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Thermal Characterization of Honeycomb and Foam Core Sandwich Structures: Experiment and Modelling
Get PDFThe thermal characterization of honeycomb and foam-cored sandwich panels is studied by both experimental (guarded hot plate apparatus, and transient laser flash technique), and theoretical (Swann Pittman model, modified Gebhart factor model, and composite theory) means to analyze and modify their thermophysical properties. The fabric’s structural attributes and their effects on the thermal conductivity of the Glass Fiber Reinforced Plastic GFRP facesheets were studied by metallographic techniques, polynomial curve fitting of the longitudinal fibers, Procrustes analysis and subsequent modelling in TexGen and ABAQUS.
The sandwich panels were dismantled into their constituent parts i.e., facesheets and cores and then the graphite & gold coated samples were subjected to transient laser flash thermal analysis technique and guarded hot plate apparatus per the ASTM E1461, ASTM C177 and ASTM C1058 standards. Though thermal diffusivity is not applicable to heterogeneous GFRPs, good accordance between analytical solution for homogeneous material and experimental results for composites allowed us to calculate the “effective thermal diffusivity”. These results were then utilized in the composite theory to compute the overall thermal conductivity of the sandwich panels. With regards to other theoretical approaches, the thermal emissivity values of the facesheet and core were measured by emissivity compensation in FLIR thermal camera.
The epoxy mounted metallographic samples were subjected to dark field, DIC, bright field, and polarized microscopy to extract various attributes of the fibers that are obscured in all the techniques but one. To enhance the contrast between the glass fibers and the polypropylene matrix, dark field microscopy was utilized but this technique is not of much help in studying the fibers from an angle orthogonal to the weave plane of the fabric which polarized light technique had to be used. In addition, the effect of the fiber volume and void fraction was studied for single- and multi-ply GFRP facesheets using thermogravimetric analysis, fiber length distribution analysis and image segmentation techniques. Finally, the modelled facesheets, with their crimp angle, wavelength, and width to height ratio, and the cores (both foam and honeycomb cores) are subject to thermal analysis. The change in the physical attributes of the facesheets and their effect on the thermal conductivity were studied. Good agreement between the model and experiment was observed
Optimal integration of compressed air energy storage system for off-grid communities
Get PDFThe integration of compressed air energy storage (CAES) and wind energy offers an attractive energy solution for remote areas with limited access to reliable and affordable energy sources. This thesis presents a design approach for an energy system comprising wind turbines, CAES, and diesel generators to satisfy the electricity demand in remote communities. This thesis proposes a bi-level programming (BLP) approach enabling the simultaneous optimization of the size and operation of the system while considering the interaction between them. Detailed mechanical design and configuration of the CAES system are considered, including the number and size of compressors and turbines, valves, recuperator operating conditions, etc. In contrast with conventional CAES systems, operating once a day for peak shaving, the proposed CAES system aims to mitigate wind fluctuations. Therefore, its operation is different from conventional CAES systems, and it would operate under partial load conditions most of the time, and as a result, the system's off-design modeling is also considered. The findings of this thesis indicate that the proposed system is a promising, cost-effective, reliable energy solution for remote areas, significantly decreasing the average daily total cost and CO2 emissions by 69% and 76%, respectively. Additionally, by studying the system's performance under both design and off-design conditions, it is concluded that considering the off-design conditions is critical to ensure a more realistic performance of the system as the system is less likely to utilize the CAES in low charging and discharging opportunities
Enhancing Text Annotation with Few-shot and Active Learning: A Comprehensive Study and Tool Development
Get PDFThe exponential growth of digital communication channels such as social media and messaging platforms has resulted in an unprecedented influx of unstructured text data, thereby underscoring the need for Natural Language Processing (NLP) techniques. NLP-based techniques play a pivotal role in the analysis and comprehension of human language, facilitating the processing of unstructured text data, and allowing tasks like sentiment analysis, entity recognition, and text classification. NLP-driven applications are made possible due to the advancements in deep learning models. However, deep learning models require a large amount of labeled data for training, thereby making labeled data an indispensable component of these models. Retrieving labeled data can be a major challenge as the task of annotating large amounts of data is laborious and error-prone. Often, professional experts are hired for task-specific data annotation, which can be prohibitively expensive and time-consuming. Moreover, the annotation process can be subjective and lead to inconsistencies, resulting in models that are biased and less accurate.
This thesis presents a comprehensive study of few-shot and active learning strategies, systems that combine the two techniques, and current text annotation tools while proposing a solution that addresses the aforementioned challenges through the integration of these methods. The proposed solution is an efficient text annotation platform that leverages Few-shot and Active Learning techniques. It has the potential to assist the field of text annotation by enabling organizations to process vast amounts of unstructured text data efficiently. Also, this research paves the way for inspiring ideas and promising growth opportunities in the future of this field
Uncovering the Archive: (Auto)biographical Documentaries and the “Moment of Discovery”
Get PDFWith the proliferation of digital archives as fixtures in our daily lives, the study of physical archives and their contents becomes more important than ever. Archives now function as sites for determining historical context and narratives, with formal archival institutions often acting as the foundations for ideas of nation-building. However, I argue that it is the informal archives—whether communal, familial, personal, or otherwise—which should be central to our analysis of physical archives and their place between the pages of history.
These informal archives necessarily question the role of the formal archive in narrativizing dominant histories with one of the key sites of debate occurring within the documentary genre, and specifically documentaries by diasporic filmmakers. In many such films, there is a crucial “moment of discovery,” wherein the found archival object marks the filmmaker as part of an alternative history that troubles the ingrained historical record. This “moment” marks the disruptions that the stories by diasporic people have upon traditions of proliferating alternative histories to counter dominant narratives and storytelling. The works which I will be exploring as examples of this filmic tradition are Random Acts of Legacy (2018), Retour (2017), and Shirkers (2018). All three of these films draw on this “moment of discovery” to build outwards, overlaying new interpretations of history onto these archival objects. I seek to understand what can be learned from these alternative histories
Building Cross-Cluster Security Models for Edge-Core Environments Involving Multiple Kubernetes Clusters
Get PDFWith the emergence of 5G networks and their large scale applications such as IoT and autonomous vehicles, telecom operators are increasingly offloading the computation closer to customers (i.e., on the edge). Such edge-core environments usually involve multiple Kubernetes clusters potentially owned by different providers. Confidentiality and privacy concerns could prevent those providers from sharing data freely with each other, which makes it challenging to perform common security tasks such as security verification and attack/anomaly detection across different clusters. In this work, we propose CCSM, a solution for building cross-cluster security models to enable various security analyses, while preserving confidentiality and privacy for each cluster. We design a six-step methodology to model both the cross-cluster communication and cross-cluster event dependency, and we apply those models to different security use cases. We implement our solution based on a 5G edge-core environment that involves multiple Kubernetes clusters, and our experi�mental results demonstrate its efficiency (e.g., less than 8 s of processing time for a model with 3,600 edges and nodes) and accuracy (e.g., more than 96% for cross-cluster event prediction
The Design and Implementation of a Query Platform and Simulation Tool for the Analysis of UML State Machines through Declarative Modeling
Get PDFAmong the various aspects of the UML, a state machine is part of the specification used to model the dynamic behavior of systems. In developing complex systems, state machines can be deployed to capture use cases and thus contribute towards requirements validation. During testing, a state machine can contribute towards requirements verification. In our proposal, we treat a state machine as a directed mathematical graph and transform it into a declarative model that is implemented as a database of clauses using Prolog. To tackle the complexity of composite states, we propose an algorithm for flattening the representation of a state machine. This model transformation occurs behind the scenes and provides the same semantic model at a lower level of abstraction. The initial and flattened declarative models provide the factbase on which we build a set of rules to study the behavior, the complexity and the structure of a state machine.
Furthermore, we treat the machine’s flattened model as a platform over which we simulate the machine’s behavior given a scenario. We support the simulation process with a tool that we developed. The tool is implemented in Java using the Java Prolog Library (JPL) that provides an interface between the two technologies. Our simulator reads in a scenario and proceeds to generate the machine’s behavior including its state at discrete time steps as output. We demonstrate the process through a case study
Student Communication Opportunities During a Teacher Planned ESL Class
Get PDFA classroom that implements Communicative Language Teaching (CLT) or Task-Based Language Teaching (TBLT) emphasizes the importance of student-centred learning that provides opportunities for students to learn from each other (Rahmatillah, 2019; Thorne, 2000; Chinyamurindi, 2018; Bruner, 1986). To explore student interaction in TBLT, this study investigates the opportunities students receive in an English as a second language (ESL) classroom to communicate about their personal experiences that are not directly related to the classroom topic. Transcripts from the House of Friendship, a Montreal community-based organization staffed by volunteer teachers and preservice teachers from Concordia’s BEd program in TESL, were analyzed for both teacher-to-student communication and student-to-student communication. The coding identified how many opportunities students had to discuss their own ideas, feelings and experiences as compared to information about the teachers’ planned topic. The findings indicated that students spend more time discussing the lesson topic than talking about unrelated personal experiences. The implications are discussed in terms of the distribution of student communication across different activity types and strategies for increasing opportunities to talk about personal experiences in ESL classrooms
Backtesting Expectiles with Moment Conditions
Get PDFUnder the current regulations, banks and insurance companies have the option to use their own internal models to monitor their risk. To this end, Value-at-Risk (VaR) and the Expected Shortfall (ES) are typically used as the risk measures to compute their capital requirements. Nevertheless, both present flaws, such as the lack of coherence for VaR and lack of elicitability for ES. Recently, expectile has attracted much attention as a potential alternative to VaR and ES. However, the literature on expectile is mainly focused on its statistical inference, and just few traditional backtesting procedures have been proposed. This thesis proposes a traditional backtesting procedure for the expectile and considers its application on financial data
The Technological Myth of Space Expansionism: Billionaire Futures in the Contemporary Space Age
Get PDFThere is consensus among space advocates that we are entering a new era of the space age. The contemporary setting is characterized by the confluence of government space programs with tax-payer funds and commercial space ventures that are innovating emergent technologies. It is also heavily associated with the actions, dialogues, and envisioned futures of tech entrepreneurs Elon Musk and Jeff Bezos, billionaires who founded and own the private space companies SpaceX and Blue Origin. Earth’s wealthiest individuals are determined to play a consequential role in exploring and exploiting other celestial bodies and extending human habitat into outer space. The multitude of ideologies, imaginaries, and discourses underpinning the project of space migration, from utopian to eschatological, can be condensed into one term: space expansionism. This thesis puts the burgeoning space economy and various theorized planetary futures into a historical context through conjunctural analysis. It finds that capitalism’s pursuit of infinite resources and growth in the solar system, as communicated in and promised by space expansionism, is not only a dubious technological myth, but a dangerous one
Overcoming “Bikelash”: Successful Implementation of an Urban Bicycle Highway in Montréal
Get PDFAmong the leading factors that frustrate bike lane development is the phenomenon known as “bikelash,” which is the organised opposition to bike lane development, usually categorised by
heated emotion. The presence of bikelash can make bike lane developments politically toxic in the public discourse, often leading to the failure to build the bike lane. The Saint-Denis Réseau
Express Vélo (REV) is one artery of the “bike highway” of Montréal that managed to be built despite the presence of bikelash from merchants, politicians and select members of the public. This thesis uses the Saint-Denis REV as a case study to understand why bikelash did not overwhelm this bike lane, despite the intense opposition to this development. Using political communication strategies and merchant subsidy programs, the municipal administration of Montréal was able to overcome bikelash and see the bike lane successfully installed. This thesis will examine the history of this bike lane, the bikelash in response to the development, and how this project managed to survive