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Assessing safety in wind-exposed installations is crucial to preventing potential failures. This example explores the calculation and design adjustments needed to mount a circular disc on a building facade, where wind forces are a primary concern. A 4-meter diameter disc was initially designed as an aesthetic feature facing winds at a velocity of 25 meters per second, with an air density of 1.25 kilograms per cubic meter. Given these conditions, the drag force on the disc was determined using...
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Updated: Aug 8, 2025

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
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Wind speed and direction measurement method based on intelligent optimization algorithm.

Xinbo Li1, Xiaoyu Wang1, Xinyu Zuo1

  • 1School of Communication Engineering, Jilin University, 130022 Changchun, China.

The Review of Scientific Instruments
|March 1, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces intelligent optimization algorithms for ultrasonic array wind measurement, significantly reducing computational load. The novel approach enables faster, more accurate wind speed and direction detection, enhancing ultrasonic wind parameter measurement technology.

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Area of Science:

  • Sensor Technology
  • Acoustic Measurement
  • Computational Fluid Dynamics

Background:

  • Accurate wind speed and direction measurement is crucial for various applications.
  • Current ultrasonic array algorithms face computational challenges due to spectrum peak search.
  • This limits the development and application of ultrasonic array wind parameter measurement.

Purpose of the Study:

  • To develop an intelligent optimization algorithm for rapid and accurate wind speed and direction measurement using a co-prime arc ultrasonic array.
  • To overcome the computational burden associated with traditional spectrum peak search methods.
  • To enhance the efficiency and applicability of ultrasonic array wind measurement technology.

Main Methods:

  • Utilized a co-prime arc ultrasonic array configuration.
  • Employed particle swarm optimization (PSO) with the spatial-spectral function of the propagator method as the fitness function.
  • Applied the artificial bee colony (ABC) algorithm to further reduce computational complexity for wind parameter estimation.

Main Results:

  • Successfully formulated wind parameter estimation as a function optimization problem, enabling fast and accurate measurements.
  • Demonstrated significant reduction in computational time complexity, up to 90%, compared to conventional methods.
  • Validated the performance, speed, and feasibility through simulations and hardware experiments.

Conclusions:

  • The proposed intelligent optimization algorithms effectively address the computational limitations of existing ultrasonic array wind measurement techniques.
  • This approach offers a feasible and efficient solution for rapid and accurate wind speed and direction determination.
  • The validated method holds promise for advancing ultrasonic array wind parameter measurement technology.