Browsing by Author "Viscaíno Cuzco, Mayra Alexandra"

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Análisis comparativo del material proveniente de las canteras “Mollepamba”, “Rubí 2” y cantera Rumipamba de la provincia de Cotopaxi utilizado para la elaboración de base y subbase en la construcción de carreteras
(Universidad Técnica de Ambato. Facultad de Ingeniería Civil y Mecánica, Carrera de Ingeniería Civil, 2024-08) Supe Castro, Jonathan David; Viscaíno Cuzco, Mayra Alexandra
The comparative analysis of the material coming from the quarries “Mollepamba”, “Rubí 2” and “Rumipamba” in the province of Cotopaxi, Ecuador, was carried out due to several problems in the roads surrounding the sector that presented structural deficiencies in the granular base and subbase materials, producing subsidence, fissures, cracks among other problems that affect the trafficability and safety of the roads. The research analyzed the index and mechanical properties of the quarry materials through various laboratory tests to determine if they comply with the Ecuadorian road standard NEVI -12. The moisture content, Atterberg limits, granulometry, maximum density and bearing capacity (CBR) were evaluated. In addition, abrasion resistance, percentage of fractured faces and sulfate wear were tested to determine durability and wear resistance. The test results were compared between the three quarries to identify the suitability of the materials for base and subbase applications. The results show that the materials from the Mollepamba quarry met all the requirements of the Ecuadorian road standard NEVI-12, proving that they are suitable for use in road construction. The materials from the Rumipamba and Rubí 2 quarries comply with most of the parameters evaluated, indicating their good quality. These results emphasize the importance of carrying out thorough evaluations of the materials before using them in road projects.
Caracterización del comportamiento frente al fuego de la madera con recubrimiento de barniz utilizados en obra civil
(Universidad Técnica de Ambato. Facultad de Ingeniería Civil y Mecánica, Carrera de Ingeniería Civil, 2025-02) Yugcha Lema, Jonathan Andrés; Viscaíno Cuzco, Mayra Alexandra
The use of wood coated with varnishes for flooring and wall coverings is widespread in the construction industry. However, its behavior in the event of a fire has been little studied, raising significant questions about its performance in fire scenarios. This research aims to characterize the behavior of Mascarey wood under fire conditions, considering its physical, mechanical, and thermal conductivity properties in three states: natural, coated with Monto brand high-gloss varnish, and coated with Condor brand Espengloss floor lacquer. Physical properties such as color and density were evaluated according to ASTM D 1535 and ASTM D2395 standards, respectively. Mechanical properties were assessed through parallel compression, perpendicular compression, and hardness tests, following the procedure described in ASTM 143-94. Additionally, a fire reaction test was conducted according to the NTE INEN ISO 11925 – 2 standards, using 18 Mascarey wood specimens with a thickness of 20 mm subjected to direct flame exposure, both on the edge and surface. The results indicate that the density of Mascarey wood increased by 4.5 percent when treated with coatings compared to its natural state. Regarding mechanical properties, specimens coated with Monto varnish showed a decrease in parallel and perpendicular to fiber compression resistance, with values of 47.97 N/mm2 and 13.71 N/mm2, respectively. Conversely, specimens coated with Espengloss lacquer showed an increase in these properties, reaching values of 50.03 N/mm2 in parallel compression and 15.06 N/mm2 in perpendicular compression, compared to natural specimens, which recorded values of 48.33 N/mm2 and 14.78 N/mm2, respectively. In terms of hardness, natural Mascarey wood presented the highest values in all three evaluated directions, with a notable value of 1013 kgf in the direction parallel to the fiber. However, in coated specimens, the highest hardness was observed in the radial direction, with values of 647 kgf for specimens coated with Monto varnish and 864 kgf for those coated with Espengloss lacquer. Furthermore, the thermal conductivity of coated Mascarey wood showed a 10 percent increase compared to uncoated specimens. In the fire reaction test, the vertical flame propagation did not exceed 150 mm in any case, classifying Mascarey wood as class D according to the EN 13501-1 standard, both in its natural state and with coatings. Although the coatings did not influence the flame propagation rate, they significantly reduced the carbonization rate. Specimens coated with Espengloss lacquer and Monto varnish recorded a carbonization rate of 0.14 and 0.19 percent, respectively. In contrast, natural specimens recorded a carbonization rate of 0.34 percent.
Modelos estocásticos para el estudio y predicción de índices de precios de viviendas en el Ecuador
(Universidad Técnica de Ambato. Facultad de Ingeniería en Sistemas, Electrónica e Industrial. Maestría en Matemática Aplicada, 2022) Viscaíno Cuzco, Mayra Alexandra; Ponsot Balaguer, Ernesto Antonio
The construction industry has a dynamic influence on the economy. In this field, it is known that construction projects carry a risk associated with fluctuations in the prices of construction materials. Estimating future values of construction price indices is important because contractors and builders use these values for budgeting. The aim of this research was to design stochastic models to explain and predict the construction price indices in single-family homes (IPCOU) and multi-family homes (IPCOM) in Ecuador. The design of univariate and multivariate models that consider exogenous variables was contemplated. Nine and eight predictors were found to be statistically significant in predicting the IPCOU and IPCOM, respectively. A set of fourteen potential models were subjected to training and validation, applying the cross-validation technique for time series. In the testing stage, it resulted that the Autoregressive Integrated Moving Average model known as ARIMA(1,1,2) and the multiple regression model to predict IPCOU values, and the ARIMA(2,1,2) model to predict the IPCOM, have good predictive capacity for the forecast horizon contemplated in this study. IPCOU and IPCOM prediction intervals were generated up to the year 2023, with a confidence level of 95%.
Predicción de la resistencia a compresión en hormigón simple mediante un modelo de regresión lineal múltiple
(Universidad Técnica de Ambato. Facultad de Ingeniería Civil y Mecánica, Carrera de Ingeniería Civil., 2025-02) Gatia Caiza, Alisson Natalia; Viscaíno Cuzco, Mayra Alexandra
The construction industry has relied on traditional methods to determine the compressive strength of concrete for the past few decades. These conventional procedures, characterized by their destructive nature and long waiting periods, have generated economic losses and delays in project execution over the years. Faced with this problem, it is appropriate to develop non-destructive predictive models that allow obtaining the compressive strength value of concrete immediately, to optimize construction processes and reduce costs associated with delays in project execution. The objective of this research work was to develop a multiple linear regression model that estimates the compressive strength of plain concrete at 7, 14, and 28 days. This research was structured in four phases to meet the established objectives: in the preliminary phase, a database was built on the physical properties that influence the compressive strength of concrete. Then, in the first phase, the predictors considered for the construction of the MLR predictive model were determined. Subsequently, in the second phase, the predictive capacity of the model was evaluated using evaluation metrics for prediction. Finally, in the third phase, the MLR model was validated by comparing its predictions with the compressive strength values obtained in concrete cylinders made with materials from the area. The multiple linear regression model built from a database with 179 records of factors that influence the compressive strength of concrete contains 13 independent variables. This model proved to have a good fit to the data, with an adjusted coefficient of determination equal to 0.7934. This value indicates that the model explains 79 percent of the behavior of the compressive strength of concrete. To evaluate the predictive capacity of the model during the testing stage, a test with 35 data was carried out, the results obtained with the evaluation metrics such as RMSE and MAPE is equal ± 20.195 kg/cm2 and 7.17 percent, respectively. Likewise, during the validation stage, the multiple linear regression model for the ages of 7, 14 and 28 days presented a MAPE of 10 percent and an RMSE equal to ± 22.148 kg/cm2. These results indicate that the proposed predictive model has an acceptable predictive capacity.
Pronóstico de precipitaciones pluviométricas usando el modelo univariante Prophet para una toma de decisiones informada.
(Universidad Técnica de Ambato. Facultad de Ingeniería Civil y Mecánica, Carrera de Ingeniería Civil., 2025-02) Zabala Cárdenas, Anthony Roger; Viscaíno Cuzco, Mayra Alexandra
Meteorological information is essential to understand the climatic state of a region and becomes a key tool for decision-making in various sectors of society. During periods of water scarcity, it is essential to implement water management systems that mitigate the impact of shortages. In this context, the main objective of this research was to forecast rainfall in the Ambato canton using the Prophet univariate model for informed decision-making. This work was structured in three phases with the purpose of implementing the Prophet model to make daily rainfall forecasts in the Ambato canton. In the first phase, a statistical analysis of the historical series was carried out, calculating measures such as average, quartiles and standard deviation. The second involved deploying the Prophet model at 19 weather stations with records between 2013 and 2024, splitting the data into proportions of 80 and 20 percent, 85 and 15 percent, and 90 and 10 percent, using the first set to train the model and the second to evaluate the results. In addition, the hyperparameters changepoint prior scale and seasonality prior scale were adjusted, with ranges between 0.05-10 and 10-100, respectively, using grid search to determine the optimal configuration that minimized MAE and RMSE errors, comparing it with the default values of the model. Finally, the third consisted of creating isohyet maps that illustrate the spatial distribution of precipitation. The results showed that, at most stations, the Prophet model fit the data split of 90 percent for training and 10 percent for evaluation more effectively, obtaining average MAE and RMSE values of 2.13 mm and 3.41 mm, respectively. This allowed us to conclude that the Prophet model demonstrated a good performance in fitting the analyzed time series. However, it had difficulties in predicting maximum precipitation values, which is a key aspect to consider in future applications of the model.
Pronóstico de precipitaciones utilizando el método de regresión lineal múltiple en el cantón de Ambato, provincia de Tungurahua
(Universidad Técnica de Ambato. Facultad de Ingeniería Civil y Mecánica, Carrera de Ingeniería Civil, 2025-02) Toscano Altamirano, Melany Monserrath; Viscaíno Cuzco, Mayra Alexandra
Accurate forecasting of future rainfall is crucial because it allows decisions to be made about urban planning, water resource management and engineering construction. Therefore, this research was developed using a multiple linear regression model which combined statistical analysis and mathematical modeling. The process began with the collection of historical precipitation data from the Chiqui Urcu, Mula Corral and Quisapincha meteorological stations, which were subjected to statistical analysis to evaluate parameters such as mean, standard deviation, and time trends, as well as to identify correlations with climatic variables such as relative humidity, wind speed and temperature. The most significant variables validated by evaluation metrics were used: MAE, RMSE and MAPE. Based on the projections generated, isohyet maps were produced that graphically represent the estimated distribution of precipitation in different areas of the canton, facilitating decision making. A data set from 2013-2024 was considered for stations CH1 and MU2 and from 2013-2023 for station QU3. Monthly precipitation averages were 89.68 mm for CH1; 78.57 mm for MU2 and 80.98 mm for QU3. Relative humidity was identified as the variable with the highest correlation with precipitation, which positioned it as a determining factor for the forecast models. Station QU3 presented a non-stationary time series, generating greater difficulty in its modeling. With a confidence level of 95 percent, the statistically significant variables were, for station CH1 relative humidity, wind speed and temperature; for MU2 relative humidity and temperature, while in QU3 only wind speed was significant with a confidence level of 85 percent. To train the models, two Hold-Out and cross-validation techniques were tested, of which the one that provided the best results was the cross-validation technique. The predictive capacity of the models was evaluated using the MAPE, obtaining values of 20.09 percent for MU2, 22.82 percent for QU3 and 23.69 percent for CH1; reasonable performance for a three-month horizon. The forecasts indicated that the highest precipitation was recorded in CH1 and MU2 during the month of July 2024, with values of 95.26 mm and 95.46 mm, respectively, while in QU3 the month with the highest precipitation was November 2023, with 73.96 mm. Finally, it was identified that the limited availability of data in QU3 restricted the updating of the forecasts, although the models can be improved with the incorporation of new information to obtain more accurate results.