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Systemic Adaptation of Soviet Mass Housing: A Computational Framework for Spatial and Structural Spatial Reorganisation

Ledina, Telma Tereze LU (2026) ASEM01 20261
Department of Architecture and Built Environment
Abstract
This thesis aims to address a dual crisis. Globally, the construction industry relies on a linear “take-make-dispose” approach and a “tabula rasa” tactic in each novel project, draining the Earth’s resources. Locally, around a half of residential buildings in Riga, Latvia, are of Soviet mass housing typology. These structures are on the verge of structural expiration, at risk of progressive collapse, and are spatially obsolete. Because conventional architectural methods, such as façade thermal insulation and renovation projects, fail to address the core spatial and structural issues due to the inherent structural complexity and rigidity of prefabricated concrete panel structures, a new approach must be designed.
Using the prevalent Soviet... (More)
This thesis aims to address a dual crisis. Globally, the construction industry relies on a linear “take-make-dispose” approach and a “tabula rasa” tactic in each novel project, draining the Earth’s resources. Locally, around a half of residential buildings in Riga, Latvia, are of Soviet mass housing typology. These structures are on the verge of structural expiration, at risk of progressive collapse, and are spatially obsolete. Because conventional architectural methods, such as façade thermal insulation and renovation projects, fail to address the core spatial and structural issues due to the inherent structural complexity and rigidity of prefabricated concrete panel structures, a new approach must be designed.
Using the prevalent Soviet series 1-464A as an object building, this research proposes a computational methodology for adaptive transformation, “self-cannibalization”, and circular material reuse. Leveraging the building’s modularity, a high-reliability digital twin of each element, as well as the overall assembly, was created. Next, the structural scheme was evaluated to form a structural dependency matrix. From this, a custom dependency script was developed to enable precise structural reliance detection.
Guided by a visual input tool – a grayscale image sampler – the user proposes spatial alterations of the building. The algorithm then uses the established dependencies, as well as the user input, to determine forced alteration versus “free to alter” ones. Additionally, this system accounts for all material and elements removed to enable immediate circular reapplication in the architectural synthesis stage.
Tested through a series of experiments, this tool successfully bridges user-guided design with computational logic. The final architectural synthesis output proves that the system successfully enables spatial reorganization while retaining the structural integrity of the building. Ultimately, this methodology challenges the construction industry’s reliance on raw material consumption, simultaneously extending the life span of “expired” buildings. (Less)
Please use this url to cite or link to this publication:
author
Ledina, Telma Tereze LU
supervisor
organization
course
ASEM01 20261
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Computational Design, Adaptive Reuse, Material Reclamation, Soviet Mass Housing, Buildings as Material Banks, Generative Deconstruction, Digital Architecture, Spatial Reorganisation, Prefabricated Concrete Panels
language
English
id
9232849
date added to LUP
2026-06-08 11:44:39
date last changed
2026-06-08 11:44:39
@misc{9232849,
  abstract     = {{This thesis aims to address a dual crisis. Globally, the construction industry relies on a linear “take-make-dispose” approach and a “tabula rasa” tactic in each novel project, draining the Earth’s resources. Locally, around a half of residential buildings in Riga, Latvia, are of Soviet mass housing typology. These structures are on the verge of structural expiration, at risk of progressive collapse, and are spatially obsolete. Because conventional architectural methods, such as façade thermal insulation and renovation projects, fail to address the core spatial and structural issues due to the inherent structural complexity and rigidity of prefabricated concrete panel structures, a new approach must be designed.
Using the prevalent Soviet series 1-464A as an object building, this research proposes a computational methodology for adaptive transformation, “self-cannibalization”, and circular material reuse. Leveraging the building’s modularity, a high-reliability digital twin of each element, as well as the overall assembly, was created. Next, the structural scheme was evaluated to form a structural dependency matrix. From this, a custom dependency script was developed to enable precise structural reliance detection.
Guided by a visual input tool – a grayscale image sampler – the user proposes spatial alterations of the building. The algorithm then uses the established dependencies, as well as the user input, to determine forced alteration versus “free to alter” ones. Additionally, this system accounts for all material and elements removed to enable immediate circular reapplication in the architectural synthesis stage.
Tested through a series of experiments, this tool successfully bridges user-guided design with computational logic. The final architectural synthesis output proves that the system successfully enables spatial reorganization while retaining the structural integrity of the building. Ultimately, this methodology challenges the construction industry’s reliance on raw material consumption, simultaneously extending the life span of “expired” buildings.}},
  author       = {{Ledina, Telma Tereze}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Systemic Adaptation of Soviet Mass Housing: A Computational Framework for Spatial and Structural Spatial Reorganisation}},
  year         = {{2026}},
}