You will earn 6 research credits over 8 weeks, conducting faculty-supervised, hands-on, directed study research projects with results that will culminate in the preparation of a research paper. You will complete a minimum of 240 hours on research in and out of the laboratory.
Faculty mentors will work closely with you to direct your continued growth and knowledge development in the chosen research topic discipline.
| Course ID | Title | Credits | Syllabus |
|---|---|---|---|
| RSTR RSLW 392S | International Independent Research in STEM Fields | 6 |
In most low- and middle-income countries (LMICs), travel demand data is difficult to access, of poor quality or simply not collected. A lack of data makes it very difficult to a) report progress against the UN’s Sustainable Development Goals (SDGs) and b) build policy, project and investment pipelines towards sustainable transport systems that promote equitable access to goods and services – including education, healthcare and economic opportunities.
Desired qualifications: Ability to conduct research independently with supervision meetings; enthusiasm & willingness to learn transport system development data requirements in LMICs; effective communication and writing.
Relevant majors: Civil Engineering; Computer Engineering; Computer Science; Data Science
Traditional scientific codes developed by academics are associated with a user manual that is hardly maintained. This often produces a discrepancy between the code and the user manual. In addition, users generally do not use provider manuals, but prefer searching for solutions on websites or chat-boxes. This project seeks to identify the most appropriate open-source model to train a local GPT chat.
Desired qualifications: The student would need to be able to program in Python or other relevant environments. Interest and previous experience using GPT boxes is highly recommended.
Relevant majors: Computer Engineering, Data Science, Statistics
The CAELUS project aims to develop a drone delivery network for delivering medical items and supporting the emergency service in Scotland (see https://projectcaelus.co.uk). Specifically, this project will contribute to the development of a digital twin, a virtual replica of the physical system, which will be used to simulate and analyze the design and operation of drone networks in real-world environments. This project will involve basic coding, and analysis of different scenarios using the digital twingin developed at the University of Strathclyde. The aim of the project is to contribute to the development of the digital twin developed at the university. The main objectives are:
Objectives can be refined according to the needs and interests of the student.
Desired qualifications: Basic understanding of probability and statistics. Basic coding skills.
Relevant majors: Mechanical Engineering, Computer Engineering, Data Science, Statistics
The research focuses on assessing and improving the resilience of fuel and biofuel supply chain infrastructure in Brazil. This project will involve creating visualizations such as maps, graphs, and diagrams to demonstrate how the fuel supply chain is organized and how it has responded to past disruptive events. Main objectives include:
Desired qualifications: Proficiency or interest in data visualization (DataViz)
Relevant majors: Data Science, Computer Science, Chemical Engineering, Environmental Engineering
This project focuses on assessing the impacts of foundation excavation on nearby subway structures. As urbanization progresses, construction activities in dense city environments often involve foundation work close to critical infrastructure such as subways. The project will explore how these excavations affect subway tunnels and associated structures, with a specific emphasis on potential deformation, displacement, and long-term stability issues. Through a detailed case study approach, this research will analyze real-world scenarios and apply numerical modeling techniques to evaluate risks and propose mitigation strategies.
The objectives could include:
Desired qualifications: Basic knowledge of geotechnical and structural engineering. Familiarity with soil-structure interaction concepts. Experience with numerical modeling software (e.g., PLAXIS, FLAC) is a plus but not mandatory.
Relevant majors: Civil Engineering, Environmental Engineering, Data science
This project will involve conducting a literature review to gather and analyze the experiences of various countries in managing disruptions in energy supply, particularly for fuels such as diesel, gasoline, biofuels and LPG. The review will explore how governments prepare for and respond to these disruptions, with a particular focus on disruptions caused by climate change-related events. The objectives are:
Desired qualifications: Ability to search for and identify relevant academic and industry sources.
Relevant majors: Engineering (all), Computer Science, Statistics
Induced carbonate precipitation is a key tool for controlling or changing the porosity, permeability and thermal properties of soil and rocks. It can be used to partition subsurface reservoirs for CO2, H2 or heat storage. The same technology can be used as low-carbon bio-cement. To optimize the process, we need to better understand how the precipitation occurs at the pore scale, and what are the key controlling factors on initiation and growth of the calcite.
This project will work on 4D in situ imaging experimental data collected at the Diamond Light Source synchrotron. Because the technique is non-destructive, the x-ray tomography imaging data give us multiple 3D images of the same internal pore network over time. This allows us to observe the location and timing rate of the calcite growth and link this to the pore scale flow field, pore morphology, and reagent concentrations. This project will use image analysis to visualize and quantify these parameters and build an understanding of the process.
Desired qualifications: Ideally have some knowledge of ground engineering, geoscience or soil engineering, and a willingness to develop skills in image analysis (full training on software will be provided and no prior knowledge of x-ray tomography is required).
Relevant majors: Civil Engineering, Chemical Engineering, Environmental Engineering, Environmental Science
Clay-rich soils exhibit substantial changes in mechanical properties and water retention over time when exposed to cyclic environmental loading. While there has been some work conducted on the ratcheting behavior seen under wetting and drying cycles, the impact of freeze-thaw cycles is less well understood. Understanding the combined impact of both wetting-drying and freeze-thaw (which will be operating on the same soils in the real world) at a range of spatial scales is important if we are to be able to mitigate the impacts of increased extreme weather on both natural and engineered clay-rich soils. This includes maintaining the stability of the embankments and cuttings infrastructure that supports most road, rail and flood defense networks. This project will look at how cyclic conditions impact the critical underpinning microstructure (e.g. pores, fractures) in these soils, allowing us a better understanding of the scale, distribution and mechanisms of degradation.
The project will analyze x-ray tomography data. This non-destructive 3D imaging technique allows us to capture the internal structure of small soil samples with micron-scale resolution; when we image the same sample through time over repeated freeze-thaw or wetting-drying cycles, we can observe how every pore and fracture in that sample expands or collapses and under what environmental conditions that change happens. The project will quantify and characterize the evolving structure and link this to the macroscopic material properties more typically measured in the engineering laboratory or in the field. The objective is to provide insight into what controls those field-measurable properties so we can better prevent infrastructure failure.
Desired qualifications: Ideally have some knowledge of ground engineering, soil engineering, soil mechanics, embankment/cutting design, or civil engineering, or some knowledge of geoscience or porous media or All training in image analysis will be provided and no prior knowledge of image analysis is needed).
Relevant majors: Civil Engineering, Environmental Engineering, Environmental Science
Today’s manufacturing must comply with the highest quality standards. Sustainability has become an integral component of any modern business. It is vital for businesses to be able to gather and analyze data beyond estimating products reliability, towards the assessment of carbon emissions and products lifetime.
Mavarick.ai is helping manufacturers and their supply chain become more sustainable using artificial intelligence and machine learning to track and manage fossil carbon emissions.
Among the digital services Mavarick produces carbon footprint auto-generated reports, visualization tools for supply chain emissions, net-zero target tracking and fossil carbon emission forecasting.
Data quality is deemed as the biggest challenge to forecast carbon emission. Mavarick are collecting data from various supply chain sources (e.g., ERP systems, smart meters, IoT devices, manual entries, PDF files), but many of these data sources have missing values or measurement imprecisions, introducing uncertainty into the database. This imprecise nature of the data directly impacts the accuracy of the carbon emissions information companies rely on for tracking sustainability progress, leading to potential errors in decision-making and reporting.
Addressing these potential data quality issues is essential for reliable sustainability management and compliance. This will enable companies to adhere to regulation.
This is an exciting opportunity to engage with a young company whose founding vision is creating a sustainable future in practice. The job will consist in creating deep learning forecasting machine learning models that can take into account the uncertainties in the various data sources.
Aims
* Develop a suite of deep learning models for statistical extrapolation in presence of imprecision.
* Test their performance on several temporal data instances.
Objectives:
* Provide mathematical insights about the performance of the forecasting models.
* Provide mathematical insights about their use in the presence of imprecision.
Desired qualifications: Excitement about quantitative science, machine learning and coding in Python.
Relevant majors: Mathematics, Computer Engineering, Computer Science, Cybersecurity, Data Science, Environmental Engineering
The project will investigate the use of radar as non-contact technology for evaluating structural vibrations and/or the presence of cracks in structures. The objective is to evaluate the metrological effectiveness of radar, and characterize measurements in terms of resolution, accuracy, and precision.
Desired qualifications: The student should ideally have some experience in coding using Matlab/Python (essential) and in radar systems and structural dynamics (not essential).
Relevant majors: Computer Engineering, Civil Engineering, Mechanical Engineering, Physics
Structural analysis is hard for humans but easy for computers. Today’s computers can handle the solution of large structures thanks to highly vectorised code for the purpose. However, structural analysis is still mostly confined behind counterintuitive and awkward looking WIMP interfaces. The aim of this project is to develop a generative artificial intelligence for structural analysis that will ultimately make structural analysis more accessible to students for self study and professionals for quick prototyping. For example, in order to calculate the deflection of a simply supported beam the user need not use a WIMP interface; the user can just write down the statement in the form of textual or verbal input. We propose the development of an AI tool that can generate structural solution schemes, in the form of diagrams, like bending moment, shear force, etc. and in the form of displacements and rotations. Our structural analysis solution generator could be embedded in a mobile app and used by site engineers or designers under time pressure. Current open AI tools produce very plausible nonsense, which motivates the need for a specialized AI generator for this kind of problem. The generator will input text in plain English and output structural solutions in the form of pictograms and formulas. The text can contain quantitative statements, including approximate ones, units and even hedge words.
Objectives:
Desired qualifications: Excitement about quantitative science, machine learning and coding in Python. Undergraduate knowledge about structural analysis can be an advantage but is not essential.
Relevant majors: Civil Engineering, Mathematics, Computer Engineering, Data Science, Environmental Engineering, Computer Science
Free-living amoeba, including acanthamoeba, reside ubiquitously in freshwater, soil, and sediment. They are most known for human pathogenesis (e.g., granulomatous amebic encephalitis and keratitis). In addition, however, they impact fish and the fishing industry. Very concerning is that acanthamoebae are bacterivorous, and bacteria resistant to digestion become endosymbionts, as such they may harbor potentially pathogenic bacteria: Legionella, Listeria, Pseudomonas, and Mycobacterium.
The project involves samples that have been collected at the Experimental Lakes Area, Ontario, where an ongoing whole-lake experiment is being conducted on the ecological effects of disinfectants in freshwater lakes. This project will not involve the fieldwork (the samples are collected on our behalf and shipped to us). However, you will gain skill and experience in:
1) Molecular techniques: DNA extractions, qPCR, and probably some bioinformatics
2) Bacterial community analyses
3) Amoebae isolations and cultivations
We aim to determine whether exposures to QACs in disinfectants impact the microbiome and amoebae.
Desired qualifications: Understanding of biological systems and laboratory experience.
Relevant majors: Biochemistry, Chemistry
Mechanized mining often uses toxic chemicals such as mercury or cyanide in the final concentration process for mined gold. As a result, these chemicals can find their way into ecosystems and poison wildlife and people directly or by bioaccumulation in the food chain. Using case study hydrochemical and metal species data the environmental impact of toxic processing chemicasl can be assessed.
This project will use a dataset from Colombia to investigate the impact of large-scale mechanized mining on a river catchment within one of the most biodiverse areas of the world. The student will assess the dataset to determine the knock-on effect of mining activity in this area. The aim of the project is to determine the scale of key risks to the river system being exploited
Objectives: (1) Synthesize field collected data from separate surveys and citizen science monitoring program; (2) Assess likely pathways from source (mining) to receptor (people); (3) Perform a risk assessment to rank socio- and environmental risks.
Desired qualifications: Understanding of hydrogeology useful but many backgrounds possible. Enthusiasm and curiosity for the topic are more important.
Relevant majors: Chemistry, Environmental Science, Marine Biology, Geology, Biology
We have a recent hydrochemical and stable isotopic dataset from a set of natural thermal springs in Svalbard, and a comparative set of published results from 25 years ago. What can comparison of these data sets, and associated information, tell us about climate change within the Arctic Circle? Can we use records of such prominent natural landmarks to predict climate impacts?
This project will review the history of these hotsprings and investigate whether this history can tell us anything about what the future has in store for the local environment and all those who depend on it.
Objectives: (1) Synthesize decade-separated geo- and hydrochemical datasets with other relevant measurements (e.g. sea level); (2) Determine and compare trends in chemical parameters; (3) Establish key parameters for assessment of climate change
Desired qualifications: Understanding of hydrogeology and / or geo- or environmental chemistry useful but many backgrounds possible. Enthusiasm and curiosity for the topic are more important.
Relevant majors: Chemistry, Geology, Environmental Engineering, Environmental Science, Geography, Oceanography
Hot Dry Rock geothermal projects have grand ambitions for low carbon power (and increasingly) heat generation largely from stimulated or naturally fractured granites several kilometers beneath ground. Several projects have popped up around the globe, including two recently in Cornwall. But are they any good? Have projects successfully delivered on their initial aims? Or have they been a waste of investment?
This project will explore the practical experiences of HDR projects to date to compare technical, financing and legislative challenges across sites and assess the practical feasibility of such projects in low-carbon energy generation.
Objectives: (1) Perform a systematic literature review; (2) Construct an HDR project database; (3) Analyze database to determine key factors behind the success and / or failure of HDR projects.
Desired qualifications: Understanding of geothermal energy and geology useful but many backgrounds possible. Enthusiasm and curiosity for the topic are more important.
Relevant majors: Geology, Civil Engineering, Chemical Engineering, Chemistry, Computer Science, Data Science, Environmental Engineering, Environmental Science
Strathclyde has a successful and continually growing research program on mine water geothermal and subsurface heat storage. Active (and future) projects involve various activities such as mapping of mine void spaces, heat resource assessment, geophysical investigations, hydrogeological surveys (including sampling & hydrochemistry), and field trials (including pump tests). There will be opportunities for student(s) to support this research program in various ways as work at several sites progresses.
Specific aims and objectives will depend on the focused topic area of the student and the work available at the time of the summer research effort, e.g. linear and 3D geophysical surveys aim to deliver more accurate imaging of flooded voids in the subsurface, integration of mine abandonment plans aim to deliver robust 3D understanding of mine architecture and optimal locations for drilling, hydrochemical investigations aim to deliver advanced understanding of operational risks and sustainability.
Desired qualifications: Understanding of hydrogeology and mining useful but many backgrounds possible. Enthusiasm and curiosity for the topic are more important.
Relevant majors: Geology, Civil Engineering, Chemical Engineering, Chemistry, Geography, Data Science, Environmental Engineering, Environmental Science, Geophysics
What factors are important when it comes to thermal properties of rocks? This project will explore areas such as mineralogy, water saturation, permeability to find out.
To meet net zero we need to enhance our understanding of the resources beneath our feet. Different types of geological reservoir are being explored for e.g., geothermal heat, thermal energy storage, nuclear waste storage, carbon storage, etc. But little is known about site specific thermal properties that control the flow of heat within these systems and temperature changes can have a large impact on a reservoirs intended use.
This project may make use of our new transient plane source thermal analysis kit, and our under development chamber to replicate in situ subsurface conditions during thermal measurements.
Aim: Determine important material properties that control thermal behavior of geological reservoirs
Objectives: (1) Survey literature; (2) Create global database of rock thermal property information; (3) Assess control of factors such as mineralogy, water saturation, permeability on thermal behavior of geological reservoirs
Desired qualifications: Understanding of geology and materials science useful but many backgrounds possible. Enthusiasm and curiosity for the topic are more important.
Relevant majors: Geology, Civil Engineering, Chemical Engineering, Chemistry, Computer Science, Data Science, Environmental Engineering, Environmental Science
The research focuses on the classification of coastal zones in North America based on long-term ocean wind and wave climate data. By analyzing available long-term datasets, e.g., over a period of 60 years, the study aims to identify change in both average and extreme wind and wave conditions along the coasts. The goal is to assess short and long-term variability in these oceanic parameters and classify regions according to their climate characteristics, highlighting areas with the least and greatest variability. This will help detect areas with higher potential for sustainable development.
The primary aim of this project is to classify North America’s coastal regions based on oceanic climate to determine the sustainability of ocean weather along the coastlines. The objectives include:
Desired qualifications: The student should have a background in Environmental Science, Civil or Environmental Engineering, or related fields. Skills in data analysis and basic knowledge of atmospheric and oceanic processes will be helpful. Experience with software such as MATLAB, Python, or similar tools for handling and analyzing large datasets will be highly beneficial. Familiarity with geospatial data and ocean modeling would also be an advantage.
Relevant majors: Civil Engineering, Environmental Engineering, Environmental Science, Data Science, Statistics, Climate Science
This project aims to develop an innovative computational toolbox that integrates advanced mathematical models with artificial intelligence techniques to predict flow characteristics in unsaturated porous media. Despite the availability of existing commercial software, these tools often struggle to balance accuracy and speed, largely due to the complexity of the underlying physics. The current challenges in modeling flow through unsaturated porous media involve non-linear behaviors, variable saturation levels, and complex boundary conditions, all of which slow down the development of quick, reliable solutions. By incorporating deep learning and machine learning algorithms into the model, this project seeks to overcome these challenges.
The project has the following specific objectives: 1) Incorporate physical principles: The model will be designed to include the complex physics of unsaturated soils, integrating theoretical knowledge with AI techniques to ensure the accuracy of the simulation. 2) Optimize prediction speed and accuracy: By combining machine learning with physics-based models, the solution aims to achieve high accuracy while significantly reducing computational time.
Desired qualifications: To successfully contribute to this project, the student should have the following background and skills:
Relevant majors: Civil Engineering, Geotechnical Engineering, Data Science
Scour, the erosion of soil around retaining structures, threatens the stability of gravity retaining walls, which rely on their weight for resistance. This project aims to address the challenge of accurately predicting scour’s impact by using numerical modeling techniques. The commercial software FLAC2D will simulate the interaction between soil, water flow, and retaining structures, providing insights into how scour affects wall stability. By comparing scoured and intact walls, the study will enhance the understanding of erosion mechanisms and inform the design of more resilient retaining walls, improving infrastructure safety and longevity.
The project’s specific objectives include:
Desired qualifications: The ideal candidate for this project should have a foundational understanding of geotechnical design principles, particularly with respect to retaining wall construction and stability analysis. The student should be comfortable working with soil mechanics and be familiar with basic engineering concepts relevant to structural stability and erosion.
Relevant majors: Civil Engineering, Geotechnical Engineering
The dynamic stiffness of foundations is crucial for analyzing soil-structure interactions, especially under dynamic loads like earthquakes or vibrations. Anisotropic and non-homogeneous soils, which vary in properties like stiffness and permeability across different directions, significantly affect foundation performance. This project aims to determine the dynamic impedance of shallow and deep foundations in anisotropic soils using analytical methods in geomechanics. By understanding how soil anisotropy influences dynamic stiffness, the research will enhance the accuracy of soil-structure interaction models, aiding in the design and analysis of foundations for critical infrastructure.
The specific objectives include:
Desired qualifications: To contribute effectively to this project, the student should have:
Relevant majors: Civil Engineering, Geotechnical Engineering