02 Fakultät Bau- und Umweltingenieurwissenschaften

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/3

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Institute: search.filters.UBSInstitut.Fakultätsübergreifend / Sonstige EinrichtungAuthor: search.filters.author.Sakiyama, Nayara R. M.

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    Building optimization through a parametric design platform : using sensitivity analysis to improve a radial based algorithm performance
    (2021) Sakiyama, Nayara R. M.; Carlo, Joyce C.; Mazzaferro, Leonardo; Garrecht, Harald
    Performance-based design using computational and parametric optimization is an effective strategy to solve the multiobjective problems typical of building design. In this sense, this study investigates the developing process of parametric modeling and optimization of a naturally ventilated house located in a region with well-defined seasons. Its purpose is to improve its thermal comfort during the cooling period by maximizing Natural Ventilation Effectiveness (NVE) and diminishing annual building energy demand, namely Total Cooling Loads (TCL) and Total Heating Loads (THL). Following a structured workflow, divided into (i) model setting, (ii) Sensitivity Analyses (SA), and (iii) Multiobjective Optimization (MOO), the process is straightforwardly implemented through a 3D parametric modeling platform. After building set up, the input variables number is firstly reduced with SA, and the last step runs with an innovative model-based optimization algorithm (RBFOpt), particularly appropriate for time-intensive performance simulations. The impact of design variables on the three-performance metrics is comprehensively discussed, with a direct relationship between NVE and TCL. MOO results indicate a great potential for natural ventilation and heating energy savings for the residential building set as a reference, showing an improvement between 14-87% and 26-34% for NVE and THL, respectively. The approach meets the current environmental demands related to reducing energy consumption and CO2 emissions, which include passive design implementations, such as natural or hybrid ventilation. Moreover, the design solutions and building orientation, window-to-wall ratio, and envelope properties could be used as guidance in similar typologies and climates. Finally, the adopted framework configures a practical and replicable approach for studies aiming to develop high-performance buildings through MOO.
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    Using CFD to evaluate natural ventilation through a 3D parametric modeling approach
    (2021) Sakiyama, Nayara R. M.; Frick, Jürgen; Bejat, Timea; Garrecht, Harald
    Predicting building air change rates is a challenge for designers seeking to deal with natural ventilation, a more and more popular passive strategy. Among the methods available for this task, computational fluid dynamics (CFD) appears the most compelling, in ascending use. However, CFD simulations require a range of settings and skills that inhibit its wide application. With the primary goal of providing a pragmatic CFD application to promote wind-driven ventilation assessments at the design phase, this paper presents a study that investigates natural ventilation integrating 3D parametric modeling and CFD. From pre- to post-processing, the workflow addresses all simulation steps: geometry and weather definition, including incident wind directions, a model set up, control, results’ edition, and visualization. Both indoor air velocities and air change rates (ACH) were calculated within the procedure, which used a test house and air measurements as a reference. The study explores alternatives in the 3D design platform’s frame to display and compute ACH and parametrically generate surfaces where air velocities are computed. The paper also discusses the effectiveness of the reference building’s natural ventilation by analyzing the CFD outputs. The proposed approach assists the practical use of CFD by designers, providing detailed information about the numerical model, as well as enabling the means to generate the cases, visualize, and post-process the results.