Ossature: Bone Remodeling as a Generative Structuring Process in Architecture
Notice bibliographique
Résumé
There is an inherent and complex interrelationship between material, structure and form that exists in nature, whereby each informs the other through a dynamic process.In nature, form is not imposed; instead it emerges as an expression and articulation of dynamic material responses to environmental stresses and circumstances.I propose looking at this responsive form generation as a model for developing architectural structures.Specifically, this thesis proposes looking at bone tissue remodeling as a new generative process for structure in architecture.Bone tissue becomes highly optimized by the self-organizing and remodeling of its structure in response to loads; creating a complex structure that is both high in strength and low in weight.Its shape is directly informed by the forces acting upon and within it; material and structure are distributed along stress paths three dimensionally.The objective of this research will be to examine the feasibility of utilizing bone remodeling algorithms as a generative design tool in the development of structures in architecture.iii Definitions Algorithm -A sequence or procedure for calculation Additive Manufacturing (AM) -The process of making a three-dimensional object by successively adding layers of material Anisotropy -The property of being directionally dependent Bidirectional Evolutionary Structural Optimization (BESO) -Based on FEM, iteratively adds or removes material from a structure Computer-Aided Optimization (CAO) -Based on FEM, this method thickens highly stress areas of a structure much like a tree Computer Aided Internal Optimization (CAIO) -Based on FEM, optimizes fiber orientation within an object Evolutionary Structural Optimization (ESO) -Based on FEM, iteratively removes unused material from a structure Finite Element Analysis (FEA) -The application of FEM to solve engineering problems Finite Element Method (FEM) -An analysis technique used to solve a complex equation using many smaller equations Generative -Refers to a rule based system where complex behaviours emerge from the interaction of simpler elements Isotropy -Identical properties in all directions Load -a force applied to a structure causing stress, deformation or displacement Optimization -In engineering, refers to the selection of the best solution from a set for the condition of maximizing or minimizing a desired property iv Soft Kill Option (SKO) -Based on FEM, removes under-stressed material within a design boundary Strain -A measure of deformation representing displacement relative to a reference length Stress -In engineering, refers to the measurable quantity of internal forces of an object Topology -The study of surfaces, concerned with preserving spatial properties under deformation Topology Optimization -A mathematical approach that optimizes material layout within a design space for a given set of loads so that the result meets desired performance targets Von Mises Stress -A criterion used to predict yielding of materials under any loading condition Voronoi -A way of dividing space into regions where a set of points has a corresponding region consisting of all points closer to it than to any other Young's Modulus -A measure of the stiffness of an elastic material defined by the ratio of stress along an axis over strain v Acknowledgements Firstly, a thank you to my supervisor, Manuel Baez, for your insight and relentless urging to do better.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,007 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».