Taguchi统计学分析方法优化Al 7068-TiC纳米复合材料的凝固行为

采用机械合金化和热压工艺制备高强Al 7068?5%TiC(质量分数)纳米复合材料。基于致密化的重要性和晶粒生长的影响,以获得较高抗压强度为目标,采用Taguchi统计法对制备Al 7068?5%TiC块体纳米复合材料的热压条件进行优化。结果表明：在500 MPa和385°C下热压30 min能获得抗压强度为938 MPa、硬度为HV 265的Al 7068?TiC纳米复合材料。此外,方差分析结果表明,外加压力是影响纳米复合材料热压过程最关键的因素。各因素对纳米复合材料热压过程影响贡献率为外加压力(61.3%)、热压温度(29.53%)和热压时间(4.49%)。     

Evolution of vinyl chloride conversion below critical micelle concentration: A response surface analysis

Utilizing response surface methodology, the conversion of vinyl chloride monomer (VCM) was monitored when the polymerization temperature, the type of surfactant, and the weight ratio of water‐to‐monomer (W/M) were taken as the emulsion polymerization variables. Because the homogeneous nucleation was found to be the dominant mechanism in VCM emulsion polymerization, irrespective of the surfactant concentration, the whole experiments have been carried out below critical micelle concentration of the used surfactants. Among all the studied variables, the polymerization temperature appeared as the most effective parameter; moreover, its interactive effect with W/M caused different trends in the alteration of final conversion being observed. Also, depending on the reaction temperature, the VCM conversion would be affected by the type of the surfactant used. Contrarily, simultaneous change in the type of surfactant and W/M revealed an insignificant effect on the evolution of VCM conversion. The optimization of final conversion of VCM was also accessible through contour plots of response surface methodology. It is worth noting that, taking a conventional approach into consideration, the alteration of VCM conversion seemed to be a monotonic function of temperature. J. VINYL ADDIT. TECHNOL., 21:157–165, 2015. © 2014 Society of Plastics Engineers     

Intrinsic reaction rate and the effects of operating conditions in dimethyl ether synthesis from methanol dehydration

The kinetic behavior of a commercial γ-Al₂O₃ catalyst for the methanol to dimethyl ether (DME) dehydration reaction has been investigated using a differential fixed bed reactor at the pressure range 1–16 barg within a temperature range of 260–380 °C. The experimental runs were performed in a wide range of feed to water ratios. The experiments were designed by general full factorial design (GEFD) and a novel rate equation has been developed which exhibited the best fitting with our experimental data. Based on the analysis of variance (ANOVA), the following order of importance for operating conditions was obtained when the objective function is the yield of DME: Temperature >Water % in feed >Pressure. In addition, the optimum operating conditions for the maximum yield of DME, were found at T= 380°C, P=16 barg and zero wt% of water in the feed.     

FQL‐RED: an adaptive scalable schema for active queue management

In a potentially congested network, random early detection (RED) active queue management (AQM) proved effective in improving throughput and average queuing delay. The main disadvantage of RED is its sensitive parameters that are impossible to estimate perfectly and adjust manually because of the dynamic nature of the network. For this reason, RED performs differently during different phases of a scenario and there is no guarantee that it will have optimal performance. Giving adaptability to RED has been the subject of broad research studies ever since RED was proposed. After a substantial study of AQM schemes and presenting a novel categorization for so‐called modern approaches utilizing artificial intelligence tools to improve AQM, this paper proposes an algorithm enhancing RED as an add‐on patch that makes minimal changes to the original RED. Being built on the basis of AQM schemes like ARED and Fuzzy‐RED, this algorithm inherits adaptability and is able to adjust RED inaccurate parameters regarding network traffic status, trying to optimize throughput and average queuing delay in a scenario. This algorithm is a Q‐learning method enhanced with a fuzzy inference system to provide RED with self‐adaptation and improved performance as a result. Given the name of FQL‐RED, this algorithm outperformed RED, ARED, and Fuzzy‐RED, as the OPNET simulations show. Copyright © 2010 John Wiley & Sons, Ltd.     

Copolymerization of ethylene/α‐olefins using bis(2‐phenylindenyl)zirconium dichloride metallocene catalyst: structural study of comonomer distribution

Catalysts have a major role in the polymerization of olefins and exert their influence in three ways: (1) polymerization behaviour, including polymerization activity and kinetics; (2) polymer particle morphology, including bulk density, particle size, particle size distribution and particle shape; and (3) polymer microstructure, including molecular weight regulation, chemical composition distribution and short‐ and long‐chain branching. By tailoring the catalyst structure, such as the creation of a bridge or introducing a substituent on the ligand, metallocene catalysts can play a major role in the achievement of desirable properties. Kinetic profiles of the metallocene catalyst used in this study showed decay‐type behaviour for copolymerization of ethylene/α‐olefins. It was observed that increasing the comonomer ratio in the feedstock affected physical properties such as reducing the melting temperature, crystallinity, density and molecular weight of the copolymers. It was also observed that the heterogeneity of the chemical composition distribution and the physical properties were enhanced as the comonomer molecular weight was increased. In particular, 2‐phenyl substitution on the indenyl ring reduced somewhat the melting point of the copolymers. In addition, the copolymer produced using bis(2‐phenylindenyl)zirconium dichloride (bis(2‐PhInd)ZrCl₂) catalyst exhibited a narrower distribution of lamellae (0.3–0.9 nm) than the polymer produced using bisindenylzirconium dichloride catalyst (0.5–3.6 nm). The results obtained indicate that the bis(2‐PhInd)ZrCl₂ catalyst showed a good comonomer incorporation ability. The heterogeneity of the chemical composition distribution and the physical properties were influenced by the type of comonomer and type of substituent in the catalyst. Copyright © 2010 Society of Chemical Industry     

A collective and abridged lexical query for delineation of nanotechnology publications

In order to monitor articles/patents in nanotechnology, there is little agreement on a universal lexical query or even an explicit definition of nanotechnology. Here in the light of a proposed definition, a set of case studies has been conducted to remove keywords which are not exclusive to nanotechnology. This resulted in a collective and abridged lexical query (CALQ) for nanotechnology delineation. Through bibliometric quantification of already-proposed as well as the novel keywords, it was shown that all keywords included in CALQ have considerable exclusive retrieval and precision, while the removed keywords do not satisfy either of these numerical thresholds. This approach may also be applied for the future updating of CALQ.     

Parametric study of a 2-d model of the nip region in a counter-rotating,non-intermeshing twin screw extruder

Within the polymer processing industry, the demand for more efficient mixing within the existing mixer geometries and keeping a tighter control over increasingly difficult applications calls for a quantitative understanding of the role of the mixer geometry on the mixing performance. An important extruder geometry to consider is the Counter-Rotating, Non-Intermeshing Twin Screw Extruder (CRTSE). Recent studies suggest that the greater than linear mixing performance in this geometry may be attributed to the flow in the nip region. Solution of the fluid dynamic equations for a 2-D model of the nip region was found in order to quantify mixing using a FEM software called FIDAP which was available to us on the CRAY X-MP supercomputer at San Diego Supercomputer Center. In order to study the effects of design parameters in the nip region, an arbitrary interface was placed in the entrance of the region. A program called “LINE” tracks the path and growth of the interface through the region. Measures of mixing are computed and compared. Effect of several design parameters on mixing performance are studied. Conclusions are presented as to the relative effect of various design parameters. Discussions regarding the measures of mixing and mixing efficiency are presented.     

Unique microstructure analysis of ethylene-propylene copolymer synthesized using catalytic system based on α-diimine nickel complexes: a comparative study by 13C NMR technique

The microstructure of rubber-like ethylene-propylene copolymer (MN4) produced by a mixed nickel-based system (MN) containing catalysts of dibromo[N,N′-bis(2,6-diisopropylphenyl)-2,3-butanediimine]nickel(II) n1 and dibromo[N,N′-(phenanthrene-9,10-diylidene)bis(2,6-diisopropylaniline)]nickel(II) n2 was determined by ¹³C NMR technique. Sequences distribution of ethylene (E), propylene (P), EP, inverted propylene and uninterrupted methylene and also methylene number-average sequence lengths for the copolymer (MN4) were estimated. The results obtained from the MN4 EP copolymer were compared with reported copolymers which had been synthesized using constrained geometry catalyst (CGC) and vanadium-based Ziegler-Natta catalyst. The results demonstrated that the MN4 EP copolymer had fewer alternating comonomer sequences than ethylene-propylene elastomers obtained by CGC and vanadium-based (V) catalysts. A large number of the inversion structures (66 %) and high mole percent of sequences containing a long branch (3.2 mol%) were also observed in unique microstructure of the copolymer (MN4).     

Optimal control of steel structures by improved particle swarm

Active control is one of the modern approaches in seismic design of steel structures. Recently, induced by economic considerations, especially high expenses of control systems, optimality has become an important issue. In this paper an active system is used to control a steel structure’s displacements by a simplified pole assignment method. To optimize the number, the locations, and the total driving force of the required actuators, an improved particle swarm algorithm is presented focusing on the parameters of the velocity equation. A Geographical neighborhood topology and an adaptive inertia weight are used to improve the standard PSO algorithm. In addition to the local and global best solutions, the positions of the best particles in the geographical neighborhood are mathematically represented in an additional term. The performance of the proposed algorithm is compared with the traditional Genetic Algorithm (GA) and the standard particle swarm considering the optimal control of a 12-story steel structure as a numerical example. High capabilities of the proposed method in terms of the control target, convergence rate, and accuracy are simultaneously clarified by the results.