Digitized by Kansas Correctional Industries

This thesis examined the feasibility of fibre composite reinforcement in the furniture industry. The development of post war furniture design was reviewed, with particular emphasis on the main design movements and the use of new materials and technologies. The use of fibre composite materials in contemporary furniture was discussed in terms of technical development, environmental effects and psychological acceptance. Fibre reinforcements and adhesives were compared, as were fabrication techniques applicable to the existing British furniture industry. Particular emphasis has been placed on the fibre reinforcement of laminated timber sections as a method of overcoming many of the manufacturing problems of composites. Methods of analysing the behaviour under load of fibre reinforced laminated wood were reviewed. Resistance among the furniture buying public to modem, non-traditional furniture design was discussed, along with ways of making composite materials more aesthetically acceptable. Experimentation to determine the mechanical properties of fibre composite reinforced wood against wood control samples was undertaken, along with methods used to analyse the results for flat and curved samples. Modulus of elasticity, modulus of rupture and impact strength were measured, as was the level of distortion of the samples before and after testing. A full size chair form was produced to demonstrate the behaviour of the material on a larger scale. The development of the design was discussed in terms of ergonomic requirements, aesthetics, practicality and environmental concerns. The problem of predicting the behaviour of complex shapes was discussed and a finite element analysis of the form is carried out to gain an accurate picture of the composite's performance. Production of fibre reinforced materials was discussed, along with the furniture industry's reluctance to invest in new materials and technologies. The feasibility of adapting traditional furniture making skills and equipment to the production of fibre composite reinforced wood has been assessed.

Sequential decision making under uncertainty is a ubiquitous problem. In everyday situations we are faced with a series of decisions that aim to maximize the probability of achieving some goal. However, decision outcomes are often uncertain and it is not always immediately evident how to determine if one decision is better than another. The Reinforcement Learning framework overcomes this difficulty by learning to make optimal decisions based on interactions with the environment. One drawback of Reinforcement Learning is that it requires too much data (interactions) to learn from scratch. For this reason, current approaches attempt to incorporate prior information in order to simplify the learning process. However, this is usually accomplished by making problem-specific assumptions, which limit generalizability of the approaches to other problems. This thesis presents the first steps towards a new framework that incorporates and exploits broad prior knowledge in a principled way. It uses Constraint Satisfaction and Bayesian techniques to construct and update a belief over the environment, as well as over good decisions. This allows for incorporating broad types of prior knowledge without limiting generalizability. Preliminary experiments show that the framework's algorithms work well on toy problems in simulation and encourage further research on real-world problems.

Sequential decision making under uncertainty is a ubiquitous problem. In everyday situations we are faced with a series of decisions that aim to maximize the probability of achieving some goal. However, decision outcomes are often uncertain and it is not always immediately evident how to determine if one decision is better than another. The Reinforcement Learning framework overcomes this difficulty by learning to make optimal decisions based on interactions with the environment. One drawback of Reinforcement Learning is that it requires too much data (interactions) to learn from scratch. For this reason, current approaches attempt to incorporate prior information in order to simplify the learning process. However, this is usually accomplished by making problem-specific assumptions, which limit generalizability of the approaches to other problems. This thesis presents the first steps towards a new framework that incorporates and exploits broad prior knowledge in a principled way. It uses Constraint Satisfaction and Bayesian techniques to construct and update a belief over the environment, as well as over good decisions. This allows for incorporating broad types of prior knowledge without limiting generalizability. Preliminary experiments show that the framework's algorithms work well on toy problems in simulation and encourage further research on real-world problems.

Thesis (Ph.D.) -- University of Texas at Arlington, 2008.

Thesis (Ph. D.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains viii, 76 p. : ill. Includes abstract. Includes bibliographical references (p. 70-76).

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In most industrialized countries, significant future activity in the construction sector will be related to repair and rehabilitation of aging infrastructure. This will require use of durable and high performance repair materials. Among various mechanisms cited for lack of durability in repairs, early-age shrinkage cracking in overlay materials is of utmost importance. Fiber-reinforcement can be used to alleviate some of the issues related to plastic shrinkage. However, quantifying the performance of cement-based composites under restrained shrinkage conditions remains an issue. Various test techniques are available to measure free and restrained shrinkage, but do not simulate the real constraint imposed by the substrate on the overlay. In this dissertation, an innovative test method called the bonded overlay technique is described. An overlay of fiber-reinforced material to be tested is cast directly on a substrate, and the entire assembly is subjected to controlled drying. Cracking in the overlay is then monitored and characterized. During the development of this test method, instrumentation was included to enable measurement of the crack propagation rate using image analysis, evaporation rate, heat development, and strain using embedded sensors. Using the above technique, the effect of mix proportion including variables such as water-cement ratio (w/c), sand-cement ratio (s/c), and coarse aggregate content were studied. An increase in w/c from 0.35 to 0.6 significantly increased the total cracking. Addition of coarse aggregates reduced shrinkage cracking, however, for the range of s/c investigated, no definite conclusions could be drawn. Mixes with 0-20% fly ash and a 7 lit/m3 dosage of shrinkage reducing admixtures indicated no significant reduction in cracking. The influence of fiber geometry on cracking in overlays was also investigated. Fiber types included different sizes of polypropylene and cellulose fibers and one type of glass fiber (volume fraction ranging between 0-0.4%). Glass fibers at a small dosage of 0.1% were the most efficient fiber and completely eliminated cracking. Of the two field projects considered: one was a plaza deck at the UBC Aquatic Center, where cellulose fibers were used, and the second at the UBC ChemBioE building, where polypropylene fibers were used in slabs-on-grade. Both overlays were instrumented with strain sensors, data from which were monitored over the Internet. Results clearly indicated that fibers reduced the strain development in fiber-reinforced overlays when compared to un-reinforced overlays. An energy-based fracture model was proposed to predict maximum crack widths and in a second study, an equation was proposed to correlate early-age shrinkage and flexural toughness of cellulose fibers. In both models, a reasonable correlation with the test data was observed. In addition, factorial design method was used and a mathematical model was proposed to correlate different variables such as w/c, s/c, and fiber dosage.

Religiosity and morality constitute the fundamental components of any culture and set up rules and regulate interpersonal behavior. In the context of religion, to understanding value transgressions, their emotional consequences and the moderating role of social threats (in-group and out-group interactions), the psychological underpinnings of value-reinforcement, and complementing role of self-affirmation at a group level represent the focal points of this dissertation. The findings of study 1 show that value transgression has a direct effect on the level of negative emotion experienced by the transgressor. The social threat that is manipulated by the presence of an out-group member during the time of transgression moderates the relationship between value transgression and level of negative emotion. Furthermore, value reinforcement (e.g, endorsing group value) can weaken the effect of threats and mitigate negative emotions. Study 1 findings show that value reinforcement's absence qualified previous proposition of value transgression and social presence interaction. In study 2, I carry on the investigation by showing that granting opportunities to affirm important group values mitigates their emotional tension. Study 2 results show that group-affirmation may work as a complementary factor that further explains the relationship between value reinforcement and emotional reaction in the event of transgressing group values.