Wind-driven rain on the facade of a monumental tower: Numerical simulation, full-scale validation and sensitivity analysis

Abstract

Wind-driven rain (WDR) is one of the most important moisture sources that affect the hygrothermal performance and the durability of building facades. The facades of the Dutch monumental building St. Hubertus show severe deterioration caused by WDR. Assessment of the amount and intensity of WDR falling onto the facades is necessary as input for numerical heat-air-moisture (HAM) transfer models to analyse the causes of the moisture problems and the impact of remedial measures. In this study, a numerical simulation method based on Computational Fluid Dynamics (CFD) is used to predict the amount of WDR impinging on the south-west facade of the tower of the building. The paper focuses on the numerical simulation results, the validation of these results and their sensitivity to two parameters: the level of geometrical detailing of the computational building model and the upstream terrain aerodynamic roughness length. Validation is performed by comparison of the numerical results with a dataset obtained from on-site WDR measurements. It is shown that the CFD simulations provide fairly good predictions of the amount of WDR impinging on the south-west facade of the tower, except for the lower part. It is also shown that the local effects of geometrical facade details are significant and can yield differences in WDR exposure up to 40%, while their effect at other positions is negligible. Finally, the sensitivity of WDR simulations to the upstream aerodynamic roughness length is discussed.

Introduction

Building Physics aims at providing a healthy, comfortable and sustainable indoor and outdoor environment of buildings. Sustainability also involves the durability of the building envelope that separates the indoor and the outdoor environment. Wind-driven rain (WDR) is one of the most important moisture sources that affect the hygrothermal performance and the durability of building facades [1], [2], [3], [4], [5]. Numerical analysis of the hygrothermal behaviour with so-called HAM (heat-air-moisture) models requires accurate WDR data as boundary condition [1], [2], [3], [4], [5], [6], [7], [8].

Three categories of methods exist for determining the WDR intensity that impinges on building facades: (1) measurements, (2) semi-empirical methods and (3) numerical methods based on Computational Fluid Dynamics (CFD). A literature review of each of these categories has been provided by Blocken and Carmeliet [5]. Measurements have always been the primary tool in WDR research, but are nowadays only rarely conducted. The most important reason is the fact that WDR measurements can easily suffer from large errors [3], [9], [10], [11]. Recently, guidelines have been proposed that should be followed for selecting accurate and reliable WDR data from experimental WDR datasets [10], [11]. The strict character of these guidelines, however, implies that only very few rain events in a WDR dataset are accurate and reliable and hence suitable for WDR studies. Other drawbacks of WDR measurements are the fact that they are time-consuming and the fact that measurements conducted at a particular building site have very limited application to other sites. Semi-empirical methods are an alternative to measurements. The main advantage of semi-empirical methods is their ease-of-use; their main disadvantage is that generally only rough estimates of the WDR exposure can be obtained [5]. Given the limitations of measurements and semi-empirical methods, in the past decades, numerical simulation with CFD has been explored. Choi [12], [13], [14] developed and applied a steady-state numerical simulation technique based on CFD. It allows determining the spatial distribution of WDR on building facades for given (fixed) values of the wind speed, the wind direction and the horizontal rainfall intensity. Later, Choi's simulation technique was extended into the time domain by Blocken and Carmeliet [15], [16]. In all of these studies, CFD simulations were based on the Reynolds-Averaged-Navier–Stokes (RANS) equations.

Validation is an essential part of RANS CFD simulations. Up to now, only a few attempts have been made for CFD validation with full-scale WDR measurements [3], [5], [15], [17], [18], [19]. van Mook [3] was the first to compare simulations with full-scale measurements at a few selected positions at the west facade of a wide, high-rise building. Blocken and Carmeliet [15], [18] performed CFD WDR validation for a low-rise building with a sloped and a flat roof module, based on measurements with 24 WDR gauges installed at the south-west and north-west facades. Tang and Davidson [17] validated numerical simulations for the rather complex Cathedral of Learning with WDR measurements at 16 different positions. Most recently, Abuku et al. [19] employed the WDR measurement data by Nore et al. [20] for the validation of WDR simulations on the west facade of a low-rise rectangular test building with various angles of wind incidence. While some authors found significant discrepancies between simulations and measurements [3], others indicated a fair to good agreement [15], [17], [18], [19].

While these efforts have provided valuable information, the need for additional WDR measurement data and CFD validation studies is still present, in particular for different types of buildings in different environment topographies [11], [18]. This need is driven by the complex nature of WDR and the wide range of influencing parameters. Additionally, sensitivity studies are needed concerning the large amount of computational parameters that have to be set by the user in such CFD simulations. Two important questions are: (1) to what extent do geometrical facade details have to be included in the computational model of the building; and (2) how sensitive are the results to the estimate of the aerodynamic roughness length of the upstream terrain. The inclusion of facade details can present a challenge in CFD WDR studies, due to the large difference in length scales between the computational domain (up to several 100 m or km) and the facade details (down to a few cm) and the subsequent need for very fine grids near the building surface. The aerodynamic roughness length determines the shape of the inlet profiles of mean wind speed, turbulent kinetic energy and turbulence dissipation rate, as well as the physical roughness height k_S that has to be applied at the bottom of the computational domain [21]. It is generally estimated from the updated Davenport roughness classification by Wieringa [22], based on a fetch (upstream distance) of at least 5 km (Table 1). However, estimating a representative aerodynamic roughness length for heterogeneous terrain is difficult, and it is therefore rather easy to be one class off in this roughness classification.

In this paper, CFD simulations of WDR on the south-west facade of the tower of Hunting Lodge St. Hubertus (Fig. 1a) are performed. It is a monumental building situated in the National Park “De Hoge Veluwe”. Especially the south-west facade of the building shows severe deterioration caused by WDR and subsequent phenomena such as rain penetration, mould growth, frost damage, salt crystallisation and efflorescence, and cracking due to hygrothermal gradients (Fig. 1b–e). The CFD WDR simulations are important to obtain accurate spatial and temporal distribution records of WDR, to be used as input for numerical HAM transfer simulations. These simulations will be used in a later stage to analyse the causes of the moisture problems and to assess the impact of remedial measures. Validation of the CFD simulations is performed by WDR measurements at a few selected locations at the south-west facade. In addition, the influence of neglecting all protruding and recessed facade details and of shifting the estimated upstream aerodynamic roughness length one class higher or lower, is investigated. This can provide some guidance for future CFD WDR simulations.

In Section 2 of the paper, the definitions of the specific catch ratio, the catch ratio and the influencing parameters are given. The building geometry and the surrounding topography are described in Section 3. In Section 4, the measurement set-up for wind, rain and WDR is described. The extended WDR simulation model, the simulation characteristics and settings and the selected rain events are described in Section 5. The simulation results are compared with the measurements in Section 6. This section also contains the results of the sensitivity study. The paper ends with a discussion (Section 7) and the conclusions (Section 8).