Imaging of Scarce Archaeological Remains Using Microwave Tomographic Depictions of Ground Penetrating Radar Data

The Romano-British site of Barcombe in East Sussex, England, has suffered heavy postdepositional attrition through reuse of the building materials for the effects of ploughing. A detailed GPR survey of the site was carried out in 2001, with results, achieved by usual radar data processing, published in 2002. The current paper reexamines the GPR data using microwave tomography approach, based on a linear inverse scattering model, and a 3D visualization that permits to improve the definition of the villa plan and reexamine the possibility of detecting earlier prehistoric remains

Modelling the variation of suction pressure during caisson installation in sand using FLAC3D

A suction caisson is an upturned ‘bucket’ of cylindrical shape made from steel. This type of foundation has been very popular in the oil and gas industry and the current trend is to extend its use to offshore wind farms. Seepage conditions play a pivotal role in suction caisson installation process in sand. Pressure gradients generated by imposed suction inside the caisson cavity cause an overall reduction in the soil resistance around the caisson wall and tip. This transient soil loosening around the caisson wall helps caisson penetration into the seabed. In this paper, we present a study of the role of seepage on the suction caisson installation process in homogenous sand. We also investigate the effects of seepage conditions on soil resistance to caisson penetration with a particular focus on how frictional and tip resistances are differently affected. For this purpose, a series of numerical models are developed using FLAC3D. These models are used to investigate the variation of suction pressure during caisson installation in homogenous sand and to predict the amount of suction required to penetrate the caisson to a certain depth. An explicit strategy is used for each embedment depth, which consists of updating current suction based on displacement history available after the previous prescribed displacement increment. The numerical models are developed for different caisson sizes and wall thicknesses to study the effects of caisson geometry on soil resistance during caisson installation. Problem dimensions are normalised with respect to the diameter of the caisson in order to obtain the results that can be applied to any caisson size. The results showed that suction pressure tends to increase with the embedment depth. Additionally, the overall behaviour and the pressure variation with depth are similar for caissons of different sizes and wall thicknesses. Finally, in order to validate the developed numerical models, data from centrifuge tests are investigated and compared with the results obtained from this study. The developed finite difference models are found to be in good agreement with centrifuge tests, in particular for thicker caissons (t/D = 1%)

The Use of GPR and Microwave Tomography for the Assessment of the Internal Structure of Hollow Trees

Peer reviewedPostprin

Prediction of sulphide build-up in filled sewer pipes

Millions of dollars are being spent worldwide on the repair and maintenance of sewer networks and wastewater treatment plants. The production and emission of hydrogen sulphide has been identified as a major cause of corrosion and odour problems in sewer networks. Accurate prediction of sulphide build-up in a sewer system helps engineers and asset managers to appropriately formulate strategies for optimal sewer management and reliability analysis. This paper presents a novel methodology to model and predict the sulphide build-up for steady state condition in filled sewer pipes. The proposed model is developed using a novel data-driven technique called evolutionary polynomial regression (EPR) and it involves the most effective parameters in the sulphide build-up problem. EPR is a hybrid technique, combining genetic algorithm and least square. It is shown that the proposed model can provide a better prediction for the sulphide build-up as compared with conventional models

An evolutionary approach to modelling concrete degradation due to sulphuric acid attack

Concrete corrosion due to sulphuric acid attack is known to be one of the main contributory factors for degradation of concrete sewer pipes. This paper proposes to use a novel data mining technique, namely, evolutionary polynomial regression (EPR), to predict degradation of concrete subject to sulphuric acid attack. A comprehensive dataset from literature is collected to train and develop an EPR model for this purpose. The results show that the EPR model can successfully predict mass loss of concrete specimens exposed to sulphuric acid. Parametric studies show that the proposed model is capable of representing the degree to which individual contributing parameters can affect the degradation of concrete. The developed EPR model is compared with a model based on artificial neural network (ANN) and the advantageous of the EPR approach over ANN is highlighted. In addition, based on the developed EPR model and using an optimisation technique, the optimum concrete mixture to provide maximum resistance against sulphuric acid attack has been identified

A cross-sectional study on the flood emergency preparedness among healthcare providers in Saudi Arabia

This study used a descriptive cross-sectional methodology to measure healthcare workers’ knowledge, attitudes, perceptions, and willingness to respond to a flood scenario in Saudi Arabia. A validated survey was distributed to collect data using a convenience sampling technique through multiple social media platforms. A total of 227 participants were included in this study: 52% of them were aged between 26 to 34 years, 74% were residents from Riyadh, and 52.4% worked in nursing divisions. A significant number of respondents (73.2%) had positive perceptions towards their hospitals’ ability to provide an effective response to a flood, 89% were willing to report to work following a flood, and 90% of participants reported the need to develop both guidelines and training for flood disaster preparedness. Preparation and successful flood mitigation in the hospital setting requires staff that have both knowledge and training in emergency management. One way to obtain such readiness is through competency-based training, including both table-top and full-scale live exercises. Although the willingness to respond to such a flooding emergency was high among staff, the development of guidelines and educational programs is needed in order to develop the competencies and skills sets to improve disaster preparedness response and preparedness efforts

Satellite remote sensing and non-destructive testing methods for transport infrastructure monitoring: advances, challenges and perspectives

High temporal frequency monitoring of transport infrastructure is crucial to prioritise mainte-nance and prevent major service disruption or structural failures. Ground-based non-destructive testing (NDT) methods have been successfully applied for decades, reaching very high standards for data quality and accuracy. However, routine campaigns and long inspection times are re-quired for data collection and their implementation into reliable infrastructure management systems (IMSs). On the other hand, satellite remote sensing techniques, such as the Mul-ti-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) method, have proven effective in monitoring ground displacements of transport infrastructure (roads, railways and airfields) with a much higher temporal frequency of investigation and the capability to cover wider areas. Nevertheless, the integration of information from i) satellite remote sensing and ii) ground-based NDT methods is still a subject to be fully explored in civil engineering. This paper aims to review significant stand-alone and combined applications in these two areas of endeavour for transport infrastructure monitoring. Recent advances, main challenges and future perspectives arising from their mutual integration are also discussed