Carbon nanotubes (CNTs) possess superior electrical and mechanical properties and thus are excellent candidates for nanostructured materials. Due to the very high length-to-diameter ratio of CNTs, they are ideal reinforcements for polymer nanocomposites. Engineering of the polymer-CNT interface through noncovalent modifications is necessary to achieve the desired mechanical properties and yet preserve the inherent properties of the CNTs. However, the effects of chemical composition and backbone stiffness on the adsorption characteristics of polymers are not well understood. Molecular dynamics simulations in vacuum were used to study the interaction between a (10,0) zig-zag type single-walled carbon nanotube (SWCNT) and a series of polymers. These simulations investigate whether the polymers prefer to wrap the SWCNT, what the molecular details of that interface are, and how the interfacial interaction is affected by the chemical composition and structure of the polymer. The simulations indicate that polymers with both flexible and stiff backbones tend to wrap around the SWCNT, although in different conformations. Flexible backbones like nylon6 (N6) and poly(lactide) (PLA) wrap in a random conformation along both the longitudinal axis and the diameter of the SWCNT. One flexible polymer, poly(acrylnitrile) (PAN), preferred to extend along the longitudinal axis rather than wrap the diameter of the SWCNT as a means of optimizing pi-pi overlap between the cyano side chain and the SWCNT; PAN was the only flexible backbone polymer that exhibited preferential orientation of chemical groups along the SWCNT surface. Flexible polymers with bulky and aromatic side groups such as poly(methylmethacrylate) (PMMA) and poly(styrene) (PS) prefer intra-chain coiling rather than wrapping the SWCNT. Poly(ethylene terephthalate) (PET), the only polymer with a semi-flexible backbone in this study, exhibited a partial wrap in an S-conformation along the side of the SWCNT. Polymers with stiff backbones such as poly(acetylene) (PA), poly(p-phenylene vinylene) (PPV), poly(pyrrole) (PPy), and poly(arylene ethynylene) (PPE) exhibit distinct conformations upon adsorption. Helical-like wrapping conformations were only obtained for PPV and PPE. Aromatic groups along the backbone tend to dictate the adsorption conformation due to pi-pi interactions with the SWCNT, although the presence of bulky aliphatic side chains can have a slight impact on this interaction. Plots of the rotational moment of inertia of each polymer about the SWCNT longitudinal axis as a function of time quantify the interplay between intra-chain coiling and adsorption to the SWCNT surface. These plots indicate that the adsorption of polymers with stiff backbones tends to be a two-step process, whereas flexible backbones tend to exhibit a multi-step wrapping mechanism, especially those that have a preference for intra-chain coiling. To quantify the correlation between the chemical composition of the repeat unit and the conformational limitations of long polymer chains, MD simulations were also performed with small molecules that correspond to the repeat units of a subset of the polymers. These simulations indicate that the individual molecules have more conformational freedom, yet still exhibit some orientation characteristics similar to the polymers, such as adsorption of both aromatic rings and aliphatic hydrocarbons along the SWCNT surface.

The increase in computing power over the last decade has led to an increase in the use of simulation programs to model real world optimization problems as well as the complexity with which these problems can be modeled. Once a model has been built, an experimental design is often used to determine the effects certain parameters have on the problem trying to determine the good settings that optimize a set of outputs. However, these problems often have a large number of variables or parameters that can be changed with wide value ranges and as these simulation models become increasingly more complex they become computationally expensive to run. Most of these problems are non-linear and may not have a true optimal solution based on the inherent variability in real-world applications and the stochastic simulation model. Evolutionary algorithms are a class of computational optimization techniques that harness the power of the computer to solve a problem. The application of evolutionary search techniques as a simulation optimization technique has yielded reasonable results. However, the algorithm can take a long time evaluating just one set of decision variables owing to replications and computational time of one simulation run and not to mention the sheer number of different sets that have to be evaluated to find good solutions for these complex problems. Linear regression and neural-network meta-models can be used to generate a surface model of the simulation. Evaluating the meta-model is very fast as compared to the simulation model. Therefore, this thesis combines the use of evolution algorithms, simulation models and meta-models to produce a more efficient simulation optimization technique. The two types of meta-models are tested to determine their effectiveness as a meta-modeling technique and the overall effectiveness of finding the best solution.

Businesses are constantly striving for a competitive edge in the economy, and data-driven decision making is crucial to achieve this goal. Four data mining tools, principal component analysis, cluster analysis, recursive partitioning, and discriminant analysis, were used to explore the major factors that contribute to ends down in a rotor spinning manufacturing process. Principal component analysis was used to explore the research question about whether the large number of cotton properties used to classify cotton could be reduced to a significant few. Cluster analysis was used to gain insight about whether there were groups of gins, counties, or classing offices that produced better raw material than others and led to less ends down. The important research question of what raw material properties were affecting ends down was explored with both recursive partitioning and discriminant analysis. Additional research investigated the effect of cotton variety and atmospheric conditions on spinning productivity. Each of the four data mining tools used was informative and offered a different perspective to the overall research question. Several significant factors emerged including humidity, temperature, %DP 555, and uniformity in addition to micronaire and the color properties (+b and Rd). With these results the researcher developed an improvement plan for better control and increased spinning productivity in future operations. A designed experiment is necessary to thoroughly investigate the impact of certain factors beyond the exploratory conclusions obtained from this study.

The surface modification of UHMPE fibers by atmospheric pressure plasma treatments was examined. In one study the aging effects of atmospheric plasma treatments were studied. UHMPE fibers were treated for 0.5 and 1 min with He/O2/air gas and for 2 and 4 min with He/air gas by atmospheric pressure plasma on a capacitively coupled device. The samples were tested for fiber/epoxy interfacial shear strength using the microbond technique at time intervals of 0, 3, 15 and 30 days after initial plasma treatment. Interfacial shear strengths (IFSS) for plasma treated fibers were 2 - 3 times as high as that of the control. The IFSS for the plasma treated fibers remained constant up to 15 days and then decreased afterwards. XPS Analysis and SEM photographs characterized the fiber surface modification. In a second study, delamination phenomena was studied by the transverse compression of seven-fiber bundle UHMPE microcomposites, a peeling test of laminated plain weave UHMPE fabric and tensile shear strength testing of a ten-layer plain weave UHMPE / Epoxy flat panel composite. Results showed a 49% increase in yield modulus of the plasma treated sample compared to the control in the transverse compression test. There was an 82.5% increase in bonding strength for the plasma treated sample during the peel test and a 25.7% increase in interlaminar shear strength of the ten-ply UHMPE composite proving that atmospheric plasma treatments are very effective in surface modification on a microscopic fiber level and a full-scale composite production level.

The purpose of the research was to develop an algorithm to permanently reduce human errors in the healthcare industry. The algorithm will be able to be applied to all healthcare organizations and provide a preventative approach to errors. The research involved looking at past methods of error reduction/prevention. Certain methods proved to be useful in generating the algorithm like the Healthcare Failure Modes and Effects Analysis while others like Root Cause Analysis proved to only have limited success. The algorithm takes a three phase approach to reducing errors. Phase One identifies the potential error producing situations. Phase Two uses error proofing principles and known solution directions to generate solutions while Phase Three uses a new method developed called Solution Priority Number to rank and evaluate the solutions. Throughout the algorithm many worksheets have been developed to aid in a team?s progression through the process. Two case studies were performed. The first case study followed a traditional team through the error prevention process while the second case used the algorithm. When comparing the two cases the team using the algorithm finished the process in shorter time, produced more effective failure modes, and generated a richer set of solutions to error proof the process.

<p>With time as a major competitive factor in today's marketplace, it is crucial to bring products to the market and solve problems in existing products in a swift manner. Rapid prototyping methods are very effective ways of streamlining this effort. However, current rapid prototyping methods generally apply after a solution concept has been selected. Many current conceptual design methods were reviewed and it was shown that a need exists for similar acceleration of the problem identification, idea generation, and concept selection portions of the design process. This would bring the conceptual front end of the design process under the umbrella of what is considered "rapid prototyping". The Ideal Final Result (IFR) of each of the three major conceptual steps was developed to be able to formulate a series of steps to accelerate the process by performing only what is necessary to accomplish the IFR's. The existing methods and custom-designed methods provided for filling in what was needed for each step. An "Ideality-based" concept selection method was developed to make the idea selection process more complete. The entire methodology is explained in detail, and a case study to use the new methodology was performed on an existing, real problem situation to show the useful and accelerated nature of the method. <P>

<p>The contents of this paper present information from work conducted by utilizing plasma technology for fabric treatment. Initially, experimentation was done in low-pressure plasma systems to change the hydrophilic properties of denim fabric. From these experiments, data was collected that proved denim fabric, both sized and desized, could obtain hydrophobicity through a fluorocarbon plasma treatment. Using C3F6 fluorocarbon gas provided a greater level of hydrophobicity than using CF4 plasma gas. The desized denim showed a greater amount of hydrophobicity, in both gases, than the sized denim. These results can be found in chapter IV. The remaining work, found in chapters II and III, focuses on the utilization of atmospheric plasmas on the treatment of nylon 6,6 fabric. Atmospheric plasmas could allow continuous treatment of fabric and shorter treatment times for fabric, all of which would be better suited for industrial processing, more specifically in textiles. Nylon 6,6 fabric was treated with air-He plasma as well as air-He-O2 plasma, where the levels of O2 varied. A significant decrease in tensile strength was found in treatments lasting five minutes or longer. However, micrographs of the fiber surface illustrate instances of surface treatment, even at times less than five minutes. Continuing work on the project includes the building of a prototype machine for industry (currently in progress), the treatment of many different kinds of fabrics, and the evaluation of their mechanical, chemical, and physical properties and functionability thereafter.<P>

No description available.

No description available.

Textiles of today are materials with applications in almost all our activities. We wear clothes all the time and we are surrounded with textiles in almost all our environments. The integration of multifunctional values in such a common material has become a special area of interest in recent years. Smart Textile represents the next generation of textiles anticipated for use in several fashion, furnishing and technical textile applications. The term smart is used to refer to materials that sense and respond in a pre-defined manner to environmental stimuli. The degree of smartness varies and it is possible to enhance the intelligence further by combining these materials with a controlling unit, for example a microprocessor. As an interdisciplinary area Smart Textile includes design spaces from several areas; the textile design space, the information technology design space and the design space of material science. This thesis addresses how Smart Textiles affect the textile design space; how the introduction of smart materials and information technology affects the creation of future textile products. The aim is to explore the convergence between textiles, smart materials and information technology and to contribute to providing a basis for future research in this area. The research method is based on a series of interlinked experiments designed through the research questions and the research objects. The experiments are separated into two different sections: interactive textile structures and health monitoring. The result is a series of basic methods for how interactive textile structures are created and a general system for health monitoring. Furthermore the result consists of a new design space, advanced textile design. In advanced textile design the focus is set on the relation between the different natures of a textile object: its physical structure and its structure in the context of design and use.