WeChat Mini Program
Old Version Features

Optimization of Airplane Landing in Crosswind Conditions for Minimum Tire Wear

MACHINES(2023)

Politecn Milan

Cited 0|Views5
Abstract
Being one of the most critical phases of a flight, landing deserves specific attention, especially when the aircraft is subject to external disturbances such as wind. A notable concern associated with touchdown events, especially when crosswind is present, is tire wear. This work is aimed first at developing a nonlinear flight simulator able to handle the entire landing maneuver in non-null wind conditions, considering the airborne phase, the ground run, and the transition between them. Then, the simulator is included in an optimal process to define the landing technique associated with the minimum tire wear. The methodology is tested in a simulation environment with a realistic model of a reference aircraft, showing that a significant reduction in tire wear can be obtained by optimizing the sideslip angle at touchdown and the lateral–directional controls after the airplane touches the runway with both legs of the main landing gear. The amount of the reduction is highly variable and depends on the landing conditions, e.g., the velocity and glide path angle. It may range from some percentage points up to 45%.
More
Translated text
Key words
landing,flight simulation,tire wear,optimization,crosswind,nonlinear flight dynamics,trim,essential matrix detection
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined