order to induce every building's performance. Moreover, in order to have a more accurate result in ML, case-based decision theory has been studied to help experts by creating structural analyses’ examples of vulnerability levels. Finally, the Fuzzy Logic Method has been employed to convert the criteria results into smoother numerical levels and to include the uncertainty of experts' judgments. Therefore, an algorithm that includes the interaction with the experts has been developed. Here, the justification for using all those procedures is shown, and it is also demonstrated that they can be applied with freeware. Copyright © 2021 Praise Worthy Prize - All rights reserved.