With the development of the biomimicry approach, new and creative ideas have been established to solve problems in architectural design. In the designs based on this process, “nature” is used as a diverse data source for the transfer of these data to various processes, functions, materials, and structures. The primary purpose of this paper is to explore the development of biomimicry as an architectural approach, with a bibliometric review of research related to biomimicry and energy efficiency. Emphasis on the importance of the need for biomimicry in modern designs is another goal of this study. In this study, articles published in the Web of Science database (2010–2021) were analyzed. VOSviewer and SankeyMATIC software were used to represent the analysis results graphically. According to the results of this study, in addition to the inadequacy of biomimicry research, the need for further research became apparent. This review can serve as a reference for future studies to transfer natural phenomena to architecture in order to solve the problem of efficient energy consumption.

Through the recent technological developments within the fourth industrial revolution, artificial intelligence (AI) studies have had a huge impact on various disciplines such as social sciences, information communication technologies (ICTs), architecture, engineering, and construction (AEC). Regarding decision-making and forecasting systems in particular, AI and machine learning (ML) technologies have provided an opportunity to improve the mutual relationships between machines and humans. When the connection between ML and architecture is considered, it is possible to claim that there is no parallel acceleration as in other disciplines. In this study, and considering the latest breakthroughs, we focus on revealing what ML and architecture have in common. Our focal point is to reveal common points by classifying and analyzing current literature through describing the potential of ML in architecture. Studies conducted using ML techniques and subsets of AI technologies were used in this paper, and the resulting data were interpreted using the bibliometric analysis method. In order to discuss the state-of-the-art research articles which have been published between 2014 and 2020, main subjects, subsets, and keywords were refined through the search engines. The statistical figures were demonstrated as huge datasets, and the results were clearly delineated through Sankey diagrams. Thanks to bibliometric analyses of the current literature of WOS (Web of Science), CUMINCAD (Cumulative Index about publications in Computer Aided Architectural Design supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD, and CAAD futures), predictable data have been presented allowing recommendations for possible future studies for researchers.

The effort to preserve historic buildings for the future has always been on the agenda of experts on local and global scales and been supported by many initiatives and strategies. Within the scope of this research, the concept of “adaptive reuse” which is often preferred as a conservation strategy for historic buildings, is discussed. The focus is on the adaptive reuse studies of historic buildings in literature that have managed to physically survive in the face of changing conditions; comprehensive and systematic research with a bibliometric analysis is presented. The study has been scanned in the Web of Science database under the heading “Title/Abstract/Keywords” and the data has been analyzed in detail with the VOSviewer program. The findings indicate the research trends in the literature and gaps for the future research. The results highlight the innovative approach for historic buildings in the context of the adaptive reuse strategy and present the field’s challenges, limitations and opportunities. It is expected this study will help researchers and policymakers to understand the evolutionary implications of conservation strategies and develop other theoretical and practical initiatives to be applied in this field.

Today, the building sector has a large share in global energy consumption. The building stock, which has increased with the increasing population, contributes more to this consumption day by day. School buildings, which constitute an important part of public buildings, are among the most used building types in the daily cycle and also have a high energy demand for heating, cooling and electricity loads. In Turkey, the implementation of the same type of school projects in different climate regions without considering the context and climatic conditions increases the amount of energy consumption. This study provides a framework for reducing energy loads in school buildings using passive design strategies. Located in two different climatic regions of Turkey, in Istanbul and Ankara, a primary school building is taken into consideration for comparison of type projects in the context of energy performance and single-objective optimization process to minimize energy use intensity (EUI). As a result of the optimization processes carried out depending on the parameters related to the building envelope, the energy performance for the Istanbul climate is improved by 5.05%, while this rate is 4.09% for the Ankara climate. The best solution individual parameters of both climate types have very close values to each other. It is thought that more efficient results can be obtained with the multi-objective optimization processes of the studies to be carried out to evaluate the type school projects on the basis of different climates.