Optimizing Airport Runway Performance by Managing Pavement Infrastructure
Bibliographic record
Abstract
The research described herein is composed of four major areas of practice. It examines the overall performance of runways and provides tools designed to improve current runway operations and management with particular emphasis on contaminated surfaces. \n \nPresented in this thesis is an overview of how to design airport pavements in order to achieve optimal friction by specifically focusing on material selection and construction techniques for rigid and flexible pavements. Rubber buildup and the impact rubber accumulation has on decreasing runway friction, particularly in a range of climatic conditions, is discussed. Four commonly used rubber removal techniques are presented and evaluated. Through this research, an analytical hierarchy process (AHP) decision making protocol was developed for incorporation into airport pavement management systems (APMS). \n \nRunway surface condition reporting practices used at the Region of Waterloo International Airport are evaluated and recommendations for improving current practices are identified. Runway surface condition reporting can be improved by removing subjectivity, reporting conditions to pilots in real time, standardizing terminology and measurement techniques, and including runway pictures or sketches to identify contaminant locations where possible. Reports should be incorporated and stored in the APMS. \n \nAircraft braking systems and their effects on landing distances under contaminated conditions are discussed. This thesis presents a proposed solution for monitoring and measuring contaminated runway surfaces and identifying the risks associated with aircraft landing through using the Braking Availability Tester (BAT). Also proposed in this thesis is a testing framework for validating the Braking Availability Tester. The proposed BAT measures interaction between aircraft antiskid braking systems and runway contaminants to determine landing distances more accurately. \n \nFinally, this thesis includes a discussion explaining how pavement design, contaminant removal, results from friction tests, and results from the BAT can be incorporated into airport pavement management systems. APMS data can be analyzed to economically optimize and prioritize scheduling of pavement maintenance, preservation and rehabilitation treatments to maintain a high level of service, thereby contributing to runway safety and optimization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".