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.

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.

The data set compiled in this file refers to the Multizone EnergyPlus model, used in the investigations of the research article entitled "Natural ventilation potential from weather analyses and building simulation". The technical information regarding the model has been grouped into tables, which include: the general simulation settings, the properties of the building materials, the Airflow Network opening settings used in the annual investigation, in addition to the controls established in the Energy Management System (EMS) for hybrid ventilation system operation. The user behaviour, regarding the living and bedrooms occupancy schedule, is also presented in a graph. This data set is made available to the public to clarify details of the EnergyPlus model and how the hybrid operation was defined. In this way, other researchers can perform an extended analysis of the information.

Natural Ventilation Effectiveness (NVE) is a performance metric that quantifies when outdoor airflows can be used as a cooling strategy to achieve indoor thermal comfort. Based on standard ventilation threshold and building energy simulation (BES) models, the NVE relates available and required airflows to quantify the usefulness of natural ventilation (NV) through design and building evaluation. Since wind is a significant driving force for ventilation, wind pressure coefficients ($C_p$) represent a critical boundary condition when assessing building airflows. Therefore, this paper investigates the impact of different $C_p$ sources on wind-driven NVE results to see how sensitive the metric is to this variable. For that, an experimental house and a measurement period were used to develop and calibrate the initial BES model. Four $C_p$ sources are considered: an analytical model from the BES software (i), surface-averaged $C_p$ values for building windows that were calculated with Computational Fluid Dynamics (CFD) simulations using OpenFOAM through a cloud-based platform (ii_a,b,c), and two databases—AIVC (iii) and Tokyo Polytechnic University (TPU) (iv). The results show a variance among the $C_p$ sources, which directly impacts airflow predictions; however, its effect on the performance metric was relatively small. The variation in the NVE outcomes with different $C_p$’s was 3% at most, and the assessed building could be naturally ventilated around 75% of the investigated time on the first floor and 60% in the ground floor spaces.

A Pegada Ecológica (PE) é a medida da carga imposta por uma população sobre a natureza, e representa a área de sustentação dos níveis de consumo dos recursos e geração de dejetos. O objetivo do trabalho foi calcular e avaliar a PE do município de João Monlevade-MG. Para o cálculo foi utilizado o método convencional proposto por Wackernagel e Rees na década de 90, baseado na soma da pegada das variáveis, calculadas da média anual de itens de consumo de dados agregados dividindo o consumo total pelo tamanho da população, subtraídos da Biocapacidade. João Monlevade Biocapacidade e PE de 0,048 e 0,643 há/hab, respectivamente, e, portanto, o consumo local ultrapassa a capacidade suporte do ambiente natural, e torna-se necessário um planejamento ambiental adequado para o município. A maior pegada foi referente a emissão de CO2 pela queima de combustíveis fósseis, 0,47 há/hab., indicando a necessidade da implementação de medidas mitigadoras. Conclui-se que cálculo da PE do município, aponta caminhos mais sustentáveis para melhor qualidade de vida da população. No entanto, requer aperfeiçoameto do cálculo, definindo outros indicadores relevantes, e análise cuidadosa dos dados.