Drilling and blasting is one of the most economical methods used for the exploitation of economic minerals from the earth crust. Ground vibrations induced by blasting are one of the fundamental problems in the mining industry due to its consequence on structural stability of buildings, socio-economical and the public involvement. Frequency is also another important parameter for the safety and stability of existing surrounding structures. There are number of vibration predictors available proposed by different researchers for the prediction of peak particle velocity (PPV) and to calculate safe charge for smooth and trouble free blasting but all the predictors are mainly based on parameters, like explosive charge used per delay and distance from the blast face to monitoring point. However, frequency prediction has been ignored while calculating the safe charge. It is well known that blast vibration is influenced by rock, explosive and blast design parameters. This book deals with assessment of the existing predictors capability vis-à-vis application of soft computing tool to compute the PPV and frequency based on rock, blast design and explosive parameters.

This book gives a rigorous and up-to-date study of the various AI and machine learning algorithms for resolving environmental challenges associated with blasting. Blasting is a critical activity in any mining or civil engineering project for breaking down hard rock masses. A small amount of explosive energy is only used during blasting to fracture rock in order to achieve the appropriate fragmentation, throw, and development of muck pile. The surplus energy is transformed into unfavourable environmental effects such as back-break, flyrock, air overpressure, and ground vibration. The advancement of artificial intelligence and machine learning techniques has increased the accuracy of predicting these environmental impacts of blasting. This book discusses the effective application of these strategies in forecasting, mitigating, and regulating the aforementioned blasting environmental hazards.

This volume gathers the latest advances, innovations, and applications in the field of mining, geology and geo-spatial technologies, as presented by leading researchers and engineers at the International Conference on Innovations for Sustainable and Responsible Mining (ISRM), held in Hanoi, Vietnam on October 15-17 2020. The contributions cover a diverse range of topics, including mining technology, drilling and blasting engineering, tunneling and geotechnical applications, mineral processing, mine management and economy, environmental risk assessment and management, mining and local development, mined land rehabilitation, water management and hydrogeology, regional Geology and tectonics, spatial engineering for monitoring natural resources and environment change, GIS and remote sensing for natural disaster monitoring, risk mapping and revisualization, natural resources monitoring and management, mine occupational safety and health. Selected by means of a rigorous peer-review process, they will spur novel research directions and foster future multidisciplinary collaborations.

In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in your company’s data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate IT and mining engineering students – with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain – in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins – in line with leading “digital” industries.

Collection of excellent articles presenting the latest developments in blast vibration measurements, modeling and mitigation techniques. Includes contributions on novel environmentally-induced vs blast-induced movements, non-conventional geophysical processing techniques, new modeling approaches, mitigation techniques using smarter blasting methods

Tunnelling in Rock by Drilling and Blasting presents the latest developments in the excavation of tunnels using the drilling and blasting method. Examples of work conducted throughout the world including the Indian sub-continent, Australia, and Sweden amongst others are discussed. These tunnel projects serve to illustrate the challenges and i