On the influence zone and the prediction of tensile strength of particulate polymeric composites

An intended numerical investigation is carried out. The results indicate that, even if a perfect adhesive bond is preserved between the particles and matrix materials, the two-phase element cell model is unable to predict the strength increment of the particulate polymeric composites (PPC). To explore the main reinforcing mechanism, additional microscopic experiment is performed. An ''influence zone'' was observed around each particle which is measured about 2 to 10 micrometers in thickness for a glass-polyethylene mixture. Then, an improved computational model is presented to include the ''influence zone'' effect and several mechanical behaviors of PPC are well simulated through this new model.

Convective coupled map for simulating spatiotemporal chaos in flows

A coupled map lattices with convective nonlinearity or, for short, Convective Coupled Map (CCM) is proposed in this paper to simulate spatiotemporal chaos in fluid hows. It is found that the parameter region of spatiotemporal chaos can be determined by the maximal Liapunov exponent of its complexity time series. This simple model implies a similar physical mechanism for turbulence such that the route to spatiotemporal chaos in fluid hows can be envisaged.

The induction plasma chemical reactor: Part II. Kinetic model

A kinetic model has been developed for the prediction of the concentration gelds in an rf plasma reactor. A sample calculation for a SiCl4/H2 system is then performed. The model considers the mixing processes along with the kinetics of seven reactions involving the decomposition of these reactants. The results obtained are compared to those assuming chemical equilibrium. The predictions indicate that an equilibrium assumption will result in lower predicted temperature fields in the reactor. Furthermore, for the chemical system considered here, while differences exist between the concentration fields obtained by the two models, the differences are not substantial.

Prediction of particle distribution in isotropic turbulence by large-eddy simulation

The recent application of large-eddy simulation (LES) to particle-laden turbulence requires that the LES with a subgrid scale (SGS) model could accurately predict particle distributions. Usually, a SGS particle model is used to recover the small-scale structures of velocity fields. In this study, we propose a rescaling technique to recover the effects of small-scale motions on the preferential concentration of inertial particles. The technique is used to simulate particle distribution in isotropic turbulence by LES and produce consistent results with direct numerical simulation (DNS). Key words: particle distribution, particle-laden turbulence, large-eddy simulation, subgrid scale model.

Prediction Of Shear-Band Thickness In Metallic Glasses

We derive an explicit expression for predicting the thicknesses of shear bands in metallic glasses. The model demonstrates that the shear-band thickness is mainly dominated by the activation size of the shear transformation zone (STZ) and its activation free volume concentration. The predicted thicknesses agree well with the results of measurements and simulations. The underlying physics is attributed to the local topological instability of the activated STZ. The result is of significance in understanding the origin of inhomogeneous flow in metallic glasses. (C) 2009 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Prediction of Effective Moduli of Carbon Nanotube-Reinforced Composites with Waviness and Debonding

Carbon nanotubes (CNTs) have been regarded as ideal reinforcements of high-performance composites with enormous applications. However, the waviness of the CNTs and the interfacial bonding condition between them and the matrix are two key factors that influence the reinforcing efficiency. In this paper, the effects of the waviness of the CNTs and the interfacial debonding between them and the matrix on the effective moduli of CNT-reinforced composites are studied. A simple analytical model is presented to investigate the influence of the waviness on the effective moduli. Then, two methods are proposed to examine the influence of the debonding. It is shown that both the waviness and debonding can significantly reduce the stiffening effect of the CNTs. The effective moduli are very sensitive to the waviness when the latter is small, and this sensitivity decreases with the increase of the waviness. (C) 2008 Elsevier Ltd. All rights reserved.

A Dynamic Model For Ice-Induced Vibration Of Structures

A dynamic model for the ice-induced vibration (IIV) of structures is developed in the present study. Ice properties have been taken into account, such as the discrete failure, the dependence of the crushing strength on the ice velocity, and the randomness of ice failure. The most important prediction of the model is to capture the resonant frequency lock-in, which is analog to that in the vortex-induced vibration. Based on the model, the mechanism of resonant IIV is discussed. It is found that the dependence of the ice crushing strength on the ice velocity plays an important role in the resonant frequency lock-in of IIV. In addition, an intermittent stochastic resonant vibration is simulated from the model. These predictions are supported by the laboratory and field observations reported. The present model is more productive than the previous models of IIV.

Few-cycle spatiotemporal soliton wave excited by filamentation of a femtosecond laser pulse in materials with anomalous dispersion

The nonlinear dynamics of 1.6-mu m fs laser pulses propagating in fused silica is investigated by employing a full-order dispersion model. Different from the x-wave generation in normally dispersive media, a few-cycle spatiotemporally compressed soliton wave is generated with the contrary contributions of anomalous group velocity dispersion (GVD) and self-phase-modulation. However, at the tailing edge of the pulse forms a shock wave which generates separate and strong supercontinuum peaked at 670 nm. It is also the origin of conical emission formed both in time and frequency domain with the contribution of normal GVD at visible light.

Prediction and elucidation of the population dynamics of Microcystis spp. in Lake Dianchi (China) by means of artificial neural networks

Lake Dianchi is a shallow and turbid lake, located in Southwest China. Since 1985, Lake Dianchi has experienced severe cyanabacterial blooms (dominated by Microcystis spp.). In extreme cases, the algal cell densities have exceeded three billion cells per liter. To predict and elucidate the population dynamics ofMicrocystis spp. in Lake Dianchi, a neural network based model was developed. The correlation coefficient (R 2) between the predicted algal concentrations by the model and the observed values was 0.911. Sensitivity analysis was performed to clarify the algal dynamics to the changes of environmental factors. The results of a sensitivity analysis of the neural network model suggested that small increases in pH could cause significantly reduced algal abundance. Further investigations on raw data showed that the response of Microcystis spp. concentration to pH increase was dependent on algal biomass and pH level. When Microcystis spp. population and pH were moderate or low, the response of Microcystis spp. population would be more likely to be positive in Lake Dianchi; contrarily, Microcystis spp. population in Lake Dianchi would be more likely to show negative response to pH increase when Microcystis spp. population and pH were high. The paper concluded that the extremely high concentration of algal population and high pH could explain the distinctive response of Microcystis spp. population to +1 SD (standard deviation) pH increase in Lake Dianchi. And the paper also elucidated the algal dynamics to changes of other environmental factors. One SD increase of water temperature (WT) had strongest positive relationship with Microcystis spp. biomass. Chemical oxygen demand (COD) and total phosphorus (TP) had strong positive effect on Microcystis spp. abundance while total nitrogen (TN), biological oxygen demand in five days (BOD5), and dissolved oxygen had only weak relationship with Microcystis spp. concentration. And transparency (Tr) had moderate positive relationship with Microcystis spp. concentration.

Analysis of steric mass-action model for protein adsorption equilibrium onto porous anion-exchange adsorbent

The ion-exchange equilibrium of bovine serum albumin (BSA) to an anion exchanger, DEAE Spherodex M, has been studied by batch adsorption experiments at pH values ranging from 5.26 to 7.6 and ionic strengths from 10 to 117.1 mmol/l. Using the unadjustable adsorption equilibrium parameters obtained from batch experiments, the applicability of the steric mass-action (SMA) model was analyzed for describing protein ion-exchange equilibrium in different buffer systems. The parametric sensitivity analysis was performed by perturbing each of the model parameters, while holding the rest constant. The simulation results showed that, at high salt concentrations or low pHs close to the isoelectric point of the protein, the precision of the model prediction decreased. Parametric sensitivity analysis showed that the characteristic charge and protein steric factor had the largest effects on ion-exchange equilibrium, while the effect of equilibrium constant was about 70%-95% smaller than those of characteristic charge and steric factor under all conditions investigated. The SMA model with the relationship between the adjusted characteristic charge and the salt concentration can well predict the protein adsorption isotherms in a wide pH range from 5.84 to 7.6. It is considered that the SMA model could be further improved by taking into account the effect of salt concentration on the intermolecular interactions of proteins. (c) 2006 Elsevier Ltd. All rights reserved.

First-principles prediction of the magnetism of 3d transition-metal-doped Rocksalt MgO

Using first-principles band structure methods, we have systematically studied the electronic structures, magnetic stabilities, and half-metal properties of 3d transition-metal (TM) doped Rocksalt MgO compounds TMMg3O4 (TM = V, Cr, Mn, Fe, Co, and Ni). The calculations reveal that only CrMg3O4 has a ferromagnetic stability among the six compounds, which is explained by double-exchange mechanism. The magnetic stability is affected by the doping concentration of TM if the top valance band is composed of partially occupied t(2g) states. In addition, CrMg3O4 is a half-metallic ferromagnet. The origins of half-metallic and ferromagnetic properties are explored. The Curie temperature (T-c) of CrMg3O4 is 182 K. And it is hard for CrMg3O4 to deform due to the large bulk modulus and shear modulus, so it is a promising spintronic material. Our calculations provide the first available information on the magnetic properties of 3d TM-doped MgO.

Kinetic Model Study on Enzymatic Hydrolysis of Cellulose Using Artificial Neural Networks

Enzymatic hydrolysis of cellulose was highly complex because of the unclear enzymatic mechanism and many factors that affect the heterogeneous system. Therefore, it is difficult to build a theoretical model to study cellulose hydrolysis by cellulase. Artificial neural network (ANN) was used to simulate and predict this enzymatic reaction and compared with the response surface model (RSM). The independent variables were cellulase amount X-1, substrate concentration X-2, and reaction time X-3, and the response variables were reducing sugar concentration Y-1 and transformation rate of the raw material Y-2. The experimental results showed that ANN was much more suitable for studying the kinetics of the enzymatic hydrolysis than RSM. During the simulation process, relative errors produced by the ANN model were apparently smaller than that by RSM except one and the central experimental points. During the prediction process, values produced by the ANN model were much closer to the experimental values than that produced by RSM. These showed that ANN is a persuasive tool that can be used for studying the kinetics of cellulose hydrolysis catalyzed by cellulase.

Species transformation of trace elements and their distribution prediction in dyestuff residue incineration

The release of heavy metals from the combustion of hazardous wastes is an environmental issue of increasing concern. The species transformation characteristics of toxic heavy metals and their distribution are considered to be a complex problem of mechanism. The behavior of hazardous dyestuff residue is investigated in a tubular furnace under the general condition of hazardous waste pyrolysis and gasfication. Data interpretation has been aided by parallel theoretical study based on a thermodynamic equilibrium model based on the principle of Gibbs free energy minimization. The results show that Ni, Zn, Mn, and Cr are more enriched in dyestuff residue incineration than other heavy metals (Hg, As, and Se) subjected to volatilization. The thermodynamic model calculation is used for explaining the experiment data at 800 degrees C and analyzing species transformation of heavy metals. These results of species transformation are used to predict the distribution and emission characteristics of trace elements. Although most trace element predictions are validated by the measurements, cautions are in order due to the complexity of incineration systems.

Study on Water Resources Regulation and Reservoir Operating Prediction for Suppression of Salt Water Intrusion in the Pearl River Estuary

Salt water intrusion occurred frequently during dry season in Modaomen waterway of the Pearl River Estuary. With the development of region's economy and urbanization, the salt tides affect the region's water supply more and more seriously in recent years. Regulation and allocation of freshwater resources of the upper rivers of the estuary to suppress the salt tides is becoming important measures for ensuring the water supply security of the region in dry season. The observation data analysis showed that the flow value at the Wuzhou hydrometric station on the upper Xijiang river had a good correlation with the salinity in Modaomen estuary. Thus the flow rate of Wuzhou has been used as a control variable for suppression of salt tides in Modaomen estuary. However, the runoff at Wuzhou mainly comes from the discharge of Longtan reservoir on the upper reaches of Xijiang river and the runoff in the interval open valley between Longtan and Wuzhou sections. As the long distance and many tributaries as well as the large non-controlled watershed between this two sections, the reservoir water scheduling has a need for reasonable considering of interaction between the reservoir regulating discharge and the runoff process of the interval open watershed while the deployment of suppression flow at Wuzhou requires longer lasting time and high precision for the salt tide cycles. For this purpose, this study established a runoff model for Longtan - Wuzhou interval drainage area and by model calculations and observation data analysis, helped to understand the response patterns of the flow rate at Wuzhou to the water discharge of Longtan under the interval water basin runoff participating conditions. On this basis, further discussions were taken on prediction methods of Longtan reservoir discharge scheduling scheme for saline intrusion suppression and provided scientific and typical implementation programs for effective suppression flow process at the Wuzhou section.

Hyperon coupling dependence of hadron matter properties in relativistic mean field model

The properties of hadronic matter at beta equilibrium in a wide range of densities are described by appropriate equations of state in the framework of the relativistic mean field model. Strange meson fields, namely the scalar meson field sigma*(975) and the vector meson field sigma*(1020), are included in the present work. We discuss and compare the results of the equation of state, nucleon effective mass, and strangeness fraction obtained by adopting the TM1, TMA, and GL parameter sets for nuclear sector and three different choices for the hyperon couplings. We find that the parameter set TM1 favours the onset of hyperons most, while at high densities the GL parameter set leads to the most hyperon-rich matter. For a certain parameter set (e.g. TM1), the most hyperon-rich matter is obtained for the hyperon potential model. The influence of the hyperon couplings on the effective mass of nucleon, is much weaker than that on the nucleon parameter set. The nonstrange mesons dominate essentially the global properties of dense hyperon matter. The hyperon potential model predicts the lowest value of the neutron star maximum mass of about 1.45 M-sun to be 0.4-0.5 M-sun lower than the prediction by using the other choices for hyperon couplings.