消能自复位摇摆框架墩结构地震反应及易损性分析

摇摆构造可限制结构的地震损伤和残余位移，从而提升结构的震后恢复能力。以消能自复位摇摆框架墩结构为研究对象，基于摇摆刚体假定，建立消能自复位摇摆框架墩结构的动力分析模型，并通过试验结果验证了该模型的有效性。模型中采用拉格朗日方程推导出结构的运动学方程，并考虑了桥墩复位碰撞所造成的速度折减以及预应力束和阻尼器的失效。以黄徐路摇摆桥梁结构为工程背景，对消能自复位摇摆框架墩结构进行实例分析、参数分析和易损性分析。实例分析和参数分析结果表明：阻尼器和预应力束的联合应用可减小结构的位移反应，阻尼器刚度的量纲一化参数（ρ_d）越大则结构减震效果越好，且在脉冲近场地震作用下的减震效果更为明显。针对阻尼器屈服、阻尼器失效、预应力束失效和结构倒塌4个极限状态的易损性分析的结果表明：在E1地震作用下，阻尼器失效、预应力束失效和结构倒塌的发生概率极小；在E2地震作用下，阻尼器极易发生屈服，阻尼器失效和预应力束失效的概率小于20%，结构倒塌的发生概率近乎为0；在脉冲近场地震作用下，ρ_d增大可降低各极限状态的发生概率，预应力束刚度的增大对各极限状态的发生概率影响较小，预应力束初始应力的增大会增加预应力束失效的发生概率。     

高疲劳抗力钢桥面板的疲劳问题Ⅱ：结构体系抗力

为了深刻认识高疲劳抗力钢桥面板的疲劳特性，准确评估其结构体系的疲劳抗力，基于等效结构应力建立了考虑焊接微裂纹对钢桥面板疲劳性能劣化效应的结构体系疲劳抗力评估方法，并通过疲劳试验对所建立的评估方法进行了验证。在此基础上采用所建立的结构体系疲劳抗力评估方法对高疲劳抗力钢桥面板的疲劳开裂模式、疲劳抗力及其影响因素等相关关键问题进行系统研究。研究结果表明：焊接微裂纹的存在会显著降低钢桥面板的疲劳性能，导致主导疲劳开裂模式发生迁移；结构体系设计参数对纵肋与顶板双面焊构造细节和纵肋与横隔板新型交叉构造细节疲劳性能的影响有显著区别，其中纵肋与顶板双面焊构造细节的疲劳性能主要对顶板厚度的变化较为敏感，其疲劳性能随着顶板厚度的增加而显著提升，而纵肋与横隔板新型交叉构造细节的疲劳性能同时受多个参数的影响，其疲劳性能随着顶板厚度、横隔板厚度和纵肋高度的增大而提升，随着横隔板间距和纵肋底板与横隔板之间焊缝长度的增大而降低；传统钢桥面板的主导疲劳开裂模式为纵肋腹板与横隔板交叉构造细节围焊焊趾开裂，高疲劳抗力钢桥面板的主导疲劳开裂模式为纵肋底板与横隔板交叉构造细节纵肋焊趾开裂；相对于传统正交异性钢桥面板，高疲劳抗力钢桥面板结构实现了主导疲劳开裂模式的迁移，疲劳性能显著提高。     

关于正交异性钢桥面板的疲劳——对英国在加固其塞文桥渡时所作研究的评介

对英国塞文桥渡正交异性板构造的疲劳裂纹产生的原因、所作试验及对其疲劳寿命计算作了介绍，并进行了探讨。     

发射内弹道计算模型研究

对以燃气-蒸汽式发射动力装置为动力源的导弹冷弹射过程进行了分析，对冷却水汽化机理进行了研究，针对不同状态的冷却水，提出了不同汽化方式组合的冷却水汽化模型，在此基础上将弹射过程划分为4个阶段，并推导出各个阶段的汽化方程和能量平衡方程，建立了发射内弹道基本方程组。计算模型改进后，发射内弹道的计算精度有很大提高。     

三维设计在船体结构中的应用

在三维空间里设计水面舰艇的船体结构是军船结构设计的发展趋势。介绍船体结构三维设计的构思;三维设计方法与传统二维设计方法的比较;目前三维设计可达到的设计深度。详细论述结构三维设计的研究内容和具体实施方法,揭示三维设计中的关键技术,最后提出舰艇船体结构三维设计的发展构想。     

基于改进型Boussinesq方程的二维波浪数值模型

基于改进型Boussinesq方程，在非交错网格下，建立了二维波浪数值模型。模型计算采用了有限差分法，时间格式上采用混合四阶Adams—Bashforth—Mouhon，空间格式上采用了Wei等（1995）给出的格式。数值计算中。采用了内部造渡技术。数值模拟针对3纽经典浅滩地形上波浪传播变形的实验进行，数值计算结果与实验结果吻合较好。验证了数值模型，该模型可期望用于实际港口渡浪预报。     

A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part II: Numerical simulations

This paper presents a global ocean implementation of a multi-component model of marine pelagic biogeochemistry coupled on-line with an ocean general circulation model forced with climatological surface fields (PELAgic biogeochemistry for Global Ocean Simulations, PELAGOS). The final objective is the inclusion of this model as a component in an Earth System model for climate studies. The pelagic model is based on a functional stoichiometric representation of marine biogeochemical cycles and allows simulating the dynamics of C, N, P, Si, O and Fe taking into account the variation of their elemental ratios in the functional groups. The model also includes a parameterization of variable chlorophyll/carbon ratio in phytoplankton, carrying chl as a prognostic variable. The first part of the paper analyzes the contribution of non-local advective–diffusive terms and local vertical processes to the simulated chl distributions. The comparison of the three experiments shows that the mean chl distribution at higher latitudes is largely determined by mixing processes, while vertical advection controls the distribution in the equatorial upwelling regions. Horizontal advective and diffusive processes are necessary mechanisms for the shape of chl distribution in the sub-tropical Pacific. In the second part, the results have been compared with existing datasets of satellite-derived chlorophyll, surface nutrients, estimates of phytoplankton community composition and primary production data. The agreement is reasonable both in terms of the spatial distribution of annual means and of the seasonal variability in different dynamical oceanographic regions. Results indicate that some of the model biases in chl and surface nutrients distributions can be related to deficiencies in the simulation of physical processes such as advection and mixing. Other discrepancies are attributed to inadequate parameterizations of phytoplankton functional groups. The model has skill in reproducing the overall distribution of large and small phytoplankton but tends to underestimate diatoms in the northern higher latitudes and overestimate nanophytoplankton with respect to picoautotrophs in oligotrophic regions. The performance of the model is discussed in the context of its use in climate studies and an approach for improving the parameterization of functional groups in deterministic models is outlined.     

货车组合式制动梁梁体的优化设计

依据货车组合式制动梁在车辆上出现的失效方式,以L-C组合式制动梁为例,提出等寿命原则作为制动梁梁体的最优设计控制律的方案,得出撑杆端头处的过载荷是制动梁失效的主要因素。提出利用前、后段的拉压应变以及降低撑杆刚度来改善制动梁体的受力分布,并提出了通过调整支柱的长度来合理地提高制动梁体在非工作状态时的预应力,借以改善制动梁各部件在工作状态时的交变疲劳应力对梁体各部件的受力状况,进而提高货车组合式制动梁整体的使用寿命。文中给出了整定梁体各部件关键尺寸的计算步骤和设计方法。     

A macroscopic theory of two-lane rural roads

A macroscopic theory for predicting the operation on two-lane, two-way roads is proposed. In this theory, the interaction between fast and slow vehicles obeys Newell’s kinematic wave theory of moving bottlenecks. Calibration is not required as all parameters are fully observable. Closed-form expressions for the capacity, average speed, percent time spent following and overtaking rates are proposed and the biases of current practice are identified. Comparisons between the proposed theory and empirical data are also included.     

Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models

Marine ecosystem models are becoming increasingly complex and sophisticated, and are being used to estimate the effects of future changes in the earth system with a view to informing important policy decisions. Despite their potential importance, far too little attention has been, and is generally, paid to model errors and the extent to which model outputs actually relate to real-world processes. With the increasing complexity of the models themselves comes an increasing complexity among model results. If we are to develop useful modelling tools for the marine environment we need to be able to understand and quantify the uncertainties inherent in the simulations. Analysing errors within highly multivariate model outputs, and relating them to even more complex and multivariate observational data, are not trivial tasks. Here we describe the application of a series of techniques, including a 2-stage self-organising map (SOM), non-parametric multivariate analysis, and error statistics, to a complex spatio-temporal model run for the period 1988–1989 in the Southern North Sea, coinciding with the North Sea Project which collected a wealth of observational data. We use model output, large spatio-temporally resolved data sets and a combination of methodologies (SOM, MDS, uncertainty metrics) to simplify the problem and to provide tractable information on model performance. The use of a SOM as a clustering tool allows us to simplify the dimensions of the problem while the use of MDS on independent data grouped according to the SOM classification allows us to validate the SOM. The combination of classification and uncertainty metrics allows us to pinpoint the variables and associated processes which require attention in each region. We recommend the use of this combination of techniques for simplifying complex comparisons of model outputs with real data, and analysis of error distributions.