Como una alternativa de solución al problema de la vivienda económica, CORDELICA planteó un proyecto de investigación que se desarrolló en el Laboratorio de Estructuras de la Universidad Católica. En este proyecto se utilizaron muros portantes que no calificaban como confinados ni armados, sino más bien como un sistema mixto, con juntas secas, sobre las cuales apoyaba un techo compuesto por viguetas prefabricadas, domos de concreto vibrado y una losa de concreto vaciado in-si tu.

This research aims to enhance the classification of the rock mass in underground mining, a common problem due to geological alterations that do not fit existing methods. Artificial neural networks are proposed as a solution, which use input/output data to learn and solve problems. The process involves gathering data on rock properties and training the neural networks to identify and classify various types of rock. Once trained, the neural networks can classify the rock mass in real-time during mine design and progression, adapting to different rock types with a low margin of error of 0.279% in determining the RMR index. This research overcomes the limitations of current classification methods, providing a more accurate and reliable solution for the classification of the rock mass in underground mining. In summary, artificial neural networks are utilized to improve the classification of r...