Performance of surface ionic conduction single chamber fuel cell prepared by the sol gel method

The performance of surface ionic conduction single chamber fuel cell (SIC‐SCFC) prepared by the sol gel method was studied on electric characteristics due to the differences of the operating temperature and humidity, the electrode distance and electrolyte film depth, and multiple cells with the series and parallel connections. The SIC–SCFC was arranged the both anode of Pt and cathode of Au on the boehmite electrolyte. The open circuit voltage (OCV) of single cell achieved a maximum of 530mV in the dry gas mixtures of O₂/H₂=50% in room temperature operation, and but it became decrease as over 60%. The OCV was maintained the constant value between operating temperatures of 30°C to 80°C, and but it was decreased sharply at over 90°C because a humidity on the cell became lower as increasing operating temperature. Then, the cell property was improved to 120°C by adding to the humidity of 70% using a humidifier. The electrode distance and the electrolyte film depth of SIC‐SCFC found to be contributed to the reductions of the cell resistance and the surface roughness on the electrode, respectively. Moreover, the power property of SIC‐SCFC was significantly improved by cell stacks comprised of the series or parallel connection of a cell.     

Hydrogen from wet air and sunlight in a tandem photoelectrochemical cell

A solid-state photoelectrochemical (SSPEC) cell is an attractive approach for solar water splitting, especially when it comes to monolithic device design. In a SSPEC cell the electrodes distance is minimized, while the use of polymer-based membranes alleviates the need for liquid electrolytes, and at the same time they can separate the anode from the cathode. In this work, we have made and tested, firstly, a SSPEC cell with a Pt/C electrocatalyst as the cathode electrode, under purely gaseous conditions. The anode was supplied with air of 80% relative humidity (RH) and the cathode with argon. Secondly, we replaced the Pt/C cathode with a photocathode consisting of 2D photocatalytic g-C₃N₄, which was placed in tandem with the photoanode (tandem-SSPEC). The tandem configuration showed a three-fold enhancement in the obtained photovoltage and a steady-state photocurrent density. The mechanism of operation is discussed in view of recent advances in surface proton conduction in absorbed water layers. The presented SSPEC cell is based on earth-abundant materials and provides a way towards systems of artificial photosynthesis, especially for areas where water sources are scarce and electrical grid infrastructure is limited or nonexistent. The only requirements to make hydrogen are humidity and sunlight.     

ACCUGRAM: A novel approach based on classification to frequency band selection for rotating machinery fault diagnosis

Frequency band selection (FBS) in rotating machinery fault diagnosis aims to recognize frequency band location including a fault transient out of a full band spectrum, and thus fault diagnosis can suppress noise influence from other frequency components. Impulsiveness and cyclostationarity have been recently recognized as two distinctive signatures of a transient. Thus, many studies have focused on developing quantification metrics of the two signatures and using them as indicators to guide FBS. However, most previous studies almost ignore another aspect of FBS, i.e. health reference, which significantly affect FBS performance. To address this issue, this paper investigates importance of a health reference and recognize it as the third critical aspect in FBS. With help of the health reference, the frequency band where the fault transient exists could be located. A novel approach based on classification is proposed to integrate all three aspects (impulsiveness, cyclostationarity, and health reference) for FBS. Classification accuracy is developed as a novel indicator to select the most sensitive frequency band for rotating machinery fault diagnosis. The proposed method (coined by accugram) has been validated on benchmark and experiment datasets. Comparison results show its effectiveness and robustness over conventional envelope analysis, the kurtogram, and the infogram.     

Regulation of sensory nerve conduction velocity of human bodies responding to annual temperature variations in natural environments

The extensive research interests in environmental temperature can be linked to human productivity / performance as well as comfort and health; while the mechanisms of physiological indices responding to temperature variations remain incompletely understood. This study adopted a physiological sensory nerve conduction velocity (SCV) as a temperature‐sensitive biomarker to explore the thermoregulatory mechanisms of human responding to annual temperatures. The measurements of subjects’ SCV (over 600 samples) were conducted in a naturally ventilated environment over all four seasons. The results showed a positive correlation between SCV and annual temperatures and a Boltzmann model was adopted to depict the S‐shaped trend of SCV with operative temperatures from 5°C to 40°C. The SCV increased linearly with operative temperatures from 14.28°C to 20.5°C and responded sensitively for 10.19°C‐24.59°C, while tended to be stable beyond that. The subjects’ thermal sensations were linearly related to SCV, elaborating the relation between human physiological regulations and subjective thermal perception variations. The findings reveal the body SCV regulatory characteristics in different operative temperature intervals, thereby giving a deeper insight into human autonomic thermoregulation and benefiting for built environment designs, meantime minimizing the temperature‐invoked risks to human health and well‐being.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

泡沫夹克管的防水与保温

针对辽河油田应用泡沫夹克管道的情况，从泡沫夹克管的制作和敷设施工直到设计等环节，结合泡沫夹克管防腐保温的机理，并从理论与实践相结合角度出发，提出导致泡沫夹克管腐蚀损坏的最主要原因是管道保温层漏水，进而提出了在设计和施工过程中提高泡沫夹克管质量的措施。     

瞬态瑞利面波技术在地震勘探方面的应用研究

运用瞬态瑞利面小勘探方法可以在寻找激发岩性和提供静校正所需参数方面取得好的效果。     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

瞬态非傅里叶导热效应判据的探讨

讨论了通用傅里叶导热定律的数学模型,推导了半无限大物体在第一类边界条件下的基于非傅里叶导热定律的双曲线型偏微分方程的解析解。通过分析非傅里叶导热定律在瞬态条件下温度分布的变化过程,提出了非傅里叶导热效应的瞬态判据以及非傅里叶导热的作用范围,对研究工程中瞬态导热问题(如激光处理,电子束处理等)有重要意义。