胜利断块油藏细分注水技术界限研究

老油田进入特高含水期后,剩余油分布更加零散,各种地质因素也因长期注水开发而发生了一定的改变.此时稳油控水难度进一步加大,为了进一步挖掘剩余油,控制含水上升速度、减缓产量递减,必须对注水井采取进一步的细分调整.基于水湿油藏注水井注水层段吸水效果,从注入水受力分析入手,运用达西定律推导出了水驱油藏水驱油全过程中的单位体积注入水沿竖直、地层两个方向运移的渗流速度公式,明晰了水驱油藏注水层段不同开发阶段砂岩吸水机理.研究结果表明,水驱油藏细分注水效果与岩石绝对渗透率、水相相对渗透率、注入水黏度、水动力压力梯度、注水井启动压力梯度、含水饱和度、地层倾角、油水密度差等参数有关.结合胜利油田断块油藏地质特征及细分注水工艺要求,制定了一套适合胜利油田不同断块区的细分注水技术政策界限:层段内渗透率变异系数小于0.3,砂岩条带宽度极比小于2.5,且东辛油区断块油藏层段内砂岩厚度小于6m,小层数小于4个;现河油区断块油藏层段内砂岩厚度小于5m,小层数小于5个;临盘油区断块油藏层段内砂岩厚度小于6m,小层数小于6个.矿场试验证实,该细分注水技术政策界限是合理、实用的,其为胜利断块油藏注上水、注够水、注好水,实现多层断块油藏的高效开发提供了技术保障,对类似油藏细分注水技术界限研究具有一定的借鉴意义.     

A computational study on fill rate expressions for single-stage periodic review under normal demand and constant lead time

This paper reviews fill rate expressions for a single stage periodic review inventory system under normal demand and constant lead time, discusses the relationship among all expressions in the literature, and evaluates their robustness and accuracy. Monte Carlo simulation is used to numerically compare all expressions. We present conditions under which some expressions produce higher values than others.     

基于语义的软件服务故障自动诊断模型

模仿学习是机器人仿生机制研究的主要内容之一,即通过观察、理解、学习、模仿示教行为实现机器人的仿生特性。基于高斯过程分别表达采集离散示教信号所构成的示教轨迹和含有未知参数策略的模仿轨迹,构建模仿学习方法框架,将概率模型匹配引入到模仿学习中,以KL散度为代价函数比较两种轨迹的概率分布,运用梯度下降法寻求使KL散度最小的最优模仿控制策略,将策略应用于模仿机器人以完成与示教相同的模仿任务。以关节型机器人的机械臂摆动行为模仿为学习任务进行仿真,结果表明基于概率轨迹匹配的模仿学习方法能够实现机械臂摆动行为模仿,学习过程较传统方法简易且学习效果较好。     

Model-Based Optimization of a Fed-Batch Bioreactor for mAb Production Using a Hybridoma Cell Culture

Production of monoclonal antibodies (mAbs) is a well-known method used to synthesize a large number of identical antibodies, which are molecules of huge importance in medicine. Due to such reasons, intense efforts have been invested to maximize the mAbs production in bioreactors with hybridoma cell cultures. However, the optimal control of such sensitive bioreactors is an engineering problem difficult to solve due to the large number of state-variables with highly nonlinear dynamics, which often translates into a non-convex optimization problem that involves a significant number of decision (control) variables. Based on an adequate kinetic model adopted from the literature, this paper focuses on developing an in-silico (model-based, offline) numerical analysis of a fed-batch bioreactor (FBR) with an immobilized hybridoma culture to determine its optimal feeding policy by considering a small number of control variables, thus ensuring maximization of mAbs production. The obtained time stepwise optimal feeding policies of FBR were proven to obtain better performances than those of simple batch operation (BR) for all the verified alternatives in terms of raw material consumption and mAbs productivity. Several elements of novelty (i–iv) are pointed out in the “conclusions” section (e.g., considering the continuously added biomass as a control variable during FBR).     

口腔医院系统发展对策生成与对策效应定量仿真评价

医院系统是一个复杂系统.对此,采用对策生成与对策实施未来效应仿真评价法对南昌大学口腔医院发展进行研究.首先,对南昌大学口腔医院发展进行了深入调查与数据分析,然后,建立7个增长正反馈环和4个制约负反馈环构成的增长制约反馈基模,揭示现行系统发展的优势和存在的问题,又围绕7个增长正反馈环和4个制约负反馈环的内涵,依据消除制约的原理,提出了消除负反馈环制约的两项管理对策.接着,对管理对策未来实施效应进行仿真评价,基于评价指标建立流位流率系,基于调查数据值及比较分析建立七棵入树的仿真方程,建立仿真模型,分别对南昌大学口腔医院系统发展两项对策实施状况进行仿真评价,定量论证了所制定的管理对策的科学性及实施的必要性,为南昌大学口腔医院十二五规划编制与发展提供了决策依据.     

Climate change and optimal energy technology R&D policy

Public policy response to global climate change presents a classic problem of decision making under uncertainty. Theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy, especially technology policy. However, theory also shows that the specific impacts of uncertainty are ambiguous. In this paper, we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development (R&D) policy in response to global climate change. We find that, given a budget constraint, the composition of the optimal R&D portfolio is highly diversified and robust to risk in climate damages. The overall optimal investment into technical change, however, does depend (in a non-monotonic way) on the risk in climate damages. Finally, we show that in order to properly value R&D, abatement must be included as a recourse decision.     

Generalized Markov Models of Infectious Disease Spread: A Novel Framework for Developing Dynamic Health Policies

We propose a class of mathematical models for the transmission of infectious diseases in large populations. This class of models, which generalizes the existing discrete-time Markov chain models of infectious diseases, is compatible with efficient dynamic optimization techniques to assist real-time selection and modification of public health interventions in response to evolving epidemiological situations and changing availability of information and medical resources. While retaining the strength of existing classes of mathematical models in their ability to represent the within-host natural history of disease and between-host transmission dynamics, the proposed models possess two advantages over previous models: (1) these models can be used to generate optimal dynamic health policies for controlling spreads of infectious diseases, and (2) these models are able to approximate the spread of the disease in relatively large populations with a limited state space size and computation time.     

第三方负责回收的Dowrside-Risk闭环供应链协调性研究

以风险中性制造商、第三方物流服务商和具有下行风险特性的销售商组成的闭环供应链系统为背景,证明了在Downside-Risk约束下收益费用共享契约不能使闭环供应链协调.通过将补偿策略附加到该契约,设计了风险共享契约,既能满足下行风险约束,又保证供应链参与方利润均有增量,实现了Downside-Risk约束下闭环供应链的协调.最后通过应用算例说明了风险共享契约的有效性和可行性.     

需求率为斜坡型的一类变质性物品最优库存策略

本文在考虑需求率服从斜坡型分布的情况下,研究了允许缺货且缺货完全回补、变质率服从威布尔分布、补货率为无穷、有限计划期内的库存模型,证明了最优补货策略的存在性,并给出了求解最优补货策略的算法.     

延期支付条件下零售商的最优售价和订货策略

在供应商给予零售商延期支付和现金折扣的优惠政策下,进一步假设产品的年需求量依赖于零售商产品售价的基础上,建立了由一个零售商和一个供应商所构成的库存决策模型,扩展了经典的经济生产批量(EPQ)模型。通过模型的分析求解,可以得出零售商在上述情况下的最优订货周期、最优售价及最优付款时间的简单判定方法。最后,通过算例,验证了模型的可行性,得出了与实际相符的结论。