Pallab Sinha Mahapatra

Bio: Pallab Sinha Mahapatra is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Heat transfer & Wetting. The author has an hindex of 17, co-authored 68 publications receiving 760 citations. Previous affiliations of Pallab Sinha Mahapatra include Kimberly-Clark & University of Illinois at Chicago.

Heat Transfer Enhancement and Entropy Generation in a Square Enclosure in the Presence of Adiabatic and Isothermal Blocks

Abstract: In the present work, heat transfer and entropy generation characteristics are numerically investigated in presence of single and double obstructive blocks within a square enclosure. It is found that the adiabatic block(s) enhance(s) the heat transfer marginally up to a critical size in a convection-dominated regime. On the other hand, the enhancement parameter is observed to be more with an increase in block size in a lower range of Rayleigh numbers for an isothermal block. The entropy generation for thermal irreversibility is observed to be several orders higher than that due to viscous dissipation in all cases.

Self-driven droplet transport: Effect of wettability gradient and confinement

Abstract: Surface tension driven droplet transport in an open surface is increasingly becoming popular for various microfluidic applications. In this work, efficient transport of a glycerin droplet on an open wettability gradient surface with controlled wettability and confinement is numerically investigated. Nondimensional track width w* (ratio of the width of the wettability gradient track w and the initial droplet diameter d0) of a wettability gradient track laid on a superhydrophobic background represents wettability confinement. A lower value of w* represents higher wettability confinement. Droplet behavior changes for different wettability confinements and gradients of the track. It is found that droplet velocity is a function of the wettability confinement and the gradient; droplet transport velocity is maximum for w* = 0.8. Higher confinement (w* 0.6 irrespective of the wettability gradient of the track. These findings provide valuable insight into efficient droplet manipulation in microfluidic devices.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Numerical Heat Transfer And Fluid Flow

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Convection Heat Transfer

Abstract: Geometry: shape, size, aspect ratio and orientation Flow Type: forced, natural, laminar, turbulent, internal, external Boundary: isothermal (Tw = constant) or isoflux (q̇w = constant) Fluid Type: viscous oil, water, gases or liquid metals Properties: all properties determined at film temperature Tf = (Tw + T∞)/2 Note: ρ and ν ∝ 1/Patm ⇒ see Q12-40 density: ρ ((kg/m) specific heat: Cp (J/kg ·K) dynamic viscosity: μ, (N · s/m) kinematic viscosity: ν ≡ μ/ρ (m/s) thermal conductivity: k, (W/m ·K) thermal diffusivity: α, ≡ k/(ρ · Cp) (m/s) Prandtl number: Pr, ≡ ν/α (−−) volumetric compressibility: β, (1/K)