Khatib 和 Alami 的马斯喀特数字孪生：加强安全和备灾
技术
- 分析与建模 - 计算机视觉软件
- 分析与建模 - 数字孪生/模拟
适用行业
- 建筑物
- 水泥
适用功能
- 质量保证
用例
- 数字孪生
- 虚拟原型与产品测试
服务
- 无人机运营服务
- 硬件设计与工程服务
关于客户
本案例研究中的客户是阿曼苏丹国，这是一个中东国家，对利用技术增强国家安全和备灾能力有着浓厚的兴趣。政府试图为该国大部分地区（特别是首都马斯喀特周边地区）创建详细的数字孪生。数字孪生旨在作为规划和管理潜在气候相关灾害以及改善国家安全的工具。政府与著名工程公司 Khatib & Alami 签订合同，在严格的时间表和高精度要求内执行这一雄心勃勃的项目。政府的愿景不仅是拥有该地区的数字孪生，而且还将其用作在该地区构建类似 3D 建模服务的模型。
挑战
阿曼苏丹国的目标是创建一个覆盖该国约 250 平方公里的详细数字孪生模型，重点关注马斯喀特及其周边地区。目标是加强国家安全并改善对气候相关灾害的准备。 Khatib & Alami 签订合同，使用无人机 (UAV) 捕捉 330,000 张图像，并构建该地区的 3D 现实模型，其中包括 43,000 座完全纹理的建筑物。该项目要求分辨率为10地面采样距离（GSD），相对精度小于20厘米。该项目严格要求在 125 天的期限内完成。然而，由于空域限制，包括机密区域和商业航班，只有 14 天的时间可用于飞行和图像捕获。恶劣的天气条件和无人机硬件的限制阻碍了对捕获的图像进行地理标记，这增加了挑战。
解决方案
Khatib 和 Alami 采用了谨慎管理的策略，团队并行工作，以在有限的飞行时间内检查捕获图像的准确性。他们寻求能够标记地面控制点以提供模型准确性的软件。在考察了各种应用程序后，他们选择了 Bentley 的实景建模应用程序 ContextCapture，该应用程序支持大面积的高效实景捕捉，并且可以快速生成多种格式的信息。 ContextCapture 的平铺支持通过查找正确图像的匹配来帮助克服捕获期间的数据错误，其重建算法有助于无缝集成不同的图像亮度级别和角度。该应用程序还支持同时在多个强大的硬件系统上运行并行处理，这有助于管理项目规模和进度。 Khatib 和 Alami 使用 ContextCapture 生成了一个现实模型，其中包括 43,000 座完全纹理的建筑物，然后将其输出到第三方应用程序中以发布并与利益相关者共享。 Bentley 的 LumenRT 用于通过模拟洪水和昼夜循环的视频来制作数字孪生动画。
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