Feri Ludia Eka, Ahn Jaehun, Lutfillohonov Shahrullohon, Kwon Joonho
Department of Big Data, Pusan National University, Busan 46241, Korea.
Department of Civil and Environmental Engineering, Pusan National University, Busan 46241, Korea.
Sensors (Basel). 2021 May 21;21(11):3603. doi: 10.3390/s21113603.
Owing to the increasing use of permeable pavement, there is a growing need for studies that can improve its design and durability. One of the most important factors that can reduce the functionality of permeable pavement is the clogging issue. Field experiments for investigating the clogging potential are relatively expensive owing to the high-cost testing equipment and materials. Moreover, a lot of time is required for conducting real physical experiments to obtain physical properties for permeable pavement. In this paper, to overcome these limitations, we propose a three-dimensional microstructure reconstruction framework based on 3D-IDWGAN with an enhanced gradient penalty, which is an image-based computational system for clogging analysis in permeable pavement. Our proposed system first takes a two-dimensional image as an input and extracts latent features from the 2D image. Then, it generates a 3D microstructure image through the generative adversarial network part of our model with the enhanced gradient penalty. For checking the effectiveness of our system, we utilize the reconstructed 3D image combined with the numerical method for pavement microstructure analysis. Our results show improvements in the three-dimensional image generation of the microstructure, compared with other generative adversarial network methods, and the values of physical properties extracted from our model are similar to those obtained via real pavement samples.
由于透水路面的使用日益增加，对能够改进其设计和耐久性的研究需求也在不断增长。导致透水路面功能降低的最重要因素之一是堵塞问题。由于测试设备和材料成本高昂，用于研究堵塞可能性的现场试验相对昂贵。此外，进行实际物理实验以获取透水路面的物理特性需要大量时间。在本文中，为了克服这些限制，我们提出了一种基于带有增强梯度惩罚的3D-IDWGAN的三维微观结构重建框架，这是一种用于透水路面堵塞分析的基于图像的计算系统。我们提出的系统首先将二维图像作为输入，并从二维图像中提取潜在特征。然后，它通过我们模型的生成对抗网络部分结合增强梯度惩罚生成三维微观结构图像。为了检验我们系统的有效性，我们将重建的三维图像与用于路面微观结构分析的数值方法相结合。我们的结果表明，与其他生成对抗网络方法相比，微观结构的三维图像生成有了改进，并且从我们模型中提取的物理特性值与通过实际路面样本获得的值相似。
