Uncertainty propagation through integrated quantities for radiation thermometry

Metrologia ◽  
2018 ◽  
Vol 55 (6) ◽  
pp. 863-871 ◽  
Author(s):  
Peter Saunders
2020 ◽  
Vol 21 (6) ◽  
pp. 612
Author(s):  
Yunkun Wei ◽  
Tianhong Zhang ◽  
Zhonglin Lin ◽  
Qi Xie ◽  
Yan Zhang

After the lean fuel premixed combustion technology is applied to aero engines, severe combustion oscillations will be cased and led to hidden safety hazards such as engine vibration, further energy waste and other problems. Therefore, it is increasingly important to actively control combustion oscillations. In this paper, a multispectral radiation thermometry (MRT) is used to analyze the hydroxyl group, which is a measurable research object in the combustion chamber of an aero engine, and to fit the functional relationship between the radiation intensity ratio and the temperature in different bands. The theoretical value of the error is <2%. At the same time, in order to solve the problem of weak detection signal and excessive interference signal, an improved frequency domain filtering method based on fast Fourier transform is designed. Besides, the FPGA platform is used to ensure the real-time performance of the temperature measurement system, and simulations and experiments are performed. An oscillating signal with an oscillation frequency of 315 Hz is obtained on the established test platform, and the error is only 1.42%.


Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1830
Author(s):  
Gullnaz Shahzadi ◽  
Azzeddine Soulaïmani

Computational modeling plays a significant role in the design of rockfill dams. Various constitutive soil parameters are used to design such models, which often involve high uncertainties due to the complex structure of rockfill dams comprising various zones of different soil parameters. This study performs an uncertainty analysis and a global sensitivity analysis to assess the effect of constitutive soil parameters on the behavior of a rockfill dam. A Finite Element code (Plaxis) is utilized for the structure analysis. A database of the computed displacements at inclinometers installed in the dam is generated and compared to in situ measurements. Surrogate models are significant tools for approximating the relationship between input soil parameters and displacements and thereby reducing the computational costs of parametric studies. Polynomial chaos expansion and deep neural networks are used to build surrogate models to compute the Sobol indices required to identify the impact of soil parameters on dam behavior.


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