Abstract

In December 2019, Puerto Rico experienced an increment in seismic activity, especially in the South and Southwestern regions of the island. The hundreds of buildings and homes damaged or destroyed prompted the hasty installation of multiple shelters and showed the little preparedness of the municipalities of the island to face emergencies of this kind and magnitude. The municipalities of Guánica and Guayanilla reported the largest impacts in terms of number and magnitudes of earthquakes. Surrounding municipalities, however, were also importantly affected. Despite a decrease in seismic activity in February 2020, event occurrences and magnitudes continued to fluctuate. The COVID-19 pandemic, due to its global reach, eclipsed many other emergencies including that of the seismic activity in the island. This study provides data and statistical summaries on this activity from the first week of December 2019 until the second week of 2021 that may be useful for future researchers in the area of seismic engineering and related fields.

Abstract

The analytical and experimental seismic response of La Mission Bridge, and the site sub-surface characterization on its neighborhood is presented in this paper. SAP 2000 (Structural Analysis Program) was used to model and characterize numerically the expected response of the bridge in terms of their vibration natural frequencies and maximum displacement. It was also generated the scenario of the bridge response upon strong motion. In both cases, ambient vibration measurements were used for the experimental studies. The stiffness matrix method was used for the analytical study (forward modeling) of wave propagation in layered media. The relevant characteristics of the results are next succinctly described: For the bridge: the theoretical fundamental frequency of vibration was 3.10 Hz., and the estimated experimental fundamental vibration frequency was 3.30 Hz. For the site characterization, our results are described starting at the north end of the bridge going through its south end: (i) The site S1_2, which is the site where the soil was artificially compacted, has a dominant frequency of 2.5 Hz and an average shear wave velocity of 195 m/s. (ii) For sites S3_1 and S2_4, the dominant frequency was 1.5 Hz and the average shear wave velocity was 115 m/s and 123 m/s, respectively. (iii) Site S2_2, the dominant frequency was 3.5 Hz and an average shear wave velocity 275 m/s. (iv) Site S2_5, in this site two clear peaks at frequencies of 1.5 and 3.75 Hz were observed, regarding to the average shear wave velocity it was 128 m/s. (v) Site S2_3, the dominant frequency was 4.0 Hz and the average shear wave velocity was 346 m/s. All the experimental sites were in soils at natural conditions, but the site S1_2, which was artificially compacted. The soil characteristics along the 163 m length of the bridge, clearly shows a rigidity change of the soil sub-surface conditions. That condition is an indication that different amplifications of the ground response will probably be experienced, being in the range of the 4.0 Hz at the south-end side of the bridge, and 1.5 Hz on the portion of the north-end of the bridge. In no case the fundamental vibration frequency of the bridge matches the fundamental vibration frequency of the ground surface. However, they are somehow no too far apart each other.

Abstract

The scientific literature on events involving the loss of containment of hazardous materials due to a natural event (known as na-tech events) is recent and limited in Brazil. Evidence was sought of the occurrence of these events in the coastal region of the state of São Paulo. The study identified fifteen na-tech events between 1940 and 2015, and showed that the events predominantly affected bodies of water. A method was then proposed to estimate the frequency of these events, relativizing them to the number of companies that generated them. Relativization allows the quantitative comparison among locations with different numbers of companies and the transfer of the estimated frequency among locations. The method also allows attributing less uncertain frequency estimates to na-tech accident hypotheses, favoring risk-based decisions. Consistent databases combined with the method allow the construction of na-tech hypotheses appropriate to the location during a quantitative risk assessment of an industrial facility.

Abstract

The archipelago of Puerto Rico is a region of high danger to tsunamis (ATC, 2019). Recognizing that the school population in Puerto Rico is around 600,000 people (including students and teachers, according to 2016 data), and that schools are essential facilities to safeguard against extreme events, the objective of the research has been to evaluate if the Puerto Rican schools are vulnerable to tsunamis. In the first instance, a comprehensive database of schools in Puerto Rico that could be affected by tsunami events was developed and critical municipalities were identified. The municipalities of San Juan and Cataño were selected as case studies in which a more detailed evaluation was carried out. This evaluation included the analysis of the evacuation time required to move from each schoolyard to a safe place as the main vulnerability factor. The shortest route and several alternative routes were evaluated for each school. The analysis included as a complementary factor the status of the critical school evacuation route in each of the two municipalities. In addition, a survey form was developed and administered to collect data on school evacuation preparedness. The study found that the most vulnerable schools in each study municipality present excessive evacuation times and unsafe and inadequate evacuation routes for the evacuation process. Several additional study areas have been identified to improve the vulnerability assessment of schools. Therefore, a second phase of the research is being developed to obtain better estimates of evacuation times, including all stages of the evacuation process (evacuation timeline), analyzing the factors that affect pedestrian dynamics and simulation of each of these phases and integrating data from evacuation drills. The results of these investigations are expected to contribute to the rehabilitation processes of coastal schools by providing refined tools to decide if vertical evacuation is required.

Abstract

Road administrators encounter situations where they must make decisions regarding the maintenance and rehabilitation of a road network without knowing the outcome of those decisions until years later. The Heavy Vehicle Simulator has been widely used as an accelerated testing tool to study pavement performance in a shorter period and under more controlled conditions than in the field. The Virginia Department of Transportation, in conjunction with the Virginia Tech Transportation Institute and the Virginia Transportation Research Council, has initiated a research project to study the behavior and performance of different pavement materials and structures under accelerated load through a Heavy Vehicle Simulator.  Six pavement sections with different structures were built and instrumented with strain gauges, load cells, temperature gauges, and linear vertical displacement transducers. Two lanes were dedicated to study reflection cracking. They included a concrete pavement with joints 9.5 mm (3/8 inch) wide to reflect cracks in the surface. These lanes were covered with two 1.5-inch (38.1-mm) layers of a control SMA mix asphalt and a similar mix modified with a synthetic fiber. This article presents the results of this reflection cracking study. The article describes the characterization of the asphalt mixtures used, the pavement structure, the construction design, the Heavy Vehicle Simulator used and the installed instrumentation. The paper also presents some of the lessons learned, experimental changes, and study results in terms of cracking and rutting performance.

Abstract

Barcelona (Spain) had a total population of 1,636,762 in 2019 that are distributed on 10 districts across the city. These districts have different characteristics in size and population density. As a result, this can lead to different traffic crashes injuries occurrences and numbers in these areas. Therefore, this study is attempting to determine the conditional probabilities for each district in order to identify the district that has highest number of injuries compared to other areas. A Bayesian network approach is utilized to analyze the dataset and identify the high-risk district alongside analyzing the varieties of traffic crashes during four-year intervals. The results have shown that the district that has the highest population, highest usage of private transport mode, and highest density of passenger cars per km2 (compared to all other districts), has the highest risk of having all types of injuries resulting from traffic crashes. For the temporal factor represented by the four years interval, traffic crashes occurrences varied from district to district based on the level of injury.