What Are The Effects On Airport Design And The Frequency Of Airport Pavement Replacement And Repairs
Based on the MEPDG method, the functioning process of MEPDG was analyzed and the MEPDG correction method practical to the remaining life prediction of airport pavement was obtained. Co-ordinate to the theory of structural reliability, the functioning role of aerodrome pavement was obtained based on the limit land equation represented by flexural stress. Considering the characteristics of airport cement physical pavement design, the calculation formula of the number of allowable load actions was obtained based on reliability past NCHRP126 fatigue equation without considering the temperature stress when the flexural fatigue forcefulness of pavement plate cement concrete was less than i.25 times of the design strength. Based on the actual situation of local ceremonious airport runways in Henan Province, the proposed MEPDG correction method was used to analyze the flexural stress of the actual operating airport runway pavement at 95% reliability level based on the mechanical numerical model of airport runway, and the number of allowable load actions of three aircraft models was obtained. Given the touch of pass-to-coverage ratio P/C, the cumulative damage factor CDF of the major aircraft models was calculated; the almanac average growth rate of unlike shipping models in the airport pavement evaluation stage was obtained based on the trend extension method. According to the predicted boilerplate almanac cumulative harm, the remaining life of pavement was predicted. Compared with the actual atmospheric condition of the airport, the remaining life predicted in this paper was consequent with the actual life, which verifies the effect of the prediction of the remaining life of airport runway considering the impact of reliability and damage accumulation.
ane. Introduction
In the mid-20th century, the aerodrome management department for the aerodrome runway only proposed "a palliative rather than a cure" for the operation and maintenance. In the early on ten years of the 21st century, the airdrome direction department cast away the passive postmaintenance and adopted the preventive maintenance, a more active maintenance, to reduce the frequency of damage. Preventive maintenance is a time-based maintenance, but it will cause runway maintenance in an uneven manner: the consequent maintenance cycle will lead to unnecessary maintenance in some pavements simply improper maintenance in other pavements. Likewise, the preventive maintenance is up to the expertise of technicians and is the lack of data support.
Currently, predictive maintenance (PdM), which emerges in many sectors, particularly industry, is a typical style of intelligent maintenance. Every bit a data-driven maintenance style, it is an integration of sensor technology, indicate processing technology, reliability analysis, statistics, machine learning, and other methods for determining potential diseases, which lays a foundation for a more reasonable and effective maintenance program [one] Remaining Service Life (RSL) tin be used by civil engineers to schedule maintenance times, optimize operational efficiency, and avert unplanned stops. Therefore, predicting RSL should be prioritized in the predictive maintenance.
Therefore, in this paper, the remaining life prediction method of the airport rail was analyzed. The functioning procedure of MEPDG was analyzed and summarized, and the MEPDG correction method was applied to the remaining life prediction of the drome runway. MEPDG provides technical support for the maintenance decision of airdrome runway and also provides reference for reasonable resource allotment of limited operation and maintenance funds in the airport management section [2].
2. Current Research Studies on the Remaining Life Prediction of Aerodrome Pavement
The input in the RSL prediction model is the state indicator of airport rails. The features are taken from the monitoring sensor information or daily maintenance information, and behavior changes with rails performance deposition or usage land changes, simply the changes tin can be predicted based on the model. RSL prediction methods applied to predictive maintenance can be divided into three categories: similarity prediction, functioning deposition model prediction, and survival bend prediction methods.
At present, as a representative method, the similarity prediction method is the constrained polynomial regression model proposed by American scholar Shahin [3]. This model is very applied. Information technology has been incorporated into the MicroPaver organization [4] and has been widely used in countries around the world. In addition, the 2-parameter nonlinear model created by Chinese scholar Sunday Lijun is widely used in People's republic of china [five]. At the same fourth dimension, many researchers accept studied the similarity prediction methods [six–9].
To study the performance degradation model based on the prediction method for the remaining life prediction of airport track, most scholars at home and abroad fit a general fatigue equation using the site or laboratory data from operation degradation equation of a linear or exponential function. So, they utilise the fatigue equation every bit the performance degradation model for predicting the future performance deposition process of airport runway, to farther predict the remaining life of drome runway. For example, Ji and Sheng [10] took the design program FAARFIELD [eleven] every bit the assay tool and predicted the remaining life of pavement using information by FAARFIELD with the back-calculated airport concrete pavement modulus as the prediction index. Taking the cumulative impairment as the status indicator, Zhao et al. proposed the estimation method for the remaining life of flexible airport pavement and carried out example assay [12].
Lytton applied the survival curve in highway engineering [xiii]. According to Lytton, the survival curve is more often than not used for design of pavement maintenance and reconstruction scheme in the road network. In the performance prediction for a single section, the distribution function (i.east., survival part) is used to conduct life analysis and prediction based on preset pavement performance. Mishalani and Madanat [14]; Yang et al. [15]; and Kobayashi et al. [16] conducted a survival curve analysis co-ordinate to the data of pavement performance failure, cracks in reinforced physical span deck, and full wheel life price of pavement and pointed out that the survival curve prediction assay may exist feasible for pavement engineering science.
Based on the above analysis, equally the remaining life prediction of airport pavement is quite complicated, scholars at home and abroad used unlike methods to predict the changes of pavement functioning, or established suitable statistical prediction models based on the survey results of pavement performance. Withal, most of the methods failed to take the bodily maintenance of pavement into consideration and the model only had the theoretical significance rather than could be applicable to the actual service pavement. Also, they failed to consider the reliability of service pavement and the impact of damage accumulation. In fact, there are many factors that touch on the service life of airport runways, such every bit airport flight traffic loading, runway structural characteristics, and the level of field maintenance technology, all of which bear upon the remaining service life of runways. Therefore, this paper proposes a prediction method that tin be used in applied applied science projects to accost the effects of airport flight traffic load, runway structural characteristics, and maintenance technology level on the remaining service life.
three. MEPDG Correction for the Remaining Life Prediction of Airdrome Rails
three.1. Functioning Process of MEPDG
Mechanistic-Empirical Pavement Blueprint Guide (MEPDG) aims to provide a design and assay method for newly congenital and repaired pavements based on the mechanistic-empirical principle [17].
The blueprint method in MEPDG includes three phases. The first phase is to develop input values. The design requirements objectives are identified, basic analysis is conducted, and the characteristics data are taken as input, including the data for pavement material, the characteristics data of traffic, and the hourly climate data of weather condition station (temperature, precipitation, solar radiation, deject cover, and air current speed). In the 2d stage, structural and functioning analysis is conducted. An initial examination design value is chosen and analyzed based on the human relationship model between pavement response and damage (mostly an expression over time). The output of the assay is the cumulative impairment and flatness over time. Based on the iteration, the predicted performance with the design indicators of multiple predicted amercement has been compared until all the design indicators meet the specified reliability requirements, and the required pavement can exist obtained. The third phase is to evaluate the structurally feasible alternatives, such every bit engineering science analysis and life cycle cost assay.
3.2. Flowchart of MEPDG Correction
Given the reliability of track, the pass-to-coverage ratio (P/C) of shipping model, and the cumulative harm of airport runway, MEPDG correction was needed for predicting the remaining life of aerodrome track. The flowchart of MEPDG correction is shown in Figure 1.
3.3. Assay of the Force Reliability of the Cement Concrete of Aerodrome Rails Pavement
According to the Specification for Design of Highway Cement Concrete Pavement, and based on the structural characteristics of drome runway pavement, its force reliability was explained as follows: based on the specified time and weather, the actual probability that pavement played a specific function was obtained, every bit shown in the following formula [eighteen]: where P r was the reliability achieved by the pavement; meant the fatigue stress of the pavement plate under the action of aircraft load (unit: MPa); meant the flexural stress of pavement plate caused by temperature; and referred to the standard value of flexural-tensile strength of cement physical (unit: MPa).
The corresponding function was obtained based on the limit state equation corresponding to the flexural-tensile stress, which was shown in the post-obit formula:
In this paper, the strength reliability of cement concrete of airport runway pavement needed to follow Formula (2). As the temperature and fatigue stress of cement concrete were closely related to the fatigue stress of shipping load, the interference theory had zippo to practice with and cannot aid solve the force reliability. In this paper, the control failure mode was causeless to remain abiding and then a reliability analysis was conducted. According to the Specification for Design of Highway Cement Concrete Pavement and based on the different airport cement concrete pavement design and the literature proposed by Cai [19], lg (Northward) was obtained, as shown in the following formula past NCHRP126 fatigue equation: where N was the number of coverages at 50% pavement plate not bad, namely, the fatigue life of pavement plate; east referred to the stress ratio; was the flexural-tensile fatigue strength of concrete; and meant the concrete design strength of pavement.
To brand the calculation process simple and piece of cake to employ, the fatigue equation for temperature stress was not considered in the analysis of fatigue life.
According to the blueprint documents and the design specifications, the flexural-tensile fatigue strength of the concrete of pavement plate ordinarily shall be less than 1.25 under aircraft load and temperature. The formula of was obtained past Formula (4), shown as follows:
Past substituting Formula (5) into Formula (2), the performance function Z was transformed into the following formula:
3.4. Calculation Principle behind the Cumulative Impairment of Airport Runway
According to studies, aircraft wheel track is most distributed in a normal manner when the aircraft takes off and lands. A pass of the aircraft bike through the maximum stress point on the pavement was chosen a coverage. The ratio of the number of passes required to use a total load on the pavement of unit surface area was expressed equally the P/C.
The statistical analysis was conducted on the distribution data of measured aircraft runway, and the number of coverages was calculated based on the P/C of aircraft on the pavement. Figure two (schematic diagram of the adding of P/C) shows the expanse between f (ten) and x axis; that is, the number of coverages during the actual operating of aircraft was equal to fifty, and the area of W t was . Thus, the calculation formula of the P/C of unmarried-wheel aircraft was equally follows [20]:where P/C was the pass-to-coverage ratio; referred to the track probability density of operating aircraft at x coordinate; and meant the effective tire contact width of aircraft, which was selected based on the design parameters of aircraft.
In the airdrome pavement pattern, Miners police force is widely used to testify the linear cumulative fatigue damage, which can be expressed past the cumulative damage factor (CDF). As the fatigue life of pavement was expressed equally the number of allowable load action repetitions, the CDF stood for the fatigue life for pavement that has been used [21]. It was equal to the ratio of the current number of actual cumulative actions on the pavement plate and the number of commanded load action repetitions of the ith aircraft (the number of load action repetitions till pavement damage).
4. Assay on Engineering Application Case
This paper selected the ceremonious Airport A's runway in Henan for the case report. This airport was the Chinese trunk send airdrome and a national outset-grade aviation port. In 2022, the rider throughput of the airdrome ranked the 15th amidst civil airports in People's republic of china. The drome was opened to traffic in 1997, and its due south flight area has been used for 22 years in 2022. The south track of the drome was three,400 k long and 45 yard wide, to grasp the comprehensive situation of the pavement in the flight area and learn nearly the basic information near the contempo management and renovation program of the expanse; the drome management department conducted comprehensive testing on the pavement of rail, taxiway, and contact surfaces in the southward flight surface area of the airport in 2007, 2022, and 2022, respectively. The section conducted comprehensive analyses of the field examination data to form a high-value database. According to the remaining life prediction procedure of airport rail (shown in Figure one), the prediction for RSL of Airport A was established to verify the feasibility and implementation effect of MEPDG correction method.
four.i. Adding on the Number of Allowable Load Actions Based on the Strength Reliability of Airport Pavement Cement Concrete
Based on the actual demands and according to the statistics of Airport A in 2022, the statistical table of the annual takeoff and landing sorties of operating aircraft at Airdrome A is shown in Table 1. According to Tabular array 1, when information technology comes to the conclusion of aircraft load simulation, Boeing B737-800, Airbus A320, and Boeing B737-700 were taken into consideration in 2022.
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| Aircraft | Annual takeoff and landing sortie | Annual takeoff and landing ratio (%) | Notes |
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| B737-800 | 38121 | 51.40 | Main model |
| A320 | 17425 | 23.50 | Main model |
| B737-700 | 4223 | 5.70 | Primary model |
| A319 | 3493 | four.lxx | Secondary models, with ratio less than v% |
| B737-300 | 2135 | 2.90 | |
| A321 | 2004 | two.seventy | |
| ERJ-190 | 1679 | 2.30 | |
| B747-400 | 1211 | 1.60 | |
| MA60 | 870 | ane.20 | |
| Others | 3064 | iv.x | |
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According to the reliability calculation method under Section 3.3, the distribution type and distribution parameters of each input variable need to exist defined in the reliability assay model. Based on the literature proposed by Zhang [22] and Gao [23], and given the bodily conditions of airport rail, the actual thickness of pavement plate, the response modulus of base class, the flexural-tensile design strength, and flexural-tensile modulus of surface course concrete were determined as the random variables of airport rail in this newspaper. The following showed the determination of the statistical properties of the random variables.
4.ane.1. Determination on the Actual Thickness of Cement Physical Pavement Plate
The radar detection of pavement was adopted to measure out the thickness of surface layer of s runway pavement. The radar detection results of typical department are shown in Figure 3. The measured thickness of surface course of south runway pavement is shown in Tabular array ii.
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| Section | Position (m) | Number of sample (pcs) | Full-thickness mean (cm) | Standard deviation (cm) | Representative value (cm) | Design value (cm) |
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| Southward runway | 0–500 grand | 500 | 38.18 | ane.32 | 38.08 | 38 |
| 500–2900 m | 2400 | 34.01 | 1.79 | 33.95 | 34 | |
| 2900–3400 m | 500 | 38.06 | 1.seven | 37.93 | 38 | |
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Based on Table 2, the measured thickness of surface layer of both ends of southward rail pavement exceeded 37.five cm, fully meeting the requirement for design thickness. Based on this table, the mean thickness of surface layer of s track pavement was determined to exist 38 cm, and the coefficient of variation was 0.03 in this paper.
4.i.2. Determination on the Modulus of Base Reaction
This newspaper adopted an HWD for the detection around the heart of the plate. Based on the obtained HWD data and the actual pavement structure, the modulus of subgrade reaction was calculated. The back-calculated results are shown in Table 3.
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| Zone (m) | Modulus of subgrade reaction (MN/k3) | Equivalent thickness of base of operations course (cm) | Modulus of base reaction (MN/m3) | |
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| Runway | 0–500 | 58 | 48 | 104 |
| 500–2900 | 52 | 48 | 100 | |
| 2900–3400 | 47 | 48 | 95 | |
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The pavement foundation comes from the compacted pavement bed soil, and the pavement foundation modulus is often affected by the material properties. Information technology is worth noting that the ecology factors directly impact the functioning of the pavement foundation, and the significant differences in soil quality too directly bear on varied characteristics of pavement foundation. Considering the above factors and the variation coefficient in the literature proposed by Li [24], the variation coefficient of the modulus of base reaction was set as 0.3.
4.1.three. Determination on the Flexural Strength and the Elastic Modulus of Airport Runway Cement Physical
The sampling scheme of pavement core was as follows: in the south runway, a total of xviii core samples were drilled alternately every 180 k forth both sides of the centerline. The drilled cement concrete core samples shall be subject to the splitting tensile strength test co-ordinate to the Technical Specification for Construction of Cement Concrete Surface of Civil Airport. The test results of the drilled cement concrete cadre samples are shown in Table four. The section structures of typical cement concrete cadre samples after the test are shown in Effigy 4.
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| Annotation. The 8 #, thirteen #, and 17 # core samples were non completely split, then their data were discarded in this calculation. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(a)
(b)
According to Tabular array 4, the mean of the flexural strength of cement physical of runway pavement surface grade was 5.78 MPa, and the coefficient of variation was 0.15; the hateful of the flexural elastic modulus was 38,537.77 MPa, and the coefficient of variation was 0.09. Given the fact that the drome pavement cement physical has been used for most 20 years and for the sake of design safety, the mean of the flexural strength of cement concrete of track pavement surface grade was set every bit 4.50 MPa, and the coefficient of variation took 0.xv.
4.1.4. Number of Allowable Load Actions of the Cement Physical Runway of the Operating Airdrome
According to the adding method of reliability under Section 3.3 mentioned above, the distribution parameters of input variables were defined. The thickness of surface form, the strength and modulus of surface form, and the modulus of base reaction were regarded as random variables. Except for the distribution of the modulus of base reaction which was in logarithmic normal distribution, the other random variables tended to be in normal distribution.
The semirigid base of that drome runway pavement is likely to cleft and lead to the damage of the base. At the same fourth dimension, the coefficient of variation will increment. These issues by and large occur in the early phase of the track. Therefore, the random variables of runway were ready according to the bodily detection values described higher up. Based on the literature proposed by Guo [25] and Gao [26], the appropriate interval for coefficient of variation was prepare; the scientific and constructive quality control was by and large made on the surface course during construction; the base showed significant deformation. The hateful and coefficient of variation of the random variables are shown in Table v.
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| Random variable | Surface thickness | Flexural strength | Modulus of surface course | Modulus of base reaction |
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| Mean | 0.38 m | 4.five MPa | 38.54 GPa | 100 MPa |
| Coefficient of variation | 0.03 | 0.fifteen | 0.09 | 0.iii |
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Take the load of twin-wheel B737-800 as an case. The load was distributed in the middle of the cross-seam edge of pavement plate because of the spacing of wheels. Based on the target reliability of 2, 3, and IV airports in the literature proposed by Li [27], the target reliability was set to 95%. Past inputting the target reliability into the numerical analysis program, the allowable activeness times of B737-800 aircraft interim on the pavement were calculated. The specific results are as follows.
In full general, the response surface method for reliability analysis does not experience many cycles and can be analyzed in low probability. The fitting coefficient can correspond the approximation between the actual response values, and can inform the users to update the definition parameters with the poor effect of the fitting of approximate role, then it is ideal for parallel processing. Thus, when computing reliability, this newspaper used the Box–Behnken matrix sampling of response surface method for analyzing probability [28]. The precision exam of response surface followed the formula as [29] where was the adding value of response surface model; referred to the true value (calculation result of finite chemical element analysis); and was the average value respective to true value. R ii ranged from 0-ane. If R 2 was large, the regression model will be more fit with the actual example.
Based on the square response surface regression results, the comparison between the response surface estimation value and the finite element true value was made, as shown in Figure 5. As can be seen from Figure 5, except for the individual data points, the other data points were distributed near the 45° line, which indicated that in that location was adept fitting betwixt the response surface interpretation value and the finite element true value.
For the response surface functions that have been fitted, the Monte-Carlo method was used for 10,000 times of sampling and a series of performance role corresponding to the sampling value distribution diagram was obtained (see Figures 6 and 7 for details). Due to the limited space, the post-obit only listed the figure of performance functions during the B738 load activity.
As can be seen from Figures 6 and vii, sampling based on the response surface role volition achieve excellent convergence. Thus, the number of samples was set to 104 to meet the preproposed reliability standard. At this point, the failure probability reached , and z at 95% target reliability was 0.476 Mpa. By substituting it into Formula (5), the number (N) of allowable load deportment of B738 meeting 95% target reliability was 133,195. Similarly, iv,175,184 times of allowable load deportment of A320 and 477,806 times of commanded load actions of B737-700 met 95% target reliability, respectively.
4.2. Calculation of Drome Pavement CDF and the RSL Prediction Based on P/C
Every bit mentioned to a higher place, the B737-800, A320, and B737-700 were the major shipping of Airport A since the calculation of CDF needed the number of coverages of shipping loads, which must be converted through the takeoff and landing sorties of unlike shipping by ways of P/C. So, separate calculation was required for the major aircraft of Airdrome A. Considering the runway cumulative impairment factor CDF is calculated based on the number of aircraft load coverage, and the number of aircraft load coverage needs to be converted by the number of takeoff and landing sorties of different aircraft types through the P/C of traffic coverage, it needs to be calculated for the chief aircraft types of Aerodrome A, respectively.
Based on the theoretical analysis nether Section iii.4 aforementioned, given the B738 parameters, the main landing gear spacing of single-wheel B738 was set to T W , and then the cycle rails status of its left and right wheels was determined. If T W was less than or equal to the passage width of aircraft pavement, the tracks of the left and right wheels did not coincide. In this process, the chief landing gear spacing was v.72 m, the wheel spacing was ready to 0.86 m, and the standard difference in the x management took 0.775 g according to the information from Federal Aviation Administration (2012). The distribution function for the bicycle runway curve of the chief landing gear spacing of B738 was as follows:
Through calculation, when 10 = 2.86 m, the maximum function value was 0.8827, the wheelmark width reached 0.296 g, and the P/C was about 3.83 based on Formula (7).
According to the in a higher place methods, the P/C of A320 and B737-700 was calculated and the results are summarized in Tabular array 6. According to the number of commanded load actions for various aircraft calculated under Section four.one, the CDF of the major aircraft can exist calculated based on the bodily traffic book of Aerodrome A in 2022, as shown in Tabular array 6.
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| Airplane | B737-800 | A320 | B737-700 |
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| Tire contact width Due west t (one thousand) | 0.296 | 0.235 | 0.287 |
| Value of x | ii.86 | iii.eight | 2.86 |
| Maximum probability function value F (x) | 0.8827 | 0.9071 | 0.8827 |
| Pass-to-coverage ratio P/C | 3.83 | 4.69 | 3.95 |
| Number of commanded load actions | 133195 | 4175184 | 477806 |
| Number of actual cumulative coverages | 91584 | 34186 | 9837 |
| CDF | 0.6876 | 0.0082 | 0.0085 |
| Sum of cumulative fatigue consumption of each model | 0.7042 | ||
| Remaining fatigue forcefulness of pavement | 0.2958 | ||
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In this paper, the annual boilerplate growth charge per unit of unlike aircraft models in the airport pavement evaluation stage was 0.20 based on tendency extension method. In this style, the number of annual aircraft operations in future can exist estimated and the cumulative pavement damage can be calculated (run into Tabular array 7 for details). Given the predicted boilerplate almanac cumulative damage of 0.2568 and the remaining fatigue strength of 0.2958, the remaining life of pavement was predicted to exist 0.2958/0.2568 = i.15 years. The Airport A has been shut down for maintenance and renovation in 2022, which was consistent with the remaining life predicted in this newspaper.
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| Note. The information in the table were those predicted of an drome in 2022. | ||||||||||||||||||||||||||||||||||||||||
5. Conclusions
In this paper, the remaining life prediction method of airport runway was analyzed. The operation process of MEPDG was analyzed and summarized, and the MEPDG correction method was practical to the remaining life prediction of the airport runway. Since the airport runway was different from the expressway, the reliability calculation method of finite chemical element numerical analysis was used to deal with the blueprint stress of pavement plate edge that met 95% target reliability. The remaining life of drome rails was analyzed based on the actual data from the MEPDG correction method. The main conclusions were equally follows: (1) Co-ordinate to the theory of structural reliability, the performance function of aerodrome pavement was obtained based on the limit state equation represented by flexural stress; the calculation formula of the number of allowable load deportment can be obtained based on reliability past NCHRP126 fatigue equation without considering the temperature stress when the flexural fatigue strength of pavement plate cement physical was less than 1.25 . (2) This paper selected a runway of the civil airport in Henan as the application case and adopted the MEPDG correction method. The flexural stress of the actual operating airdrome runway pavement at 95% reliability level was analyzed based on the mechanical numerical model of airport runway, and the number of allowable load actions of three aircraft models was obtained; given the affect of P/C, the CDF of the major aircraft models was calculated; the annual boilerplate growth charge per unit of dissimilar aircraft models in the airdrome pavement evaluation phase was 0.20 obtained based on the trend extension method. In this mode, the number of almanac shipping operations in future can exist estimated and the cumulative pavement damage could be calculated. Given the predicted average annual cumulative damage of 0.2568 and the remaining fatigue strength of 0.2958, the remaining life of pavement was predicted to be 1.15 years. Airdrome A has been close downward for maintenance and renovation in 2022, which was consistent with the remaining life predicted in this newspaper.
Information Availability
The figure and table data used to support the findings of this study are included in the paper. In addition, the information and the models of assay are available from the corresponding author upon asking.
Conflicts of Interest
The authors declare that there are no conflicts of involvement regarding the publication of this paper.
Acknowledgments
This inquiry was funded past the Primal Research Program in Universities of Henan Province (No. 21B580008) and the Science and Technology Projection of Henan Province (No. 182102310747), for which the authors are grateful.
Copyright
Copyright © 2022 Baoli Wei and Chengchao Guo. This is an open access commodity distributed under the Artistic Commons Attribution License, which permits unrestricted utilise, distribution, and reproduction in any medium, provided the original piece of work is properly cited.
Source: https://www.hindawi.com/journals/amse/2022/6494812/
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