Aerosol transport and deposition modelling. Tim Foat Fluid Dynamics and Indoor Dispersion Team Detection Department

Transcription

1 Aerosol transport and deposition modelling Tim Foat Fluid Dynamics and Indoor Dispersion Team Detection Department

2 Introduction Work of the team focuses on three main areas Indoor dispersion Transport, deposition, surface interaction of aerosol and gas / vapours Experimental and modelling capability Aerosol collection Design & development of aerosol collectors and inlets Fluid dynamics Small to large scales

3 CFD modelling for inlet design Develop complimentary techniques to aid in inlet design SMEs & wind tunnel testing Commercial CFD software Ansys Fluent & Gambit Development of accurate modelling methods Aerosol deposition Validation against wind tunnel data

4 Virtual vs. Real Reproducible Common software used elsewhere Good technical support Setting up models is complex Model can be run in parallel out of hours Can try out many candidate designs Small changes can be investigated Give details that could be easily measured No limits on wind speed and flow rates Can save on expensive initial trials Use to down select candidates for final wind tunnel testing Can be used to optimise location on platforms Can be used to replicate realistic scenarios Varying wind speed and direction Customer Confidence Perception that it is more realistic Simulant and ambient materials Large error bars? Poor replication? Variation from session to session? Difficult to identify effects of small changes to inlet parameters Needs reference technology Resource intensive staff, material, facility, time Limitations windspeed, materials

5 2D axi-symmetric models Model a slice that is rotated about 360 No external wind is included Zero or low wind speed Particles are injected directly into inlet, therefore only transmission efficiency is calculated

6 3D models Model the 3D inlet in isolation Symmetry assumed Obtain estimate of transmission efficiency Model the 3D inlet in a wind stream Symmetry assumed Particles are injected at the model boundary Aspiration and transmission efficiency

7 Collection efficiency Aerosol deposition in straight pipes and bends Bend collection efficiency for three different cases 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% Case 1 Exp Re=6000 i.d.=5.03mm, CR=5.7 Case 1 CFD Case 2 Exp Re=10000 i.d.=5.03mm, CR=5.7 Case 2 CFD Case 3 Exp Re=10000 i.d.=8.51mm, CR=5.6 Case 3 CFD 0% Particle Stokes number Methodology study for prediction of aerosol deposition Turbulent flow Stochastic modelling Parker, S., Foat, T., Preston, S., Towards quantitative prediction of aerosol deposition from turbulent flows, Journal of Aerosol Science, 39, (2008).

8 Modelling requirements High quality mesh y+ = 1 Reynolds stress turbulent model Anisotropic representation of turbulence Second order discretisation Large number of particles tracked Error reduction as count increases Particles stick or bounce?

9 Total efficiency Time taken on 12 CPUs (hours) 80% 18 70% 16 60% 14 50% 40% 30% % 4 10% 2 0% 0 1.E+05 1.E+06 1.E+07 1.E+08 Total number of particles

10 Efficiency Inlet efficiency - 1m/s No trapping Total efficiency Transmission efficiency Particle Diameter (μm)

11 Aerosol modelling examples Biological reference equipment Slit samplers Electrostatic effects Charge aerosol tracking in electric fields 1 m and 10 m particle tracks 90 o, 2.2ms -1

12 Drift-flux modelling CFD based approach to predicting aerosol movement and deposition Faster than individual aerosol tracking Suitable for indoor air flows Gravity, Brownian and turbulent diffusion m m 0.1 m 4.64 m 2.15 m 1.0 m 46.4 m 21.5 m 10.0 m Parker,S., et al. Refinement and testing of the drift-flux model for indoor aerosol dispersion and deposition modelling. Journal of Aerosol Science, 41, (2010).

13 Drift-flux modelling CFD based approach to predicting aerosol movement and deposition Faster than individual aerosol tracking Suitable for indoor air flows Gravity, Brownian and turbulent diffusion m m 0.1 m 4.64 m 2.15 m 1.0 m 46.4 m 21.5 m 10.0 m Parker,S., et al. Refinement and testing of the drift-flux model for indoor aerosol dispersion and deposition modelling. Journal of Aerosol Science, 41, (2010).

14 Deposition Concentration 0.35 m 12.5 m

15 Indoor dispersion gas or aerosol Objectives Hazard assessment Building protection Detector or monitor placement Mathematical models Range of tools Choice depends on requirements Toolkit development and modelling frameworks Experimental work Surveying building air flow Tracer trials and validation

16 Concentration (kg m-3) Capabilities - Modelling Supply Return Lobby Floor 1 Floor 2 Floor 3 Stairwell Stairwell 2 Stairwell Tools for the study of indoor environment High resolution models Computational Fluid Dynamics Medium resolution Multizone modelling Low resolution Simple calculations Space state approach Choice depends on the building and study scope Size of study (room, building, station) Degree of mixing Ventilation (mechanical, natural, hybrid) Information available Time available Time (hr)

17 Capabilities - Trials Validation of models Understanding of flow phenomena Examine scenarios Building surveys Equipment Tracer dissemination Tracer monitors Gas or aerosol phase Anemometry Temp / humidity / pressure Thermal imagery

18 Capabilities - Trials Building surveys Flow Pressure Temperature Humidity Tracer studies SF 6 Propylene Aerosol Sodium bicarbonate