Cu-Cr-Zr-Ag合金高温流变行为及织构演化研究

采用Gleeble-1500D热模拟试验机对Cu-Cr-Zr-Ag合金进行热压缩试验,研究了Cu-Cr-Zr-Ag合金在不同应变速率和变形温度的流变应力行为、微观组织演变和动态再结晶机制,利用光学显微镜(OM)研究了Cu-Cr-Zr-Ag合金的压缩速率、形变温度对合金微观织构的影响.结果表明:在压缩速率为0.001~10 s^-1的区间内,Cu-Cr-Zr-Ag合金存在近稳态流变特征,即流变应力随温升及压缩速率的降低而变小.形变温度越高,越能促使再结晶形核,压缩速率越低,越利于动态再结晶充分发生.     

透平湿蒸汽非平衡流动仿真模型

分析了湿蒸汽的自发凝结特性,假设湿蒸汽叶栅流动为两个过程:叶栅内流动和叶栅后穿越凝结冲波的流动.建立了透平湿蒸汽非平衡流动动态仿真模型,并进行了时间步长修正,模型可以用于蒸汽轮机的动态仿真计算.模型由两相流体质量守恒方程、动量守恒方程、能量守恒方程,过热蒸汽方程、流动压降方程、激波前后关系式及其它两相流关系式组成,考虑了叶栅几何尺寸、叶型损失等多个影响因素.仿真算例表明,稳态仿真结果满足精度要求,动态仿真结果趋势合理.     

基于伪谱方法的自适应鲁棒实时再入制导律研究

为了提高飞行器再入制导的鲁棒性和自适应性,将再入弹道跟踪问题转化为再入弹道状态调节问题,得到了一个LTV系统最优控制问题.在此基础上,利用基于伪谱算法的最优反馈控制算法,设计了一种便于在线实现的自适应鲁棒再入制导律.仿真结果表明,这种再入制导律对于再入点误差不敏感,具有良好的鲁棒陛.在气动参数模型存在较大误差的情况下,依然能够取得较高的再入制导精度.它不需要显示增益调度和积分,并且在不同情况下控制结构和参数无需改变.     

A linear benchmark for forecasting GDP growth and inflation?

Predicting the future evolution of GDP growth and inflation is a central concern in economics. Forecasts are typically produced either from economic theory‐based models or from simple linear time series models. While a time series model can provide a reasonable benchmark to evaluate the value added of economic theory relative to the pure explanatory power of the past behavior of the variable, recent developments in time series analysis suggest that more sophisticated time series models could provide more serious benchmarks for economic models. In this paper we evaluate whether these complicated time series models can outperform standard linear models for forecasting GDP growth and inflation. We consider a large variety of models and evaluation criteria, using a bootstrap algorithm to evaluate the statistical significance of our results. Our main conclusion is that in general linear time series models can hardly be beaten if they are carefully specified. However, we also identify some important cases where the adoption of a more complicated benchmark can alter the conclusions of economic analyses about the driving forces of GDP growth and inflation. Copyright © 2008 John Wiley & Sons, Ltd.     

Participatory Sustainability Impact Assessment: Scientific Policy Advice as a Social Learning Process

This paper deals with the development of scientific policy advice by providing a methodology to foster a social learning process. The methodology, called participatory Sustainability Impact Assessment (pSIA), aims to structure complex problem situations, to clarify interests and basic assumptions, to interpret scientific studies, to develop impact assessment, and to explore sensitivity of uncertainty and lack of information. In pSIA workshops the participants are supposed to build conceptual models with different modelling methods, like System Dynamics, Value Chain Analysis, and Morphological Analysis. A case study is presented that describes a workshop series with political as well as academic actors, applying the pSIA approach to an impact assessment of Economic Partnership Agreements between the European Union and the Eastern and Southern Africa Region.

六垛南闸闸下淤积现状分析

针对我国在滨海河口地区修建的挡潮闸在河口建闸后普遍存在的泥沙淤积问题,根据苏北灌溉总渠入海口六垛南闸等处的实测资料,分析该挡潮闸下潮汐引河通道冲淤特性,指出挡潮闸下引河的潮流特性、潮流挟沙特性及引河淤积的原因。认为对闸门进行科学合理的控制、有效利用上游有限的泄水量和闸下落潮水流拖淤来防淤减淤是较为简便易行且经济的措施。     

最优资金流施工进度计划的风险分析

本文以合成事件技术为基础,研究进度计划中非关键路径对于关键路的时间干扰问题,定义了安全使用时差的新概念,以便对松驰时间和资金最佳运用情况作出可靠的风险决策。     

月径流序列的多层递阶预报研究

月径流序列是一类具有周期变化的非平稳时间序列．本文根据其特点,建立了多层递阶预报模型,文中对此类非平稳时间序列的建模及预报方法进行了深入研究     

汽轮机通流部分清洗技术在6MW机组中的应用

通过对霍州煤电煤矸石热电厂2#汽轮机组推力瓦温度高原因分析,得出其主要原因为通流部分结垢严重,流通不畅,导致汽轮机做功能力下降,使机组无法带至额定负荷;并对通流部分结垢的原因进行分析、研究,作出清洗处理,有效降低了机组运行中的推力瓦温度,以提高机组的安全经济性。     

一种新的RBF神经网络非线性动态系统建模方法

将遗传算法与正交优选法结合 ,用来训练径向基函数 ( RBF)神经网络 ,并对基函数宽度进行自动地调整 ,得到了一种训练 RBF神经网络的新方法 .将其应用于连续流体搅拌反应槽 ( CFSTR)生化反应器的建模中 ,得到了令人满意的结果 .该算法提高了径向基函数神经网络的泛化能力和鲁棒性 ,研究表明是一种有效的“黑箱”动态建模方法