Optimization Efficiency of Monte Carlo Simulation Tool for Evanescent Wave Spectroscopy Fiber-Optic Probe

Abstract

In a previous work, we described the simulation tool (FOPS 3D) (Khankin et al., 2001) which can simulate the full three-dimensional geometrical structure of a fiber and the propagation of a light beam sent through it. In this paper we are focusing on three major points: the first concerns the improvements made with respect to the simulation tool and the second, optimizations implemented with respect to the calculations' efficiency. Finally, the major research improvement from our previous works is the simulation results of the optimal absorbance value, as a function of bending angle for a given uncladded part diameter, that are presented; it is suggested that fiber-bending may improve the efficiency of recording the relevant measurements. This is the third iteration of the FOPS development process (Mann et al., 2009) which was significantly optimized by decreasing memory usage and increasing CPU utilization.

Visible and near-infrared bulk optical properties of raw milk

“…In practice, a wide range of sensor configurations is physically possible. So, it is preferred to test the potential of each sensor configuration through these simulations, rather than building each of them and evaluating their performance from measurements on an extensive set of raw milk samples (Luo et al, 2005;Liu and Ramanujam, 2006;Sharma et al, 2006;Palmer and Ramanujam, 2007;Cen et al, 2010;Gamm et al, 2011;Khankin et al, 2012;Zamora-Rojas et al, 2014). The sensor configuration, which allows for the most robust separation between the absorption and scattering properties, would obviously have the highest potential to retrieve accurate predictions for the milk composition (fat, protein, lactose, urea, and so on) and physical properties (fat globule and CN micelle size distribution) from, respectively, the obtained absorption and scattering properties.…”

“…Accordingly, the potential of each sensor configuration can be defined as the ability to extract the BOP from the collected signals, after adding noise typical for a Vis/NIR spectrometer. Such procedures of sensor design optimization have been widely studied and improved in the last decade and are still an important topic of research (Luo et al, 2005;Liu and Ramanujam, 2006;Sharma et al, 2006;Palmer and Ramanujam, 2007;Cen et al, 2010;Gamm et al, 2011;Khankin et al, 2012;Zamora-Rojas et al, 2014). However, to consult these algorithms to obtain an optimal sensor design for quality control of raw milk, knowledge on the Vis/NIR BOP of raw milk is crucial.…”