Gravity sensing for rail construction feasibility study

地下灾害识别是铁路建设中的关键问题。在施工过程中发现意想不到的特性可能会产生重大的成本和时间影响。同样，如果没有识别危险，可能会导致轨道在使用寿命期间下沉和变形。地下危险可能是人为的，如旧的采矿或隧道，也可能是天坑或喀斯特的自然形式，随着时间的推移可能形成。传统的现场测量技术，如探地雷达、电磁和地震等，广泛用于现场测量，但都有其局限性。重力感应长期以来一直被认为是一种可以为现场调查增加重要价值的测量方法。任何地下特征的密度变化都会引起重力的变化。但到目前为止，还缺乏一种商业上可行的传感系统。硅微重力公司花了七年的时间研究和开发MEMS相对重力仪。一个原型地面系统已于2021年在国家地下基础设施设施成功测试，商业原型将于2023年第一季度末投入使用。该项目是一项可行性研究，旨在确定重力测量在GCRE以及更广泛的铁路建设行业中的适用性。拟议的项目将首先与GCRE合作，确定现场潜在的地下危险，并商定一套方案。这将包括确定危险的类型、深度、大小和密度与周围材料的对比。然后，这些数据将用于对危险可能产生的重力异常进行正演模拟。然后将其与SMG重力仪的预测灵敏度进行评估，以确定在现实场景中可以识别哪些危险。利用正演模型，将开发一个重力站调查程序，以确定在大范围内进行危害检测的最佳测量站数据密度。这将证明SMG重力测量在GCRE和更广泛的铁路行业进行现场测量的商业可行性。

Identifying subsurface hazards is a critical issue for railway construction. Finding unexpected features during construction can have major cost and time impacts. Similarly, if not identified hazards can cause subsidence and deformation during the life of the track. Subsurface hazards may be man-made such as old minings or tunnels or natural in the form of sinkholes or karsts which can form over time.Traditional site survey technologies such as ground penetrating radar, electro-magnetics and seismic are used extensively for site surveying but all have limitations. Gravity sensing has long been identified as a measurement which would add significant value to site surveys. Any subsurface feature that has a change in density will create a change in gravity. But until now a commercially viable sensing system has been lacking.Silicon Microgravity has spent seven years of research and development on MEMS relative gravimeters. A prototype surface system has been successfully tested at the National Buried Infrastructure Facility in 2021 and the commercial prototype will be available at the end of Q1 2023\. This Project is a feasibility study to determine the applicability of gravity surveying to GCRE but also to the wider rail construction industry.The proposed project will start by working with GCRE to identify potential subsurface hazards at the site and agreeing a set of scenarios. This will involve defining the type of the hazard, the depth, size, and density versus the surrounding material. This data will then be used to forward model the gravity anomaly that the hazard would create. This will then be evaluated versus the projected sensitivity of the SMG gravimeter to determine which hazards can be identified in a real-world scenario. Using the forward modelling, a gravity station survey program will be developed to determine optimal survey station data density for hazard detection over large areas. This will demonstrate the commercial viability of SMG gravity surveys for site surveys at GCRE and more broadly in the rail industry.