Malzeme İnovasyonu ve Ekolojik Zekâya Sahip Mimarlık için Kod Tabanlı Bakteriyel Selüloz Büyüme Simülasyonu

Abstract

Bakteriyel selüloz, kendini organize eden lif ağlarıyla, biyomimetik ve sürdürülebilir malzeme tasarımı için umut vadeden bir model sunmaktadır. Bu çalışma, bakteriyel selüloz lif ağlarının büyümesini, difüzyon sınırlı birikim (DLA) algoritması kullanarak hesaplamalı olarak araştırmakta ve bu doğal desenlerin ekolojik ve rejeneratif tasarım uygulamalarına nasıl ilham verebileceğini anlamayı amaçlamaktadır. Bu ağların oluşumunun simüle edilmesiyle, DLA algoritmasının bakteriyel selülozun büyüme sürecinde var olan karmaşıklığı ve uyarlanabilirliği taklit etme potansiyeli incelenmiştir. Sonuçlar, DLA’nın yalnızca bakteriyel selülozun yapısal organizasyonunu taklit etmekle kalmadığını, aynı zamanda malzeme özelliklerini ekolojik uygulamalar için optimize etmeye yönelik yeni içgörüler sunduğunu göstermektedir. Kod tabanlı bu hesaplamalı yaklaşım aracılığıyla, bu araştırma tasarımda ekolojik zekâya yönelik çalışmalara katkıda bulunmayı hedeflemekte ve sürdürülebilirlik ve dayanıklılığı teşvik eden biyomimetik malzemelerin geliştirilmesi için bir çerçeve sunmaktadır. Araştırma, mikrobiyal süreçler ile hesaplamalı tasarımı bir araya getirerek, malzeme inovasyonu ve rejeneratif mimarlıkta ekolojik zekânın uygulanmasını ileriye taşımaktadır.

Keywords

• Bakteriyel selüloz
• rejeneratif tasarım
• hesaplamalı tasarım
• difüzyon sınırlı birikim.

Code-driven Simulation of Bacterial Cellulose Growth for Material Innovation and Eco-intelligent Architecture

Abstract

Bacterial cellulose, with its self-organizing fiber networks, offers a promising model for bio-inspired, sustainable material design. This study explores the computational growth of bacterial cellulose fiber networks using the diffusion-limited aggregation (DLA) algorithm, aiming to decode how these natural patterns can inform ecological and regenerative design practices. By simulating the formation of these networks, the potential of DLA to replicate the complexity and adaptability inherent in bacterial cellulose’s growth process is investigated. The results demonstrate that DLA not only mimics the structural organization of bacterial cellulose but also offers new insights into optimizing material properties for ecological applications for a guided growth. Through this code-driven computational approach, this research aims to contribute to the growing body of work on ecological intelligence in design, providing a framework for developing biomimetic materials that promote sustainability and resilience. This research bridges microbial processes with computational design, advancing the application of ecological intelligence in material innovation and regenerative architecture.

Keywords

• Bacterial cellulose
• regenerative design
• computational design
• diffusion-limited aggregation

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