The amount of received sunlight and radiant energy could affect the energy consumption in heating, cooling and lighting systems. Utilization of natural daylight in architecture, in addition to fulfilling the inhabitants' mental and physical needs, could greatly reduce fossil fuel consumption. Although higher levels of daylight can be obtained by increasing light transmission, this increased transmission could negatively affect the building's sustainability and thus result in higher energy consumption in turn. So, designers must seek an acceptable balance, in which not only optimal daylight comfort and usage are met but also the best possible thermal performance is achieved. The use of a parametric design model can facilitate the simulation of lighting and annual thermal performance of a building in the early stages of the design or restoration process. In this paper, the daylight and thermal performances of an office building are optimized using a simulated parametric-based design model and the Octopus plug-in which is an optimizing tool based on genetic algorithms developed for Grasshopper. By applying the developed workflow, the enhanced results for (useful daylight illuminance) is up by 20.56% and for energy use intensity by 141 kWh/m 2 /yr.

Studies of historical buildings in Persian architecture have resulted in knowing a kind of masonry structure with a harmonic lattice geometry, which has been titled “Karbandi.” The most important and highly acclaimed feature of Karbandi is the correlation and coordination between its architectural and structural functions, which results in creating esthetic and meaningful spaces. The use of this structure is highly demanded in contemporary Persian architecture, but very little information about historical techniques survives to the present day and accordingly, there are ambiguities about its drawing and geometric design. Therefore, this research aims at discovering geometric relationships and principles of Karbandi to regulate and facilitate its design process in contemporary architecture. Toward this end, its historical samples were analyzed and their geometric features were found. As a consequence, the connection distance of dividing points on the circle is an important parameter for creating various types of Karbandi on a base. For instance, the height of a Karbandi and its elaboration are directly related to the connection distance. In addition, it was clarified that the height of a Karbandi and the size of its Shamseh are in an inverse relationship. Finally, a comprehensive classification was presented based on found geometric features.

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PurposeHistorical bazaars, a huge treasure of Iranian culture, art and economy, are places for social capital development. Un-supervised management in past decades has led to the demolition and change of historical bazaars and negligence of its different aspects. The present research aims to investigate the resilience of historical bazaars preserving their identity and different developments.Design/methodology/approachThe artificial neural network (ANN) has been applied to investigate the resilience of historical bazaars. This model consists of three main networks for evaluating the resilience of historical networks in terms of adaptability, variability and reactivity.FindingsThe ANN proposed to evaluate the resilience of historic bazaars based on the mentioned factors is efficient. By calculating mean squared error (MSE), the model accuracy for evaluating adaptability, variability and reactivity were obtained at 7.62e-25, 2.91e-24 and 1.51e-24. The correlation coefficient was obtained at a significance level of 99%. This indicates the considerable effectiveness of the artificial intelligence model in modeling and predicting the qualitative properties of historical bazaars resilience.Originality/valueThis paper clarifies indexes and components of resilience in terms of adaptability, variability and reactivity. Then, the ANN model is obtained with the least error and very high accuracy that predict the resilience of historical bazaars.