Jinzhao Wang

Journal Entry For
Module 6 - Evaluate Your Alternatives
ACC Folder Link
https://acc.autodesk.com/docs/files/projects/6db2c3ca-7a2c-4f34-96a1-8a8189c7754d?folderUrn=urn%3Aadsk.wipprod%3Afs.folder%3Aco.ws988fewSAy4fUmOKIo_Aw&viewModel=detail&moduleId=folders
Link to Student
Jinzhao Wang

🏗️ Design Journal – Evaluate Your Alternatives

🔧 Custom Node 1: Cost Estimation

To better estimate the construction cost for a high-rise building, I developed a custom node called CostEstimation, which integrates three key modifiers reflecting real-world construction complexity:

🟡 1. Height Penalty Factor

A quadratic function based on the floor number (e.g., 1 + 0.01·n + 0.0002·n²) accounts for increasing structural complexity, crane logistics, and labor inefficiency as building height rises.

🔵 2. Height Adjustment Factor

This factor normalizes cost based on floor height. Taller stories typically require more material, structural support, and labor time, hence increasing the per-floor cost proportionally.

🔴 3. MEP Level Factor

Every 15th floor is assumed to be a mechanical/electrical/plumbing (MEP) level, and receives a 1.75× cost multiplier to reflect the intensive infrastructure, pressure zones, and non-rentable nature of these spaces.

🐍 A Python Script is used within the node to modify cost factors at MEP levels programmatically and cleanly.

🔍 Workflow Overview

Using base logic inspired by shared resources (e.g., Google Drive custom nodes), the process is as follows:

  1. Compute the floor area per level.
  2. Apply the three factors described above.
  3. Aggregate the adjusted values to compute total and per-floor cost. 📎 Factor visualization
image
image

🧭 Custom Node 2: Directionality Analysis

To assess the directional exposure of building surfaces to a reference point (e.g., a landmark or sun direction), I created a DirectionessAnalysis node.

🟩 Key Steps:

  1. Select exterior surfaces of the tower.
  2. Identify those that are facing or visible from the object of interest.
  3. Compute:
    • Surface centroids
    • Normal vectors
    • A vector from object → surface
  4. Use the dot product between normals and object vectors to quantify directional exposure.

This analysis helps in façade design decisions — e.g., determining which panels receive the most solar radiation or visual attention.

image
image

📐 Custom Evaluation Criteria

To move beyond basic geometry and incorporate design intelligence, I defined two custom metrics:

📊 1. Volume-to-Floor Area Ratio

This ratio gives a sense of spatial efficiency or vertical compactness of the building:

Volume-to-Floor Area Ratio=Total Building VolumeTotal Floor Area\text{Volume-to-Floor Area Ratio} = \frac{\text{Total Building Volume}}{\text{Total Floor Area}}

A higher ratio may indicate:

  • Generous ceiling heights or atriums (luxury/ventilation)
  • Lower density (possibly lower ROI per unit volume)

A lower ratio suggests:

  • Denser stacking and efficient use of vertical space
  • Potential mechanical tightness or lower daylight access

💰 2. Cost-to-Floor Area Ratio

This metric is vital for value engineering and design comparisons:

Cost-to-Floor Area Ratio=Estimated Construction CostTotal Floor Area\text{Cost-to-Floor Area Ratio} = \frac{\text{Estimated Construction Cost}}{\text{Total Floor Area}}

It answers: How much are we spending per square foot/meter of usable space?

  • Helps compare design options early on
  • Highlights the impact of height, MEP strategy, or extravagant geometry

📊 Design Component Summary

Height (ft)
Top Rotation (°)
Gross Surface Area (ft^2)
Gross Floor Area (ft^2)
Gross Volume (ft^3)
Cost ($)
Directioness
Volume to Floor Area ratio
Cost to Floor Area ratio
725
40
959682
2549533
29467896
8.34E+09
21.60268
11.55815
3272.436
725
50
970495
2633894
30480298
8.66E+09
21.40403
11.57233
3286.175
725
60
979881
2711173
31407850
8.94E+09
21.39092
11.5846
3296.263
750
40
1026663
2792534
32385890
9.27E+09
21.885
11.59731
3319.791
750
50
1038745
2889154
33545293
9.64E+09
21.63226
11.61077
3335.804
750
60
1049249
2977807
34609427
9.97E+09
21.4907
11.62245
3347.94

🧠 Objective:

We aim to select the most efficient and well-performing design, considering:

Metric
Desirable Direction
Cost to Floor Area Ratio
Lower is better (cost-efficient)
Volume to Floor Area Ratio
Context-dependent; balanced (neither too low nor too inflated)
Directioness
Higher is better (greater façade exposure/view potential)

🏆 Best Option: 725 ft Height, 40° Rotation

✅ Why:

  1. Lowest Cost to Floor Area Ratio:
    • 3272.436 is the lowest among all options — excellent cost-efficiency.
  2. Compact & Efficient Volume-to-Floor Area Ratio:
    • 11.55815 is slightly lower than others, suggesting more space-efficient stacking.
  3. High Directioness:
    • 21.60268 is the third-highest, and the highest among 725-ft options, suggesting strong façade exposure.

✨ Final Verdict:

725 ft height + 40° top rotation offers the most cost-efficient and spatially efficient design, with very good directional exposure. It strikes an excellent balance between economic, volumetric, and environmental performance.

If the owner wants to slightly prioritize views or wind exposure, the 750 ft, 40° version could be a close runner-up, but it comes at a higher cost.

Points to ponder:

❓ Do the new evaluation metrics capture meaningful differences?

Yes — the Cost-to-Floor Area Ratio highlights economic efficiency across different forms, while the Volume-to-Floor Area Ratio reflects spatial compactness. These metrics reveal performance variations that aren’t obvious from total cost or volume alone.

➕ What other metrics would be useful?

Additional metrics to improve comparison:

  • Usable-to-Gross Floor Area Ratio – efficiency of floor layout
  • Solar Exposure per Surface Area – daylighting or PV potential
  • Material Volume or Weight – for cost and embodied carbon
  • MEP Zoning Complexity – lifecycle and operational implications
  • Wind or Shadow Impact – for urban and structural performance

Together, these would give a more holistic view of design quality.