Automated Back Analysis of Geotechnical Infrastructure Performance using Optimization

最近发展的强大的，高分辨率的全场测量技术（如数字成像）现在可以在实验测试或监测现场施工或现场变形（如土方工程）期间访问非常大量的数据。试点研究现在表明，有可能利用这些数据直接表征系统中土壤的特性，而不必在实验室中对土壤进行取样和测试。这为任何问题增加了重要的额外数据集，并为工程师提供了评估手头问题的宝贵额外能力。这种技术可以应用于实验室模型测试水平，也可以应用于现场的全尺寸测试。建议的博士项目侧重于前者。在实验室模型测试的背景下，现代数字图像相关技术允许从一组图像中确定高分辨率位移和应变场的大型数据集。目前，这些通常是使用具有透明壁的平面应变模型生成的。谢菲尔德的试点研究（Gueguin et al., 2015）表明，可以将优化技术与这些应变场和结构的力-位移响应结合起来，重建不排水（粘土）土的应力-应变响应，而不需要对被测系统进行特定的分析或数值模型，即这是一个问题不可知的过程。这样就不需要通过取样和测试对土壤的应力-应变响应进行单独的直接测量。这种过程引入了土壤的扰动和结果的不确定性，可能是一些实验数据与理论之间缺乏拟合的重要原因。（然而，抽样和测试仍然可以用来提供额外的上下文数据）。博士学位的目的是进一步发展和探索这种技术，在选定的物理模型研究中对其进行校准，并将其扩展到颗粒材料。这将通过使用最先进的1g和离心机物理建模设施，以及岩土技术研究小组的透明和光弹性土壤能力，设计和测试特定的物理模型来实现。分析/数值开发将利用CMD团队在土木工程应用优化方面的领先能力。这样的工作将加强谢菲尔德在物理建模和使用优化方面的地位。虽然该技术的现场应用并不是该博士学位的直接目标，但像Network Rail这样的行业机构已经对该技术表现出了兴趣，该技术可以将空中和地面数字成像、激光雷达和无线传感器数据结合起来，生成详细的数据集。研究项目的一个方面将是概要地探讨这些可能性，以便为拟议的工作提供更广泛的背景。

The recent development of powerful, high resolution full-field measurement techniques (e.g. digital imaging) now gives access to a very large quantity of data during an experimental test or when monitoring field construction or field deformations (e.g. earthworks). Pilot studies now indicate that it is possible to utilise this data to directly characterise the properties of the soil in the system without having to sample the soil and test it in the laboratory. This adds a significant additional dataset to any problem and gives the engineer valuable additional capability with which to assess the problem in hand. Such a technique may be applied at laboratory model test level or at full scale in the field. The proposed PhD project is focused on the former.In the context of laboratory model tests, modern digital image correlation techniques allow determination of large dataset of high resolution displacement and strain fields from a set of images. At present these are typically generated using plane strain models with transparent walls. Pilot studies at Sheffield (Gueguin et al., 2015) have shown that it is possible to utilise optimization techniques in combination with these strain fields and the force-displacement response of a structure to reconstruct the stress-strain response of an undrained (clay) soil without any need for a specific analytical or numerical model of the system being tested, i.e. this is a problem agnostic process.This obviates the need to undertake a separate direct measurement of the stress-strain response of the soil by sampling and testing. Such a process introduces disturbance of the soil and uncertainty in results and may be a significant cause of the lack of fit that has been seen between some experimental data and theory. (Sampling and testing can however still be used to provide additional contextual data).The aim of the PhD is to develop and explore this technique further, calibrating it on selected physical model studies and extending it to granular materials. This will be enabled through design and testing of specific physical models using the state of the art 1g and centrifuge physical modelling facilities, together with transparent and photo-elastic soil capabilities in the geotechnics research group. Analytical/numerical developments will take advantage of the leading capabilities of the CMD group in applying optimization in Civil Engineering. Such work will strengthen Sheffield's status in physical modelling and use of optimization.Whilst field application of the technique is not the direct aim of this PhD, industry bodies such as Network Rail have shown interest in the technique where aerial and ground based digital imaging, LIDAR and wireless sensor data can be combined to generate a detailed dataset. One aspect of the research project will be to explore these possibilities in outline in order to provide a wider context for the proposed work.