The exploitation of acoustic-to-seismic coupling for the determination of soil properties

Laboratory measurements of three predicted wave types (two compressional or P-waves and one shear S-wave) have been made in artificial soils. The Type-I P and S-wave are predicted to be most sensitive to the macroscopic elastic properties of the frame, whilst the Type II P-wave is predicted to be most sensitive to the hydrodynamic material properties. A loudspeaker source has been used for the preferential excitation of the Type II P-wave whilst preferential excitement of the Type-I P-wave has been accomplished using a mechanical shaker. Probe microphone measurements of the Type-II wave allowed the flow resistivity and tortuosity of the material to be determined using a rigid frame model, whilst deduction of elastic moduli has been made from signals received at buried geophones. It has been shown that microphone signals include Type-I P-wave energy in a high flow resistivity soil. Acoustically deduced soil properties are consistent with mechanically derived values. A systematic investigation of outdoor measurements of acoustic-to-seismic coupling ratio has been made. From the measurements, it has been found that the geophone-ground coupling has a great effect upon the measured coupling ratio. In-situ calibration methods have been developed to overcome this problem. whilst the novel use of a Laser Doppler Vibrometer has been proposed to provide a completely non-invasive method of measuring motion in soils. The measured coupling ratio has been compared with theoretical predictions, using a modified Bio-Sto11 formulation. The model can be used to predict values of flow resistivity, porosity, bulk and shear moduli and layer depths. Reasonable agreement has been obtained between the model and data. Procedures that exploit acoustic-to-seismic coupling data and models to determine soil properties have been developed and used to measure the soil properties of friable agricultural soils where more standard investigation techniques have proved unsuitable

Dynamic Characterization of Open-ended Pipe Piles in Marine Environment

This chapter is focused on the experimental investigations that can be carried out to dynamically characterize open-ended pipe piles in marine environment. Different test typologies, such as impact load test, free vibration test, forced vibration test, and ambient vibration test, are presented and described with the purpose to provide the right tools to analyze the dynamic behavior, at both small and large strains, of single piles or a system of piles. The appropriate instrumentation, with the suitable protection from marine environment and pile driving installation procedure, is also illustrated. Furthermore, the most common signal processing techniques useful for handling the experimental raw data are addressed together with the analysis techniques for the evaluation of the modal parameters: natural frequencies, damping ratios, and mode shapes. Finally, a part of the experimental campaign carried out by the authors on near-shore open-ended pipe piles is reported as a case study

Comparison study of precise monitoring techniques applied to engineering specimens tested under dynamic loading

Initially, the thesis shows a state of the art for structural health monitoring techniques and procedures. Different types of instrumentations and sensors employed under different requirements, which are presented with the view to monitor a variety of structural issues resulted by numerous conditions. It also presents examples from the literature following the proposed monitoring strategy as a novel pattern. These show how close-range digital photogrammetry and strain gauges have been employed in the past with the view to obtain strain evaluation assessments of the relevant monitored structural elements. Based on three surveys which have been carried out in a historical masonry church in Athens (Greece), the methodology of the thesis is generated with the experimental framework being also formed. Eight experiments have been carried out, five of them at the Advanced Structures Laboratory (CEGE – UCL), one at the Concrete Laboratory (CEGE – UCL) and two of them at the Earthquake and Large Structures Laboratory (EQUALS – University of Bristol). Two scale engineering specimens are employed for the experimental needs, both are scaled down using as a prototype element, the north-eastern wall of the studied church. The five experiments which are carried out in CEGE, are made on small scale masonry specimens, of 1/17th scale and the two experiments in EQUALS are made on large scale masonry specimens, of 1/5th scale. All the seven experiments are dynamically loaded. The only static loaded experiment is carried out at the Concrete Laboratory and it is made on a masonry specimen. Through the comparison of the two monitoring methods, close-range digital photogrammetry (CRDP) and strain gauges (SG), is concluded that both methods can capture a change in strain, on the tested specimens, when a crack is occurring

A high precision accelerometer-based sensor unit for the acquisition of ultra low distortion seismic signals

Over 800,000 people worldwide lost their lives to earthquakes in the last decade and on average 171 people die every day due to earthquake related damage to structures and buildings. Precisely understanding the effects ground motion has on manmade structures is crucial to making them earthquake resistant. This can only be achieved by the precise measurement, recording, and analysis of ground displacement trends during a seismic event. Although there is a vast amount of recorded seismological data available, current technology and processing methods fail to represent accurate ground displacement over time as the considerable technological challenges have yet to be overcome. Raw seismic data has so far been primarily acquired with instruments utilising geophone or accelerometer based sensors. These instruments produce prominent time domain displacement errors due to the various system and sensor inaccuracies, and due to non-linear response. Since accelerometers provide acceleration over time data: whilst geophones are velocimeters, and therefore provide velocity over time data; in order to derive true ground displacement over time, a double, or single numerical integration is required respectively. During this essential numerical integration processes of data from such sensors, even small in magnitude errors accumulate to yield rather large displacement trend offsets over a typical event recording period of 60 to 120 seconds. In addition, the numerical integration process itself poses considerable challenges due to the theoretically infinite number of samples and the accurate determination of initial conditions required for an exact mathematical result to be obtained. The latter, is currently performed by averaging an up to 60 second pre-event data trend stored on the instrument. Most post-integration data from current instruments appears to contain low frequency drifts amongst other noise artefacts, and generally requires baseline correction algorithms in an attempt to correct for these effects. Such corrections, although helpful, only aid to minimise the perceived effects of an assumed and collective source of error, and hence are largely unable to tackle the individual error contribution of each element within the system. Since individual element contribution is of a dynamic nature, the validity of these algorithms is limited by the accuracy of the initial assumptions made about a specific set of data. Faced with such a multivariable and uncertain dynamic behaviour, where even mathematical system modelling is of inadequate long term accuracy, a solution that aims to directly minimise these errors at source, rather than attempt to correct them postacquisition, is of immense importance when it comes to the recording, analysis, and understanding of earthquakes. This thesis describes the design, implementation, and evaluation of a High Precision Active Gyro Stabilised (HPAGS) sensor unit of exceptional performance for the provision of highly accurate ground displacement data. Experimental results demonstrated that the device described herein, was able to diminish the inherent non-linear and environment-dependant effects of current sensors, and thus was able to provide highly improved time domain displacement data

Machine Learning-Based Data and Model Driven Bayesian Uncertanity Quantification of Inverse Problems for Suspended Non-structural System

Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and control strategies based on simulation or prediction results. However, in the surrogate model, preventing overfitting and incorporating reasonable prior knowledge of embedded physics and models is a challenge. Suspended Nonstructural Systems (SNS) pose a significant challenge in the inverse problem. Research on their seismic performance and mechanical models, particularly in the inverse problem and uncertainty quantification, is still lacking. To address this, the author conducts full-scale shaking table dynamic experiments and monotonic & cyclic tests, and simulations of different types of SNS to investigate mechanical behaviors. To quantify the uncertainty of the inverse problem, the author proposes a new framework that adopts machine learning-based data and model driven stochastic Gaussian process model calibration to quantify the uncertainty via a new black box variational inference that accounts for geometric complexity measure, Minimum Description length (MDL), through Bayesian inference. It is validated in the SNS and yields optimal generalizability and computational scalability

MEMS accelerometer: proof of concept for geotechnical engineering testing

Geotechnical engineering materials are inherently variable, which leads to many simplifications when trying to model their behavior. The materials must always be characterized prior to any design work so that the engineer knows which direction he must progress to have a reliable design. Although subsurface characterization techniques and geotechnical design steadily improve, they are by no means infallible. The combination of geotechnical subsurface characterization along with geophysical techniques for improved design and construction monitoring has begun to surface as a viable alternative to the standard techniques in geotechnical engineering. This is important because there is a lack of Quality Control/Quality Assurance during the construction stage of a project, which further compounds the problems inherent from the complexity of the subsurface. Geophysical techniques based on elastic wave propagation provide an excellent combination of characterization and monitoring for the observation of geotechnical engineering projects. Elastic wave propagation provides coverage between traditional boreholes and it helps infer changes in the state of stresses. Unfortunately, sensors for this type of monitoring have typically been expensive, and the use of elastic wave propagation for characterization and monitoring has just begun to become to be implemented. The application of elastic wave tomography needs an inexpensive set of sensors to help justify its inclusion in the broad area of construction monitoring and characterization systems. This set of inexpensive sensors has arrived on the market developed from Miniature Electro-Mechanical Systems (MEMs) technology. This research developed the Analog Devices’ ADXL250 MEMS accelerometer to determine its limitations and its range of applications. In addition, a packaging system developed to allow for a broader range of applications in geotechnical engineering. Once the sensor was fully calibrated, a long-term goal for the research was to utilize the instrument in a laboratory experiment to obtain a tomographic image of the state of stress within a model. While the sensor was utilized in a model in this study, the final reasoning for its use within the model was simply to show its capabilities and areas of application. Simple velocity distributions are given as well as inferences made about the driving factors for these behaviors

Physical modelling of the seismic response of gas pipelines in laterally in homogeneous soil

This paper reports on results from a series of 1-g, reduced-scale, shake table tests of a 216mlong portion of an onshore steel gas transmission pipeline embedded in horizontally layered soil. A set of first-order set of dynamic similitude laws was employed to scale system parameters appropriately. Two sands of different mean grain diameter and bulk density were used to assemble a compound symmetrical test soil consisting of three uniform blocks in a dense-loose-dense configuration. The sandpipe interface friction coefficients were measured at 0.23 and 0.27. Modulated harmonic and recorded ground motions were applied as table excitation. To monitor the detailed longitudinal strain profiles in the model pipe, bare Fiber Bragg Grating cables were deployed. In most cases, the pipe response was predominantly axial while bending became significant at stronger excitations. levels. Strain distributions displayed clear peaks at or near the block interfaces, in accord with numerical predictions, with magnitudes increasing at resonant frequencies and with excitation level. By extension to full-scale, peak axial strain amounted to approximately 10-3, a demand half the yield strain, but not negligible given the low in-situ soil stiffness contrast and soil-pipe frictio