Uncertainty quantification and design-of-experiment in absorption-based aqueous film parameter measurements using Bayesian inference.
Uncertainty quantification and design-of-experiment in absorption-based aqueous film parameter measurements using Bayesian inference.
复制标题
使用贝叶斯推理进行基于吸收的水膜参数测量的不确定性量化和实验设计。
DOI:
10.1364/ao.56.0000e1
复制
发表时间:
2017
期刊:
影响因子:
1.9
通讯作者:
C. Schulz
中科院分区:
文献类型:
--
作者:
R. Pan;K. Daun;T. Dreier;C. Schulz
Diode laser-based multi-wavelength near-infrared (NIR) absorption in aqueous films is a promising diagnostic for making temporally resolved, simultaneous measurements of film thickness, temperature, and concentration of a solute. Our previous work in aqueous urea solutions aimed at determining simultaneously two of these system parameters, while the third one must be fixed or specified by additional measurements. The current work presents a simultaneous NIR absorption-based multi-parameter measurement of thickness, temperature, and solute concentration coupled with the Bayesian methodology that is used to infer probability densities for the obtained data. The Bayesian analysis is based on a temperature- and concentration-dependent spectral database generated with a Fourier transform infrared spectrometer in the range 5500-8000 cm-1 for water with variable temperature and urea concentration. The concept was first validated with measurements using a calibration cell. Probability densities in the measured parameters were quantified using a Markov chain Monte Carlo algorithm, which were used to derive credibility intervals. As a practical demonstration, the temporal variation of film thickness, urea concentration, and liquid temperature were recorded during evaporation of a liquid film deposited on a transparent heated quartz plate.