Strain-energy density ratio criterion for failure of composite-materials

n the authors' previous paper, the Strain Energy Density Ratio (SEDR) criterion was proposed. As an example of applications, it was used to predict cracking direction of mixed-mode fracture in a random short fibre laminated composite.

Gain saturation in gas flow and chemical lasers

A theoretical model for gain saturation in gas flow and chemical lasers is presented. The theory is applicable to all possible numerical values of τ/τc, where τ is the characteristie flow time for the flowing gas to move across the laser action region and τc is the characteristic collision relaxation time. The saturation effects of the convection and the "source flow" of the inverted population are revealed. A general relation of gain coefficient and some new gain saturation laws are obtained. For the special case of τ/τc1, the present theoretical results agree with the experimental results on the "anomalous" saturation phenomena in the supersonic diffusion HF chemical laser determined recently by Gross and Coffer[8]. The theory also agrees with the measured results of saturation intensity varying with τ/τc in gas flow CO2 lasers[7]. For the special case of τ/τc1, the present theory is consistent with both the standard theory[1] for gas lasers where the gas has no macroscopic motion and the known gain saturation theory[2-5] for gas flow and chemical lasers.

COIL基于小信号增益系数的最佳流量配比选择

氧碘化学激光器（COIL）的混合喷管内发生的是气体动力学、化学反应动力学以及光学等相互耦合的复杂过程，每个过程都对COIL性能有着至关重要的影响。利用3维CFD技术，通过求解层流Navier—Stokes方程与组分输运方程，结合10种组分和21个基元反应的化学反应模型，对简化后的化学氧碘激光RADICI。模型在亚声速段横向射流情况下，不同的主副流流量配比对小信号增益系数的影响情况进行了比较与分析。结果证明：过高或过低的碘分子浓度均不利于产生合理的小信号增益系数；存在最佳流量配比使小信号增益系数得到显著提高且分布均匀。

Another Look to the Price-Dividend Ratio: A Markov-Switching Approach

This paper analyzes the stationarity of this ratio in the context of a Markov-switching model à la Hamilton (1989) where an asymmetric speed of adjustment is introduced. This particular specification robustly supports a nonlinear reversion process and identifies two relevant episodes: the post-war period from the mid-50’s to the mid-70’s and the so called “90’s boom” period. A three-regime Markov-switching model displays the best regime identification and reveals that only the first part of the 90’s boom (1985-1995) and the post-war period are near-nonstationary states. Interestingly, the last part of the 90’s boom (1996-2000), characterized by a growing price-dividend ratio, is entirely attributed to a regime featuring a highly reverting process.