Application of Novel Fibre Optic Sensors to Monitor Geostructures

作为我们基础设施支撑结构的地面可能是一种重大的地质灾害，其复杂的行为(仍相对较少了解)往往与各种环境条件下的含水率、温度和孔隙水压力的变化有关，可能会通过损坏建筑物、交通网络故障或重大公用事业损失(如漏水或停电)而对城市有形基础设施造成巨大风险。土壤水分、温度、孔隙水压力和土壤应变的变化可能是全球气候变化(极端干湿天气周期)、季节变化或局部场地变化(如公用设施管道的泄漏)造成的。偶尔发生的毁灭性故障直接源于支撑地面的坍塌以及相关基础设施的坍塌；这一问题不仅关系到土木工程师，而且关系到服务用户、更广泛的社会和国家基础设施的所有者。这一问题给世界各国带来了巨大的财政、环境和社会代价。仅在英国，在过去的15年里，这个问题就给经济造成了超过30亿GB的损失，成为最具破坏性的地质灾害。土壤吸力和土壤含水率对土壤的力学性质起着关键作用，如强度的发展和位于自然地下水位以上的土壤体积的变化。该项目是一项多学科研究，将使用最先进的聚合物光纤(POF)传感器精确测量物理参数和先进的地面数值模拟结合在一起，以加强我们对地面条件及其与地面和地下城市基础设施的共生关系的了解。在这项研究的第一阶段，博士将专注于包装、校准和研究新型POF传感器的应用，这些传感器可以准确地测量土壤水分含量、吸力、温度和地面应变。这种新型传感器可以超越目前市场上领先的传感器，因为它们更具成本效益，并提供更高的精度。在第二阶段，目的是建立准确的地面数值模型，特别注意用POF测量的上述物理参数(即含水率、温度、应变和吸力)的作用，并考虑到其部分饱和的性质以及其他主要物理、机械和环境条件的作用。数值模型(将根据现有的实验室实验和/或现场数据进行验证)将被扩展，以探索各种情况，并捕捉岩土工程问题(如斜坡滑动、路堤稳定性和地面塌陷)的影响参数之间的相互关系。数值模型将在土木工程的几个关键领域有广泛的应用，可以作为分析岩土结构的工具，并准确地预测系统的实际情况。数值模型可以用作评估工具，以消除导致地面和基础设施致命故障的条件。

The ground as supporting structure to our infrastructure can be a major geohazards and its complex behaviour (still relatively poorly understood), often associated with changes in water contents, temperature and porewater pressure under the various environmental condition, can result in huge risk to urban physical infrastructure, through damage to building, failure of transportation networks or significant loss of utility such as water leakage or power outings. The change in soil water content, temperature, porewater pressure and consequently the soil strain can be due to global climate change (extreme wet and dry weather cycles), seasonal variations, or local site changes such as leakage from utility pipes. Occasional devastating failures result directly from collapse of the supporting ground and consequently the associated infrastructures; a matter that not only concerns civil engineers but also the service users, wider society and owners of the nation's infrastructure. The problem imposes significant financial, environmental and social costs to nations across the world. In the Britain alone in the past 15 years this problem has imposed over £3 billion costs to the economy becoming the most damaging geo-hazard. Soil suction and soil water content play a key role in mechanical properties of the soils such as development of strength and changes in volumes of soil that lie above the natural water table. This project is a multidisciplinary research that brings together the precise measuring of physical parameters using state-of-the-art polymer optic fibre (POF) sensors and advanced numerical modelling of the ground in order to enhance our understanding of the ground condition and its symbiotic relationship with both surface and buried urban infrastructure. In the first stage of this research the PhD will focus on packaging, calibration and investigating the application of novel POF sensors that can accurately measure soil moisture contents, suction pressure, temperature and strain in the ground. The novel sensors can outperform current leading sensors in the market as they are more cost effective and provide higher accuracy. In the second stage, the aim is to develop accurate numerical models of the ground with a specific attention to the role of the above physical parameters measured with POFs (i.e. moisture contents, temperature, strain and suction) and taking cognisance of its partly-saturated nature as well as the role of other major physical, mechanical and environmental conditions. The numerical models (to be validated against available laboratory experiments and/or field data) will be extended to explore various scenarios and capture inter-relationship between contributing parameters of geotechnical engineering problems such as slope sliding, embankment stability and ground collapse. The numerical models will have extensive applications in several key areas of civil engineering and can serve as a tool to analyse geo-structures, and accurately predict the actual condition of the system. The numerical models can be used as an assessment tool to eliminate conditions that lead to fatal failures of both ground and infrastructure.