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This paper aims to apply a pavement design by LEDFAA for a sample airport, and design results involving layer thickness, modulus and cumulative damage factor (CDF) achieved are shown in figures.

Finite element (FE) simulation is applied for sample airport pavement and based on results involving stress and strain, CDF amount is shown by using related equations. To analyze the accuracy of modeling, a comparison has been made between the values of ABAQUS and case study results at Denver International Airport (DIA).

The present study includes a comparison between the two conventional methods for runway pavement design. There is linear relation between layered elastic design (LED) and FE method results, so CDF rate achieved by the FE method is always smaller than the LED method. To assess the accuracy of the applied modeling with ABAQUS software, the validation was done using the deformations under the concrete slabs of DIA. The results are compatible with the results acquired from the case study, and the high accuracy of modeling was approved. This research shows that B-777 on rigid pavements and A-340-500/600 on flexible pavements have the most CDF contribution, among other aircrafts. Also, CDF rate for any aircraft in the LED method is higher than the FE method.

To assess the accuracy of the applied modeling with ABAQUS software, the validation was done using the deformations under the concrete slabs of DIA. The results are compatible with the results acquired from the case study, and the high accuracy of modeling was approved.

The purpose of this study is the development of an objective approach to prioritize and rank airfield pavement sections based on their condition and justify their funding requirements using a soft-computing technique.

The airfield pavement condition is evaluated by collecting data through field tests and visual surveys. The performance indicators are selected as deflection, structural index, subgrade modulus and pavement condition index, by taking the help of field experts. The condition of pavement sections is analyzed by obtaining scores for each sections using Buckley’s fuzzy analytic hierarchy process. The sections are finally ranked for performing their maintenance and repair activities.

The condition of pavements is represented using a single score that takes an account of cumulative impact of various parameters as well as any subjectivity associated with human perceptions.

The developed methodology is very useful for its practical implications, and it is explained using a case study of an international airport.

Decision-making for maintenance and repair practices is often based on subjective decisions and lacks a robust and judicious approach. Thus, obtaining sufficient budget for repair and maintenance becomes one of the primary challenges. This study adds a value to prevailing practices by developing an objective decision-making methodology. Additionally, the use of non-destructive testing techniques, which pose little or no necessity to destructive coring and boring, eases this task.

Given the importance of airports and the need to develop this issue in runway, the purpose of this study, pavement response values under loading of different aircraft have been obtained using tire and pavement modeling by finite element method (FEM). To predict the actual behavior of pavements under aircraft loading, dynamic analysis of runway flexible pavement was performed using Abaqus software version 6.10.

The method is based on finite element analysis and software simulation. And the main goal to obtain the amount of pavement stress and deflection at different speeds.

The results of modeling showed that aircraft movement at a speed of 5-8 km/h leads to the highest stresses and deflections in the pavement. Moreover, the effect of elastic modulus variations of the asphalt concrete on the tensile strain under advisory circular layer was calculated for Airbus A380 by using FEM. To validate the results of the runway pavement dynamic analysis, the results of modeling have been compared with the field test results of National Airport Pavement Test Facility.

Stresses and deflections of pavement during aircraft movement at different speeds of 5, 8 and 20 km/h on the runway have been presented, and the critical points in length, width and depth of runway pavement, as well as the most critical speed of aircraft in terms of induced damage to the pavement, have been obtained.

The massive number of pavements and buildings coupled with the limited inspection resources, both monetary and human, to detect distresses and recommend maintenance actions lead to rapid deterioration, decreased service life, lower level of service and increased community disruption. Therefore, this paper aims at providing a state-of-the-art review of the literature with respect to deep learning techniques for detecting distress in both pavements and buildings; research advancements per asset/structure type; and future recommendations in deep learning applications for distress detection.

A critical analysis was conducted on 181 papers of deep learning-based cracks detection. A structured analysis was adopted so that major articles were analyzed according to their focus of study, used methods, findings and limitations.

The utilization of deep learning to detect pavement cracks is advanced compared to assess and evaluate the structural health of buildings. There is a need for studies that compare different convolutional neural network models to foster the development of an integrated solution that considers the data collection method. Further research is required to examine the setup, implementation and running costs, frequency of capturing data and deep learning tool. In conclusion, the future of applying deep learning algorithms in lieu of manual inspection for detecting distresses has shown promising results.

The availability of previous research and the required improvements in the proposed computational tools and models (e.g. artificial intelligence, deep learning, etc.) are triggering researchers and practitioners to enhance the distresses’ inspection process and make better use of their limited resources.

A critical and structured analysis of deep learning-based crack detection for pavement and buildings is conducted for the first time to enable novice researchers to highlight the knowledge gap in each article, as well as building a knowledge base from the findings of other research to support developing future workable solutions.

To explore the economical and reasonable semi-rigid permeable base layer ratio, solve the problems caused by rainwater washing over the pavement base layer on the slope, improve its drainage function, improve the water stability and service life of the roadbed pavement and promote the application of semi-rigid permeable base layer materials in the construction of asphalt pavement in cold regions.

In this study, three semi-rigid base course materials were designed, the mechanical strength and drainage properties were tested and the effect and correlation of air voids on their performance indexes were analyzed.

It was found that increasing the cement content increased the strength but reduced the air voids and water permeability coefficient. The permeability performance of the sandless material was superior to the dense; the performance of the two sandless materials was basically the same when the cement content was 7%. Overall, the skeleton void (sand-containing) type gradation between the sandless and dense types is more suitable as permeable semi-rigid base material; its gradation is relatively continuous, with cement content? 4.5%, strength? 1.5 MPa, water permeability coefficient? 0.8 cm/s and voids of 18–20%.

The study of permeable semi-rigid base material with large air voids could help to solve the problems of water damage and freeze-thaw damage of the base layer of asphalt pavements in cold regions and ensure the comfort and durability of asphalt pavements while having good economic and social benefits.

Examines, through examples of disasters cited in the text, how response and assistance is given and at what speed, with particular reference to oceans, when applicable. Looks particularly at the part played by the Canadian Navy in many of these events.