In the initial planning phases, it is vital to promptly assess various design alternatives. Parametric modeling plays a crucial role in this context. It involves using computer software to create a flexible digital representation of architectural designs. This method enables a systematic exploration of different design options by adjusting key elements like the layout of urban elements, placement, components, and procedures. Integrating Life Cycle Assessment (LCA) into the parametric modeling process helps architects and engineers evaluate the environmental impact of different designs in a more streamlined way. By connecting the parametric model with LCA software or databases, this method automates the generation of LCA results for different design options. This allows for a real-time assessment and comparison of the environmental consequences associated with various design possibilities.
The use of parametric design, a computational approach, involves using algorithms to adjust design parameters, making it easier to assess various design options. This method shows promise in effectively addressing sustainability and environmental concerns in urban design, facilitating well-informed decision-making in the early stages of the design process. The use of parametric design is a significant and widespread trend in computational design research, aiming to improve project performance by incorporating considerations for microclimates and bioclimates. In urban planning, parametric design explores the connection between design and concepts like spatial arrangement, functionality, morphological organization, and architectural typology. Moreover, the application of parametric design has the potential to reduce energy consumption, especially when integrated into urban settings and building simulation software. This integration offers designers a valuable tool for creating environmentally sustainable urban environments.
Given the size and complexity of the challenge, a strategic solution involves dividing urban projects into separate categories.
These categories include:
- urban elements,
- urban landscape,
- urban infrastructure
These categories are meant to be tackled one after another to effectively lessen environmental impacts. The order of priority is determined by the perceived importance of each category in influencing the environment.
The initial phase focuses on urban elements, specifically different building types like residential, commercial, and industrial structures, along with their surroundings. This prioritization is justified by the significant effects these elements have, not only in terms of their environmental impact during construction but also because of substantial consequences throughout
their operational lifespan. Therefore, addressing these aspects in the first phase is considered crucial.
The next phase, which focuses on the urban landscape, is expected to overlap significantly with the first phase. After this, the final phase deals with urban infrastructure, considered the most complex stage of the project. Due to this complexity, it is necessary to integrate diverse expertise and use data from the earlier phases. Given its extensive scope and intricacy, it is recommended to approach the urban infrastructure phase independently. It is believed that the first two stages align with the constraints of the established challenge.
The approach to solve the challenge begins by using computer simulations tailored to the specific characteristics of the urban environment. The goal is to collect crucial data that helps evaluate the most environmentally friendly way to use the urban land. This information is then used to create a design for the urban features and structure that is guided by data. After gathering this information, the next step is to assess different design possibilities by running simulations for various stages of construction. Each construction stage has its own specific process that can be adjusted by the operator, allowing them to tweak various parameters to achieve the best outcome.
We will outline a systematic process, using parameters, to categorize different parts of the urban area, such as buildings and constructed spaces. These parts will then be broken down into smaller components like building facades, structures, green areas, and parking canopies. At the same time, we will create processes to simulate the energy needs of each part and outline how they are constructed. Another process will focus on what happens to these components at the end of their life. By using mathematical algorithms, we can estimate the total carbon footprint by combining the results from these
processes. Next, different buildings and materials will be assigned to each part. By using parametric design, we can measure and assess the total carbon footprint of each design. In the end, incorporating machine learning algorithms shows potential for improving designs and finding the best solution for the specific urban area in question. This thorough approach aims to systematically combine parametric design principles, simulation methods, and machine learning algorithms to develop and enhance sustainable urban design solutions.