A numerical study of dynamic behaviors of a unitized regenerative fuel cell during gas purging

The gas purging states affect electricity output and energy storage capacity of unitized regenerative fuel cells. In this study, a model of unitized regenerative fuel cell is established. Cell voltages and operating temperatures influences on the dynamic distribution of thermal fluid during purging process and the discharge of residual liquid water in electrolytic cell mode are investigated. The motivation of the present study is better understanding the gas purging characteristics and its effect on reaction behaviors of unitized regenerative fuel cells. Simulation results reveal a significant influence of purging gas temperature on the water flooding and a great effect of operating voltage on the water diffusion. The operating temperature of electrolytic cell model almost has little effect on purging results at different cell temperature and the same purging gas temperature. When the purging gas temperature is changed, higher temperatures of cell and purging gas facilitate liquid water discharging out from the cell regions. In cell water flooding situation, when having large liquid content, the purging gas has little effects on the water expelling process.     

低渗致密砂岩气藏SEC储量评估实例分析--以A气田JS气藏为例

在对气藏的地质特征、开发历程以及生产规律充分了解的基础上,确定合理的评估方法、递减率及初始产量等参数的取值,可合理评价气藏的SEC储量,为气藏储量评估提供方法指导。     

In-fibre LP11–LP21 mode conversion using force-induced long-period fibre gratings with polarization controllers

ABSTRACT

Mode conversion between higher-order modes is attained in a step-index four mode fibre using an in-line polarization controller followed by a force-induced long period fibre grating. By adjusting the field orientation of the LP₁₁ mode to the antisymmetric fibre grating, the LP₁₁ mode is converted to the LP₂₁ mode with a spatially periodic force of 50 N along the fibre length of 50?mm. The mode conversion is evaluated by observing the far-field and near-field patterns of the fibre output and by comparing the transmitted optical power with and without the additional two-mode fibre. The phase-matching grating period is required of the accuracy of roughly ±5?μm and the radiation loss during the mode conversion is as low as 0.01?dB.     

山东栖霞—大柳行地区金矿找矿靶区地质评价及优选

栖霞—大柳行地区位于胶东中部栖霞—蓬莱金矿成矿带内，是胶东重要的金成矿区，成矿条件优越。为了对圈定靶区进行优选分类，通过对该区地质背景、找矿靶区评价、找矿靶区优选方面展开综合研究，并结合勘查工作程度和矿业权设置情况，划分出3类预测区，选定了5个靶区为今后优先部署勘查工作的方向。     

Common Mode Voltage Reduction Using 3D-SVPWM for 3-level CI-NPC Inverter with Hybrid Energy System

This paper elucidates Common Mode Voltage (CMV) reduction in transformerless 3-phase 3-level Coupled Inductor Neutral Point (CI-NPC) Clamped Inverter with Hybrid Energy System. The three dimensional Space Vector Pulse Width Modulation (3D-SVPWM) with Nearest State Vector (NSV) is implemented to reduce the CMV by proper selection of medium, large and small vectors in 3D cubic space region. This NSV scheme in addition to CMV reduction, reduces the capacitor voltage balancing issues and minimizes switching losses. The proposed control provides full utilization of dc link voltage with reduced harmonics. This 3-level CI-NPC inverter is energized by hybrid energy source which includes photovoltaic system and wind energy system. The results obtained for the proposed scheme through simulation and experimental setup is compared with the conventional 2D-SVPWM and 3D-SVPWM scheme. From the compared results it is evident that the proposed scheme reduces CMV to a larger extent than 2D and 3D-SVPWM control. The simulation and experimental results are verified using matlab-simulink and FPGA-Spartan-6 controller respectively.     

石油套管质量评价方法研究

石油套管是油气田开采中重要的物资装备,其质量直接影响油气田的生产安全与开采效率。对石油套管质量评价方法进行研究,优选反映石油套管质量的性能参数,通过归一化处理,结合专家知识,建立评价模型,进而得到石油套管质量的评价结果。将所研究的评价方法应用于P110石油套管质量评价中,评价结果准确、直观,方法有效实用。     

钻井液纳米颗粒封堵性评价方法研究

目前没有针对纳米封堵剂封堵效果评价的方法。在室内进行评价时，实验结果往往会无法反映出纳米颗粒的封堵作用。在借鉴现有评价方法的基础上，通过对滤失介质的选择和改善，形成了渗透性滤失评价方法。该方法可操作性高，能反映出纳米颗粒的封堵效果，并通过对不同粒径的纳米颗粒封堵效果的评价对该方法进行了验证。该方法对于纳米颗粒的评价和在现场施工中的选择都有一定评价参考作用。      

仿真软件Aspen Plus在化工原理实验教学中的应用研究

以精馏塔分离乙苯-苯乙烯为例,将Aspen Plus软件应用于化工原理实验教学,分别进行简捷塔DSTWU和严格塔RADFRAC模块模拟优化。通过Aspen Plus与化工原理实验的结合,提高了学生分析解决工程问题的能力,加深了对该课程的理解,促进教学质量提升。     

Clean hydrogen production in a full biological microbial electrolysis cell

The recent interest in microbial electrolysis cell (MEC) technology has led the research platform to develop full biological MECs (bioanode-biocathode, FB-MEC). This study focused on biohydrogen production from a biologically catalyzed MEC. A bioanode and a biocathode were initially enriched in a half biological MFC (bioanode-abiocathode, HB-MFC) and a half biological MEC (abioanode-biocathode, HB-MEC), respectively. The FB-MEC was established by transferring the biocathode of the HB-MEC and the bioanode of the HB-MFC to a two-chamber MEC. The FB-MEC was operated under batch (FB-MEC-B) and recirculation batch (FB-MEC-RB) modes of operation in the anodic chamber. The FB-MEC-B reached a maximum current density of 1.5 A/m² and the FB-MEC-RB reached a maximum current density of 2.5 A/m² at a similar applied voltage while the abiotic control system showed the maximum of 0.2 A/m². Hydrogen production rate decreased in the FB-MEC compared to that of the HB-MEC. However, the cathodic hydrogen recovery increased from 42% obtained in the HB-MEC to 56% in the FB-MEC-B and 65% in the FB-MEC-RB, suggesting the efficient oxidation and reduction rates in the FB-MEC compared to the HB-MEC. The onset potential for hydrogen evolution reaction detected by linear sweep voltammetry analysis were −0.780 and −0.860 V vs Ag/AgCl for the FB-MEC-RB and the FB-MEC-B (−1.26 for the abiotic control MEC), respectively. Moreover, the results suggested that the FB-MEC worked more efficiently when the biocathode and the bioanode were enriched initially in half biological systems before transferring to the FB-MEC compared to that of the simultaneously enriched in one system.     

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

Prediction of mode I fracture toughness (K_IC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression (LMR) and gene expression programming (GEP) methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and elastic modulus (E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets. Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of K_IC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were utilized herein. In the case of testing datasets, the values of R², RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156, respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R² value and lower errors.