Mining Safety and Sustainability I

Safety and sustainability are becoming ever bigger challenges for the mining industry with the increasing depth of mining. It is of great significance to reduce the disaster risk of mining accidents, enhance the safety of mining operations, and improve the efficiency and sustainability of development of mineral resource. This book provides a platform to present new research and recent advances in the safety and sustainability of mining. More specifically, Mining Safety and Sustainability presents recent theoretical and experimental studies with a focus on safety mining, green mining, intelligent mining and mines, sustainable development, risk management of mines, ecological restoration of mines, mining methods and technologies, and damage monitoring and prediction. It will be further helpful to provide theoretical support and technical support for guiding the normative, green, safe, and sustainable development of the mining industry

Development of a distributed optical fiber sensor for geological applications

The purpose of the study was to develop a distributed optical fiber acoustic sensor for monitoring ground subsidence before collapse sinkholes form causing costly damage on infrastructure. Costs in excess of R1.3 billion have been incurred while dealing with sinkhole related measures in South Africa. Monitoring sinkholes and the presence of an early warning alert system can drastically reduce the impact, risk and cost caused by sudden ground collapse. A related goal was to construct a reliable collapse alert early warning system to facilitate disaster preparedness and avoid further damage from accidents. This was achieved by developing a spectroscopic shift monitoring algorithm which analysed changes in the subsurface vibration modes using ambient noise signals. For the first time to our knowledge, an optic fiber sensor with an early warning alarm, using ambient noise vibrations to detect and monitor sinkholes was developed at NMU. A polarisation-based, interferometric optical fiber seismic sensor was developed and compared to a commercial geophone. The fiber sensor exhibited superior performance in sensitivity, bandwidth, signal response and recovery times. The sensitivity of the optical fiber sensor was 0.47 rad/Pa surpassing the geophone sensitivity by 9.32%, and the bandwidth of 3.349kHz was 20 times greater for the optical fiber sensor. The fiber sensor was used to measure millisecond events as the impact duration of a bouncing ball was successfully obtained. It was used to detect sinkhole formation in the simulator model, designed. Ground collapse precursors were identified, and early warning alert was achieved using the spectral analysis algorithm, developed. The collapse precursor condition was identified as a functional combination of variations in the peak frequency, bandwidth and peak intensity. A distributed acoustic sensor was built to detect ambient noise induced subsurface signals. Vibrations were located along the 28km length of optical fiber with a relative error of 9.6%. The sensor demonstrated a frequency response range of 212.25Hz, an event distance precision of 224m with time resolution of 1.12µs, and a spatial resolution of 1km. The position of disturbance was measured within 300m of its actual point of 3.21km along the optical fiber. The results showed that distributed optical fiber sensing allows real-time monitoring of the subsurface over extended distances, using ambient noise signals.Thesis (PhD) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 202

Development of a distributed optical fiber sensor for geological applications

The purpose of the study was to develop a distributed optical fiber acoustic sensor for monitoring ground subsidence before collapse sinkholes form causing costly damage on infrastructure. Costs in excess of R1.3 billion have been incurred while dealing with sinkhole related measures in South Africa. Monitoring sinkholes and the presence of an early warning alert system can drastically reduce the impact, risk and cost caused by sudden ground collapse. A related goal was to construct a reliable collapse alert early warning system to facilitate disaster preparedness and avoid further damage from accidents. This was achieved by developing a spectroscopic shift monitoring algorithm which analysed changes in the subsurface vibration modes using ambient noise signals. For the first time to our knowledge, an optic fiber sensor with an early warning alarm, using ambient noise vibrations to detect and monitor sinkholes was developed at NMU. A polarisation-based, interferometric optical fiber seismic sensor was developed and compared to a commercial geophone. The fiber sensor exhibited superior performance in sensitivity, bandwidth, signal response and recovery times. The sensitivity of the optical fiber sensor was 0.47 rad/Pa surpassing the geophone sensitivity by 9.32%, and the bandwidth of 3.349kHz was 20 times greater for the optical fiber sensor. The fiber sensor was used to measure millisecond events as the impact duration of a bouncing ball was successfully obtained. It was used to detect sinkhole formation in the simulator model, designed. Ground collapse precursors were identified, and early warning alert was achieved using the spectral analysis algorithm, developed. The collapse precursor condition was identified as a functional combination of variations in the peak frequency, bandwidth and peak intensity. A distributed acoustic sensor was built to detect ambient noise induced subsurface signals. Vibrations were located along the 28km length of optical fiber with a relative error of 9.6%. The sensor demonstrated a frequency response range of 212.25Hz, an event distance precision of 224m with time resolution of 1.12µs, and a spatial resolution of 1km. The position of disturbance was measured within 300m of its actual point of 3.21km along the optical fiber. The results showed that distributed optical fiber sensing allows real-time monitoring of the subsurface over extended distances, using ambient noise signals.Thesis (PhD) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 202

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

Signal processing methods for defect detection in multi-wire helical waveguides using ultrasonic guided waves

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University LondonNon-Destructive Testing of industrial components carries vital importance, both financially and safety-wise. Among all Non-Destructive techniques, Long Range Ultrasonic Testing utilizing the guided wave phenomena is a young technology proven to be commercially valid. Owing to its well-documented analytical models, Ultrasonic Guided Waves has been successfully applied to cylindrical and plate-like structures. Its applications to complex structures such as multi-wire cables are fairly immature, mainly due to the high complexity of wave propagation. Research performed by the author approaches the long range inspection of overhead transmission line cables using ultrasonic guided waves. Existing studies focusing on guided wave application on power cables are extremely limited in inspection range, which dramatically degrades its chances of commercialization. This thesis consists of three main chapters, all of which approaches different problems associated with the inspection of power cables. In the first chapter, a thorough analysis of wave propagation in ACSR (most widely used power cable) cables is conducted. It is shown that high frequency guided waves, by concentrating the energy on the surface layers, can travel much further in the form of fundamental longitudinal wave mode, than previous studies have shown. Defect detection studies proved the system’s capability of detecting defects which introduce either increase or decrease in cross sectional area of the cable. Results of the chapter indicate the detectability of defects as small as 4.5% of the cross sectional area through a 26.5 meter long cable without any post-processing. In the second chapter, several algorithms are proposed to increase the inspection range and signal quality. Well-documented wavelet-denoising algorithm is optimized for power cables and up to 24% signal-to-noise ratio improvement is achieved. By introducing an attenuation correction framework, a theoretical inspection range of 75 meters is presented. A new framework combining dispersion compensation and attenuation correction is proposed and verified, which shows an inspection range of 130 meters and SNR improvement up to 8 dBs. Last chapter addresses the accurate localization of structural defects. Having proven the optimum excitation and related wave propagation in ACSR cables, a system having a more complex wave propagation characteristics is studied. A new algorithm combining pulse compression using Maximal Length Sequences and dispersion compensation is applied to multi-modal signals obtained from a solid aluminum rod. The algorithm proved to be able to improve signal quality and extract an accurate location for defects. Maximal Length Sequences are compared to chirp signals in terms of SNR improvement and localization, which produced favourable results for MLS in terms of localization and for chirp in terms of SNR improvement

Selected Papers from 2020 IEEE International Conference on High Voltage Engineering (ICHVE 2020)

The 2020 IEEE International Conference on High Voltage Engineering (ICHVE 2020) was held on 6–10 September 2020 in Beijing, China. The conference was organized by the Tsinghua University, China, and endorsed by the IEEE Dielectrics and Electrical Insulation Society. This conference has attracted a great deal of attention from researchers around the world in the field of high voltage engineering. The forum offered the opportunity to present the latest developments and different emerging challenges in high voltage engineering, including the topics of ultra-high voltage, smart grids, and insulating materials

Smart Flow Control Processes in Micro Scale

In recent years, microfluidic devices with a large surface-to-volume ratio have witnessed rapid development, allowing them to be successfully utilized in many engineering applications. A smart control process has been proposed for many years, while many new innovations and enabling technologies have been developed for smart flow control, especially concerning “smart flow control” at the microscale. This Special Issue aims to highlight the current research trends related to this topic, presenting a collection of 33 papers from leading scholars in this field. Among these include studies and demonstrations of flow characteristics in pumps or valves as well as dynamic performance in roiling mill systems or jet systems to the optimal design of special components in smart control systems

An experimental and modelling investigation on the water content of CO2-rich mixtures

As global warming concerns grow, a worldwide appeal for immediate action to reduce greenhouse gas (GHG) emissions unfold. Many factor such as the emission gap between nations, reliance on petrochemicals in all industrial sectors, and the difficulty in estimating the carbon footprint in complex and highly specialised production chains, delay the implementation of practical solutions. In this context, carbon capture, storage and utilisation (CCSU) emerges as the most readily available option for reducing CO2 emission while promoting a smooth and efficient transition into alternative energy sources. However, transporting and processing carbon dioxide and CO2-rich mixtures represent a challenging task for many industrial processes. The unavoidable presence of water and the necessity of handling such mixtures over various operational conditions raises concerns about hydrate formation and corrosion suppression. This study presents an experimental and modelling investigation for improving field monitoring and model predictions for water content in CO2- rich mixtures. Measurements are performed using a Tunable Diode Laser Spectroscopy (TDLAS) and a calibration-free fluid-independent new methodology named Differential Scanning Hygrometry (DSH). This novel analytical approach has been successfully tested for measuring dew/frost temperatures for carbon dioxide, methane, nitrogen, CO2-rich mixtures and natural-gas-like synthetic mixtures in equilibrium with hydrates, free water and ice. In addition, a procedure for dew/frost temperature conversions to mole concentration is also discussed. Further investigations on vapour-liquid CO2/methane and hydrate dissociation for CO2/propane binary systems are also conducted showing good agreement with recent publications. Finally, the study has also evaluated the capabilities and limitations of six well-established EoS for modelling natural gas and CCSU fluids. This evaluation has included the advanced and asymmetric mixing rules (Huron-Vidal, Orbey-Wong-Sandler and Non-density dependent) coupled with Soave-Redlich-Kwong and Peng-Robinson EoS, cubic-plus association SAFT hybridisation (CPA) approach and the multiparametric GERG model (a modified EoS-CG version). A detailed fitting process included tuning saturation pressure for single components, VLE for methane/carbon dioxide, hydrate dissociation, and mutual solubility in binary systems involving water. Once adjusted, the capabilities of these adjusted models in describing multicomponent mixtures has been assessed. Overall, sCPA and a proposed predictive SRK combined with Huron-Vidal mixing rules for water-involving binary systems displayed good results with average deviations slightly below 11%

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space