The computation of the friction velocity u * and the temperature scale T * from temperature and wind velocity profiles by least-square methods

1978 ◽  
Vol 14 (2) ◽  
pp. 235-246 ◽  
Author(s):  
F. Nieuwstadt
Keyword(s):  
Wind Velocity ◽  
Friction Velocity ◽  
Temperature Scale ◽  
Velocity Profiles ◽  
Least Square

On wind velocity profiles over urban area

2003 ◽  
Vol 20 (1/2/3/4/5/6) ◽  
pp. 196
Author(s):  
Klara Bezpalcova ◽  
Zbynek Janour ◽  
Viktor M.M. Prior ◽  
Cecilia Soriano ◽  
Michal Strizik
Keyword(s):  
Urban Area ◽  
Wind Velocity ◽  
Velocity Profiles

Research on Zero Bias Characteristic of MEMS Accelerometer in FBW

2014 ◽  
Vol 609-610 ◽  
pp. 1046-1052
Author(s):  
Lun Chao Zhong ◽  
Jian Zhong Wang ◽  
Jia Dong Shi
Keyword(s):  
Random Error ◽  
Temperature Scale ◽  
Least Square Method ◽  
Temperature Characteristic ◽  
Least Square ◽  
Measuring Error ◽  
Zero Bias ◽  
Mems Accelerometer ◽  
Temperature Bias ◽  
Bias Stability

Zero bias is an important performance index of MEMS accelerometerscope. Based on the large amount of given accelerometer experiments, we study zero bias of random error properties, temperature characteristic, large overload environment variation, and then calculate MEMS accelerometer bias, bias stability, zero bias repeatability. Through least-square method,we fit temperature scale factor and temperature bias of MEMS accelerometer. The experimental results show that the compensation method has the advantages of simple operation, effectively compensation for measuring error of MEMS accelerometer which is induced by temperature, and has strong engineering using value.

Lidar Measurement of Wind Velocity Profiles in the Boundary Layer

1980 ◽  
Vol 19 (5) ◽  
pp. 598-605 ◽  
Author(s):  
Jeffery T. Sroga ◽  
Edwin W. Eloranta ◽  
Ted Barber
Keyword(s):  
Boundary Layer ◽  
Wind Velocity ◽  
Velocity Profiles ◽  
Lidar Measurement
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