The use of isolated vaulted canopy roofs (VCR) for schools, emerging shelters, sports and recreational centers, among others, is quite popular worldwide. However, the design of such structures to resist wind effects is usually a problem due to the scarce technical information available in the literature. As an alternative resource, in the present research, wind effects on this type of structures immersed in the atmospheric boundary layer (ABL) are studied numerically by using the 3D Reynolds averaged Navier Stokes (RANS) approach considering different aspect ratios and wind directions. Since wind tunnel testing information for these structures is limited, experimental results of a Gabled Canopy Roof (GCR) as well as some experimental results for VCR are used as a validation source for the numerical models. Based on this validation, the simulation results of the mean wind loads of VCR appear to be reasonably good. The numerical results are used to study the mean net-pressure coefficients (C_PN) over the VCR models and to establish the theoretical bases for coding them. It was found that the C_PN are very sensitive to the VCR curvature and wind direction (90°, 75°, and 60°), and to a less extent to the plan and elevation geometric ratios. Further, it was also found that the use of GCR C_PN for the design of VCR, as is usually done in professional practice, could lead to important differences in the magnitude of pressure coefficients and pressure distribution regarding actual VCR C_PN and its distribution. A detailed analysis of the C_PN for VCRs is presented.

El periodo fundamental de vibración de los aerogeneradores de eje horizontal es un parámetro esencial en el diseño y desempeño de sus componentes principales, como el rotor, la góndola y los sistemas electromecánicos responsables de transformar la energía del viento en electricidad. Este parámetro se determina comúnmente mediante análisis dinámicos modales o a partir de expresiones cerradas aproximadas; sin embargo, cuando se requiere evaluar múltiples configuraciones, como en la etapa de prediseño o al realizar estudios paramétricos, el uso reiterado de estos métodos puede volverse poco práctico. En este trabajo se propone la aplicación de Redes Neuronales Artificiales (RNA) como una alternativa para estimar el periodo fundamental de aerogeneradores de eje horizontal. Se implementaron RNA multicapa, de entrenamiento hacia adelante y aprendizaje supervisado, empleando como base de datos modelos con rotores de 70 a 120 m de diámetro, torres de soporte con alturas entre 70 y 100 m y diámetros entre 3 y 6 m. Se observó que, al comparar las predicciones de las redes contra resultados obtenidos con ecuaciones cerradas y superficies de respuesta, las RNA se correlacionan mejor con los resultados de referencia dentro del intervalo paramétrico analizado. Estos resultados muestran que la Inteligencia Artificial, aplicada al campo de la Ingeniería Estructural, constituye una herramienta poderosa y confiable, capaz de complementar métodos tradicionales, abriendo posibilidades para el diseño y optimización de aerogeneradores modernos.

The wind pressure coefficient $C_P$ is a key aerodynamic parameter for describing wind-induced pressure fields on building envelopes and is widely used as an input in air flow network (AFN) models. Most CFD validation studies rely on wall-averaged $C_P$ or a limited number of center-line sensors, implicitly assuming these represent the entire surface, which can mask significant local discrepancies. In this work, Reynolds-averaged Navier–Stokes (RANS) simulations are validated against pointwise pressure-tap data from the Tokyo Polytechnic University (TPU) database for an isolated low-rise hexahedral building. Wind incidence angles of 0°, 15°, 30°, and 45° are analyzed using five turbulence closures: standard, realizable, and RNG k-$ϵ$, and standard and SST k-$\omega$. All simulations are performed in an icositetragon-shaped computational domain using OpenFOAM, allowing wind-direction changes without remeshing. While wall-averaged $C_P$ shows good agreement with experimental data for all models, local (tap-by-tap) comparisons reveal errors as high as 30–45% on leeward walls, exposing discrepancies that global metrics conceal. No single turbulence model performs best across all walls and incidence angles: RNG k-$ϵ$ and SST k-$\omega$ alternate as the top performer depending on wall orientation and wind direction, a pattern quantified here through a wall-by-angle model-selection map based on the normalized mean square error. The results and the underlying local $C_P$ dataset provides practical guidance for selecting a turbulence model according to the dominant wind direction and facade orientation of a given natural-ventilation case, as well as a reference dataset for future wind-driven ventilation studies.

With the aim to improve and promote Mexican Wind Engineering research, a low-speed closed return wind tunnel for atmospheric environment and structural wind-loading simulations was built at the National Autonomous University of Mexico (UNAM). The testing calibration procedure was developed based on many recommendations specified by several authors on the literature to assure compliance with full-scale measurements, laboratory results and international coding. The calibration procedure consists of four stages: the first stage is to represent adequately the atmospheric boundary layer; the second, to obtain adequate pressure coefficients for rigid models; the third, to perform tests to obtain the aerodynamic forces and some dynamic properties from structural models; and the fourth is to develop aeroelastic models. This paper focuses on the first two stages. Therefore, during the first stage, various tasks were developed to perform adequate representation on the lower-portion of the atmospheric boundary layer to characterize mean velocity profiles and turbulence fluctuations. On the second stage, the main task was to replicate external mean pressure coefficients of a typical cubic low-rise building as many other laboratories have done before. During the first stage it was possible to adequately replicate an urban atmospheric boundary layer artificially. During the second stage, some results reveal the need to update the current Mexican regulations for wind design, since some pressure coefficients considerably exceeds the threshold values. Finally, although other types of tests are in progress, it is considered that the new boundary layer wind tunnel of the UNAM can be used with confidence to test different type of structures and contribute to the development of Mexican Wind Engineering.