Тау-кен инжинирингі саласындағы докторантура бағдарламасы

This course provides students with a practical understanding of the application of the fundamental principles governing the behavior of geo-materials (soil, soft and hard rock) in surface and underground mining environments. It covers: firstly a review of some fundaments of geomechanics; then basic and more advanced applications of geomechanics and finally discusses the implementation of computational tools including numerical modeling, artificial intelligence and data analytics in geomechanics.

Course learning outcomes
1. Recognize the major geotechnical applications and their significance within the mainstream mining systems and conditions.
2. Have a sound working knowledge of fundamental mechanisms and geotechnical principles within the context of practical mining applications.
3. Demonstrate the role and importance of these principles in a comprehensive range of mining applications, both from a technical perspective, and from the risk and operational management perspective.
4. Analyze data objectively using quantitative and mathematical methods.

A research plan is developed by the student in collaboration with the Program Advisor or Research Supervisor at the start of the semester outlining the research goals to be accomplished. At the end of the semester the student files a research report which is graded (P/F) by the Program Advisor or Research Mentor (when selected). The “in-progress” grade is submitted and maintained on the student’s transcript; credit is awarded on successful completion of thesis requirements.

Course learning outcomes
1. Prepare and design research framework.

Statistics course will focus on the statistical and data analytics techniques applied for onshore and marine petroleum and gas & mining industry. This course will provide PhD students with the practical skills and theoretical knowledge on how to collect, analyze, interpret and present different types of data and research results for onshore and marine petroleum and gas & mining industry. Different data types will be addressed and used in this course to cover broad range of research interests by PhD students. Moreover, along with the standard statistical techniques, this course will introduce the aspects of spatial statistics. The scientific research and publication skills will also be strengthened in the process of this course. This course will be targeted to the research interests of PhD students so that they can practically apply what they learnt out of this course and demonstrate the research results in their finalizing projects. The interdisciplinary research principles will also be promoted so that PhD students are able to consider and integrate more aspects in their statistical analysis from different petroleum and gas & mining disciplines.

Course learning outcomes
1. Perform exploratory and descriptive analyses of statistical data.
2. Analyze statistical relationships using regression techniques.
3. Quantitatively compare differences and visualize statistical data.

Advanced Mining Systems is a high level discussion of mining systems in a Systems Engineering context. The course is focused on facilitating critical thinking in how various mining systems should be applied to challenging orebodies for safe and profitable extraction of such orebodies. The course will be started with an introduction to Systems Engineering and why systems thinking in mining engineering is critical. Further discussions will include design of unconventional pillars in room-and pillar mining, innovative approaches to the extraction thick and low grade orebodies and coal seams, application of block caving mining to inclined orebodies and super caves, longwall top coal caving (LTCC), transition from open pit to underground mining strategies, super pits, complex orebodies, strategies for mining in burst-prone ground conditions and at ultra-depths and high temperatures, recovery of remnant pillars and multi-seam and multiple lenses, extraction of ultra-narrow orebodies.

Course learning outcomes
1. Undertake tasks on the design of complex orebodies for their safe and economic extraction.
2. Apply mining systems/methods selecting and designing a mine.
3. Apply critical thinking to optimize the extraction of difficult orebodies.
4. Demonstrate their familiarity with state of the art mining systems and the options often available to them in the decision making process.

This course will help PhD students to become more familiar with the literature of the research direction and research topic they choose as their PhD thesis. Main outcomes in the field, research methodology, and gaps in the literature will be studied and analyzed by each PhD student. This course will help students to prepare their research proposal. Each student will work under the supervision of an expert faculty in the research area of the student. At the end of the course, a report will be submitted by the student to the supervising faculty. 

Course learning outcomes
1. Evaluate and critique existing research sources and materials in their field.
2. Construct a coherent literature review organized in themes and appropriate sub-topics.
3. Articulate a clear and focused research question.
4. Present a well-argued rationale for the selection of a particular methodology or a combination of methods.

The “Doctoral Thesis” course fulfills the four-year research/thesis work of the student. A research plan developed by the student in collaboration with the Program Advisor or Research Supervisor at the start of the studies should be accomplished by the end of the semester. Within the end of the course, the student will be expected to be able to: 1. defend his/her Doctoral Thesis topic; 2. show designed and conducted original research project; 3. Prove the developed skills in designing a discipline-specific research methodology. By the end of the successful defense, a student will be awarded a Doctoral degree.

Course learning outcomes
1. Discover and pursue a unique topic of research in order to construct new knowledge.
2. Design and conduct an original research project.
3. Develop skills in designing a discipline specific research methodology.
4. Develop a working knowledge of relevant literature in the thesis discipline.
5. Practice academic writing appropriate to the discipline and learn how to participate in the peer review process.
6. Plan research activities.
7. Prepare accurate research progress reports.
8. Discuss research and other topics with academics in the thesis discipline.

The objective of this course is to introduce the advanced numerical methods used in rock engineering with application within the mining industry. Fundamentals of continuum and discontinuum mechanics will be reviewed. Theories of continuum and discontinuum modelling techniques will be presented and discussed as appropriate to the development of numerical modelling tools. The governing boundary conditions associated with rock engineering problems and key issues to be considered in the modelling of complex geomechanical problems will be discussed. The application of advanced numerical methods to actual engineering will be demonstrated through case studies and modelling exercises.

Course learning outcomes
1. Undertake a comprehensive numerical study.
2. Apply geomechanics design software to surface and underground mine design studies.
3. Construct geometric models for numerical simulation exercises.
4. Demonstrate the significance of applied numerical modelling in mine design.
5. Relate how to work in groups and objectively evaluate their peers.
6. Create presentations and deliver these professionally.

This course is intended to educate advanced degrees seekers in mining engineering other sources of valuable minerals and how they could be mined for the benefit of society.

Course learning outcomes
1. Demonstrate how other technologies can be applied in the extraction of valuable minerals underwater and off-earth.
2. Develop skills that will enable them mine under extreme conditions.
3. Anticipate through critical thinking how to mine intelligently.
4. Develop interest in mining.

Rapid advances in technological innovation, including automation, digitization, and electrification, fundamentally impact the mining sector. Therefore, this course is designed to equip the students with the latest advancement in automated and autonomous operations in the mining industry. Topics covered in the course will include the latest developments in (1) sensor technology, (2) teleoperated, automated and autonomous equipment and systems, (3) Big Data and Internet of Things IoT, (4) mine robotics and tele-robotics, (5) emerging technologies and adoption of technologies /systems from other fields (space, aviation, military) for terrestrial mining applications, (6) human factors issues in autonomous systems, and (7) strategic mine planning and design for autonomous mining. The course explains and evaluates the latest technological advancements enabling mining automation. It also examines their impact on mine planning and mine management. In addition, it provides comparisons between the mechanized, automated and autonomous mining.


Course learning outcomes
1. Demonstrate the significance of robotics and automation in the mining industry.
2. Appraise the application of automation in mining operations.
3. Demonstrate state-of-the-art mining technologies´ application for different cases.
4. Identify emerging and potential allied field technologies for application in mining operations.

This course provides a technical knowledge for application of geometallurgy in ore characterization. Geometallurgy is an important strategy for any mining project, where the prime objective is to improve the profitability of mines through the use of spatial models of rock properties that have a significant impact on value in a mining project, because it directly influences the revenue from saleable material. This knowledge promotes sustainable development when all stages of extraction are performed in an optimal manner from a technical, environmental, and social perspective. To achieve these goals, development of innovative technologies and approaches along the entire mine value chain are being established. Key component of this allows the students to factor the ore variability into the flowsheet, infrastructure design, production and quality forecasts over life-of-mine. Companies that embrace the geometallurgical program benefit from increased net present value and shareholder value.

Course learning outcomes
1. Design of a technical geometallurgical program for acquisition of data through sampling and measurement.
2. Interpreting and exploratory analysis of geometallurgical data using data analytics methods.
3. Builde a geometallurgical spatial model based on advance geostatistical techniques.
4. Analyses and post processing the produced models to optimize economical parameters in mine for the purpose of mine planning.

This course provides a solid background to students for tunnelling in rock masses. It is designed for students in mining, mechanical, civil, petroleum and electrical and electronical engineering with some background in rock mechanics and engineering.

Course learning outcomes
1. Examine the geotechnical properties of earth materials such as rock and soil.
2. Apply the principles of geotechnical engineering in the context of excavation and tunneling.
3. Evaluate the interaction of rock and machine parameters for estimating the project time and cost.
4. Use various present performance prediction model to estimate the performance of machines, such as TBM, roadheader.
5. Compare the different existing models and discuss advantages and disadvantages of the models for applications.