Tecnura

13-26

Authors: Alejandro Duitama Leal, José John Fredy González Veloza, Luis Antonio Castillo López, Javier Hernán Gil Gómez, Rodrigo Elías Esquivel

Objective: this work presents the results obtained in the development of a seismic velocity inversion mo­del. The reference times recorded on the surface are taken and using the inversion model to obtain the initial reference model (hypocenters and velocities), starting from an unknown model. Methodology: A hypothetical reference model is pro­posed containing 64 blocks with interval velocity, 16 recording stations on the surface, and 64 earth­quakes in the center of each block. With this model, the reference arrival times are generated for each ear­thquake registered in each station. The inversion mo­del is made up of two parts: the direct model, which allows calculating the arrival times of the signal regis­tered on the surface according to the hypo-central lo­cation of the earthquake and the velocity of the P and S wave of the medium; and the inverse model, which estimates a model of the velocity of the environment and hypo-central locations of the earthquakes that are the input variables of the direct model. The direct model was developed with the wave equation, while the inverse model was developed by modifying the generalized inverse matrix by introducing a factor called “damping.” Results: The discretization model is based on the finite difference method.. When estimating the values of velocity and hypo-central location with the inverse algorithm, the propagation of the wave is simulated with the direct model, and they are compared with the data of reference times measured on the surface. Depending on the value of the mean square error, we proceed to modify the mean velocities and hypo­centers of the earthquakes. This process is repeated iteratively until the calculated error is less than a to­lerance of 2x10-3s2. Conclusions: It was found that the estimated values of velocity and hypo central locations coincide well for regions closer to the surface, while for deep regions the error is greater compared to the hypothetical re­ference model.

36-46

Authors: Sebastián Macías Gallego, Álvaro Guzmán Aponte, Robison Buitrago Sierra, Juan Felipe Santa Marín

Context: Tetra Pak® is a common material used for the production of food containers. Currently, those containers are recycled by physical separation of the cellulose fibers through a hydro pulped process, but sometimes separating the individual components is not economically viable. This work evaluates an al­ternative process to obtain composites from recycled Tetra Pak®. Methodology: Tetra Pak® used containers were co­llected and cut into small pieces at the laboratory. Then, the containers were hot-pressed to obtain sheets in a manual hydraulic press by using different confi­gurations. Samples were cut, and their tensile stren­gth was evaluated (ASTM D3039). Failure analysis of samples was carried out by FE-SEM to identify issues related to processing and to understand the differen­ces in mechanical properties. Results: The results showed that the lowest tensile strength was 9.5 MPa (type I sample) and the highest tensile strength was 37.4 MPa (type III sample). Conclusions: The results of mechanical tests show that this material can be used for non-structural purposes in the building industry. Failure analysis shows that fiber pull-out and delamination are the most impor­tant failure mechanisms in type I samples. For type III sample, failure was produced by a sequence of intralaminar fractures

62-75

Authors: Edwin Vargas, Kevin Arias, Fernando Rojas, Henry Arguello

Objective: Hyperspectral (HS) imaging systems are commonly used in a diverse range of applications that involve detection and classification tasks. However, the low spatial resolution of hyperspectral images may limit the performance of the involved tasks in such applications. In the last years, fusing the information of an HS image with high spatial resolution multispectral (MS) or panchromatic (PAN) images has been widely studied to enhance the spatial resolution. Image fusion has been formulated as an inverse problem whose solution is an HS image which assumed to be sparse in an analytic or learned dictionary. This work proposes a non-local centralized sparse representation model on a set of learned dictionaries in order to regularize the conventional fusion problem. Methodology: The dictionaries are learned from the estimated abundance data taking advantage of the depth correlation between abundance maps and the non-local self- similarity over the spatial domain. Then, conditionally on these dictionaries, the fusion problem is solved by an alternating iterative numerical algorithm. Results: Experimental results with real data show that the proposed method outperforms the state-of-the-art methods under different quantitative assessments. Conclusions: In this work, we propose a hyperspectral and multispectral image fusion method based on a non-local centralized sparse representation on abundance maps. This model allows us to include the non-local redundancy of abundance maps in the fusion problem using spectral unmixing and improve the performance of the sparsity-based fusion approaches.

85-94

Authors: Adriana Patricia Gallego Torres, Edier Hernán Bustos Velazco, Jaime Duván Reyes Roncancio

Context: This article presents the arguments that su­pport the formulation of a research model from the idea of “guided models,” which allows the designing of routes and methodologies for the approaching, formulating, and solving problems in the training of technologists and engineers. Method: The methodology used was based on groun­ded theory, which allows solving problems and de­velop innovative research through theoretical and methodological categories. Results: It was possible to organize the model with a special emphasis on the generation of monitoring and contrasting matrices as a control mechanism and guide for the researcher. Conclusions: The implications of the incorporation of this model are analyzed in relation to the training purposes of engineering and technology professio­nals, articulated through a progression hypothesis as a reference every researcher will be able to get when analyzing and reviewing their own research processes regardless of the methodology developed.

109-118

Authors: Jorge Andrés Sarmiento-Rojas , Juan Sebastian Gonzalez-Sanabria, Carlos Gabriel Hernández Carrillo

Objective: Construction is one of the fastest growing and most important economic sectors worldwide, mainly due to its impact on job creation, trade in materials and the creation of essential infrastructure for social development. However, the behavior of the global market has recently been immersed in an environment of economic and political uncertainty, causing trade and industrial production to show signs of vulnerability. Despite the unfortunate ones established in the global economy, there will be moderate growth in rankings of developing countries like Colombia in different sectors. Methodology: Consequently, this research focused on analyzing the construction sector starting from its historical impact on Colombian economic development and its relationship with external phenomena, to the evaluation of macroeconomic indicators, supply and demand for capital goods, infrastructure and job creation through the formulation of projects in this sector, which are differential for having a public investment effect in the construction of houses and civil works. Results and conclusions: Likewise, deduce a weak recovery in the general market in relation to the factors surrounding the construction sector, evaluate and focus trends and the impact on the formulation of construction projects in the Colombian economy.