考虑地震持时的钢筋混凝土构件损伤性能指标研究

基于9个RC构件在不同变幅历程下的往复加载试验,研究根据刚度损伤指数对不同变幅历程下的损伤过程给出性能划分标准的可能性,并探讨地震持时、峰值位移、配筋量对RC构件损伤发展的影响。研究发现,刚度损伤指数能够对不同变幅历程下的损伤过程给出统一的性能划分标准,提出了对应于5个性能状态（无损、轻度损伤、中度损伤、重度损伤和破坏）的刚度损伤指数区间,并采用PEER数据库中的9个矩形受弯破坏试件对该标准进行了验证;通过将刚度损伤指数与峰值变形指标、Park-Ang损伤指数进行对比,发现刚度损伤指数与峰值变形指标在界定RC构件的轻度损伤时具有较好的一致性,刚度损伤指数与Park-Ang损伤指数在界定RC构件的中、重度损伤时,两者具有较好的一致性;基于算例分析,讨论了刚度损伤指数与配箍率、强震持时、延性系数的相互关系。     

Variability of waste copper slag concrete and its effect on the seismic safety of reinforced concrete building: A case study

Proven research output on the behavior of structures made of waste copper slag concrete can improve its utilization in the construction industry and thereby help to develop a sustainable built environment. Although numerous studies on waste copper slag concrete can be found in the published literature, no research has focused on the structural application of this type of concrete. In particular, the variability in the strength properties of waste copper slag concrete, which is required for various structural applications, such as limit state design formulation, reliability-based structural analysis, etc., has so far not attracted the attention of researchers. This paper quantifies the uncertainty associated with the compressive-, flexural- and split tensile strength of hardened concrete with different dosages of waste copper slag as fine aggregate. Best-fit probability distribution models are proposed based on statistical analyses of strength data generated from laboratory experiments. In addition, the paper presents a reliability-based seismic risk assessment of a typical waste copper slag incorporated reinforced concrete framed building, considering the proposed distribution model. The results show that waste copper slag can be safely used for seismic resistant structures as it results in an identical probability of failure and dispersion in the drift demand when compared with a conventional concrete building made of natural sand.     

煤与瓦斯突出区域性预测的综合判据研究

为了准确、快速地预测煤与瓦斯突出,以焦作中马村矿为实施矿井,采用瓦斯地质理论全面分析了影响瓦斯突出的地质条件,利用数量化理论Ⅲ筛选了瓦斯突出的敏感指标,应用数量化理论Ⅱ建立了煤与瓦斯突出区域性预测的综合判据,选用二维判别方法对中马村矿二l煤层未采区进行了预测,预测结果为突出危险区23个,突出威胁区41个,非突出区106个,与实际突出结果吻合．表明采用瓦斯地质理论和数量化理论相结合的方法预测煤与瓦斯突出是可行的．煤与瓦斯突出区域性预测综合判据的建立使突出预测规范化,有望推广应用．     

厚截面碳纤维复合材料远表面微缺陷超声检测

为了识别厚截面碳纤维复合材料(CFRP)远表面的微缺陷,使用递归分析方法对超声检测信号进行分析。首先在厚截面CFRP材料上打孔以模拟微缺陷,采用水浸超声脉冲反射法对不同大小的模拟缺陷进行检测。然后选取缺陷位置附近信号段,确定嵌入维数m、延迟时间τ、阈值ε等参数,对各信号段进行递归分析,得到递归图及递归定量分析结果。比较无缺陷信号和有缺陷信号的递归图,从宏观上定性确定微缺陷对超声信号的影响;比较无缺陷信号和有缺陷信号的递归定量分析结果,根据每个递归定量参数的物理意义,对缺陷产生的影响作出合理的解释。最后,使用不同中心频率探头进行实验,确定合适的探头参数。分析结果表明,使用7.5MHz高分辨率超声探头时检测效果最好;当嵌入维数为7、延迟时间为2、阈值为2时,递归图中出现异常白色区域、递归点增多且对角线结构变长,同时所选取的递归定量参数随缺陷增大而上升,表明厚截面CFRP远表面超声信号可能存在混沌结构,而微缺陷的存在会改变原有信号结构。所研究内容为实际微缺陷的定量识别及分类打下基础。     

协同商务环境中的主观信任模型研究

针对开放网络环境中协同商务的动态、多域、异构等特点,提出了适用于开放式协作环境的基于云模型的主观信任评价方法,给出了基于云模型的信任更新算法.通过源实体与恶意推荐实体交互的仿真实验证明,应用该算法不仅可以有效抑制恶意实体的推荐行为,还可以激发实体的积极推荐.     

海绵城市建设雨水基础设施优化配置研究进展

气候变化和快速城市化改变了城市生态水文循环过程,加剧了水资源短缺、水环境污染、水生态破坏、暴雨洪涝灾害等城市问题.为获取低影响开发措施(low impact development,LID)/绿色基础设施(green infrastructure,GI)与城市灰色基础设施耦合系统空间优化配置方案以及多目标成本-效益最优...     

电力市场与电力系统交互动态仿真设计

分析了电力交易市场、投资市场与电力系统的功能关系及其数学描述。借鉴实验经济学方法，将电力市场中能用数学模型表达的环节表达为数学模型，而将参与者的主观行为、市场规则、市场监管行为作为数学模型的输入，在实验环境中动态地交互。定义失稳风险，将输电动态阻塞对交易的物理制约转化为经济上各交易应承担的输电风险。在此基础上，建立电力市场动态过程的仿真器平台，实现电力市场与电力系统动态仿真，并采用市场调节的预交易阻塞管理模式实现电力系统技术问题与电力市场经济问题的协调。     

Towards optimal allocation of computer resources: Trade-offs between uncertainty quantification,discretization and model reduction

The computational complexity of numerical models can be broken down into contributions ranging from spatial, temporal and stochastic resolution, e.g., spatial grid resolution, time step size and number of repeated simulations dedicated to quantify uncertainty. Controlling these resolutions allows keeping the computational cost at a tractable level whilst still aiming at accurate and robust predictions. The objective of this work is to introduce a framework that optimally allocates the available computational resources in order to achieve highest accuracy associated with a given prediction goal. Our analysis is based on the idea to jointly consider the discretization errors and computational costs of all individual model dimensions (physical space, time, parameter space). This yields a cost-to-error surface which serves to aid modelers in finding an optimal allocation of the computational resources (ORA). As a pragmatic way to proceed, we propose running small cost-efficient pre-investigations in order to estimate the joint cost-to-error surface, then fit underlying complexity and error models, decide upon a computational design for the full simulation, and finally to perform the designed simulation at near-optimal costs-to-accuracy ratio. We illustrate our approach with three examples from subsurface hydrogeology and show that the computational costs can be substantially reduced when allocating computational resources wisely and in a situation-specific and task-specific manner. We conclude that the ORA depends on a multitude of parameters, assumptions and problem-specific features and, hence, ORA needs to be determined carefully prior to each investigation.     

Visualization and quantification of water movement in porous cement-based materials by real time thermal neutron radiography:Theoretical analysis and experimental study

Water movement in porous cement-based materials is of great importance when studying their deterioration processes and durability.Many traditional methods based on mass changes,electricity or nuclear magnetic resonances are available for studying water transport in cement-based materials.In this research,an advanced technique i.e.thermal neutron radiography was utilized to achieve visualization and quantification of time dependent water movement including water penetration and moisture vapor in porous cemen...     

Inverse identification of the release location,temporal rates,and sensor alarming time of an airborne pollutant source

With an accidental release of an airborne pollutant, it is always critical to know where, when, and how the pollutant has been released. Then, emergency measures can be scientifically advised to prevent any possible harm. This investigation proposes an inverse model to identify the release location, the temporal rate profile, and the sensor alarming time from the start of a pollutant release. The first step is to implement the inverse operation to the cause–effect matrix to obtain the release rate profiles for discrete candidate scenarios with concentration information provided by one sensor. The second step is to interpret the occurrence probability of each solution in the first step with the Bayesian model by matching the concentration at the other sensor. The proposed model was applied to identify a single pollutant source in a two‐dimensional enclosure using measurement data and in a three‐dimensional aircraft cabin with simulated data. The results show that the model is able to correctly determine the pollutant source location, the temporal rate profile, and the sensor alarming time. The known conditions for input into the inverse model include a steady flow field and the valid temporal concentrations at two different locations.