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Volume 14, No. 25Journal 25

DOI:https://doi.org/10.15517/2t83bt06

Published October 28, 2025

Scientific Papers

  1. Oisy Hernández Menéndez, María Liliana Alba Menéndez, José M. Villaroel Castro (Author)

    Assessment of accident rates at level crossings in La Habana, Cuba

    The present paper constitutes a deeply of a previous investigation carried out in Cuba in the year 2007 for the same authors, on the behavior of the accident in the level crossing to national scale, in which Havana was identified as the country of more incidence in these facts, that which will be analyzed detailed. The analysis is centered in the statistical aspect with the collection of information on the accidents of the traffic with the objective of determining the municipalities of bigger concentration of the same ones, the lines where they happen, hours of the day and types of vehicles with those that more collide with the trains, and then, to identify for frequency of accidents, the locations at more dangerous levels in the territory, to which will be determined the risks factors that are impacting in this accident in the following phase of the investigation.

  2. David José Aragón Matamoros, Alejandro Navas Carro (Author)

    Measurement of concrete compressive strength using 100×200 mm and 150×300 mm cylinders for construction quality control

    This study compared the concrete’s compressive strength of cylinders of 100 mm by 200 mm and 150 mm by 300 mm for two different mix designs, and two different sizes of coarse aggregate. Two hundred eighty eight concrete cylinders were made and tested; 144 at age of 7 days and 144 at age of 28 days. The study revealed that the average resistance measured in cylinders of 100 mm diameter is 10% greater than the resistance measured in cylinders of 200 mm diameter. Additionally it was found that the standard deviation is approximately 20% higher in the cylinders with a diameter of 100 mm and in this case, that the maximum aggregate size did not influence the compressive strength recorded in cylinders of 100 mm by 200 mm.

  3. Diego Alberto Cordero Carballo, Rosario Espinoza Carazo (Author)

    Early warning systems for landslide monitoring

    os deslizamientos de tierra generados por lluvia o sismo son una de las principales amenazas para la infraestructura de transportes y las líneas vitales. Debido al desarrollo progresivo de zonas urbanas e infraestructura en lugares antes no ocupados, cada vez más personas y actividades se asientan en ambientes que están, o pueden estar, expuestas a este tipo de amenazas. Por lo anterior, en la actualidad se les está dando mayor atención a las amenazas geológicas en el contexto de la prevención y gestión de desastres. Debido al aumento de la vulnerabilidad de la infraestructura a las amenazas naturales, la demanda por sistemas de alerta temprana y monitoreo se está incrementando, siendo estos una herramienta más para prevenir desastres y mitigar el riesgo de la población.

  4. María J Correa, Luciana García Eiler, Hugo Botasso, Cecilia Soengas, Oscar Rebollo (Author)

    Relationship between the petrographic and geotechnical characteristics of aggregates from Buenos Aires Province

    In this paper are presented the relationships found between first geotechnical results and geologic and petrography characteristics studied in aggregates of Buenos Aires province (Argentina). Samples are coming from main aggregates quarries of Sierras Septentrionales near Olavarría and Tandil city. The observations indicate that geotechnical results are not only dependent on the mineralogy of the rock, but also it performs supreme importance its texture, which is directly linked by the geological origin. On the other hand is estimated that crushing technology used at cracking plants must be adapted to the characteristics mentioned of the rock to promote their properties and to obtained aggregates which expire with the needs of the market.

  5. Luis Amador Jiménez, Donath Mrawira (Author)

    Bayesian Regression in Pavement Deterioration Modeling: Revisiting the AASHO Road Test Rut Depth Model

    Traditional pavement deterioration modeling is normally based on historical condition data alone without incorporating the fundamental relationships between the causal factors and the response. Also, typical approaches do not quantify the uncertainty of the predicted response. This paper uses Bayesian regression for pavement deterioration modeling. This method is applied to an existing model for the prediction of rut depth progression from the AASHO Road Test. A classical regression model developed elsewhere is herein summarized and its results are then compared with those from the Bayesian regression in order to validate. A second model based on the entire dataset of the AASHO road test is used to demonstrate the advantages of such approach. The models are capable of employing expert criteria combined with historical knowledge and current observations in order estimate posterior probabilistic distributions for the regression coefficients of the mechanistic equation. The predictive model calibrated to local conditions is able to forecast within pre-specified confidence intervals the range of values for the expected deterioration. Bayesian regression modeling produces more reliable predictions for deterioration performance, which in turn, can be used to improve decision-making on road management systems.