course-details-portlet

GB8411 - Modelling and Optimisation in Mineral Production

About

Examination arrangement

Examination arrangement: Oral exam and report
Grade: Passed / Not Passed

Evaluation Weighting Duration Grade deviation Examination aids
Report 60/100
Oral exam 40/100 1 hours D

Course content

Responsible mining practise, considering Sustainable Development Goals (UNSDGs), gains high importance due to the increasing economic competition, social and environmental concerns. Conventionally empirical methods are widely used in many areas of mining engineering starting from mining method selection to the design of different operations. Such methods may not yield in responsible mining practice due to local dependency, inherent variability and high uncertainty in rock properties. Thus, there is a need for advanced and modern computational tools for modelling and optimisation of mining operations to assure responsible mining practise for sustainable development.

This course is designed for PhD students who are familiar with mineral production methods and operations. The course covers modelling and optimisation of mineral production operations using up to date computational tools covered many licenced and open source software. Operations from development to primary crushing stages including but not limited to rock mass characterisation, drilling and blasting, cemented paste backfill, support design, underground stope dimensioning will be modelled and optimised. The content will be customised depending on the student's background and nature of the selected project. It is expected that the selected project is related to the student’s PhD thesis and thus the student has enough information on the subject.

Learning outcome

Knowledge: The student will have detailed knowledge about the factors affecting the selected mining operation, interaction between these factors and their effect outcome of the operation.

Skills: The student will be able to describe the problem and develop model(s) for the considered operation using available software. Upon model development the student will be able to optimize selected operation considering specific objectives and limitations.

General competence: The student will improve critical thinking skill and be able to identify most effective parameters for the selected operation. The student will gain knowledge and skill for performing modeling and optimization of mining engineering related operations using software covered under the course.

Learning methods and activities

Self study on the selected project topic, study groups, project work and practical classes.

Further on evaluation

In order to pass the course, both the report (counts 60%) and the oral exam (counts 40%) must receive a passing score. For a re-take of an examination, all assessments during the course must be re-taken.

Specific conditions

Admission to a programme of study is required:
Engineering (PHIV)

Required previous knowledge

The course requires admission to the PhD programme Engineering, or approval by the person with course responsibility. The student has to have a Master’s degree in mining engineering or related disciplines. The course must be relevant to mineral production operations. The student should have a broad idea about the selected project subject and dependent and independent variables. The approval will be given by the course coordinator.

Course materials

Given at the start of the semester.

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Doctoral degree level

Coursework

Term no.: 1
Teaching semester:  SPRING 2025

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Mineral Production
Contact information
Course coordinator:

Department with academic responsibility
Department of Geoscience

Examination

Examination arrangement: Oral exam and report

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Report 60/100 INSPERA
Room Building Number of candidates
Autumn ORD Oral exam 40/100 D
Room Building Number of candidates
Spring ORD Report 60/100 INSPERA
Room Building Number of candidates
Spring ORD Oral exam 40/100 D
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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