Yueer Cai - Module 7

Please enter the following info in the fields above:

  • Your Name as the Card title
  • The link to your Module 7 folder in our Autodesk Construction Cloud project

Please also type the first few letters of your first name into the Link to Student field, then hover over your name from the list of matching records and click the blue plus sign to link this entry to your Design Journal.

Then, share your Design Journal entry here (replacing these instructions) ... Click the text area below the headers and just start typing your response. There's no need to add new properties.

Please include:

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Shanghai's office building landscape has witnessed significant growth and transformation in recent years. With its dynamic economy and status as a global financial hub, the city boasts a vast array of modern and sophisticated office buildings. These structures showcase innovative architectural designs, advanced technologies, and sustainable features.

In order to better understand the dynamics of Shanghai's office market, it is crucial to delve into the relationship between building height, floor area, and monthly rental prices. Researching this connection would shed light on the factors that influence rental rates, provide insights into market demand, and aid in urban planning and real estate development strategies.

In Shanghai, taller office buildings often command higher rental prices due to their perceived prestige, prime locations, and enhanced visibility in the city skyline. These skyscrapers offer panoramic views, ample space for multinational corporations, and access to modern amenities and services. On the other hand, smaller office buildings or those with fewer floors may cater to smaller businesses or startups, offering more affordable rental options.

Step 1 - Generative Design Framework

A very brief description of the design decisions from Step 1 following the Generative Design Framework.

  • Design Decision 1: Sustainability
    • Design Variables
      1. Energy Efficiency Measures
      2. Material Selection (recyclability, embodied carbon)
      3. Water Conservation Systems
      4. Green Space Allocation
      5. Renewable Energy Integration
    • Evaluators
      1. Energy Consumption and Efficiency Ratings
      2. Life Cycle Assessment (LCA) of Materials
      3. Water Usage and Conservation Metrics
      4. Green Area Ratio (GAR) or Green Roof Coverage
      5. Renewable Energy Generation and Integration Metrics
    • Most Important Tradeoffs to Consider
      1. Upfront Costs vs Long-term Energy Savings
      2. Material Environmental Impact vs Performance and Durability
      3. Water Conservation Measures vs Operational Efficiency
      4. Green Space vs Usable Floor Area
      5. Renewable Energy Investment vs Energy Independence
  • Design Decision 2: Structural Integrity and Safety
    • Design Variables
      1. Structural System Selection (e.g., steel, reinforced concrete)
      2. Seismic Design Parameters
      3. Fire Safety Measures
      4. Occupant Evacuation Plans
      5. Building Code Compliance
    • Evaluators
      1. Structural Analysis and Stability Assessments
      2. Seismic Design Performance Evaluation
      3. Fire Safety and Prevention Inspections
      4. Evacuation Simulations and Emergency Response Evaluation
      5. Building Code Compliance Verification
    • Most Important Tradeoffs to Consider
      1. Structural System Performance vs Construction Costs
      2. Seismic Resilience vs Design Complexity
      3. Fire Safety Measures vs Aesthetics and Functionality
      4. Occupant Safety vs Floor Area Efficiency
      5. Code Compliance vs Design Flexibility
  • Design Decision 3: Building Economics
    • Design Variables
      1. Building Height: Investigate the impact of building height on rental prices, considering factors such as prestige, visibility, and desirability.
      2. Floor Area: Analyze the relationship between floor area and rental prices, examining how larger or smaller spaces affect leasing rates.
    • Evaluators
      1. Rental Prices: Assess the monthly rental rates of office spaces in various buildings across different height and floor area categories.
    • Most Important Tradeoffs to Consider
      1. Height vs Rental Prices: Determine whether taller buildings command higher rental prices due to increased demand or if other factors play a significant role.
      2. Floor Area vs Rental Prices: Investigate whether larger floor areas correspond to higher rental prices due to increased utility and flexibility.

Step 2 - Generative Design Study

  • A more detailed description of the design decision from Step 2 that you decided to run a Generative Design Study with.
  • Use the Generative Design Framework structure to explain how you’ve set up your Generative Design Study to keep it consistent.

Graph Properties:

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Case Study Set:

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Overall Model Code:

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All Inputs:

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Create Building Model:

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Evaluator Formula:

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All Outputs:

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Objective: The objective of this study is to examine the relationship between building height, floor area, and rental prices in the context of Shanghai's office market.

Model: A long cylindrical shape to represent a high-rise building.

Design Variables:

  1. Building Height: This variable represents the vertical dimension of office buildings and aims to investigate the influence of height on rental prices. Factors such as prestige, visibility, and desirability will be considered when analyzing the impact of building height on rental rates. (30—800 ft)
  2. Floor Area: This variable refers to the total area of office space within a building and will be examined to understand its relationship with rental prices. The study will explore whether there is a correlation between floor area and rental prices due to factors like increased utility and flexibility. In this model, I change the floor radius to change the floor area. (Floor radius: 10-70 ft)

Constants:

  1. Average monthly office rent in Shanghai 277(Yuan/month)
  2. Floor height 15 m

Evaluator:

  1. Maximize total rent for a month
  2. Minimize total building area

Interpretation: The study will assess the impact of building height and floor area on rental prices in the Shanghai office market. By analyzing rental rates across various buildings with different heights and floor areas, the research aims to provide insights into the tradeoffs between height, floor area, and rental prices. The objective is to determine whether taller buildings or larger floor areas are associated with higher rental prices and understand the factors driving these relationships. The findings will contribute to a deeper understanding of the dynamics of the Shanghai office market and provide valuable information for real estate investors, developers, and tenants.

Step 3 - Generative Design Study Results

  • The screenshot of the Scatterplot or Parallel Coordinates Graph illustrating the tradeoff that you chose to model and study.
  • Provide a brief explanation of what’s being shown in the Scatterplot or Parallel Coordinates Graph and how the tradeoff being illustrated would impact the design decision. What would you do with this info?
  • An image of your Dynamo Study Graph (showing all your nodes and the connecting logic) -- You can use the File > Export Workspace As Image... command in Dynamo to save a PNG image to upload with your posting

Graph of total rent for a month vs. height

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Graph of total rent for a month vs. building radius

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Graph of total rent for a month vs. building areas

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Based on the graph of total rent for a month vs. building areas, I can visually perceive that there is a linear relationship between building areas and total rent for a month. Therefore, when designing office buildings in Shanghai, I will strive to maximize the building area whenever feasible to pursue higher rental income.

The unexpected findings from the Graph of total rent for a month vs. height have given me significant food for thought. I initially assumed that higher building heights would lead to increased monthly rental income. However, the results from the Generative Design Study indicate otherwise. Interestingly, the peak of the monthly rental income did not align with the tallest building height but rather concentrated around 650ft. This realization has prompted me to reflect deeply on the significance of these generated design outcomes, which prove valuable for testing hypotheses and uncovering the need for further research.

The ability for computers to creatively propose alternative solutions within human-defined constraints is indeed useful. It emphasizes the importance of analyzing each specific situation individually, as there may be various factors at play that influence rental income beyond just building height. This reinforces the need for careful consideration and thorough research when designing and evaluating building models.

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