Article
Construction & Building Technology
R. A. Pietersen, M. S. Beauregard, H. H. Einstein
Summary: This paper presents a method for partially automated airfield pavement condition assessment using drone mounted imaging technology, which shows strong agreement with manual inspection results. This indicates that automation of pavement evaluation is achievable using drone-captured images and machine learning.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Chemistry, Multidisciplinary
Ming Qiao, Xue Wang, Rui Hou
Summary: This study used the SASW method to evaluate the modulus performance of concrete pavement and validated its accuracy through comparison with other testing results. The method also has the capability to identify the location of inherent distress in the pavement and assist in determining the design thickness and material of overlay asphalt.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Multidisciplinary
Amjad Issa, Haya Samaneh, Mohammad Ghanim
Summary: This research models the relationship between distress types and severity and Pavement Condition Index (PCI) using Artificial Neural Networks (ANN). The results show that the ANN model can predict PCI with high reliability.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Review
Construction & Building Technology
Nima Sholevar, Amir Golroo, Sahand Roghani Esfahani
Summary: This study reviews the latest techniques in pavement condition data evaluation using machine learning methods, specifically focusing on the application of image classification, object detection, and segmentation in pavement distress assessment. The study also evaluates pavement automated data collection tools and condition indices from the perspective of machine learning applications. The review concludes that the overall trend in pavement condition evaluation is to apply machine learning techniques, although there are some limitations in detecting certain pavement distresses with complex patterns and indicating the severity and density of distresses, which warrant further research.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Engineering, Environmental
Youen Pericault, Maria Viklander, Annelie Hedstrom
Summary: Urban water pipe networks require annual rehabilitation due to deterioration, but the amount of rehabilitation performed worldwide often falls short of the actual needs, resulting in increased risks of failures, lower performance, and financial burdens for future generations. Coordinating rehabilitation projects between different utility sectors is important to limit the impacts on the urban environment, but current models do not consider how this coordination process affects the long-term financial and environmental impacts of infrastructure rehabilitation.
Article
Construction & Building Technology
Afarin Kheirati, Amir Golroo
Summary: The study aims to develop a novel pavement condition index using a machine learning model to comprehensively represent pavement condition in terms of structural adequacy, pavement roughness, road safety, and surface distress. The outcome shows an approximately 84% reduction in pavement distress analysis efforts, with the model having more than 80% accuracy and precision highly correlated with the Pavement Condition Index (PCI).
AUTOMATION IN CONSTRUCTION
(2022)
Article
Construction & Building Technology
Waqar S. Qureshi, David Power, Ihsan Ullah, Brian Mulry, Kieran Feighan, Susan McKeever, Dympna O'Sullivan
Summary: This paper proposes a deep-learning framework for automatically rating the condition of rural road pavements using digital images. The framework includes pavement segmentation, data cleaning, image cropping and resizing, and pavement condition rating classification. A dataset of images captured from roads in Ireland was created and rated by expert raters. Deep-learning models were developed to perform pavement segmentation and condition rating classification. The automated rating achieved high scores on an independent test set, demonstrating the robustness of the models against variations in background and clutter.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Chemistry, Analytical
Konstantinos Gkyrtis, Andreas Loizos, Christina Plati
Summary: This research focuses on integrating different types of non-destructive data to provide a more comprehensive assessment of pavement condition and enable a more rational pavement management and decision-making process.
Review
Environmental Sciences
I. Kousis, A. L. Pisello
Summary: Cool Pavements (CPs) can maintain a lower surface temperature than conventional pavements and mitigate urban overheating. Several studies have reported substantial surface temperature decreases, however, a wide application of CPs is still impeded. This review reports on CP studies performed in the outdoors with respect to reflective, evaporative and thermal energy storage techniques and proposes a monitoring protocol for the outdoor evaluation of CPs.
Article
Computer Science, Interdisciplinary Applications
Guangwei Yang, Kelvin C. P. Wang, Joshua Qiang Li, Yue Fei, Yang Liu, Kamyar C. Mahboub, Allen A. Zhang
Summary: This study presents a CNN-based PvmtTPNet to automatically recognize pavement types with high levels of consistency, accuracy, and speed. By training and testing on a large dataset of pavement images, the network achieved excellent performance in identifying different pavement types.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2021)
Article
Construction & Building Technology
Amr A. Elhadidy, Sherif M. El-Badawy, Emad E. Elbeltagi
Summary: This study developed a simplified regression model linking PCI with IRI using the LTPP database and found that a sigmoid function best expressed the relationship between the two indices. The model had a high coefficient of determination (R-2) and low bias in predicted IRI values, with validation on a different dataset also yielding highly accurate predictions. This research proposed a pavement condition rating system based on IRI that is equivalent to the widely-used PCI rating method.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2021)
Article
Construction & Building Technology
Wangda Guo, Jinxi Zhang, Dandan Cao, Hui Yao
Summary: This article presents a method for assessing the condition of in-service asphalt pavement using the Random Forests algorithm and Gini importance measurement to extract key detection indicators. A cost-effective approach is proposed by reducing data dimensions. The results demonstrate that the proposed method achieves consistent assessment results with the traditional method, while reducing the burden of data collection.
CONSTRUCTION AND BUILDING MATERIALS
(2022)
Article
Construction & Building Technology
Arieh Sidess, Amnon Ravina, Eyal Oged
Summary: Road pavements deteriorate due to traffic load and environmental conditions. A model has been developed to predict the deterioration of the Pavement Condition Index (PCI) based on pavement structural factors and environmental conditions. The model shows a good correlation with measured results from road sections in varied climate zones managed by Netivei Israel (NETI).
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2021)
Article
Engineering, Civil
Prajwol Tamrakar, Jayhyun Kwon, Mark H. Wayne, Hyung S. Lee
Summary: Many transportation agencies have adopted the Mechanistic-Empirical (ME) approach for designing and analyzing pavements in order to improve performance-based design and accurate prediction of distresses. The ME approach involves mechanical analysis and empirical analysis, aiming to enhance pavement design and maintenance practices.
TRANSPORTATION GEOTECHNICS
(2021)
Article
Engineering, Civil
Mai Sirhan, Shlomo Bekhor, Arieh Sidess
Summary: This paper develops and trains a deep artificial neural network (DNN) model to predict the pavement condition index (PCI) values. The DNN model outperforms traditional prediction methods, such as linear and nonlinear regression, in terms of accuracy. The most influential variables for PCI prediction are found to be distresses related to alligator cracking, swelling, rutting, and potholes.
JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS
(2022)
Article
Construction & Building Technology
Aleli Osorio-Lird, Alondra Chamorro, Alvaro Gonzalez
Summary: Rural roads are crucial for economic and social development, requiring proper management and support. Maintenance requirements and costs are dependent on traffic conditions, with chloride stabilisers used to improve service levels. A model was developed to evaluate road roughness, providing confident performance information based on road age.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
Alondra Chamorro, Tomas Echaveguren, Eduardo Allen, Marta Contreras, Joaquin Daga, Hernan de Solminihac, Luis E. Lara
Review
Geosciences, Multidisciplinary
Gabriela Quitana, Maria Molinos-Senante, Alondra Chamorro
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2020)
Article
Geosciences, Multidisciplinary
Pablo Cartes, Tomas Echaveguren Navarro, Alondra Chamorro Gine, Eduardo Allen Binet
Summary: The paper aims to develop a model integrating cost-saving and resilience evaluation in order to prioritize recovery strategies for road performance. Indexes are proposed to estimate the relative change in resilience and costs caused by different recovery strategies, and then integrated into a priority index for comprehensive assessment.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Geosciences, Multidisciplinary
Pablo Cartes, Alondra Chamorro, Tomas Echaveguren
Summary: Tunnels play a crucial role in maintaining the continuity of rural road and urban transportation networks. The impact of earthquakes on tunnel serviceability is significant, and the estimation of traffic interruption probability requires the use of fragility curves. A simplified procedure was proposed for evaluating the traffic interruption probability of tunnels due to earthquakes, utilizing existing seismic exposure maps and suitable fragility curves.
Article
Computer Science, Interdisciplinary Applications
Eduardo Allen, Alondra Chamorro, Alan Poulos, Sebastian Castro, Juan Carlos de la Llera, Tomas Echaveguren
Summary: This study proposes a risk framework to evaluate operational consequences in interurban road networks exposed to seismic hazard using travel time delays and propagate uncertainty in the model. The risk values are evaluated using Monte Carlo simulations, and uncertainty is propagated using a polynomial chaos expansion meta-model. The results demonstrate that the parameters that most significantly influence risk are fragility, loss of road capacity, and traffic volume.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2022)
Article
Geography, Physical
Natalia Nieto, Alondra Chamorro, Tomas Echaveguren, Cristian Escauriaza
Summary: Recent studies have shown the damage or failure of transportation networks caused by various types of flows, especially the adjacent debris flows that affect road embankments. While fragility curves have been developed for bridges and roads exposed to debris flows, there is currently no model available to estimate the road damage probability of embankments exposed to adjacent debris flows. This paper aims to develop such a model and finds that lower heights and platform widths increase the probability of road embankment damage.
PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT
(2023)
Article
Geosciences, Multidisciplinary
Nikole Guerrero, Marta Contreras, Alondra Chamorro, Carolina Martinez, Tomas Echaveguren
Summary: Socio-natural disasters can have profound consequences for countries exposed to natural hazards. Disaster Risk Reduction (DRR) management and the development of techniques to measure social vulnerability are crucial. This research aims to identify the factors determining social vulnerability in Chile, using different spatial scales and differentiating urban and rural areas. The study found that access to basic services, education level, housing quality, and income levels are significant factors affecting social vulnerability. The use of different territorial scales provides valuable insights for decision-makers and DRR policies.
Article
Engineering, Civil
Alondra Chamorro, Tomas Echaveguren, Carlos Pattillo, Manuel Contreras-Jara, Marta Contreras, Eduardo Allen, Natalia Nieto, Hernan de Solminihac
Summary: This study discusses the development of SIGeR-RV, an RMS developed in Chile for road networks exposed to multiple natural hazards. The system serves as a tool for decision makers to estimate budget requirements, identify vulnerable road segments, and assess the socioeconomical impacts of risk reduction.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Green & Sustainable Science & Technology
Nicolas C. Bronfman, Javiera V. Castaneda, Nikole F. Guerrero, Pamela Cisternas, Paula B. Repetto, Carolina Martinez, Alondra Chamorro
Summary: Although Chile is highly exposed to natural hazards, there is currently no national index to depict the disparities in resilience levels within the country. This research creates a national-scale community resilience index for Chile based on the BRIC index. The study reveals that resilience is unevenly distributed across the country, with the highest levels concentrated in the central macro-zone. Conversely, the extreme zones have a population concentration, with about 90% at the lowest levels, resulting in unequal allocation of resources and services that impact resilience. Indicators such as the percentage of population without health insurance, without internet access, and electoral participation largely contribute to these differences. The study demonstrates the successful implementation of the BRIC model in assessing community resilience in Chile and suggests targeting resources and strategies to enhance resilience in areas with the lowest levels.
Review
Engineering, Civil
Eduardo Allen, Seosamh B. Costello, Theunis F. P. Henning, Alondra Chamorro, Tomas Echaveguren
Summary: Transportation asset management is a systematic process for the operation, maintenance, and upgrade of physical transportation assets over their life cycle. However, integrating transportation resilience into this process remains a ongoing challenge for transportation agencies. Given the potential damage and cascading effects of natural hazard events on transportation assets and critical networks, addressing this challenge is crucial.
STRUCTURE AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Engineering, Civil
Gustavo Jimenez-Ramos, Tomas Echaveguren, Jose Vargas-Baecheler, Alondra Chamorro
Summary: This study proposes a method for evaluating the probability of cut-slope landslides and traffic interruption. First-order reliability analysis and Monte Carlo simulation were used to analyze different slope and rainfall scenarios. The analysis found 24 failure probability curves for slope inclination, rainfall intensity, and duration, providing insights into the magnitude of road blockage induced by slope failure.
TRANSPORTATION GEOTECHNICS
(2023)
Article
Geosciences, Multidisciplinary
Natalia Nieto, Alondra Chamorro, Tomas Echaveguren, Esteban Saez, Alvaro Gonzalez
Summary: Debris flows have significant economic impact on rural road networks, especially on road embankments in mountainous areas. This study aims to develop fragility curves to assess the potential damage on road embankments exposed to debris flows. The probability of headcut erosion is higher compared to sliding failure, and two-lane roads present higher probabilities of headcut erosion than multilane roads.
GEOMATICS NATURAL HAZARDS & RISK
(2021)
Article
Engineering, Industrial
Maria Calahorra-Jimenez, Keith Molenaar, Cristina Torres-Machi, Alondra Chamorro, Luis F. Alarcon
JOURNAL OF MANAGEMENT IN ENGINEERING
(2020)