炼油厂全流程优化建模方法研究

为了克服使用线性规划和单处理单元非线性规划进行生产优化的内在缺点，在建立原油单元、催化裂化、催化重整和汽油调合等4个重要处理单元详细模型的基础上，将单处理单元非线性过程模型集成到一个全流程优化非线性模型中。优化的目标函数是使炼油厂全厂利润最大。决策变量是那些显著影响全厂效益的变量，约束条件是单个处理单元约束条件的集合。对某炼油厂进行实例研究，结果表明该全流程模型能有效处理全厂优化问题，所得利润在线性规划的基础上提高4．5％。     

渤海绥中油田J3井疏水缔合聚合物驱数值模拟研究

为了进一步提高渤海油田J3井区缔合聚合物驱的技术经济效果,在渤海油田室内配方和先导性矿场试验研究基础上,利用化学驱油藏数值模拟软件FAPMS,分析和研究了高浓度缔合聚合物前置段塞、主段塞的大小和浓度以及段塞组合方式对驱油效果的影响,优化设计了渤海绥中油田J3井区块矿场试验的最佳注入程序及段塞大小。结果表明,通过对不同浓度的疏水缔合聚合物注入的前置段塞及主段塞和梯度式后续段塞的优化后,原油采收率比未优化时提高了约10个百分点。研究表明,渤海油田应该高度重视聚合物驱的注入方式和段塞优化设计,进一步提高聚合物的技术经济效果。     

Measurement and Identification of the Parameters of SPICE-Models of a Bipolar Transistor

A method of measuring and identifying the static parameters of a bipolar transistor is considered. The characteristic of the transistor, from which the parameters of the model are determined, is chosen depending on what group the calculated parameters belong to. The characteristics are measured in such a way that the equations of the model describing them can be reduced to the simplest form.     

基于模式理论光栅椭偏参数反演的数值模拟

将一种广泛用于求解系统优化问题的方法——正单纯形法，求解光栅的椭偏方程。首先，利用求解光栅的傅立叶模式理论对TE和TM波的复反射系数进行求解。然后计算出其相应的椭偏参数(△，Ψ)，并在该值的基础上加入不同偏差的随机高斯噪声，将加入噪声后的值(△m，Ψm)作为模拟测量值。最后使用优化算法进行反演。通过对几种常用面形光栅椭偏参数的数值模拟，一方面表明傅立叶模式理论计算光栅的椭偏参数不仅精度高。而且速度快；另一方面表明利用正单纯形法得到的光栅参数值很接近于正演时假设的参数值，从而从理论上证明了利用椭偏法测量光栅各种光学参数的可行性。     

钻井参数仪的模块化设计方法研究

文章以模块化设计原理为基础，讨论了钻井参数仪的模块划分，模块化设计准则和主要设计内容。采用模块化设计方法、现场设备网络的开放网络和现场总线解决方案设计的钻井参数仪，具有传输信号稳定、可靠性高、抑制噪声能力强、组建现场网络成本低等特点。     

宝浪油田宝北区块低渗透油藏层系优化研究

针对宝浪油田宝北区块低孔低渗油藏地质特征以及油层层数多、分布井段长、部分零散层动用难度大等问题 ,研究了宝北区有效厚度、油层层数、单井产能及单井控制地质储量等层系划分与组合的技术经济界限 ,并在此基础上进行了宝北区层系划分与组合优化论证 ,最终优选出宝北区开发层系     

带参数的一阶脉冲微分方程边值问题

利用上下解和单调迭代法。讨论了带参数的一阶脉冲微分方程。获得了单边Lipschitz条件下这类方程边值问题的解的存在性。     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Texture Changes During the Ripening of Port Salut Argentino Cheese in 2 Sampling Zones

ABSTRACT: Texture changes during ripening of Port Salut Argentino cheese for different sampling zones were studied. Compression relaxation tests were performed and results were analyzed using both Maxwellian and Peleg's models. Elastic equilibrium modulus obtained from the Maxwellian model decreased from 1.22 to 0.11 10⁴Pa during ripening. The constants derived from Peleg's model, k₁ and k₂, diminished with ripening time from 1.18 to 0.71 min and from 1.27 to 1.12, respectively. Asymptotic equilibrium modulus from Peleg's model decreased from 0.95 to 0.07 10⁴Pa during ripening. Rate parameters derived from a 1st order kinetics applied to both equilibrium moduli showed that the decrease was faster in the external zone (0.0846 d⁻¹) than in the central zone (0.0368 d⁻¹). The correlation between equilibrium moduli, salt concentration, moisture content, and maturation indexes was obtained with a determination coefficient of 0.76.