Search

Architectural construction is responsible for the consumption of large amounts of resources, so the optimization of architectural design and evaluation is significant for sustainable global development. Most architectural assessments focus on energy conservation, novel materials and eco-friendly strategies, but without agreed indicators and criteria. Since the consideration of natural aspects is somewhat fuzzy and vague, this study utilized data mining technology to explore the major factors related to relationships between buildings and nature. By employing the popular technique of web crawling, this study collected 38,320 architectural descriptions from the "Archdaily", including descriptions of 11 types of buildings, four of which were taken as typical research representatives. The 100 most frequent words were used to create a word cloud. Using Python script, all of the text was refined and processed with the word2vec model, thereby allowing to conduct Agglomerative Hierarchical Clustering (AHC). The frequency of words related to natural aspects were analyzed within 15 architectural design elements. Different building types in different areas have obvious similarities in terms of design elements, so it is feasible to adopt the same evaluation factors for the building evaluation systems of different regions. This paper mainly focuses on improving the accuracy and validity of assessment by providing basic evaluation indicators that could enhance connections between design and evaluation progress, stimulating the improvement of building environmental performance. [ABSTRACT FROM AUTHOR]

Currently, there is a lack of accurate simulation tools for the thermal performance modeling of courtyards due to their intricate thermodynamics. Machine Learning (ML) models have previously been used to predict and evaluate the structural performance of buildings as a means of solving complex mathematical problems. Nevertheless, the microclimatic conditions of the building surroundings have not been as thoroughly addressed by these methodologies. To this end, in this paper, the adaptation of ML techniques as a more comprehensive methodology to fill this research gap, covering not only the prediction of the courtyard microclimate but also the interpretation of experimental data and pattern recognition, is proposed. Accordingly, based on the climate zoning and aspect ratios of 32 monitored case studies located in the South of Spain, the Support Vector Regression (SVR) method was applied to predict the measured temperature inside the courtyard. The results provided by this strategy showed good accuracy when compared to monitored data. In particular, for two representative case studies, if the daytime slot with the highest urban overheating is considered, the relative error is almost below 0.05%. Additionally, values for statistical parameters are in good agreement with other studies in the literature, which use more computationally expensive CFD models and show more accuracy than existing commercial tools. [ABSTRACT FROM AUTHOR]

Building constraints hinder building operations from meeting a project's time, budget, and quality objectives. For a construction project to provide satisfying results, it is essential to recognize and address such constraints early on. Unfortunately, research on the causes of building constraints and their implications for building management has been limited. Therefore, there is a pressing need to study the sources of constraints and how they impact project results. Consequently, this study addresses this gap by examining the hurdles confronting Egypt's general building construction projects. Building constraints were identified from previous studies, which were then contextually investigated using a survey questionnaire within the Egyptian construction sector. The exploratory factor analysis (EFA) findings indicated that the constraint factors could be divided into six constructs: environment, stakeholders, regulations, policies, management, and traditional beliefs and ownership. Partial least square structural equation modeling was also utilized to create a constraint factor model. The findings demonstrated that environmental restrictions were significant obstacles to the effective execution of a project. The results of this research can assist decision makers in Egypt's building sector in cutting costs and improving sustainability by easing the effects of limiting variables. [ABSTRACT FROM AUTHOR]

The analysis and modeling of unconventional thermal zones is a first step for the inclusion of low-cost spaces and for the assessment of the environmental impact among areas of human use in warm climates. In this paper, the heat transfer in a geodesic dome located at the University of Magdalena (Colombia) is modeled and simulated. The simulator is calibrated against experimental measurements and used to study the effect of different loads which are regulated by a controller in sliding modes explicitly designed for this case. The closed-loop system is used together with ASHRAE Standard 55 to characterize comfort conditions within the dome and the effect on the overall thermal sensation with increasing the number of occupants. [ABSTRACT FROM AUTHOR]

With rapid economic development and restructuring, the number of old or obsolete buildings is growing in large cities. Construction practice has actively focused in recent decades on the regeneration of brownfield areas and creating opportunities for their cost-effective and sustainable reuse. Some of the buildings could be identified as-built industrial heritage whose purpose could be modified and used differently. Adaptive reuse can make a major contribution to sustainable development by reducing construction waste and saving natural resources. In the reuse management process, the problem is how to deal with multiple criteria that are imposed as factors in assessing the reuse of a building. Using the adjusted fuzzy analytical hierarchy process (FAHP), we explore the potential for the adaptation and new use of industrial buildings in the former area of Electronic Industry Nis (EI Nis) in Serbia. The standard FAHP, in which we determine the weights of each sub-criterion based on the expert's evaluation, we adjusted for use when no pairwise comparison of existing alternatives was available. Multiple criteria evaluation was performed by applying many criteria and sub-criteria, taking into account the different spatial and physical performance of buildings, as well as their locational indicators. A case study is used to demonstrate the application of the method and show its effectiveness. [ABSTRACT FROM AUTHOR]

There is an increasing interest in reducing the energy consumption in buildings and in improving their energy efficiency. Building retrofitting is the employed solution for enhancing the energy efficiency in existing buildings. However, the actual performance after retrofitting should be analysed to check the effectiveness of the energy conservation measures. The aim of this work was to detect and to quantify the impact that a retrofitting had in the electrical consumption, heating demands, lighting and temperatures of a building located in the north of Spain. The methodology employed is the application of Functional Data Analyses (FDA) in comparison with classic mathematical techniques such as the Analysis of Variance (ANOVA). The methods that are commonly used for assessing building refurbishment are based on vectorial approaches. The novelty of this work is the application of FDA for assessing the energy performance of renovated buildings. The study proves that more accurate and realistic results are obtained working with correlated datasets than with independently distributed observations of classical methods. Moreover, the electrical savings reached values of more than 70% and the heating demands were reduced more than 15% for all floors in the building. [ABSTRACT FROM AUTHOR]