Efficient air pass setup for local ventilation STAR-Global-Conference 2017, Berlin Efficient air pass setup for local ventilation Gerrid Brockmann Good afternoon Ladies and gentlemen! Thank you … I‘m Gerrid Brockmann from TU Berlin and my topic today is … This investigation is part of the governement funded MinMax-Project.

Progress air pass setup Summary Contents MinMax-Project CFD-model General problems Progress air pass setup Summary Therfore i start with an short introduction about the project and my used model. Then i show you some general problems with the air distribution though an underfloor in terraced venues. Before i focus on progressing an air pass control setup with optimate. I will fininsh with an small summary and answer your questions. STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Motivation Current state of the art Ventilation of venues with UFAD UFAD = Underfloor Air Distribution MinMax-Lüftung Local UFAD concept minimized energy demand and maximized ventilation effectiveness Besides: What do i mean with air pass? The interface beween the underfloor to the room. Thats what i named an air pass … others would probably call it supply air inlets. Global vs. Local ventilation. STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Geometry Parameter: Occupation scenario Sun protection Parts Regions Room Underfloor Air Distribution (UFAD) Seats (occupied seat is turned down) Computer Simulated Persons (CSP) Regions Room (= Room – Seats – CSP, Fluid) UFAD (Fluid) Parameter: Occupation scenario Sun protection Only fluid, no cht. Investigations with UFAD and without. Example with: Air distribution, Validation Example without: Parameterstudies STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Boundaries and numerical methods Supply air   Velocity inlet, passive scalar ( V air = 40 m3/h per open air pass, T = 20°C, cCO2 = 400 ppm)* Exhaust air Pressure outlet Ceiling, floor, Indoor walls, radiators, seats and tables Adiabatic wall Outdoor walls Environement (Tex = 20°C, U = 0.82 W/m2K)* Windows Environement (Tex = 20°C, Uw = 1.2 W/m2K, τ = 1)* Sun protection Environement (Tex = 20°C, U = 1.2 W/m2K)* Occupants Heat load and CO2 source, (PCSP = 90 W, V CO2 = 20 l /h Occupant) Turbulence model Realizable k-ε Two-Layer All y+ Radiation model Surface-to-Surface Radiation Solver Steady segregated slow and fluid temperature Other Ideal gas (Air), gravity, passive scalar (CO2) Summary of boundaries and numerical methods for the later presented air pass setup investigations *Boundaries for the air pass setup investigation STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Mesh generation Fine mesh for detailed investigations Coarse mesh for fast parameter and optimization studies Fine mesh 20 – 60 mio. polyhedral cells Coarse mesh 1 – 2 mio. polyhedral cells Prism layer wall 3 layers  y+ < 2 Prism layer CSP 10 layers  y+ < 1 Mesh size depend on number of CSPs. Fine mesh for investigations in the near field of the CSPs. STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Validation Temperature field Mean deviation 7 % Comparison between measurments recorded with different ambient conditions and occupation cases over the last year and simulations Temperature field Mean deviation 7 % CO2 concentration field Mean deviation 11 % Coarse mesh + 20 % Winter cases + 24 % Mean deviation: difference between the value at one point is around 0 and 20% for the temperature and 0 and 40% for the CO2. The deviation rise about 20% using the coarse mesh and 24% investigating winter cases. Cause of the storage capacity of the ground floor: negation of this effect by implementing an isothermal wall instead adiabatic. Required a measurement of the groundfloor temperature STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Non-uniform air distribution Problem: inflow into the UFAD real distribution ideal distribution Total volume flow: 3600 m3/h Isosurface T=Tair + 0.5 K One of our general Problems: Non uniform air distribution is a problem for the global and local ventilation. Inflow in the underfloor with an high impact, thus … Countermeasures: increasing the pressure loss at the air passes, baffle, perforated plate …. Streamlines 2.5 m from air pass into the room STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Pressure loss air passes Pressure loss measurements of air passes in wind channel: Porous baffle: ∆𝑝/𝜑= 𝛼 𝑣 +𝛽 𝑣 𝛼 - inertial resistance 𝛽 - viscous resistance Re < 10  𝛼 ≈ 0 ∆𝑝/𝜑≈5𝑣 ∆𝑝/𝜑≈16𝑣 To simplify pressure loss in the simulation … just viscous resistance (laminar, darcy) STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Air distribution over air passes Experiment With fleece Filter fleece do not fit Improvement of the uniformity index with the installation of filter fleece mats on the air passes for a volume flow of 4900 m3/h: UIExperiment from 0.70 to 0.87, UISimulation from 0.72 to 0.89. Simulation With fleece Comparison of the air distribution by measurement and simulation. Increasement of the Unifomrity index by using a fleece before the air pass. Experimental data is measured with an omnidirectional anemometer at 20 air passes. STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Air drop effect Open seat rows: fresh air is not blocked to fall down to lower tiers Open rows Closed rows 2 Problem is the missing barrier in the rows of the lecture hall stopping the air flow from dropping down to lower tiers Streamlines 2.5 m from air pass into the room STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Air pass setup  Multi-Objective Pareto Optimization Case 30 occupants in an open row lecture hall 120 air passes can be open or closed  2120 Possibilities Fixed volume flow per open air pass Efficient air pass setup High thermal comfort and indoor air quality Energy savings  reduced total volume air flow  Multi-Objective Pareto Optimization Standard case: 30 people … average group size in our lecture hall Problem of air drop … non uniform distribution is ignored How to control 120 air passes? STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Use Optimate+ Multi-Objective Pareto Optimization: Variables: 120 air passes  total volume flow Evaluation points  objectives: Mean, minimum and maximum value for the temperature and CO2 concentration Total volume flow simple objectives! Clima is suitable for every person in the room. Alternatives: for example uniformity index … to ignore hard outliners STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Results: thermal comfort All points are near Pareto-Front for the mean value Pareto-Front for temperature field is significant In the mean it could be comfortable for every one but with an high gradient there Air change rate too low STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Results: air quality All points are near Pareto-Front for the mean value Pareto-Front for CO2 field is significant discrepancy Air change rate too low STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Finding optimized setup Setup which parameter are closest to all pareto fronts! Energy savings, comfort and air quality Final selection criteria: lowest possible air change rate for acceptable air quality level Matrix: 1 = open air pass 1 To good to be true … I chose it cause of my rule STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Next step!? Discussion Using for efficient control Finding connections Huge amount of offline data High runtime  more restrictions Finding connections Next step!? Using for efficient control: Huge amount of offline data needed Mesh with 1.2E6 cells, 500 iterations by recommended 960 runs on a HPC with 16 cores; runtime of 2 weeks More restrictions needed to reduce the effort Finding connections to calculate directly the best air pass setup for an individual occupation scenario STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Improve air quality: open lower tiers Examples Improve air quality: open lower tiers Improve thermal comfort: supply air near occupant Finding a compromise STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Conclusion and Outlook Engineering success?! Finding an efficient air pass setup Alternative strategies: closing the rows Implementation of a local air distribution in the lecture hall is starting in march It is a beginning but there is still a lot of work: Error: density differences between air and carbondioxid Error: instationary effects are vanished STAR-Global 2017 | Efficient air pass setup for local ventilation | Gerrid Brockmann

Thank you for your attention! Thanks to our sponsors and partners. Thanks to Siemens for the invitation to present my work here. And Thank you for your attention!