利用ADCP回波强度估算河流悬移质含沙量的应用研究

通过简要介绍利用声学多普勒水流剖面仪(ADCP)回波强度估算悬移质含沙量的基本原理,结合梧州水文站的应用实例,利用ADCP的回波强度数据和现场采集的水样含沙量建立相关关系,根据相关关系由回波强度反演估算的水体悬移质含沙量验证了利用ADCP的回波强度估算悬移质含沙量的可行性。应用于梧州水文站的实践表明,左河道推算的系统误差为-0.1%,右河道推算的系统误差为1.5%。这种方法具有不扰动流场、测量剖面同步性较好、数据空间分辨率较高的优点,与传统的取样过滤称量法相比,计算效率显著提高。     

汽轮发电机组负荷波动的原因分析及解决措施

详细分析了汽轮发电机组在运行过程中出现电负荷波动和瞬间突降的原因，重点介绍了如何调节、维持汽轮发电机组的经济运行以及解决电负荷波动的措施，从而保证汽轮发电机组的稳定运行。     

活性污泥法处理污水两个重要参数的理论探讨

负荷、泥龄是活性污泥法处理城市污水设计、运行中的重要参数.给出了有机负荷的动力学表达形式(称之为动力学负荷),并对有机负荷和泥龄的关系,有机负荷和泥龄对水质、污泥沉降性能影响进行了理论探讨.     

机动车制动液的研制

介绍了合成型机动车制动液的生产和配方，讨论了物料组成对产品的影响。     

Dynamic equivalent method of interconnected power systems with consideration of motor loads

The existing equivalent methods usually only deal with static load models and neglect the dynamic characteristics of loads such as induction motors.This paper presents a dynamic equivalent method which considers motor dynamics.At first,the clustering criterion of motor loads is given.The motors with similar dynamic characteristics are classified into one group.Then,reduction of motors in the same group is carried out.Finally,parameters of the equivalent motor are calculated and the equivalent system is thus...     

Optimizing storage performance in public cloud platforms

Cloud computing is an elastic computing model where users can lease computing and storage resources on demand from a remote infrastructure.It is gaining popularity due to its low cost,high reliability,...     

大内跨小边跨框架结构预应力筋优化布置方法

预应力筋的优化布置是大内跨小边跨的多跨预应力混凝土框架结构合理设计计算的关键.为满足控制截面承载力最大的需要,以往常将大跨所需预应力筋布置为连续曲线,并按水平直线延伸通过其相邻的两小跨,按这种布置方式仅使大跨内产生竖向向上的预应力等效荷载,可较好平衡大跨的竖向外荷载;而若将大跨及相邻的两小跨统一考虑,预应力筋按连续曲线布置,张拉产生的预应力等效荷载不但可有效平衡大跨的竖向外荷载而且也可平衡小跨的竖向外荷载,可以使荷载平衡得到优化实现.以一典型工程为例,分析了在相同条件下两种预应力筋布置过程中张拉引起的综合弯矩、主弯矩和次弯矩的分布和量值上差异,比较了两类布筋形式对正截面承载力计算结果的影响,验证了对大内跨小边跨框架结构统一考虑后整体上按三段连续正反抛物线预应力筋布置的合理性.     

Limit load and shakedown analysis of plastic structures under stochastic uncertainty

Problems from plastic analysis are based on the convex, linear or linearised yield/strength condition and the linear equilibrium equation for the stress (state) vector. In practice one has to take into account stochastic variations of several model parameters. Hence, in order to get robust maximum load factors, the structural analysis problem with random parameters must be replaced by an appropriate deterministic substitute problem. A direct approach is proposed based on the primary costs for missing carrying capacity and the recourse costs (e.g. costs for repair, compensation for weakness within the structure, damage, failure, etc.). Based on the mechanical survival conditions of plasticity theory, a quadratic error/loss criterion is developed. The minimum recourse costs can be determined then by solving an optimisation problem having a quadratic objective function and linear constraints. For each vector a(·) of model parameters and each design vector x, one obtains then an explicit representation of the “best” internal load distribution F^∗. Moreover, also the expected recourse costs can be determined explicitly. Consequently, an explicit stochastic nonlinear program results for finding a robust maximal load factor μ^∗. The analytical properties and possible solution procedures are discussed.     

Reliability analysis on systems with self-healing and self-repairing under different environments and shock models

Inspired by the process of self-healing of biological damage, high technology materials with self-healing and self-repairing mechanisms have been developed for high reliability and long lifetime. Therefore, the reliability modeling on intelligent systems with healing performance has become a research hotspot. Based on the diversity of healing mechanisms, this paper proposes a two-phase reliability model method on self-healing and self-repairing systems. Impacts of environments, shock loads, self-healing, and self-repairing mechanisms are taken into account in this novel model. Besides, system lifetime and some reliability indexes under two shock models are derived, respectively. Moreover, Monte Carlo simulations are conducted to verify the accuracy of reliability under two models. Finally, an engineering case of metallized film capacitor is provided to illustrate the effectiveness and applicability of the proposed models by comparing numerical results and simulation results.     

Models to predict the deformation modulus and the coefficient of subgrade reaction for earth filling structures

Determination of deformation modulus and coefficient of subgrade reaction of soils have major importance, whether the projects are in design, and construction or compaction assessment stage of earth filling structures. Plate load test is one of the frequently used method to directly determine the parameters but the method is both costly and time consuming. For this reason, this paper is concerned with the applications of artificial neural networks (ANN) and simple-multiple regression analysis to predict deformation modulus and coefficient of subgrade reaction of compacted soils from compaction parameters (such as maximum dry density (MDD) and optimum moisture content (OMC), field dry density (FDD), and field moisture content (FMC)). Regression analysis and artificial neural network estimation indicated that there are acceptable correlations between deformation modulus and coefficient of subgrade reaction and these parameters. Artificial neural networks model exhibits higher performance than traditional statistical model for predicting deformation modulus and coefficient of subgrade reaction.