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Thermal conductivity and rheology behavior of aqueous nanofluids containing alumina and carbon nanotubes
This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.In this study, thermal conductivity and rheology behavior of aqueous alumina and multi-walled carbon nanotube (MWCNT) nanofluids were measured and compared with several analytical models. Both thermal conductivity and viscosity of the two nanofluids increase with increasing volume fraction. The experimental thermal conductivity data for the two nanofluids are located near the lower Hashin-Shtrikman bound and far away from the upper Hashin-Shtrikman bound. Therefore there is still enough room for thermal conductivity enhancement. Further conductivity enhancement of the nanofluids can be achieved by manipulating particle or agglomeration distribution and morphology. The structure-property relationship was checked for the nanofluids. Possible agglomeration size and interfacial thermal resistance were obtained and partially validated. Based on the Chen et al. model, a revised model was developed by incorporating the effects of interfacial thermal resistance into the Hamilton-Crosser model. The revised model can accurately reproduce the experimental data based on the agglomeration size extracted from the rheology analysis. In addition, thermal conductivity change of the alumina/water nanofluid with elapsed time was also investigated. The average thermal conductivity decreases with elapsed time. Besides, thermal conductivity measurements were conducted for nanofluid mixtures of alumina/water and MWCNT/water nanofluids
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Effect of surfactant on flow boiling heat transfer of ethylene glycol/water mixtures in a mini-tube
This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.In this study, the effect of adding a surfactant (sodium dodeobcylbenzene sulfonate, SDBS) to ethylene glycol/water mixtures boiling in a vertical mini-tube was studied. Experiments were done using solutions containing 300 ppm by weight of surfactant and the results were compared with those for pure mixture. Local heat transfer coefficient was measured and found to be dependent on the mass quality. Addition of surfactant significantly enhanced the evaporation of saturated liquid, so that the difference between outlet fluid temperature and outlet bubble point temperature of SDBS solutions was much higher than that of ethylene glycol/water mixture. Though the surfactant intensifies the vaporization process, it does not necessarily enhance the heat transfer coefficient. The heat transfer coefficients at two different mass fluxes were compared, and the result could be explained based on the local flow pattern and heat transfer mechanism. After a critical quality, higher quality will deteriorate the heat transfer due to intermittent dryout, therefore adding surfactant to generate more vapor may have a negative effect on the heat transfer of flow boiling in a mini-tube, which is contrast to the experience of enhancing nucleate pool boiling heat transfer with trace surfactant
Global behavior of cosmological dynamics with interacting Veneziano ghost
In this paper, we shall study the dynamical behavior of the universe
accelerated by the so called Veneziano ghost dark energy component locally and
globally by using the linearization and nullcline method developed in this
paper. The energy density is generalized to be proportional to the Hawking
temperature defined on the trapping horizon instead of Hubble horizon of the
Friedmann-Robertson-Walker (FRW) universe. We also give a prediction of the
fate of the universe and present the bifurcation phenomenon of the dynamical
system of the universe. It seems that the universe could be dominated by dark
energy at present in some region of the parameter space.Comment: 8 pages, 7 figures, accepted for publication in JHE
On tree amplitudes with gluons coupled to gravitons
In this paper, we study the tree amplitudes with gluons coupled to gravitons.
We first study the relations among the mixed amplitudes. With BCFW on-shell
recursion relation, we will show the color-order reversed relation,
-decoupling relation and KK relation hold for tree amplitudes with gluons
coupled to gravitons. We then study the disk relation which expresses mixed
amplitudes by pure gluon amplitudes. More specifically we will prove the disk
relation for mixed amplitudes with gluons coupled to one graviton. Using the
disk relation and the properties of pure gluon amplitudes, the color-order
reversed relation, -decoupling relation and KK relation for mixed
amplitudes can also be proved. Finally, we give some brief discussions on
BCJ-like relation for mixed amplitudes.Comment: 33pages,no figur
A 3D Face Modelling Approach for Pose-Invariant Face Recognition in a Human-Robot Environment
Face analysis techniques have become a crucial component of human-machine
interaction in the fields of assistive and humanoid robotics. However, the
variations in head-pose that arise naturally in these environments are still a
great challenge. In this paper, we present a real-time capable 3D face
modelling framework for 2D in-the-wild images that is applicable for robotics.
The fitting of the 3D Morphable Model is based exclusively on automatically
detected landmarks. After fitting, the face can be corrected in pose and
transformed back to a frontal 2D representation that is more suitable for face
recognition. We conduct face recognition experiments with non-frontal images
from the MUCT database and uncontrolled, in the wild images from the PaSC
database, the most challenging face recognition database to date, showing an
improved performance. Finally, we present our SCITOS G5 robot system, which
incorporates our framework as a means of image pre-processing for face
analysis
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