Введение
В области проектирования конструкций точное прогнозирование воздействия ветра на конструкции имеет решающее значение для обеспечения безопасности и производительности. To enhance the reliability of CFD simulations, validating data from experimental or field measurements (Figure 1) is essential. This FAQ outlines the process of using validating data in RWIND to achieve reliable results.
Importance of Validation Example
Validation is a key step in any simulation process. It ensures that the model accurately represents real-world conditions. By comparing simulation results with experimental data, engineers can identify discrepancies and refine their models, leading to more accurate predictions.
Step-by-Step Process for Using Validating Data in RWIND
1. Prepare Experimental Data
- Collect Wind Tunnel or Field Data
Obtain wind pressure distributions from wind tunnel tests or field measurements. In this example, we used wind pressure data from experimental data on probe points.
Convert the data into including coordination of point probes and experimental wind pressure with a format compatible with RWIND, you can also easily transfer data by using copy-paste option (Figure 2).
2. Set Up RWIND Simulation
- Create a New Project: Open RWIND and start a new project.
- Import the geometry of the validation example.
- Define Simulation Parameters: Set up the domain size, boundary conditions, mesh density, wind profile and turbulence intensity.
3. Results and Interpolation Methods
Two interpolation methods are available in RWIND: diffusion interpolation and Gaussian interpolation kernel (Figure 3). Only one method must be selected for all probes (see
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).
The diffusion method distributes the data from the "source" point over the surface. It is suitable for dense mesh of measuring points. In the case of thin open structures, this method interpolates values only on one side of the plate. It is possible to transfer experimental wind load by using motioned technique in order to structural analysis and design.
Here is the results for diffusion Interpolation (Figure 4):
Also calculation of statistical parameters and related diagram are provided manually to show how much the results of RWIND and experimental are close to each other. The Simplified Mesh RWIND simulation data shows a slightly better correlation with the experimental wind pressure data than the Exact Mesh RWIND data (Figure 5). However, both meshes exhibit strong agreement with the experimental data, making RWIND a reliable tool for predicting wind pressures. The high statistical values (R and R2) demonstrate that both simulation approaches can effectively replicate experimental wind pressure results, with the Simplified Mesh performing slightly better (Figure 6).
Заключение
Integrating validating data into RWIND is a crucial step in achieving accurate and reliable wind flow predictions. By following a systematic approach to prepare, import, and compare experimental data with simulation results, engineers can refine their models and ensure that their designs are both efficient and safe. This process not only enhances the credibility of RWIND simulations but also contributes to the overall advancement of structural engineering practices.
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