结构参数对缠绕管式换热器传热性能的影响研究

缠绕管式换热器作为一种新型高效的换热器,具有传热系数高,结构紧凑,且能够同时适用于多种流体进行换热的特点。本文开发了一款能够用于设计计算缠绕管式换热器的工业软件,并经过了大量工程项目的验证;同时研究了换热器的螺旋倾角θ、缠绕管外径D、径向间隙Pd、轴向间隙Pl、中芯筒直径DZ与缠绕管层数CS对换热器传热性能、壳程压降ΔPS与管程压降ΔPT的影响。结果表明,随着θ、D、Pd、DZ与CS的增加以及Pl的减小,换热器的传热性能逐渐降低;在这些结构参数中,对传热性能影响最大的是θ,最小的是Pl;在改变结构参数增大换热器传热性能的同时,往往会导致ΔPS与ΔPT增加。因此,在工程实际项目中进行换热器的设计计算时,需要综合考虑传热性能与压降,最终设计出ΔPS与ΔPT在允许范围内具有更大传热性能的缠绕管式换热器。     

基于实测频率振型的大跨斜拉桥响应面模型修正研究

为了验证基于实测频率和振型的响应面模型修正方法的准确性与可行性,以某大跨斜拉桥为工程背景,分别进行静载试验和环境激励下的模态测试。以竖向前4阶实测频率及振型作为状态变量,选取合理的修正参数,进行中心复合试验设计;采用考虑交互项的响应面模型进行数据拟合,并计算参数R²值的范围,进行精度检验;分析频率及振型的改变率,将修正后模型的挠度与实测挠度进行对比,验证该模型修正的准确性。结果表明：在参数范围内,各响应面模型的R²值均接近于1,拟合精度较高;修正后模型的频率与振型均接近实测值,能准确反映桥梁的动力特性;修正后模型的挠度计算值与实测值最大误差不超过7.98%,满足工程精度要求,能够真实反映大跨斜拉桥的工作状态。研究证明了基于实测频率与振型的响应面模型修正方法对大跨斜拉桥的适用性和可行性,可为实际工程中类似桥梁的模型修正提供参考。     

Excel在指数平滑法参数优选中的应用

指数平滑法在预测中被广泛应用,该方法最重要、而且最困难的是确定平滑系数的取值。利用Excel能很方便地实现最优平滑系数的选择。     

集约化变量与集约用地量度--节约集约用地基本理论系列之五

通过剖析200多年来报酬递减规律的发展过程,发现集约化现象才是人类社会发展最基本现象,并通过构建集约化变量、集约化模型、集约化曲线、集约化参数以及集约化变量应用等提出了集约化变量理论。集约化变量是人类活动使自然资源价值、效益或承载增加的变量,用单位自然资源量的价值、效益或承载表示。集约化是连续增函数,报酬递减是这个增函数中的状态函数。可持续发展的核心是集约化发展。     

Modeling and Forecasting the Sales of Technology Products

Managers in technology product markets require sales response models that provide substantive insights into the effects of marketing activities as well as reliable sales forecasts. Such markets are characterized by frequent introductions and withdrawals of multiple models by different companies. Thus, the data available on the performance of any individual model is scarce. A second characteristic is that the effects of product attributes and marketing activities could change over time as different types of consumers participate in the market at different points in time. Given sparse data, it becomes critical to specify a model that allows pooling of information across brand-models while at the same time providing brand-model specific parameters. We accomplish this via a hierarchical Bayesian model specification. Further, to capture the effects of changing consumer preferences over time, we specify a time varying parameter model. Our modeling framework therefore, integrates a hierarchical Bayesian model within a time varying parameter framework to develop a dynamic hierarchical Bayesian model. We employ data on digital cameras in the U.S. market to estimate the parameters of our proposed model. We use thirty-three months of national level data on the digital camera market with the data series beginning very close to the inception of this product category. We find that while there is little variation in reliance of benefits by early adopters, the second wave of adopters focus on Ease of Use followed by later adopters who rely on Storage and Image Quality. Looking at the elasticities of demand with respect to the various benefits, we find that at around the halfway point of our data series, the industry as a whole would have been better off investing in increasing image quality rather than storage if costs associated with the two are equal. However, at the end of the time horizon both benefits appear to have about equal impact. Further, the relative benefits of improving these attributes vary across brands and points in time. We then generate single period and multiple period ahead sales forecasts. We make different assumptions about information availability and find that the average (across brand-models and time) MAPE ranges from 7.5 to 14.5% for the model. We provide extensive comparisons of our model with 4 potential alternatives and find that our model outperforms these alternatives on the nature of substantive insights obtained as well as in forecasting out-of-sample especially when there is a very short time window of data.     

基于时变混合 Copula 模型的配对交易策略

由于金融时间序列数据通常具有动态时变、非对称和非线性相关特征,本文给出了一类权重系数和Copula参数均时变的混合Copula模型。同时基于权重系数和Copu－la参数时变的混合Copula模型,刻画不同频率互联网金融概念股价格序列之间的相关性,构建配对交易策略模型,并与静态混合Copula模型下的策略结果进行比较。实证分析表明：基于时变混合Copula模型的配对交易策略可以获得较高收益; Copula 参数和权重系数均时变的混合Copula模型能捕获更多交易机会,策略表现最好;含有较多成分Copula的混合模型在配对交易策略中并不具有优势;高频率金融市场比相应低频率金融市场的策略盈利更高。