scholarly journals Influence of Pavement Structure, Traffic, and Weather on Urban Flexible Pavement Deterioration

2020 ◽  
Vol 12 (22) ◽  
pp. 9717
Author(s):  
David Llopis-Castelló ◽  
Tatiana García-Segura ◽  
Laura Montalbán-Domingo ◽  
Amalia Sanz-Benlloch ◽  
Eugenio Pellicer
Keyword(s):  
Condition Index ◽  
Flexible Pavement ◽  
Average Height ◽  
Annual Average ◽  
Climate Conditions ◽  
Pavement Condition ◽  
Traffic Demand ◽  
Pavement Deterioration ◽  
Deterioration Process ◽  
Pavement Structure

Various studies have been recently conducted to predict pavement condition, but most of them were developed in a certain region where climate conditions were kept constant and/or the research focused on specific road distresses using single parameters. Thus, this research aimed at determining the influence of pavement structure, traffic demand, and climate factors on urban flexible pavement condition over time. To do this, the Structural Number was used as an indicator of the pavement capacity, various traffic and climate variables were defined, and the Pavement Condition Index was used as a surrogate measure of pavement condition. The analysis was focused on the calibration of regression models by using the K-Fold Cross Validation technique. As a result, for a given pavement age, pavement condition worsens as the Equivalent Single Axle Load and the Annual Average Height of Snow increased. Likewise, a cold Annual Average Temperature (5–15 °C) and a large Annual Average Range of Temperature (20–30 °C) encourage a more aggressive pavement deterioration process. By contrast, warm climates with low temperature variations, which are associated with low precipitation, lead to a longer pavement service life. Additionally, a new classification of climate zones was proposed on the basis of the weather influence on pavement deterioration.

scholarly journals Study of Flexible Pavement Structure Maintenance in Runways with Pavement Condition Index (PCI) Method

2020 ◽  
Vol 27 (1) ◽  
pp. 25
Author(s):  
Meilinda Atika Rachman ◽  
Harmein Rahman ◽  
Bambang Sugeng Subagio ◽  
Sri Hendarto
Keyword(s):  
Condition Index ◽  
Flexible Pavement ◽  
Pavement Condition ◽  
Pavement Condition Index ◽  
Pavement Structure

VALIDITY OF GARBER MODEL IN PREDICTING PAVEMENT CONDITION INDEX OF FLEXIBLE PAVEMENT IN KERBALA CITY

2018 ◽  
Vol 09 (02) ◽  
pp. 139-151
Author(s):  
Hussein Ewadh ◽  
◽  
Raid Almuhanna ◽  
Saja Alasadi ◽  
◽  
...  
Keyword(s):  
Condition Index ◽  
Flexible Pavement ◽  
Pavement Condition ◽  
Pavement Condition Index

scholarly journals Pavement Deterioration Rate and Maintenance Cost for Low-Volume Roads

2020 ◽  
Vol 312 ◽  
pp. 06002
Author(s):  
Turki I Al-Suleiman ◽  
Subhi M Bazlamit ◽  
Mahmoud Azzama ◽  
Hesham S Ahmad
Keyword(s):  
Surface Defects ◽  
Condition Index ◽  
Maintenance Cost ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Deterioration Rate ◽  
Pavement Deterioration ◽  
Pavement Condition Index ◽  
Traffic Volumes ◽  
Over Time

Allocated budgets for maintenance of road networks are normally limited. Therefore, not all roads receive the required attention they deserve in a timely manner. These roads are left to deteriorate until the next maintenance round. The cost associated with delayed maintenance is significantly excessive. A Pavement Maintenance Management System (PMMS) can be a useful tool for evaluation, prioritization of Maintenance and Rehabilitation (M&R) projects, and determination of funding requirements and allocations. The pavement condition is normally indexed using a parameter called Pavement Condition Index (PCI) which represents an overall assessment of surface defects by type, severity and extent. Periodic collections of PCI over time for different sections within the roadway network provide an approach to monitor changes in pavement serviceability over time and can produce useful data to predict and evaluate required maintenance solutions and their associated cost. The researchers intend to use available data collected over the span of a year and a half on sections within the roadway network at the campus of Al-Zaytoonah University of Jordan (ZUJ) to study the relation between the maintenance cost and the pavement deterioration rate. This study may incorporate variables such as pavement age, traffic volumes, maintenance history and pavement condition assessment results. The available records of PCI will be analyzed and the findings will be clearly presented. The practical inclusion of the findings within the current PMMS used at the university will also be detailed.

scholarly journals Comparison of Pavement Performance Models for Urban Road Management System

2020 ◽  
Vol 15 (3) ◽  
pp. 111-129
Author(s):  
Igoris Kravcovas ◽  
Audrius Vaitkus ◽  
Rita Kleizienė
Keyword(s):  
Bearing Capacity ◽  
Management System ◽  
Condition Index ◽  
Performance Model ◽  
Pavement Management ◽  
Pavement Performance ◽  
Performance Models ◽  
Climate Conditions ◽  
Pavement Condition ◽  
Pavement Performance Model

The key factors for effective pavement management system (PMS) are timely preservation and rehabilitation activities, which provide benefit in terms of drivers’ safety, comfort, budget and impact on the environment. In order to reasonably plan the preservation and rehabilitation activities, the pavement performance models are used. The pavement performance models are usually based on damage and distress observations of rural roads, and can be applied to forecast the performance of urban roads. However, the adjustment of the parameters related to traffic volume, speed and load, climate conditions, and maintenance has to be made before adding them to PMS for urban roads. The main objective of this study is to identify the performance indicators and to suggest pavement condition establishment methodology of urban roads in Vilnius. To achieve the objective, the distresses (rut depth and cracks), bearing capacity, and international roughness index (IRI) were measured for fifteen urban roads in service within a two-year period. The distresses, rut depth and IRI were collected with the Road Surface Tester (RST) and bearing capacity of pavement structures were measured with a Falling Weight Deflectometer (FWD). The measured distresses were compared to the threshold values identified in the research. According to the measured data, the combined pavement condition indices using two methodologies were determined, as well as a global condition index for each road. The analysed roads were prioritized for maintenance and rehabilitation in respect to these criteria. Based on the research findings, the recommendations for further pavement condition monitoring and pavement performance model implementation to PMS were highlighted.

scholarly journals Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index

2020 ◽  
Vol 26 (12) ◽  
pp. 81-94
Author(s):  
Muataz Safaa Abed
Keyword(s):  
Regression Models ◽  
Essential Element ◽  
Condition Index ◽  
Flexible Pavement ◽  
Transportation Infrastructure ◽  
International Roughness Index ◽  
Pavement Condition ◽  
Roughness Index ◽  
Pavement Condition Index ◽  
Quadratic Models

Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of each observed distress, the pavement condition surveys were conducted by actually walking through all the sections. Using these data, PCI was calculated utilizing Micro PAVER software. Dynatest Road Surface Profiler (RSP) was used to collect IRI data of all the sections. Using the SPSS software, linear and nonlinear regressions have been used for developing two models between PCI and IRI based on the collected data. These models have the coefficients of determination (R2) equal to 0.715 and 0.722 for linear and quadratic models. Finally, the results indicate the linear and quadratic models are acceptable to predict PCI from IRI directly.

scholarly journals EVALUASI PENILAIAN PERKERASAN JALAN DENGAN METODE PAVEMENT CONDITION INDEX (PCI) (STUDI KASUS RUAS JALAN GAJAH MADA DAN SOROGO KEC. CEPU)

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Hariyanto Hariyanto
Keyword(s):  
Condition Index ◽  
Flexible Pavement ◽  
Pavement Condition ◽  
Pavement Condition Index

<strong>Ruas  jalan  Gajah  Mada  dan  Sorogo  merupakan  akses  menuju  dua perguruan tinggi serta akses menuju instansi pertamina di kota Cepu yang menggunakan perkerasan lentur (<em>flexible pavement</em>). Berbagai kendaraan berat dan ringan melewati ruas jalan tersebut sehingga menyebabkan terjadinya kerusakan jalan. Evaluasi kondisi kerusakan jalan sangat perlu dilakukan untuk monitoring seberapa tingkat kerusakan jalan yang terjadi pada suatu ruas jalan. Penelitian ini bertujuan untuk mengetahui tingkat kerusakan yang terjadi, serta menentukan jenis penanganan kerusakan jalan yang sesuai.Metode yang dipakai dalam penilaian kondisi kerusakan perkerasan jalan ini adalah metode PCI (Pavement Condition  Index), melakukan  survei  secara visual dengan cara melihat dan menganalisis kerusakantersebut berdasarkan jenis, tingkat kerusakaannya serta kuantitas kerusakan untukdigunakan sebagai dasar dalam melakukan kegiatan pemeliharaan dan perbaikan.Cara menganalisanya dengan membagi ruas jalan dalam sampel seluas ±50 m2,menghitung densitas, mencari <em>deduct value </em>pada grafik lalu menghitung <em>PavementConditional Index (PCI).</em>Hasil  evaluasi  penelitian  kondisi  ruas  jalan  Gajah  Mada  dan  Sorogo dengan metode PCI diperoleh kerusakan lubang (1,21%), retak kulit buaya (10,19%), retak pinggir (7,94%), retak memanjang dan melintang (7,45%), bergelombang  (8,1%),  amblas(1,7%),  bahu  jalan  turun(7,1%),  pelapukan  dan butiran lepas (3,25%), dan alur (15,93%), pengelupasan (2,25%), benjol &amp; turun (0,9%),  retak  berkelok  (3,2%),  dan  mengembang  (1,1%).  Dengan  nilai  PCI sebesar 80 untuk ruas jalan Gajah Mada dan 78 untuk ruas jalan Sorogo.</strong>

scholarly journals DEVELOPMENT OF PROGRAM IN C++ FOR ANALYSIS OF NSV SURVEY DATA BY PCI METHOD FOR FLEXIBLE PAVEMENT

2019 ◽  
Vol 31 (3) ◽  
Author(s):  
Soumadeep Bagui ◽  
Swapan Kumar Bagui ◽  
Anukul Saxena
Keyword(s):  
Road Network ◽  
Design Procedure ◽  
Condition Index ◽  
Flexible Pavement ◽  
Regression Equations ◽  
Pavement Condition ◽  
C Language ◽  
Pavement Condition Index ◽  
Future Requirement

This paper presents the development of software in C++ Language for the determination of Pavement Condition Index (PCI) based on the design procedure mentioned in ASTM D 4433 and future requirement of maintenance of existing road /road network. Presently in India, Manual Pavement Condition survey has been replaced by automated Network Survey Vehicle (NSV). PCI procedure mentioned in ASTM D 4433 which needs uses of several curves and same curves have been converted in regression equations. These equations are used to prepare a Program in C++ Language. This will be useful for Pavement Engineer to determine PCI and maintenance strategy.

scholarly journals Identifikasi Kerusakan Perkerasan Lentur Pada Ruas Jalan Soekarno – Hatta, Palembang

2020 ◽  
Vol 20 (01) ◽  
pp. 19-26
Author(s):  
Muhammadiya Rifqi ◽  
Heni Fitriani
Keyword(s):  
Surface Damage ◽  
Condition Index ◽  
Flexible Pavement ◽  
Road Surface ◽  
Survey Method ◽  
Pavement Condition ◽  
The Road ◽  
Road Section ◽  
Pavement Condition Index ◽  
The City

[IN] Ruas Jalan Soekarno-Hatta kota Palembang merupakan Jalan Nasional yang berkelas Jalan Arteri Primer yang dilapisi dengan perkerasan lentur (flexible pavement). Jalan yang diamati dari Simpang Empat fly over Tanjung Api-Api hingga Simpang Empat Macan Lindungan  memiliki panjang 8,45 kilometer. Saat itu kota Palembang sedang menggenjot pembangunan proyek venue dan LRT guna menyukseskan perhelatan olahraga Asian games. Ruas Jalan Soekarno-Hatta Palembang digunakan sebagai aktivitas lalulintas kendaraan proyek akibatnya terjadi peningkatan volume kendaraan dan kepadatan lalulintas yang tak terkendali, sehingga dikhawatirkan berdampak pada kualitas perkerasan jalan tersebut. Tujuan Penelitian ini adalah untuk mengidentifikasi kerusakan permukaan perkerasan lentur jalan dengan menggunakan metode PCI (Pavement Condition Index). Survei metode PCI dilakukan secara visual berdasarkan jenis dan tingkat kerusakan jalan dengan penilaian numerik antara nol (gagal) hingga seratus (sempurna). Hasil identifikasi kerusakan permukaan jalan menunjukkan bahwa kerusakan yang terjadi pada ruas jalan tersebut sebanyak tujuh jenis yaitu kegemukan, amblas, keriting, pelepasan butiran, retak kulit buaya serta tonjolan dan lengkungan. Jumlah unit sampel segmen jalan yang mengalami kerusakan sebanyak 17 unit sampel dari total yang diteliti 68 unit sampel dengan nilai rata-rata PCI didapatkan sebesar 95,655 artinya jalan tersebut dengan kondisi “Sempurna”. Meskipun ruas jalan tersebut tergolong sempurna secara kondisi, akan tetapi masih terdapat kerusakan yang terjadi pada ruas tersebut, untuk itu perlu dilakukan pemeliharaan jalan pada unit sampel yang rusak sehingga dapat menjaga kualitas serta umur layak ruas jalan tersebut. [EN] The Soekarno-Hatta Road section of the city of Palembang is a classy National Road of the Primary Arterial Road that is equipped with flexible pavement. The road chosen from Simpang Empat fly over Tanjung Api-Api to Simpang Empat Macan Lindungan has a length of 8.45 kilometers. At present the city of Palembang is being promoted by a construction site and LRT project to succeed in the sporting event Asian games. The Soekarno-Hatta Palembang Road Section is used as a project vehicle traffic activity resulting in an increase in vehicle volume and uncontrolled traffic density, so it is feared to have an impact on the quality of the pavement. The purpose of this study was to identification road surface damage using the PCI (Pavement Condition Index) method. PCI survey method is carried out  visually based on the type and severity level of road damage with a numerical rating between zero (failed) to one hundred (excellent). The results of identification of road surface damage showed that there were 7 types of damage that occurred on the road section namely bleeding, depression, corrugation, weathering and raveling, potholes, alligator cracking, and bumps and sags. The number of sample units of the road segment that suffered damage as many as 17 sample units of the total studied by 68 units samples with an average value of PCI obtained by 95,655, This means that the road with the condition "excellent". Even though the road is classified as excellent, but damage is still needed in that section, for this reason it is necessary to maintain the road on the damaged sample unit so that it can be used at a reasonable quality for the life of the road section.

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