Wind Prediction System for Runway Reconfiguration
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Solution Overview
Problem
Current air traffic management systems lack the ability to predict wind direction changes in advance, leading to disruptive reconfiguration of runway use, resulting in flight delays, increased costs, and safety concerns due to tailwinds, and the wind energy industry faces inaccuracies in wind speed forecasts affecting turbine power output.
Innovation Solution
A decision aid tool and wind speed prediction system that uses 3-D wind field sampling with arbitrary resolution to forecast wind direction and speed changes, allowing for early planning and reconfiguration of runway use and wind turbine operations, incorporating lidar and radar sensors to propagate wind vectors and determine prevailing wind vectors for accurate predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ATM re-configures runway use after wind direction changes, then aircraft safety is maintained by avoiding tailwinds, but air traffic flow is significantly disrupted causing flight delays and no aircraft touchdowns
Solution Approach 1:
The wind prediction system performs preliminary action by forecasting wind direction changes 30 minutes in advance, allowing ATM to proactively re-configure runway use before the actual wind change occurs. This advance planning enables smooth transition of aircraft to new approach directions without disruptive interruptions to air traffic flow, while still maintaining safety by avoiding tailwinds.
2Reliability
If ATM performs holding maneuvers for aircraft during reconfiguration, then aircraft safety is maintained by preventing touchdowns with tailwinds, but additional danger is introduced due to disrupted aircraft flow
Solution Approach 1:
By predicting wind direction changes 30 minutes in advance, the system enables ATM to issue preliminary instructions to aircraft about upcoming runway re-configuration. This allows aircraft to plan their approach paths in advance, minimizing the need for disruptive holding maneuvers like dog-legs and S-turns, thereby reducing the dangers associated with disrupted aircraft flow while still preventing tailwind touchdowns.
3Loss of information
If numerical weather models are used to predict wind speeds, then wind speed forecasts are obtained, but large wind speed errors occur due to coarsely sampled atmospheric information
Solution Approach 1:
The system segments the atmosphere into multiple discrete levels or layers and collects wind speed measurements at each level. By dividing the atmospheric column into segments and gathering data from each, the system obtains fine-scale wind information that captures vertical wind shear and local variations, thereby significantly improving wind speed forecast accuracy compared to coarsely sampled numerical weather models.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system significantly reduces or eliminates periods of no aircraft touchdowns due to tailwind-related reconfiguration, offering substantial financial and safety benefits for airports and airlines, while providing highly accurate wind speed forecasts for wind turbines, reducing errors associated with traditional numerical weather models.
Implementation Method 1
at least one wind sensor configured to sample wind vectors for a plurality of parcels of air
Implementation Method 2
incorporating lidar and radar sensors to propagate wind vectors
Data Source
AI summary
A wind prediction system is provided that can be implemented in an air-traffic decision tool or a wind turbine system. An air-traffic decision tool may incorporate a wind prediction system to generate prevailing wind direction predictions and determine a time at which to re-configure runway directions. A wind turbine system may incorporate a wind prediction system to predict power output of a wind turbine.