Molecular dynamics simulation on flow behavior of nanofluids between flat plates under shear flow condition

Molecular dynamic model of nanofluid between flat plates under shear flow conditions was built. The nanofluid model consisted of 12 spherical copper nanoparticles with each particle diameter of 4 nm and argon atoms as base liquid. The Lennard–Jones (LJ) potential function was adopted to deal with the interactions between atoms. Thus, the motion states of nanoparticles during the process of flowing were obtained and the flow behaviors of nanofluid between flat plates at different moments could be analyzed. The simulation results showed that an absorption layer of argon atoms existed surrounding each nanoparticle and would accompany with the particle to move. The absorption layer contributed little to the flow of nanoparticles but much to the heat transferring in nanofluids. Another phenomenon observed during shear flowing process was that the nanoparticles would vibrate and rotate besides main flowing with liquid argon and these micro-motions could strengthen partial flowing in nanofluids.     

Molecular dynamics simulation of nanofluid’s flow behaviors in the near-wall model and main flow model

The flow behaviors of nanofluids were studied in this paper using molecular dynamics (MD) simulation. Two MD simulation systems that are the near-wall model and main flow model were built. The nanofluid model consisted of one copper nanoparticle and liquid argon as base liquid. For the near-wall model, the nanoparticle that was very close to the wall would not move with the main flowing due to the overlap between the solid-like layer near the wall and the adsorbed layer around the nanoparticle, but it still had rotational motion. When the nanoparticle is far away from the wall (d > 11 Å), the nanoparticle not only had rotational motion, but also had translation. In the main flow model, the nanoparticle would rotate and translate besides main flowing. There was slip velocity between nanoparticles and liquid argon in both of the two simulation models. The flow behaviors of nanofluids exhibited obviously characteristics of two-phase flow. Because of the irregular motions of nanoparticles and the slip velocity between the two phases, the velocity fluctuation in nanofluids was enhanced.     

Nanofluids thermal conductivity prediction applying a novel hybrid data-driven model validated using Monte Carlo-based sensitivity analysis

Accurate estimation of the thermal conductivity of nanofluids plays a key role in industrial heat transfer applications. Currently available experimental and empirical relationships can be used to estimate thermal conductivity. However, since the environmental conditions and properties of the nanofluids constituents are not considered these models cannot provide the expected accuracy and reliability for researchers. In this research, a robust hybrid artificial intelligence model was developed to accurately predict wide variety of relative thermal conductivity of nanofluids. In the new approach, the improved simulated annealing (ISA) was used to optimize the parameters of the least-squares support vector machine (LSSVM-ISA). The predictive model was developed using a data bank, consist of 1800 experimental data points for nanofluids from 32 references. The volume fraction, average size and thermal conductivity of nanoparticles, temperature and thermal conductivity of base fluid were selected as influent parameters and relative thermal conductivity was chosen as the output variable. In addition, the obtained results from the LSSVM-ISA were compared with the results of the radial basis function neural network (RBF-NN), K-nearest neighbors (KNN), and various existing experimental correlations models. The statistical analysis shows that the performance of the proposed hybrid predictor model for testing stage (R = 0.993, RMSE = 0.0207) is more reliable and efficient than those of the RBF-NN (R = 0.970, RMSE = 0.0416 W/m K), KNN (R = 0.931, RMSE = 0.068 W/m K) and all of the existing empirical correlations for estimating thermal conductivity of wide variety types of nanofluids. Finally, robustness and convergence analysis were conducted to evaluate the model reliability. A comprehensive sensitivity analysis using Monte Carlo simulation was carried out to identify the most significant variables of the developed models affecting the thermal conductivity predictions of nanofluids.

     

Scientometric Study of the Progress and Development of e-Government Research During the Period 2000–2012

Many countries have implemented changes in public-sector management models, based on the strategic and intensive use of new information and communication technologies. From a critical standpoint, this paper analyzes and characterizes the contributions made by research in the field of e-government, identifying future areas of interest and potentially valuable methodologies. In addition, it compares research efforts focused on developing countries with those concerning developed economies, in order to identify research gaps and possibilities for improvement in the context of e-government research in developing countries. Diverse scientometric approaches are employed in this analysis of papers published by international journals listed in the SSCI index in the fields of Public Administration and of Information Science & Library Science. Our findings reveal the existence of various research gaps and highlight areas that should be addressed in future research, especially in developing countries. Indeed, the research approach to e-government remains immature, focusing on particular cases or dimensions, while little has been done to produce theories or models to clarify and explain the political processes of e-government. In addition, significant differences are found between the impact of scientific output and patterns of scientific production as regards developing and developed countries.     

An approach to integrating shape and biomedical attributes in vascular models

Computational models have been used widely in tissue engineering research and have proven to be powerful tools for bio-mechanical analysis (i.e., blood flow, growth models, drug delivery, etc). This paper focuses on developing higher-fidelity models for vascular structures and blood vessels that integrate computational shape representations with biomedical properties and features. Previous work in computer-aided vascular modeling comes from two communities. For those in biomedical imaging, the goal of past research has been to develop image understanding techniques for the interpretation of x-ray, magnetic resonance imaging (MRI), or other radiological data. These representations are predominantly discrete shape models that are not tied to physiological properties. The other corpus of existing work comes from those interested in developing physiological models for vascular growth and behavior based on bio-medical attributes. These models usually either have a highly simplified shape representation, or lack one entirely. Further, neither of these representations are suitable for the kind of interactive modeling required by tissue engineering applications.This paper aims to bridge these two approaches and develop a set of mathematical tools and algorithms for feature-based representation and computer-aided modeling of vascular trees for use in computer-aided tissue engineering applications. The paper offers a multi-scale representation based on swept volumes and a feature-based representation that can attribute the geometric representation with information about blood flow, pressure, and other biomedical properties. The paper shows how the resulting representation can be used as part of an overall approach for designing and visualizing vascular scaffolds. As a real-world example, we show how this computational model can be used to develop a tissue scaffold for liver tissue engineering. Such scaffolds may prove useful in a number of biomedical applications, including the growth of replacement tissue grafts and in vitro study of the pharmacological affects of new drugs on tissue cultures.     

Green synthesis of silver nanoparticles-based nanofluids and investigation of their antimicrobial activities

We have proposed a facile green technique for synthesizing silver nanoparticles-based nanofluids at high temperature and pressure using low molecular weight lactulose solution, which is playing the role of a reducing as well as stabilizing agent. The particle/crystallite sizes, morphology, crystallinity of the nanoparticles are characterized using spectroscopic, microscopic, and diffraction techniques. Since the properties of nanofluids are attractive for technological applications, the investigation of their thermal and electrical conductivities is also immensely important. The material shows a significant enhancement of both thermal and electrical conductivities in comparison to the base fluid due to high surface area, enhanced Brownian motion and layering at the liquid–solid interface of the nanofluids. Moreover, these nanofluids offer excellent antimicrobial activities to different gram class bacteria.     

Comparing classical and neural regression techniques in modeling crude oil viscosity

The importance of crude oil viscosity makes its accurate determination necessary for reservoir performance calculations, evaluation of hydrocarbon reserves, planning thermal methods of enhanced oil recovery, and designing production equipment and pipelines. Viscosity data are also involved in several dimensionless parameters to calculate flow regimes, friction factors and pressure gradients in multiphase flow problems. Numerous research efforts have been directed towards the development of viscosity models that are capable of accurately predicting crude oil viscosity as a function of production data, and/or composition of well stream fluids, if available, using equation of State. Since fluid compositions are not always available, most of the efforts were focused on developing viscosity correlations using classical regression techniques.The study presents, for the first time, a comparison among several models developed using both classical regression techniques (CRT) and neural regression techniques (NRT). These models are developed in this study from viscosity data collected from different oil fields. The models have also been tested using another collection of viscosity data that was not used before in the development phase. Results show that viscosity models developed using NRT were more accurate than viscosity models developed using CRT. Based on this comparison, a viscosity model is therefore presented, which uses stock-tank oil API gravity, gas gravity, pressure(s), and temperature(s) to predict crude oil viscosity. The model was developed using General Regression Neural Network algorithm.     

Experimental study of thermal conductivity and phase change performance of nanofluids PCMs

A new sort of nanofluids phase change materials (PCMs) is developed by suspending small amount of TiO₂ nanoparticles in saturated BaCl₂ aqueous solution. The resulting nanofluids PCMs possess remarkably high thermal conductivities compared to the base material. Cool storage/supply experiments conducted in a small apparatus have shown the excellent phase change performance of the nanofluids PCMs. The cool storage/supply rate and the cool storage/supply capacity all increase greatly those that of BaCl₂ aqueous solution without added nanoparticles. The higher thermal performances of nanofluids PCMs indicate that they have a potential for substituting conventional PCMs in cool storage applications.     

涌现视角下的网络空间安全挑战

网络空间的安全性属于涌现属性,该属性给网络空间安全带来了严峻的挑战.国内外已有不少研究者关注网络空间安全的涌现现象,迄今已取得不少成果.然而,人们对网络空间安全涌现性的认识还非常不足.针对这一状况,从涌现性的视角对网络空间安全挑战进行全面考察,旨在促进网络空间安全新思想、新理论的发展.首先,从系统科学中的涌现性的本意出发,揭示网络空间安全涌现性的基本思想;其次,从攻击、漏洞和防御3个角度,考察网络空间中存在的涌现式安全挑战;然后,按描述性、指导性和操作性3种类型,分析网络空间安全涌现性研究的发展状况;最后,从基础理论、基本模型和实用工具3个方面,讨论开展未来工作的基本途径.     

The effects of augmented virtual science laboratories on middle school students' understanding of gas properties

The Next Generation Science Standards (NGSS) emphasize authentic scientific practices such as developing models and constructing explanations of phenomena. However, research documents how students struggle to explain observable phenomena with molecular-level behaviors with current classroom experiences. For example, physical laboratory experiences in science enable students to interact with observable scientific phenomena, but students often fail to make connections to underlying molecular-level behaviors. Virtual laboratory experiences and computer-based visualizations enable students to interact with unobservable scientific concepts, but students can have difficulties connecting to actual instantiations of the observed phenomenon. This paper investigates how combining physical and virtual experiences into augmented virtual science laboratories can help students build upon intuitive ideas and develop molecular-level explanations of macroscopic phenomena. Specifically, this study uses the Frame, a sensor-augmented virtual lab that uses sensors as physical inputs to control scientific simulations. Eighth-grade students (N = 45) engaged in a Frame lab focused on the properties of gas. Results demonstrate that students using the Frame lab made progress developing molecular-level explanations of gas behavior and refining alternative and partial ideas into normative ideas about gases. This study offers insights for how augmented virtual labs can be designed to enhance science learning and encourage scientific practices as called for in the NGSS.     

Chasing a Definition of “Alarm”

Alarm management has been around for decades in telecom solutions. We have seen various efforts to define standardised alarm interfaces. The research community has focused on various alarms correlation strategies. Still, after years of effort in industry and research alike, network administrators are flooded with alarms; alarms are suffering from poor information quality; and the costs of alarm integration have not decreased. In this paper, we explore the concept of ‘alarm’. We define ‘alarm’ and alarm-type concepts by investigating the different definitions currently in use in standards and research efforts. Based on statistical alarm data from a mobile operator we argue that operational and capital expenditures would decrease if alarm sources would apply to our alarm model.     

Thermally developing electroosmotic transport of nanofluids in microchannels

A theoretical analysis is presented in this work to assess the influence of nanofluids on thermally developing and hydrodynamically developed electroosmotic transport in parallel plate microchannels (Graetz problem). The hydraulic diameters of the microchannels are assumed to be beyond a certain threshold limit, so that the electric double layers formed adjacent to the plates do not overlap with each other. The volumetric heating arising from the conduction currents in the flow is modeled using Ohm’s law. The viscous generation terms in the energy equation are neglected, based on the earlier findings that the consequent effects are negligible as compared to the Joule heating effects in electroosmotically driven microchannel flows. Closed form expressions for the pertinent temperature distributions and the Nusselt number variations are obtained by employing the method of separation of variables in conjunction with an eigen value formulation, in order to assess the influence of volume fraction of the dispersed nano-particles on the overall rates of convective transport. It is revealed that the effects of nano-particles in the fluid turn out to be significant in the thermal entrance region only, especially for higher Peclet number values. The implications of the incorporation of nanofluids are demonstrated to be somewhat non-trivial in nature, and are strongly determined by the effective Peclet number values obtained on the basis of the phase-integral values of the thermo-physical properties and the pertinent flow parameters.     

Ferrofluid actuation with varying magnetic fields for micropumping applications

Magnetic nanoparticle suspensions and their manipulation are becoming an alternative research line. They have vital applications in the field of microfluidics such as microscale flow control in microfluidic circuits, actuation of fluids in microscale, and drug delivery mechanisms. In microscale, it is possible and beneficial to use magnetic fields as actuators of such ferrofluids, where these fluids could move along a dynamic gradient of magnetic field so that a micropump could be generated with this technique. Thus, magnetically actuated ferrofluids could have the potential to be used as an alternative micro pumping system. Magnetic actuation of nanofluids is becoming an emergent field that will open up new possibilities in various fields of engineering. Different families of devices actuating ferrofluids were designed and developed in this study to reveal this potential. A family of these devices actuates discrete plugs, whereas a second family of devices generates continuous flows in tubes of inner diameters ranging from 254?μm to 1.56?mm. The devices were first tested with minitubes to prove the effectiveness of the proposed actuation method. The setups were then adjusted to conduct experiments on microtubes. Promising results were obtained from the experiments. Flow rates up to 120 and 0.135?μl/s were achieved in minitubes and microtubes with modest maximum magnetic field magnitudes of 300?mT for discontinuous and continuous actuation, respectively. The proposed magnetic actuation method was proven to work as intended and is expected to be a strong alternative to the existing micropumping methods such as electromechanical, electrokinetic, and piezoelectric actuation. The results suggest that ferrofluids with magnetic nanoparticles merit more research efforts in micro pumping.     

Particle and thermohydraulic maldistribution of nanofluids in parallel microchannel systems

A deep understanding of fluidic maldistribution in microscale multichannel devices is necessary to achieve optimized flow and heat transfer characteristics. A detailed computational study has been performed using an Eulerian–Lagrangian twin-phase model to determine the concentration and thermohydraulic maldistributions of nanofluids in parallel microchannel systems. The study reveals that nanofluids cannot be treated as homogeneous single-phase fluids in such complex flow situations, and effective property models drastically fail to predict the performance parameters. To comprehend the distribution of the particulate phase, a novel concentration maldistribution factor has been proposed. It has been observed that the distribution of particles does not entirely follow the fluid flow pattern, leading to thermal performance that deviates from those predicted by homogeneous models. Particle maldistribution has been conclusively shown to be due to various migration and diffusive phenomena such as Stokesian drag, Brownian motion and thermophoretic drift. The implications of particle distribution on the cooling performance have been illustrated, and smart fluid effects (reduced magnitude of maximum temperature in critical zones) have been observed for nanofluids. A comprehensive mathematical model to predict the enhanced cooling performance in such flow geometries has been proposed. The article clearly highlights the effectiveness of discrete phase approach in modeling nanofluid thermohydraulics and sheds insight on the specialized behavior of nanofluids in complex flow domains.     

Precipitation phenomenon of nanoparticles in power-law fluids over a rotating disk

The steady flow and mass transfer of nanofluids with power-law type base fluids over a free-rotating disk are investigated. Previously, we have modeled the volume fraction of nanoparticles and verified the experimental conclusion through the numerical simulation of particle distribution in nanofluid in a Petri dish under the influence of movement using a power-law model of mass diffusivity. We further this study by a similar model of the mass diffusivity following a power-law type to consider the laminar non-Newtonian power-law flow in a rotating infinite disk with angular velocity about the z-axis. The coupled governing equations are transformed into ODEs. Homotopy analysis method (HAM) is applied to solve the ODEs while special attention is paid to deal with the nonlinear items in the ODEs. In the last section, we provide images of nanoparticles suspended in power-law fluids in a rotating disk as obtained using the laser speckle method. When they are compared with the analytical results gained by the HAM, they qualitatively matched the solutions of the concentration equation of nanofluids.     

Theoretical and practical issues in evaluating the quality of conceptual models: current state and future directions

An international standard has now been established for evaluating the quality of software products. However there is no equivalent standard for evaluating the quality of conceptual models. While a range of quality frameworks have been proposed in the literature, none of these have been widely accepted in practice and none has emerged as a potential standard. As a result, conceptual models continue to be evaluated in practice in an ad hoc way, based on common sense, subjective opinions and experience. For conceptual modelling to progress from an “art” to an engineering discipline, quality standards need to be defined, agreed and applied in practice. This paper conducts a review of research in conceptual model quality and identifies the major theoretical and practical issues which need to be addressed. We consider how conceptual model quality frameworks can be structured, how they can be developed, how they can be empirically validated and how to achieve acceptance in practice. We argue that the current proliferation of quality frameworks is counterproductive to the progress of the field, and that researchers and practitioners should work together to establish a common standard (or standards) for conceptual model quality. Finally, we describe some initial efforts towards developing a common standard for data model quality, which may provide a model for future standardisation efforts.     

Microfluidic synthesis of copper nanofluids

Copper nanofluids have been chemically synthesized by using home-made microfluidic reactors and by using a boiling flask-3-neck. The influence of flow rates of reactants, reactants concentrations, and surfactant concentrations on copper particle size and size distribution has been investigated. It has been found that neither of them has much influence on particle size and size distribution of copper nanoparticles synthesized in microfluidic reactors due to the fast and efficient mass diffusion in microscale dimension. The copper nanoparticles have an average size of about 3.4 nm with a relatively narrow size distribution of around 22% evaluated by the coefficient of variation. While the average size of copper nanoparticles synthesized by flask method changes from 2.7 to 4.9 nm with a coefficient of variation larger than 30%, depending on concentrations of [Cu(NH₃)₄]·(OH)₂ and surfactant sodium dodecylbenzenesulfonate. In addition, by using microfluidic reactors the synthesis time of copper nanofluids can be reduced as much as one order of magnitude, from ~10 min to ~28 s.     

Representations in Human–Computer Systems Development

When system developers design a computer system (or other information artefact), they must inevitably make judgements as to how to abstract the domain and how to represent this abstraction in their designs. Over the years human–computer interaction, or more generally information systems design, has had a history of developing competing methods and models for both the process and products of its development. Various paradigms have been suggested, often trying to keep pace with the changing nature of the design problem; from batch processing to interactive systems to work situations and most recently to designing for household environments. It appears timely, then, to review the nature of the design problem that faces the developers of human–computer systems and to consider some of the impact that different representations and different conceptualisations may have on their activities. Green (1998) has suggested that a single model of developing human–computer systems is not desirable, instead arguing for a number of limited theories each of which provides a useful perspective. The aim of this paper is to place competing methods side by side in order to see their strengths and weaknesses more clearly. The central tenet of the paper is that different views of both the human–computer system design process and the different abstractions, or models, that are produced during the design process have varying degrees of utility for designers. It is unlikely that any single method or modelling approach will be optimal in all circumstances. Designers need to be aware of the range of views that exist and of the impact that taking a particular approach may have on the design solution.     

Microdroplet formation of water and nanofluids in heat-induced microfluidic T-junction

This paper reports experimental investigations on the droplet formation and size manipulation of deionized water (DIW) and nanofluids in a microfluidic T-junction at different temperatures. Investigations of the effect of microchannel depths on the droplet formation process showed that the smaller the depth of the channel the larger the increase of droplet size with temperature. Sample nanofluids were prepared by dispersing 0.1 volume percentage of titanium dioxide (TiO₂) nanoparticles of 15 nm and 10 nm × 40 nm in DIW for their droplet formation experiments. The heater temperature also affects the droplet formation process. Present results demonstrate that nanofluids exhibit different characteristics in droplet formation with the temperature. Addition of spherical-shaped TiO₂ (15 nm) nanoparticles in DIW results in much smaller droplet size compared to the cylindrical-shaped TiO₂ (10 nm × 40 nm) nanoparticles. Besides changing the interfacial properties of based fluid, nanoparticles can influence the droplet formation of nanofluids by introducing interfacial slip at the interface. Other than nanofluid with cylindrical-shaped nanoparticles, the droplet size was found to increase with increasing temperature.     

A study of mobile internet user’s service quality perceptions from a user’s utilitarian and hedonic value tendency perspectives

Although a few studies have focused on mobile value from the distinctive feature of a mobile technology perspective, limited attempts have been made from a mobile user’s value tendency perspective. In this study, building upon prior research on productivity-oriented and pleasure-oriented nature of systems, we categorize mobile values as having utilitarian and hedonic use. Based on these two values, we conceptualize types of tendency of mobile users’ application use namely utilitarian tendency and hedonic tendency. The goal of this study is to examine the relationships between mobile consumers’ value tendency and their perceptions of mobile Internet service quality in terms of three different mobile quality dimensions (i.e., connection quality, design quality, and information quality). In addition, drawing upon the “digital divide” literature, the relationships between mobile users’ personal dispositions (i.e., maturity and socio-economic status) and their mobile value tendency are also tested. The empirical results of the study, the interpretation of the results, research contributions, and limitations are discussed.