地球物理方法在土木工程研究中的应用综述

A.A. Akinlalu , M.M. Futai , D.O. Afolabi , R.M. Abraham-A
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引用次数: 0

摘要

本文通过查阅同行评议期刊上发表的75多篇论文,综述了地球物理方法在土木工程项目中地下表征的应用。本文重点介绍了工程场地表征中考虑的各种地质条件,以及相应的地球物理方法,如电阻率层析成像、地震折射层析成像、自电位、感应极化、电磁、多通道表面波分析和地下表征中使用的磁性方法。从26份出版物中提取的案例研究展示了地球物理方法在土木工程项目地下表征中的成功应用。本文还强调了地球物理数据在土木工程项目中的挑战,包括数据解释的模糊性、数据处理的复杂性以及在文化嘈杂环境中的高噪声与信号比。本文还提出了地球物理方法在土木工程表征中的局限性和挑战,其中最主要的是近年来受到关注的地球物理方法的综合应用。进一步的解决方案是在地球物理设备的设计中加入适当的带通滤波器,以提高文化噪声环境中的信噪比。未来在土木工程项目中使用地球物理方法进行地下表征的研究应涉及综合地球物理方法的联合反演和建模,以获得最佳的地下成像结果。未来的研究还应结合机器学习和深度学习技术,以增强自动化解释,促进异常检测,并在民用基础设施应用中实现实时地球物理监测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A review on the application of geophysical methods in civil engineering studies

A review on the application of geophysical methods in civil engineering studies
This paper reviewed the application of geophysical methods in civil engineering projects by way of subsurface characterization by examining more than 75 publications in peer–reviewed journals. The paper highlighted various geological conditions considered in engineering site characterization and the appropriate geophysical methods such as electrical resistivity tomography, seismic refraction tomography, self-potential, induced polarization, electromagnetic, multichannel analysis of surface waves and magnetic methods used in subsurface characterization. Case studies drawn from 26 publications were presented to show the successful application of geophysical methods in subsurface characterization in relation to civil engineering projects. The paper also highlighted the challenges of geophysical data in civil engineering projects involving ambiguities in data interpretation, complexity in data processing and high noise to signal ratio in culturally noisy environments. Resolutions in the limitations and challenges of geophysical methods in civil engineering characterization were also offered in the paper, chief among them is integrated use of geophysical methods which has gained traction in recent years. Further solutions are incorporating appropriate band pass filters in the design of geophysical equipment’s to enhance signal to noise ratio in culturally noisy environments. Future researches in the use of geophysical methods in subsurface characterization in relation to civil engineering projects should involve joint inversion and modelling of integrated geophysical methods to achieve optimum results for subsurface imaging. Future researches should also incorporate the integration of machine learning and deep learning techniques, which enhance automated interpretation, facilitate anomaly detection, and enable real-time geophysical monitoring in civil infrastructure applications.
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