Corrosion in underground and submerged steel pipes is a global problem. Coatings serve as an impermeable barrier or a sacrificial element to the transport of corrosive fluids. When this barrier fails, corrosion in the metal initiates. There is a critical need for sensors at the metal/coating interface as an early alert system. Current options utilize metal sensors, leading to accelerating corrosion. In this dissertation, a non-conductive sensor textile as a viable solution was investigated. For this purpose, non-woven zinc (II) oxide-polyvinylidene fluoride (ZnO-PVDF) nanocomposite fiber textiles were prepared in a range of weight fractions (1%, 3%, and 5% ZnO) and placed at the coating/steel interface. Electrochemical impedance spectroscopy (EIS) testing was performed during the immersion of the coated samples to validate the effectiveness of the sensor textile. In the second part of this dissertation, an accelerated thermal cyclic method has been applied to determine sensor's reliability in detecting corrosion under actual service condition. The results suggested that the coating is capable of detecting corrosion under harsh conditions. Moreover, the addition of ZnO decreases the error in sensor textile and improved coating's barrier property. In the next phase, experiments were conducted to detect the type of corrosion (pitting or uniform) underneath …

Electrically conductive fabrics are one of the major components of smart textile that attracts a lot of attention by the energy, medical, sports and military industry. The principal contributors to the conductivity of the smart textiles are the intrinsic properties of the fiber, functionalization by the addition of conductive particles and the architecture of fibers. In this study, intrinsic properties of non-woven carbon fabric derived from a novel linear lignin, poly-(caffeyl alcohol) (PCFA) discovered in the seeds of the vanilla orchid (Vanilla planifolia) was investigated. In contrast to all known lignins which comprise of polyaromatic networks, the PCFA lignin is a linear polymer. The non-woven fabric was prepared using electrospinning technique, which follows by stabilization and carbonization steps. Results from Raman spectroscopy indicate higher graphitic structure for PCFA carbon as compared to the Kraft lignin, as seen from G/D ratios of 1.92 vs 1.15 which was supported by a high percentage of graphitic (C-C) bond observed from X-ray photoelectron spectroscopy (XPS). Moreover, from the XRD and TEM a larger crystal size (Lc=12.2 nm) for the PCFA fiber was obtained which correlates to the higher modulus and conductivity of the fiber. These plant-sourced carbon fabrics have a valuable impact on zero …

The coronary heart disease kills more than 350,000 persons/year and it costs $108.9 billion for the United States each year, in spite of significant advancements in clinical care and education for public, cardiovascular diseases (CVD) are leading cause of death and disability to the nation. A cardiovascular disease involves mainly heart or blood vessels (arteries, veins and capillaries) or both, and then mainly occurs in selected regions and affects heart, brain, kidney and peripheral arteries. As a surgical interventions, stent implantation is deployed to cure or ameliorate the disease. However, the high failure rate of stents used in patients with peripheral artery diseases has lead researchers to give special attention towards analyzing stent structure and characteristics. In this research, the mechanical properties of a stent based on the rhombus structure were analyzed and verified by means of analytical and numerical approaches. Theoretical model based on the beam theory were developed and numerical models were used to analyze the response of these structures under various and complex loading conditions. Moreover, the analysis of the stent inflation involves a model with large deformations and large strains, nonlinear material properties need to be considered to accurately capture the deformation process. The maximum stress …

Texas, due to its geographical area, population, and economy is home to a variety of industrialized areas that have significant air quality problems. These urban areas are affected by elevated levels of fine particulate matter (PM2.5). The primary objective of this study was to identify and quantify local and regional sources of air pollution affecting the city of Houston, Texas. Positive Matrix Factorization (PMF) techniques were applied to observational datasets from two urban air quality monitoring sites in Houston from 2003 through 2008 in order to apportion sources of pollutants affecting the study region. Data from 68 species for Aldine and 91 for Deer Park were collected, evaluated, and revised to create concentration and uncertainty input files for the PMF2 and EPA PMF (PMF3) source apportionment models. A 11-sources solution for Aldine and 10-sources for Deer Park were identified as the optimal solutions with both models. The dominant contributors of fine particulate matter in these sites were found to be biomass burnings (2%-8.9%), secondary sulfates I (21.3%-7.6%) and II (38.8%-22.2%), crustal dust (8.9%-10.9%), industrial activities (10.9%-4.2%), traffic (23.1%-15.6%), secondary nitrates (4.4%-5.5%), fresh (1%-1.6%) and aged(5.1%-4.6%) sea salt and refineries (1.3%-0.6%), representing a strong case to confirm the high influence of …