3 results
A macrotransport equation for the Hele-Shaw flow of a concentrated suspension
- Sourojeet Chakraborty, Arun Ramachandran
-
- Journal:
- Journal of Fluid Mechanics / Volume 924 / 10 October 2021
- Published online by Cambridge University Press:
- 09 August 2021, A1
-
- Article
- Export citation
-
A depth-averaged, convection-dispersion equation is derived for the particle volume fraction distribution in the pressure-driven flow of a concentrated suspension of neutrally buoyant, non-colloidal particles between two parallel plates, by implementing a two-time-scale perturbation expansion of the suspension balance model (Nott & Brady, J. Fluid Mech., vol. 275, 1994, pp. 157–199) coupled with the constitutive equations of Zarraga et al. (J. Rheol., vol. 52, issue 2, 2000, pp. 185–220). The Taylor-dispersion coefficient in the macrotransport equation scales as $U_c^{\prime}B^{\prime 3}/a^{\prime 2}$, where $U_c^{\prime}$ is the characteristic depth-averaged velocity, $B^{\prime}$ is the half-depth of the channel and $a^{\prime}$ is the particle radius. Taylor dispersion relaxes gradients in the depth-averaged volume fraction along the local velocity vector. Perpendicular to the flow, however, only shear-induced migration can cause particle redistribution, leading to fluxes down gradients in volume fraction, shear rate and streamline curvature that scale as $U_c^{\prime}a^{\prime 2}/B^{\prime}$. To determine the velocity and particle distributions in Hele-Shaw suspension flows, one only needs to solve two coupled partial differential equations in the pressure and the depth-averaged volume fraction, achievable on commercially available solvers. Analogous to the macrotransport equation for suspension flow through a circular tube (Ramachandran, J. Fluid Mech., vol. 734, 2013, pp. 219–252), the evolution of the particle volume fraction distribution is dependent only on the total strain experienced by the suspension, and is independent of the suspension velocity scale. However, unlike the tube problem, a positive concentration gradient along the flow direction is susceptible to viscous miscible fingering. A linear stability analysis performed for a step increase in the volume fraction in the direction of flow with a velocity $U^{\prime}$ reveals that the growth rate and wavenumber corresponding to fastest growing mode scale as $U^{\prime}a^{\prime 2}/B^{\prime 3}$ and $a^{\prime 2/3}/B^{\prime 5/3}$, respectively.
Effects of flux concentrations and sintering temperature on dental porcelain
- Polash Ghose, Md. Abdul Gafur, Sujan Kumar Das, Shyamal Ranjan Chakraborty, Md. Mohsin, Arun Kumar Deb, Md. Rakibul Qadir
-
- Journal:
- The European Physical Journal - Applied Physics / Volume 65 / Issue 2 / February 2014
- Published online by Cambridge University Press:
- 14 February 2014, 20701
- Print publication:
- February 2014
-
- Article
- Export citation
-
In this study, samples of dental porcelain bodies have been made by using the materials collected from selected deposits employing different mixing proportions of clay, quartz and feldspar. Dental porcelain ceramics have been successfully fabricated by using the sintering technique together with some Na2CO3 additive. The dental porcelain powder has been pressed into pellets at first and subsequently sintered at 700, 800, 900, 1000 and 1100 °C for 2 h. The physical and mechanical properties of the prepared samples have been investigated. The sintering behavior of the fired samples has been evaluated by bulk density, linear shrinkage, water absorption and apparent porosity measurements. This study includes the evaluation of the Vickers’s microhardness by microhardness tester. Phase analysis and microstructural study have been performed by XRD and optical microscope respectively. Optical properties have been investigated using UV-visible spectroscopy. Influence of firing conditions on leucite formation, densification and microstructural development of the sintered samples has been investigated. It has been found that the choice of sintering temperature is one of the key factors in controlling leucite crystallization in dental porcelain ceramics. It has also been found that the flux concentration of material and the effect of temperature on preparation of dental porcelain contribute to the firing shrinkage and hardness, which has been found to increase with the increase of treatment temperature.
Chapter 20 - Weather and seasonal climate forecasts using the superensemble approach
-
- By T. N. Krishnamurti, Department of Meteorology, Florida State University, Tallahassee, T. S. V. Vijaya Kumar, Department of Meteorology, Florida State University, Tallahassee, Won-Tae Yun, Department of Meteorology, Florida State University, Tallahassee, Arun Chakraborty, Department of Meteorology, Florida State University, Tallahassee, Lydia Stefanova, Department of Meteorology, Florida State University, Tallahassee
- Edited by Tim Palmer, Renate Hagedorn
-
- Book:
- Predictability of Weather and Climate
- Published online:
- 03 December 2009
- Print publication:
- 27 July 2006, pp 532-560
-
- Chapter
- Export citation
-
Summary
In this chapter we present a short overview of the Florida State University (FSU) superensemble methodology for weather and seasonal climate forecasts and cite some examples on application for hurricanes, numerical weather prediction (NWP) and seasonal climate forecasts. This is a very powerful method for producing a consensus forecast from a suite of multimodels and the use of statistical algorithms. The message conveyed here is that the superensemble reduces the errors considerably compared with those of the member models and of the ensemble mean. This is based on results from several recent publications, where varieties of skill scores such as anomaly correlation, root-mean-square (rms) errors and threat scores have been examined. The improvements in several categories such as seasonal climate prediction from coupled atmosphere–ocean multimodels and NWP forecasts for precipitation exceed those of the best models in a consistent manner and are more accurate compared with the ensemble mean. It is difficult to state, soon after a forecast is made, as to which among the member models would have the highest skill. The superensemble is very consistent in this regard and is thus more reliable. In this study, we show walk-through tables that illustrate the workings of the superensemble for a hurricane track and heavy rain forecast for a flooding event. A number of features of the superensemble – number of training days, behaviour as the number of models increased, reduction of systematic errors and use of a synthetic superensemble – illustrate the strength of this new forecast experience.