Pre-diploma topics for Winter Semester 2022-2023
Here is a list of Pre-diploma topics suggested by the LSU team. Students can select between these topics or suggest their own. The following topics are divided into sub-categories based on their general fields of structures, natural-based design, patterns, artificial intelligence, human-machine interaction, and fabrication-based design.
Field | Topic | |
|---|---|---|
| structures | Structural forms based on elastically-bent modules (Exploring bending-active modules with the potential of being used as structural elements and how they can combine to generate structural forms) | |
| structures | Structural optimization on elastic gridshell topologies (The importance of grid topology on structural performance of elastic gridshells and applying optimization algorithms to get optimum results) | |
| structures | Design of adaptive spatial structures (Exploring structures that can respond to environmental parameters) | |
| structures | Transformable structures (Exploring the possibilities of elastically-bent elements and connections in changing form) | |
| structures | Structural form-finding of shells (Studying the structural form-finding methods and comparing them for the design of shells) | |
| Nature_based | Growing spatial structures (Exploration of natural growth systems and their implementation on form-finding of spatial structures) | |
| Nature_based | Natural principle study in structural form-finding (Studying the architecture of naturaly built structures such as animal nests, spider web to implement them in design) | |
| patterns | Exploration on the gridshell topologies (Exploring the possible topologies of structural pattern of gridshells, their effect on structural performance, aesthetics, and architectural aspects) | |
| patterns | Structural design based on natural pattern exploration (Exploring natural patterns such as plants, and trees and finding their application in design of structures) | |
| Artifical intelligence | Deep-learning for structural form-finding (Implementation of deep-learning as an alternative to common methods of structural form-finding such as physical or FEM analysis) | |
| Artifical intelligence | Intelligent generative design (Using machine learning systems to improve the generative design process) | |
| Artifical intelligence | Artificial intelligence for design exploration (Decision-making in exploring the design space using supervised, semi-supervised, and unsupervised learning methods) | |
| Human-machine interaction | Cyber-physical systems in design (Combining digital and physical environments in design) | |
| Human-machine interaction | Computer vision in interactive design (A design framework based on user interaction and gesture) | |
| Fabrication-based | Design for assembly and disassembly (Particle-based systems and using modulear or semi-modular elements for genearing structures that can be assembled and dissambled easily to shape different forms) |
