Bioclimatism in Architecture : an evolutionary perspective

The well-known Darwinian evolutionary theory (1859) introduced natural selection as the most important mechanism of evolutionary processes at every level from biological systems, including species, individual organisms... to molecules, such as DNA or proteins. In architecture we observe similar evolution processes, which lead to the development of various architectural movements and concepts from common primitive living structures. Fundamentals of vernacular architecture have been used in bioclimatic architecture, which has gradually become the inspiration of various movements in contemporary architecture. The study points out that the development of bioclimatism in architecture has followed the pattern of a natural evolutionary process in which ‘natural selection’ is likely motivated by several factors, including resources and environment problems, and driven by different mechanisms including novel building design concepts and methods, new standards and codes, discoveries in building science and construction costs. This study is an effort aimed to clarify the evolution process of the bioclimatic approach in architecture over time and its influences on contemporary movements in architecture. The paper shows also that the evolutionary theory generated new scientific tools able to improve building design thanks to simulation-based optimization methods applied to building performances. Finally, this study investigates new motivations in the era of climate change whose effects are expected to introduce more challenges as well as more trends towards a sustainable built environment through the new concept of Eco-adaptive architecture.

[1]  Weimin Wang,et al.  Applying multi-objective genetic algorithms in green building design optimization , 2005 .

[2]  Anh Tuan Nguyen,et al.  Passive designs and strategies for low-cost housing using simulation-based optimization and different thermal comfort criteria , 2014 .

[3]  Sigrid Reiter,et al.  AN ADAPTIVE THERMAL COMFORT MODEL FOR HOT HUMID SOUTH- EAST ASIA , 2012 .

[4]  Jonathan A. Wright,et al.  A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization , 2004 .

[5]  A. S. FRASER,et al.  Monte Carlo Analyses of Genetic Models , 1958, Nature.

[6]  Sigrid Reiter,et al.  Assessing Wind Comfort in Urban Planning , 2010 .

[7]  Sigrid Reiter,et al.  Toward low energy cities : A case study of the urban area of Liège , 2012 .

[8]  C. Darwin.  The Origin of Species by Means of Natural Selection, Or, The Preservation of Favoured Races in the Struggle for Life , 1859 .

[9]  Anh Tuan Nguyen,et al.  The efficiency of different simulation-based design methods in improving building performance , 2014, ARC 2014.

[10]  Sigrid Reiter,et al.  A performance comparison of sensitivity analysis methods for building energy models , 2015 .

[11]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[12]  Jihun Kim,et al.  Building form optimization in early design stage to reduce adverse wind condition - using computational fluid dynamics , 2011 .

[13]  Fariborz Haghighat,et al.  Multiobjective optimization of building design using TRNSYS simulations, genetic algorithm, and Artificial Neural Network , 2010 .

[14]  Sigrid Reiter,et al.  An investigation on thermal performance of a low cost apartment in hot humid climate of Danang , 2012 .

[15]  Mo Jamshidi,et al.  Tools for intelligent control: fuzzy controllers, neural networks and genetic algorithms , 2003, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[16]  V. Olgyay.  Design With Climate: Bioclimatic Approach to Architectural Regionalism , 1963 .

[17]  Donald Watson,et al.  Climatic Design: Energy-Efficient Building Principles and Practices , 1983 .

[18]  Frank Jochen Dieterle,et al.  Multianalyte Quantifications by Means of Integration of Artificial Neural Networks, Genetic Algorithms and Chemometrics for Time-Resolved Analytical Data , 2003 .

[19]  Anh Tuan Nguyen,et al.  The effect of ceiling configurations on indoor air motion and ventilation flow rates , 2011 .

[20]  Sigrid Reiter,et al.  An investigation on climate responsive design strategies of vernacular housing in Vietnam , 2011 .

[21]  William L. Newman,et al.  The Geologic Time Spiral - A Path to the Past , 2008 .

[22]  Manjusha Misra.  Bioclimatic housing: innovative designs for warm climates , 2013 .

[23]  Ola Wedebrunn,et al.  Climate and architecture , 2010 .

[24]  A. Marshall,et al.  QUESTIONING THE THEORY AND PRACTICE OF BIOMIMICRY , 2009 .

[25]  Sigrid Reiter,et al.  A climate analysis tool for passive heating and cooling strategies in hot humid climate based on Typical Meteorological Year data sets , 2014 .

[26]  Sigrid Reiter,et al.  A method to evaluate the energy consumption of suburban neighborhoods , 2011 .

[27]  Sigrid Reiter,et al.  Coupling building energy simulation and computational fluid dynamics: application to a two-storey house in a temperate climate , 2014 .

[28]  Sigrid Reiter,et al.  A simplified framework to assess the feasibility of zero-energy at the neighbourhood/community scale , 2014 .

[29]  Philippe Rigo,et al.  A review on simulation-based optimization methods applied to building performance analysis , 2014 .