Modeling and simulation of output power of a high-power He–SrBr2 laser by using multivariate adaptive regression splines

Due to advancement in computing technology researchers are focusing onto novel predictive models and techniques for improving the design and performance of the devices. This study examines a recently developed high-powered SrBr2 laser excited in a nanosecond pulse longitudinal He–SrBr2 discharge. Based on the accumulated experiment data, a new approach is proposed for determining the relationship between laser output power and basic laser characteristics: geometric design, supplied electric power, helium pressure, etc. Piece-wise linear and nonlinear statistical models have been built with the help of the flexible predictive MARS technique. It is shown that the best nonlinear MARS model containing second degree terms provides the best description of the examined data, demonstrating a coefficient of determination of over 99%. The resulting theoretical models are used to estimate and predict the experiment as well as to analyze the local behavior of the relationships between laser output power and input laser characteristics. The second order model is applied to the design and optimization of the laser in order to enhance laser generation.

► The nonlinear MARS model describes more than 99% of all examined data.
► By means of MARS models one can discover specific basic local relationships.
► The obtained results are used for estimating and predicting the laser output power.