砂砾石地基上水闸闸墩下局部灌浆效果及合理范围分析

水闸通常需要进行地基处理,以降低差异沉降和底板应力。根据水闸荷载集中在闸墩上的特点,提出了一种在闸墩下的砂砾石地基局部灌浆的处理方式。结合工程实例,通过有限元软件ABAQUS计算和比较地基局部灌浆前后闸底板的应力,该地基处理方式降低了底板应力。比较不同灌浆范围时闸底板的最大拉应力,发现当地基局部灌浆区域总宽度与闸室宽度的比值约为35%时,闸底板最大拉应力的降幅效果最好。     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.     

A practical reliability assessment approach and its application for pile-stabilized slopes using FORM and support vector machine

Bulletin of Engineering Geology and the Environment - Many uncertainties exist in pile-stabilized slopes which make their design substantially complicated. In this paper, a first-order reliability...     

Toxic response of aquatic organisms to guide application of artemisinin sustained-release granule algaecide

In our previous study, we prepared the granules by embedding artemisinin into alginate-chitosan using microcapsule technology. Thesgranules can release artemisinin sustainably and have a strong inhibitory effect on the growth of both single Microcystis aeruginosa and mixealgae. To safely and effectively use artemisinin sustained-release granules to control algal blooms, the ecotoxicity was studied by assessing theacute and chronic toxicity to Daphnia magna(D. magna) and Danio rerio(D. rerio), along with their antioxidant activities. The results showethat the 48-h median effective concentration(EC50) of pure artemisinin to D. magna was 24.54 mg/L and the 96-h median lethal concentratio(LC50) of pure artemisinin to D. rerio was 68.08 mg/L. Both values were classified as intermediate toxicity according to the Organization foEconomic Co-operation and Development(OECD). The optimal algae inhibitory concentration of artemisinin sustained-release granules(1 g/Lhad low acute toxicity to both D. magna and D. rerio. The sustained-release granules had higher chronic toxicity to D. magna than to D. reriPartial indices of D. magna were inhibited by granules when the concentrations were larger than 0.1 g/L. Low granule concentration had ainductive effect on antioxidant enzyme activities in D. magna and D. rerio. With the increase of the exposure concentration and time, the enzymactivity presented a trend of first increasing and then decreasing, and the overall changes were significant. The change trend and range of enzymactivity indicated that the granules could cause serious oxidative stress to D. magna and D. rerio, and the changes were consistent with the resultof toxicity experimentation.     

Influences of flow rate and baffle spacing on hydraulic characteristics of a novel baffle dropshaft

Due to limited flow capacity and the instability of the asymmetric structure of traditional baffle dropshafts, a novel baffle dropshaft with a symmetric structure, adopting the construction shield well directly, is proposed for large-range flow discharge in deep tunnel drainage systems. In this study, a two-phase flow field of the novel baffle dropshaft with three different baffle spacings was simulated at seven different flow rates with a three-dimensional (3D) numerical model verified with experiments, to study hydraulic characteristics of this novel baffle dropshaft. The results show that the novel baffle dropshaft has a remarkable energy dissipation effect. Baffle spacing of the novel baffle dropshaft has a greater effect on flow patterns and baffle pressure distributions than the comprehensive energy dissipation rate. Flow rate is a critical issue for the selection of baffle spacing in the design. Some guidance on baffle spacing selection and structure optimization for the application of this novel baffle dropshaft in deep tunnel drainage systems is proposed.     

基于FBS模型的儿童电动牙刷知识库设计研究

目的有效地将模糊的用户需求转变为明确的设计要求。方法以儿童电动牙刷为研究对象,以需求的认知、获取和表达—需求的转化—需求的呈现为研究思路,结合感性工学方法和FBS模型理论,研究基于FBS模型的感性工学应用方法模型。结果搭建了感性词汇和FBS模型单元基之间的有效映射,实现了从用户需求到设计要求之间的转化,产出了儿童电动牙刷的产品信息知识库。结论经过研究所搭建的儿童电动牙刷产品小型知识库完成了用户需求的呈现,一方面,用户通过搜索可以匹配到最符合自己需求的产品,另一方面,设计师既可以在知识库产品的基础上进行创新设计,又可以通过知识库检索大数据,掌握用户需求的变化趋势和方向,把握设计方向,避免重复工作,提高设计效率。     

变化环境下由设计暴雨推求设计洪水方法研究

为推求变化环境下的设计洪水,以黄河上游唐乃亥站以上流域1967~2006年的年最大15d降雨量系列为例,基于设计暴雨与SWAT模型相结合的方法,首先构建变参数概率分布函数模型描述变化环境下非一致性暴雨极值系列的分布规律,随后基于等可靠度方法推求给定重现期条件下的设计暴雨值,再结合SWAT水文模型推求设计洪水。结果表明,变化环境下唐乃亥站以上流域各设计频率(P=10%、5%、2%、1%)的设计暴雨值随工程设计寿命(20、30、50、80、100年)的增大而减小,百年一遇设计洪峰从3 292m^3/s降至3 023m^3/s,洪量从29.9×10^8 m^3降至27.4×10^8 m^3。实例应用验证了该方法的可行性,可为变化环境下的设计洪水计算提供参考。     

桩土复合路基静载试验改进方法研究

静载试验作为复合路基的一种重要检测手段而广泛应用,然而,在工程质量检测中,常出现检测结果与实际情况不符的情况,除人为操作因素外,垫层模拟过于简单是主要原因。借助引入弹性垫层,提出一种桩土复合路基静载试验改进方法。首先,基于数值模拟计算,建立复合路基桩土应力比n和桩土相对位移Δs、弹性垫层厚度h和弹性垫层模量E的函数关系;其次,通过模拟结果和路堤荷载结果对比,确定不同桩型复合路基静载试验中弹性垫层参数选择范围,最后,利用现场对比试验和实测结果,论证桩土复合路基静载试验改进方法的正确性和可靠性。     

Energy and exergy performance assessments of a high temperature-proton exchange membrane fuel cell based integrated cogeneration system

High-temperature proton exchange membrane fuel cell (HT-PEMFC), which operates between 160 °C and 200 °C, is considered to be a promising technology, especially for cogeneration applications. In this study, a mathematical model of a natural gas fed integrated energy system based on HT-PEMFC is first developed using the principles of electrochemistry and thermodynamics (including energy and exergy analyses). The effects of some key operating parameters (e.g., steam-to-carbon ratio, HT-PEMFC operating temperature, and anode stoichiometric ratio) on the system performance (electrical, cogeneration, and exergetic efficiencies) are examined. The exergy destruction rates of each component in the integrated system are found for different values of these parameters. The results show that the most influential parameter which affects the performance of the integrated system is the anode stoichiometric ratio. For the baseline conditions, when the anode stoichiometric ratio increases from 1.2 to 2, the electrical, cogeneration, and exergetic efficiencies decrease by 42.04%, 33.15%, and 37.39%, respectively. The highest electrical power output of the system is obtained when the SCR, operating temperature, and anode stoichiometric ratio are taken as 2, 160 °C, and 1.2, respectively. For this case, the electrical, cogeneration, and exergetic efficiencies are found as 26.20%, 70.34%, and 26.74%, respectively.     

Efficient Identification of water conveyance tunnels siltation based on ensemble deep learning

The inspection of water conveyance tunnels plays an important role in water diversion projects. Siltation is an essential factor threatening the safety of water conveyance tunnels. Accurate and efficient identification of such siltation can reduce risks and enhance safety and reliability of these projects. The remotely operated vehicle (ROV) can detect such siltation. However, it needs to improve its intelligent recognition of image data it obtains. This paper introduces the idea of ensemble deep learning. Based on the VGG16 network, a compact convolutional neural network (CNN) is designed as a primary learner, called Silt-net, which is used to identify the siltation images. At the same time, the fully-connected network is applied as the meta-learner, and stacking ensemble learning is combined with the outputs of the primary classifiers to obtain satisfactory classification results. Finally, several evaluation metrics are used to measure the performance of the proposed method. The experimental results on the siltation dataset show that the classification accuracy of the proposed method reaches 97.2%, which is far better than the accuracy of other classifiers. Furthermore, the proposed method can weigh the accuracy and model complexity on a platform with limited computing resources.