仙游抽水蓄能电站尾水系统充排水试验

为检查工程质量,查找输水系统可能存在的问题并消除隐患,保障电站安全运行,福建仙游抽水蓄能电站在投产发电前,要对输水发电系统进行充水试验与放空排水试验,在试验过程中监测输水系统的应力、应变与渗漏水情况。本文以尾水系统为例,介绍了试验所应具备的工程条件、工作程序及技术要求、试验成果分析和存在问题处理等。试验表明,仙游抽水蓄能电站尾水系统设计合理,施工质量优良,结构可靠,可供同类工程参考与借鉴。     

Carbon nanotube filter for heavy metal ion adsorption

This study investigated carbon nanotube filtration technology using catalyst particles supported on silicalite-1–biomorphic carbon materials (BCMs). Aqueous solutions of Mn(II), Cu(II), Cr(III), Cd(II), and Pb(II) were used to test the efficiency of heavy metal ions removal. Carbon nanotubes (CNTs) were synthesized and grown on BCMs by the chemical vapor deposition method catalyzed with the catalyst (Co, Fe, and Ni). The synthesized CNTs with Co– and Fe– nanoparticles were typically multi-walled carbon nanotubes, and they showed good crystallinity (I_D/I_G = 1.05) and yield of (11.10 and 8.86) %. The removal efficiency of Mn(II), Cu(II), Cr(III), Cd(II), and Pb(II) ions using Co-catalyzed CNT filter was 97.57%, 98.01%, 97.89%, 97.42%, and 99.99%, respectively.     

高温氢工质热物理性质计算分析

氢工质在新能源与动力、航天推进、化工材料等领域有着广泛应用。通过开展高温氢工质热力学与输运性质研究，建立了原子态氢、分子态氢、热解平衡态氢的热物理性质计算模型，开发了热物性计算程序Prop_H_H2，适用范围为温度100~3 500 K、压力104~5×107 Pa 。验证表明，Prop_H_H2在适用范围内计算氢工质的物性参数合理可靠，在温度200~3 000 K、压力104~107 Pa范围内，程序预测值更加准确，相对偏差在±5%左右。本研究可为氢工质相关的航天推进、应用物理学、能源动力等行业的科研和应用提供支持借鉴。     

高瓦斯突出矿井底抽巷一巷多用技术研究与实践

胡底煤业为高瓦斯高突出高矿压的三高矿井。对高瓦斯高突出的治理，该矿采用“地面网络预抽、区域模块降量、底抽穿层保掘、高位顺层保采”的四级模式，施工底抽巷，实现“底抽穿层消突、区域模块降量、异巷探测增效、多巷通风治患、循环排矸减压”等“一巷多用”。该4种方法已在1303（上）、1305（上）工作面应用并推广，取得了良好的效果，大大提高了掘进效率且满足抽放、探放水、通风需要；回填矸石初步设计现已经完善，待下一步掘进将实现填矸作用。     

脉冲电沉积镍-铜合金

采用脉冲电沉积技术在304不锈钢表面制备Ni-Cu合金镀层,镀液组成和工艺条件为:NiSO4ꞏ6H2O 200g/L,CuSO4ꞏ5H2O 10 g/L,十二烷基硫酸钠0.2 g/L,柠檬酸钠80 g/L,糖精0.2 g/L,pH 4.0,温度25°C,搅拌速率30 r/min,平均电流密度40~120 mA/cm2,脉冲频率0~100 Hz,占空比20%~90%,时间30 min。研究了平均电流密度、脉冲频率和占空比对Ni-Cu合金镀层的元素组成、表面形貌和显微硬度的影响,得到较优的工艺参数为:平均电流密度40 mA/cm2,脉冲频率50 Hz,占空比60%。该条件下所得Ni-Cu合金镀层由质量分数分别为56.53%和43.47%的Ni和Cu组成,呈“菜花”状形貌,结晶细致、均匀,显微硬度为614.4 HV。     

Behavior of 316L stainless steel containing corrosion pits under cyclic loading

The environmental performance of 316L grade stainless steel, in the form of tensile specimens containing a single corrosion pit with various aspect ratios, under cyclic loading in aerated chloride solutions is investigated in this study. Results from environmental tests were compared and contrasted with those obtained using finite element analysis (FEA). Fractography of the failed specimens obtained from experiments revealed that fatigue crack initiation took place at the base of the shallow pit. The crack initiation shifted towards the shoulder and the mouth of the pit for pits of increasing depth. This process is well predicted by FEA, as the strain contour maps show that strain is the highest around the centric strip of the pit. However, for shallow pits, local strain is uniformly distributed around that strip but begins to concentrate more towards the shoulder and the mouth region for increasingly deep pits.     

Hot corrosion Type II of FeCr‐based model alloys for boiler and heat exchanger applications

The hot corrosion Type II of the alloys FeCr20, FeCr20Ni10, FeCr20Ni20, and FeCr20Co10 is investigated at 700°C in air + 0.5% SO₂ with deposits consisting of Na₂SO₄ and a eutectic mixture of Na₂SO₄ and MgSO₄ for 24, 100, and 300 h. The alloying elements nickel and cobalt have a positive influence when tests are conducted using a MgSO₄‐Na₂SO₄ deposit. In this case, they reduce the metal loss and increase the time to the propagation stage. In contrast, when the alloys are exposed with a Na₂SO₄ deposit, these alloying elements increase the metal loss and allow for the transition to the propagation stage because they can form molten phases with the Na₂SO₄. During the incubation stage an oxide scale forms on the FeCr20 alloy, which is thicker than the one formed during exposure without a deposit, and iron oxides are observed, which precipitate in the deposit. The propagation stage occurs by a dissolution and precipitation mechanism forming localized pitting attack. Iron is the main species that dissolves and precipitates, while chromium remains mainly as an oxide beneath the initial surface. The additional elements are found in the pit and in the salt deposit.     

Sensor network design based on system-wide reliability criteria. Part I: Objectives

Reliability based criteria are quite popular for optimal sensor network design. We present a modified definition of system reliability for sensor network design for two applications: reliable estimation of variables in a steady state linear flow process, and reliable fault detection and diagnosis for any process. Unlike the weakest-link based definition of system reliability in the literature, the proposed definition considers the entire system and is consistent with the reliability concept used in classical reliability literature. For each application, dual approaches for defining system reliability are proposed, and their analogy with the reliability problem in the classical reliability literature is established. Using examples and stochastic simulations, the advantage of using the proposed system reliability in contrast to the existing definition is illustrated. Part II of this series of articles presents methods for efficient generation of the system reliability function and its use in optimization-based approaches for designing optimal sensor networks.     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.