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Fatigue Crack Growth Life Assessment Using 3D Finite Element Analysis
Get PDFDamage tolerance and fatigue crack growth life assessments allow manufactures to predict the in-service behaviour of high-risk components. Fatigue crack growth solutions are mostly generated using reduced order models that are based on simple geometries (i.e., corner crack at a bolt hole or surface crack in a plate) with the assumption that cracks hold an elliptical shape during propagation. A new finite element-based modelling process that takes into account component geometry, service loading conditions and minimizes simplifications with respect to crack front shape or planarity of the crack growth path is demonstrated.
A 3D finite element-based approach to fatigue crack growth propagation was evaluated as an alternative to reduced order modeling. The modelling approach was verified and validated in three main stages: simple plate geometry, specimens with multiple out of plane cracks, and full-sized specimen panel. A MATLAB analytical solution-based model was developed to estimate crack front evolution and fatigue crack growth life for surface, corner and internal cracks. The analytical results are verified with 3D finite element (FE) based approach implemented in SimModeler Crack. A set of experimental fatigue crack growth measurements based on Al 2024-T3 specimens containing multiple cracks was used to validate the 3D FE modelling solutions. Lastly, fatigue crack growth measurements from a full-sized spar experiment were used to ascertain the accuracy of the proposed FE model
A Music Therapist’s Exploration of Vocal Psychotherapy and Somatic Experiencing: A Heuristic Self-Inquiry
Get PDFMusic therapists often pursue specialized trainings to obtain additional skills that will enhance their work with specific client populations or help them to address particular health concerns. When trainings may contain techniques or theoretical orientations that seem contradictory rather than complementary, it can lead to confusion for therapists in their day-to-day practice, as was the case for the current author. The purpose of this heuristic self-inquiry was for the researcher to engage in self-reflective and experiential practices and to explore her feelings and perspectives on perceived disparities between vocal psychotherapy and somatic experiencing techniques used within her music therapy practice. Data collection and analysis procedures integrated components of vocal psychotherapy and somatic experiencing and were conceptualized within Moustakas’ six phases of heuristic inquiry. Content analysis of the material that emerged resulted in three overarching categories: personal insights, clinical insights, and insights about my professional identity––each one containing sub-categories supported by personal explications, journal quotes, and audio excerpts from self-reflective experiential improvisations. A creative synthesis of results and vision for moving forward was realized within the form of a sound collage, built from layered audio samples taken from the improvisations. Multiple implications are discussed, and the researcher offers concluding remarks about the multi-faceted value of reflective practice
Music Therapy and the Advancement of Family-Centred Care in the Neonatal Intensive Care Unit: A Philosophical Inquiry
Get PDFThe purpose of this philosophical inquiry was to understand and articulate the barriers to Family-Centred Care (FCC) implementation, to connect Neonatal Intensive Care Unit Music Therapy (NICU MT) to the principles of FCC, and to position music therapy as a unique and important contributor to the advancement of FCC principles within the Canadian NICU context. Since the inception of NICU MT as an area of specialization in the 1990’s, the shift towards FCC perspectives has been reflected in music therapy research, with significant outcomes for both improved physical parameters of fragile infants and the reduced anxiety and stress of parents. While NICU MT alignment with a FCC approach has become common, there has been limited explicit discourse on this alignment. This inquiry provides a comprehensive alignment of NICU MT’s research and approaches with the four FCC principles of Dignity and Respect, Information Sharing, Participation, and Collaboration, while articulating some of the systemic barriers that have impeded the full implementation of FCC. Canada’s unique health care system, in combination with the burgeoning NICU MT field worldwide, sets the stage for new and innovative models of care that are truly family centred
AI-Based Mode of Transportation and Destination Classification and Prediction in Origin-Destination Surveys
Get PDFTravel patterns and mode choice depend on individual socio-economic attributes that need better understanding. As a result, deciding which features to investigate is a challenge in data analysis.
This study investigates people's activities and trips to explore the correlation between individual and household socio-economic attributes, neighbourhood socioeconomic level and land use, and the choice of mode of transportation to access destinations in the city of Montreal. The study found that the land-use characteristics of Montreal and the shapes of its residents' travel patterns impact the design and implementation of public transportation projects throughout the census agglomeration of Montreal. These transportation infrastructure influences people's commuting behaviour patterns. How to predict these patterns using historical data and existing master plans is a major goal of this work. Machine learning and deep learning algorithms were used to predict trip destination and mode of transportation.
Numerous factors influence a person's travel pattern, including their age, residence location, and purpose of the trip. The most critical attributes were detected based on feature extraction methods and correlations between features were analyzed using a correlation heat map. This allowed to determine the most significant features to predict the trip's destination and mode of transportation.
Three most recent versions (2008-2013-2018) of the Montreal Origin-Destination (OD) data were used. Furthermore, a comparison between the accuracy of several well-known algorithms, such as decision trees, random forests, SVMs, and feedforward neural networks, was conducted. Comparing different results yielded from different algorithms shows that neural networks outperform all the other algorithms in terms of accuracy in predicting both modes of transportation and destination (78 percent in mode choice and 68.7 percent in destination). Therefore, it was used to predict the future trip pattern of the year 2023.
Moreover, this study proposes a Bayesian network to forecast the entire trip patterns for Montreal in 2023. This network is used to create a scaled-down version of OD2023. For this purpose, both OD and census data were used for the past 15 years. Different characteristics of trip patterns in each year were plotted. The Bayesian network captured and modelled how the trips changed over time.
This study provides a baseline for developing an application to extract critical statistical information about trip patterns on a neighbourhood scale in Montreal. Finally, the foundations for an application to extract critical statistical information about various trip patterns in various Montreal neighbourhoods were created.
This section combined various datasets from different years, including Census, land
use, and OD survey data. This application displays the extracted data in various plots and tables.
This research is meant to serve as a summary of previous studies as well as a reference for future research
A Lightweight Anomaly Detection Approach in Large Logs Using Generalizable Automata
Get PDFIn this thesis, we focus on the problem of detecting anomalies in large log data. Logs are generated at runtime and contain a wealth of information, useful for various software engineering tasks, including debugging, performance analysis, and fault diagnosis. Our anomaly detection approach is based on the multiresolution abnormal trace detection algorithm proposed in the literature. The algorithm exploits the causal relationship of events in large execution traces to build a model that represents the normal behaviour of a system using varying length n-grams and a generalizable automaton. The resulting model is later used to detect deviations from normalcy.
In this thesis, we investigate the application of this algorithm in detecting anomalies in log data. Logs and execution traces are different. Unlike traces, logs do not exhibit a causal relationship among their events, raising questions as to the effectiveness of automata to model log data for anomaly detection. Logs are unstructured data and hence require the use of parsing and abstraction techniques.
We propose a process, called LogAutomata, which uses the multiresolution abnormal trace detection algorithm as its primary mechanism. When applying LogAutomata to a large log file generated from the execution of Hadoop Distributed File System (HDFS), we show that the multiresolution algorithm can be a very effective way to detect anomalies in log data
The Legend of John Baptist Grimaldi: Sexual Comportment and Masculine Styles in Early Tudor London
Get PDFA small but wealthy and powerful group of Italian merchants lived in early sixteenth-century London, representing the international banking and mercantile firms of Genoa, Florence, Venice, Lucca, and other northern Italian city-states. Though favourites at the royal court, with direct access to the ears of the king himself, these Lombards (as the English termed them) were highly unpopular with their English mercantile rivals. London merchants’ hostility drew obviously from the economic competition the Italians posed, but their animosity was cultural as well as commercial. One particular bone of contention was that Italian merchants did not play by English rules regarding sexual relationships: they were accused of seducing the wives and daughters of respectable men. The Italians may have pursued such seductions not simply for sexual gratification but also as a strategy to embarrass and shame their English counterparts. At the same time, it is also clear that there were quite different sexual ethics at work among the English and Italian mercantile elites that signified incompatible reactions to sexual situations
Direct Sound Printing
Get PDFPhoto- and thermo-activated reactions are dominant in Additive Manufacturing (AM) processes for polymerization or melting/deposition of polymers. However, ultrasound activated sonochemical reactions present a unique way to generate hotspots in cavitation bubbles with extraordinary high temperature and pressure along with high heating and cooling rates which are out of reach for the current AM technologies. Here, we demonstrate 3D printing of structures using acoustic cavitation produced directly by focused ultrasound which creates sonochemical reactions in highly localized cavitation regions. Complex geometries with zero to varying porosities and 280 μm feature size are printed by our method, Direct Sound Printing (DSP), in a heat curing thermoset, Poly(dimethylsiloxane) that cannot be printed directly so far by any method. Sonochemiluminescnce, high speed imaging and process characterization experiments of DSP and potential applications such as remote distance printing are presented. Our method establishes an alternative route in AM using ultrasound as the energy source
Living la vida loca: The ups and downs of learning in a cohort system.
Get PDFThis paper describes the use of cohort structures in management and leadership education. Cohorts privilege social interaction as the locale where cognition and culture are co-created between individuals. A cohort learning community format allows students and faculty to create opportunities for significant and deep learning—learning that integrates both the conceptual, the social and emotional, the self and the other—in relational spaces by promoting zones of proximal development, multisubjectivity, multivocality, and shared cognition. These are hallmarks of effective learning organizations and communities of practice. But they also present significant and tough challenges. Using creative nonfiction to frame reflections, five authors illuminate their experiences in cohort communities: the benefits, difficult sides, and challenges of creating crucible spaces where social and emotional learning can be explored, and its role in promoting transformational learning
Low-Cost Portable Wireless Electroencephalography to Detect Emotional Responses to Visual Cues: Validation and Potential Applications
Get PDFThis paper validates the using a low-cost EEG headset – Emotiv Insight 2.0 – for detecting emotional responses to visual stimuli. The researchers detected, based on brainwave activity, the viewer’s emotional states in reference to a series of visuals and mapped them on valance and arousal axes. Valence in this research is defined as the viewer’s positive or negative state, and arousal is defined as the intensity of the emotion or how calm or excited the viewer is. A set of thirty images – divided into two categories: Objects and Scenes – was collected from the Open Affective Standard Image Set (OASIS) and used as a reference for validation. We collected atotal of 720 data points for six different emotional states: Engagement, Excitement, Focus, Interest, Relaxation, and Stress. To validate the emotional state score generated by the EEG headset, we created a regression model using those six parameters to estimate the valence and arousal level, and compare them to values reported by OASIS. The results show the significance of the Engagement parameter in predicting the valence level in the Objects category and the significance of the Excitement parameter in the Scenes category. With the emergence of personal EEG headsets, understanding the emotional reaction in different contexts will help in various fields such as urban design, digital art, and neuromarketing. In architecture, the findings can enable designers to generate more dynamic and responsive design solutions informed by users’ emotions
Gender, Affective Labour, and Community-Building Through Literary Audio Recordings
Get PDFThis article emerged from the “feminist close listening” methodology we devised together during a collaborative listening session in Montreal, December, 2017. We began the practice of listening to recordings together, in real time, as a way of attuning ourselves to the related inquiries that our archives of interest shared. For Karis, this archive is the SoundBox Collection, housed in the AMP Lab at the University of British Columbia, Okanagan Campus, where she serves as Director. For Deanna, this archive is the Roy Kiyooka Audio Archive, housed in the Contemporary Literature Collection at Simon Fraser University. The archives share the same media formats (reel-to-reel and compact cassette tapes) as well as the common generic features of recording spontaneous, candid conversation, often voiced in contexts that are considered domestic, intimate, and private. Our listening sessions aimed to collaboratively outline questions, approaches, and best practices toward this unique subset of literary recordings. The article that follows is one concrete example of how those conversations unfolded