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Article:Hoyle, B.S., Jia, X., Podd, F.J.W. et al. (6 more authors) (2001) Design and application of a multi-modal process tomography system. Measurement Science and Technology, 12 (8 ABSTRACTThis paper presents a design and application study of an integrated multi-modal system designed to support a range of common modalities: electrical resistance, electrical capacitance and ultrasonic tomography. Such a system is designed for use with complex processes that exhibit behaviour changes over time and space, and thus demand equally diverse sensing modalities. A multi-modal process tomography system able to exploit multiple sensor modes must permit the integration of their data, probably centred upon a composite process model. The paper presents an overview of this approach followed by an overview of the systems engineering and integrated design constraints. These include a range of hardware oriented challenges: the complexity and specificity of the front end electronics for each modality; the need for front end data pre-processing and packing; the need to integrate the data to facilitate data fusion; and finally the features to enable successful fusion and interpretation. A range of software aspects are also reviewed: the need to support differing front-end sensors for each modality in a generic fashion; the need to communicate with front end data pre-processing and packing systems; the need to integrate the data to allow data fusion; and finally to enable successful interpretation. The review of the system concepts is illustrated with an application to the study of a complex multi-component process.

An experimental and numerical investigation on natural convection heat transfer of TiO2–water nanofluids in a square enclosure was carried out for the present work. TiO2–water nanofluids with different nanoparticle mass fractions were prepared for the experiment and physical properties of the nanofluids including thermal conductivity and viscosity were measured. Results show that both thermal conductivity and viscosity increase when increasing the mass fraction of TiO2 nanoparticles. In addition, the thermal conductivity of nanofluids increases, while the viscosity of nanofluids decreases with increasing the temperature. Nusselt numbers under different Rayleigh numbers were obtained from experimental data. Experimental results show that natural convection heat transfer of nanofluids is no better than water and even worse when the Rayleigh number is low. Numerical studies are carried out by a Lattice Boltzmann model (LBM) coupling the density and the temperature distribution functions to simulate the convection heat transfer in the enclosure. The experimental and numerical results are compared with each other finding a good match in this investigation, and the results indicate that natural convection heat transfer of TiO2–water nanofluids is more sensitive to viscosity than to thermal conductivity.

in Wiley Online Library (wileyonlinelibrary.com) Collisions between frictional particles and flat walls are determined using Coulomb friction and both tangential and normal restitution, and pseudothermal states of particles are described by both the translational and rotational granular temperatures. Then, new models for the stresses and the fluxes of fluctuation energy for the collisional granular flows at the walls are derived. These new models are tested and compared with the literature data and models. The ratio of rotational to translational granular temperatures is shown to be crucial on accurately predicting the shear stress and energy flux and is dependent on the normalized slip velocity as well as the collisional parameters. Using a theoretical but constant value for this ratio, predictions by the new models could still agree better with the literature data than those by the previous models. Finally, boundary conditions are developed to be used within the framework of kinetic theory of granular flow. V C 2014 American Institute of Chemical Engineers AIChE J, 60: 4065-4075, 2014 Figure 4. Stress ratio over normalized slip velocity for different coefficients of normal restitution. (The lines and symbol have the same meaning as in Figure 3. Besides, red dashed line ---: present model with specified k. Inset: red dashed line ---: specified k.) [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] 4070