five

Data and code for "Modified Parker's method for gravitational forward and inverse modeling using general polyhedral models"

收藏
DataCite Commons2025-06-01 更新2024-07-28 收录
下载链接:
https://figshare.com/articles/dataset/Data_and_code_for_Modified_Parker_s_method_for_gravity_forward_modeling_of_general_polyhedral_models_/13058840/4
下载链接
链接失效反馈
官方服务:
资源简介:
We propose a new modified Parker's method for efficient gravitational forward modeling and inversion using general polyhedral models. We have made several important modifications to the classical method, including: 1) The new method is now applicable to a general polyhedron represented by triangulated surface or tetrahedral mesh, and with arbitrarily variable 3D density distribution. 2) An optimal Fourier-domain sampling strategy is used to improve the numerical accuracy of the new algorithm significantly. 3) A simple and effective automatic layering technique is introduced to accelerate the convergence rate of Parker's method. The method is demonstrated using both synthetic and real polyhedral models, including a sphere model approximated by a polyhedron, two asteroids, a digital elevation model in the Himalaya region, and the Yucca Flat basin model in Nevada. The numerical results show that, compared with analytical solutions of polyhedral models in the space domain, the modified Parker's method can improve the computational efficiency by several orders of magnitude while obtaining almost the same simulation results. The difference is well below existing instrumentation error level. By embedding the new forward algorithm into an iterative process, it can be used for fast inversion of density interfaces. Our new method is suitable for the efficient modeling and inversion of gravitational potential, gravitational vector, and gravitational gradient tensor caused by polyhedral models with a large number of faces, representing geological abnormal bodies, asteroids, and single or multilayer density interface models with triangulated surfaces.
提供机构:
figshare
创建时间:
2021-09-24
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作