No abstract

No abstract

We present an investigation on a coupled system consists of gold nanoparticles and silicon nanocrystals. Gold nanoparticles (AuNPs) embedded into porous silicon (PSi) were prepared using the electrochemical deposition method. Scanning electron microscope images and energy-dispersive X-ray results indicated that the growth of AuNPs on PSi varies with current density. X-ray diffraction analysis showed the presence of cubic gold phases with crystallite sizes around 40 to 58 nm. Size dependence on the plasmon absorption was studied from nanoparticles with various sizes. Comparison with the reference sample, PSi without AuNP deposition, showed a significant blueshift with decreasing AuNP size which was explained in terms of optical coupling between PSi and AuNPs within the pores featuring localized plasmon resonances.

Abstract. Water is the most treasure natural resources, however, a huge amount of water are lost during its distribution that leads to water leakage problem. The leaks meant the waste of money and created more economic loss to treat and fix the damaged pipe. Researchers and engineers have put tremendous attempts and effort, to solve the water leakage problem especially in water leakage of buried pipeline. An advanced technology of ground penetrating radar (GPR) has been established as one of the non-destructive testing (NDT) method to detect the underground water pipe leaking. This paper focuses on the ability of GPR in water utility field especially on detection of water leaks in the underground pipeline distribution. A series of laboratory experiments were carried out using 800-MHz antenna, where the performance of GPR on detecting underground pipeline and locating water leakage was investigated and validated. A prototype to recreate water-leaking system was constructed using a 4-inch PVC pipe. Different diameter of holes, i.e. ¼ inch, ½ inch, and ¾ inch, were drilled into the pipe to simulate the water leaking. The PVC pipe was buried at the depth of 60 cm into the test bed that was filled with dry sand. 15 litres of water was injected into the PVC pipe. The water leakage patterns in term of radargram data were gathered. The effectiveness of the GPR in locating the underground water leakage was ascertained, after the results were collected and verified.

Modern industrial plant operations often require accurate level measurement of process liquids in production and storage vessels. A variety of advanced level indicators are commercially available to meet the demand, but these may not suit specific need of situations. The neutron backscatter technique is exceptionally useful for occasional and routine determination, particularly in situations such as pressure vessel with wall thickness up to 10 cm, toxic and corrosive chemical in sealed containers, liquid petroleum gas storage vessels. In level measurement, high energy neutrons from 241 Am-Be radioactive source are beamed onto a vessel. Fast neutrons are slowed down mostly by collision with hydrogen atoms of material inside the vessel. Parts of thermal neutron are bounced back towards the source. By placing a thermal detector next to the source, these backscatter neutrons can be measured. The number of backscattered neutrons is directly proportional to the concentration of the hydrogen atoms in front of the neutron detector. As the source and detector moved by the matrix around the side of the vessel, interfaces can be determined as long as it involves a change in hydrogen atom concentration. This paper presents the slow neutron mapping technique to indicate level interface of a test vessel.

Ground Penetrating Radar (GPR) is a high resolution electromagnetic techniques that is designed primarily to investigate the shallow subsurface of the earth, building material, roads and bridges. GPR was also able to detect water leaks in the underground distribution system. A series of laboratory experiments were conducted to determine the validity and effectives of GPR technology in detecting water leakage using two different types of pipes which are metal and polyvinyl chloride (PVC) pipes. Experiment was conducted using GPR 800 MHz antenna using 4 inch pipe with diameter of hole is ¼ inch to stimulate the leakage. GPR identify leaks in buried water pipes either by detecting underground voids created by the leaking water as it erodes the material around the pipe or by detecting anomalous change in the properties of the materials around pipes due to the water saturation.

Ground penetrating radar (GPR) is one of the promising non-destructive imaging tools investigations for shallow subsurface exploration such as locating and mapping the buried utilities. In practical applications, GPR images could be noisy due to the system noise, the heterogeneity of the medium, and mutual wave interactions thus, it is a complex task to recognizing the hyperbolic signature of buried objects from GPR images. Therefore, this paper aims to develop nonlinear feature extraction technique of using Empirical Mode Decomposition (EMD) in recognizing the four geometrical shapes (cubic, cylindrical, disc and spherical) from GPR images. A pre-processing step of isolating hyperbolic signature from different background was first employed by mean of Region of Interest (ROI). The hyperbolic signature that describes the shapes was extracted using EMD decomposition to obtain a set of significant features. In this framework, the hyperbolic pattern was decomposed of using EMD, to produce a small set of intrinsic mode functions (IMF) via sifting process. The IMF properties of the signature that exhibit the unique pattern was used as potential features to differentiate the geometrical shapes of buried objects. The extracted IMF features were then fed into machine learning classifier namely Support Vector Machines. To evaluate the effectiveness of the proposed method, a set data collection of GPR-images has been acquired. The experimental results show that the recognition rate of using IMF features was achieved 99.12% accuracy in recognizing the shapes of buried objects whose shows the promising result.

This paper presents a review on Ground Penetrating Radar (GPR) detection and mapping of buried utilities which have been widely used as non-destructive investigation and efficiently in terms of usage. The reviews cover on experimental design in GPR data collection and survey, pre-processing, extracting hyperbolic feature using image processing and machine learning techniques. Some of the issues and challenges facing by the GPR interpretation particularly in extracting the hyperbolas pattern of underground utilities have also been highlighted.