scholarly journals Evaluation of Asphalt Concrete Airport Pavement Conditions Based on the Airfield Pavement Condition Index (APCI) in Scope of Flight Safety

Aerospace ◽  
2020 ◽  
Vol 7 (6) ◽  
pp. 78
Author(s):  
Mariusz Wesołowski ◽  
Paweł Iwanowski
Keyword(s):  
Quality Management System ◽  
Condition Index ◽  
Assessment Method ◽  
Technical Condition ◽  
Pavement Management ◽  
Infrastructure Development ◽  
Pavement Condition ◽  
Airport Pavement ◽  
Pavement Condition Index ◽  
High Level

Airoport infrastructure development requires care to maintain it in proper technical condition. Due to this, airport pavements should be constantly monitored, and, above all, correctly managed. High-level airport pavement management requires access to reliable information about their current technical condition as well as proper forecasting of this condition in the future. Obtaining good quality information about the technical condition of airport pavement should be based on a proven methodology, taking into account the introduced quality management system. The authors propose a method of technical pavement condition assessment based on the Airfield Pavement Condition Index (APCI), taking into account not only the results of the surface deterioration inventory, but also repair overviews, load bearing capacity, evenness and roughness of the surface, as well as the surface tensile bond strength. The method was developed during long-term work financed by the Ministry of Science and Higher Education. At the beginning of the article, the authors focus on reviewing the currently available methods of assessing the technical condition of the pavement. Then they briefly present the most popular surface assessment method based on the PCI indicator. Afterwards, a proprietary asphalt pavement assessment method based on the APCI indicator is proposed and an example of how to use the method is presented. Finally, they discuss the results and summarize the work done, and present further directions of work.

scholarly journals Proposal and Implementation of a Heliport Pavement Management System: Technical and Economic Comparison of Maintenance Strategies

2021 ◽  
Vol 13 (16) ◽  
pp. 9201 ◽  
Author(s):  
Paola Di Mascio ◽  
Alessio Antonini ◽  
Piero Narciso ◽  
Antonio Greto ◽  
Marco Cipriani ◽  
...  
Keyword(s):  
Management System ◽  
Condition Index ◽  
Pavement Management ◽  
Pavement Management System ◽  
Pavement Condition ◽  
Airport Pavement ◽  
Maintenance And Rehabilitation ◽  
Pavement Condition Index ◽  
Rotary Wing ◽  
Economic Comparison

Maintenance and rehabilitation (M&R) scheduling for airport pavement is supported by the scientific literature, while a specific tool for heliport pavements lacks. A heliport pavement management system (HPMS) allows the infrastructure manager to obtain benefits in technical and economic terms, as well as safety and efficiency, during the analyzed period. Structure and rationale of the APSM could be replicated and simplified to implement a HPMS because movements of rotary-wing aircrafts have less complexity than fixed-wing ones and have lower mechanical effects on the pavement. In this study, an innovative pavement condition index-based HPMS has been proposed and implemented to rigid and flexible surfaces of the airport of Vergiate (province of Varese, Italy), and two twenty-year M&R plans have been developed, where the results from reactive and proactive approaches have been compared to identify the best strategy in terms of costs and pavement level of service. The result obtained shows that although the loads and traffic of rotary-wing aircrafts are limited, the adoption of PMS is also necessary in the heliport environment.

Estimation of Pavement Serviceability Index Through Android-Based Smartphone Application for Local Roads

2017 ◽  
Vol 2639 (1) ◽  
pp. 129-135 ◽  
Author(s):  
Waleed Aleadelat ◽  
Khaled Ksaibati
Keyword(s):  
Smartphone Application ◽  
Condition Index ◽  
Pavement Management ◽  
Pavement Condition ◽  
Explanatory Variables ◽  
Pavement Condition Index ◽  
Local Roads ◽  
Series Acceleration ◽  
The Difference ◽  
The Cost

The Wyoming Technology Transfer Center is in the process of developing a pavement management system (PMS) for county paved roads in Wyoming. This PMS uses the present serviceability index (PSI) as a main pavement performance parameter. This PMS depends on pavement condition index, international roughness index, and pavement rutting as explanatory variables to estimate PSI. This study researched new explanatory variables measured by using smartphones’ sensors to estimate PSI. It was found that the variance of the signals (time series acceleration data) acquired by smartphones’ accelerometers could work as a very good explanatory variable to estimate PSI. Two models were developed with high significance ( R2 higher than .9) to predict PSI using the variance of smartphone signals. The initial validation results suggested that using these models could predict, with high certainty, the actual PSI values. The difference between the predicted and the actual PSI values was not statistically different. The study was performed on 20 roadway segments extracted from the Wyoming county roads’ PMS database. In addition, the selected segments had various lengths and geometric features reflecting various roadway segments under any PMS. The proposed methodology is intended to lower the cost of measuring county roads’ pavement conditions by estimating PSI directly without the reliance on the direct measurement of pavement condition parameters.

scholarly journals Assessment of the road based on PCI and IRI roadroid measurement

2018 ◽  
Vol 195 ◽  
pp. 04006 ◽  
Author(s):  
Donny A. Putra ◽  
Mamok Suprapto
Keyword(s):  
Good Condition ◽  
Visual Assessment ◽  
Condition Index ◽  
Assessment Method ◽  
Visual Methods ◽  
International Roughness Index ◽  
Pavement Condition ◽  
The Road ◽  
Roughness Index ◽  
Pavement Condition Index

There are two methods of road assessment, ie, visually and using tools. Visual assessment makes use of the PCI (Pavement Condition Index), while assessment with the Roadroid app can be used to obtain the value of IRI (International Roughness Index) with less cost. Functional assessment of roads in the field more use of visual methods. This method is influenced by the subjectivity of surveyors. Therefore, the assessment using the visual method should be correlated with the assessment method using tools, in order to reduce the subjectivity of road assessment. The research location used is Magetan District Road consisting of 5 road segments. The result shows that the r road assessment using the PCI method has a very good condition, and using IRI Roadroid has a Medium condition. There is a negative (r) correlation between PCI and IRI Roadroid, valued at -0.23. The negative correlation shows that both judgments reversed. Comparison of PCI assessment with IRI Roadroid has a low correlation value and with ttest, yields no comparison of correlation. This result is because the PCI and IRI equally assess the pavement, using different methods.

scholarly journals Assessment of Al-Amarah street within the Al-kut city using pavement condition index (PCI) and GIS technique

2018 ◽  
Vol 162 ◽  
pp. 01033
Author(s):  
Mohammed Al-Neami ◽  
Rasha Al-Rubaee ◽  
Zainab Kareem
Keyword(s):  
Condition Index ◽  
Pavement Management ◽  
Pavement Condition ◽  
The Road ◽  
Gis Technique ◽  
Gis Data ◽  
Pavement Condition Index ◽  
Specific Sign ◽  
Maintenance Process

The capabilities of geographical system and their spatial analysis is considered the most appropriate tools to enhance pavement management operations, with features such as graphical display of pavement condition. In Iraq, most of transportation agencies do not have a tool that is used as a database for road deteriorations, so there is a need for road surveying and storing the collected information in GIS to know the condition of every road with details. Furthermore, these data can be used for maintenance process and estimation of prior cost. This research has been carried out to estimate of flexible pavement condition through visual surveys using the Pavement Condition Index (PCI) method; so it can provide an easy way to calculate the PCI based on GIS data with Micro PAVER software 5.2. Al-Amarah Street, which is internal road in Al-Kut city in the eastern part of Iraq, is used as a case study. The average pavement condition index of the selected case study is found to be “64” using Micro PAVER 5.2 software which mean “Fair” pavement condition. Arc Map 9.3 has been applied in this study to make an integrated maintenance system for each road in the region demonstrating the annual road deteriorations and the resulting change in the PCI values which occurs every year. The study provides an easy and simplified way of presentation the details of deteriorations on the satellite or the geographical map of the road in which each type of distress has been symbolized with specific sign and each PCI value has been represented with specific color.

scholarly journals Use of Deep Learning to Study Modeling Deterioration of Pavements a Case Study in Iowa

2020 ◽  
Vol 5 (11) ◽  
pp. 95
Author(s):  
Seyed Amirhossein Hosseini ◽  
Ahmad Alhasan ◽  
Omar Smadi
Keyword(s):  
Short Term Memory ◽  
Weighted Average ◽  
Condition Index ◽  
The State ◽  
Pavement Management ◽  
Department Of Transportation ◽  
Pavement Condition ◽  
Process And Outcome ◽  
Pavement Condition Index

This paper describes the process and outcome of deterioration modeling for three different pavement types (asphalt, concrete, and composite) in the state of Iowa. Pavement condition data is collected by the Iowa Department of Transportation (DOT) and stored in a Pavement-Management Information System (PMIS). In the state of Iowa, the overall pavement condition is quantified using the Pavement Condition Index (PCI), which is a weighted average of indices representing different types of distress, roughness, and deflection. Deterioration models of PCI as a function of time were developed for the different pavement types using two modeling approaches. The first approach is the long/short-term memory (LSTM), a subset of a recurrent neural network. The second approach, used by the Iowa DOT, is developing individual regression models for each section of the different pavement types. A comparison is made between the two approaches to assess the accuracy of each model. The results show that the LSTM model achieved a higher prediction accuracy over time for all different pavement types.

scholarly journals Evaluation of Natural Airfield Pavements Condition Based on the Airfield Pavement Condition Index (APCI)

2021 ◽  
Vol 11 (13) ◽  
pp. 6139
Author(s):  
Mariusz Wesolowski ◽  
Pawel Iwanowski
Keyword(s):  
Bearing Capacity ◽  
Condition Index ◽  
Technical Condition ◽  
Load Bearing Capacity ◽  
Load Bearing ◽  
Pavement Condition ◽  
Pavement Condition Index ◽  
Probe Test ◽  
The Mathematical Model

Natural pavements are an important element of flights. Among other things, they allow the plane to be safely slowed down after it has exited the runway. For this reason, load bearing capacity of natural airfield pavements and strength of turf layer at a specified level are required. Currently used testing methods, such as CBR (Californian Bearing Ratio) tests or turf probe test, separately do not give a full image of pavement technical condition. The authors presented the methodology for assessing the technical condition of natural airfield surfaces based on the APCI (Airfield Pavement Condition Index). The index is based at the same time on the load bearing capacity of the surface layer up to 0.85 m and turf layer strength. The mathematical model and the classification of airfield pavements in terms of the APCI indicator are presented. The article also presents an example of using the APCI method to assess shoulders and end safety areas of the runway at one of the operating airport facilities.

Sign in / Sign up

Export Citation Format

Share Document