Modular Design Optimization for Multi-Scale Construction Projects
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional multi-scale construction design approaches are limited by cascading dependencies between design stages, restricting the exploration and optimization of diverse design combinations across multiple goals and objectives, such as carbon emissions, habitability, and cost, due to computational resource constraints and the large number of possible permutations.
Innovation Solution
A modular design technique that generates and optimizes designs across multiple scales using a design optimization framework, which includes a site layout generator, building layout generator, design detail generator, and orchestrator, to reduce dependencies between smaller and larger-scale designs, employing modular representations and iterative optimization methods to explore a diverse range of design attributes and objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional sequential multi-scale design approaches are used, then design stages can be completed in a structured manner, but the exploration of diverse design combinations is restricted due to cascading dependencies
Solution Approach 1:
The patent segments the design space into discrete modular units (e.g., spatial bins, design attributes) that can be independently varied. This allows the system to explore diverse design combinations by recombining modular units without being constrained by sequential dependencies, thus resolving the contradiction between structured process and design versatility
Solution Approach 2:
The system dynamically adjusts the design exploration process by iteratively generating and evaluating design combinations based on performance metrics. Rather than following a fixed sequential path, the system adapts its exploration strategy to balance structured progression with diverse combination generation, enabling both ease of manufacture and adaptability
2Reliability
If all possible design permutations are explored to optimize multiple goals, then comprehensive optimization is achieved, but computational resources are exceeded
Solution Approach 1:
The system performs partial exploration of the design space by focusing computational resources on generating and evaluating a representative subset of design combinations. Rather than exhaustively exploring all permutations, it uses performance metrics and diversity objectives to guide exploration toward the most promising regions, achieving comprehensive optimization of key goals without exceeding computational resources
Solution Approach 2:
The system changes parameters by varying design attributes (e.g., spatial configurations, building densities, unit types) within defined ranges and evaluating their impact on performance metrics. This parameter-based approach allows systematic exploration of design trade-offs while maintaining computational efficiency through targeted variation rather than full permutation enumeration
3Stability of the object's composition
If cascading dependencies are enforced from larger to smaller design scales, then design consistency is maintained, but certain design combinations are excluded
Solution Approach 1:
The patent adds a new dimension to design exploration by treating design attributes and spatial configurations as independent variables that can be varied simultaneously across multiple scales. This multi-dimensional approach allows the system to maintain design consistency through coordinated variation while excluding fewer combinations, as it can explore attribute-space rather than being constrained to sequential scale-based dependencies
Data Source
Figure 1
Figure 2
Figure 3A
AI summary
A method for generating a modular design for a construction project includes determining (414) a first set of candidate designs for the construction project. The method also includes for each candidate design included in the first set of candidate designs, generating (404) a set of design options based on one or more portions of the candidate design and determining (406, 410) a set of performance metrics and a set of attributes associated with the set of design options. The method further includes generating a second set of candidate designs for the construction project based on the sets of design options associated with the first set of candidate designs, the sets of performance metrics associated with the sets of design options, and the sets of attributes associated with the sets of design options.