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Abstract To increase the thermal performance of massive masonry walls, exterior or interior insulation can be used. The latter insulation technique is the most risky, though forms for example in cases of historical buildings, buildings with a worth-preserving facade or buildings in the urban context the only solution to increase the thermal performance of the wall. The current article compares the hygric performance of massive masonry walls provided with different interior insulation systems. To do so, small test walls are placed all together in a single hot box–cold box. The total moisture increase in the walls is measured by weighing the test walls. In addition, to investigate the working principle of the insulation systems the moisture distribution across the wall assemblies is investigated using the X-ray projection method. In the analysis capillary active as well as more standard non-capillary active insulation systems are investigated. For the imposed quasi steady-state winter condition, the increase of stored moisture inside walls with a capillary active system is found to be higher than for walls with a traditional vapour tight system.

Abstract In the course of the European Project Energy Efficiency and Risk Management in public buildings (EnRiMa), a mathematical model has been needed, predicting the room air temperatures based on the physical properties of the thermal zone and weather forecasts. Existing models based on physical building properties and weather forecasts did not deliver acceptable results. Based on the hypothesis that the missing thermal mass in the existing models is the main reason for the unacceptable results, a model based on physical properties and weather forecast, including the storage mass of a building has been developed. Based on this developed model and real data from a test site, Campus Pinkafeld of the University of Applied Science Burgenland, Austria, the model has been verified and validated. With the new developed model it is possible to predict the occurring room air temperature for a whole day with a maximum deviation of approximately ±1 K, which increases the precision compared to other models.

This paper draws the attention to the importance of a correct modelling of the inlet temperature of naturally and mechanically ventilated multiple-skin facades. Measurements demonstrate that the assumption of an inlet temperature equal to the interior or exterior air temperature is usually not valid. A sensitivity study illustrates the significance of the inlet temperature as a boundary condition for numerical multiple-skin facade models. Finally, the inlet temperature model and multiple-skin facade model are used in a whole building energy simulation to indicate the importance of a correct inlet temperature on the energy performance.

Abstract Smart windows are used to reduce energy consumption and improve thermal and visual comfort mainly by controlling the solar flux entering into a building. This article presents a simulation study in which the impact of the applied control strategy on the overall energy consumption (heating, cooling and lighting) is investigated. A commercial building located in Montreal (Canada) with south-oriented integrated electrochromic windows is modeled. The hour-by-hour state of the smart windows required to minimize overall energy consumption while respecting constraints related to thermal and visual comfort is determined through an optimization strategy based on genetic algorithms (GA). Then, this quasi-optimal control is compared to other approaches that could be applied in real-time applications: (i) two types of rule-based controls (RBC), i.e. RBC1 and RBC2 and (ii) a model predictive control (MPC). The impacts of thermal mass and installed light power density are also analyzed. Results show that the four control strategies under study presented similar energy consumption with differences in total energy consumption ranging from 4% to 10%. While more complex controllers such as MPC could potentially lead to improved performances considering more design variables, complex models and extensive commissioning, this study illustrates that simpler control strategies such as RBC2 can also lead to satisfying results.

Abstract During the master planning of neighbourhoods, design decisions related to the urban layout and typology affect the building form and availability of solar radiation considerably. The influence of those decisions on the energy demand for heating is often neglected however because appropriate energy simulation tools are lacking. This paper proposes a simple and accurate design tool to assess the solar gains and heating energy demand in buildings during the master planning phase of neighbourhoods. Detailed information on building geometry, constituting building elements and solar obstructions, is extracted from a 3D neighbourhood model using a plugin implemented in the modelling software SketchUp. This information is used to assess the heating energy demand of the buildings in the neighbourhood based on the dynamic Equivalent Heating Degree Day (dEHDD) method. Furthermore, the associated financial and environmental impacts are calculated based on an integrated life cycle approach, combining Life Cycle Costing (LCC) and Environmental Life Cycle Assessment (E-LCA) respectively. The design tool proposed is implemented for the Belgian context and used to analyse a number of schematic residential neighbourhood models with diverse built densities. The analysis reveals substantial differences in heating energy demand, life cycle financial and environmental costs. Neighbourhoods with a high built density and compact building types have a lower heating energy demand with potential reductions of up to 40% compared to neighbourhoods with a low built density and detached building types.