An analytical model for gas leakage through contact interface in proton exchange membrane fuel cells

Sealing performance between two contacting surfaces is of significant importance to stable operation of proton exchange membrane (PEM) fuel cells. In this work, an analytical micro-scale approach is first established to predict the gas leakage in fuel cells. Gas pressure and uneven pressure distribution at the interface are also included in the model. At first, the micro tortuous leakage path at the interface is constructed by introducing contact modelling and fractal porous structure theory. In order to obtain the leakage at the entire surface, contact pressure distribution is predicted based on bonded elastic layer model. The gas leakage through the discontinuous interface can be obtained with consideration of convection and diffusion. Then, experiments are conducted to validate the numerical model, and good agreement is obtained between them. Finally, influences of surface topology, gasket compression and gasket width on leakage are studied based on the model. The results show that gas leakage would be greatly amplified when the asperity standard deviation of surface roughness exceeds 1.0 μm. Gaskets with larger width and smaller thickness are beneficial to sealing performance. The model is helpful to understand the gas leakage behavior at the interface and guide the gasket design of fuel cells.     

Dynamic simulation of hydrogen-based off-grid zero energy buildings with hydrogen storage considering Fanger model thermal comfort

In this study, some locations with different climates, off-grid zero energy buildings with hydrogen energy storage systems are designed, and transient analysis is conducted. These considered buildings supply their electricity consumption without using the electrical grid and PV panels or wind turbines. Also, they supply thermal comfort to occupants by using a vapor compression chiller and humidifier. Domestic hot water of occupants is supplied using solar collectors. For analyzing building's performance and objectives achievement, TRNSYS software is used. Also, for evaluating occupant thermal comfort, the Fanger model is used. The considered building is a one-story building with a 150 m² area. Four occupants are considered. Both of them are seated at rest, and another is seated with light working such as typing. Using the Fanger model equation and MATLAB software, the thermal comfort of occupants is determined. For domestic hot water consumption, verified profiles that vary during 24 h of the day are considered. Achieved results show that for humid and cold cities, PV panels with an area of 73 and 76 m² can be supplied the required electricity of considered building with four occupants and battery state of charge is higher than 50% and 10%, respectively. Moreover, with a suitable air conditioner system, the predicted percentage of dissatisfied (PPD) can be lower than 12% and 8% for humid and cold cities. Therefore, the building can be converted to a zero-energy building using its rooftop area.     

A numerical study on nonlinear DPL model for analyzing heat transfer in tissue during thermal therapy

In the present paper, therapeutic treatment of infected tumorous cells has been studied through mathematical modeling and simulation of heat transfer in tissues by using a nonlinear dual-phase lag bioheat transfer model with Dirichlet boundary condition. The components of volumetric heat source in this model such as blood perfusion and metabolism are assumed experimentally validated temperature-dependent function, which gives more accurate temperature distribution in tissues through this model. We have used the finite difference and RK (4, 5) techniques of numerical methods to solve the proposed problem and obtained the exact solution in a particular case. After comparison, we got a good agreement between them. We have used dimensionless quantities throughout this paper. The effect of relaxation and thermalization time with respect to dimensionless temperature distribution has been analyzed in the treatment process.     

Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.     

Constitutive model for gas hydrate-bearing soils considering different types of hydrate morphology and prediction of strength-band

The present study proposes a new elasto-plastic constitutive model that considers different types of hydrates in pore spaces. Many triaxial compression tests on both methane hydrate-bearing soils and carbon dioxide hydrate-bearing soils have been carried out over the last few decades. It has been revealed that methane hydrate-bearing soils and carbon dioxide hydrate-bearing soils have different strength and dilatancy properties even though they have the same hydrate contents. The reason for this might be due to the different types of hydrate morphology. In this study, therefore, the effect of the hydrate morphology on the mechanical response of gas-hydrate-bearing sediments is investigated through a model analysis by taking into account the different hardening rules corresponding to each type of hydrate morphology. In order to evaluate the capability of the proposed model, it is applied to the results of past triaxial compression tests on both methane hydrate-containing and carbon dioxide hydrate-containing sand specimens. The model is found to successfully reproduce the different stress–strain relations and dilatancy behaviors, by only giving consideration to the different morphology distributions and not changing the fitting parameters. The model is then used to predict a possible range in which the maximum deviator stress can move for various hydrate morphology ratios; the range is defined as the strength-band. The predicted curve of the maximum deviator stress obtained by the constitutive model matches the empirical equations obtained from past experiments. It supports the fact that the hydrate morphology ratio changes with the total hydrate saturation. These findings will contribute to a better understanding of the relation between the microscopic structures and macro-mechanical behaviors of gas-hydrate-bearing sediments.     

5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。     

基于移动窗口法的城市遥感生态质量评价研究

为进一步提高城市生态监测的精确度，在前人开展的城市生态遥感监测研究的基础上引入“区域尺度”的概念，充分考虑小区域范围内不同地物间的交互作用，并利用移动窗口模型(Moving Window-Remote Sensing Ecology Index, MW-RSEI)对沈阳市浑南区的遥感影像进行逐像元分析。实验结果表明，MW-RSEI模型和生态遥感监测模型（Remote Sensing Ecology Index, RSEI)在整体生态评价趋势上表现出一致性。但MW-RSEI模型对城市生态中的细节区域表征更明显。考虑到建筑及裸地周围植被的影响，其较差生态区域的占比仅为6%，生态评价为优的区域占比为11%。研究区生态评价结果表现得较为连续，并未出现明显的断层现象。该结果具有现实意义且与实际生态分布更为符合。MW-RSEI模型在城市生态监测中更为适用，可为相关部门提供一定的技术参考。     

A kinetic model involving oxidation and volatilization in SiC-B4C-xAl2O3 ceramics system

In this paper, a new kinetic model considering both oxidation and volatilization kinetics is established and applied to analyze the oxidation of SiC-B₄C-xAl₂O₃ ceramics and other systems in various oxidation conditions. The effects of diffusion area and volume changes during the oxidation process are considered in this model. The physical meaning of each parameter in this model is explicit and simple. According to this model, the diffusion coefficient of species and the corresponding diffusion activation energy are easily available. The practicability of this model is well verified by the experimental data of SiC-B₄C-xAl₂O₃ and other systems oxidized under different conditions. In addition, the practice shows that the model is applicable not only to the systems where oxidation and volatilization coexist, but also to the system where only oxidation plays a major role. We hope the model proposed in this work can be used in other materials with more complex environments.