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The beneficial effects of solar radiation on human health are well documented. One necessary mechanism triggers the production of vitamin D, whose insufficiency has been linked to a variety of disorders such as diabetes; hypertension; and, more recently, amyloidosis and Alzheimer's disease. However, there are few architectural designs capable of ensuring the adequate provision of solar radiation inside buildings. Conventional fenestration is not sufficient to provide for significant doses of sunlight, even to prevent seasonal affective disorder (SAD). In this paper, we discuss the effect of new design alternatives for skylights, especially in the refurbishment of obsolete facilities. Based on the authors' previous studies, we defined a theoretical model that was subsequently adapted to a real building that was to be retrofitted in an area near Sevilla. After such complex refurbishment was executed, we analyzed the performance of buildings in warm and sunny climates, as is the case of southern Spain, where cloudiness is very scarce and available simulation models are not useful. The study of the factors that relate to sunlight; UV reception and energy; and, to a certain extent, other aspects such as ventilation and insulation has been considered a priority. Many architectural designs are presented as correct if the thermal requirements alone are met, even at the risk of later energy waste in lighting devices and visual or physical discomfort. On the other hand, large glazed areas allow for more daylight and UV radiation into a space if properly treated, but they may also produce excessive heat gains or losses, which increase the air-conditioning cooling or heating load, respectively. The uncontrolled increase in temperature can have negative effects on the well-being of a person with Alzheimer's dementia. To avoid these problems, we have considered the combined effect of daylight and energy from the beginning of the skylight design-process. Daylighting software, based on configuration factors that we have applied in studies of the complex problem of there being direct sunlight over architectural structures, has been used. This question cannot be treated adequately with conventional programs for overcast skies. The skylights have already been constructed, with special UV increasing glazing and on-site measurements in the offices to complement the computer simulation data. The results show that it is possible to achieve energy saving and high radiation levels in winter without increasing heat loads during the summer. Ventilation is also improved through the aerodynamic design of the clerestories. All this is considered beneficial to improve the condition of users with cognitive diseases as Alzheimer's disease, by virtue of adapted spaces. [ABSTRACT FROM AUTHOR]

Cross-sectional energy benchmarking in the building domain has become crucial for policymakers, energy managers and property owners as they can compare an immovable property performance against its closest peers. For this, Key Performance Indicators (KPIs) are formulated, often relying on multiple and heterogeneous data sources which, combined, can be used to set benchmarks following normalization criteria. Geographically delimited parameters are important among these criteria because they enclose entities sharing key common characteristics the geometrical boundaries represent. Linking georeferenced heterogeneous data is not trivial, for it requires geographical aggregation, which is often taken for granted or hidden within a pre-processing activity in most energy benchmarking studies. In this article, a novel approach for Linked Data (LD) generation is presented as a methodological solution for data integration together with its application in the energy benchmarking use case. The methodology consists of eight phases that follow the best principles and recommend standards including the well-known GeoSPARQL Open Geospatial Consortium (OGC) for leveraging the geographical aggregation. Its feasibility is demonstrated by the integrated exploitation of INSPIRE-formatted cadastral data and the Buildings Performance Certifications (BPCs) available for the Catalonia region in Spain. The outcomes of this research support the adoption of the proposed methodology and provide the means for generating cross-sectional building energy benchmarking histograms from any-scale geographical aggregations on the fly. [ABSTRACT FROM AUTHOR]

Climate conditions affect buildings' performance and durability. The purpose of this paper is to examine the influence of climate conditions on roof deficiencies. 763 cases of such deficiencies were analyzed in this regard. Once the construction deficiencies were quantified, they were characterized from a climatological point of view and their 'climate location segments' were studied to obtain 'ranges of concentration of anomalies' according to the obtained percentage. A direct relation is shown to exist between the location of the building (latitude, situation, type of climate, precipitation, thermal demands, and average wind speed) and a greater or smaller concentration of deficiencies found in both flat and pitched buildings. It was also found that an annual average wind speed greater than 3 m/s increases the appearance of deficiencies in roofs. A higher prevalence of deficiencies was also found in those geographical zones with a thermal demand of 1800–2800 heating degree days or 450–700 cooling degree days. It was found that a higher percentage of construction deficiencies are concentrated in buildings located in the northern coastal climate segments of Spain. With these results, technicians will be able to take more appropriate precautions during both the building process and the use and maintenance phase. [ABSTRACT FROM AUTHOR]

Climate change will have a great impact on the hottest climates of southern Europe and the existing residential stock will be extremely vulnerable to these future climatic conditions. Therefore, there is an urgent need to update this building stock considering imminent global warming by applying climatic files that predict future conditions in building performance simulations. This research makes use of the two most applied tools (Meteonorm and CCWorldWeatherGen) for generating future climate hourly datasets for 2050 and 2080 in southern Spain. The results predicted for outdoor and indoor thermal conditions and cooling and heating demands are evaluated for two different scale simulation models: a test cell and a multi-family building located in southern Spain. The main aim of this work is the development of a comparative analysis of the results to highlight their potential differences and raise awareness of the influence of the climate data projection method on the simulation outcome. The results show that the projection method selected for producing future climatic files has relevant effects on the analysis of thermal comfort and energy demand, but it is considerably reduced when an annual evaluation is developed. [ABSTRACT FROM AUTHOR]

The energy-supply crisis, aggravated by the war in Ukraine, has prompted EU governments to approve urgent energy-saving measures. The new Spanish energy-saving standard aims to reduce energy consumption by changing the regulatory limits for indoor hygrothermal conditions in buildings. This regulation has provoked a great social debate about its real effectiveness and its impact on user comfort. This work explores the hygrothermal performance of an office building in southeastern Spain. The objective of this research is to determine qualitatively and quantitatively how the new energy-saving standard in Spain influences energy efficiency and indoor thermal comfort, by considering the characteristics of the dry Mediterranean climate (BShs) within a warm semi-arid climate (BSh). The scientific novelty of the study is to demonstrate that the new Spanish standard not only reduces energy costs but also makes the indoor comfort of buildings much worse; for this reason, an improvement in the standard is also proposed. The study methodology consists of a comparative study between the thermal performance, thermal comfort, and energy demand of the building, considering both the new and previous standards' requirements. It also includes the evaluation of a proposal to improve the current standard. The results showed that the new energy-saving standard reduced energy consumption by 21.78% in comparison to former standards, but the new comfort ranges were not acceptable for 60% of the users. The proposed improvement does achieve acceptable comfort for most users (75%) and an additional reduction in energy demand of 48.76% compared to current standard. We conclude that the thermal comfort requirements of the current energy standard should be modified to better adapt the design criteria to the dry Mediterranean climate. [ABSTRACT FROM AUTHOR]

Improving the energy performance of existing buildings is one of the main strategies defined by the European Union to reduce global energy costs. Amongst the actions to be carried out in buildings to achieve this objective is working with passive measures adapted to each type of climate. To assist designers in the process of finding appropriate solutions for each building and location, different tools have been developed and since the implementation of building information modeling (BIM), it has been possible to perform an analysis of a building's life cycle from an energy perspective and other types of analysis such as a comfort analysis. In the case of Spain, the first BIM environment tool has been implemented that deals with the global analysis of a building's behavior and serves as an alternative to previous methods characterized by their lack of both flexibility and information offered to designers. This paper evaluates and compares the official Spanish energy performance evaluation tool (Cypetherm) released in 2018 using a case study involving the installation of sunlight control devices as part of a building refurbishment. It is intended to determine how databases and simplifications affect the designer's decision-making. Additionally, the yielded energy results are complemented by a comfort analysis to explore the impact of these improvements from a users' wellbeing viewpoint. At the end of the process the yielded results still confirm that the simulation remains far from reality and that simulation tools can indeed influence the decision-making process. [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]

This paper examines the actual knowledge regarding Building Performance Simulation Tools (BPSTs) of recent graduate architects in Spain. BPSTs quantify aspects of building performance that are relevant to design, construction, and operation. Recent graduate architects are those who have been awarded a first degree from a university or college and face their first professional experience. This article aims to identify the deficiencies within the current curricula of Spanish universities relating to BPSTs. The authors have surveyed 171 recent graduate architects, and the analysis of the data reveals the deficiencies in university education. Regarding the collected results, the Spanish university syllabi must undergo necessary modifications to encourage the use of simulation as a part of university training courses. The incorporation of energy simulation in such training courses can provide recent graduate architects with tools that would assist them during the design stage. The use of these tools is key in the development of innovative pedagogy-based teaching materials for the courses. In this sense, the present work aims to delve into the usage deficiencies associated with BPSTs and propose ways in which to bridge the gap between higher education and first professional experiences. [ABSTRACT FROM AUTHOR]

Accurate prediction of building indoor temperatures and thermal demand is of great help to control and optimize the energy performance of a building. However, building thermal inertia and lag lead to complex nonlinear systems is difficult to model. In this context, the application of artificial neural networks (ANNs) in buildings has grown considerably in recent years. The aim of this work is to study the thermal inertia of a building by developing an innovative methodology using multi-layered perceptron (MLP) and long short-term memory (LSTM) neural networks. This approach was applied to a public library building located in the north of Spain. A comparison between the prediction errors according to the number of time lags introduced in the models has been carried out. Moreover, the accuracy of the models was measured using the CV(RMSE) as advised by AHSRAE. The main novelty of this work lies in the analysis of the building inertia, through machine learning algorithms, observing the information provided by the input of time lags in the models. The results of the study prove that the best models are those that consider the thermal lag. Errors below 15% for thermal demand and below 2% for indoor temperatures were achieved with the proposed methodology. [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]