Natural ventilation and the use of fans are recognized as sustainable design strategies to reduce energy use while reaching thermal comfort. A big challenge for designers is to predict ventilation rates of buildings in dense urban areas. One significant factor for calculating the ventilation rate is the wind pressure coefficient (Cp). Cp values can be obtained at a high cost, via real measurements, wind tunnel experiments, or high computational effort via computational fluid dynamic (CFD) simulation. A fast surrogate model to predict Cp for a schematic urban environment is required for the integration in building performance simulations. There are well-known surrogate models for Cp. The average surface pressure coefficient model integrated in EnergyPlus considers only a box-shaped building, without surrounding buildings. CpCalc, a surrogate model for Cp, considers only one height of neighbouring buildings. The Toegepast Natuurwetenschappelijk Onderzoek (TNO) Cp Generator model was available via web interface, and could include several box-shaped buildings in the surrounding area. These models are complex for fast integration in a natural ventilation simulation. For optimization processes, with thousands of simulation runs, speed is even more essential. Our study proposes a new surrogate model for Cp estimation based on data obtained from the TNO CP Generator model. The new model considers the effect of different neighbouring buildings in a simplified urban configuration, with an orthogonal street pattern, box-shaped buildings, and repetitive dimensions. The developed surrogate model is fast, and can easily be integrated in a dynamic energy simulation tool like EnergyPlus for optimization of natural ventilation in the urban areas.

High-rise buildings in areas with thick layers of sedimentation require deep pile foundations which lead to higher costs. The height, layout and location of high-rise buildings are crucial to reducing costs. The aim of this paper is to propose a cost estimation model for buildings, which includes pile foundation and land cost. The element method for cost control and structural theories are integrated in order to predict costs per m² of floor. Specific soil characteristics have been combined with wind and seismic loads. The result of this study is a cost estimation model that allows for the comparison of these different layouts (building height and depth). The effect of land cost and soil conditions (requiring appropriate pile foundation) on the price per m² of floor can be calculated. The model can support designers, developers and policymakers in making decisions in the early design stages.

In recent decades, as a result of continuously increasing urbanization and climate change, energy saving has become a critical issue. Due to the high dwelling density, most compact urban areas have limited possibilities for natural ventilation combined with reduced solar radiation. As a consequence, a balance has to be found between reduced comfort and increased energy cost for cooling or heating. The aim of this study is to minimise the energy consumption and optimize thermal comfort of terraced houses in different urban patterns, by using natural ventilation and considering solar radiation. This study analyses different parameters on the level of buildings and urban layouts. The building characteristics include building sizes, window design, materials and internal wind permeability. The urban layouts consist of different building heights, setbacks and road widths. Energy consumption and thermal comfort are calculated by a dynamic simulation using EnergyPlus. Then the generic optimisation tool GenOpt is used to search for the lowest cost to reach a predefined minimum thermal comfort. Both the temperate climate in Belgium and the tropical climate in Vietnam were analysed to check the efficiency and robustness of the models. Conclusions are drawn for sketch design in the given contexts.

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