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1
Zafar, Muhammad Saleem, Syed Naveed Raza Shah, Muhammad Jaffar Memon, Touqeer Ali Rind, and Muhammad Afzal Soomro. "Condition Survey for Evaluation of Pavement Condition Index of a Highway." Civil Engineering Journal 5, no. 6 (June 23, 2019): 1367–83. http://dx.doi.org/10.28991/cej-2019-03091338.
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Pavements are major means of highway infrastructure. Maintenance and rehabilitation of these pavements for the required serviceability is a routine problem faced by highway engineers and organizations. Improvement in road management system results in reduction of time and cost, the pavement condition survey plays a big role in the pavement management. The initial phase in setting up a pavement management system (PMS) is road network identification. A vital element of a PMS is the capacity to assess the present condition of a pavement network and anticipation of future condition. The pavement condition index (PCI) is a numerical index generally utilized for the assessment of the operational condition & structural reliability of pavements. Estimation of the PCI is dependent on the results of a visual inspection in which the type, severity, and quantity of distresses are distinguished. In this research, a pavement distress condition rating strategy was utilized to accomplish the goals of this study. The main targets of this research were to categorize the common types of distress that exist on “Lakhi Larkana National Highway (N-105)”, and to estimate the pavement condition index. Using these data, Average PCI for the highway section was calculated. PCI to assess the pavement performance, 10 out of 19 defects were recognized in the pavement, as stated by the PCI method. Results indicated that the common pavement distress types were depressions, polished aggregate, rutting, potholes, block cracking, and alligator cracking.
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Abed, Muataz Safaa. "Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index." Journal of Engineering 26, no. 12 (December 1, 2020): 81–94. http://dx.doi.org/10.31026/j.eng.2020.12.05.
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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.
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Wesolowski, Mariusz, and Pawel Iwanowski. "Evaluation of Natural Airfield Pavements Condition Based on the Airfield Pavement Condition Index (APCI)." Applied Sciences 11, no. 13 (July 1, 2021): 6139. http://dx.doi.org/10.3390/app11136139.
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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.
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Zhang, Zhanmin, German Claros, Lance Manuel, and Ivan Damnjanovic. "Development of Structural Condition Index to Support Pavement Maintenance and Rehabilitation Decisions at Network Level." Transportation Research Record: Journal of the Transportation Research Board 1827, no. 1 (January 2003): 10–17. http://dx.doi.org/10.3141/1827-02.
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Every year, state highway agencies apply large amounts of seal coats and thin overlays to pavements to improve the surface condition, but these measures do not successfully address the problem. Overall pavement condition continues to deteriorate because of the structural deformation of pavement layers and the subgrade. To make effective decisions about the type of treatment needed, one should take into consideration the structural condition of a pavement. Several different structural estimators can be calculated by using falling weight deflectometer data and information stored in the Pavement Management Information System (PMIS) at the Texas Department of Transportation. The analysis considers pavement modulus and structural number as the structural estimators of a pavement. The evaluation method is based on the sensitivity of the structural estimators to deterioration descriptors. The deterioration per equivalent single-axle load of all major scores stored in the Texas PMIS is proposed as the primary indicator of pavement deterioration. In addition, the use of the structural condition index is recommended as a screening tool to discriminate between pavements that need structural reinforcement and those that do not. This index is calibrated for use in maintenance and rehabilitation analysis at the network level.
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Zoccali, Pablo, Giuseppe Loprencipe, and Andrea Galoni. "Sampietrini Stone Pavements: Distress Analysis Using Pavement Condition Index Method." Applied Sciences 7, no. 7 (June 29, 2017): 669. http://dx.doi.org/10.3390/app7070669.
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Wesołowski, Mariusz, and Paweł Iwanowski. "Evaluation of Asphalt Concrete Airport Pavement Conditions Based on the Airfield Pavement Condition Index (APCI) in Scope of Flight Safety." Aerospace 7, no. 6 (June 15, 2020): 78. http://dx.doi.org/10.3390/aerospace7060078.
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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.
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Bryce, James, Richard Boadi, and Jonathan Groeger. "Relating Pavement Condition Index and Present Serviceability Rating for Asphalt-Surfaced Pavements." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 3 (February 27, 2019): 308–12. http://dx.doi.org/10.1177/0361198119833671.
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In response to the two latest transportation funding authorization bills, the Moving Ahead for Progress in the 21st Century Act and the Fixing America’s Surface Transportation Act, rules that require the reporting of specific pavement condition measures have been developed and encoded into federal regulation. Pavement performance rules published to the federal register require the reporting of the International Roughness Index (IRI), percent cracking, rutting (for asphalt-surfaced pavements) and faulting (for jointed concrete pavements). Allowing that the measurement of the IRI on pavements with a speed limit below 40 mph is not expected to provide a reliable estimation of ride quality, the rules permit the reporting of the present serviceability rating (PSR) on these routes. However, many agencies do not measure the PSR or collect the slope variance data required to estimate the PSR. In light of not having the data required to directly estimate the PSR, this paper presents a model to estimate the PSR using data collected during a Pavement Condition Index (PCI) survey. Furthermore, this paper explores the reasons why pavements can have a good PCI and poor PSR and vice versa. The model presented in this paper provides a reasonable estimate of the PSR, though it is noted that agencies who wish to report PSR should conduct an updated assessment of rider satisfaction to develop a stronger correlation of PSR and PCI.
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Jung, Haekook, Yongjae Kim, Seungwon Kim, Cheolwoo Park, and Jeong-Hee Nam. "Life Extension of Aged Jointed Plain Concrete Pavement through Remodeling Index–Based Analysis." Materials 13, no. 13 (July 4, 2020): 2982. http://dx.doi.org/10.3390/ma13132982.
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As jointed plain concrete pavements (JPCP) age in South Korea, the cost of pavement maintenance is increasing annually. To extend the life of jointed concrete pavements through preventive maintenance, this study used 2017 pavement management system data to analyze the effects of traffic volume, alkali–silica reaction (ASR) grade, age, smoothness, and damaged area on the remodeling index (RMI—a measure of expressway pavement condition). In addition, this study evaluates the final RMI as well as the corresponding pavement condition and change in RMI value after conducting preventive maintenance in lieu of resurfacing or overlaying. The results demonstrated that the effect of ASR grade increased as the RMI forecast year increased and that change in surface distress (△SD) increased with age (most intensively when the pavement was 15–20 years of age). Moreover, change in international roughness index (△IRI) increased with age and traffic volume (similarly within 15–20 years of pavement age). Hence, preventive maintenance is a must for sections with high traffic volume and age even if the RMI is low. Finally, performing repairs through preventive maintenance decreases the number of expressway sections requiring resurfacing and overlaying, thus extending the life of the concrete pavement.
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Chou, Chia-Pei, and Chien-Yen Chang. "Algorithm for Determining Weight Factors of Pavement Distress Index." Transportation Research Record: Journal of the Transportation Research Board 1592, no. 1 (January 1997): 63–69. http://dx.doi.org/10.3141/1592-08.
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Distress is one of the primary measurements of pavement condition. Thus, in a pavement evaluation program, distress type, severity, and extent should be properly identified. A pavement distress index (PDI) may be calculated by mathematically combining the effects of distresses on pavement conditions. Before the calculation of PDI, each distress attribute must be assigned a weight factor and a severity factor. An analytical algorithm that converts the subjective rating values of distress attributes to a rational weighting scale that provides quantified measurements of the effects of each distress on pavement damage and riding quality is presented. A case study for applying this procedure to the pavements of roadway samples from the Highway Bureau and the National Freeway Bureau in Taiwan also is presented. Through the analysis procedure, it was found that pothole has the largest weight factor (100) and that longitudinal crack has the lowest (49). The severity factors vary from 0.24 to 1.00, depending on the distress type and severity level.
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Nurjanah Ahmad, Siti, Tri Harianto, Lawalenna Samang, and Muralia Hustim. "Level vulnerability damage of pavement using Pavement Condition Index method." MATEC Web of Conferences 181 (2018): 11003. http://dx.doi.org/10.1051/matecconf/201818111003.
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This study aims to assess the vulnerability of road pavement damage using the Pavement Condition Index (PCI) method, including the direction of handling pavement road damage. Assessment of the level of road surface damage is based on the type of damage, the degree of damage, and amount of damage. Field observations and surveys were conducted on several Collector roads in Kendari. The mean PCI score as an indicator of damage to the Mokodompit road segment shows moderate damage conditions with a mean the value PCIaverage = 53 and surface damage area = 34.419% and the countermeasures according to the Bina Marga Standard recommend patching and adding pavement layers. Assessment of vulnerabilities Manunggal road damage indicates moderate damage to the value PCIaverage = 49 With the extent of surface damage = 34,419% and the response according to Standard by filling a crack with a mixture of liquid asphalt and sand.
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Shah, Anwar, Susan Tighe, and Allen Stewart. "Development of a unique deterioration index, prioritization methodology, and foreign object damage evaluation models for Canadian airfield pavement management." Canadian Journal of Civil Engineering 31, no. 4 (August 1, 2004): 608–18. http://dx.doi.org/10.1139/l04-018.
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Modelling of pavement performance deterioration is a critical engineering process in Pavement Management Systems. Most of the existing Airport Pavement Management Systems (APMS) employ limited surface distresses in their performance evaluation models. These systems may not serve the objectives of some agencies. It is essential for an effective APMS to include evaluation models that adequately address the specific needs of the agency. This paper presents the development of a unique pavement deterioration index, i.e., the Condition Rating Index, developed for 1 Canadian Air Division (1 CAD). This index is modelled to serve the specific needs of 1 CAD effectively. Performance prediction models for the various classes of pavements are developed based on Markov Chains. The prioritization methodology employed also reflects the needs of 1 CAD. Consequently, this paper investigates the quantification and prediction of Foreign Object Damage (FODp). The FODp Index is developed as well as defined. Prediction models for FODp are developed along with the establishment of critical states of the FODp Index.Key words: airport pavement management system, Condition Rating Index, pavement performance evaluation models, Foreign Object Damage, 1 Canadian Air Division.
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Wesołowski, Mariusz, and Paweł Iwanowski. "APCI Evaluation Method for Cement Concrete Airport Pavements in the Scope of Air Operation Safety and Air Transport Participants Life." International Journal of Environmental Research and Public Health 17, no. 5 (March 4, 2020): 1663. http://dx.doi.org/10.3390/ijerph17051663.
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Many factors have an impact on flight operation safety and air transport participants life. This article presents one of them, which is maintenance of the airport infrastructure in a good condition, with proper infrastructure management, in particular of cash and human resources. At the beginning of the article, attention is paid to the aspect of safety and human life in air transport. Also, an overview of world experience in the field of assessment of the technical condition of airport pavements was presented, including the standard method of the Pavement Condition Index (PCI) estimation. Then, the authors propose an innovative method of assessing the condition of airport pavements based on the Airfield Pavement Condition Index (APCI), taking into account, apart from the extent of surface damage, such parameters as load capacity, evenness, roughness, and bond strength. This approach gives a broader picture of the actual condition of the airport pavement, which has a great importance on flight operation safety, including passengers and cruel life. Next the described research method is experimentally verified in real conditions at Polish airports. Finally, an example of using the APCI method in the assessment of selected airport pavements from Polish airports is presented. The results of tests performed on five functional elements of a military airfield are presented. A satisfactory result is obtained for three elements, an adequate—for two.
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Yuan, Jie, and Michael A. Mooney. "Development of Adaptive Performance Models for Oklahoma Airfield Pavement Management System." Transportation Research Record: Journal of the Transportation Research Board 1853, no. 1 (January 2003): 44–54. http://dx.doi.org/10.3141/1853-06.
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The Oklahoma airfield pavement management system (APMS) is a set of pavement management tools that can assist with pavement condition evaluation, as well as prioritization and scheduling of pavement maintenance and rehabilitation activities. Pavement performance models were developed to support the APMS for more than 70 Oklahoma general aviation airports. The family modeling method based on the pavement condition index was tailored to fit the deterioration characteristics of these airfield pavements. The statistical and engineering significance of seven levels of pavement factors was investigated, and pavement factors that affect pavement deterioration significantly were identified as family variables. Asphalt concrete pavement families were formed by sorting pavement function, distress cause, and pavement thickness, while portland cement concrete pavements were divided into families according to pavement function and climate zone. The family polynomial curves were able to reveal the expected deterioration patterns and are logical in engineering principle. Rooted by an adaptive database, the system accepts expert opinion and automatically integrates effects of major maintenance and rehabilitation activities into modeling. From the up-to-date database, the performance models update forecasts automatically.
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Qiao, Y. J., and X. R. Ma. "Analysis on Shear Stress Design Index of Long-Life Asphalt Pavement under Complex Traffic Conditions." Applied Mechanics and Materials 743 (March 2015): 115–20. http://dx.doi.org/10.4028/www.scientific.net/amm.743.115.
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Overloading, horizontal load effect and soft ground are the main factors that influence the formation of shear rutting of asphalt pavement. Based on the analysis on the mechanical features of Long-life asphalt pavement with flexible base, this thesis puts forward asphalt pavement’s shear stress design index under the condition of shear fatigue damage and one-off shear damage of asphalt pavement, and provides their calculating method , and gives cases analysis.
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Golroo, Amir, and Susan L. Tighe. "Fuzzy set approach to condition assessments of novel sustainable pavements in the Canadian climate." Canadian Journal of Civil Engineering 36, no. 5 (May 2009): 754–64. http://dx.doi.org/10.1139/l09-025.
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Since the use of pervious concrete pavement structures (PCPSs) is essentially still in the trial stage in Canada, long-term and quantitative pavement condition data are not available. The existing approaches applied to assess pervious concrete pavement structure (PCPS) conditions are ad hoc and suffer from methodological limitations. A fuzzy set technique is proposed herein as an efficient tool for dealing with qualitative and incomplete pavement condition data on distress types, severities, densities, and weighting factors. Using this method, a comprehensive fuzzy condition index was developed based on Ministry of Transportation of Ontario (MTO) methodology and using fuzzy pavement condition data. This fuzzy condition index was converted to a single value that allowed for comparisons of pavement conditions using several ranking techniques. A case study of 24 PCPS sites was utilized to demonstrate how the fuzzy representations of the condition index compared with associated single values. It is shown that this approach can effectively provide extensive condition indices for PCPSs and rank them accordingly, using only limited and imprecise pavement condition data.
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Wadalkar, Shruti, Ravindra K. Lad, and Rakesh K. Jain. "Performance Assessment of Flexible Pavements: Fuzzy Evidence Theory Approach." Civil Engineering Journal 6, no. 8 (August 1, 2020): 1492–502. http://dx.doi.org/10.28991/cej-2020-03091562.
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Pavement performance evaluation is one of the most important steps of the pavement management system. It consists of identifying pavement condition according to various distresses occurs in the pavement surface. Data collection in performance assessment of road is done in several ways. An attempt has been made to address the problem and a new formalism is proposed for performance assessment of flexible pavements. Vagueness in the perception of expert for performance assessment of pavement based on techno-scientific parameters in linguistic terms for the domain base usage coupled with impression in parametric data calls for the application of fuzzy modeling. For this study fuzzy evidence theory weightage method “Dempster’s Shafer’s (D-S)” is applied to determine the Pavement Condition Distress Index (PCDI) of flexible pavement. D-S theory provides a designed framework to overcome the risk of uncertainty and ignorance. For the assessment of pavements five major structural indicators like longitudinal cracks, transverse cracks etc. and eleven major functional indicators like potholes, rutting, patching etc. are considered. Expert opinion is taken from the experts who are involved in the field of transportation engineering. Questionnaire Survey methodology has been adopted for the collection of experts opinions. Five linguistic terms are used for the same, which are, ‘Very important’, ‘Important’, ‘Average’, ‘Less important’ and ‘Not Important’. Based on PCDI, Pavement Condition Index (PCI) is calculated. The rating of flexible pavements is also done based on PCI. For the application of the model, five road segments of MIDC Chakan, Pune area is considered. PCI of all the road segments is determined by using the stated index. Based on PCI value, road segment 1 rated 5 with less PCI value and road segment 4 rated 1 with high PCI value. The defined method is also compared with the rating system given in Indian Road Congress (IRC -82-2015).
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Robbins, Mary, Nam Tran, and Audrey Copeland. "Determining the Age and Smoothness of Asphalt and Concrete Pavements at the Time of First Rehabilitation using Long-Term Pavement Performance Program Data." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 40 (August 29, 2018): 176–85. http://dx.doi.org/10.1177/0361198118792120.
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Initial performance period is an important input in life-cycle cost analysis (LCCA). An objective of this study was thus to determine actual initial performance periods, as the pavement age at first rehabilitation, for asphalt and concrete pavements using Long-Term Pavement Performance (LTPP) program data. In addition, most agencies use International Roughness Index (IRI), a measure of pavement roughness applicable to both asphalt and concrete pavements, in their decision-making and performance-evaluation process. A secondary objective was, therefore, to determine the pavement roughness condition at the time of first rehabilitation using the same dataset. Based on surveys of highway agencies, initial performance periods frequently used in LCCA for asphalt pavements are between 10 and 15 years, while the average asphalt pavement age at time of first rehabilitation in the LTPP program was found to be approximately 18 years. For concrete pavements, most initial performance periods used in LCCA are between 20 and 25 years, whereas the average concrete pavement age at the time of first rehabilitation in the LTPP program is about 24 years. This suggests initial performance period values used for LCCA do not adequately represent the actual age of asphalt pavements at the time of first rehabilitation, while they are generally representative of actual concrete pavement age at the time of first rehabilitation. Also, it was found that asphalt pavements are typically rehabilitated when they are in good or fair condition according to Federal Highway Administration (FHWA) IRI criteria whereas concrete pavements are typically not rehabilitated until the pavement is in fair or poor condition.
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Simpson, Amy L., James M. Bryce, Gonzalo R. J. Rada, and Jonathan L. Groeger. "Time-Series Review of Highway Performance Monitoring System Data." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 40 (April 30, 2018): 1–6. http://dx.doi.org/10.1177/0361198118767415.
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The passing of the Moving Ahead for Progress in the 21st Century Act required the FHWA to adopt pavement performance measures for evaluating the condition of the interstate highway system (IHS) and the national highway system (NHS). In January 2015, the FHWA issued a notice of proposed rulemaking (NPRM) to establish performance measures to assess pavement conditions on the IHS and NHS, with the final rule published in January 2017. The four measures were 1) Percentage of pavements on the IHS in good condition; 2) Percentage of pavements on the IHS in poor condition; 3) Percentage of pavements on the NHS (excluding IHS) in good condition; and 4) Percentage of pavements on the NHS (excluding IHS) in poor condition. Pavement condition is determined by the following metrics in the Highway Performance Monitoring System (HPMS): International Roughness Index, cracking percent, rutting, and faulting. FHWA commissioned a study to collate a statistically significant sample of the IHS to evaluate the efficacy of the HPMS and to recommend improvements in data collection and reporting processes to meet NPRM requirements. As part of the referenced study, a time-series review was conducted of the HPMS to identify changes in the data from 2013 to 2015 and to determine how these data compare with the study-collected data. This paper discusses the review of HPMS data, identifying changes in the pavement condition metrics, and overall condition. In general, the HPMS database exhibited improvements, with more complete data and fewer anomalies, in 2015 compared with 2013.
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Yang, Jidong, Jian John Lu, Manjriker Gunaratne, and Qiaojun Xiang. "Forecasting Overall Pavement Condition with Neural Networks: Application on Florida Highway Network." Transportation Research Record: Journal of the Transportation Research Board 1853, no. 1 (January 2003): 3–12. http://dx.doi.org/10.3141/1853-01.
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Timely identification of undesirable crack, ride, and rut conditions is a critical issue in pavement management systems at the network level. The overall pavement surface condition is determined by these individual pavement surface conditions. A research project was carried out to implement an overall methodology for pavement condition prediction that uses artificial neural networks (ANNs). In the research, three ANN models were developed to predict the three key indices—crack rating, ride rating, and rut rating—used by the Florida Department of Transportation (FDOT) for pavement evaluation. The ANN models for each index were trained and tested by using the FDOT pavement condition database. In addition to the three key indices, FDOT uses a composite index called pavement condition rating (PCR), which is the minimum of the three key indices, to summarize overall pavement surface condition for pavement management. PCR is forecast with a combination of the three ANN models. Results of the research suggest that the ANN models are more accurate than the traditional regression models. These ANN models can be expected to have a significant effect on FDOT's pavement management system.
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Psalmen Hasibuan, Rijal, and Medis Sejahtera Surbakti. "Study of Pavement Condition Index (PCI) relationship with International Roughness Index (IRI) on Flexible Pavement." MATEC Web of Conferences 258 (2019): 03019. http://dx.doi.org/10.1051/matecconf/201925803019.
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Road is an infrastructure that built to support the movement of the vehicle from one place to another for different purposes. Today, it is often found damage to road infrastructure, both local roads, and arterial roads. Therefore, to keep the pavement condition to remain reliable, in Indonesia has a periodic program by conducting an objective functional inspection of roads regulated by Bina Marga using the International Roughness Index (IRI). However, the IRI examination is not sufficient to represent the actual field condition; it is necessary to perform subjective functional examination by appraising the road one of them is Pavement Condition Index (PCI, ASTM D 6433). This method has been widely applied in some countries because it has many advantages. However, to do this inspection requires considerable cost, then there needs to be a model to get the relationship between these two parameters of the road. The selected case study was arterial road segment in Medan City, that is in Medan inner ring road. Based on the results of the analysis, there is a difference between the functional conditions of PCI and IRI. The equation derived from these two parameters is by exponential regression equation, with equation IRI = 16.07exp-0.26PCI. with R2 of 59% with correlation coefficient value (r) of -0.768. The value of R2 indicates that PCI gives a strong influence on IRI value.
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Wesołowski, Mariusz, Piotr Barszcz, and Krzysztof Blacha. "Influence of the condition of the airfield pavement structures on the operation safety of aircraft." Journal of KONBiN 42, no. 1 (June 1, 2017): 305–28. http://dx.doi.org/10.1515/jok-2017-0031.
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Abstract The structure of the airfield pavement is a set of layers, whose task is to take over and transfer loads from moving aircraft to a ground subsoil in a safety manner. Airfield pavements are designed for a specific period of operation, assuming the forecasted intensity and the structure of the air traffic. The safety of air operations executed by the aircraft on airfield pavements depends primarily on the condition of their structure’s load capacity. In order to assess the load capacity of airfield pavements, the method ACN-PCN, which was introduced by the International Civil Aviation Organization ICAO and according to which the load capacity of the airfield pavement is expressed with the PCN index, is applied.
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Isradi, Muhammad, Zaenal Arifin, and Asep Sudrajat. "Analysis of the Damage of Rigid Pavement Road by Using Pavement Condition Index (PCI)." Journal of Applied Science, Engineering, Technology, and Education 1, no. 2 (June 27, 2020): 193–202. http://dx.doi.org/10.35877/454ri.asci1242.
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Bogasari Road, which is located in Citeureup sub-district, Bogor Regency, within the PT Indocement Tunggal Prakarsa industrial area, is a road that uses rigid pavement. The road is always passed by heavily loaded vehicles that affect road pavement conditions and the level of comfort and safety for road users. The study's purpose is to determine the average daily traffic volume, determine the value of conditions in the rigid pavement, and provide input to relevant agencies in terms of solutions and road repair costs. The method used in the analysis is the Pavement Condition Index (PCI). The study shows the average daily traffic of 2,883 vehicles/hour/day and the average pavement condition value of 66.57 with a good rating, or in good condition. It also provides a method of repair by functional means.
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Youssef, Medhat Abdelrahman, and Abdelbary Altayb Elbasher. "Optimal Maintenance Works for the Aborshada Road in the Western Region of Libya." Slovak Journal of Civil Engineering 22, no. 3 (September 1, 2014): 37–44. http://dx.doi.org/10.2478/sjce-2014-0016.
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Abstract In this research, the condition of a road pavement was investigated for the Aborshada Road in the Gharian region of Libya to determine the optimal maintenance works. Previously, a simple engineering judgment was the only procedure followed by the Gharian municipal engineers for evaluating pavements and prioritizing maintenance. The surface condition of the Aborshada Road pavement was investigated using “the Pavement Condition Index (PCI)” visual technique. The pavement was inspected to survey the different distresses in each sample unit. Ninteen pavement distresses were classified according to the PCI standards (PCI for roads and parking lots became an ASTM standard in 2007 (D6433-07)). It was necessary to know the most common distresses of the Aborshada Road to provide assistance for the decision maker in his evaluation of the pavement and the optimum repair method to be selected. This study reveals the actual performance of the pavements and suggests the research required for dealing with the pavement maintenance problem in Libya, especially in the western region. The best maintenance alternative for Aborshada Road was Case No. 3 (Potholes, Long. & Trans. Cracking and Alligator Crack Maintenance). Also, the most common pavement distresses on the Aborshada Road were Distress Nos. 1, 3, 6, 7, 10 and 13 according to the ASTM - D6433-07 classification
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Dossey, Terry, Mauricio Ruiz, and B. Frank Mccullough. "Development of Jointed Concrete Pavement Database for State of Texas." Transportation Research Record: Journal of the Transportation Research Board 1525, no. 1 (January 1996): 97–106. http://dx.doi.org/10.1177/0361198196152500111.
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A jointed concrete pavement database was developed as part of a pavement information management system for Texas. Topics discussed include the identification of variables, a statewide selection of pavement projects using an experimental factorial design, and the collection of performance information through a visual condition survey. A preliminary distress index for jointed pavements is also presented. In this analysis, the distress variables collected in the field are reduced to a single performance value and related statistically to the various design variables of the pavement projects investigated.
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Choi, Seunghyun, and Myungsik Do. "Development of the Road Pavement Deterioration Model Based on the Deep Learning Method." Electronics 9, no. 1 (December 18, 2019): 3. http://dx.doi.org/10.3390/electronics9010003.
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In Korea, data on pavement conditions, such as cracks, rutting depth, and the international roughness index, are obtained using automatic pavement condition investigation equipment, such as ARAN and KRISS, for the same sections of national highways annually to manage their pavement conditions. This study predicts the deterioration of road pavement by using monitoring data from the Korean National Highway Pavement Management System and a recurrent neural network algorithm. The constructed algorithm predicts the pavement condition index for each section of the road network for one year by learning from the time series data for the preceding 10 years. Because pavement type, traffic load, and environmental characteristics differed by section, the sequence lengths (SQL) necessary to optimize each section were also different. The results of minimizing the root-mean-square error, according to the SQL by section and pavement condition index, showed that the error was reduced by 58.3–68.2% with a SQL value of 1, while pavement deterioration in each section could be predicted with a high coefficient of determination of 0.71–0.87. The accurate prediction of maintenance timing for pavement in this study will help optimize the life cycle of road pavement by increasing its life expectancy and reducing its maintenance budget.
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Vyas, Vidhi, Ajit Pratap Singh, and Anshuman Srivastava. "Quantification of airfield pavement condition using soft-computing technique." World Journal of Engineering 17, no. 6 (October 7, 2020): 877–90. http://dx.doi.org/10.1108/wje-01-2020-0021.
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Purpose 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. Design/methodology/approach 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. Findings 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. Practical implications The developed methodology is very useful for its practical implications, and it is explained using a case study of an international airport. Originality/value 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.
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Do, Myung-Sik, Yong-Jun Lee, Kwang-Su Lim, and Soo-Ahn Kwon. "Estimation of Performance and Pavement Life using National Highway Pavement Condition Index." Journal of the Korean Society of Road Engineers 14, no. 5 (October 15, 2012): 11–19. http://dx.doi.org/10.7855/ijhe.2012.14.5.011.
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Al-Rubaee, Rasha H. A., Ammar A. M. Shubber, and Hussein Saad Khaleefah. "Evaluation of rigid pavement using the Pavement Condition Index: A Case Study." IOP Conference Series: Materials Science and Engineering 737 (March 6, 2020): 012128. http://dx.doi.org/10.1088/1757-899x/737/1/012128.
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Wu, Shi Mei, Guo Zhu Cheng, and Yu Long Pei. "Evaluation on Driver’s Mental Tenseness under the Condition of Snow Pavement." Advanced Materials Research 446-449 (January 2012): 2422–25. http://dx.doi.org/10.4028/www.scientific.net/amr.446-449.2422.
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In order to study driver’s mental workload when driving on snow pavement, data of snow pavement’s friction coefficient were observed and blood flow, skin temperature and respiration volume of driver’s were obtained through field experiment. Friction coefficient of snow pavement ranges from 0.04 to 0.31. The correlation between temperature of atmosphere and friction coefficient, snow’s thickness and friction coefficient are weak. And the correlation between moisture of atmosphere and friction coefficient, snow’s degree of compaction and friction coefficient are strong. Multi-linear regression model was established among moisture of atmosphere, snow’s degree of compaction and friction coefficient. The average value of inexperienced driver’s blood flow, skin temperature and respiration volume are 171.423mv, 33.263°C and 2317.263ml when driving on snow pavement, which are far greater than that of experienced driver’s and that of inexperienced driver’s when being immobile and driving on non-snow pavement. The effects of snow pavement on mental workload of inexperienced driver’s are obvious. According to driver’s physiological index, calculation model of diver’s tenseness degree was established and it can evaluate tenseness of drivers quantitatively.
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Kim, Jangrak, Daegeun Park, Youngchan Suh, and Donghyuk Jung. "Development of Sidewalk Block Pavement Condition Index (SBPCI) using Analytical Hierarchy Process." Sustainability 11, no. 24 (December 11, 2019): 7086. http://dx.doi.org/10.3390/su11247086.
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This study aimed at developing SBPCI (Sidewalk Block Pavement Condition Index) with sidewalk pavement condition survey data of Seoul city in order to attain a quantitative evaluation method of sidewalk pavement condition. The distress patterns of sidewalk pavement were classified into four groups of Crack/Loss, Roughness, Aging, and Corner Break. AHP (Analytic Hierarchy Process) technique was employed on the basis of the raking process of 31 pavement managers in order to analyze the influence of the distress patterns on the sidewalk pavement condition. The AHP analysis result indicated the weight of pop out, roughness, surface abrasion, and corner break were 0.521, 0.244, 0.164, and 0.070, respectively, by distress type. A model equation was derived by using the sidewalk pavement condition data from 420 sections. The correlation analysis between the result of the model equation and distress type revealed that the correlation of corner break was low to be excluded from SBPCI model; while pop out, roughness, and surface abrasion were statistically significant to be used as three variables of the developed SBPCI model.
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Baker, Michael J., Joe P. Mahoney, and Nadarajah “Siva” Sivaneswaran. "Engineering Application of Washington State’s Pavement Management System." Transportation Research Record: Journal of the Transportation Research Board 1643, no. 1 (January 1998): 25–33. http://dx.doi.org/10.3141/1643-05.
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Previous investigation into the Washington State Department of Transportation’s (WSDOT) Pavement Management System (WSPMS) revealed pavement sections on the state route system that were outperforming or underperforming other pavement sections constructed of similar materials and subjected to similar traffic and environmental conditions. Reasons were not clear. The WSPMS was used to identify superior and inferior candidate pavements for further investigation. All state route pavements were stratified into 18 distinct analysis groups, and population statistics were generated for each group providing WSDOT with a snapshot of the current “state of the state route system” and providing the basis for selecting candidate pavements. The five performance measures considered included: age of the surface course, a distress-based pavement structural condition score, annual design-lane equivalent single axle loads, roughness (in terms of International Roughness Index), and rutting. Results of the analysis suggest that WSDOT is properly designing layer thicknesses at appropriate reliability levels. Also, in 6 of 10 analysis group comparisons, inferior pavements were actually thicker than superior pavements. Both findings suggest that thickness design factors are not the primary cause of inferior performance in Washington State; construction, material and site specific factors are likely the cause. Additionally, in an international effort to exchange information on pavement performance and construction practices, highlights of a comparative study of pavement performance with South Africa’s Gauteng Department of Transportation are presented.
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Figueroa, Miguel. "Relationship of operating speed with pavement serviceability from the pavement condition index. Case of study: Barranquilla, Colombia." Indian Journal of Science and Technology 13, no. 37 (October 10, 2020): 3904–9. http://dx.doi.org/10.17485/ijst/v13i37.764.
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Objectives: The present research aims to find the relationship in the field that the road condition index has concerning its operating speed, based on the expected assumption that the worse the condition index, the lower the road operating speed will be. Methodology: The methodology used to carry out this research consisted in the estimation of the condition index (PCI) and the measurement of speeds in different road sections of the city of Barranquilla (Colombia), where a record of the surface conditions of the pavement from 0 when it was failed and 100 for pavement in excellent condition. In the case of speed recording, the plate method was used to obtain operating speeds. Then, using the UNALPCIA software, the value of the PCI of the evaluated road sections was estimated and then correlated with the operating speeds obtained in the field of those sections. Findings: The main findings obtained from the investigation consist of the effective relationship between the value of the PCI and the operating speed, having that the lower the condition index, the lower the operating speed on the road due to the presence of damage to the road pavement surface. Novelty: The study of the surface conditions of the pavement in the cities of Colombia is little studied, which leads to policies associated with the maintenance of pavement structures becoming late, given that the comfort and speed of operation allowed by these do not is appropriate, even though its structural function is still in force. Keywords: Condition index; comfort; policies; surface condition
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Eldin, Neil N., and Ahmed B. Senouci. "Condition rating of rigid pavements by neural networks." Canadian Journal of Civil Engineering 22, no. 5 (October 1, 1995): 861–70. http://dx.doi.org/10.1139/l95-104.
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This paper discusses the development and the implementation of a neural network for the condition rating of rigid concrete pavements. The condition rating scheme employed by Oregon State Department of Transportation was used as the basis for the development of the network presented. A training set of 298 cases was used to train the network. The network adequately learned the training examples with an average training error of 0.011. A testing set of 3902 cases was used to check the generalization ability of the system. The network was able to determine the correct condition ratings with an average testing error of 0.022. The network ability of dealing with noisy data was also tested. Up to 40% noise was added to the data and introduced to the network. The results showed that the network presented could accurately identify condition rating relationships at high level of noise. Finally, a statistical hypothesis test was conducted to demonstrate the system's fault-tolerance and generalization properties. Key words: neural networks, condition rating, condition index, rigid pavements, pavement distresses, pavement maintenance, fault-tolerance, generalization, noisy data.
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Hajek, Jerry J., Thomas J. Kazmierowski, and Graham Musgrove. "Switching to International Roughness Index." Transportation Research Record: Journal of the Transportation Research Board 1643, no. 1 (January 1998): 116–24. http://dx.doi.org/10.3141/1643-15.
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The International Roughness Index (IRI) has become a well-recognized standard for measurement of pavement roughness. The main objectives of the study were to evaluate the consequences of switching to IRI roughness measurements, and to develop a procedure for switching from measuring roughness with a response-type device, used for more than 10 years, to an IRI device. The study consisted of two parts. In the first part, the repeatability and consistency of roughness measurements obtained by three different IRI-measuring systems using a 10-section calibration circuit was evaluated. In the second part, transfer functions relating IRI with a subjectively measured ride condition rating for a large pavement network consisting of asphaltic concrete, rigid, and surface-treated pavements were developed. Based on the results of the calibration circuit, the three IRI-measuring systems were proved equally capable of providing repeatable and reliable roughness measurements for network-level monitoring purposes, and their individual results correlated very well. However, because of systematic differences between the results, the IRI-measuring systems cannot be used interchangeably and without proper calibration. Based on the results obtained for the network, different transfer functions were required and developed for the four pavement types (asphaltic concrete, composite, jointed portland cement concrete, and surface-treated). IRI roughness measurements provided better prediction of the ride condition rating than the response-type roughness measurements. These results support the switch to IRI roughness measurements.
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Shoukry, Samir N., David R. Martinelli, and Jennifer A. Reigle. "Universal Pavement Distress Evaluator Based on Fuzzy Sets." Transportation Research Record: Journal of the Transportation Research Board 1592, no. 1 (January 1997): 180–86. http://dx.doi.org/10.3141/1592-20.
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Setting priorities for pavement maintenance and rehabilitation depends on the availability of a universal scale for assessing the condition of every element in the network. The condition of a pavement section has traditionally been assessed by several condition indexes. The present serviceability index (PSI) is one common evaluator used to describe the functional condition with respect to ride quality. Pavement condition index is another index commonly used to describe the extent of distress on a pavement section. During the decision-making process, both classes of indexes are needed to evaluate the overall status of a pavement section in comparison to other sections in the network. Traditionally, regression techniques were used for the development of functions that relate condition indexes to the information recorded in the pavement management database. This approach produces mathematical functions that are limited to a particular database. The functions so developed may also suffer from inaccuracies due to errors in data collection and recording. There is a need for a more generalized approach for the evaluation of pavement conditions to enable efficient management of large transportation networks. The development of a universal measure capable of formally assessing the condition of a pavement section within the universe of pavement conditions is described. This is accomplished by the fusion of a set of fuzzy membership functions that describe different parameters in the database with the perception of each parameter’s significance. The model output is the fuzzy distress index (FDI), which combines the extent of structural distress with traditional performance parameters such as roughness to describe the overall status of the pavement section. The behavior of FDI over time is examined for a random sample of pavement sections and is compared with trends in the corresponding PSI values (PSI was used only because it was readily available in the database). The results indicate that the flexible, universal FDI is a consistent and accurate measure of the overall pavement condition. The set of generated membership functions describing the different extents of every distress type can be easily standardized over the 50 states, allowing the model to be implemented on any pavement at any location. Also, the parameter weights used in the assessment may be easily adjusted (increased or decreased) to reflect changes in maintenance policies or budget availability at the local, state, or national decision-making level. Moreover, the concept allows for the omission of any number of parameters that might not be available in a particular pavement management database.
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Shrestha, Satkar, and Rajesh Khadka. "Assessment of Relationship between Road Roughness and Pavement Surface Condition." Journal of Advanced College of Engineering and Management 6 (July 10, 2021): 177–85. http://dx.doi.org/10.3126/jacem.v6i0.38357.
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Pavement evaluation is the most significant procedure to minimize the degradation of the pavement both functionally and structurally. Proper evaluation of pavement is hence required to prolong the life year of the pavement, which thus needs to be addressed in the policy level. By this, the development of genuine indices are to be formulated and used for the evaluation. In context of evaluating the pavement indices for measuring the pavement roughness, International Roughness Index (IRI) is used, whereas for calculating the surface distress, indices as such Surface Distress Index (SDI) and Pavement Condition Index (PCI) are used. Past evaluating schemes used by Department of Roads (DOR) were limited to IRI for evaluating the pavement roughness and SDI for measuring the surface distress, which has least variability in categorizing the pavement according to the deformation. Apart from these, PCI which has wide range of categories for evaluating pavement, is not seen in practice in Nepal due to its cumbersome field work and calculations. In this paper the relationship is developed relating PCI with IRI and SDI using regression analysis by using Microsoft excel. In the other words, the pavement roughness index is compared with the surface distress indices. In 2017, 23.6Km of feeder roads in various locations of Kathmandu and Lalitpur districts were taken for this study which comprised of 236 sample data, each segmented to 100m. For this, IRI was sourced as secondary data, obtained from Highway Maintenance and Information System (HMIS) unit, Kathmandu, whereas, PCI and SDI were calculated from the field data obtained from the survey carried out in those sections manually. Then after, among 236 samples, 189 samples were taken for the relationship development which was then validated using 47 remaining samples. Furthermore, in the year, 2019 additional 3 Km of data was taken for validating the obtained relationships. It was done to improve the numerical predictions of data with such variation and thus satisfactory relationships were developed among the indices discussed in this study. The regression relationships between the two indices, IRI-PCI and IRI-SDI were thus significantly obtained. It has been found that the R² value for these relationships developed were statistically significant with 5% level of significance. The R² value for all the relationships showed that these relationships could be used for predicting the indices which would help in evaluating the pavement.
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Karballaeezadeh, Nader, Danial Mohammadzadeh S., Dariush Moazemi, Shahab S. Band, Amir Mosavi, and Uwe Reuter. "Smart Structural Health Monitoring of Flexible Pavements Using Machine Learning Methods." Coatings 10, no. 11 (November 17, 2020): 1100. http://dx.doi.org/10.3390/coatings10111100.
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The pavement is a complex structure that is influenced by various environmental and loading conditions. The regular assessment of pavement performance is essential for road network maintenance. International roughness index (IRI) and pavement condition index (PCI) are well-known indices used for smoothness and surface condition assessment, respectively. Machine learning techniques have recently made significant advancements in pavement engineering. This paper presents a novel roughness-distress study using random forest (RF). After determining the PCI and IRI values for the sample units, the PCI prediction process is advanced using RF and random forest trained with a genetic algorithm (RF-GA). The models are validated using correlation coefficient (CC), scatter index (SI), and Willmott’s index of agreement (WI) criteria. For the RF method, the values of the three parameters mentioned were −0.177, 0.296, and 0.281, respectively, whereas in the RF-GA method, −0.031, 0.238, and 0.297 values were obtained for these parameters. This paper aims to fulfill the literature’s identified gaps and help pavement engineers overcome the challenges with the conventional pavement maintenance systems.
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Nielsen, Christoffer P. "Deriving Pavement Deflection Indices from Layered Elastic Theory." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 12 (October 5, 2020): 278–90. http://dx.doi.org/10.1177/0361198120953433.
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Pavement deflection indices such as the surface curvature index or base damage index are widely used to characterize the condition of pavements. Often, the indices are constructed to provide an estimate of a particular strain component somewhere in the pavement structure. Since the pavement damage is a function of the strain, structural indices provide a simple way of estimating the damage rate in a pavement. Despite their widespread use, it has so far proven difficult to derive deflection indices from first principles; instead, new indices are found by evaluating a range of candidates using a trial-and-error approach. In this paper, a systematic method of deriving deflection indices is presented. The method is based on applying the convolution theorem for Hankel transforms to the solution of a layered elastic problem. Besides allowing for easy derivation of new deflection indices, the method can be used to account for the impact of varying layer thicknesses in the pavement.
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Peng, Jr Hung, Po Hsun Sung, Jyh Dong Lin, and Kuang Yi Wei. "Practice Analysis of Urban Road Pavement Roughness and Detect of Destruction." Advanced Materials Research 250-253 (May 2011): 3688–91. http://dx.doi.org/10.4028/www.scientific.net/amr.250-253.3688.
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The urban road becoming more perfect, pavement engineering is from new construction to maintenance management. The authorities, from acceptance the new construction turn into survey of the road‘s situation and control of various types of damage and road conditions on time, to maintain a good condition of the road. In this study we use the CCD with the general Global Positioning System to provide GPS coordinates and have a street shooting for each 20m of road, record of the CCD road imaging system, and with GPS coordinates, the street pavement shooting can identify the highest frequency distress type within 100m of the road, and compare with the value of IRI for statistics, considering different distress conditions associated with the International Roughness Index, and to explore the causes. This study has an Urban Road Management System, it divided into road flat index query and pavement condition index query, and user can use this system know the pavement condition every section. The road maintenance unit can be judged by this indicator status of pavement roughness to develop a conservation strategy of each section, reflecting the degree of conservation of each section, making the pavement to maintain a good quality. Urban road maintenance management system is for the each authorities built the road pavement maintenance management system for pavement managers with different levels of management authority, and to assist in the system can provide information for urban roads to do planning, query and management, it is beneficial to the authorities to implementation of urban roads and other road maintenance operations, they can immediately understand the pavement condition.
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Yamali, Fakhrul Rozi, Elvira Handayani, and Eben Ezer Sirait. "Penilaian Kondisi Jalan dengan Metode Pci (Pavement Condition Index)." Jurnal Talenta Sipil 3, no. 1 (March 6, 2020): 47. http://dx.doi.org/10.33087/talentasipil.v3i1.27.
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Perkerasan jalan merupakan komponen pokok di bidang transportasi, Kondisi perkerasan mempengaruhi kenyamanan, keamanan dan keselamatan pengguna jalan. Dalam metode PCI, tingkat keparahan kerusakan perkerasan merupakan fungsi dari 3 faktor utama, yaitu: tipe kerusakan, tingkat keparahan kerusakan, jumlah atau kerapatan kerusakan. PCI ini merupakan indeks numerik yang nilainya berkisar diantara 0 sampai 100. Berdasarkan hasil penelitian didapatkan Jenis dan nilai rata-rata kerusakan pada ruas Jl.Jambi-lintas Muara Bulian Kelurahan Muara Pijoan sampai Jl.Jambi-lintas Muara Bulian KM 27 desa Lopak Aur dengan panjang 4 KM dan lebar 6 M antara lain : Retak Buaya (1.473%), Retak Kotak-Kotak (0.078%), Retak Pinggir Jalan (0.083%), Pinggir Jalan Turun Vertiakal (0.038%), Retak Memanjang/Melintang (0.065%), Tambalan (3.018%), Lubang (0.200%), Alur (0.049%), Sungkur (0.076%), Pelepasan Butir (2.878%), Amblas (0.037%) dengan nilai PCI rata-rata yaitu 48.90%.
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Qiu, Shi, Wenjuan Wang, and Kelvin C. P. Wang. "A comprehensive system for AASHTO PP67-10 based asphalt surfaced pavement cracking evaluation." Canadian Journal of Civil Engineering 43, no. 3 (March 2016): 260–69. http://dx.doi.org/10.1139/cjce-2014-0519.
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In light of the newly released AASHTO cracking protocol PP67-10 and high quality cracking data produced from a novel 3D 1 mm pavement data collection and automated analysis system, this paper develops an index system for overall cracking evaluation. The Analytical Hierarchy Process (AHP) is employed to establish a general framework and fuzzy set theory is adopted to convert actual severity and intensity measures into normalized scores. Multiple data combination techniques are applied for data aggregation. The ultimate product of this system, a single number cracking index representing the overall cracking condition, can be used to rank pavements and prioritize crack-oriented maintenance and rehabilitation projects. Furthermore, cracking indices for different pavement zones can also be derived from the system, which would be significant to examine the pavement failure mechanism. A case study containing 10 pavement sections is performed to demonstrate the applicability of this proposed evaluation system.
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Sahagun, Lauren K., Moses Karakouzian, Alexander Paz, and Hanns de la Fuente-Mella. "An Investigation of Geography and Climate Induced Distresses Patterns on Airfield Pavements at US Air Force Installations." Mathematical Problems in Engineering 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/8721940.
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This study investigated climate induced distresses patterns on airfield pavements at US Air Force installations. A literature review and surveys of Pavement Condition Index indicated that the predominant factor contributing to the development of pavement distress was climate. Results suggested that, within each type of pavement distress, a geographic pattern exists which is strongly correlated to conventional US climate zones. The US Air Force Roll-Up Database, housing over 50,000 records of pavement distress data, was distilled using a process designed to combine similar distresses while accounting for age and size of samples. The process reduced the data to a format that could be used to perform krig analysis and to develop pavement behavior models for runways built with asphalt cement (AC) and Portland cement concrete (PCC). Regression and krig analyses were conducted for each distress type to understand distress behavior among climate zones. Combined regression and krig analyses provided insight into the overall pavement behavior for AC and PCC runways and illustrated which climate zone was more susceptible to specific pavement distresses. Distress behavior tends to be more severe in the eastern US for AC and in the western US for PCC runway pavements, respectively.
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Rachman, Meilinda Atika, Harmein Rahman, Bambang Sugeng Subagio, and Sri Hendarto. "Study of Flexible Pavement Structure Maintenance in Runways with Pavement Condition Index (PCI) Method." Jurnal Teknik Sipil 27, no. 1 (April 14, 2020): 25. http://dx.doi.org/10.5614/jts.2020.27.1.4.
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Lee, Kang-Jin, Young-Chan Seo, Nam-Hyun Cho, and Dae-Wook Park. "Development of Deduct Value Curves for the Pavement Condition Index of Asphalt Airfield Pavement." Journal of the Korean Society of Road Engineers 15, no. 3 (June 17, 2013): 37–44. http://dx.doi.org/10.7855/ijhe.2013.15.3.037.
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Zakaria, Mohamed Hamed, Amal H. Al-Ayaat, and Sayed A. Shwaly. "Impact of Road Humps on the Pavement Surface Condition." Civil Engineering Journal 5, no. 6 (June 23, 2019): 1314–26. http://dx.doi.org/10.28991/cej-2019-03091334.
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In order to fight against over-speeding, the government and people in Egypt resorted to the installation of speed humps without adequate studies. On this basis, speed humps became widespread in most of the Egyptian roads in a semi-random way. It has been observed that the pavement condition of the roads has deteriorated in the vicinity of these humps. For impact assessment of speed humps on the pavement condition index (PCI), three roads link Kafr El-Sheikh city with three major towns in Kafr El-Sheikh governorate were selected to conduct PCI survey. The results indicated that the presence of speed humps contributes greatly to reduce the pavement condition index (PCI) values. It should be mentioned that the average reduction in PCI values ranged between 15% and 22% due to the presence of speed humps. Also, the most frequently observed distress on the pavement sections including humps considered for the selected roads was Raveling and Rutting. Accordingly, to avoid the pavement defects at the locations where the speed humps are installed, it is proposed to study the structural section of the road in the vicinity of the speed hump to resist the braking force and speed reduction effect.
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Llopis-Castelló, David, Tatiana García-Segura, Laura Montalbán-Domingo, Amalia Sanz-Benlloch, and Eugenio Pellicer. "Influence of Pavement Structure, Traffic, and Weather on Urban Flexible Pavement Deterioration." Sustainability 12, no. 22 (November 21, 2020): 9717. http://dx.doi.org/10.3390/su12229717.
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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.
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Wesołowski, Mariusz, Piotr Barszcz, and Krzysztof Blacha. "Impact of Airfield Concrete Pavements Deterioration Level on the Safety of Air Operations." Journal of KONBiN 47, no. 1 (October 1, 2018): 123–42. http://dx.doi.org/10.2478/jok-2018-0042.
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Abstract The essential factor, which affects the safety of air operations, is the proper airport management based on systemically acquired information regarding the condition of the pavement surfaces of their functional elements. One of the elements in evaluating an airfield pavement technical condition is the assessment of their deterioration degree. This paper contains an extract from a broad study aimed at developing an index characterizing the deterioration degree of cement concrete airfield pavements, based on the results of visual inspections of damage and repairs, and their stock-taking based on a catalogue of common damage and the defined damage and repair quantity surveying principles.
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Abedal, Abdulhaq Hadi, and Tuqa Khalid. "Assessment of the Functional Performance of Mohammed Al-Qasim Expressway Pavement Surface." Journal of University of Babylon for Engineering Sciences 26, no. 6 (April 10, 2018): 60–75. http://dx.doi.org/10.29196/jubes.v26i6.1059.
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To achieve these requirements need to assess the pavement surface condition (Functional Performance). The pavement surface damage that frequently happens has an effect on the safety and comfort of road users. Pavement condition assessment is the basic step to select a suitable type of maintenance and rehabilitation program. This study aims to estimate the functional condition of the Mohammed Al-Qasim Expressway pavement surface by the Pavement Condition Index (PCI) assessment with data collected throughout 2017. The result showed that the AC pavement surface condition assessment is equal to 70 based on PCI value, and rated as fair, and the transverse tining PCC pavement surface condition is rated as satisfactory and PCI value equals 77.
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McNerney, Michael T., and B. Frank McCullough. "Fatigue Cracking in Rigid Airfield Pavements at Large Commercial-Service Airports." Transportation Research Record: Journal of the Transportation Research Board 1703, no. 1 (January 2000): 65–71. http://dx.doi.org/10.3141/1703-09.
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Fatigue of airport pavements is an important consideration in the analysis of high-traffic pavements. The current pavement condition index (PCI) method of pavement evaluation does not adequately evaluate fatigue cracking of airport pavements and should be considered for modification. Recent field inspections by the authors of Atlanta Hartsfield International Airport, Dallas–Fort Worth International Airport, and Albuquerque International Sunport have shown the fatigue cracking in thick concrete pavements to be prevalent. However, it is not normally recorded in a normal PCI inspection because the crack widths are less than 3 mm (1/8 in.). A properly designed, constructed, and maintained pavement should theoretically fail only in fatigue because all other distresses caused by construction deficiencies, material deficiencies, environmental distresses, and maintenance deficiencies would be avoided. Therefore, it is important for the management of airport pavements that receive high levels of traffic to consider fatiguecracking distress. In practice, it is not possible to sample 100 percent of pavements to fully evaluate all hairline cracking. However, a geographical distribution of pavement control sections can be established and monitored for changes over time. The PCI should be revised or a new distress identification method should be developed to account for fatigue cracking.
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Belete Werkineh, Ashebir, and Bekele Arega Demissie. "Evaluation of Pavement Distress for Asphalt Pavement Using Pavement Condition Index: Case Study from Adama to Awash Arba." American Journal of Science, Engineering and Technology 4, no. 4 (2019): 73. http://dx.doi.org/10.11648/j.ajset.20190404.13.
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