A Generalized Methodology to Characterize Composite Materials for Pyrolysis Models

The predictive capabilities of computational fire models have improved in recent years such that models have become an integral part of many research efforts. Models improve the understanding of the fire risk of materials and may decrease the number of expensive experiments required to assess the fire hazard of a specific material or designed space. A critical component of a predictive fire model is the pyrolysis sub-model that provides a mathematical representation of the rate of gaseous fuel production from condensed phase fuels given a heat flux incident to the material surface. The modern, comprehensive pyrolysis sub-models that are common today require the definition of many model parameters to accurately represent the physical description of materials that are ubiquitous in the built environment. Coupled with the increase in the number of parameters required to accurately represent the pyrolysis of materials is the increasing prevalence in the built environment of engineered composite materials that have never been measured or modeled. The motivation behind this project is to develop a systematic, generalized methodology to determine the requisite parameters to generate pyrolysis models with predictive capabilities for layered composite materials that are common in industrial and commercial applications. This methodology has been applied to four common composites in this work that exhibit a range of material structures and component materials. The methodology utilizes a multi-scale experimental approach in which each test is designed to isolate and determine a specific subset of the parameters required to define a material in the model. Data collected in simultaneous thermogravimetry and differential scanning calorimetry experiments were analyzed to determine the reaction kinetics, thermodynamic properties, and energetics of decomposition for each component of the composite. Data collected in microscale combustion calorimetry experiments were analyzed to determine the heats of complete combustion of the volatiles produced in each reaction. Inverse analyses were conducted on sample temperature data collected in bench-scale tests to determine the thermal transport parameters of each component through degradation. Simulations of quasi-one-dimensional bench-scale gasification tests generated from the resultant models using the ThermaKin modeling environment were compared to experimental data to independently validate the models.

The Effect of Attentional Focus on Singing Voice Quality: Towards the Interdisciplinary Experimental Investigation of Singing Pedagogy

Instructional methods employed by teachers of singing are mostly drawn from personal experience, personal reflections, and methods encountered in their own voice training (Welch & Howard, 2005). Even in Academia, singing pedagogy is one of the few disciplines in which research of teaching/learning practice efficacy has not been established (Crocco, et al., 2016). This dissertation argues the reason for this deficit is a lack of operationalization of constructs in singing, which, to date has not been undertaken. The researcher addresses issues of paradigm, epistemology, and methodology to suggest an appropriate model of experimental research towards the assessment of teaching/learning practice efficacy. A study was conducted adapting attentional focus research methodologies to test the effect of attentional focus on singing voice quality in adult novice singers. Based on previous attentional focus studies, it was hypothesized that external focus conditions would result in superior singing voice quality than internal focus conditions. While the hypothesis was partially supported by the data, the researcher welcomed refinement of the suggested research model. It is hoped that new research methodologies will emerge to investigate singing phenomena, yielding data that may be used towards the development of evidence-based frameworks for singing training.

Experimental Modeling of Twin-Screw Extrusion Processes to Predict Properties of Extruded Composites

Twin-screw extrusion is used to compound fillers into a polymer matrix in order to improve the properties of the final product. The resultant properties of the composite are determined by the operating conditions used during extrusion processing. Changes in the operating conditions affect the physics of the melt flow, inducing unique composite properties. In the following work, the Residence Stress Distribution methodology has been applied to model both the stress behavior and the property response of a twin-screw compounding process as a function of the operating conditions. The compounding of a pigment into a polymer melt has been investigated to determine the effect of stress on the degree of mixing, which will affect the properties of the composite. In addition, the pharmaceutical properties resulting from the compounding of an active pharmaceutical ingredient are modeled as a function of the operating conditions, indicating the physical behavior inducing the property responses.