SEMI-EMPIRICAL KERNEL FUNCTION FOR THE ANALYSIS OF FIBER BRAGG GRATINGS UNDER TEMPERATURE DISTRIBUTIONS

2011 ◽  
Vol 25 (31) ◽  
pp. 4208-4211
Author(s):  
JINHO BAE ◽  
CHONG HYUN LEE ◽  
JOON-YOUNG KIM ◽  
YUN-HAE KIM
Keyword(s):  
Kernel Function ◽  
Coupling Coefficient ◽  
Fundamental Matrix ◽  
Fiber Bragg Gratings ◽  
Bragg Gratings ◽  
Thermal Change ◽  
Temperature Distributions ◽  
Proposed Model ◽  
Thermal Changes ◽  
Semi Empirical

To analyze the various Fiber Bragg gratings (FBGs) with thermal changes, we present how makes a kernel function to translate the information of thermal change into coupling coefficient and detuning factor. We also propose an accurate and versatile extended fundamental matrix model (EFMM) with the kernel function. The proposed model is then can be used to design the piecewise uniform FBGs with the thermal changes. Sensitivity of a temperature variation is performed using Mote Carlo simulations.

Local coupling-coefficient characterization in fiber Bragg gratings

2003 ◽  
Vol 28 (8) ◽  
pp. 598 ◽  
Author(s):  
Ph. Giaccari ◽  
H. G. Limberger ◽  
R. P. Salathé
Keyword(s):  
Coupling Coefficient ◽  
Fiber Bragg Gratings ◽  
Bragg Gratings ◽  
Local Coupling

Fabrication of superimposed fiber Bragg gratings and applications in fiber laser oscillators

Optik ◽  
2020 ◽  
Vol 214 ◽  
pp. 164583
Author(s):  
Qihao Hu ◽  
Pengrui Wang ◽  
Meng Wang ◽  
Zefeng Wang
Keyword(s):  
Fiber Laser ◽  
Fiber Bragg Gratings ◽  
Bragg Gratings ◽  
Laser Oscillators

scholarly journals A Semi-Empirical Model for Predicting Frost Properties

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 412
Author(s):  
Shao-Ming Li ◽  
Kai-Shing Yang ◽  
Chi-Chuan Wang
Keyword(s):  
Thermal Conductivity ◽  
Linear Programming ◽  
Numerical Model ◽  
Empirical Model ◽  
Quantitative Method ◽  
Predictive Ability ◽  
Dimensionless Temperature ◽  
Crystal Shape ◽  
Proposed Model ◽  
Semi Empirical

In this study, a quantitative method for classifying the frost geometry is first proposed to substantiate a numerical model in predicting frost properties like density, thickness, and thermal conductivity. This method can recognize the crystal shape via linear programming of the existing map for frost morphology. By using this method, the frost conditions can be taken into account in a model to obtain the corresponding frost properties like thermal conductivity, frost thickness, and density for specific frost crystal. It is found that the developed model can predict the frost properties more accurately than the existing correlations. Specifically, the proposed model can identify the corresponding frost shape by a dimensionless temperature and the surface temperature. Moreover, by adopting the frost identification into the numerical model, the frost thickness can also be predicted satisfactorily. The proposed calculation method not only shows better predictive ability with thermal conductivities, but also gives good predictions for density and is especially accurate when the frost density is lower than 125 kg/m3. Yet, the predictive ability for frost density is improved by 24% when compared to the most accurate correlation available.

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