Autonomous structure detection and inspection using unmanned aerial systems

In this project, a new method is developed to optimize the performance of an Unmanned Aerial Vehicle (UAV) for autonomous detection and on-the-job view-planning of infrastructure elements with the purpose of their accurate three-dimensional (3D) modeling. The existing view-planning approaches in the literature have mostly modeled non-complex or small-scale objects and have rarely been adapted to flying robots. In addition, the target object is often identified by human operators.

CO2-EOR in Devonian Reefs of Alberta: Reservoir Characterization and Screening

Devonian reservoirs have contributed significantly to the development of the petroleum industry in Alberta. This is mainly due to their favourable characteristics of high permeability enhanced by dolomitization in these often reefal structures. Although many have had good recoveries, much oil remains to be recovered. Many of the same characteristics that led to good production performance during the past decades are expected to contribute to good production potential if CO2-based enhanced-oil recovery (CO2-EOR) methods are employed.

Mobilizing Ulukhaktok Traditional Knowledge of the Dolphin and Union Caribou Herd

The Dolphin and Union caribou herd is integral to Inuit culture, subsistence and identity. Preliminary local and scientific knowledge both indicate that this caribou herd is declining and in poorer health than before. We need to bring everyone together and use everything we know about Dolphin and Union caribou, the environment and the other animals to help protect and care for these animals.

Oil price prediction using dynamic multiresolution modeling

In this project, we will explore novel modeling methods to predict oil prices, based on a combination of machine learning methods with dynamic multiresolution analysis. The objective is to develop a software to better forecast oil prices. Oil is the world’s leading fuel, and its prices have a big impact on the global environment, the economy as well as oil exploration and exploitation activities. Oil price forecasts are very useful to relevant industries, governments, and many individuals. Many methods have been developed for predicting oil prices.

Leveraging micro-sensors for minimally invasive neuromodulation device

More than 1/3 of people will be affected by a neurological condition in their lifetime. Seeking effective treatments for various brain ailments is paramount to a healthy and prosperous society. Both the quality of life and the economic impact of brain disorders is staggering, costing our healthcare systems billions of dollars annually. Unfortunately, most patients impacted by brain-related ailments can only be managed either pharmacologically or surgically; both approaches however fail to resolve the underlying neurological problems, which is likely to exacerbate as our population ages.

Enhanced Techniques for History Matching and Forecasting of Petroleum Reservoir Data - Year Two

History matching refers to calibrating numerical or analytical models by the observed data. However, this task can be very challenging in presence of complex geology and/or many unknown data .
The purpose of this project is to introduce and apply the new techniques for efficient creation of predictive history-matched models for reservoir characterization of conventional and unconventional reservoirs, which can be used for probabilistic forecast and uncertainty quantification.

CardiAI Point-of-Care Device for High-Caliber and Rapid Diagnosis of Biomarkers from Blood of Patients for Early Heart Failure Detection

The aim of this research and development project is to design and develop a bedside point-of-care device to be equipped with the CardiAI’s machine learning technology for heart failure management. Our POC system will include disposable cardiac biomarker strips and an electronic reader.

Mathematical modelling of Reversible Solid Oxide Fuel Cells (RSOFCs) for the conversion of CO2 and H2O to syngas

SeeO2 energy and the Birss group (UCalgary) have developed world-leading catalysts for RSOFC systems with promising performance for the production of syngas and power from H2O/CO2 feeds. Today, the company is aiming to scale-up this technology and move towards commercialization by building larger cells, up to 5 x 5 cm2 (16 cm2 electrode area). However, the process of scaling-up RSOFCs presents many challenges in understanding the effects of fabrication and operation parameters on the cell performance at larger scale.

Pipe Acoustical Characterization of Packaged Screw Compressors

The gas processing industry is fielding screw compressors of increasingly larger size. These machines are usually packaged together with process piping and equipment by several local packaging companies that regularly hire consultants (such as AP Dynamics) to conduct design reviews geared to mitigate potential issues with pulsations and mechanical vibrations.

Ultrasound Device for Superficial Targets

This project intents to design and build a prototype for a device that uses low-intensity ultrasound for localized treatment of malignant skin cells. The industrial partner is interested on evaluate the performance of a current cosmetic device and the feasibility to use a device with similar characteristics to treat malignancy. We propose to first characterize this existing device to determine the conditions of operation, then evaluate the biological effects that are expected for those conditions.

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