Innovative Projects Realized

Deep learning-based steel corrosion and fatigue crack detection using a depth camera

In order to overcome the drawbacks of the traditional approaches to steel structure damage detection and to improve reliability and safety of existing steel structures, this research proposes to develop an innovative autonomous SHM system that offers transformative enhancements over existing steel structure monitoring systems.
This will involve:
1. Collecting
Collecting image data from various steel corrosion and cracks to establish databank to train a deep faster region-based convolutional neural network.
2. Developing Algorithm
Developing a deep faster R-CNN-based steel damage detection system using a 3-dimensional depth camera that is able to provide first warnings of structural damage by localizing and quantifying damage.
3. Application
Developing an automated system to apply this research o real-world problems.
We will install a web camera on a steel bridge to providing monitoring in real-time using a wireless system that will transfer the image data to a base workstation.

Numerical study of load carrying capacity of offshore mooring piles in sand

Pile foundations have been widely used in many offshore structures and oil and gas development

programs such as tension leg platfonn, jack up platfonn, spar platfonn, and mooring of floating

production, storage and offloading (FPSO) units. The FPSO units are usually moored to the seabed

with various kinds of anchors, including offshore piles. These piles are subjected to inclined upward

load from FPSO. The objective of this research is to develop advanced method to estimate load

carrying capacity of offshore mooring piles in sand subjected to inclined loading. The proposed

research is a part of intern’s M.Eng. research at Memorial University. The partner organization will get

advanced tools for modeling soiVstructure interaction, which will be useful for offshore oil and gas

development projects.

Defining the role of gut microbiota in intestinal stem cell development and inflammation

Neonatal necrotizing enterocolitis (NEC) is one of the most common and deadly disorders of the gastrointestinal tract in preterm infants, accounting for the second highest percentage of neonatal deaths. Although the underlying disease mechanisms are still unclear, the increased incidence of NEC has been associated with excessive antibiotic use during pregnancy. Newborns become exposed to gut microbiota, which coincides with intestinal stem cells (iSCs) differentiation into paneth cells (PCs), a critical cell type controlling immune response. Therefore, we hypothesize that exposure to normal gut microbiota is essential for iSCs differentiation into PCs, thereby preventing NEC. Cellular differentiation involves the dynamic chromatin alterations to direct lineage-specific gene expression patterns. We will define the role of gut microbiota in establishing PCs-specific chromatin structures and regulators by analyzing chromatin and gene expression patterns in mice treated with antibiotics.TO BE CON’T

Efficient harvesting of solar energy: plasmon enhanced upconversion for organic photovoltaics

In a conventional solar cell, over half of the incident sunlight goes to waste, due to failure by the stable semiconductors to absorb the lower energy ranges of the solar spectrum. Attempts to improve the semiconductor absorption capabilities have proved difficult, with relatively little progress made thus far.
An alternative solution is to make the most of existing semiconductor materials by tuning the incident sunlight into more easily absorbed frequencies. The ‘upconversion’ materials used in this technique, which convert the lower frequency light into higher frequency light, have great potential to increase the efficiency of solar cell technology. However, the conversion efficiency of the upconversion technique is currently too low (~1%) to provide substantial improvement.
This project aims to combine the ‘plasmon enhancement effect’, which amplifies local electric and magnetic fields, with upconversion in order to enhance both the absorption and the emission of light. TO BE CONT’D

A case study on the business impact of personalized shopping experience on retail stores

This research will determine what factors are the most significant when it comes to the personalized shopping experience from the perspective of both customers and retailers, and shed light on opportunities and options for North American retailers to innovate within the retail space. We will conduct surveys with both retailers and customers to determine the level of value that each cohort places on the various factors and data points that can improve the personalized shopping experience. Three pilot-studies will be conducted in retailers stores in which new data to provide personalized shopping experiences will be provided to retailers through the addition of a sensor that tracks customer behaviours, and through the collection of POS data to show previous purchasing patterns. We will survey these retailers at the end of the 45-day pilot-studies to uncover how retailers might use this additional data to provide a personalized shopping experience, what factors or data points they found most helpful, and what areas of opportunity they believe exist in the retail landscape in North America. The results of this study will help inform future innovations from RetailDeep in its mission to provide customer-based data to retailers that will support the personalized shopping experience.

Monitoring and Visualization of Air Pollutions on Construction Sites

Construction industry is considered as one of the major air pollutant emissions sources, such as NOx, PM, COx, SOx and so on. Those air pollutants are detrimental to the ambient air quality, and they can cause immediate and serious damage to the workers’ health. However, in current practices, the potential impacts are significantly underestimated and neglected. Therefore, this study is to create an affordable and portable IoT (Internet of Things)-based air pollution monitoring system with the low-cost microcontrollers and sensors to measure the air pollutants in an automated and real-time manner. With such system, construction professionals can assess the environmental impacts of the ongoing construction operations and track what pollutants the workforces are exposed to and take actions to protect workers from harms in a timely manner. Also, the proposed system can be extended to monitor other industry with the disturbing issue of air pollutions.

Aircraft sensors fusion algorithms optimisation

This project is to study the sensors (e.g., accelerometers, gyros, magnetometers) which used to measure the flight control system. These sensors are usually are effecting with bias, drift and noise effects. Therefore, the use of sensors fusion algorithms is key to estimate accurately measured and filtered values and to ensure the correct behavior of the flight controller. These algorithms (EKF,Mahony and Madgwick) and proper sensors models (with bias, noise, etc…) have already been
implemented in Matlab and C++ and tested on aircraft scenarios.

In the second step of this study, the new algorithms/features might be implemented and integrated such as Unscented Kalman Fiter (UKF) or Least Square Methods (LSM). These new approaches will have to be compared to the previous results.

Study of Corner Brook Pulp and Paper Limited (CBPPL) byproducts and potential uses for food production

Overall this study aims to determine feasibility, parameters, and processes related to improved utilization of selected byproducts resulting from Corner Brook Pulp and Paper Limited (CBPPL) operations. The proposed activities and ideas relate to monitoring and understanding the nature of the composition of the mill’s production of wood ash over time, determining the suitability, feasibility of improving mill competitiveness through alternate/improved processing of ash, sludge and waste heat. The combined possibility of more environmentally sustainable processing, potential reduction of current expenses, and potential creation of new revenue streams all provide opportunities to increase competitiveness for members of the industry.

Research on Architecture Systems

The aim of the project is to contribute to reshaping conceptual design by incorporating state-of-the-art design theories and model-based systems engineering. Concept design is the first phase of the design process, the time needed to make basic decisions that set the specifications for a proposed artifact and begin to determine its ultimate shape. To better support this first phase of design, the use of model-based systems engineering is studied. The proposed project will contribute to these research efforts by contributing to the model itself, its use, applied to aircraft concept design, and its integration into the model and the process. The project will include, but is not limited to:
• Research on (formal) design theory
• Research on the integration into systems engineering approaches
• What indicators can be used to best support the design approach
• Modeling the approach.
The project will start with the follow?up of the literature study already started by the ISAE?SUPAERO M1?student, followed by an extension of the modeling work that he started. This modeling takes place in SysML (essentially) and in OPM.

Two-phase measurement of the flow around multi-droplet array on various functional surfaces and its modeling

The objectives of the proposed research internship is to develop a model of the critical airflow velocity at which the droplets start to move according to the arrangement of the droplets, the wettability of the surface, and the interaction between the droplets on the various functional surfaces and the airflow passing over them, which is further followed by the experimental validation. It is very important to understand and control the thermal fluid phenomena of the system, especially two-phase flow phenomena, in order to maintain its stability or improve the performance in various industrial problems. In particular, it is often necessary to efficiently remove droplets that are unnecessarily present on a solid surface, however in-depth studies have not been conducted so far. TO BE CONT’D

Analysis of a Model for Shipping Grains from Summerside (PEI) to Corner Brook (NL)

Corner Brook Port Corporation (CBPC) and the Summerside Port Corporation, Inc. (SPCI) are exploring the opportunity to ship grains from Prince Edward Island to Western Newfoundland. First discussions between the two ports indicate that there this may be a viable business opportunity for both entities. The Port of Summerside is currently shipping grains from producers on the island outbound in bulk. Meanwhile, there are a number farms, particularly dairy farms, in Western Newfoundland located close to the Port of Corner Brook. The ability to ship grains by vessel directly to Corner Brook could reduce costs and shipping times, and could mean access to fresher products and possibly a wider range of grain and related products. CBPC and SPCI require further research to move forward with this project.

Mobile Beacon-based Localization with Motion Compensation for Underwater Acoustic Sensor Networks

The aim of this project is to propose an improved mobile-based localization scheme by considering a practical factor (i.e., ship-motion) in Underwater Acoustic Sensor Networks (UASNs).
In the last decade, localization techniques associated with UASNs have been widely studied as a method to provide fundamental support for many location-based applications. In particular, mobile beacon-based localization schemes (e.g., usage of ship or AUV) have been proposed as a more promising method than static anchor-based localization in terms of energy efficiency. Further, the mobile beacon-based schemes have similar effects (i.e., accuracy) as the use of many static anchors. TO BE CONT’D