2018 Undergraduate Research Opportunities

Application Instructions

To apply, send your resume and a list of up to five projects of interest to underground@mines.edu.
Applications are due Tuesday, September 4, 2018.

2018 Projects

Advanced rock fragmentation techniques

Faculty Mentor: Rennie Kaunda

This project aims to improve underground excavation of hard rock using advanced technologies such as microwaves. The project comprises data analysis and laboratory experiments such as microwave treatment of rock samples, linear cutting tests, uniaxial compressive strength tests, indirect tensile strength tests, punch penetration tests, point load index tests, etc. The ideal candidate is a self-starter and highly motivated, with an eye for detail and safety minded. A background in rock mechanics is desired but not a requirement.

Artificial Intelligence / Machine Learning / Data Analysis on Tunnel Boring Machine (TBM) and other Amazing Construction Equipment

Faculty Mentor: Mike Mooney

In this project, we are learning about equipment performance and machine/ground interaction from 1000s of sensors, providing continuous data over months to years. The student(s) will work with our existing team of researchers using the latest artificial intelligence / machine learning methods to examine data. No experience in tunneling or underground engineering is required, but a willingness to learn generally about these massive machines is a must! (See https://www.youtube.com/watch?v=z38JIqGDZVU if you’re curious!).

Earth Pressure Balance Soil Conditioning

Faculty Mentor: Mike Mooney

Participate in a team environment to perform sets of experiments to applying conditioning agents to clay, silt and sand to observe the changes in engineering behavior. Soil mechanics and soil mechanics lab class experience is preferable.

Direct shear testing of soil specimens

Faculty Mentor: Reza Hedayat

Using an advanced geophysical imaging system and in collaboration with a graduate student, the undergraduate student researcher will conduct experiments on soil layers. During the experiments, the soil layer will be sheared while the layer is being monitored by geophysical waves propagated through the layer. This project is experiment-based and provides a great opportunity for a student to develop research skills and gain experience from multiple disciplines including geophysics, mining, and civil engineering. This research work has a very high chance of publication in a high impact journal.

Development of an analytical solution for ground and tunnel interaction

Faculty Mentor: Reza Hedayat

In order to analyze a tunnel, it is essential to understand the various rock mass behaviors after an excavation. The original properties of a rock or rock mass near a tunnel are changed after the excavation. The excavation impact (e.g. due to blasting, TBM drilling, etc.) induces an excavation damaged or disturbed zone around a tunnel. In this regard, in drill and blast method, the damage to the rock mass is more significant. In this zone, the stiffness and strength parameters of the surrounding rock mass are different. The real effect of a damage zone developed by an excavation impact around a tunnel, and its influence on the overall response of the tunnel are of interest to be quantified. The student will be involved with the expansion of an existing analytical solution and implementation of the solution into the Matlab code. Experience with Matlab and other programming languages is desired. This project is suitable for a student from any discipline, e.g., mathematics, statistics, computer science, electrical, civil, mechanical, geological, mining, and physics. Given that a new solution for ground-support interaction has already been developed, there is very high chance of publishing the results of this research effort in a tunneling related journal.

Statistical analysis and machine learning for establishing correlations among soil properties

Faculty Mentor: Reza Hedayat

An extensive database of soil properties is developed for Colorado soils and the goal of this research project is to establish correlations for estimating soil behavior such as shear strength and modulus based on basic soil properties such as density, gradation, moisture content, etc. Through statistical analysis, a set of independent soil variables will be identified for the correlations. The ideal candidate would have some experience with MATLAB and especially the Statistics and Machine Learning Toolbox or similar software such as SAS.

Applications of LiDAR to Deformation Monitoring

Faculty Mentor: Gabe Walton

Monitoring ground movement is a critical component of any instrumentation program. 3D laser scanning (LiDAR) represents a potential valuable tool for making such measurements. By taking advantage of the large volumes of data collected by LiDAR, highly accurate convergence measurements can be made. This position will involve processing LiDAR data collected from various sites to evaluate the accuracy of the data and the trends deformation; there may also be opportunities for short fieldwork stints to collect more data. The ideal candidate would have some experience either with MATLAB or working with LiDAR data.

Rock Joint Roughness Quantification

Faculty Mentor: Gabe Walton

Rock joints have a significant influence on the overall response of a rockmass to tunneling. The behaviour of individual joints is strongly related to their roughness, but limited tools for the measurement and characterization of roughness currently exist. This position will build on previous research focused on lab-scale characterization of joint roughness to study the efficacy of LiDAR for joint roughness measurement in the field. There may also be an opportunity to conduct direct shear testing on rock joints with the goal of correlating joint mechanical behavior with roughness attributes. The ideal candidate would have some experience with laboratory work, MATLAB, and/or laser scanning.

Optimization of Rockbolt Support for Flat-Roofed Excavations

Faculty Mentor: Gabe Walton

Flat-roofed excavations are typically only constructed in horizontally stratified (e.g. sedimentary) rock. Because of the unique excavation geometry and anisotropic rock characteristics in such cases, typical rockbolt support patterns may not be optimal. This position will involved developing and interpreting a series of numerical models to predict rockbolt performance for different geological scenarios and different support designs. The ideal candidate would have some background in rock mechanics and programming.

Rock Fracture mechanics

Faculty Mentor: Eunhye Kim

Understanding the fracture mechanics is important for the improvement of safety and cost-effectiveness in mining processes and geostructure construction. Our research question is to understand the effects of porosity and water content on the fracture toughness, initiation, and propagation. Also, numerical simulation is a useful technique in engineering, especially when a lab or field test is expensive or impractical. I am looking for undergraduate students interested in PFC and/or UDEC software.

Cutting tool design and optimization

Faculty Mentor: Eunhye Kim

I am interested in understanding how cutting tool shape (geometry) and skew angle affect spark mitigation, bit wear, and excavation performance. Also, I am studying the contact mechanism between cutting tool and rocks using a benchtop cutting machine and numerical simulation.

Rock mechanics database using machine learning

Faculty Mentor: Eunhye Kim

Significant rock mechanics database is being constructed to provide public such as students, researchers, and industry workers with rock mechanics information. To enrich the database, I am extracting and collecting rock mechanics data from the literature using machine learning methods. Currently, I am finding undergraduate students interested in data mining (machine learning) techniques.

Evaluating the Strength of Frozen Lunar Regolith for geotechnical evaluation of possible construction on the Moon

Faculty Mentor: Jamal Rostami

The Colorado School of Mines team is currently working on a project for developing a robotic drill that will characterize the ground as it drills through the material. This information will be a part of site investigation for follow up activities such as lunar mining and construction projects. Currently, a team of researchers are working on preparation of samples of moist lunar simulant which will be frozen in a first stage refrigerator and then frozen to -190 degree C with liquid nitrogen to perform strength testing. The objective is to evaluate the material strength and behavior relative to excavation of frozen regolith to allow for selection of the best cutting tools for excavation units. The students participating in this project will work with the research team in preparation of the specimens and conducting of the tests. They will also be involved in analysis of the results and time permitting, some indentation tests to see how the material will behave under different cutting tools.

Miniature linear cutting machine (MLCM) testing of rock for estimation of rock strength

Faculty Mentor: Jamal Rostami

A miniature LCM has been developed that can make small incisions and scratches into the rock surface and the past experience has shown that the cutting forces measured by the dynamometer is directly related to rock strength. In other words, measured forces can be used to estimate the rock strength. There is a database of various rock types that has been cut by MLCM and we have various rock properties and an undergraduate student can develop a relationship between these parameters using statistical analysis. The study may need classification of rock types and developing various formulas for different rock types. There are plans to perform additional tests in near future to expand the database and targeted testing can be performed to complement existing data for the analysis. A Mining or Geological engineering student can work on this topic and make a good product that can easily be published.

Design of the electronic circuits of rock strength borehole probe (RSBP)

Faculty mentor: Jamal Rostami

RSBP is a cylindrical probe that is designed to make an scratch on borehole wall and estimate rock strength from measured forces. The system has already been designed and fabricated and all the main mechanical and electronic components including the guide wheels, scratcher, force measurement system, optical motion detection system, and microprocessor for collecting and storing the data has been fully developed and the system has been assembled and tested in the lab and in the field. Howver, the microprocessor seem to be vulnerable and the electronic circuit needs to be revamped. Ideally an electrical engineering or a mechanical engineering student with strong background in control and robotics can look through the available schematics and trouble shoot the system and modify it to become operation ready. There funds available to procure the components to make this system work.