► An approach for developing guidelines on sensitive and robust design parameters. ► We present the application of the approach to an actual case study in Turkey. ► Global sensitivity analysis can be ...used to develop guidelines. ► The approach is helpful during the design of low-rise apartment buildings.
High levels of energy consumption in residential buildings and global warming are important issues. Thus the energy performance of buildings should be improved in the early stages of design. This article describes an approach for developing guidelines on sensitive and robust design parameters for the present, the 2020s, the 2050s and the 2080s. Such guidelines can help architects to design low-rise apartment buildings that require less energy for various purposes, such as heating or cooling. The article consists of a general literature review, interviews with architects, the generation of case-specific information and a mock-up presentation and a meeting with professionals. An example guideline that aims to reduce annual cooling energy loads under global warming in low-rise apartment buildings located in hot-humid climates is presented to demonstrate how the proposed approach can be applied. For this guideline, case-specific information was generated, and a global sensitivity analysis based on Monte Carlo Analysis and the Latin Hypercube Sampling technique was performed. The results show that the suggested approach is feasible and could be used to provide helpful information to architects during the design of low-rise apartment buildings with high energy performance. The most sensitive design parameters that affect annual cooling energy loads in low-rise apartment buildings were natural ventilation, window area, and the solar heat-gain coefficient (SHGC) of the glazing. The results are relevant for the present, the 2020s, the 2050s and the 2080s.
In this research, several models were developed to forecast the daily mean indoor temperature (IT) and relative humidity values in an education building in Izmir, Turkey. The city is located at a ...hot–humid climatic region. In order to forecast the IT and internal relative humidity (IRH) parameters in the building, a number of artificial neural networks (ANN) models were trained and tested with a dataset including outdoor climatic conditions, day of year and indoor thermal comfort parameters. The indoor thermal comfort parameters, namely, IT and IRH values between 6 June and 21 September 2009 were collected via HOBO data logger. Fraction of variance (R2) and root-mean squared error values calculated by the use of the outputs of different ANN architectures were compared. Moreover, several multiple regression models were developed to question their performance in comparison with those of ANNs. The results showed that an ANN model trained with inconsiderable amount of data was successful in the prediction of IT and IRH parameters in education buildings. It should be emphasized that this model can be benefited in the prediction of indoor thermal comfort conditions, energy requirements, and heating, ventilating and air conditioning system size.
Selection of an appropriate structural system for an industrial facility is a difficult task for decision makers since it is the essential component, and it is hard to satisfy the owner's demands as ...well as the legal requirements. There are many conflicting preferences that have to be considered to assess the performance of the structural system alternatives. Decision support systems (DSSs) such as multi-criteria decision-making (MCDM) methods are useful in making an objective and rational choice. It is important to use MCDM methods in order to analytically evaluate different factors affecting the structural system selection. To address these challenges, the selection of the structural system of an industrial facility project in Turkey was carried out by applying Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) MCDM methods. Eight evaluation criteria were determined for the selection process within the scope of the study, which are project cost, project duration, project lifetime, labour and equipment requirement, recycling opportunities, resistance to environmental effects, suitability for installation and natural lighting needs. Prefabricated reinforced concrete (PRC), on-site reinforced concrete (RC) and steel structural system alternatives were evaluated according to each criterion by a survey study conducted by 193 civil engineer participants. Using the AHP and TOPSIS methods, it is determined that the most suitable alternative for industrial facilities is the steel structural framing system. The results were argued with the design team, and they confirmed that MCDM methods could be easily integrated in selecting the most appropriate structural system.
•A historical public building built in 19th century is selected as a case study.•Real energy consumption, temperature and relative humidity data is collected.•The dynamic building energy-performance ...simulations are validated by real data.•365 energy-retrofit packages are applied to reduce the total energy consumption.•The cost-optimal energy analysis of the historical building is performed.
The energy efficiency concept has attracted significant attention over the last few years and has taken a prominent role in the development goals of countries. Considering that buildings have a high share in total energy consumption, it is crucial to improve their energy performance both in environmental and economic terms. Although efforts in increasing buildings’ energy efficiency have primarily focused on new buildings, existing buildings still retain their importance. Historical buildings are included in the existing building stock. It is essential to increase their energy efficiency to achieve carbon–neutral building targets set from EU Directives. In this paper, we proposed measures to improve the energy efficiency and determine cost‐optimal levels of a public historical building located in a hot-humid climate zone of Turkey. An integrated approach based on in situ measurements and building energy simulations was used to create a building energy model that was calibrated by using real measurements. Then, 365 energy-efficient measures are applied to the building and conducted an economic feasibility study by utilizing a cost-optimal envelope, lighting, heat pump and photovoltaic panel. A sensitivity analysis is performed to determine the impact of investing on optimal cost-of-energy level calculations with focus on the inflation rate, different interest rates, and calculation periods. Sensitivity analysis of discount rate has shown when the discount rate increases, global costs decrease. It is observed that the changes in economic parameters that could cause a decrease in annual costs reduced the cost effectiveness of the scenarios with high initial investment costs.
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