1. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS XIUFANG ZHAO 2015.10.9

2. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS It starts with a simple question: How do you design the shadings? Could the decision making process be automated? Yes! Select the best solutions for you based on your objectives. Image: Pentagram

3. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Basic Guidelines for Shading Design Norbert Lechner, Heating, Cooling, Lighting: Sustainable Design Methods for Architects

4. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Shading Period Selection

5. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Form-finding

6. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Daylight Availability Avoid Glare Energy Saving Occupant Well-being …

7. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Q: How to find the best shading based on your objectives? Illuminance June 21 st 3 pm @ Philadelphia

8. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Fitness Test Population Survive Breeding

9. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Shading Solution Pool Objectives Run the Simulation Breeding Shading Solutions based on the simulation result

10. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS

13. Possibility without programing?

14. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS It starts with a simple example: design the shading for a reference office. What are the best shading size and open-angle based on sDA and ASE evaluation? PARAMETERS OBJECTIVES Christoph f. Reinhart, J. Alstan Jakubiec and Diego Ibarra Definition of a reference office for standardized evaluations of dynamic façade and lighting technologies

15. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS It starts with a simple example: design the shading for a reference office. What are the best shading size and open-angle based on sDA and ASE evaluation? PARAMETERS OBJECTIVES

16. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS It starts with a simple example: design the shading for a reference office. 30x90=2700 solutions Which ones could achieve a better sDA and ASE? Optimization. Number of shading panel: 1-30 Opening angle: 1-90 Christoph f. Reinhart, J. Alstan Jakubiec and Diego Ibarra Definition of a reference office for standardized evaluations of dynamic façade and lighting technologies 2700 times annual daylight simulation

17. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS It starts with a simple example: design the shading for a reference office. 30x90=2700 solutions Which ones could achieve a better sDA and ASE? Optimization. 1. SET THE MODEL2. SET THE SIMULATION 3. SET THE OPTIMIZATION

18. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS 1.SET THE MODEL Geometry Window Shading Material

19. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS 1.SET THE MODEL Geometry Window Shading Material

20. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS 1.SET THE MODEL Geometry Window Shading Material Parameters: Size: depth and number Angle

21. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS 1.SET THE MODEL Geometry Window Shading Material Material reflectance: Ceiling: 0.8 Wall: 0.5 Floor: 0.2 Glazing transmittance: 0.65

22. 2. SET THE SIMULATION Weather Data Grid Annual Simulation SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS New York Laguardia Arpt,NY,USA,TMY3

23. 2. SET THE SIMULATION Weather Data Grid Annual Simulation SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS

24. 2. SET THE SIMULATION Weather Data Grid Annual Simulation SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS

25. 2. SET THE SIMULATION Weather Data Grid Annual Simulation SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS

26. 3. SET THE OPTIMIZATION Octopus Interface Setting Run SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS

27. 3. SET THE OPTIMIZATION Octopus Interface Setting Run SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS

28. 3. SET THE OPTIMIZATION Octopus Interface Setting Run SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS

29. 4. Reading the Result Pareto-Frontier Solutions! SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS

30. 4. Reading the Result Pareto-Frontier Solutions! SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Image: Noesis Solutions, Multi-Objective Optimization

31. 3. SET THE GA RUNNING SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS

32. 30x90=2700 solutions Which ones could achieve a better sDA and ASE? Optimization. sDA 25.0 ASE 20.8 sDA 29.2 ASE 33.3 sDA 8.3 ASE 16.7

33. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Other parameters and objectives? Geometry, Material, Control Mode, Context

34. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Other parameters and objectives? O: DF, DA, UDI, DGP, Energy Saving, Cost Objectives from different roles: Clients/Building Owner/Designer/User Image: Mostapha Sadeghipour Roudasri

35. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Disadvantages: Time Definition of objectives

36. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS What could a designer do? Possibilities empowered by open-source programs.

37. SHADING OPTIMIZATION BASED ON MULTI-OBJECTIVE GENETIC ALGORITHMS Thanks for the guide and help from: Dr. Yun Kyu Yi, School of Design, University of Pennsylvania Thanks for the open-source programs or published papers: Honeybee Octopus DIVA OpenStudio

38. THANKS! Q&A TIME.