1. 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.

2. 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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. 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

17. 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

18. 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

19. 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

20. 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!