Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

A team of researchers at Google's DeepMind Technologies has been working on a means to increase the capabilities of computers by combining aspects of data processing and artificial intelligence and have come up with what they are calling a differentiable neural computer (DNC.) In their paper published in the journal Nature, they describe the work they are doing and where they believe it is headed. To make the work more accessible to the public team members, Alexander Graves and Greg Wayne have posted an explanatory page on the DeepMind website. [13]

Convolutional Neural Network를 이용한 한국어 영화평 감성 분석

Advances, limitations and prospects of nondestructive testing and evaluation of thick composites and sandwich structures: A state-of-the-art review

Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms

Ultrasonic guided wave (UGW) is one of the most commonly used technologies for non-destructive evaluation (NDE) and structural health monitoring (SHM) of structural components. Because of its excellent long-range diagnostic capability, this method is effective in detecting cracks, material loss, and fatigue-based defects in isotropic and anisotropic structures. The shape and orientation of structural defects are critical parameters during the investigation of crack propagation, assessment of damage severity, and prediction of remaining useful life (RUL) of structures. These parameters become even more important in cases where the crack intensity is associated with the safety of men, environment, and material, such as ship’s hull, aero-structures, rail tracks and subsea pipelines. This paper reviews the research literature on UGWs and their application in defect diagnosis and health monitoring of metallic structures. It has been observed that no significant research work has been convened to identify the shape and orientation of defects in plate-like structures. We also propose an experimental research work assisted by numerical simulations to investigate the response of UGWs upon interaction with cracks in different shapes and orientations. A framework for an empirical model may be considered to determine these structural flaws.

Structural Health Monitoring (SHM) and Determination of Surface Defects in Large Metallic Structures using Ultrasonic Guided Waves.

Tungsten inert gas (TIG) welding of austenitic stainless steels is a critical process used in industries. Several properties of the welds must be controlled depending on the application. These properties, which include the geometrical, mechanical and microstructural features, can be modified through an appropriate composition of shielding gas. Researchers have studied the effects of the addition of nitrogen through the shielding gas; however, due to limited amount of experimental data, many of the interaction effects are not yet reported. In this study, welds were made homogeneously as well as heterogeneously with various concentrations of nitrogen added through the shielding gas. The gas compositions used were 99.99%Ar (pure), 2.5% N2 + Ar, 5% N2 + Ar and 10% N2 + Ar. Additionally, the welding process parameters were varied to understand different interaction effects between the shielding gas chemistry and the process variables such as filler wire feed rate, welding current, etc. Strong interactions were observed in the case of heterogeneous welds between the gas composition and the filler wire feed rate, with the penetration depth increasing by nearly 30% with the addition of 10% nitrogen in the shielding gas. The interactions were found to influence the bead geometry, which, in turn, had an effect on the mechanical properties as well as the fatigue life of the welds. A nearly 15% increase in the tensile strength of the samples was observed when using 10% nitrogen in the shielding gas, which also translated to a similar increase in the fatigue life.

/pdf/effect-of-the-addition-of-nitrogen-through-shielding-gas-on-kj6k08efl5.pdf

Effect of the addition of nitrogen through shielding gas on tig welds made homogenously and heterogeneously on 300 series austenitic stainless steels

Welding high-strength aluminium alloys is generally a delicate operation due to the degradation of mechanical properties in the thermally affected zone (TAZ) and the presence of porosities in the molten metal. Furthermore, aluminium alloys contain compounds that solidify before the rest of the base alloy, therefore acting as stress concentration points that lead to the phenomenon of hot cracking. This paper investigates the process of applying ultrasonic vibrations to the molten pool aluminium alloy AA6082 to improve both its microstructure and mechanical properties. We analysed conventional and ultrasonic-assisted laser welding processes to assess the sonication effect in the ultrasonic band 20–40 kHz. Destructive and nondestructive tests were used to compare ultrasonically processed samples to baseline samples. We achieved a 26% increase in the tensile and weld yield strengths of laser welds in the aluminium plates via the power ultrasonic irradiation of the welds under optimum ultrasonic variable values during welding. It is estimated that the ultrasound intensity in the weld melt, using a maximum power of 160 W from a pair of 28 kHz transducers, was 35.5 W/cm2 as a spatial average and 142 W/cm2 at the antinodes. Cavitation activity was significant and sometimes a main contributor to the achieved improvements in weld quality.

/pdf/improvements-in-the-microstructure-and-mechanical-properties-1dusk1ia.pdf

Improvements in the Microstructure and Mechanical Properties of Aluminium Alloys Using Ultrasonic-Assisted Laser Welding

ABSTRACT The industry 4.0 has created a paradigm shift in how industrial equipment could be monitored and diagnosed with the help of emerging technologies such as artificial intelligence (AI). AI-driven troubleshooting tools play an important role in high-efficacy diagnosis and monitoring processes, especially for systems consisting of several components including wind turbines (WTs). The utilization of such approaches not only reduces the troubleshooting and diagnosis time but also enables fault prevention by predicting the behavior of different components and calculating the probability of near future failure. This not only decreases the costs of repair by providing constant component’s monitoring and identifying faults’ causes but also increases the efficacy of the apparatus by lowering the downtimes due to the AI-driven early warning system. This article evaluated, compared, and contrasted eight different artificial neural network (ANN) models for diagnosis and monitoring of WTs that predict the machinery’s system failure based on internal components’ sensor signals and generation temperature. This article employed a machine learning model approach with two hidden layers using multilayer linear regression to achieve its objective. The developed system predicted the output of the WT’s generator temperature with an accuracy of 99.8% with 2 months in advance measurement prediction.

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2034718?needAccess=true

An Artificial Intelligence Neural Network Predictive Model for Anomaly Detection and Monitoring of Wind Turbines Using SCADA Data

Gallium phosphate single crystal has a very stable thermal response, ideal for high temperature applications such as transducers for in-service monitoring of HT infrastructure in Power and Oil & Gas industries. Broadband transducers are designed to resonate with a specific mode of vibration within a frequency range of interest. This desired frequency response depends on how the transducer is mounted on the structure and the target defect sensitivity. Electrode configurations are defined to achieve the transducer design. This study investigates the parallel and wrap-around electrode configurations on the transducer response. An electro-mechanical finite element model was developed to analyse the transducer response and predicted a disparity in the modes of vibration between the two configurations within the same frequency range. This model was experimentally validated by measuring the displacement patterns using 3D Laser Doppler Vibrometry.

/pdf/effect-of-electrode-configuration-on-high-temperature-58u9ysn4gk.pdf

Effect of Electrode Configuration on High Temperature Thickness Shear Gallium Phosphate Transducer

Over the past hundred years, overhead power line cables have been widely installed around the world. These cables are commonly exposed to adverse environmental conditions that can affect their structural integrity and over time, could lead to the complete failure of the structure. This research presents the use of guided waves for the inspection of the structural integrity of the overhead power line cables. The proposed system relies on permanently installing on power line cables a multiple transducers collar as well as a pulse receiver. The system is installed on the cable and performs automated regular inspections. One of the key features of this technique is its ability to inspect a long section of the cable from a single inspection point. To achieve this objective, the wave propagation features have been studied in a wide range of frequencies in 50m long cables, where different collar configurations were used. In addition, power line cables, when installed, are subjected to different axial loads depending on the type of cable and the distance between pylons. The effects of the axial load on the wave propagation have been studied. To assess the defect detection capabilities of the system over a wide range of distances without damaging the cable samples, a metallic clamp is used to introduce a crosssection change on the cables, simulating the effect of a fault on the cables (i.e. corrosion). The experimental results show the highly attenuative effect of the axial load on the wave propagation for most of the frequency spectrum. However, it was found that at low frequencies the system performance allowed the inspection of long distances. This was further proven with the experimental results for the clamp detection study.

/pdf/long-range-guided-wave-propagation-experimental-analysis-in-56o88vp6ek.pdf

Jamil Kanfoud

Papers

Effect of the addition of nitrogen through shielding gas on tig welds made homogenously and heterogeneously on 300 series austenitic stainless steels

Improvements in the Microstructure and Mechanical Properties of Aluminium Alloys Using Ultrasonic-Assisted Laser Welding

An Artificial Intelligence Neural Network Predictive Model for Anomaly Detection and Monitoring of Wind Turbines Using SCADA Data

Effect of Electrode Configuration on High Temperature Thickness Shear Gallium Phosphate Transducer

Long Range Guided Wave Propagation Experimental Analysis in Overhead Power Line Cables under Different Axial Load Levels