在页岩气试井分析中Bessel函数溢出问题的解决方法

Bessel函数在页岩气藏多段压裂水平井的试井解释理论中发挥着非常重要的作用,但变形Bessel函数I_n(x)和K_n(x)在自变量趋于无限小或无限大时,使用多项式逼近的方法求解往往会溢出,难以得到典型曲线致使试井解释困难。为此,从理论上剖析了当储集层渗透率非常低时在无因次时间低于10~(-6)时变形Bessel函数都会溢出的原因。结果表明:对于第一类Bessel函数I_n(x),当x650,I_0(x)与I_1(x)部分计算机出现浮点数溢出,高于10~(215)。页岩气试井理论中根据无因次时间的定义,渗透率越小,压裂裂缝半长越大,测试时间越短,根据Laplace反演I_0与I_1的值非常容易溢出,难以绘制出早期典型曲线。在理论研究的基础上,通过对第一、二类变形Bessel函数的重新组合计算,将I_0与I_1计算过程中都乘以,保证了变形Bessel函数在计算过程中不会溢出。结论认为,大长度水平井或大型压裂井模型中,由于水平段长度或裂缝长度越大,无因次时间相应的就越短、Laplace变量就越大,必须用该方法处理Bessel函数的I_0与I_1,才能获得完整的典型曲线,否则计算就会溢出。     

A Comparative Study on Scaling Capabilities of Si and SiGe Nanoscale Double Gate Tunneling FETs

Silicon - In the last few years, an accelerated trend towards the miniaturization of nanoscale circuits has been recorded. In this context, the Tunneling Field-Effect Transistors (TFETs) are...     

Analytical analysis of nanoscale multiple gate MOSFETs including effects of hot-carrier induced interface charges

As the channel length rapidly shrinks down to the nanoscale regime, the multiple gate MOSFETs structures have been considered as potential candidates for a CMOS device scaling due to its good short-channel-effects (SCEs) immunity. Therefore, in this work we investigate the scaling capability of Double Gate (DG) and Gate All Around (GAA) MOSFETs using an analytical analysis of the two dimensional Poisson equation in which the hot-carrier induced interface charge effects have been considered. Basing on this analysis, we have found that the degradation becomes more important when the channel length gets shorter, and the minimum surface potential position is affected by the hot-carrier induced localized interface charge density. Using this analysis, we have studied the scaling limits of DG and GAA MOSFETs and compared their performances including the hot-carrier effects. Our obtained results showed that the analytical analysis is in close agreement with the 2-D numerical simulation over a wide range of devices parameters. The proposed analytical approach may provide a theoretical basis and physical insights for multiple gate MOSFETs design including the hot-carrier degradation effects.     

An optimized metal grid design to improve the solar cell performance under solar concentration using multiobjective computation

In this paper, a new multiobjective genetic algorithm (MOGA)-based approach is proposed to optimize the metal grid design in order to improve the electrical performance and the conversion efficiency behavior of the solar cells under high intensities of illumination. The proposed approach is applied to investigate the effect of two different metal grid patterns (one with 2 busbars outside the active area (linear grid) and another one with a circular busbar surrounding the active area (circular grid)) on the electrical performance of high efficiency c-Si solar cells under concentrated light (up to 150 suns). The dimensional and electrical parameters of the solar cell have been ascertained, and analytical expressions of the power losses and conversion efficiency, including high illumination effects, have been presented. The presented analytical models are used to formulate different objective functions, which are the prerequisite of the multiobjective optimization. The optimized design can also be incorporated into photovoltaic circuit simulator to study the impact of our approach on the photovoltaic circuit design.