The development of automated probabilistic and optimization design tools for chemical laser systems.

摘要

The Chemical Oxygen-Iodine Laser (COIL) was first demonstrated by the United States Air Force in 1977 [1]. Singlet state oxygen is produced by a two-phase reaction of chlorine gas and liquid basic hydrogen peroxide. The singlet oxygen is then transported from the generator to a bank of supersonic nozzles where molecular iodine is injected transverse to the primary oxygen flow near the throat of the supersonic nozzle. The molecular iodine rapidly dissociates into atomic iodine. At the exit of the nozzle, the fully dissociated flow enters the gain region. In this region, the iodine will undergo many energy transfer excitation and stimulated emission cycles in order to extract most of the energy from the singlet oxygen during the lasing process. The entire process is complex and still poorly understood; as a result mixing nozzle designs have largely remained unaltered for the last 30 years.;The goal of my work is to develop the first computational process for automated design optimization and probabilistic analysis of the COIL mixing nozzle. My main objective of this paper is to present the development and implementation of automated design tools utilized on chemical laser systems. This will demonstrate how dimensional changes to the nozzle within the laser cavity can impact the mixing performance. The probabilistic analysis will provide insight into the importance and sensitivities of selected parameters within the design, while the optimization will converge to an optimal design for the system. The complete analysis will not only include full kinetic reactions and compressible multi-species phenomena, but unlike other computational efforts, it will also include output design manufacturing tolerances for specified performance limits, optimized geometric design, and operating conditions. For the first time, we will be able to configure a COIL for maximum performance while eliminating the expense of trial and error experimentation. Additionally, the tool will enable the evaluation of cost-saving and weight-saving modifications on performance.