Innovative Projects Realized

Plastics Packaging Materials with Antifungal/microbial Properties

Plastic packaging materials are needed in many food products to prevent spoilage and to extend shelf-life. This project focuses on developing plastic packaging materials that will not permit bacteria and fungi to grow on the surface of the plastic in contact with the food , bread in this particular case. Besides the obvious performance requirement of incorporating a barrier against fungal/bacterial growth, the packaging solution must also satisfy the following criteria: i) it must not affect the taste, texture of the bread, ii) the additive must be "natural" and not contain preservatives such as calcium propionate which compromises the healthy connotation of the particular product line of bread, iii) the optical and mechanical properties of the packaging fi lm must not be compromised, iv) the solution must be industrially amenable to existing plastic processing techniques and v) not have any negative environmental impact upon disposal.

Condition Assessment of Concrete Bridges using GPR Technology

Bridge Management Systems (BMSs) are being used worldwide by transportation agencies as a means to effectively manage the stocks of existing bridges. Quebec Ministry of Transportation (MTQ) own and maintain a huge inventory of over 9,600 bridges, i.e. provincial: 5,300 and municipal: 4,300 bridges. MTQ uses visual inspection, which is always subjective to operators’ technique, experience, and interpretation, to record defects on bridges and assess their conditions. Although visual inspection can find most of the external flaws; however, it cannot detect internal defects in structures. Many efforts have been made to solve such problems using non-destructive evaluation (NDE) technologies, which is still rather limited. In addition, most of the developed techniques focused on condition rating of bridge decks neglecting to include the other bridge elements. Therefore, the main objective of this research is to develop a condition assessment system for concrete bridges based upon the inspection outputs of Ground Penetrating Radar (GPR) as a NDE technology. The proposed research will make bridges safer to the society and environment by developing innovative/GPR-based bridge condition assessment model(s) and tool(s), which facilitate the role of decision makers in assessing the status of bridge decks and deciding on the most appropriate method to rehabilitate or replace decks.

Building Equity and Inclusion through the Arts

Teaching through the arts has often been heralded as an effective way to engage marginalized students. As such, it would seem that an arts-infused approach to learning may promote equity and inclusion in schools. This research project endeavours to engage students as co-researchers to investigate how exactly the arts and creativity allow moments of equity to arise in the classroom. To achieve this overarching objective, the intern will develop a pre- and post- equity consciousness assessment tool for students, as well as a documentation strategy for students to capture and reflect on moments of equity that arise during their participation in an ArtsSmarts project. These tools will advance the research agenda of ArtsSmarts Waterloo Region and also support the work of Overlap Associates in fostering innovation by building inclusive contexts for collaboration.

Impact modeling of composite aircraft structure

Composite structures are vulnerable to impact damage, and have to satisfy certification procedures for high velocity impact from bird strike and foreign object damage. Since performing full scale impact tests is highly expensive and thus impractical, the development of validated analytical tools for the prediction of the structural response is essential for the industry to reduce development costs and to speed up the development process. Today, the capabilities for modeling the initial and progressive failure of composite materials has not been thoroughly evaluated or validated for commercial finite elements codes. Thus, accurate modeling of the impact response and failure of composite airframe structures subjected to impact and crash conditions still remains a challenging problem. Despite of the existence of a large body of literature on progressive damage analysis in composites, our understanding of the fundamental failure mechanisms and behaviour of composites is not yet complete. This largely stems from the complex multiscale and interactive nature of damage in composites.

Human Health Risk Assessment of Manganese and Inorganic Manganese Compounds and the Application of Categorical Regression in the Quantitative Risk Assessment of Manganese

Risk Sciences International is currently completing a comprehensive risk assessment of the potential human health effects of manganese. This assessment involves a systematic review of the worlds’ literature on epidemiological and toxicological studies of manganese, following which an international expert panel has scored all of the adverse health outcomes identified through this review using a 12-point severity scoring scale. By standardizing diverse health outcomes on a common severity scale it is now possible to conduct a categorical regression analysis of the results of over 200 scientific papers containing relevant dose-response information on manganese. During the course of this MITACS internship, Ms. Milton will assist Senior Scientists at RSI in conducting the detailed categorical regression of this unique comprehensive database on the human health effects of exposure to manganese.

Improving user experience with a social gaming platform: Identifying and adapting to significant user traits and behaviors

This project will involve using statistical modeling and machine learning techniques in order to identify significant factors that exist in user interaction logs collected from a social gaming system. Next, these factors will be used to inform, implement, and test an adaptive platform for managing and improving behaviors that relate to user experience and/or user retention.

Computer Algebra and High-Performance Computing Support for Model Predictive ControlComputer Algebra and High-Performance Computing Support for Model Predictive Control

In many industrial and engineering applications, process control plays a central role. Among the possible control strategies, model predictive control (MPC), also called receding horizon control (RHC), stands out for its excellent ability to handle constraints. While MPC has been successfully applied to many industrial applications, further developments are limited when it becomes necessary to solve many large on-line optimization problems. To overcome this situation, parametric optimization is often used such that most of the computation burden is pushed to an off-line phase. In this project, we propose to develop algorithms and software tools based on symbolic computation, to perform parametric optimization together with the corresponding on-line procedures, targeting MPC in the case of polynomial constraints and polynomial objective function. The proposed research will bring together the latest advances in computational real algebraic geometry and high-performance computing techniques. Our goal is to generate application driven packages for MAPLE, the flagship product of our industrial partner. In particular, the deployed infrastructure will be used to support another application relying on an off-line on-line strategy, namely code generation of parallel programs. Not only will this allow us to capitalize on the effort invested to support MPC via symbolic parametric optimization, but it will also serve as a development tool in this project by generating portable and efficient parallel code in support of our MPC solvers.

Identification of Power System Security Region using PMUs

Maintaining power system security is one of the major challenges facing transmission system operators today. In fast moving and de-regulated electricity markets, transmission companies across the globe often have a dual and conflicting responsibility for maintaining system security and for achieving high transmission performance levels.

The power system security is a complex function of many variables including network connectivity, load and generation pattern, and contingencies that may occur. There are a number of analytical engines such as powerflow, transient stability, voltage stability, etc., that are continually being used toperform simulations at the control centers of utilities to determine safe operating region in normal and under contingency states. Even though some of these analytics are being used in an on-line (nearly real-time) environment, the need for faster and more accurate techniques has been an importantsource of inspiration for many researchers worldwide.

In this research project the team will develop a framework to identify the security region of a power system using the phasor measurement units and data mining technique. The framework can be used in an on-line application to track system security from the real-time measurements of voltage magnitude and angle obtained from PMUs. This research project once completed will benefit utilities in several ways including operating the power system close to its stability limits, maximizing the power transfer capability limits to/from a power system, and better preparedness to undertake preventive and corrective actions. The developed technique and framework will be tested on a few realistic power systems including the power system of BC Hydro.

Novel Boundary Element Method for Inductance Extraction in Cables of Complex Cross-Sections

The proposed project is dedicated to fast resistance and inductance extraction for multiconductor transmission lines. Since the complexity of power cable designs has grown significantly over the past decade, fast and accurate tools for electromagnetic characterization are required. The cable models presently used by Manitoba Hydro however are overly simplified compared to the ones available on the market. The alternative surface-volume-surface integral equation formulation is proposed to reduce computational time and memory. During this project the Method of Moments solver based on the novel formulation will be accelerated via hierarchical matrices and/or adaptive cross approximation. This resistance and inductance extractor will be integrated in PSCAD software currently developed by Manitoba Hydro.

Investigate machine learning algorithms to detect anomalies in computing infrastructures in real-time

The industry partner, Metafor is developing a new class of IT system management solution. As part of this project, Metafor is building a product feature that monitors computer and network activities and looks for signs of anomalies. This is an important problem as anomalies are usually associated with abnormal user or system behaviors that can potentially result in problems such as system breakdown. As the properties of anomalies and normal behaviours are stochastic and dynamic by nature, efficient and intelligent signal processing and machine learning algorithms are required to detect these anomalies. In this project, the intern will do a comprehensive survey on the state-of-the art of real-time anomaly detection; investigate a set of system indicators or features as well as machine learning algorithms that can potentially be useful in detecting anomalies. Finally, the intern will implement suitable algorithms to predict the presence of anomalies in the system in real time.

The effects of stress during white sturgeon early life history on larval physiology, development and olfactory sensitivity

Elevated levels of stress hormones (i.e. cortisol) provide a potential mechanism by which substrate condition affects larval development and survival in the endangered white sturgeon. The possibility that stress hormones mediate larval response to substrate conditions will be investigated by artificially elevating cortisol levels and identifying effects on larval physiology. Cortisol levels of wild caught adult fish will also be investigated to determine the effects of capture and handling on spawning success and larval quality. Two final projects will investigate whether substrate condition (habitat stress) affects larval olfactory development and/or thyroid hormone levels. Both of these factors may be linked to the mechanism of imprinting by which fish return to their birthplace to spawn (e.g. salmon). A better understanding of factors affecting larval survival and quality will help both project partners implement both hatchery and habitat based components of the species recovery plan.

4D modeling of potential fields at active volcanic systems

Explosive silica-rich volcanic eruptions pose a major, recurring threat to Earth’s surface environment; these eruptions can immediately deposit up to several hundred cubic kilometers of volcanic ash over hundreds to millions of square kilometers, posing a societal hazard at the scale of an entire continent. It is therefore essential that we collect comprehensive data and develop 4D models (3D through time) that realistically account for the dynamics that lead to these destructive events. This requires that we understand the precursory magma dynamics on both long (years to millennia), and short (months to weeks) human time scales. The PhD student will make annual field campaigns to Chile and New Zealand to collect potential field (gravity, magnetic and electrical) data; this will subsequently be analyzed and modeled in conjunction with a range of other complimentary data. Using an extraordinarily wide range of non-proprietary data, this research partnership will allow for the cross-calibration and optimization of commercial modeling code that will benefit both academia and industry.