Infrastructure plays a key role in society. Recent collapses of bridges have underlined their importance for road functionality, causing disruptions to commuters and emergency vehicles. Major issues arise on rural roads, where the lack of redundancy leads to the isolation of entire communities. Actual approaches to assess the resilience of countryside roads rely on the availability of specific datasets, limiting their practical application; this issue is typically related to traffic data. This research aims to propose innovative algorithms to assess the road network’s vulnerability in rural areas, including a novel traffic data collection process and its calibration. The aggregate metric is called Detour-Impact Index (DII) and compares user costs before and after a disruptive event. The method uses traditional network-impact metrics in combination with a new algorithm that allows us to gather quantitative traffic data starting from qualitative information. User travel time showed good agreement between the proposed procedure and traditional web-based methods. Furthermore, the paper provides user delay costs functions accounting for traffic composition, trip purposes, vehicle operative costs, nonlinear volume–capacity relation, and average daily traffic. A significant aspect is the adaptability of this framework, as it is designed to be coupled with existing approaches. The method is demonstrated on a case study in Tuscany (Italy).
Preprocessing and postprocessing computer programs that enhance the utility of the U.S. Geological Survey radial-flow model have been developed. The preprocessor program (1) generates a triangular finite-element mesh from minimal data input, (2) produces graphical displays and tabulations of data for the mesh, and (3) prepares an input data file to use with the radialflow model. The postprocessor program is a version of the radial-flow model, which was modified to (1) produce graphical output for simulation and field results, (2) generate a statistic for comparing the simulation results with observed data, and (3) allow hydrologic properties to vary in the simulated region. Examples of the use of the processor programs for a hypothetical aquifer test are presented. Instructions for the data files, format instructions, and a listing of the preprocessor and postprocessor source codes are given in the appendixes.
<p>In the last years, extreme rainfalls have caused many collapses of bridges. In Italy several of those were short span’s ones that failed during or after extreme events of this nature. This work presents a method for inspection survey and its results regarding a campaign on 71 bridges, located in Tuscany (Massa Carrara, Italy). This area was affected by a big flood that took place in 2014 and also two earlier ones in 2012 with only 15 days apart one from the other, leading to a huge disrupting situation for the population’s daily life and consequent economical loss. Concerning this issue, the local stakeholders showed an increasing interest for sustainable methods for monitoring the built environment, thus the results of this research have been made available for integration on the Civil Protection Emergency Plan (CLE) and can be used in a decision-making prioritization list of actions. The framework uses a Gis- based approach combined with a quick survey technique. This method balances costs of surveying with the accuracy needed in inspections, bypassing the classical procedure which requires several onsite surveys. This procedure uses only three transversal river sections for each bridge. The method also comprises a tailored survey inspection form and a user-friendly worksheet was designed to build the database, applicable for further studies. Results showed the absence of maintenance on existing structures and riverbeds, often resulting in a partially or fully bridge section obstruction, and material’s decay. The framework created in this work allowed to assess the conditions of several bridges in the studied region, to further analyse the resilience of the infrastructure system and proceed with adequate interventions.</p>
Recent failures in road networks highlight their vulnerability towards natural hazards, particularly to extreme weather events. This paper proposes a method to evaluate the safety of road networks in case of collapse of one or more bridges. In addition, relevant consequences in terms of safety of human life, direct and indirect cost are crucial aspects to consider. The framework described here is based on the knowledge of road and river network, of the individual bridges and of the traffic data. However, this approach can be generalized in case of interruption of road network due to other causes. An algorithm has been developed to extract traffic data from Google and elaborate it throughout a procedure based on the application of the USA Highway Capacity Manual. This consents to have a quantitative definition of the road traffic directly from the users and to get updated traffic data. The maps are processed throughout a GIS software and, thanks to the application of a routing algorithm and proper constraints, it is possible to evaluate the effects of the interruption of one or more bridges. The consequences are evaluated in terms of drivers’ delay and time cost. This provides useful information about priority of intervention with the aim of proposing to stakeholders a suitable instrument for disaster prevention and management.
Risk management plays a crucial role in the stakeholders' decision making because it is directly related to safety, serviceability and economy. There is now a growing concern about how to relocate known risks into an acceptance threshold: this implies the evaluation of several options obtained from hazard scenarios considering the related consequences. In parallel, practitioners usually rely on standard tools for risk assessment, and on structural codes to compute performances. Although this approach is currently widely implemented, this research shows that hazardous situations can arise in properly designed infrastructures, due to errors in management. This paper deals with such issue, also highlighting a gap in current codes that could contribute to losses caused by unforeseen failure modes. In this study, a preliminary FMEA assessment was performed to identify the failure modes that required a deeper quantitative analysis. In a second step, a quantitative analysis was implemented, using a modular methodology that combines reliability theory with a risk-based approach. The results evidenced that a wider analysis focused on the identification of vulnerable areas shall be considered in every stage of the asset management. Furthermore, the dynamic of this process is regulated by the established safety level concerning possible damages to people, production sites and commercial activities.
<p>Planet Earth is naturally subject to climatic variability, but over the recent decades extreme deviations have been observed. Climate change, as a manmade-induced process, is mainly due to the increase of greenhouse gasses emission. Global warming consequences drive also to an intensification of hydrological cycles, leading to more frequent and severe precipitations. In parallel, several bridges have collapsed in the last years due to extreme rainfalls. Although the impacts of climate change on built environment do not always present a direct cause-effect relation, analysis on specific parameters (as rain volume) that are inputs in bridge design, can clarify some aspects of this interaction. In this paper, the peak discharge variation of different rivers located in the northwest of Italy, within the last 100 years, is analyzed. A cluster analysis was performed to understand if the hydraulic design loads should be considered with a different intensity if the bridge had been built with reference to an up-to-date database, or if in the last decades, when the majority of these structures were built. The rainfall data was analyzed through classical techniques, such as the frequency-based statistical method, but without the stationary time hypothesis. In this case, the extreme value theory was used for the estimation of intensity-duration curve parameters. By introducing a second-order analysis, where random variables can change over time, an increase-trend of rainfall height was found, and the peak discharge was determined accordingly. The relevant parameters on the case-study area were preliminarily obtained through geographic information systems. The results evidenced that nowadays-floods parameters are significantly different from those of the past, and this behavior is escalated when high return period values are assumed. Furthermore, although hydraulic design loads are increasing, many existing bridges are not properly maintained, leading to an increased number of collapses.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.