3Com统一网络与增强型业务的发展实施框架与策略

１概述目前,业内人士普遍认识到,统一网络能够简化企业运营,提高向市场提供增强型新业务的能力,并且为此已经做了大量工作,包括将所有的网络流量从已经拥有一个世纪的悠久历史并且遍布全球的交换式公用电话网络转移到同样已经是十分普及的并且效率很高的基于数据包的网络?..     

Theoretical investigation of methane adsorption onto boron nitride and carbon nanotubes

Methane adsorption onto single-wall boron nitride nanotubes (BNNTs) and carbon nanotubes (CNTs) was studied using the density functional theory within the generalized gradient approximation. The structural optimization of several bonding configurations for a CH₄ molecule approaching the outer surface of the (8,0) BNNT and (8,0) CNT shows that the CH₄ molecule is preferentially adsorbed onto the CNT with a binding energy of −2.84 kcal mol⁻¹. A comparative study of nanotubes with different diameters (curvatures) reveals that the methane adsorptive capability for the exterior surface increases for wider CNTs and decreases for wider BNNTs. The introduction of defects in the BNNT significantly enhances methane adsorption. We also examined the possibility of binding a bilayer or a single layer of methane molecules and found that methane molecules preferentially adsorb as a single layer onto either BNNTs or CNTs. However, bilayer adsorption is feasible for CNTs and defective BNNTs and requires binding energies of −3.00 and −1.44 kcal mol⁻¹ per adsorbed CH₄ molecule, respectively. Our first-principles findings indicate that BNNTs might be an unsuitable material for natural gas storage.     

Simplification of composite parametric surface meshes

This paper concerns the simplification of composite parametric surface meshes which conform to the boundary of each constituting patch. The goal is to eliminate the small edges which result from this boundary patch preserving constraint, provided that these small edges belong to an almost flat area. To this end, two tolerance areas with respect to the initial reference mesh are introduced to keep close to the surface. The reference mesh is then simplified and optimized (in terms of shape quality) so that the resulting mesh belongs to these tolerance areas. Several examples of surface meshes are provided in order to assess the efficiency of the simplification method.     

Stochastic behavior of a two-unit cold standby redundant system subject to random failure

The present paper deals with a stochastic model of a two-unit cold standby redundant system subject to random failure. The random failure occurs at random times which follow an exponential distribution. Using a regenerative point technique in the Markov-renewal process, several reliability characteristics are obtained. The mean time to system failure function is studied graphically.     

Associative Liquid-In-Liquid 3D Printing Techniques for Freeform Fabrication of Soft Matter

Shaping soft materials into prescribed 3D complex designs has been challenging yet feasible using various 3D printing technologies. For a broader range of soft matters to be printable, liquid-in-liquid 3D printing techniques have emerged in which an ink phase is printed into 3D constructs within a bath. Most of the attention in this field has been focused on using a support bath with favorable rheology (i.e., shear-thinning behavior) which limits the selection of materials, impeding the broad application of such techniques. However, a growing body of work has begun to leverage the interaction or association of the two involved phases (specifically at the liquid–liquid interface) to fabricate complex constructs from a myriad of soft materials with practical structural, mechanical, optical, magnetic, and communicative properties. This review article has provided an overview of the studies on such associative liquid-in-liquid 3D printing techniques along with their fundamentals, underlying mechanisms, various characterization techniques used for ensuring the structural stability, and practical properties of prints. Also, the future paths with the potential applications are discussed.     

The impact of pigment volume concentration on the protective performance of polyurethane coating with second generation of phosphate based anticorrosion pigment

In this study the effect of conventional zinc phosphate and zinc aluminum phosphate, which represents second generation of phosphate based anticorrosion pigments, on the performance of a polyurethane coating was studied. While zinc phosphate modification was proved to be effective on the corrosion resistance, EIS data facilitated the determination of the optimum pigment volume concentration in which the coating offered the most efficient protection. The superiority of zinc aluminum polyphosphate was attributed to the release of more inhibiting species, leading to the formation of a protective layer at the coating/substrate interface. In addition to the assessment of the impact of pigment content on the resistance of polyurethane primer to cathodic disbonding, the dependency of adhesion strength on the pigment type was also studied using pull-off test.     

Antimonide-Based Type II Superlattices: A Superior Candidate for the Third Generation of Infrared Imaging Systems

Type II superlattices (T2SLs), a system of interacting multiquantum wells, were introduced by Nobel Laureate L. Esaki in the 1970s. Since then, this material system has drawn a lot of attention, especially for infrared detection and imaging. In recent years, the T2SL material system has experienced incredible improvements in material growth quality, device structure design, and device fabrication techniques that have elevated the performance of T2SL-based photodetectors and focal-plane arrays (FPAs) to a level comparable to state-of-the-art material systems for infrared detection and imaging, such as mercury cadmium telluride compounds. We present the current status of T2SL-based photodetectors and FPAs for imaging in different infrared regimes, from short wavelength to very long wavelength, and dual-band infrared detection and imaging, as well as the future outlook for this material system.     

Application of Fuzzy C-means algorithm as a novel approach to predict solubility of hydrocarbons in carbon dioxide

In the recent years, declination of oil reservoir causes the importance of researches on enhancement of oil recovery processes become more important. One of wide applicable approaches in enhancement of oil recovery is carbon dioxide injection which becomes interested because of relative low cost, good displacement and environmentally aspects. The injection of carbon dioxide to oil reservoir causes the lighter hydrocarbons of crude oil are extracted by CO₂. This phenomena can be affected by various factors such the solubility of hydrocarbons in carbon dioxide so in the present investigation Fuzzy c-means (FCM) as a novel approach for estimation of solubility of alkanes in carbon dioxide in terms of temperature, pressure and carbon number of alkane were utilized. The predicting algorithm FCM has reliable ability to estimate solubility based on graphical and statistical results. The coefficient of determination (R²) for training and testing data are calculated as 0.9856 and 0.9529 respectively.     

Application of Grid partitioning based Fuzzy inference system method as a novel approach for prediction of interfacial tension of hydrocarbon and carbon dioxide

Nowadays the importance of enhanced oil recovery (EOR) processes increases because of increasing demand of energy and declination of oil reservoirs. Due to this fact the researchers attracted to study performance of EOR methods. one of the high efficient methods is carbon dioxide injection which is favorable because of low cost and environmental friendly viewpoints. One of important parameters which have straight effect on recovery of injection is interfacial tension between carbon dioxide and hydrocarbons. In the present investigation the main objective is proposing the Grid partitioning based Fuzzy inference system method as novel approach to predict interfacial tension of carbon dioxide and hydrocarbon in terms of temperature, pressure, liquid and gas densities and molecular weight of alkane. The coefficients of determination for different datasets of training and testing of estimating algorithm are determined as 0.9919 and 0.9899. This results express the algorithm has potential of estimating interfacial tension of hydrocarbons and carbon dioxide.     

Utilization of RBF-ANN as a novel approach for estimation of asphaltene inhibition efficiency

One of the problematic concerns in petroleum industries is the deposition of heavy fractions of crude oil such as asphaltene fraction during production and transportation. The utilization of inhibitors is known as a relative low cost and effective method for asphaltene inhibition. In this study, Radial basis function artificial neural network (RBF-ANN) was applied to predict asphaltene precipitation reduction in terms of structure and concentration of inhibitor and oil properties. In order to training and testing of RBF-ANN the required data are extracted from reliable sources. The predicted asphaltene precipitation reduction values were compared with the actual data statistically and graphically. The coefficients of determination for training and testing phases of RBF-ANN were determined as 0.995906 and 0.994853 respectively. These evaluations showed that the RBF-ANN as a predictive tool has great capacity to estimate effect of asphaltene inhibitors on reduction of asphaltene precipitation.