一款新型太阳辐射测量仪的结构设计与热仿真

近年来由于人类生产活动日益加剧,引起的大气气溶胶和臭氧等大气粒子含量的变化对全球气候变化有着重要影响.为了监测上述大气粒子含量,在总结国内外研究现状的基础上,提出使用合理的温控结构来设计制造一款新型多波段太阳辐射测量仪,用来适应国内纬度跨越大、温差大的工作环境.新型太阳辐射测量仪涵盖可见-红外波段,采用九个带通滤光片分别对应两个光电探测器的结构,可以避免探测器相互定标引起的定标误差并减少定标工作量.经ANSYS Workbench热-力耦合仿真,上述太阳辐射测量仪所采用的温控结构在两个极端温度条件下的变形量满足设计要求.     

Design of the low power wake-up receiver for internet of things communication

A wake-up receiver with high energy efficiency and low power consumption is proposed for solving the power consuming problems of wireless nodes communication in the Internet of Things. The proposed wake-up receiver based on the wake-up mechanism can effectively schedule the network nodes communication, and use the simple envelope detection structure to achieve frequency down-conversion, which can flexibly manage energy and reduce power consumption. Based on UMC 65nm CMOS process technology, the wake-up receiver is designed and simulated. The results show that it can achieve S₁₁ of -21dBm and a sensitivity of -75dBm at a data rate of 1Mb/s, when operating at the central frequency of 780MHz and input signal adopting an on-off keying (OOK) modulation, and the power consumption is 82μW at 1.2V voltage supply.     

Probabilistic and interval reliability design of the composite pressure vessel

Considering the randomness or interval character of physical parameters and applied loads of composite pressure vessels (COPV), the COPV reliability-analyzing model is built. And then the computational expressions for the mean value, standard deviation and deviation of fiber stress are deduced by the random factor method. The probabilistic and interval reliability designs on COPV are implemented by utilizing the probabilistic method and interval method combined with the improved particle swarm optimization (PSO) algorithm, respectively. The influence of fluctuation of structure uncertain parameters on COPV design thickness is inspected. Finally, examples are given to demonstrate that both probabilistic and interval reliability methods can satisfy the safety requirement and both are of higher rationality than the traditional safety factor method. And probabilistic method has a lower relative error but a higher computational complexity contrasted with the interval method.     

A brief review on α-zirconium phosphate intercalation compounds and nano-composites

The layer structured zirconium phosphate(Zr P) can be intercalated with atoms, molecules, small organic groups and even polymers. The structures and properties of the Zr P intercalation compounds can be deliberately tuned, leading to promising potential applications in many fields. This article provides a brief review on the experimental results of the Zr P intercalation compounds, with the focus on the polymer/a-zirconium phosphate (α-Zr P) nano-composites. The computer simulations of the Zr P intercalation compounds at the atomic level play a significant role in designing and understanding the properties of Zr P, and in the promotion of the applications of compounds.     

消泡剂在发酵工业中的应用

泡沫问题是发酵工业中一个棘手的问题,几乎所用的液体深层发酵都会用到天然或者化学消泡剂。在过去的发酵过程中,泡沫控制一般是依靠经验,关于消泡剂的系统知识较少。本文综述了发酵工业中消泡剂的种类和作用机制,以及消泡剂的应用进展。     

以就业指导为新载体加强大学生理想信念教育

理想信念是人生的动力和源泉。正确的世界观、人生观、价值观是大学生形成正确就业观的基础。开展积极有效的大学生理想信念教育,将就业指导作为新时期大学生理想信念教育的新载体,意义重大而深远。本文基于大学生就业难的背景,在分析就业指导与理想信念教育之间内在联系的基础上,为大学生理想信念教育的载体提出一些合理的新看法。     

Electrochemical investigation of La0.4Sr0.6TiO3 synthesized in air for SOFC application

Journal of Applied Electrochemistry - La-doped titanate materials have been widely investigated as alternative Ni-free anodes for solid oxide fuel cells (SOFCs). In this study, La0.4Sr0.6TiO3 (LST)...     

国内外不锈钢精炼剂研究发展现状

分析了精炼剂组元元素的作用能力，讨论并总结了精炼剂组元的复合作用，介绍了几种国内、国外精炼剂产品，提出发展高效复合精炼剂的想法。     

Fuzzy adaptive networks in machining process modeling: surface roughness prediction for turning operations

Due to the complexity of the machine tool structure and the cutting process, the dynamics of machining processes are still not completely understood. This is especially true due to the demand of high-speed machining to increase productivity. In order to model and control these complex processes, new approaches, which can represent complex phenomenon combined with learning ability, are needed. The combined neural–fuzzy approach appears to be ideally suited for this purpose. In this paper, the recently developed fuzzy adaptive network (FAN) is used to model surface roughness in turning operations. The FAN network has both the learning ability of neural network and linguistic representation of complex, not well-understood, vague phenomenon. Furthermore, it can continuously improve the initially obtained rough model based on the daily operating data. To illustrate this approach, a model representing the influences of machining parameters on surface roughness is established and then the model is verified by the use of the results of pilot experiments. Finally, a comparison with the results based on statistical regression is provided.