Doğa bilgili mimarlık (DBM): Kristallerdeki kusurlardan öğrenmek

The transformation of design problems, processes, and praxis of construction by continuously increasing data mass is one of the major concerns of this dissertation. In this change, nature is re-emerging as an important source of information in the search for such processes, in which architects become not only their designers but also their programmers and even their supervisors. This dissertation values defects in nature and abiotic part of it as a source of information in design. While the majority of current nature-based studies are mostly focused on the biotic part of nature with its flawless forms, patterns, and behaviors as a reference, nature also offers various exciting references showing how to deal with defects and encouraging examples in diverse entities of abiotic nature. Therefore, in this thesis, the relation between nature and architecture is revisited focusing on abiotic nature, defects, and the method of learning from them. The information of defects in nature are found valuable to be learnt from for architecture, not only to adopt the strategies of nature to cope with them, but also to understand the role of defects on the responsive, adaptive and resilient nature of beings. With transferring the information of defects, it is aimed to be find the fitness defects of architecture that will enable us to fit new and challenging environments and technologies. The resultant approach encapsulating all these constituents, which is called nature-informed architecture (NiA), is proposed. In the scope of NiA, the concepts of data, data literacy, capta, and model are revisited and well-known terms like scale, precision, and accuracy are redefined. Hence, a new metadata model, named transfer learning model (TLM), defining the data transfer from one domain to another is introduced. In this context, crystal formations are studied, a computational model revealing the behaviors observed in crystal formation is developed; then, this model is employed to inform the models created for extended design processes encapsulating form, fabrication and construction specific parameters for additive and modular construction techniques.