Step 1 - Generative Design Framework
The design decisions that I thought about for this assignment generally relate to a building’s constructibility and form. These are listed in the following order:
- Design Decision 1 - Building Design & Costs in Construction
Objective: What is the ideal shape for a building using different geometry forms to maximize floor area while minimizing material costs?
Model: To model this design, I require design inputs that inform the dimensions of the different geometry groups to create the various solid masses. I will also need to provide inputs that will allow me to determine the costs associated with each geometric form.
Design Variables: Height of building form, Radius of building form
Constants: Location of each building form relative to the origin, Building Material Costs
Evaluators: Determine best building form that maximizes floor area (for increased occupancy/commercial returns) while minimizing construction costs
- Design Decision 2 - Architectural Form & Design Efficiency
Objective: Determine if the number of curves introduced in a superstructure (e.g. roof) would compromise design efficiency (e.g. more structural support needed).
Model: To model this design, I require design inputs that inform the relationship between the number of curves in the roof structure against the number of column supports needed. I will also need to provide inputs that allow me to benchmark the outputs of the relationship against each other.
Design Variables: Number of Sine Curves, Size of Structural Columns
Constants: Number of columns required, location roof structure.
Evaluators: Determine design that maximizes the number of curves (for increased aesthetics) while minimizing column sizes
- Design Decision 3 - Operational & Sustainability Factors
Objective: What is the most ideal number of windows that maximizes ventilation while minimizing building energy loss?
Model: Develop a model that measures the relationship between window quantity, ventilation flow rates and building envelop energy gain/loss.
Design Variables: Number of Windows, Window Placement
Constants: Size of windows, Wall Insulation
Evaluators: Determine best window placement strategy that minimizes energy loss while maximizing passive ventilation
Step 2 - Generative Design Study
For this assignment, I elected to model the graph for Design Decision 1 to take a deeper look at the relationship between building geometry and construction costs. I was also curious to know if rectangular or cyclindrical shapes could be innovatively incorporated into structural design.
To develop this model, I first established the building geometries that I wished to study comprising of two rectangular cuboids and a cylindrical structure. I setup the graph to create these geometries and used design nodes to compute the total floor area of the merged structure as well as other evaluation parameters such as total wall material cost.
The design inputs (both fixed and generative) for this graph can be seen in the following figures below. I elected to study the shape and form of the structure by setting the heights for all the different structures and cylindrical radius as generative inputs to be tested. For the other design parameters (e.g. solid mass location, material cost), these were fixed constants that could be defined by the user.
The model relationships to setup the mass structure study and compute the corresponding evaluation parameters can be seen from the following figures.
These parameters were then defined as evaluator outputs based on total volume, total gross floor area and total material cost to be studied through generative design as seen below.
The overview of the final graph logic before the generative design study is carried out can be observed in the following figure.
Step 3 - Generative Design Study Results
For my generative study, I sought to optimize the results based on results that maximized total floor area for more useable space while minimizing material costs for economic efficiencies. The generative study parameters and resulting scatterplot can be found in the following figures.
The scatterplot demonstrates a relatively linear relationship between total building gross floor area and material cost. Interestingly, it also revealed that there could be significant cost differences between designs that provide the same floor area but with different geometry shapes. For instance, the following figures illustrate two designs that provide similar total gross floor area but with significant cost differentials of over 25%.
This assignment highlighted the potential for generative design to inform my design decisions by allowing me to iteratively explore multiple structure options that achieved the intended design objective (e.g. defined total floor area) while minimizing overall construction costs. The final overview of my generative study in dynamo is as attached.