Transformation, adaptive reuse, and circular construction

Adaptive Relocation

Computational Design Strategies for Spatial Memory Preservation in Climate-Driven Displacement Scenarios.

This thesis addresses the challenge of relocating communities displaced by environmental change, exploring how architecture, spatial memory and social relationships can be preserved and translated through computational design. 

As disaster-related displacement increases globally, the project responds to the urgent need for relocation strategies that balance spatial accuracy with cultural continuity, offering communities a process to engage with relocation, reflect on the spatial relationships they fear losing, and contribute to shaping possible futures. The research develops a digital workflow based on capturing architectural reality through LiDAR scanning and drone photogrammetry to document, analyse and translate the spatial relationships embedded in a Polish village threatened by flooding. By transforming the physical environment into a structured dataset for analysis and reinterpretation through point cloud processing, applying machine learning and artificial intelligence techniques, by neural network-based segmentation, the project extracts features and organises data into environmental, architectural and relational categories. This process enables the creation of geometric and informational models that catalogue building attributes, proximity, connections, orientation and topographic context. These coded parameters form the basis of an algorithmic system that reconfigures the village layout on new terrain. At its core, the project simulates relocation through an iterative optimisation process that balances environmental conditions with socio-spatial considerations. Digital agents, simulating residents' preferences, evaluate each configuration by assigning satisfaction scores, embedding a participatory dimension where community members interact with the simulation, encouraging dialogue and reflection as they explore evolving spatial scenarios. The result is a collection of spatial configurations, each visualising different trade-offs between technical constraints and human-centred values. By computationally documenting sites threatened by demolition or disaster, the project preserves them by proposing a digital negotiation method that frames architectural design as an act of translation, mediating between data and preserving the intangible qualities and identity of place in the context of environmental displacement.

Algorithmic Assembly procedure for Upcycled Concrete Rubble

The thesis project explores a circular approach to architectural design by developing an algorithmic method for vaulted floor slabs using re-assembled upcycled concrete rubble. 

The project aims to establish a reflection on the idea of the linear cradle-to-grave design -in which materials have a life ending- and propose a way to give them a new use and transform waste into resources (Lendager, Pedersen 2020). This project reimagines waste concrete as a valuable resource for new structures.

The design process begins with scanning irregular concrete rubble pieces using image processing libraries in Python (OpenCV) and converting 2D contours into scaled 3D geometries. A machine learning pipeline (PCA-based) is used to simulate additional rubble variations, expanding the digital stock of elements and embracing the ad-hoc condition of reclaimed concrete pieces.

Structural analysis and form finding methods are performed using Kiwi3D and Karamba, to simulate funicular vault shapes that efficiently transfer loads. These shapes guide a custom stacking algorithm built in Grasshopper, which uses OpenNest and iterative geometric optimization to minimize voids and maximize material use, achieving more than 90% packing efficiency.

A stability-checking algorithm further ensures that the assembled pieces align correctly within the stress lines, avoiding connections parallel to the structural efforts, reducing the risk of displacements and guaranteeing a correct stable assembly.

Finally, an LCA analysis is performed in a case study project, comparing the environmental impact of using upcycling construction methodologies versus the traditional construction method.

The system will demonstrate not only material and CO₂ reductions, but also adaptability and structural logic. This computational design workflow provides a scalable, replicable strategy for integrating reclaimed concrete into architectural practice, pointing towards a more circular and conscious design approach.

Death is not the end. Transforming Existing but unfinished structures: The case of Sefwi-Wiawso, Ghana

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Kulturbageriet: From abandoned industry to new social node in the countryside

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