A prototype online database-enabled design framework for wind analysis/design of low-rise buildings

Abstract

This study presents a development of an advanced cyberbased database-enabled design module for low-rise buildings (DEDM-LR) which provides estimation of the wind-induced responses for main wind force resisting frames by making direct use of pressure time histories measured at a large number of pressure taps over a suite of building models. These responses may be considered in lieu of code-specified load effects in which the overall accuracy may be influenced by the inherent simplifications in codes. In addition, this new automated approach is particularly attractive and advantageous as it allows a web-based online analysis/design via intuitive user-friendly interfaces for both the input and output in terms of familiar web-style forms that are nowadays very common in most of web-based services. Presently, the DEDM-LR hosts an aerodynamic database developed by the Tokyo Polytechnic University (TPU), Japan for a variety of building configurations like flat, gable, and hip roofs under suburban terrain flow condition with immediate application to other databases. The paper shows the efficacy and validity of the DEDM-LR by walking through its details and examples on selected gable-roofed buildings. The architecture of DEDM-LR platform offers the ability to pool resources by hosting other databases that may become available in the near future.

Graphical abstract

Keywords

wind loads / low-rise building / pressure measurement / aerodynamics / building design / structural response / building codes / information technology (IT)

1 Introduction

Most codes and standards offer provisions for the design of low-rise buildings subjected to winds, which include constant pressure coefficients around the building to estimate equivalent static wind loads. This is the case, for example of the current North American [1] and Canadian (NRC) standards, which are largely based on wind tunnel experiments conducted at the University of Western Ontario (UWO) in the late 1970s [2]. Recent comparison studies on peak structural responses of main wind force resisting frames (MWFRF) in low-rise buildings using recent wind tunnel data sets have pointed out significant underestimations through codes-specified procedures, due to mainly turbulence levels and other possible factors such as pressure tap density, resolution of wind angles, etc. (e.g., [3,4]).

The advances both in experimental and computational aspects in the past decades have opened a new avenue to the development of database-enabled design (DED) procedures that couples computational schemes with experimental data for low-rise buildings (e.g., [5–7]). With acknowledging the usefulness of such an approach, the NIST windPRESSURE [7] for gable-roofed buildings [3,6–9], was introduced in the latest ASCE 7-10 Commentary.

Although the advantages of such time domain based DED procedures driven by data sets of synchronously measured surface pressures for low-rise buildings such as WiLDE-LRS [5] and NIST windPRESSURE [7] are well known, however, such off-line DED procedures may be often difficult to use, requiring that the end-users are familiar with the treatment and management of the numerous wind tunnel data sets. In addition, they often necessitate the knowledge of comprehensive background theories for correct interpretation. A possible way to address this difficulty is through the introduction of information/internet technologies, which have been utilized for the cases of high-rise buildings such as the NALD v. 2.0 [10], the DEDM-HR [11], and the DEDM-HRP [12]. These advanced DED frameworks are likely to become ever more poignant due to the popularity of network-enabled devices such as desktop/laptop computers, smartphones, and tablets, therefore making world-wide-web based technologies/interfaces an important resource for facilitating active interaction of geographically dispersed researchers/engineers. However, at present, no such online on-the-fly analysis/design framework exists for Simultaneous pressure measurement (SPM) databases in low-rise buildings.

In response to this need, this paper presents an advanced analysis/design framework that takes advantage of recent developments in Information Technology (IT), termed as database-enabled design module for low-rise buildings (DEDM-LR). This prototype framework provides more reliable estimates of wind load effects as compared to what can be obtained by code-specified procedures. Indeed, the DEDM-LR provides calculation of wind-induced forces and moments in MWFRFs of low-rise buildings by making direct use of pressure time histories measured at a large number of pressure taps over building models in wind tunnel. The use of the DEDM-LR is particularly attractive because it allows a web-based online on-the-fly analysis/design via intuitive user-friendly interfaces for both the input and output, adopting familiar web-style forms and submission buttons that are nowadays very common in most web-based services. For this reason, this novel approach is particularly useful for those who may not be very familiar with the theoretical background necessary for dealing with complex sets of wind tunnel experimental data and their application to actual buildings to assess extreme loads. Presently, the prototype DEDM-LR hosts the TPU aerodynamic database developed at the Tokyo Polytechnic University (TPU), Japan [13,14] for a variety of building configurations like flat, gable and hip roofs. The main analysis/design engine inside the DEDM-LR searches for extreme load effects based on pressure data at multiple locations and wind directions given the influence coefficients for the load effects of interest. This paper shows the efficacy of the DEDM-LR by walking through its details and examples on selected gable-roofed buildings. The architecture of the DEDM-LR platform also offers the ability to pool resources by hosting other databases that may become available in the near future.

2 Database-enabled design module for low-rise buildings (DEDM-LR)

2.1 Theoretical background of the DEDM-LR

The theoretical background employed in the DEDM-LR is mainly based on procedures such as WiLDE-LRS and NIST windPRESSURE [5,7], which were designed to directly use synchronous pressure data sets measured for various wind directions on test models to evaluate wind-induced responses of MWFRFs in low-rise buildings, e.g., bending moments at the knee, using influence coefficients. The procedure is briefly described here for completeness, while detailed information can be found in Whalen et al. [5] and Main and Fritz [7].

In general, the MWFRFs in a rigid low-rise building are attached to cladding panels with the help of girts (horizontal structural members in the side walls) or purlins (horizontal structural members in the roof), which transfer the pressure acting on cladding panels to the MWFRFs. The pressure coefficients obtained through wind tunnel experiments using hundreds of pressure taps can be viewed as pressures acting on the cladding panels. Accordingly, a wind-induced response in a MWFRF (R_θ), e.g., the bending moment at the knee, associated with the pressure coefficients may be expressed as a matrix notation:

(1)R_{\theta }={\displaystyle \frac{\mathrm{1}}{\mathrm{2}}}\rho V_z^{\mathrm{2}}{N}^{T}A{C}_{p,\theta },

where q = wind direction (Fig. 1); r = air density; V_z = mean wind velocity at a reference height z; N = influence coefficient; superscript T = transpose of a matrix; A = tributary area matrix associated with C_p,q; C_p,q = time history of non-dimensional pressure coefficients obtained through wind tunnel experiments. The reference height z is in general either eave height (H) or mean roof height (h) as shown in Fig. 1 depending on the definition of non-dimensional pressure coefficients used in wind tunnel experiments, as further explained in the example section later. The influence coefficients, N, are defined as the value of each response quantity resulting from a unit load applied at each of attachment locations where girts or purlins are connected to MWFRFs, and can be obtained from a structural analysis software, e.g., SAP2000 (CSI 2014, SAP2000, Computers & Structures, Inc.). The unit load is applied normal to the corresponding frame element in the direction of the positive pressure as measured pressures in wind tunnel experiments represent values are perpendicular to the surface of the building model. Accordingly, caution should be exercised for roof regions of gable or hip buildings when applying a unit load for the calculation of influence coefficients. Each value in the tributary area matrix (A) indeed indicates a contribution of a pressure tap to an attachment location of a MWFRF.

2.2 Architecture of the DEDM-LR

A schematic diagram of the DEDM-LR framework is illustrated in Fig. 2. To implement this framework, various web-based tools/languages such as HTML/JavaScript, PHP (PHP 2014, Hypertext preprocessor. http://www.php.net), and database management system, MySQL (MySQL 2014), were utilized. This framework is basically operated in an Apache web server (Apache 2014, Apache HTTP server project, Apache Software Foundation, http://www.apache.org) with two main processes such as foreground and background processes. The foreground process includes user-friendly interfaces to enable interactive web-delivered system consisting of five interface tabs: 1) “Building Information” tab for user inputs regarding building properties such as building dimensions, frame locations, attachment locations of girts and purlins, and influence coefficients of wind-induced responses of interests (Fig. 3(a)); 2) “Data Sources” tab for displaying the closest data set in the database based on the user’s input and providing the choice of available wind directions (Fig. 3(b)); 3) “Pressure analysis” tab for displaying analysis results such as a time history of response corresponding to a wind direction, the observed peaks for all wind directions and a design load distribution of a MWFRF for a wind direction where the largest peak occurs. In addition, this tab offers pull-down menus for selecting various wind directions, frames and responses, and a link to download the output file (Fig. 4(a)). Note that the current version of the DEDM-LR relies on observed peaks; however, the peak estimates derived simply from the sample peak may not be as robust and reliable as those derived from theoretical approaches [15]. The introduction of a data-driven model in the DEDM-LR for providing extreme values for different percentile (e.g., [15–17]) is currently in progress; 4) “Hurricane Input” tab for considering a specific location of interest in hurricane-prone regions and mean recurrence interval (MRI) as shown in Fig. 4(b); 5) “Hurricane Analysis” tab for estimating maximum/minimum responses on various MRIs and wind directions (Fig. 4(b)). Note that the DEDM-LR employed data sets of simulated 1-min hurricane wind speeds near the coastline, which are publicly available at the NIST website (http://www.itl.nist.gov/div898/winds/hurricane.htm).

The DEDM-LR offers two user-friendly methods for the input of influence coefficients in the first tab (Building Information tab). The first method is to input the coefficients one-on-one as shown in Fig. 3(a). Note that the number of nodes (indexes) and element (face) numbers are automatically generated in the DEDM-LR based on the attachment location inputs. User can also assign the name of the responses and their units, e.g., moment at left knee, moment at ridge etc. The second method offers an attractive input style, Input Field. It was intended for inputting many influence coefficients simultaneously in the case where the number of nodes/responses becomes large. If the user presses the button “Show CSV Input Field,” then a text field is shown (marked in arrow in Fig. 3(a)), instead of the first input interface. Users can copy comma-delimited influence coefficients (e.g., from ASCII file obtained from a structural analysis software) and paste them to the field at once. Then, pressing “Parse” button will automatically lead to the same results shown in the first interface where all fields are automatically filled in. For user’s convenience, detailed information about each tab is provided by a help file, and an example of a low-rise building as well as its screen recording regarding the DEDM-LR operation for a tutorial purpose is provided on top of the first user interface, “Building information” tab.

The background process (Fig. 2) is a server-side operation involving database operations such as database query and computations implicitly performed inside the DEDM-LR, which are shown in “Data Sources” and “Pressure Analysis” tabs, respectively. The MATLAB [18] is chosen as the major numerical calculation tool of the e-analysis/design in terms of a pre-programmed MATLAB code inside the main server in which such analysis/design is carried out after all user’s inputs are made.

2.3 Aerodynamic database

Presently, the DEDM-LR hosts a simultaneous pressure measurement (SPM) database developed by the Tokyo Polytechnic University (TPU), Japan [13,14] for a variety of building configurations like flat, gable and hip roofs, which are listed in Table 1. SPMs were carried out in the TPU boundary layer wind tunnel which has 2.2m wide and 1.8m high rectangular cross-section. The geometric scale of the test models was set to 1/100 and the velocity scale was assumed at 1/3, which results in a time scale of 3/100 using the reduced frequency relationship between model-scale and full-scale. Suburban terrain corresponding to Category III in AIJ [19] was chosen as the tested wind field, which is close to exposure B in ASCE 7-10. An example of verification can be found in the document linked in the TPU website [14] in which mean wind pressure coefficients on the centerline of a gable-roof model were compared to similar test cases reported in the literatures showing good agreement in spite of the different test conditions and models. Note that Hagos et al. [20] have recently performed a comparison of TPU and NIST databases based on peak pressure coefficients on selected pressure taps and reported that the two databases were reasonably equivalent for practical engineering purposes, though they showed some degrees of differences, e.g., 15 % to 71 % differences in the coefficients. In the case of relatively small coefficients, larger discrepancies were observed.

3 Examples

The reliability of a DED framework depends on both on the accuracy of the analysis methodologies implemented in the framework as well as the accuracy of the driving aerodynamic database. In an attempt to check the validity of the DEDM-LR framework, two examples are demonstrated in this paper, presenting comparisons with wind-induced responses estimated through the ASCE 7-10 procedures and the NIST windPRESSURE.

3.1 Comparison with ASCE 7-10

Four examples of gable-roofed buildings with different roof angles (Case 1 to 4) were utilized to compare the DEDM-LR results with those by ASCE 7-10 procedures. The example building characteristics, with reference to Fig. 1, are: building width B = 16 m; building depth D = 16 m; building eave height H = 8 m; roof angle (b) = 4.8°, 14°, 30° and 45°; three MWFRFs (Frame 1, 3 and 5) located at 0, 8 and 16 m, supported by hinges. The comparison was made for peak bending moments at the right knee of the middle frame (Frame 3), considering that knee moments generally have the largest magnitude of wind-induced response at a MWFRF. The 3-s gust speed was assumed to be 62.59 m/s ( = 140 mph) for ASCE 7-10 procedures and it was converted to the mean wind speed for the DEDM-LR using Durst Curve in the ASCE 7, i.e., a conversion factor of 1.52 was used. Wind directionality factor (K_d = 0.85 in ASCE 7-10), importance factor (I), topographic factor (K_zt) and internal pressure coefficient were not considered in this study and influence coefficients for example buildings were obtained using SAP2000.

For the estimation of wind design loads of low-rise buildings, ASCE 7-10 provides two analytical procedures: the directional procedure for all building heights and the envelope procedure for low-rise buildings with mean building height (h) less than 18 m ( = 60 ft). The directional procedure offers pressure coefficients for two main wind directions (Fig. 27.4-1 in ASCE 7-10), i.e., parallel to ridge (q = 0°) and perpendicular to ridge (q = 90°), and two pressure coefficients for the windward roof slope subjected to either positive or negative values. While, the envelope procedure instead utilizes pseudo external pressure coefficients (GC_pf), representing pseudo loading conditions that envelop the desired structural actions (bending moment, shear, thrust) independently of the wind direction for two load cases such as Load Case A (q = 45° ~ 90°), Case B (q = 0° ~ 45°) and respective symmetric wind directions (Fig. 28.4-1 in ASCE 7-10). In terms of external pressure coefficients defined in ASCE 7-10 standard, i.e., C_p for the directional procedure and (GC_pf) for the envelope procedure, two-dimensional frame analyses were made through SAP2000 to obtain peak bending moment at right knee in the middle frame.

Table 2 shows the peak bending moments obtained through various ASCE 7 procedures and the DEDM-LR. The peak moments by the directional procedure were taken to be the largest among the values obtained through all the combination of four different scenarios corresponding to q = 0° & q = 90° and positive and negative pressures at the windward roof slope for each test case. Overall, the directional procedure resulted in higher responses than the envelope procedure, and Load Case A led to significantly higher moments than Case B. For a wind direction that led to the peak moment at right knee, all peak responses were observed in the range of q = 45° − 90°, i.e., q = 90° for the directional procedure, Load Case A for the envelope procedure, and the wind directions for the DEDM-LR indicated in Table 2. This emphasizes importance of the wind directional effects on gable-roofed low-rise buildings where pressure distributions are significantly affected by flow separation at leading edges and a secondary separation of the flow at ridges according to the wind direction (e.g., [8]). It was also observed that DEDM-LR showed much higher responses, about 30% – 90% as indicated in Table 2, than ASCE 7 for these example buildings, and the peak moments increased when the roof angle increased. Note that St. Pierre et al. [3] and Coffman et al. [4], based on the NIST aerodynamic database, have reported that responses obtained using ASCE 7 were non-conservative in many cases. Particularly, Coffman et al. [4] reported underestimates of the knee moments ranging from 15 to 90 % based on seven gable-roofed buildings and that such discrepancies became larger for higher roof angles. Mensah et al. [21] also reported that results predicted by ASCE 7 procedure were highly non-conservative compared to those obtained through a DED approach with the wind tunnel test results of a 1/3 light-framed wood building and experimental influence coefficients. These scatters were attributed to the test models/conditions conducted in the earlier experiments [3,4,22]. Although direct comparison of the DEDM-LR with other literature results was not possible due to different configuration of test models and conditions, overall DEDM-LR results showed the same trends observed in the literatures.

3.2 Comparison of the NIST windPRESSURE and the DEDM-LR

The NIST windPRESSURE [7] is a database-assisted design software for rigid, gable-roofed buildings, which is comprised of MATLAB codes for offline calculation in conjunction with the NIST aerodynamic database. The database contains time histories of pressure coefficients for various gable-roofed building models tested in the UWO [8] and it is open to the public in the web [9].

Due to the similarity of background theory employed both in the NIST windPRESSURE and the DEDM-LR, the comparison of the results between two DED frameworks provides a cross-checking of two databases (the TPU and the NIST aerodynamic databases). Nonetheless, the two databases do not have any model geometry in common which prevents direct comparison, thus models having the same dimensional ratio of breadth (B), depth (D) and eave height (H) as well as the same roof angle (b), as listed in Table 3, were considered instead. Test wind speed and turbulence intensity profiles between the two databases are also shown in Fig. 5. The dimensional ratio between the TPU and the NIST models was 1.52 for all example buildings. For Cases 5 to 7, the actual building dimensions were based on the NIST models, i.e., the TPU models were scaled up to the NIST ones, while for Cases 8 to 10, the NIST models were scaled down to the TPU ones. The buildings in this comparison were assumed to have five equally spaced frames, e.g., Frame 1 to 5 in Fig. 1, and peak bending moments at of the right knee of the first internal frame (Frame 2 in Fig. 1) were compared.

Before directly comparing the results obtained through the two DED frameworks, it was necessary to adjust the pressure coefficients for the same reference height because the TPU data sets were based on mean roof height (h), the same definition used in ASCE 7 standard [1], while the NIST data sets defined the reference height as eave height (H). To compensate this difference, the following relation was utilized (e.g., Ref. [23]):

(2)C_{p,h}=C_{p,\mathit{H}}{\left({\displaystyle \frac{V_H}{V_h}}\right)}^{\mathrm{2}},

where (V_H/V_h)² = a conversion factor. For wind-induced responses, this factor can be used to adjust either pressure coefficients or computed responses due to the relationship between structural responses and pressure coefficients in Eq. (1). In this study, the reference height was set to mean roof height (h), thus the NIST windPRESSURE results were adjusted.

Figure 6 shows the observed peak bending moments for all wind directions for both the NIST windPRESSURE and the DEDM-LR, for unit wind speed. Shade areas in the figures indicate±20 % bounds of NIST windPRESSURE results at each wind direction for a better representation. Some observations can be drawn in the figure. First, a comparison of the results of the NIST windPRESSURE or the DEDM-LR between scale-up and scale-down cases for the same roof angle, i.e., Case 5 vs. 8 (top two figures), Case 6 vs. 9 (middle two figures), and Case 7 vs. 10 (bottom two figures), they showed almost identical trends. It is not surprising because both the NIST windPRESSURE and the DEDM-LR have employed linear interpolation/extrapolation for building dimensions, i.e., locations of pressure taps are linearly adjusted to different building dimensions. Second, overall trends considering all wind directions between two DED frameworks agreed well, however, peak values at q = 105° for the Cases 5 and 8 in the DEDM-LR (top two figures) were significantly higher than those obtained through the NIST windPRESSURE. Third, it is noted that the Cases of b = 26.7° (bottom two figures) showed more discrepancies than the cases of lower roof angles.

A certain degree of scatter and some differences in the peak values obtained through the two DED frameworks are likely due to differences in the wind tunnel test conditions, especially concerning the inflow boundary layer conditions, such as: test wind speed and turbulence intensity profiles between the two databases (Fig. 5) which would affect the spatial distribution of the wind pressures along the building models; differences in total number of pressure taps (about 200 in the TPU and 700 in the NIST) and different characteristics of the instrumentations used during the tests. Similar observations were made by Fritz et al. [24] for a low-rise building when comparing test results performed in six different wind tunnels. They reported that the variability among data sets (COV= 10% − 40 %) was primarily the result of differences in the approach flows employed by the participating wind tunnel laboratories. Endo et al. [25] studied the issue of the influence of test conditions during wind tunnel experiments and showed that good agreement among roof pressures of low-rise building models could be obtained when wind exposure characteristics, such as the mean velocity, turbulence intensity profiles and along-wind spectra, were simulated in a consistent fashion. This would seem to indicate that some discernible differences seen in the response estimates of this study between two DED frameworks are mainly due to different inflow conditions occurring during the wind tunnel experiments. Considering this inherent uncertainty, the results obtained through the two frameworks were rather consistent except a few cases. More detailed analysis of data would be necessary to identify such discrepancies observed in this example.

4 Discussion on the scope of application of the prototype DEDM-LR

Despite the advantages of this prototype framework over code-specified procedures, caution should be exercised for a practical application. It is a common feature in all state-of-the-art DED frameworks that they require a database of wind tunnel data, which often present a limited range of generic building shapes and configurations. If a target low-rise building of interest is identical or close to the geometry of a test model in the TPU database, the DEDM-LR will probably produce better and more reliable results than the code-specified procedure because wind codes have generally been established based on a simplification as well as a generalization from a limited number of data sets to accommodate a wide range of application. However, in the absence of closer match, the DEDM-LR may provide results that are similar in fidelity as the code-specified procedures.

To overcome this issue, an option is to host multiple databases to fill the gap resulting from missing data among databases. The architecture of the DEDM-LR is tailored to host other available databases, e.g., the NIST database, to increase the range of application more than a single database would offer. Nonetheless, in view of infinite combination of different building configurations, there would always be some gaps as the cumulative configurations offered by multiple databases are still finite. For this reason, a more feasible way is to employ an appropriate interpolation/extrapolation scheme, expanding the usability of already well-established database(s). In this regard, several studies have been carried out over the years, e.g., simple linear interpolation based on geometric approach (e.g., [7]), aerodynamic aspects of interpolation using artificial neural network (e.g., [26,27]), and interpolation focusing on spectral and probabilistic descriptors of non-Gaussian correlated pressure coefficients [28]. Note that the DEDM-LR currently employed a linear interpolation scheme introduced by Main and Fritz [7] who reported that the interpolation of different eave heights with constant plan dimension was satisfactory, but it was quite inaccurate for different roof slopes. While others (e.g., [26–28]) have reported better interpolation schemes, they are still restricted to special cases. More effort in developing a universal interpolation/extrapolation scheme is needed to enhance the capability of the DED framework.

In addition, current DED frameworks such as the NIST windPRESSURE and the DEDM-LR proposed in this study require the influence coefficients of a building of interest by user, which are usually obtained through a structural analysis software. Please note that a real building consists of a complex configuration thus accurate modeling is required to obtain realistic influence coefficients. However, caution should be exercised that accurate estimation of influence coefficients may not always be possible by a straightforward numerical model. In such situations, the readers are referred to the following studies that have looked into the impact of the choice of influence coefficients on the results: Hagos et al. [20]; Mensah et al. [21]; Doudak et al. [29]; Datin et al. [30]; Zisis and Stathopoulos [31]; Roueche et al. [32].

5 Concluding remarks

This paper presents a prototype database-enabled design module for low-rise buildings, the DEDM-LR, which features a cyberbased online on-the-fly analysis/design framework with a suite of building models and roof types hosted as an e-module of the VORTEX-Winds, a virtual organization (https://vortex-winds.org/). The framework allows the assessment of wind-induced forces and moments on MWFRFs of low-rise buildings, for various wind directions based on database of pressure measured in the TPU wind tunnel. Examples of structural response estimations and comparisons with the results given by ASCE 7-10 and the NIST windPRESSURE demonstrated the capability of the DEDM-LR and the aerodynamic database developed at the TPU. With its convenience due to the web-enabled format, versatility given by the use of various data sets and expandability to host multiple databases, the DEDM-LR can serve as an effective and convenient alternative design procedure or as a supplementary one to be used in conjunction with the recommendations of codes/standards. This will offer a more consistent design procedure in lieu of simplified approaches used in codes and standards. It is anticipated that this prototype framework will further popularize the concept of DED and evolve with future refinements and additional features, such as the employment of robust and validated interpolation/extrapolation schemes etc. This will promise to further improve not only the convenience in use and but also expand the access to a larger database of measurements.

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