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« Simplified Urban Heat Island Modelling » By Adil Rasheed.

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  • Simplified Urban Heat Island ModellingBy Adil Rasheed

  • Some QuestionsHow does a city development affect the microclimate ?How important is the effect of environment on buildings ?How should building design respond to urban microclimate ?Is it possible to minimise the energy consumption and improve pedestrian comfort by designing/modifying certain parameters in a city?Is it possible to develop a strategy for city design ?

  • Overview of the presentationBrief description of Urban Heat Island State of ResearchState of research conducted by the studentFuture plan of research

  • Urban Heat Island EffectTemperature profile in a plain rural area

  • Urban Heat Island EffectTemperature profile of a UHI-0.5 to 7 C

  • Measured data: London

  • Measured data: London

  • Urban Heat Island EffectCauses of UHI:RadiometricAlbedo, emmisivityThermophysicalCp, KGeometricChange in drag and shearEvaporative and evapotranspirationAnthropogenic heat

  • Consequences of UHIChanges heating and cooling loads.Changes comfort level.Influences pollutant dispersion.Can severely affect the cloud formation and rainmean monthly rainfall rates within 30-60 kilometers (18 to 36 miles) downwind of the cities are, on average, about 28% greater than the upwind region. (research conducted by NASA)

    http://www.gsfc.nasa.gov/topstory/20020613urbanrain.htmlConclusion: Urban area changes the energy, momentum and humidity balance.

  • UHI ModellingGoverning Equations:Comments on the governing equations:Highly non linearStrongly coupled.Mismatch between the number of unknowns and number of equations (problem of closure)

  • UHI modellingAll the existing models can be categorized intoAnalytical ModelPhysical ModelNumerical ModelAll these models are governed by the same set of conservation equations

  • Analytical ModellingSolving the governing equation with assumptions which simplifies the equation.Flow over a gaussian mountainPlume from a constant area sourceAdvantages: Gives exact solution.Reliable for validation.Computationally inexpensiveDisadvantages: Doesnt represent reality.Very limited application.

    Sample assumptions: No pressure gradients in 2 directions Free slip BC near the ground No consideration for urban geometry Radial Symmetry

  • Physical ModellingRequirements:Similarity criteria3-D model of the cityHi-tech instrumentationAdvantages:More close to reality.Can handle the complexities of fluid flow.Disadvantages:Difficulties in satisfying the similarity criteria.Measuring instruments can alter the flow.Difficult to maintain the desired boundary conditionsEffects of radiation, cloud formation etc. can not be simulated

    Similarity Criteria

  • Physical ModellingLU et al. Dept. Of marine, earth and atmospheric sciences, North Carolina State Univ.

  • Numerical ModellingInvolves solving the governing equations numerically.Advantages:Takes into account the key parameters that can affect UHI with (potentially) good spatio-temporal resolution.Disadvantages:Numerically very expensive.The model is complex and needs experties to run the model.Error analysis is not feasible at the moment.

  • Numerical Modelling: ScalesMicroscale (buildings resolved)Mesoscale (Buildings cant be resolved)MacroscaleMicroscale Grid size is much smaller than the dimension of buildings to be resolved.MesoscaleGrid is very coarse (a few km)Simulation should be run for sufficiently long duration so that the wind sweeps the whole domainMacroscalePresent Challanges: Urban and Turbulence parametrisation

  • Numerical Modelling: Urban Parametrization City to be modelled.

  • Numerical Modelling: Urban ParametrizationFine Grid: Can resolve the effects of buildings but is computationally intractable.

  • Numerical Modelling: Urban ParametrizationVery coarse Grid: Cant resolve the effects of buildings explicitly but is computationally feasible. Implicit modelling required(parametrization of urabn effects)

  • Martillis Urban ParametrisationHighlights:Impact of horizontal and vertical wall (drag and shear)Accounts for solar radiationAccounts for building density, urban forms and different landuse1D heat conduction is solved in the soil, wall and roof to estimate the surface heat fluxes(Source)mesoscale = (urban fraction)*(urban effect on urban grid)+(rural fraction)*(rural effect)+.. Surface temperature: Computed by solving 1D heat transfer equationSource

  • Numerical Modelling: Turbulence

    Big whorls have little whorls, Which feed on their velocity; And little whorls have lesser whorls, And so on to viscosity

    -Lewis Richardson in 1922

  • Numerical Modelling: TurbulenceDifferent approaches to make turbulence computationally tractable:DNS: Direct Numerical Simulation. RANS: Reynolds Averaged Navier Stokes (or time or ensemble)LES: Large Eddy Simulation (Spatially average )

    (wave number)E(k)ResolvedModelledResolvedModelledFilter

  • Turbulence: Direct Numerical Simulation (DNS)Resolves all the turbulent length and time scalesComputationally expensive.Can be applied only for low reynolds number flow.

  • Turbulence: RANSReynolds Averaged Navier Stokes Predicts only the time averaged effects.Based on the assumption that the instantaneous fluctuations are much smaller than the fluctuations in the mean flow.Since all the turbulent scales are modelled the result may deviate significantly from reality.Two additional equations are required to predict the length and velocity scales.

  • Large Eddy Simulation (LES)Some applications need explicit computation of accurate unsteady fields.

    Bluff body aerodynamicsAerodynamically generated noise (sound)Fluid-structure interactionMixingCombustion

  • LES - Rationales

    Large eddies: responsible for the transports of momentum, energy, and other scalars. anisotropic, subjected to history effects, are strongly dependent on boundary conditions, which makes their modeling difficult.k,f

    Small eddies tend to be more isotropic and less flow-dependent (universal), mainly dissipative scales, which makes their modeling easier.

    Eu,ETe

  • RANS vs LES

  • Historic climate file for some (possibly distant) locationBuildingCurrent situationHistoric climate file for some (possibly distant) locationRealityDue to large scale flow and topographical features, the climate bounding the city is differentUrban albedo (sw, lw), evapotranspiration, anthropogenic gains, momentum transfer BuildingPossible solutionHistoric climate files for some (possibly distant) locationsInterpolation or macroscale flow modelMesoscale flow model with urban parameterisationLocal microscale (simple CFD) flow modelBuildingPre-processUnidirectional model nestingHypothesis

  • ApproachMicroscale ModelMesoscale ModelGlobal Model + Measured dataBuilding SimulationProgram

  • Research done by the candidateCo-development and Restructuring of the FVM code.Development of the Microscale Model.Test of various Convective Schemes for Atmospheric flow.

  • Co-development and restructuring of the FVM codeThis work was done along with Andrea Krpo from LPAS

  • Microscale ModelFeatures:Based on SIMPLE algorithm. (Semi Implicit Method for Pressure Linked Equations)Explicit resolution of buildings.Solves for velocity and scalars in 3DProblems:Based on cartesian grid so cant be adapted to the terrain

  • Convective SchemesOne dimensional fluid flow:?Closer to 100 C Closer to 0CConclusion: Interpolation schemes should be sensitised to magnitude as well as the direction of flow100 C0 Cwhere

  • Future plan of researchValidation of the basic assumptions in Urban ParametrisationImprovement in the Urban ParametrisationCoupling with the Microscale ModelApplication to real cities

  • VerificationTest the urban canopy model against experimental and LES results.Finetune the RANS model to suite the common geometries occuring in the city by comparing the result against LES for isothermal cases.Repeat the step 1 and 2 for non-isothermal cases.

  • Improvement of Urban ParametrizationStudy the effects of changing the urban geometry.Introduce the simplified radiosity algorithm to compute the radiative fluxes accurately.Further Verifications.

  • Numerical Modelling: Urban ParametrizationCan be approximated to a regular array of buildings

  • Numerical Modelling: Urban ParametrizationMay not be well represented by a regular array of buildings.

  • Numerical Modelling: Urban ParametrizationParametrization schemes can be defined which cover the entire set of urban characteristics

  • Coupling of Mesoscale and Microscale ModelsSupply the boundary conditions from the Mesoscale Model to the Microsclae Model

  • Application of the Model to real citiesRun the model on cities and investigate Effects of variables (geometric, surface, sources, sinks)Effects of latitudeGenerate annual data sets.Statistical Reduction of the annual data sets.First contribution to urban planning guidelines to best control UHI

  • Schedule

  • Thank You

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