scholarly journals A Broad-Based Decision-Making Procedure for Runway Friction Decay Analysis in Maintenance Operations

2020 ◽  
Vol 12 (9) ◽  
pp. 3516 ◽  
Author(s):  
Salvatore Antonio Biancardo ◽  
Francesco Abbondati ◽  
Francesca Russo ◽  
Rosa Veropalumbo ◽  
Gianluca Dell’Acqua
Keyword(s):  
Surface Characteristics ◽  
Pavement Management ◽  
Performance Characteristics ◽  
Surface Layers ◽  
Airport Management ◽  
Traffic Loads ◽  
Pavement Management Systems ◽  
Key Factor ◽  
And Performance ◽  
Aircraft Loads

The evaluation of friction is a key factor in monitoring and controlling runway surface characteristics. For this reason, specific airport management and maintenance are required to continuously monitor the performance characteristics needed to guarantee an adequate level of safety and functionality. In this regard, the authors conducted years of experimental surveys at airports including Lamezia Terme International Airport. The surveys aimed to monitor air traffic, features of geometric infrastructure, the typological and physical/mechanical characteristics of pavement layers, and runway maintenance planning. The main objective of this study was to calibrate specific models to examine the evolution of friction decay on runways in relation to traffic loads. The reliability of the models was demonstrated in the light of the significance of the friction measurement patterns by learning algorithms and considering the traffic data by varying the geometric and performance characteristics of the aircraft. The calibrated models can be implemented into pavement management systems to predict runway friction degradation, based on aircraft loads during the lifetime of the surface layers of the pavement. It is thus possible to schedule the maintenance activities necessary to ensure the safety of landing and takeoff maneuvers.

Acoustic and Performance Characteristics of an Ideally Twisted Rotor in Hover

2021 ◽  
Author(s):  
Nicole A. Pettingill ◽  
Nikolas S. Zawodny ◽  
Christopher Thurman ◽  
Leonard V. Lopes
Keyword(s):  
Performance Characteristics ◽  
And Performance

Local Calibration of Pavement Mechanistic-Empirical Faulting Reliability using Pavement Management Data

2021 ◽  
pp. 036119812110013
Author(s):  
Lucio Salles de Salles ◽  
Lev Khazanovich
Keyword(s):  
Model Calibration ◽  
Prediction Models ◽  
Plain Concrete ◽  
Performance Model ◽  
Pavement Management ◽  
Pavement Design ◽  
Reliability Model ◽  
Transverse Joint ◽  
Design Characteristics ◽  
And Performance

The Pavement ME transverse joint faulting model incorporates mechanistic theories that predict development of joint faulting in jointed plain concrete pavements (JPCP). The model is calibrated using the Long-Term Pavement Performance database. However, the Mechanistic-Empirical Pavement Design Guide (MEPDG) encourages transportation agencies, such as state departments of transportation, to perform local calibrations of the faulting model included in Pavement ME. Model calibration is a complicated and effort-intensive process that requires high-quality pavement design and performance data. Pavement management data—which is collected regularly and in large amounts—may present higher variability than is desired for faulting performance model calibration. The MEPDG performance prediction models predict pavement distresses with 50% reliability. JPCP are usually designed for high levels of faulting reliability to reduce likelihood of excessive faulting. For design, improving the faulting reliability model is as important as improving the faulting prediction model. This paper proposes a calibration of the Pavement ME reliability model using pavement management system (PMS) data. It illustrates the proposed approach using PMS data from Pennsylvania Department of Transportation. Results show an increase in accuracy for faulting predictions using the new reliability model with various design characteristics. Moreover, the new reliability model allows design of JPCP considering higher levels of traffic because of the less conservative predictions.

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