Optical design of the Lyman alpha based beam emission spectroscopy(LAB)diagnostic on the HL-2A tokamak

In this article, we present the optical design of a novel diagnostic on the HL-2 A tokamak, i.e. the20-channel edge Lyman-alpha beam emission spectroscopy, which is a promising solution for edge density turbulence research on tokamaks, as it offers the possibility of density fluctuation measurement with a 3.3 mm spatial resolution while maintains a high temporal resolution of1 μs. The optical path, including the reflective collection optics, the high-dispersion spectrometer, and the linear detector array, is carefully optimized to obtain a good image quality and a high throughput. The maximum root mean square radius of the collection optics is 64 μm.The detected photon flux is estimated to be about 10~(11) photons/s/channel.     

The Bisphosphonate Clodronate Modifying Hydroxyapatite Bioceramics for Bone Scaffold

To investigate the efficiency of clodronate modifying HA bioceramics,and to evaluate the effect of clodronate modifying HA bioceramics on the cells in vitro,clodronate modified the porous HA bioceramics for bone scaffold by chelation .The outermost layer of the specimens was analyzd by XPS and FI-IR ,The depth profile was investigated by the argon-ion sputtering method.The cell culture test was conducted using MC3T3-E1 osteoblastic cells,The cells were inoculated and cultured on the scaffolds.Morphological observation of the cells,MTT test and ALP activity test evaluated the cell attachment ,proliferation and activity on the scaffolds.The cell culture test in cell quantity and morphology indicated active proliferation of the cells on the scaffolds.The ALP activity of the cells cultured for 3d and 7d on clodronate-HA bioceramics was slightly higher than that on HA bioceramics ,but the difference was not signifcant,This result indicated that clodronate-HA bioeramics had favorable cytocompatibility to be used as bone scaffold with potential ability to improve asteogensis.     

EFFECT OF COMPOSITION ON HYDROGEN EMBRITTLEMENT IN Ni-Fe FCC ALLOYS

The ductility loss and threshold stress intensity,K_(IH)during hydrogen charging were measuredfor pure Ni and four Ni-Fe fcc alloys.The results show that ductility loss in 40Ni60Fe alloyand K_(IH)a 50Ni50Fe alloy have a minimum value.The variations of the amounts of hydride,hydrogen evolution and dislocation structure with composition have been investigated.The va-riation of hydrogen embrittlement susceptibility with composition measured by ductility lossand by K_(IH)or K_(IH)/K_C can be explained by means of the synthetical effects of amount ofhydride,solutionized hydrogen and the extent of dislocation planarity on hydrogenembrittlement susceptibility.     

DYNAMIC RECRYSTALLIZATION OF INTERMETALLIC COMPOUND Fe_3AI

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Fenton试剂对铁锰矿井废水处理的实验研究

使用Fenton试剂对铁锰矿井水进行处理试验,论述了反应温度、H2O2的投加量、pH、反应时间对Fenton试剂处理矿井水的影响,讨论了Fenton试剂处理酸性矿井废水的机理。结果表明:芬顿试剂对铁锰矿井水中锰的去除效率很高,矿井水中的Fe2+能与H2O2形成Fenton试剂后产生的具有强氧化性的.OH能有效处理矿井水中的Mn2+。对于原水Mn2+的初始浓度为2 mg/L,Fe2+的初始浓度为250 mg/L,pH为5,当控制反应温度为25℃,H2O2的投加量为8 mmol/L,调节pH值为4.5,反应时间为10 m in,Mn2+去除效率可以达到78.1%以上。     

遗传-神经网络算法在水下隧道涌水量预测中的应用

水下隧道涌水问题受到多种因素的综合影响,具有非线性和高度复杂性。本文应用遗传算法和BP神经网络,结合工程实例,选用隧道围岩裂隙发育情况、上覆含水体富水性、上覆水压、隧道埋深、隧道围岩上覆相对隔水层强度和上覆基岩破碎带与隧道顶板的距离作为影响水下隧道涌水的主要因素,以调查的数据作为训练样本,使用遗传算法优化BP神经网络的初始权值和阈值,建立了水下隧道涌水量的遗传-神经网络预测模型,并进行了计算分析。结果表明:该模型收敛性能好,预测精度高,简单可行。该方法为水下隧道涌水量的预测提供了一条新思路。     

Fenton接触氧化法强化石英砂—锰砂滤料处理铁锰矿井废水

为了解决目前常用的接触氧化法除铁除锰工艺中铁离子存在时锰离子难去除的问题,本文重点研究了Fenton接触氧化法强化石英砂-锰砂滤料的除铁除锰效率和机理。结果表明:Fenton试剂+锰砂+石英砂工艺除铁锰的效果很好,影响因素的最佳值如下:加入H2O2形成Fenton试剂后可以强化石英砂-锰砂工艺除铁除锰的效果,当H2O2投加量为0.15 mg/L、滤速为8 m/h、pH为7时,铁离子的去除率可达到92%,当H2O2投加量为0.17mg/L、滤速为8 m/h、pH为7时,锰离子的去除率可以达到97%。     

H_2O_2、Fenton试剂与活性炭联用对COD_(Cr)去除效果的对比试验研究

为了开发高效低成本、达到回用水质标准的污水处理工艺,本试验采用H2O2、Fenton试剂与活性炭联用对CODCr进行去除的对比试验研究。结果表明:在室温下200 mL水样,当pH为3,震荡强度为150 rpm时,Fenton试剂-活性炭联用与H2O2-活性炭相比,活性炭用量少200 mg,时间缩短10 h,CODCr去除率高17.6%。试验揭示了Fenton试剂-活性炭联用的反应机理:Fe2+与活性炭共同催化分解H2O2生成大量.OH,能快速氧化降解有机物,使CODCr浓度迅速降低。从工程应用角度和技术经济方面考虑,Fenton试剂-活性炭联用的pH值在5～7适宜;且处理成本更低。Fenton试剂-活性炭联用是处理二级出水CODCr高效、低耗的方法,值得进一步研究和推广应用。     

Sensor selection for parameterized random field estimation in wireless sensor networks

We consider the random field estimation problem with parametric trend in wireless sensor networks where the field can be described by unknown parameters to be estimated. Due to the limited resources, the network selects only a subset of the sensors to perform the estimation task with a desired performance under the D-optimal criterion. We propose a greedy sampling scheme to select the sensor nodes according to the information gain of the sensors. A distributed algorithm is also developed by consensus-based ...     

Energy-efficient adaptive sensor scheduling for target tracking in wireless sensor networks

Sensor scheduling is essential to collaborative target tracking in wireless sensor networks (WSNs). In the existing works for target tracking in WSNs, such as the information-driven sensor query (IDSQ), the tasking sensors are scheduled to maximize the information gain while minimizing the resource cost based on the uniform sampling intervals, ignoring the changing of the target dynamics and the specific desirable tracking goals. This paper proposes a novel energyefficient adaptive sensor scheduling approach that jointly selects tasking sensors and determines their associated sampling intervals according to the predicted tracking accuracy and tracking energy cost. At each time step, the sensors are scheduled in alternative tracking mode, namely, the fast tracking mode with smallest sampling interval or the tracking maintenance mode with larger sampling interval, according to a specified tracking error threshold. The approach employs an extended Kalman filter (EKF)-based estimation technique to predict the tracking accuracy and adopts an energy consumption model to predict the energy cost. Simulation results demonstrate that, compared to a non-adaptive sensor scheduling approach, the proposed approach can save energy cost significantly without degrading the tracking accuracy.