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目前,由于缺少直接测量水力裂缝长度及导流能力等重要参数的手段,而地下水力裂缝的存在总要反映到油气井压力与产量的变化上来,特别是压力与产量随时间的变化速度与水力裂缝的长短、导流能力的大小等参数有直接关系。在常规压裂井试井分析过程中,所使用的数据主要是停泵后的压降数据,而岩石发生破裂到停泵前这一段压裂施工压力数据则没有得到有效利用;同时,在压裂施工作业过程中也不能对裂缝的延伸状况进行动态监测。文章提供了裂缝模型的诊断技术,通过对岩石发生破裂到停泵前这一段压裂施工压力数据进行分析,确定裂缝参数随压裂时间的变化关系。这样,就可以实时地知道裂缝发育、发展和闭合的过程,对于正确指导压裂施工作业以及获得优质裂缝具有十分重要的意义。     

Distributed Construction of Connected Dominating Set in Wireless Ad Hoc Networks

Connected dominating set (CDS) has been proposed as virtual backbone or spine of wireless ad hoc networks. Three distributed approximation algorithms have been proposed in the literature for minimum CDS. In this paper, we first reinvestigate their performances. None of these algorithms have constant approximation factors. Thus these algorithms cannot guarantee to generate a CDS of small size. Their message complexities can be as high as O(n ²), and their time complexities may also be as large as O(n ²) and O(n ³). We then present our own distributed algorithm that outperforms the existing algorithms. This algorithm has an approximation factor of at most 8, O(n) time complexity and O(nlogn) message complexity. By establishing the (nlogn) lower bound on the message complexity of any distributed algorithm for nontrivial CDS, our algorithm is thus message-optimal.     

Absolute configuration of monodentate phosphine ligand enantiomers on Cu(111)

Scanning tunneling microscopy (STM) has been employed to investigate the chirality of monophosphine compounds that are highly efficient chiral ligands in transition-metal-catalyzed organic transformations. The absolute configuration of 1-(2-diphenyphosphino-1-naphthyl)isoquinoline enantiomers with axial chirality was discriminated directly by the "marker" group, PPh(2) substitutes. Although the two enantiomer molecules adsorb on a Cu(111) surface and form well-defined (4 x 4) structures, the positions of PPh(2) substitutes in the molecular adlayers are different. The mirror symmetry between two adlayers is demonstrated. On the basis of STM results, structural models are proposed to interpret the chiral adsorption. The results presented here supply a straightforward method for axial chirality analysis in adsorbed adlayers by STM.     

Design and analysis of a uranium hexafluoride actinide transmutation reactor

The long-term (> 1000 years) hazards of high-level wastes (HLW) can be reduced substantially by practising waste-actinide partitioning-transmutation (P-T). This paper investigates the waste-actinide transmutation performance of a uranium hexafluoride actinide transmutation reactor (UHATR). Using mostly present-day and near-term technology, a preliminary UHATR design is established. Because of the gaseous nature of the fuel, very high neutron fluxes are obtained. Compared with an LWR, the average blanket thermal flux of this UHATR is about 10–30 times higher, leading to a 15-fold improvement in the percentage of actinides fissioned per year of irradiation.     

Methoxymethylation of Alcohols Catalyzed by Sulfated Metal Oxides

More acidic sulfated metal oxides (SMO) such as SO₄ ^2-/ZrO₂ and SO₄ ^2-/TiO₂ catalyzed the methoxymethylation of alcohols with dimethoxymethane at ambient temperature to achieve a product yield of greater than 90% within a few hours. The reaction displayed a significant steric effect on the product yield with a preferential order of primary alcohol > secondary alcohol tertiary alcohol. The observed steric effect might result from the repulsion between the bulky alkyl group in the alcohol and the two methoxy groups in the protonated dimethoxymethane (oxonium ion).     

《家用和类似用途的过电流保护断路器》IEC60898—2国际电工标准续篇第二部分研究

文章对《家用和类似用途的过电流保护断路器》IEC60898－2国际标准的主要特点,特性和要求进行了研究。     

An interactive example-driven approach to graphics recognition in engineering drawings

An interactive example-driven approach to graphics recognition in engineering drawings is proposed. The scenario is that the user first interactively provides an example of a graphic object; the system instantly learns its graphical knowledge and uses the acquired knowledge to recognize the same type of graphic objects. The proposed approach represents the graphical knowledge of an object in terms of its structural components and their syntactical relationships. We summarize four types of geometric constraints for knowledge representation, based on which we develop an algorithm for knowledge acquisition. Another algorithm for graphics recognition using the acquired graphical knowledge is also proposed, which is actually a sequential examination of these constraints. In the algorithm, we first guess the next component’s attributes (e.g., size, position and orientation) by reasoning from an earlier found component and the constraint between them, and then search for this hypothetical component in the drawing. If all of the hypothetical components are found, a graphic object of this type is recognized. For improving the system’s recognition accuracy, we develop a user feedback scheme, which can update the graphical knowledge from both positive (missing) and negative (mis-recognized) examples provided by the user for subsequent recognition. Experiments have shown that our proposed approach is both efficient and effective for recognizing various types of graphic objects in engineering drawings. This paper is an extension of our papers published in ICDAR2003 and GREC2003.     

Statistical fuzzy interval neural networks for currency exchange rate time series prediction

In this paper, the statistical fuzzy interval neural network with statistical interval input and output values is proposed to perform statistical fuzzy knowledge discovery and the currency exchange rate prediction. Time series data sets are grouped into time series data granules with statistical intervals. The statistical interval data sets including week-based averages, maximum errors of estimate and standard deviations are used to train the fuzzy interval neural network to discover fuzzy IF-THEN rules. The output of the fuzzy interval neural network is an interval value with certain percent confidence. Simulations are completed in terms of the exchange rates between US Dollar and other three currencies (Japanese Yen, British Pound and Hong Kong Dollar). The simulation results show that the fuzzy interval neural network can provide more tolerant prediction results.