Next Article in Journal
Tax Rate of Management Control: The Mexican Income Tax Rates System for Resident and Non-Residents
Next Article in Special Issue
Surrogate Safety Measures Prediction at Multiple Timescales in V2P Conflicts Based on Gated Recurrent Unit
Previous Article in Journal
National and International Policies and Policy Instruments in the Development of Agroforestry in Chad
Previous Article in Special Issue
A Machine Learning Approach to Determine Airport Asphalt Concrete Layer Moduli Using Heavy Weight Deflectometer Data
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

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

1
Department of Civil, Constructional and Environmental Engineering, Sapienza University of Rome, Via Eudossiana 18, 00184 Rome, Italy
2
Leonardo, Department of Vergiate Fal-Aeroporto Vergiate-Plant Maintenance, Via Roma 51, 21029 Vergiate, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(16), 9201; https://doi.org/10.3390/su13169201
Submission received: 11 July 2021 / Revised: 6 August 2021 / Accepted: 12 August 2021 / Published: 17 August 2021
(This article belongs to the Special Issue Transportation Safety and Pavement Management)

Abstract

:
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.

1. Introduction

Since the 1970s, pavement management systems (PMS) have been applied to roads and airports, and currently, they are considered a good and useful aid for the infrastructure manager [1,2,3,4]. A PMS provides a systematic and consistent method for assessing the current state of a pavement, predicting its future condition, determining priorities and the optimal time for repair, and selecting maintenance or repair and rehabilitation (M or R&R, respectively) needs [5]. This process has overturned how to approach the maintenance of transport infrastructure pavements. Indeed, in the past, the pavement maintenance was performed only when needed, without a work plan over time, and carrying out the repeated application of some alternatives of M&R based on past experience, without considering better alternatives. With the introduction of the PMS, the importance of monitoring the pavement conditions and planning the M&R has been understood and implemented, and the adoption of the best alternative among the available ones is a consequence of these actions [6]. In addition, a proper definition of PMS allows the reduction of overall pavement costs (both construction and maintenance) as well as traffic disruptions and their related risks. Moreover, the methodology of system dynamics could support PMS in order to identify the interrelationship between the elements of the systems, to distinguish causes and effects, and to investigate which parameters are pivotal to improve the system’s behavior [7].
A PMS includes several steps: pavement distress survey [8,9], pavement evaluation [1], life-cycle cost analysis (LCCA) [10], and finally, definition of the maintenance strategies [11,12,13]. M&R planning for airport pavements complies with the airport pavement management system (APMS) method [6]. Starting from data collection and storage of data about pavement smoothness, adherence, and distresses, APMS permits:
  • To assess current conditions of the pavement,
  • To predict the future condition of the pavement using performance prediction models,
  • To identify the optimum when implementing the best M&R option, optimizing currently available resources and avoiding greater future costs,
  • To define a priority list of interventions,
  • To assess the economic resources needed for M&R.
The International Civil Aviation Organization (ICAO) prescribes that airports adopt APMS in order to maintain the optimal conditions of their pavements to the required operating conditions (e.g., safety, regularity, and efficiency) without compromising air navigation for a defined period [14] in ordinary and emergency exercise [15].
In the past, most of the PMS were created to manage large networks, and therefore they refer to major road and airport infrastructures [16,17]; in recent years, PMS has been implemented to sidewalks and urban shared areas in order to assess pavements’ quality conditions for pedestrians and to improve walking comfort for vulnerable users [18,19,20]. This paper adapts conventional PMS methodologies to a heliport (i.e., an aerodrome for use by helicopters only according to [21]). Indeed, it deals with the implementation of a PMS to develop strategies to maintain, preserve, and rehabilitate heliport infrastructures (HPMS). In order to extend the implementation of PMS to heliport pavements, the structure and management of APMS should be modified considering the different traffic (both dynamics and weight). Indeed, rotary-wing vehicles have low effects on pavements compared to fixed-wing aircrafts; in some cases, helicopters move without touching the pavement, and in any case, the weight of helicopters is generally much lower than that of aircrafts. Nevertheless, the pavement condition should be monitored to avoid potential foreign object debris (FOD) and the consequent damage, although this problem differs from that observed at airports. While in the latter FOD represents a real danger for the integrity of the aircraft engines, in heliports, it generates damage to the helicopter bodywork, which in any case involves a considerable economic commitment. For these reasons, unlike APMS, HPMS of pavements designed for rotary-wing vehicles does not consider smoothness and adherence, it only considers the pavement condition index (PCI), a common distress survey method that rates the general condition of a pavement considering the extent and severity of the surface defects. The proposed method includes the creation of the heliport network inventory, the visual surveys of the pavement, and the evaluation of its condition by PCI [5], and it allows analysis and modeling for heliport managers to compare alternative maintenance strategies and define the priority needs on their managed network. Moreover, the proposed method can be easily adapted to all the infrastructures in the heliport and it does not require a large amount of time and money for its implementation.

2. Methods

The main objective of this study is the implementation of a HPMS to assess the pavement condition through visual surveys according to the American Society for Testing and Materials for roads [22] and airports [23]. In this context, three hierarchical management levels are usually identified:
  • Network level: The highest level of the hierarchy. It considers the overall network of pavements (e.g., all the pavements of the heliport).
  • Branch level: The middle level of the hierarchy. It includes a specific portion of the network identified for its specific functions. Each branch is composed of at least one section.
  • Homogeneous section: The lowest level of the hierarchy. It is a part of a branch with uniform construction, maintenance, service life, superficial condition, traffic mix, and traffic volume.
In order to develop an efficient HPMS, a database with a pavement inventory, history of M&R, superficial condition, and traffic data should be structured and updated. This information allows the prediction of future pavement conditions and identification of the best M&R procedure. First, the inventory of pavements within the system [6] includes the following types of data: construction year, maintenance history, pavement type (e.g., rigid, flexile, semirigid, modular) and structure (e.g., thickness of layers, slab dimensions if rigid), traffic composition and repetitions, performed function (e.g., touchdown and lift-off area, taxiway, safety area, apron), and rank (i.e., primary, secondary, tertiary). The history of both preventive and reactive M&R strategies should contain information about repair history [6]: date, type, and cost of rehabilitation works, size of rehabilitated area, materials’ properties, and layers’ thickness. PCI calculation complies with the standards ASTM D 5340-20 [23] and ASTM D 6433-20 [22], where the former is specific to the airport, where rotary-wing vehicles autonomously move on the pavements, and the latter is specific to roads or where rotary-wing vehicles are pulled. Both methods prescribe that the pavement should be divided into homogeneous sections and the sections into sample units to be surveyed [22,23]. With regard to traffic data, the number of yearly movements and the rotary-wing vehicles found to be moving should be considered to distinguish homogeneous sections in branches.
Predictive models permit to adapt the deterioration curve to the decay evolution of a pavement or a series of pavements that have homogeneous sections with similar decay characteristics: function, rank, and type. Forecasting of the pavement condition derives from treatment of data collected during survey campaigns, using several regression curves, such as straight-line extrapolation, mechanistic empirical, polynomial constrained least square, S-shaped curve, probability distribution, and Markovian. The simplest regression model is based on a straight-line extrapolation of the last two condition points [5,24]. This method can be used when the monitoring of the pavement is in the starting phase and consolidated data are not available. However, at a minimum, availability of data required is: the year of the construction or reconstruction, when the PCI can be assumed equal to 100, and the PCI calculated on the last (probably the only one available) survey. The straight-line extrapolation is applicable only for single-section branches and it cannot be used with other pavement sections [5].
Four types of M&R could be implemented [11] depending on the PCI value with respect to the critical PCI (i.e., value at which PCI rapidly decreases with time or the time when the cost of localized preventive maintenance significantly increases) [11] and based on the performance or characteristics of the pavement to be improved [25,26,27]:
  • Localized preventive M&R: Consists of localized distress maintenance activities (e.g., cracking sealing or patching) to slow the rate of distress progression. Localized preventive M&R can be implemented when pavement PCI is above the critical value.
  • Global preventive M&R: Consists of maintenance activities applied to the whole section (e.g., rejuvenation, thin overlay or joint sealing for concrete pavements) to slow the rate of distress progression. Global preventive M&R is cost-effective if pavement PCI is above the critical value.
  • Major M&R: Consists of activities applied to the entire pavement section to correct or improve its structural or functional performance. Major M&R is applied to pavements both below and above the critical PCI.
  • Localized stopgap (safety) M&R: Localized activities to keep the pavement in safe and operational conditions when economic resources for higher M&R activities are not available. Localized stopgap (safety) M&R can be implemented when the PCI pavement is below the critical threshold.
Calculation of the discounted M&R cost in the specific year during the analyzed period complies with the economic model proposed in the Technical Manual No. 5-623 Pavement Maintenance Management [28].
The software PAVEair has been used [29]. It has been developed by the FAA to fulfil the requirements of an APMS according to [6] and it is designed to support infrastructure managers in evaluating, managing, and maintaining their pavement networks [29].
The proposed model has been adopted to implement a HPMS to the pavements of the airport in Vergiate (Varese province, Italy), owned by Leonardo. This proposal aims to have an effective 20-year-long plan to maintain safe and operational conditions of surfaces where rotary-wing vehicles move.

3. Results

Figure 1 shows the geometrical and functional layout of the Vergiate airport and its pavement types.
All the heliport pavement has been divided into branches, and each branch into homogeneous sections, as listed in Table 1. All section details have been implemented in the software PAVEAIR. There are three types of pavement surface: asphalt pavement (AC), concrete slab pavement (PCC), and semi-flexible. The latter is an open-grade asphalt concrete with the voids filled with a high-strength cement-based mortar. This material combines the flexible properties of asphalt concrete with the high bearing capacity and durability of concrete [30,31]. The load-bearing capacity of the subgrade is good: the California Bearing Ratiois more than 25% throughout the airport. All sections belong to primary and secondary rank.
Figure 2a–d represents the cross-section of runway sections A, B, C, Helipad H1, and Helideck, Runway section D, East Apron section A, and East Apron section B, respectively.
Table 2 lists the M&R activities applied to the identified sections. Work details have been added to the model in PAVEAIR to complete the pavements’ description.
High-definition georeferenced images from surveys carried out on 1 June 2019 allowed identification of distresses. Figure 3 represents the surveyed distresses of the semi-flexible pavement in the East Apron: blue lines represent damaged joints, pink lines represent sealed joints, green lines represent <0.5 cm wide cracks, yellow lines represent 0.5–1 cm wide cracks, red lines represent >1 cm wide lines, and green and black squares represent existing patches and all-depth M&R treatments, respectively.
Surveyed distresses were implemented in PAVEAIR to calculate the PCI value for each homogeneous section (Table 3): ASTM D 5340-20 [23] has been considered to assess PCI of surfaces where rotary-wing aircrafts move by themselves, while ASTM D 6433-20 [22] was considered for surfaces where rotary-wing aircrafts are pulled by a tractor.
Figure 4 shows a chromatic layout of the calculated PCI values, and the PCI rating scale complies with [5].
The prediction of the pavement condition has been performed by a straight-line extrapolation (PCI-time) because no data are available on past surveys, and in the literature, decay curves for heliport pavements are not available. In addition, the pavements cannot be considered as included in the same family because their characteristics in terms of traffic and structure are too different from each other. Table 4 lists the yearly PCI decay obtained for each section, which derives from Equation (1):
yearly   PCI   decay = 100   PCI 2019 2019   Y
where PCI2019 refers to the PCI values listed in Table 3 for each section and Y is the year of construction or the year of the last rehabilitation works.
For pavements whose PCI value was 100 on 1 June 2019, the yearly PCI decay has been assumed 1 for the ATO Apron, and 0.5 for the Painting Apron according to the yearly decay obtained for the same functional elements in the branch (e.g., the yearly decay of section B of the ATO Apron coincides with that of section A). For functional elements composed of only one section, the yearly decay has been obtained from that of a section in a different branch on the basis of the traffic type and volume (e.g., the yearly PCI decay of Helipad H1 is four times that of Helipad H2 because the traffic in the former is four times the traffic in the latter).
In August 2020, sections in Table 1 were surveyed to assess PCI2020 and monitor its trend. The obtained results confirmed more than 70% of the values of yearly PCI decay listed in Table 4. Due to the effects of COVID-19 on movements in the period from March to August 2020, the authors assumed the yearly PCI decay values in Table 4 to define the maintenance strategies. Particularly, two M&R strategies have been developed:
  • A proactive M&R plan which provides for local and global preventive M&R activities. The plans are not expensive but guarantee good conditions during the entire twenty-year analysis period and guarantee the absence of detached elements on the surface, avoiding additional costs for FOD. Table 5 shows the M&R plan for section A of the Tango taxiway and the before/after values of PCI, as an example.
  • A reactive M&R plan which provides for major M&R reconstruction interventions at the end of the pavement service life. Activities are expensive and do not guarantee the absence of FOD whose related costs should be added to the cost of the M&R plan. In the literature, there are not costs for FOD in the heliport, therefore, data from airports have been considered, however the reference is not disclosed herein due to privacy reasons. Table 6 shows the M&R plan with a reactive approach for section A of the Tango taxiway and the before/after values of PCI, as an example.
The proactive and reactive M&R plans are shown in Table 5 and Table 6, respectively. The discounted costs have been calculated according to [23].
Figure 5 compares the curves of the discounted costs obtained for the examined M&R solutions (Table 5 and Table 6) and their PCI values.
The benefit from the initial low maintenance costs of the reactive approach disappears after 15 years (i.e., in 2035), when the first reactive activity has higher costs than the cumulative one compared to the proactive approach. Over the 20-year service period, the proactive approach implies 40,114 EUR M&R activities, while the reactive one 965,983 EUR. Moreover, the curve of PCI highlights that the latter strategy implies an average PCI during the observed period equal to 60, which is lower than that ensured by the former one (i.e., 75). The lower PCI value obviously increases the danger of FOD, because the worst condition of the pavement leads to an evident danger of detachment of material from the pavement.
The same comparative approach has been implemented to the whole pavement network (Table 7).

4. Conclusions

A pavement management system helps transport infrastructure agencies in the decision-making process: it provides procedures to evaluate the distress pavement condition and to evaluate the best M&R strategies. Although evenness and skid resistance are not meaningful for heliport pavements and distress rates of pavements used by rotary-wing vehicles are less than those of pavements used by fixed-wing vehicles, PMS is necessary to manage heliport pavements, but in the scientific and technical literature, there are no tools available for these surfaces. Therefore, this study adapted the structure of an APMS to the Vergiate Heliport and tried to fill this gap in the sector. A conventional PMS includes technical and economic steps: pavement distress survey, pavement evaluation, life-cycle cost analysis (LCCA), and finally, definition of the maintenance strategies. HPMS is simpler than APMS because movements of rotary-wing vehicles are not affected by surface unevenness: HPMS depends on the current and predicted PCI values in order to identify the M&R option which balances safety, economic, and technical issues. Twenty-six homogeneous sections identified in the functional elements of the airport have been surveyed and their PCI has been calculated. For each section, the prediction of the pavement condition has been performed by a straight-line extrapolation in order to predict the future pavement condition and identify the time when maintenance or rehabilitation are needed. Two M&R options have been proposed to manage the surveyed surfaces: the former has a proactive approach, while the latter complies with a reactive approach. The comparison between them highlighted that the proactive option implies less costs than the reactive one, without FOD during the twenty-year analysis period.
The obtained results confirm that even in the heliport environment, despite the limited loads and traffic of rotary-wing vehicles, M&R programming through HPMS is necessary, and it should be developed according to a proactive approach. Particularly, the presented case study could be improved by carrying out regular surveys of the surface conditions in order to monitor their evolution. Ongoing technology development could support this process, and in recent years, remote sensing methodologies for pavement management and assessment have been under development. Indeed, nondestructive methods provide frequent, comprehensive, and quantitative surveys of surface infrastructures that are useful to collect data and identify critical conditions. Different heliport sites could apply the proposed process in order to implement network level maintenance strategies and to organize maintenance and rehabilitation works according to a so far not available methodological approach.

Author Contributions

Conceptualization, P.D.M., A.A., P.N. and A.G.; Data curation, A.A., P.N. and A.G.; Formal analysis, M.C.; Investigation, P.D.M. and L.M.; Methodology, P.D.M. and L.M.; Supervision, P.D.M.; Validation, P.D.M. and L.M.; Writing—original draft, P.D.M., M.C. and L.M.; Writing—review and editing, P.D.M. and L.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to privacy reasons.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Pérez-Acebo, H.; Linares-Unamunzaga, A.; Abejón, R.; Rojí, E. Research trends in pavement management during the first years of the 21st century: A bibliometric analysis during the 2000–2013 Period. Appl. Sci. 2018, 8, 1041. [Google Scholar] [CrossRef] [Green Version]
  2. Wesołowski, M.; Iwanowski, P. Evaluation of asphalt concrete airport pavement conditions based on the Airfield Pavement Condition Index (APCI) in scope of flight safety. Aerospace 2020, 7, 78. [Google Scholar] [CrossRef]
  3. Loprencipe, G.; Pantuso, A.; Di Mascio, P. Sustainable Pavement Management System in Urban Areas Considering the Vehicle Operating Costs. Sustainability 2017, 9, 453. [Google Scholar] [CrossRef] [Green Version]
  4. Di Mascio, P.; Moretti, L. Implementation of a pavement management system for maintenance and rehabilitation of airport surfaces. Case Stud. Constr. Mater. 2019, 11, e00251. [Google Scholar] [CrossRef]
  5. Shahin, M.Y. Pavement Management for Airports, Roads, and Parking Lots, 2nd ed.; Springer: New York, NY, USA, 2005; ISBN 0387234640. [Google Scholar]
  6. Federal Aviation Administration AC 150/5380-7B Airport Pavement Management Program; Federal Aviation Administration: Washington, DC, USA, 2014.
  7. Di Nardo, M.; Converso, G.; Castagna, F.; Murino, T. Development and implementation of an algorithm for preventive machine maintenance. Eng. Solid Mech. 2021, 9, 347–362. [Google Scholar] [CrossRef]
  8. Fan, Z.; Li, C.; Chen, Y.; Wei, J.; Loprencipe, G.; Chen, X.; Di Mascio, P. Automatic crack detection on road pavements using encoder-decoder architecture. Materials 2020, 13, 2960. [Google Scholar] [CrossRef] [PubMed]
  9. Fan, Z.; Li, C.; Chen, Y.; Di Mascio, P.; Chen, X.; Zhu, G.; Loprencipe, G. Ensemble of deep convolutional neural networks for automatic pavement crack detection and measurement. Coatings 2020, 10, 152. [Google Scholar] [CrossRef] [Green Version]
  10. Onyango, M.; Merabti, S.A.; Owino, J.; Fomunung, I.; Wu, W. Analysis of cost effective pavement treatment and budget optimization for arterial roads in the city of Chattanooga. Front. Struct. Civ. Eng. 2018, 12, 291–299. [Google Scholar] [CrossRef]
  11. Shahin, M.Y. Analyzing Consequences of Pavement Maintenance and Rehabilitation Budget Scenarios; PERFORM PCI SURVEY; Transportation Research Board: Washington, DC, USA, 1994. [Google Scholar]
  12. Miccoli, S.; Finucci, F.; Murro, R. The evaluation of architectural design quality. In Proceedings of the SGEM Conference on Arts, Performing Art, Architecture and Design, STEF92 Technology, Sofia, Bulgaria, 2–7 September 2014; pp. 1023–1029. [Google Scholar]
  13. Leonelli, F.; Di Mascio, P.; Germinario, A.; Picarella, F.; Moretti, L.; Cassata, M.; de Rubeis, A. Laboratory and on-site tests for rapid runway repair. Appl. Sci. 2017, 7, 1192. [Google Scholar] [CrossRef] [Green Version]
  14. ICAO. Annex 14, Aerodromes, Montréal, QC, Canada, 8th ed.; International Civil Aviation Organization: Montreal, QC, Canada, 2018; Volume I. [Google Scholar]
  15. De Rubeis, A.; Di Mascio, P.; Montanarelli, F.; Moretti, L. Design of a temporary surface-level helipad paved with aluminium mats. Eur. Transp. Trasp. Eur. 2019, 72, 5. [Google Scholar]
  16. Pantuso, A.; Loprencipe, G.; Bonin, G.; Teltayev, B.B. Analysis of pavement condition survey data for effective implementation of a network level pavement management program for Kazakhstan. Sustainability 2019, 11, 903. [Google Scholar] [CrossRef] [Green Version]
  17. Pantuso, A.; Flintsch, G.W.; Katicha, S.W.; Loprencipe, G. Development of network-level pavement deterioration curves using the linear empirical Bayes approach. Int. J. Pavement Eng. 2021, 22, 780–793. [Google Scholar] [CrossRef] [Green Version]
  18. Di Mascio, P.; D’Alessandro, D.; Moretti, L.; Corazza, M.V. Walking on the safe side: A methodology to assess pavements quality conditions for pedestrian. Transp. Res. Procedia 2020, 45, 360–367. [Google Scholar] [CrossRef]
  19. Corazza, M.V.; Di Mascio, P.; Moretti, L. Management of sidewalk maintenance to improve walking comfort for senior Citizens. WIT Trans. Built Environ. 2018, 176, 195–206. [Google Scholar]
  20. Corazza, M.V.; Di Mascio, P.; Moretti, L. Managing sidewalk pavement maintenance: A case study to increase pedestrian safety. J. Traffic Transp. Eng. 2016, 3, 203–214. [Google Scholar] [CrossRef] [Green Version]
  21. ICAO. Annex 14, Aerodromes, Montréal, QC, Canada, 5th ed.; International Civil Aviation Organization: Montreal, QC, Canada, 2020; Volume II. [Google Scholar]
  22. ASTM (American Society for Testing and Materials International). ASTM D6433. Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys; ASTM International: West Conshohocken, PA, USA, 2020. [Google Scholar]
  23. ASTM (American Society for Testing and Materials International). ASTM D5340. Standard Test Method for Airport Pavement Condition Index Surveys; ASTM International: West Conshohocken, PA, USA, 2020. [Google Scholar]
  24. Shahin, M.Y.; Walther, J.A. Pavement Maintenance Management for Roads and Streets Using the PAVER System No. CERL-TR-M-90/05; U.S. Army Construction Engineering Research Laboratory: Champaign, IL, USA, 1990. [Google Scholar]
  25. Loprencipe, G.; Cantisani, G. Evaluation methods for improving surface geometry of concrete floors: A case study. Case Stud. Struct. Eng. 2015, 4, 14–25. [Google Scholar] [CrossRef] [Green Version]
  26. Bonin, G.; Cantisani, G.; Loprencipe, G.; Ranzo, A. Effetti dinamici nei giunti delle pavimentazioni aeroportuali in calcestruzzo. Ind. Ital. Cem. 2007, 77, 590–607. [Google Scholar]
  27. Cantisani, G.; D’Andrea, A.; Di Mascio, P.; Loprencipe, G. Reliance of pavement texture characteristics on mix-design and compaction process. In 8th RILEM International Symposium on Testing and Characterization of Sustainable and Innovative Bituminous Materials; Canestrari, F., Partl, M., Eds.; Springer: Dordrecht, The Netherlands, 2016; pp. 271–281. [Google Scholar]
  28. United States Department of the Army. Pavement Maintenance Management, Technical Manual No. 5–623; United States Department of the Army: Washington, DC, USA, 1982. [Google Scholar]
  29. FAA PAVEAIR. Available online: https://faapaveair.faa.gov/ (accessed on 27 December 2020).
  30. Da Rios, G.; Agostinacchio, M.; Fiori, F. Performance and durability of grouted open grade asphalt concretes. In Proceedings of the Fifth International Conference on Maintenance and Rehabilitation of Pavements and Technological Control (MAIREPAV5), Park City, UT, USA, 8–10 August 2007; Politecnico di Torino (DIMEAS): Torino, Italy; pp. 505–510. [Google Scholar]
  31. Mukherjee, D.; Sahoo, U.C. Laboratory characterization of a cement grouted bituminous macadam made with Portland slag cement. Int. J. Pavement Res. Technol. 2019, 12, 574–580. [Google Scholar] [CrossRef]
Figure 1. Layout of the Vergiate airport.
Figure 1. Layout of the Vergiate airport.
Sustainability 13 09201 g001
Figure 2. Cross-section of (a) runway sections A, B, C, Helipad H1, and Helideck, (b) runway section D, (c) East Apron section A, and (d) East Apron section B.
Figure 2. Cross-section of (a) runway sections A, B, C, Helipad H1, and Helideck, (b) runway section D, (c) East Apron section A, and (d) East Apron section B.
Sustainability 13 09201 g002
Figure 3. Distresses on the East Apron.
Figure 3. Distresses on the East Apron.
Sustainability 13 09201 g003
Figure 4. PCI rating on 1 June 2019.
Figure 4. PCI rating on 1 June 2019.
Sustainability 13 09201 g004
Figure 5. M&R alternatives for the Tango taxiway.
Figure 5. M&R alternatives for the Tango taxiway.
Sustainability 13 09201 g005
Table 1. Pavement inventory.
Table 1. Pavement inventory.
Heliport Functional ElementSectionSurface (m2)Type of Pavement SurfaceRank
RunwayA9020.6ACP
B16,227.1ACP
C15,511.3ACP
D9018.0ACP
Helipad H1A1296.0ACP
HelideckA400.0ACP
Helipad H2A719.2semi-flexibleP
B573.0ACP
East ApronA21,948.6semi-flexibleP
B9894.1semi-flexibleP
West ApronA17,086.0PCCS
ATO ApronA1453.0PCCS
B1239.9ACS
Painting Apron A3169.4ACS
B1599.7ACS
Compass AreaA349.0PCCP
B177.4ACP
Alfa TaxiwayA1487.8PCCS
B230.8semi-flexibleS
Bravo TaxiwayA3539.7ACP
Charlie TaxiwayA3066.9ACP
Delta TaxiwayA1598.5ACP
Echo TaxiwayA708.7ACP
B914.5ACP
Sierra TaxiwayA1143.3ACS
Tango TaxiwayA2660.6ACP
Table 2. History of applied M&R activities.
Table 2. History of applied M&R activities.
Heliport Functional ElementSectionDateM&RM&R TypeQuantity (m2)
RunwayA25/11/2018Reconstruction—ACMajor516.7
25/11/2018Patching—ACLocalized preventive1327.4
B25/11/2018Reconstruction—ACMajor2109.2
25/11/2018Patching—ACLocalized preventive2623.0
C25/11/2018Patching—ACLocalized preventive1819.1
D25/11/2018Patching—ACLocalized preventive85.8
Helipad H1A25/11/2018Reconstruction—ACMajor1296.0
HelideckA25/11/2018Reconstruction—ACMajor400.0
West ApronA30/11/2009Reconstruction—PCCLocalized preventive22.1
30/11/2009Patching—PCCLocalized preventive60.7
30/11/2015Reconstruction—SemiflexibleMajor1136.3
ATO ApronA30/11/2018Patching—PCCLocalized preventive14.2
Alfa TaxiwayA30/11/2015Reconstruction—PCCMajor0.4
Bravo TaxiwayA30/11/2018Patching—ACLocalized preventive15.3
Charlie TaxiwayA30/11/2018Patching—ACLocalized preventive16.9
Delta TaxiwayA30/11/2017Patching—ACLocalized preventive14.3
Echo TaxiwayB30/11/2018Patching—ACLocalized preventive0.3
Table 3. PCI values.
Table 3. PCI values.
Heliport Functional ElementMoving/Towed Helicopters or VehiclesSectionSample Unit NumberPCIComment
RunwayMoving helicoptersA1510Failed
B2719Very poor
C257Failed
D1520Very poor
Helipad H1Moving helicoptersA3100Excellent
Helipad H2Moving helicoptersA295Excellent
B194Excellent
HelideckMoving helicoptersA1100Excellent
East ApronMoving helicoptersA4768Good
B1659Good
West ApronTowed helicoptersA4676Very good
ATO ApronVehiclesA443Fair
B4100Excellent
Painting ApronTowed helicoptersA698Excellent
B3100Excellent
Compass AreaMoving helicoptersA173Very good
B194Excellent
Alfa TaxiwayTowed helicoptersA537Poor
B169Good
Bravo TaxiwayMoving helicoptersA748Fair
Charlie TaxiwayMoving helicoptersA657Good
Delta TaxiwayMoving helicoptersA356Good
Echo TaxiwayMoving helicoptersA291Excellent
B291Excellent
Sierra TaxiwayMoving helicoptersA396Excellent
Tango TaxiwayMoving helicoptersA672Very good
Table 4. Yearly PCI decay.
Table 4. Yearly PCI decay.
Heliport Functional ElementSectionConstruction YearReconstruction YearPCI at 01/06/2019Yearly PCI Decay
RunwayA19371980102.3
B19371980192.1
C1937198072.4
D19601980202.1
Helipad H1A198020181002.0
Helipad H2A2008-950.5
B2008-940.5
HelideckA198020181002.0
East ApronA19802008682.9
B20082008593.7
West ApronA1937-760.3
ATO ApronA19371960431.0
B193720101001.0
Painting ApronA19702015980.5
B197020151000.5
Compass AreaA1980-730.7
B1980-940.2
Alfa TaxiwayA1937-370.8
B19372015690.8
Bravo TaxiwayA1980-481.3
Charlie TaxiwayA1980-571.1
Delta TaxiwayA1980-561.1
Echo TaxiwayA19802008910.8
B19802008910.8
Sierra TaxiwayA19802013960.7
Tango TaxiwayA19802010723.1
Table 5. Proactive M&R plan for section A of the Tango taxiway.
Table 5. Proactive M&R plan for section A of the Tango taxiway.
YearInterventionPresent Worth (EURO, €)PCIBEFOREPCIAFTER
2020--6969
2021Localized preventive M&R (crack sealing)286674
2026Localized preventive M&R11355867
2031Bituminous emulsion352351100
Global preventive M&R (overlay 5 cm)34,611
2036Localized preventive M&R8178493
2040--8080
Table 6. Reactive M&R plan for section A of the Tango taxiway.
Table 6. Reactive M&R plan for section A of the Tango taxiway.
YearInterventionPresent Worth (EURO, €)PCIBEFOREPCIAFTER
2020--6969
2025--5353
2030--3838
2035Milling 10 cm974322100
Major M&R (reconstruction 10 cm)86,240
2040--8484
Table 7. Network level M&R alternatives.
Table 7. Network level M&R alternatives.
Proactive M&R PlanReactive M&R Plan
YearM&R Present Worth (EURO, €)M&R Present Worth (EURO, €)
2020--
2021694,305470,468
202512,243-
202616,935-
202878,674-
203011,696564,537
203156,158-
2035438,6211,245,655
203615,237-
204014,044230,509
Proactive M&R plan total cost (€)Reactive M&R plan total cost (€)
1,337,9132,511,169
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Di Mascio, P.; Antonini, A.; Narciso, P.; Greto, A.; Cipriani, M.; Moretti, L. Proposal and Implementation of a Heliport Pavement Management System: Technical and Economic Comparison of Maintenance Strategies. Sustainability 2021, 13, 9201. https://doi.org/10.3390/su13169201

AMA Style

Di Mascio P, Antonini A, Narciso P, Greto A, Cipriani M, Moretti L. Proposal and Implementation of a Heliport Pavement Management System: Technical and Economic Comparison of Maintenance Strategies. Sustainability. 2021; 13(16):9201. https://doi.org/10.3390/su13169201

Chicago/Turabian Style

Di Mascio, Paola, Alessio Antonini, Piero Narciso, Antonio Greto, Marco Cipriani, and Laura Moretti. 2021. "Proposal and Implementation of a Heliport Pavement Management System: Technical and Economic Comparison of Maintenance Strategies" Sustainability 13, no. 16: 9201. https://doi.org/10.3390/su13169201

APA Style

Di Mascio, P., Antonini, A., Narciso, P., Greto, A., Cipriani, M., & Moretti, L. (2021). Proposal and Implementation of a Heliport Pavement Management System: Technical and Economic Comparison of Maintenance Strategies. Sustainability, 13(16), 9201. https://doi.org/10.3390/su13169201

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop