交流接触器温度场仿真及试验验证

将ANSYS有限元热分析应用到交流接触器热特性分析中,模仿其实际工作环境,构建交流接触器三维稳态热分析模型,确定热源、导热系数和表面散热系数,对接触器的稳态温度场进行分析;进一步改变施加的边界条件,研究不同散热方式下接触器的温度分布。最后对CJX2-0910型交流接触器进行温升试验,将温度场的仿真结果与试验结果比较,误差较小,表明所建立热分析模型的可行性。研究结果对接触器材料的选择、结构的设计及其性能的优化有重要意义。     

α-Fe2O3/煤矸石复合光催化剂的制备及其降解五氯酚性能的研究

以Fe（NO₃）₃、煤矸石和NaOH为原料,采用沸腾回流法制得了一系列不同质量比的α-Fe₂O₃/煤矸石复合光催化剂。采用场发射扫描电子显微镜（FESEM）、X射线衍射仪（XRD）及紫外-可见漫反射光谱（UV-Vis DRS）等多种手段对产物做了表征。以五氯酚为目标降解物,考察了模拟太阳光照下样品的光催化效果。结果表明,将球形α-Fe₂O₃负载于改性煤矸石表面可有效提高其光催化活性,且α-Fe₂O₃/煤矸石复合光催化剂的性能与α-Fe₂O₃的含量有关,当α-Fe₂O₃与煤矸石的质量比为30∶100时,样品的光催化效果最佳,180 min内即可将五氯酚降解完全。此外,α-Fe₂O₃/煤矸石复合光催化剂还具有可重复使用的特点。     

Comments on “Exact and approximate feedback linearization without the linear controllability assumption [Automatica 48 (2012) 2221–2228]”

The conditions for state feedback linearization suggested in the aforementioned article are shown, by means of counterexamples, not to be sufficient. In view of this, modified results are proposed for ensuring the sufficiency.     

压力容器用封头制造质量控制和专业化生产发展方向

中国法规首次对压力容器等特种设备用封头实施制造资格许可和强制的监督检验制度。本文根据法规标准的规定,对压力容器封头制造质量控制和专业化生产发展方向的要求作一系统的综述,以提高压力容器产品的整体质量,确保特种设备安全万无一失。     

R407系列产品专利研究

介绍了杜邦公司R407系列产品专利申请、授权和专利权有效期情况。     

气化炉锥底砖、激冷环与下降筒的损毁与解决对策

针对国产化大氮肥水煤浆气化炉中锥底砖、激冷环和下降筒使用过程中出现的问题,分析了损毁原因,分别从技术改进、工艺操作和设备管理等方面提出了相应的解决对策,可以不同程度地延长锥底砖、激冷环、下降筒的寿命。     

Synthesis and properties of new polymerized monomer reactants matrix resins of pyrrolone–benzimidazole copolymers containing pyridine unit

A series of new polymerized monomer reactants (PMR) matrix resins of poly(pyrrolone‐benzimidazole)s containing a pyridine unit (PPBP) were synthesized by polycondensation of monoethyl ester of cis‐5‐norbornene‐endo‐2,3‐dicarboxylic acid, 2,6‐diphenyl ester pyridinedicarboxylic acid or 3,5‐diphenyl ester pyridinedicarboxylic acid, and diethyl ester of 4,4′‐oxydiphthalic acid with 3,3′‐diaminobenzidine in a mixing solution of anhydrous ethyl alcohol and N‐methylpyrrolidone under given temperature and pressure conditions. The resulting resin solutions showed good solubility in polar organic solvents and stability at room temperature. The corresponding PPBP matrix resin, molded powder, and molded plate were prepared by undergoing amidation, imidization, cyclization, and crosslinking reactions when the reaction temperature was increased from 80 to 350°C, successively; the crosslinking structure was formed by the reverse Diels–Alder reaction at 270–290°C under 50 MPa pressure (2.5–3.5 MPa displayed by the pressure meter). The chemical reactions and properties of the resulting PPBP were studied by means of FTIR, TGA, and DMA methods, and the results indicated that the kinds of PPBP materials retain excellent thermal stability and processability; when the initial decomposition temperature was above 620°C the T_g was at 413.5°C for 3,5‐PPBP‐20 molded plate. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 91: 3981–3990, 2004     

Optimizing ranking method using social annotations based on language model

Recent research has shown that more and more web users utilize social annotations to manage and organize their interested resources. Therefore, with the growing popularity of social annotations, it is becoming more and more important to utilize such social annotations to achieve effective web search. However, using a statistical model, there are no previous studies that examine the relationships between queries and social annotations. Motivated by this observation, we use social annotations to re-rank search results. We intend to optimize retrieval ranking method by using the ranking strategy of integrating the query-annotation similarity into query-document similarity. Specifically, we calculate the query-annotation similarity by using a statistical language model, which in a shorter form we call simply a language model. Then the initial search results are re-ranked according to the computational weighted score of the query-document similarity score and the query-annotation similarity score. Experimental results show that the proposed method can improve the NDCG score by 8.13%. We further conduct an empirical evaluation of the method by using a query set including about 300 popular social annotations and constructed phrases. More generally, the optimized results with social annotations based on a language model can be of significant benefit to web search.     

Event-based optimization of admission control in open queueing networks

In this paper, we use the event-based optimization framework to study the admission control problem in an open Jackson network. The external arriving customers are controlled by an admission controller. The controller makes decision only at the epoch when an event of customer arrival happens. Every customer in the network obtains a fixed reward for each service completion and pays a cost with a fixed rate during its sojourn time (including waiting time and service time). The complete information of the system state is not available for the controller. The controller can observe only the number of total customers in the network. Based on the property of closed form solution of Jackson networks, we prove that the system performance is monotonic with respect to the admission probabilities and the optimal control policy has a threshold form. That is, when the number of total customers is smaller than a threshold, all of the arriving customers are admitted; otherwise, all are rejected. The sufficient condition and necessary condition of optimal policy are also derived. Furthermore, we develop an iterative algorithm to find the optimal policy. The algorithm can be executed based on a single sample path, which makes the algorithm online implementable. Simulation experiments are conducted to demonstrate the effectiveness of our approach.     

A new dynamic Bayesian network approach for determining effective connectivity from fMRI data

Two techniques based on the Bayesian network (BN), Gaussian Bayesian network and discrete dynamic Bayesian network (DBN), have recently been used to determine the effective connectivity from functional magnetic resonance imaging (fMRI) data in an exploratory manner and to provide a new method for exploring the interactions among brain regions. However, Gaussian BN ignores the temporal relationships of interactions among brain regions, while discrete DBN loses a great deal of information by discretizing the data. To overcome these limitations, the current study proposes a new BN method based on Gaussian assumptions, termed Gaussian DBN, to capture the temporal characteristics of connectivity with less associated loss of information. A set of synthetic data were generated to measure the robustness of this method to noise, and the results were compared with discrete DBN. In addition, real fMRI data obtained from twelve normal subjects in the resting state was used to further demonstrate and validate the effectiveness of the Gaussian DBN method. The results demonstrated that the Gaussian DBN was more robust than discrete DBN and an improvement over BN.