Massing Advisor
In the initial stages of architectural design, manually adjusting building layouts to accommodate site-specific factors can be time-consuming and inefficient. Factors such as sunlight direction, terrain topology, and pedestrian flow patterns all influence the placement and massing of buildings. Traditional methods often require numerous iterations to balance these elements, potentially delaying project timelines and compromising quality.
Authors: Hanyin Zhang, Joe Zhang, Kate Perez, & Lucas Gonzalez
Introduction
To address this challenge, our project aims to develop an automated tool that integrates Grasshopper (GH) to streamline the massing and layout process in architectural design. By considering various site constraints, our tool will automatically generate a series of form distributions, including massing and functional zone distribution. This approach allows for dynamic adjustments, enabling a more efficient and convenient workflow for presenting design options to clients.
Value Proposition & Market
Our designed tool caters to a diverse range of professionals, including architects, urban planners, real estate developers, and government departments. Architects can use the tool to enhance their design process, while urban planners can assess the impact of new buildings within existing urban landscapes. Real estate developers can optimize designs to maximize land use and adhere to urban development regulations, while government departments can evaluate proposed designs for compliance with zoning laws and urban planning considerations.
Core Values
The core values of our tool include efficiency improvement, enhanced decision-making, increased creativity and innovation, and improved client engagement and satisfaction. By employing a data-driven approach and automating routine tasks, our tool frees designers to focus on creativity, encourages exploration of innovative design solutions, and fosters collaborative design processes.
Case Study
We utilized the MIT Sustainability Lab’s Urban Daylight Simulation tool as a precedent for developing our script generation. This tool served as a useful anchor for building off from during the initial planning stages of analyzing daylighting potential in urban environments. By studying the approaches outlined in the MIT article, like the two-step workflow involving Radiance/Daysim simulations and the computation of climate-based daylighting metrics, we understood the technical aspects of daylight analysis in urban contexts. By leveraging the script and research from the MIT Sustainability Lab, we were able to adapt and refine our own script generation process to suit the specific needs and objectives of our project. Incorporating these methodologies into our workflow not only facilitated rigorous assessment of daylighting performance but allowed us to expand beyond daylighting and consider massing and program.
Methodology
Our methodology was guided by several key principles and considerations aimed at addressing the lack of input driven massing generators within the architecture and real-estate sphere. We aimed to develop an automated Grasshopper script to smoothly streamline the initial building steps of identifying maximum solar gain, building orientation, and restrictions.
Our main drivers were efficiency improvement, enhanced building decision-making, increased creativity and innovation, and client engagement and satisfaction. To achieve these goals, we heavily considered the diverse needs of our potential users, including architectural designers, urban planners, real estate developers, and government planning departments.
Our first step was to identify the primary site-specific factors through ZOLA, as well as constraints that impact building placement and massing, such as sunlight direction, terrain topology, and pedestrian flow. Next, we developed algorithms to automatically generate form distributions for massing, layout, and functional zone distribution based on these factors.
We then focused on the dynamic adjustment of each site condition, allowing designers to fine-tune the design process according to project requirements and client preferences. This step ensured flexibility and customization in the design process, enabling the generation of tailored design options.
Throughout the development process, we prioritized efficiency improvements by automating routine tasks and leveraging data-driven design decisions. This approach not only saved time and effort but also optimized projects based on specific site constraints.
Our methodology prioritizes efficiency, informed decision-making, creativity, and client satisfaction. By automating routine tasks and facilitating data-driven design decisions, our project aims to revolutionize the architectural design process and foster collaborative and innovative design solutions.
Grasshopper: Zoning and Program Considerations
In optimizing spatial configurations, we consider two primary factors: zoning regulations and program requirements. We first begin with identifying the current site and investigating its regulated building codes and zoning qualities. We identify a lot line as a boundary box in grasshopper where the building configurations can be developed, see below.
The grasshopper script begins with identifying zoning regulations, input parameters include regulations pertaining to lot lines, setbacks, and Floor Area Ratio (F.A.R.). Setbacks are established to achieve various urban planning goals, such as ensuring adequate light, air, and space between buildings, promoting safety, and managing environmental concerns.The Floor Area Ratio refers to the total floor area of a building in relation to the size of the lot or parcel of land on which it is built. We construct setbacks by offsetting the original site boundary, within which building dimensions are accommodated and multiplied by F.A.R. standards.
Regarding program requirements, live conditions such as height limits and floor heights are considered. The maximum building area is determined according to regulations and building codes, considering anticipated height limits divided by floor heights.
Integration
When working with multiple components in Grasshopper, controlling data flow becomes essential. The Stream Gate component functions as a valve, allowing the user to manage data flow through specific branches of the data stream. This control enables efficient management of data paths based on defined conditions of our script.
The “Series” component in Grasshopper requires three inputs: “Start” for the initial value, “Step” for the increment between each consecutive number, and “Count” for the total number of values. Once set, it generates a list of numbers following these parameters. When paired with the “Extrusion” component, it allows for the creation of 3D geometries by extruding shapes along the Z-axis with a specified unit length. The extrusion element is then considered to be visualized as the altering floor levels.
Featured in these images is the repeated approach for each program segment. The commercial space has a corresponding script that has applied parameters similar to the residential areas considering applied parameters.
In conclusion, automating massing based on square footage for programs and zoning using Grasshopper scripts offers advantages and challenges. Grasshopper’s efficiency iterates and explores design configurations, providing precise parametric control and flexibility in incorporating intricate algorithms. However, a limitation arises from the necessity of input parameters such as varying building height restrictions, zoning metrics, or maximum square footage based on the program. This requirement can slow the workflow and require additional user input, impacting the overall automation process. There is also a limitation to the lot line or geometry the script is given; it can limit creative ideas of options. Despite this challenge, Grasshopper remains a valuable tool for streamlining massing design processes, offering designers the ability to explore and refine design solutions efficiently.
