Boundary layer

Abstract: 1 Mean Boundary Layer Characteristics.- 1.1 A boundary-layer definition.- 1.2 Wind and flow.- 1.3 Turbulent transport.- 1.4 Taylor's hypothesis.- 1.5 Virtual potential temperature.- 1.6 Boundaiy layer depth and structure.- 1.7 Micrometeorology.- 1.8 Significance of the boundary layer.- 1.9 General references.- 1.10 References for this chapter.- 1.11 Exercises.- 2 Some Mathematical and Conceptual Tools: Part 1. Statistics.- 2.1 The significance of turbulence and its spectrum.- 2.2 The spectral gap.- 2.3 Mean and turbulent parts.- 2.4 Some basic statistical methods.- 2.5 Turbulence kinetic energy.- 2.6 Kinematic flux.- 2.7 Eddy flux.- 2.8 Summation notation.- 2.9 Stress.- 2.10 Friction velocity.- 2.11 References.- 2.12 Exercises.- 3 Application of the Governing Equations to Turbulent Flow.- 3.1 Methodology.- 3.2 Basic governing equations.- 3.3 Simplifications, approximations, and scaling arguments.- 3.4 Equations for mean variables in a turbulent flow.- 3.5 Summary of equations, with simplifications.- 3.6 Case studies.- 3.7 References.- 3.8 Exercises.- 4 Prognostic Equations for Turbulent Fluxes and Variances.- 4.1 Prognostic equations for the turbulent departures.- 4.2 Free convection scaling variables.- 4.3 Prognostic equations for variances.- 4.4 Prognostic equations for turbulent fluxes.- 4.5 References.- 4.6 Exercises.- 5 Turbulence Kinetic Energy, Stability, and Scaling.- 5.1 The TKE budget derivation.- 5.2 Contributions to the TKE budget.- 5.3 TKE budget contributions as a function of eddy size.- 5.4 Mean kinetic energy and its interaction with turbulence.- 5.5 Stability concepts.- 5.6 The Richardson number.- 5.7 The Obukhov length.- 5.8 Dimensionless gradients.- 5.9 Miscellaneous scaling parameters.- 5.10 Combined stability tables.- 5.11 References.- 5.12 Exercises.- 6 Turbulence Closure Techniques.- 6.1 The closure problem.- 6.2 Parameterization rules.- 6.3 Local closure - zero and half order.- 6.4 Local closure - first order.- 6.5 Local closure - one-and-a-half order.- 6.6 Local closure - second order.- 6.7 Local closure - third order.- 6.8 Nonlocal closure - transilient turbulence theory.- 6.9 Nonlocal closure - spectral diffusivity theory.- 6.10 References.- 6.11 Exercises.- 7 Boundary Conditions and External Forcings.- 7.1 Effective surface turbulent flux.- 7.2 Heat budget at the surface.- 7.3 Radiation budget.- 7.4 Fluxes at interfaces.- 7.5 Partitioning of flux into sensible and latent portions.- 7.6 Flux to and from the ground.- 7.7 References.- 7.8 Exercises.- 8 Some Mathematical and Conceptual Tools: Part 2. Time Series.- 8.1 Time and space series.- 8.2 Autocorrelation.- 8.3 Structure function.- 8.4 Discrete Fourier transform.- 8.5 Fast Fourier Transform.- 8.6 Energy spectrum.- 8.7 Spectral characteristics.- 8.8 Spectra of two variables.- 8.9 Periodogram.- 8.10 Nonlocal spectra.- 8.11 Spectral decomposition of the TKE equation.- 8.12 References.- 8.13 Exercises.- 9 Similarity Theory.- 9.1 An overview.- 9.2 Buckingham Pi dimensional analysis methods.- 9.3 Scaling variables.- 9.4 Stable boundary layer similarity relationship lists.- 9.5 Neutral boundary layer similarity relationship lists.- 9.6 Convective boundary layer similarity relationship lists.- 9.7 The log wind profile.- 9.8 Rossby-number similarity and profile matching.- 9.9 Spectral similarity.- 9.10 Similarity scaling domains.- 9.11 References.- 9.12 Exercises.- 10 Measurement and Simulation Techniques.- 10.1 Sensor and measurement categories.- 10.2 Sensor lists.- 10.3 Active remote sensor observations of morphology.- 10.4 Instrument platforms.- 10.5 Field experiments.- 10.6 Simulation methods.- 10.7 Analysis methods.- 10.8 References.- 10.9 Exercises.- 11 Convective Mixed Layer.- 11.1 The unstable surface layer.- 11.2 The mixed layer.- 11.3 Entrainment zone.- 11.4 Entrainment velocity and its parameterization.- 11.5 Subsidence and advection.- 11.6 References.- 11.7 Exercises.- 12 Stable Boundary Layer.- 12.1 Mean Characteristics.- 12.2 Processes.- 12.3 Evolution.- 12.4 Other Depth Models.- 12.5 Low-level (nocturnal) jet.- 12.6 Buoyancy (gravity) waves.- 12.7 Terrain slope and drainage winds.- 12.8 References.- 12.9 Exercises.- 13 Boundary Layer Clouds.- 13.1 Thermodynamics.- 13.2 Radiation.- 13.3 Cloud entrainment mechanisms.- 13.4 Fair-weather cumulus.- 13.5 Stratocumulus.- 13.6 Fog.- 13.7 References.- 13.8 Exercises.- 14 Geographic Effects.- 14.1 Geographically generated local winds.- 14.2 Geographically modified flow.- 14.3 Urban heat island.- 14.4 References.- 14.5 Exercises.- Appendices.- A. Scaling variables and dimensionless groups.- B. Notation.- C. Useful constants parameters and conversion factors.- D. Derivation of virtual potential temperature.- Errata section.

Abstract: One major drawback of the eddy viscosity subgrid‐scale stress models used in large‐eddy simulations is their inability to represent correctly with a single universal constant different turbulent fields in rotating or sheared flows, near solid walls, or in transitional regimes. In the present work a new eddy viscosity model is presented which alleviates many of these drawbacks. The model coefficient is computed dynamically as the calculation progresses rather than input a priori. The model is based on an algebraic identity between the subgrid‐scale stresses at two different filtered levels and the resolved turbulent stresses. The subgrid‐scale stresses obtained using the proposed model vanish in laminar flow and at a solid boundary, and have the correct asymptotic behavior in the near‐wall region of a turbulent boundary layer. The results of large‐eddy simulations of transitional and turbulent channel flow that use the proposed model are in good agreement with the direct simulation data.

Abstract: Nanofluids are engineered colloids made of a base fluid and nanoparticles (1-100 nm) Nanofluids have higher thermal conductivity' and single-phase heat transfer coefficients than their base fluids In particular the heat transfer coefficient increases appear to go beyond the mere thermal-conductivity effect, and cannot be predicted by traditional pure-fluid correlations such as Dittus-Boelter's In the nanofluid literature this behavior is generally attributed to thermal dispersion and intensified turbulence, brought about by nanoparticle motion To test the validity of this assumption, we have considered seven slip mechanisms that can produce a relative velocity between the nanoparticles and the base fluid These are inertia, Brownian diffusion, thermophoresis, diffusioplwresis, Magnus effect, fluid drainage, and gravity We concluded that, of these seven, only Brownian diffusion and thermophoresis are important slip mechanisms in nanofluids Based on this finding, we developed a two-component four-equation nonhomogeneous equilibrium model for mass, momentum, and heat transport in nanofluids A nondimensional analysis of the equations suggests that energy transfer by nanoparticle dispersion is negligible, and thus cannot explain the abnormal heat transfer coefficient increases Furthermore, a comparison of the nanoparticle and turbulent eddy time and length scales clearly indicates that the nanoparticles move homogeneously with the fluid in the presence of turbulent eddies so an effect on turbulence intensity is also doubtful Thus, we propose an alternative explanation for the abnormal heat transfer coefficient increases: the nanofluid properties may vary significantly within the boundary layer because of the effect of the temperature gradient and thermophoresis For a heated fluid, these effects can result in a significant decrease of viscosity within the boundary layer, thus leading to heat transfer enhancement A correlation structure that captures these effects is proposed

Abstract: This modern climatology textbook explains those climates formed near the ground in terms of the cycling of energy and mass through systems.