ACD_SM1/2021_Assignment 3_Jason Leung by Gabriele Mirra

2.7

Proposal Development For New MSD Building Computational Design and Optimisation Strategy

A. Massing & MLP Design & Optimisation

B. Facade & Structural System Optimisation

C. Layout & Circulation Optimisation

Using the information from the site context and design brief, the optimisation aim to shape the base massing of the building that fully utilizes all the ready resource and explore the potential of the site as the icon of the campus for the next generation

To consider the practicality and constructibility of the proposed design, all the building elements should be designed with wellutilised and precise performance by the aid of computational optimisation.

The accessibility and solar exposure from skylight to atrium could be optimized by the improvement of the bridge circulation, which also facilitates the visitor transition experience within the building. (Not to be developed in this assignment)

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

3.1

Massing Design Optimisation Optimisation Intent & Fitness Objectives

Union House

The first optimisation process focus on the new building massing design with respect to the existing context. To enhance the benefit of environmental condition and visual privacy between building, separation between each blocks is taken as the indicator ans attempted to be maximized. The building notability is also important for visitors to identify such iconic building from a far distance perspective. Lastly, the proposed GFA should closely meet the design belief requirement as a way to optimize the land usage and its allowed capacity.

Raymond Priestley Building

Baldwin Spencer Building University Plaza

Redmond Barry Building

St. Mary College Physic South Building

Chemistry Building Old Geology Building

Elisabeth Murdoch Building

Design Optimization by Context Parameters Union House Entrance

Redmond Barry Building

Baldwin Spencer Building Entrance

Entrance of St. Mary College

University Plaza

RF L4 L3 L2 L1 G Chemistry Building

18k - Total GFA

Old Geology Building

Fitness Objective 1: Building Separation

Elisabeth Murdoch Building

Visible

Invisible

Fitness Objective 2: Visibility from a Distance

ABPL90123_Advanced Computational Design 2021_SM1

Campus Entrance Towards Tram Stop

Fitness Objective 3: GFA Difference with Design Brief

Assignment 3 Horror Vacui

3.2

Massing Design Optimisation Flowchart of computational design workflow

Reference a 60m x 45m srf. as Lower Block base

Exploded base srf. as four Slab Edge

Create Floor Slab at corresponding levels

Reference a 75m x 60m srf. as Upper Block base

Shift points along curve for responding building context

No. of Massing Breakdown (n)

Position Shift Along Curve ( ti )

Join the corner segment as polylines

Offset Curves outward to create in&out Massing

Join all the curves end pts as a continuous polyline

Orient Slab Outline to first two levels

Extrude as a solid massing block

Rebuild all curves as a continuous polyline

Orient Slab Outline to remaining levels

Extrude as a solid massing block

Offset distance wrt to base srf ( di )

Lower Massing Block

Exploded base srf. as four Slab Edge

Create points on line as the Massing twist

Group points as NW & SE Corners

Twist Position Along Curve ( ui )

Design Constraints & Constants Design Variables for Optimisation

Divide lines into even segments according to Design intent

Create Rectangle by two points with rotation

Trim and Join the base srf with the rotated rectangle

Rotation for better visual exposure ( ri )

Upper Massing Block

Geometries for Analysis Setup

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

3.2

Massing Design Optimisation Flowchart of computational design workflow

Massing Blocks

Solid Union Two Massing Blocks

Extract all Vertical Srfs (Building Envelope)

Massing Union

Generate a testing mesh for analysis

Find Closest pts to Context Building as its separation

Testing Mesh Grid Size (Δ)

Context Buildings

Design Constraints & Constants

Take average as fitness objective

Orient Void Edge to corresponding levels

Combine Curves into a matched data list

Extract the actual slab area for GFA calculation

Take the total slab area as overall GFA

Visibility Analysis from a far distance

Count % of points that are visible from either location

Testing points Location

FO1: Building Separation

Slab Outlines

Reference a 25m x 20m srf. as Atrium Void

Join pts into lines and obtain its length

FO2: Visibility from a Distance

Subtract two numbers as net difference

Take the result as absolute value

Target GFA (18k sqm)

Slab Union FO3: GFA Difference with Design Brief

Geometries for Analysis Setup

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

3.3

Massing Design Optimisation Design Variables & Constraints

60m

25m d4

t1 t2

ti є [ -0.10 , 0.10 ] Variable 1: Position Shift Along Curve

45m

East Entry

di є [ 1.0 , 5.0 ]

Variable 2: Offset distance wrt to base srf ( di ) Building Parameters: Lower Block Dimension = 60m x 45m Upper Block Dimension = 75m x 60m Atrium Void & Skylight Dimension = 25m x 20m Floor-to-Floor Height = 5m Number of Floor = 5 Floors

rNW

Massing Parameters: No. of Lower Block Massing Breakdown on each side ( n ) = 3 Optimization Setup Parameters: Testing Mesh Grid Size ( Δ ) = 1m

rSE u1

u2 ui є [ 0.30, 0.45 ]

Variable 3: Twist Position Along Curve

ri є [ -0.10π , 0.10π ] Variable 4: Rotation for better visual exposure

ABPL90123_Advanced Computational Design 2021_SM1

Constraints & Constants

Assignment 3 Horror Vacui

3.4

Massing Design Optimisation Optimisation Process and Parameters

The Optimization Process is carried out with the following parameter setting. Population Generation Size = 50 Generation Count = 50 Population Size = 2500 Optimization Parameters Crossover Probability = 0.9 Mutation Probability = 1/22 Crossover Distribution Index = 20 Mutation Distribution Index = 20 Simulation Parameters No. of Genes (Sliders) = 22 No. of Values (Sliders Values) = 3502 No. of Fitness Objectives = 3 FO1: Building Separation [Maximize] FO2: Visibility from a Distance [Maximize] FO3: GFA Difference with Design Brief [Minimize] Size of Search Space = 2.2e39

Pareto-front Solutions

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

3.5

Massing Design Optimisation Optimisation Result Over Generation

From the Observation of the Optimisation Result over generation, three fitness values are all improved in its next generation, which reveals these established objectives are not conflicting but can be taken as valid and effective objectives to optimise the massing design.

First Ind.

Last Ind.

First Gen.

Last Gen.

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

3.6

Massing Design Optimisation Synthesis on Optimisation Process

Evolutionary Process Gen 6, Iter 6

Visible

Gen 17, Iter 4

Gen 26, Iter 31

Gen 32, Iter 33

Gen 45, Iter 20

Gen 49, Iter 30

Invisible

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

3.7

Massing Design Optimisation Selected Result

From the Analysis of all the Pareto-front Solutions, the following iteration is selected for next round of optimization, as it has achieved a balanced fitness result in three objectives with a relatively bold twisted gesture on the upper massing block.

Visible

ABPL90123_Advanced Computational Design 2021_SM1

Invisible

Assignment 3 Horror Vacui

4.1

Facade & Structural Design Proposal Optimisation Optimisation Intent & Fitness Objectives

The Second optimisation process focus on the building design itself, focusing on the facade and structure system. To maintain minimal structural elements by incorporating the facade as part of the structural system and express its structural lightness as the building identity, the structure composition is optimized in the way of minimizing its deflection displacement with the optimal use of structural component. Considering the practicality and constructibility of the facade module, the optimisation process is executed to optimize the potion of typical module such that the design proposal is more cost-efficient. By reducing number of facade junction, the facade appears more homogeneous to its adjacent facade as diagonal mullions meet on the same spot.

FO1

FO2

FO3

Design Optimization by Practicality and Constructibility

F8 F5

F1 F4

Fitness Objective 1: Max Displacement

Fitness Objective 2: Facade Junction

ABPL90123_Advanced Computational Design 2021_SM1

No. of interface points along facade edge

% of Typical Module = Σ Ftypical module / Σ Ftotol module

Fitness Objective 3: Facade Typical Module

Assignment 3 Horror Vacui

4.2

Facade & Structural Design Proposal Optimisation Flowchart of computational design workflow

Chosen Iteration from Previous Optimisation

Design Constraints & Constants

Take Upper Block Face as Reference, and split list according to its Elevation

Offset Slab Edge inward as Support Edge

Divide first line into even segments by no. of support

Create points on line as the position of Support

Create a Ref XY-Plane at Support Position

Setback from Upper Glazing Line ( Δ )

No. of support along each side (n)

Position on Structural Grid ( ti )

Tilted Angle A (α)

In Clockwise Direction

Tilted Angle B (β)

In Anticlockwise Direction

Assemble Model as V-Columns

Rotate the plane along its local Y-axis of its Trunk line

Apply to other elevation with same workflow

Intersect with the slab level and join as line

Distort the curve end point along base srf normal

Distort Distance ( di )

Extrude with corresponding uniform profile

V-Columns

Design Variables for Optimisation

Categorise as C_Branch

Geometries for Analysis Setup

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

4.2

Facade & Structural Design Proposal Optimisation Flowchart of computational design workflow

Offset from Atrium Void

Divide Edges as Column Positions

Generate Structure Grid by interval intersection

Offset Distance ( c )

No. of column along each side (p)

Max Internal Column Spacing ( g )

Extrude Points as Internal Columns

Filter out the Ground Floor Slab Edge

Loft Edges as Glazing Surface

Create Setout Point along bottom Edge

Orient Tilted Plane to the center of Glazing Surface

Contour and Intersect with Glazing Surface as Mullion Grid

Setout Point (s)

Tilted Angle A (α)

Tilted Angle B (β)

Mullion/ Facade Grid Spacing ( m )

Assemble Model as Facade

Apply to other elevation with same workflow

Core Columns Categorise as C_ Internal Column Design Constraints & Constants

Extrude with uniform profile

Mullion & Facade Structure

Design Variables for Optimisation

Geometries for Analysis Setup

ABPL90123_Advanced Computational Design 2021_SM1

Categorise as F_Mullion

Assignment 3 Horror Vacui

4.2

Facade & Structural Design Proposal Optimisation Flowchart of computational design workflow

Formulate Slab into Beam Network (Srf to Mesh)

Extract Edges As Beams

Extract Upper Block Face F_Mullion

Beam Spacing/ Structure Grid (b)

Design Variables for Optimisation

Geometries for Analysis Setup

Extract All Edge Interface Points

Cull Duplicate Points within tolerance

Count total no. of interface points along edge

Extract All Typical Module

Count % of Typical Module in the facade

Create the shading according to orientation FO2: Facade Junction

Facade Modules

Slab & Beams

Design Constraints & Constants

Split the base glazing srf. as Facade Module

FO3: Facade Typical Module

Categorise as S_Mid Floor, S_Roof Beams & S_Floor Beams

C_Internal Column & C_Branch

All Geometries for Analysis Setup

F_Mullion

Rebuild, Shatter all the geometry intersection such that all lines are interconnected for load transfer

FO1: Max Displacement Structural Analysis & Optimisation

ABPL90123_Advanced Computational Design 2021_SM1

Assign Supports, Loads, Material Selection, Profile Cross Section to corresponding components

Send the Assembled Model for FEM Analysis and Optimisation for Max Displacement in the Model

Loop & Feedback the Model with new set of Variables for iteration with a better Fitness Performance

Assignment 3 Horror Vacui

Refer to the Details in the following Sections

4.3

Facade & Structural Design Proposal Optimisation Design Variables & Constraints

t2 ti є [ 0.40 , 0.60 ]

α є [ 0.25π , 0.35π ] Variable 2: Tilted Angle A

Variable 1: Support Position on Structural Grid (Curve Parameters)

β є [ 0.35π , 0.45π ] Variable 3: Tilted Angle B Internal Column Parameters:

Offset Distance from Void Edge ( c ) = 3m No. of column along each side ( p ) = 4 Max Internal Column Spacing ( g ) = 12m Structural Facade Parameters:

Setback from Upper Glazing Line & S. Grid ( Δ ) = 4m No. of support along each side ( n ) = 2(longer one), 1(shorter one) Mullion/Facade Grid Spacing ( m ) = 2m Beam Spacing/ Structure Grid ( b ) = 1.6m

d3 d4

di є [ -2.0 , 2.0 ] Variable 4: Distort Distance ( di )

si є [ -0.10 , 0.10 ] Variable 5: Setout Point ( s )

ABPL90123_Advanced Computational Design 2021_SM1

Constraints & Constants

Assignment 3 Horror Vacui

4.4

Facade & Structural Design Proposal Optimisation FEM Analysis Setup for Structural Performance

Gravity Load Live Loads: 2kN/m2

Conditions: (Tx ,Ty ,Tz ) & (Rx ,Ry ,Rz ) Ground Supports

Loads

Material S_Roof Beams Steel S235 S_Floor Beams

Cross Section I-Section Height: 30cm Upper/ Lower Width: 20cm Upper/ Lower THK: 0.8cm Web THK: 0.5cm

Horizontal Members (Beams, Slab & Roof)

Assembled Model

Material C_Internal Column Reinforced Steel C_Branch Vertical Members (Branches & Columns)

ABPL90123_Advanced Computational Design 2021_SM1

Cross Section Sqaurish-Section Height & Width: 30cm Upper/ Lower THK: 0.4cm Sqaurish-Section Height & Width: 50cm Upper/ Lower THK: 0.4cm

F_Mullion

Material

Cross Section

Aluminium

Sqaurish-Section Height & Width: 20cm Upper/ Lower THK: 0.4cm

Facade System

Assignment 3 Horror Vacui

4.5

Facade & Structural Design Proposal Optimisation Optimisation Process and Parameters

The Optimization Process is carried out with the following parameter setting. Population Generation Size = 50 Generation Count = 50 Population Size = 2500 Optimization Parameters Crossover Probability = 0.9 Mutation Probability = 1/24 Crossover Distribution Index = 20 Mutation Distribution Index = 20 Simulation Parameters No. of Genes (Sliders) = 24 No. of Values (Sliders Values) = 524 No. of Fitness Objectives = 3 FO1: Max Displacement [Minimize] FO2: Facade Junction [Minimize] FO3: Facade Typical Module [Maximize] Size of Search Space = 5.7e31

Pareto-front Solutions

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

4.6

Facade & Structural Design Proposal Optimisation Optimisation Result Over Generation

From the Observation of the Optimisation Result over generation, both the fitness value of FO1 and FO3 are improved throughout the whole optimisation process, while the optimisation trend of FO2 is scattered and fluctuating. Its improvement is not as obvious as another objectives, which explains the reduction of facade junction could be possibly achieved by chance when structure and facade system are optimized at the same time.

First Ind.

Last Ind.

First Gen.

Last Gen.

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

4.7

Facade & Structural Design Proposal Optimisation Synthesis on Optimisation Process

Optimisation Convergence Graph

Gen 8, Iter 35

Evolutionary Process Gen 17, Iter 37

Gen 25, Iter 21

ABPL90123_Advanced Computational Design 2021_SM1

Gen 36, Iter 28

Gen 45, Iter 29

Assignment 3 Horror Vacui

Gen 49, Iter 45

4.8

Facade & Structural Design Proposal Optimisation Selected Result

From the Analysis of all the Pareto-front Solutions, the following iteration is selected for as the final output of the optimisation process. It has achieved well in three fitness objectives. In particular to the second objective, the corner details and junctions are jointed quite well from those key perspective. The v-columns are also positioned in a way doesn’t bother the building circulation and the prominence of main entrance.

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui

Aerial Perspective

ABPL90123_Advanced Computational Design 2021_SM1

Assignment 3 Horror Vacui