Parametric Massing Optimization Tools

The separation between architect and engineer is a relatively recent event, in comparison to the long history of human constructions. In modern times the separation of the two professions and the involvement of engineers in later design stages has proved problematic, because of the large effort needed to make changes in later design stages. On the other hand, the rising importance of engineering and financial objectives that building projects have to meet, calls for a more integrated design approach since the very early design stages. Contemporary parametric tools give the possibility to enhance multidisciplinary communication by providing the ability to quickly extract needed values from preliminary design geometries (or “massings”) and assess them through properly defined evaluation scripts. This thesis investigated this prospect, focusing on the aspect of energy demand, which emerges as a central design consideration in contemporary architecture. The thesis report identified the main objectives that would serve as fitness values for it’s assessment optimization systems, including in them the main parameters of influence for each of these objectives. These objectives have been the minimization of solar gains, annual heating and cooling demand, annual total energy demand per GFA, annual total energy demand per NFA, and embodied + operational (for 1, 10, 50 years) CO2 emissions. The choice of the optimization objective and thus the optimization system that has to be set to assess it, was proved to have great influence on the optimization process and results. Because of that, this thesis concluded that it this is a point that has to be considered carefully, according to the design’s priorities, to find out which specific objective is set as fitness value, for each design project. That is because an extension of the optimization in unneeded areas, might diminish the accuracy of the results and increase the computational demand needed. To support these assessment and optimization systems, a parametric toolbox has been developed, named MEOtoolbox (MEO derived from the initials of the words Massing Energy Optimization). The components developed mainly aimed to facilitate the calculation of the annual demand for heating and cooling, using the quasi-steady state method for energy demand calculations described in the ISO13790 international standard. The MEOtoolbox will be made available to download after the end of this thesis project, through MEOtoolbox.blogspot.com. Possible design scenarios where the MEOtoolbox could be particularly useful, have been outlined through design dilemmas that also formed the case studies of this thesis. To validate the results of these case studies, results, relevant to the case studies, have been beforehand compared to results of similar studies and software. The design case studies have investigated the effect of tilting the facades of a recreation centre in Paris (France), and the effect of orientation and the effect of self shading in a design of a highrise building for the European Union in Brussels (Belgium). The study showed that: Tilting downwards a south facing facade, in Paris, can reduce the solar load in half during summer, while not greatly reducing solar load in winter. For the climate of Brussels, the maximum effect that orientation could have, for the particular design geometry, was an increase of 5% in the annual cooling demand and 1% in the annual heating demand. The effect of shifting in order to self-shade building geometries proved that it is an effective way of reducing cooling demand, without increasing greatly the heating demand. The two case studies also exemplified some of the additional benefits and shortcomings of the parametric tools. In the advantages, it has been shown how design choices can be visually supported, forming arguments for a specific design decision. On the shortcomings, the unavailability of tools to assess the multiplicity of parameters that a designer might consider and the sensitivity of the results in certain parameters, (which could, if not set properly, lead to invalid feedback) are issues that have to be addressed by parametric design software developers, for example through detailed manuals. For the comparative research, six basic building typologies (“Warehouse”, “Cube”, “Tower”, “Caterpillar”, “Fence”, “Slab”) were compared with regards to their operational energy per area in different climates and with different glass percentages in the facades. The thesis concluded that: For all the typologies studied, with the absence of external shading and for the glass percentages studied, cooling demand seems to be more critical for the determination of optimal energy massing, due to it’s greater fluxuation depending on the typology. As far as the absolute energy demand values are concerned, location seems to be the most largely influencing parameter, followed by glass percentage. Orientation and programmatic function seem to have much less influence on the absolute value of the energy demand of the typologies. As far as the ratio between the typologies is concerned, the switch of the assessment value from Energy per GFA to Energy per NFA, strongly influences the energy demand per area ratio between the typologies, as spaces with less rentable space often seem to be good energy solutions. Minimizing the expected Energy/NFA gives different results than Energy/GFA, taking into account also space efficiency. Since NFA is usually a primary goal for construction and real-estate companies, it is a realistic aim to try to minimize energy costs to cover a specific programmatic NFA demand. Location also influences largely the ratio between typologies, which seems to be similar in locations with similar ratio between the needs in heating and cooling. The typology study showed that the energy per NFA can be reduced in the magnitude of 40% by selecting an optimal typology for the climate of the Netherlands For the climate of Amsterdam, and for the characteristics for facade and structure employed for the analysis, embodied energy seems to correspond, roughly, to 10 years of operational energy for all of the typologies. The fact that this was the result for all the typologies studied, suggests that it could potentially be used as a rule of thumb, when assessing the importance of embodied energy for a specific project, depending on it’s expected functional lifetime.