Innovative Projects Realized

Prototyping and Characterization of TLC Photovoltaics

Solar panel cost has decreased dramatically over the year, but to fully displace fossil fuels from the power sector panels must further decrease in cost, and must increase in efficiency and durability.
TLC is a novel solar panel design that combines high efficiency, high durability and low cost. TLC uses three very-low-cost optical stages to concentrate up to 1500x onto array of ultra-efficient tandem microcells. Detailed optical, thermal, mechanical, electrical and cost studies show that TLC has exceptional promise – with today’s tandem cells, module efficiency should be twice that of typical silicon solar panels, cost per Watt should be roughly half that of silicon panels, and well-cooled tandem cells in a hermetically sealed module should provide a 50-year life.
This Mitacs project will build the first TLC prototype and characterize its performance on-sun.

Flaw Growth Thresholds in Composites

A new generation of composites-intensive aircraft designs promises to

dramatically accelerate the growth of a market currently valued at more than $7 billion (USD).

The objective of this research program is to propose experimental and modeling

methodologies to determine endurance limit for damage onset in composite based on

fracture mechanics and fatigue crack initiation monitoring using wave mode propagation

based on Modal Acoustic Emission new approaches (MAE). Through an analysis of the

guided wave mode propagation and signal contents, the approach will be developed to

determine the endurance limit related to the onset of delamination and cracks initiation in composite materials, as function of cyclic loading and environmental conditions related to

temperature and humidity. Analytical and numerical modeling tools will be performed to

predict delamination onset and growth. Crack propagation of the starting delamination will be

modeled by the Virtual Crack Closure Technique and Cohesive Zone method. Experimental

procedures and analytical model will be proposed to determine composite stiffness loss….TOBECONTINUED

Goal-oriented Safety-Guided Design and Assurance for FinTech

With the increasing popularity of digital assets such as cryptocurrencies, many financial technology (FinTech) systems have become safety critical. However, current FinTech system development approaches often lack the rigorous safety practices found in the aerospace, nuclear, automotive, and military industries. To address safety concerns of FinTech stakeholders (users, but also regulators and financial institutions), this project aims to support FinTech system development with safety-guided design principles, with goals elicited from stakeholders and results clearly communicated to them using appropriate models. The intern will use and adapt standard requirements engineering modelling notations, hazard causation theory, and assurance cases to develop safety-guided design principles. This will be done through a digital asset management case study of value to and provided by the partner organization. This will help the partner organization to more rigorously assess and demonstrate to other stakeholders the safety of its FinTech solutions.

An Automatic Tool for Developing Transactive Energy Smart-Contracts: Development, Validation and Integration with the IEMS Blockchain Platform

Energy consumers and prosumers are currently dealing with each other via utility companies, which is a slow, costly and indirect mechanism. With the aim of moving toward a free market, the goal of this project is to provide a suitable platform for automatic development and evolution of smart contracts in distributed transactive energy markets. This platform will make the blockchain technology, underlying smart contracts, applicable to direct transactions between energy consumers and prosumers, enabling additional steps towards a free market. This platform and its smart contract tools will build on the IEMS blockchain and IBM’s Hyperledger platforms, hosted by The Linux Foundation. The resulting platform and tools will help the energy market developers, including IEMS, to develop, edit and apply smart contracts following changes in market policies.

W?SÁNE? Law and Governance: Marine and Terrestrial Management in the Southern Gulf Islands

The proposed research project will explore the question: How can existing mechanisms (National Marine Conservation Area Reserve (NMCAR), Indigenous Protected and Conserved Areas (IPCA), and Management Agreements with Parks Canada in the Southern Gulf Islands (GINPR)) be used to uphold Indigenous W?SÁNE? laws, governance structures, values, and responsibilities within W?SÁNE? territory? Exploring the benefits, limits, and processes for funding, establishment, and enforcement of these mechanisms will help the W?SÁNE? Leadership Council make informed decisions regarding the feasibility and potential negotiation of these agreements within W?SÁNE? territory. Importantly, the research will also help the W?SÁNE? Leadership Council asses how these processes might help further objectives of environmental stewardship and care within W?SÁNE? territory, as informed by W?SÁNE? laws, values, and worldview.

Investigating multi-task learning in semantic parsing

Current research in semantic parsing suffers from lack of annotated data, which is hard to acquire. In this project, we aim at tackling the problem of converting natural language utterances to SQL language (Text-to-SQL) on complex databases in a low-resource environment. More specifically, we focus on the research of how multi-task learning (MTL) can help in this task. We will first identify the related natural language processing (NLP) tasks that can contribute to improving the performance of semantic parsing. Additionally, we will explore the methods of bridging multiple NLP tasks, and justify by empirical results what are the better methods for knowledge transferring. We want to push the state-of-the-art on the existing benchmarks on semantic parsing, and eventually, we hope this project could result in a successful product. The product will then help RBC reduce the analysts’ workload so that they can provide better services. Furthermore, the potential publications in this domain would also contribute to the overall research leadership that Canada maintains in AI.

Climate volatility and its impact on baseline trends, natural variability, productivity, and disaster potential in the Canadian ecozones

This project is designed to assess both natural variability and the future change of forest productivity and natural disaster risks that are related to climate. These areas are important to study as climatic change is projected to impact northern latitudes more strongly and disasters, such as floods, droughts, and fires, are predicted to increasingly impact human populations and infrastructure. To assess these components, a combination of satellite remote sensing, in-situ and UAV data will be utilized in conjunction with large ensemble modelling.

Analysis of the cryptocurrency market microstructure: role of smart order routing

Over the recent years, cryptocurrencies have attracted tremendous amount of attention from both general public and professional investors as a new asset class. However, trading activities of cryptocurrencies are extremely fragmented and unregulated in most of countries around the world. The proposed research project aims to empirically study the microstructure of cryptocurrency exchanges in order to gain insight on what elements are needed to improve the market. In particular, the proposed research focuses on the potential role of smart order router (SOR). The proposed research project will work with CLTS, a Canadian start-up company working on building a platform to aggregate the fragmented cryptocurrency market for investors. The project focuses on potential improvements in market quality (e.g., depth, costs, liquidity, price discovery) that such an aggregation platform can bring into the current fragmented market. Overall, the proposed project aims to shed light on the role of smart order routing in both the market quality and regulatory perspective.

Development and evaluation of semi-passive biological water treatment processes for water impacted by resource extraction

One of the most vital challenges within the mining and oil sands industries is management of water impacted by resource extraction. Semi-passive biological treatment systems (PTSs) treat water close to the source of contamination and often prevent contamination from occurring in the first place, making them suitable options for management of water impacted by resource extraction. These biological treatment systems require minimal or no chemicals and energy input and minimal ongoing management and care. Therefore, semi-passive biological treatment systems are ideal for closure scenarios. However, current biological piloting-scale testing systems pose a great challenge for full-scale design of semi-passive biological treatment systems as the lack the ability to effectively operate on-site and incorporate multiple treatment steps.

Maven Water and Environment (Maven) is developing a modular biological piloting system technology (WaterMaven system) that can mitigate the existing challenges associated with current PTS piloting strategies and allow for integration of multiple treatment technologies. This research will be involved in the development and beta testing of the WaterMaven technology for treatment of impacted by the mining and oil sands industries.

Molecular signatures and predictive biomarkers for phenotyping allergic rhinitis responses

Allergic rhinitis (AR) is in inflammatory disease characterized by nasal symptoms. It affects 20-25% of Canadians and is recognized as the most common allergic disorder worldwide. Patients can experience one of several types of responses to allergen onset hence a key hurdle to developing effective treatment plans is accurate diagnosis. The allergic responses are characterized by an early response, with a subsequent late response in a subgroup of patients. Based on severity of nasal symptoms, patients can be stratified as early responders, protracted early responders or dual responders. Presently there is limited knowledge of the mechanisms underscoring the observed heterogeneity in allergic responses. This project will address this limitation by aiming to differentiate the types of AR using molecular differences in blood. This work will help lead to the development of diagnostic tools hence improving diagnosis and management of AR, furthering the mandates of our partner organization – PROOF Centre for Excellence.

Identification of a constitutive material model for an aircraft engine abradable rub strip material

This research project between the University of Windsor and Pratt & Whitney Canada (P&WC) is focused on a porous composite material used by aircraft engine manufacturers in the design of fancases of turbofan engines. The objective of the project is two-fold and includes 1) experimentally investigating the behavior of the composite material at different loading conditions; and 2) identifying a model that can be used to represent this material in fan blade-off simulations. A major benefit to P&WC from having this material model will be increased accuracy of their full-engine numerical models in predicting the outcomes of fan blade-off events. Potentially, this will enable minimizing the number of physical tests required for new engines certification, thus providing multimillion-dollar cost avoidance and decreasing engine development costs and lead-time, allowing P&WC to be more competitive in the global market and deploy new products much faster.

Parallelization of an Industrial Optimization Application

Acculogic develops state-of-the-art testers for short-batch electronic circuit boards (ECBs). The order

in which the required tests are performed affects the amount of shuttle and probe movements required

between the tests, and this affects the overall efficiency of the test procedure. Unique characteristics of

the problem (e.g. the ability to move one set of probes to the next test location while another set of

probes is performing a test) make the problem too large and too complex to be solved with most

traditional combinatorial optimization and heuristic search techniques (e.g. integer programming and

genetic algorithms). Supporting the integration of both artificial intelligence-based and mathematicalbased

optimization techniques, a unique optimization architecture derived from “Asynchronous

Teams” has been developed. A parallel implementation of the new optimization process promises

significant improvements in efficiency and effectiveness, and these advances will be quickly

implemented into Acculogic’s product offerings.