CHARACTERIZATION OF THERMAL AND MECHANICAL PROPERTIES OF POLYPROPYLENE–BASED COMPOSITES FOR FUEL CELL BIPOLAR PLATES AND DEVELOPMENT OF EDUCATIONAL TOOLS IN HYDROGEN AND FUEL CELL TECHNOLOGIES

In this project we developed conductive thermoplastic resins by adding varying amounts of three different carbon fillers: carbon black (CB), synthetic graphite (SG) and multi–walled carbon nanotubes (CNT) to a polypropylene matrix for application as fuel cell bipolar plates. This component of fuel cells provides mechanical support to the stack, circulates the gases that participate in the electrochemical reaction within the fuel cell and allows for removal of the excess heat from the system. The materials fabricated in this work were tested to determine their mechanical and thermal properties. These materials were produced by adding varying amounts of single carbon fillers to a polypropylene matrix (2.5 to 15 wt.% Ketjenblack EC-600 JD carbon black, 10 to 80 wt.% Asbury Carbons’ Thermocarb TC-300 synthetic graphite, and 2.5 to 15 wt.% of Hyperion Catalysis International’s FIBRILTM multi-walled carbon nanotubes) In addition, composite materials containing combinations of these three fillers were produced. The thermal conductivity results showed an increase in both through–plane and in–plane thermal conductivities, with the largest increase observed for synthetic graphite. The Department of Energy (DOE) had previously set a thermal conductivity goal of 20 W/m·K, which was surpassed by formulations containing 75 wt.% and 80 wt.% SG, yielding in–plane thermal conductivity values of 24.4 W/m·K and 33.6 W/m·K, respectively. In addition, composites containing 2.5 wt.% CB, 65 wt.% SG, and 6 wt.% CNT in PP had an in–plane thermal conductivity of 37 W/m·K. Flexural and tensile tests were conducted. All composite formulations exceeded the flexural strength target of 25 MPa set by DOE. The tensile and flexural modulus of the composites increased with higher concentration of carbon fillers. Carbon black and synthetic graphite caused a decrease in the tensile and flexural strengths of the composites. However, carbon nanotubes increased the composite tensile and flexural strengths. Mathematical models were applied to estimate through–plane and in–plane thermal conductivities of single and multiple filler formulations, and tensile modulus of single–filler formulations. For thermal conductivity, Nielsen’s model yielded accurate thermal conductivity values when compared to experimental results obtained through the Flash method. For prediction of tensile modulus Nielsen’s model yielded the smallest error between the predicted and experimental values. The second part of this project consisted of the development of a curriculum in Fuel Cell and Hydrogen Technologies to address different educational barriers identified by the Department of Energy. By the creation of new courses and enterprise programs in the areas of fuel cells and the use of hydrogen as an energy carrier, we introduced engineering students to the new technologies, policies and challenges present with this alternative energy. Feedback provided by students participating in these courses and enterprise programs indicate positive acceptance of the different educational tools. Results obtained from a survey applied to students after participating in these courses showed an increase in the knowledge and awareness of energy fundamentals, which indicates the modules developed in this project are effective in introducing students to alternative energy sources.

From the traditional verification approach to the spatial methods: a study of applicability of the SAL metric in the framework of the WMO project MesoVICT

Increasing in resolution of numerical weather prediction models has allowed more and more realistic forecasts of atmospheric parameters. Due to the growing variability into predicted fields the traditional verification methods are not always able to describe the model ability because they are based on a grid-point-by-grid-point matching between observation and prediction. Recently, new spatial verification methods have been developed with the aim of show the benefit associated to the high resolution forecast. Nested in among of the MesoVICT international project, the initially aim of this work is to compare the newly tecniques remarking advantages and disadvantages. First of all, the MesoVICT basic examples, represented by synthetic precipitation fields, have been examined. Giving an error evaluation in terms of structure, amplitude and localization of the precipitation fields, the SAL method has been studied more thoroughly respect to the others approaches with its implementation in the core cases of the project. The verification procedure has concerned precipitation fields over central Europe: comparisons between the forecasts performed by the 00z COSMO-2 model and the VERA (Vienna Enhanced Resolution Analysis) have been done. The study of these cases has shown some weaknesses of the methodology examined; in particular has been highlighted the presence of a correlation between the optimal domain size and the extention of the precipitation systems. In order to increase ability of SAL, a subdivision of the original domain in three subdomains has been done and the method has been applied again. Some limits have been found in cases in which at least one of the two domains does not show precipitation. The overall results for the subdomains have been summarized on scatter plots. With the aim to identify systematic errors of the model the variability of the three parameters has been studied for each subdomain.

The Performance and Service Life Prediction of High Performance Concrete in Sulfate and Acidic Environments

Concrete substructures are often subjected to environmental deterioration, such as sulfate and acid attack, which leads to severe damage and causes structure degradation or even failure. In order to improve the durability of concrete, the High Performance Concrete (HPC) has become widely used by partially replacing cement with pozzolanic materials. However, HPC degradation mechanisms in sulfate and acidic environments are not completely understood. It is therefore important to evaluate the performance of the HPC in such conditions and predict concrete service life by establishing degradation models. This study began with a review of available environmental data in the State of Florida. A total of seven bridges have been inspected. Concrete cores were taken from these bridge piles and were subjected for microstructural analysis using Scanning Electron Microscope (SEM). Ettringite is found to be the products of sulfate attack in sulfate and acidic condition. In order to quantitatively analyze concrete deterioration level, an image processing program is designed using Matlab to obtain quantitative data. Crack percentage (Acrack/Asurface) is used to evaluate concrete deterioration. Thereafter, correlation analysis was performed to find the correlation between five related variables and concrete deterioration. Environmental sulfate concentration and bridge age were found to be positively correlated, while environmental pH level was found to be negatively correlated. Besides environmental conditions, concrete property factor was also included in the equation. It was derived from laboratory testing data. Experimental tests were carried out implementing accelerated expansion test under controlled environment. Specimens of eight different mix designs were prepared. The effect of pozzolanic replacement rate was taken into consideration in the empirical equation. And the empirical equation was validated with existing bridges. Results show that the proposed equations compared well with field test results with a maximum deviation of ± 20%. Two examples showing how to use the proposed equations are provided to guide the practical implementation. In conclusion, the proposed approach of relating microcracks to deterioration is a better method than existing diffusion and sorption models since sulfate attack cause cracking in concrete. Imaging technique provided in this study can also be used to quantitatively analyze concrete samples.

Average-case analysis of power consumption in embedded systems

Power efficiency is one of the most important constraints in the design of embedded systems since such systems are generally driven by batteries with limited energy budget or restricted power supply. In every embedded system, there are one or more processor cores to run the software and interact with the other hardware components of the system. The power consumption of the processor core(s) has an important impact on the total power dissipated in the system. Hence, the processor power optimization is crucial in satisfying the power consumption constraints, and developing low-power embedded systems. A key aspect of research in processor power optimization and management is “power estimation”. Having a fast and accurate method for processor power estimation at design time helps the designer to explore a large space of design possibilities, to make the optimal choices for developing a power efficient processor. Likewise, understanding the processor power dissipation behaviour of a specific software/application is the key for choosing appropriate algorithms in order to write power efficient software. Simulation-based methods for measuring the processor power achieve very high accuracy, but are available only late in the design process, and are often quite slow. Therefore, the need has arisen for faster, higher-level power prediction methods that allow the system designer to explore many alternatives for developing powerefficient hardware and software. The aim of this thesis is to present fast and high-level power models for the prediction of processor power consumption. Power predictability in this work is achieved in two ways: first, using a design method to develop power predictable circuits; second, analysing the power of the functions in the code which repeat during execution, then building the power model based on average number of repetitions. In the first case, a design method called Asynchronous Charge Sharing Logic (ACSL) is used to implement the Arithmetic Logic Unit (ALU) for the 8051 microcontroller. The ACSL circuits are power predictable due to the independency of their power consumption to the input data. Based on this property, a fast prediction method is presented to estimate the power of ALU by analysing the software program, and extracting the number of ALU-related instructions. This method achieves less than 1% error in power estimation and more than 100 times speedup in comparison to conventional simulation-based methods. In the second case, an average-case processor energy model is developed for the Insertion sort algorithm based on the number of comparisons that take place in the execution of the algorithm. The average number of comparisons is calculated using a high level methodology called MOdular Quantitative Analysis (MOQA). The parameters of the energy model are measured for the LEON3 processor core, but the model is general and can be used for any processor. The model has been validated through the power measurement experiments, and offers high accuracy and orders of magnitude speedup over the simulation-based method.

Development of multicomponent models for the prediction of lubricant oil-fuel dilution in internal combustion engines

The current environmental crisis is forcing the automotive industry to face tough challenges for the Internal Combustion Engines development in order to reduce the emissions of pollutants and Greenhouse gases. In this context, in the last decades, the main technological solutions adopted by the manufacturers have been the direct injection and the engine downsizing, which led to the rising of new concerns related to the fuel-cylinder walls physical interaction. The fuel spray possibly impacts the cylinder liner wall, which is wetted by the lubricant oil thus causing the derating of the lubricant properties, increasing the oil consumption, and contaminating the lubricant oil in the crankcase. Also, concerning hydrogen fuelled internal combustion engines, it is likely that the high near-wall temperature, which is typical of the hydrogen flame, results in the evaporation of a portion of the lubricant oil, increasing its consumption. With regards on the innovative combustion systems and their control strategies, optical accessible engines are fundamental tools for experimental investigations on such combustion systems. Though, due to the optical measurement line, optical engines suffer from a high level of blow-by, which must be accounted for. In light of the above, this thesis work aims to develop numerical methodologies with the aim to build useful tools for supporting the design of modern engines. In particular, a one-dimensional modelling of the lubricant oil-fuel dilution and oil evaporation has been performed and coupled with an optimization algorithm to achieve a lubricant oil surrogate. Then, a quasi-dimensional blow-by model has been developed and validated against experimental data. Such model, has been coupled with CFD 3D simulations and directly implemented in CFD 3D. Finally, CFD 3D simulations coupled with the VOF method have been performed in order to validate a methodology for studying the impact of a liquid droplet on a solid surface.

Analysis and prediction of fretting fatigue life.

Fretting fatigue is a fatigue damage process that occurs when two surfaces in contact with each other are subjected to relative micro-slip, causing a reduced fatigue life with respect to the plain fatigue case. Fretting has been now studied deeply for over 50 years, but still no univocal design approach has been universally accepted. This thesis presents a method for predicting the fretting fatigue life of materials based on the material specific fatigue parameters. To validate the method, a set of fretting fatigue experimental tests have been run, using a newly designed specimen. FE analyses of the tests were also run and the SWT parameter was retrieved and it was found to be useful to successfully identify which samples failed. Finally, S-N curves were retrieved by using two different fatigue life predicting methods (CoffinManson and Jahed-Varvani). The two different methods were compared with the experimental results and it was found that the Jahed-Varvani method gave accurate results in terms of fretting fatigue life.

Numerical prediction of the lateral displacement capacity of flexural reinforced concrete shear walls

Previous earthquakes showed that shear wall damage could lead to catastrophic failures of the reinforced concrete building. The lateral load capacity of shear walls needs to be estimated to minimize associated losses during catastrophic events; hence it is necessary to develop and validate reliable and stable numerical methods able to converge to reasonable estimations with minimum computational effort. The beam-column 1-D line element with fiber-type cross-section model is a practical option that yields results in agreement with experimental data. However, shortcomings of using this model to predict the local damage response may come from the fact that the model requires fine calibration of material properties to overcome regularization and size effects. To reduce the mesh-dependency of the numerical model, a regularization method based on the concept of post-yield energy is applied in this work to both the concrete and the steel material constitutive laws to predict the nonlinear cyclic response and failure mechanism of concrete shear walls. Different categories of wall specimens known to produce a different response under in plane cyclic loading for their varied geometric and detailing characteristics are considered in this study, namely: 1) scaled wall specimens designed according to the European seismic design code and 2) unique full-scale wall specimens detailed according to the U.S. design code to develop a ductile behavior under cyclic loading. To test the boundaries of application of the proposed method, two full-scale walls with a mixed shear-flexure response and different values of applied axial load are also considered. The results of this study show that the use of regularized constitutive models considerably enhances the response predictions capabilities of the model with regards to global force-drift response and failure mode. The simulations presented in this thesis demonstrate the proposed model to be a valuable tool for researchers and engineers.

Evaluation Metrics and Transfer Learning for Sales Prediction

Sales prediction plays a huge role in modern business strategies. One of it's many use cases revolves around estimating the effects of promotions. While promotions generally have a positive effect on sales of the promoted product, they can also have a negative effect on those of other products. This phenomenon is calles sales cannibalisation. Sales cannibalisation can pose a big problem to sales forcasting algorithms. A lot of times, these algorithms focus on sales over time of a single product in a single store (a couple). This research focusses on using knowledge of a product across multiple different stores. To achieve this, we applied transfer learning on a neural model developed by Kantar Consulting to demo an approach to estimating the effect of cannibalisation. Our results show a performance increase of between 10 and 14 percent. This is a very good and desired result, and Kantar will use the approach when integrating this test method into their actual systems.

A Highly Improved Method For Sensitive Determination Of Amitriptyline In Pharmaceutical Formulations Using An Unmodified Carbon Nanotube Electrode In The Presence Of Sulfuric Acid.

The present paper describes a novel, simple and reliable differential pulse voltammetric method for determining amitriptyline (AMT) in pharmaceutical formulations. It has been described for many authors that this antidepressant is electrochemically inactive at carbon electrodes. However, the procedure proposed herein consisted in electrochemically oxidizing AMT at an unmodified carbon nanotube paste electrode in the presence of 0.1 mol L(-1) sulfuric acid used as electrolyte. At such concentration, the acid facilitated the AMT electroxidation through one-electron transfer at 1.33 V vs. Ag/AgCl, as observed by the augmentation of peak current. Concerning optimized conditions (modulation time 5 ms, scan rate 90 mV s(-1), and pulse amplitude 120 mV) a linear calibration curve was constructed in the range of 0.0-30.0 μmol L(-1), with a correlation coefficient of 0.9991 and a limit of detection of 1.61 μmol L(-1). The procedure was successfully validated for intra- and inter-day precision and accuracy. Moreover, its feasibility was assessed through analysis of commercial pharmaceutical formulations and it has been compared to the UV-vis spectrophotometric method used as standard analytical technique recommended by the Brazilian Pharmacopoeia.

Exploring Iris Colour Prediction And Ancestry Inference In Admixed Populations Of South America.

New DNA-based predictive tests for physical characteristics and inference of ancestry are highly informative tools that are being increasingly used in forensic genetic analysis. Two eye colour prediction models: a Bayesian classifier - Snipper and a multinomial logistic regression (MLR) system for the Irisplex assay, have been described for the analysis of unadmixed European populations. Since multiple SNPs in combination contribute in varying degrees to eye colour predictability in Europeans, it is likely that these predictive tests will perform in different ways amongst admixed populations that have European co-ancestry, compared to unadmixed Europeans. In this study we examined 99 individuals from two admixed South American populations comparing eye colour versus ancestry in order to reveal a direct correlation of light eye colour phenotypes with European co-ancestry in admixed individuals. Additionally, eye colour prediction following six prediction models, using varying numbers of SNPs and based on Snipper and MLR, were applied to the study populations. Furthermore, patterns of eye colour prediction have been inferred for a set of publicly available admixed and globally distributed populations from the HGDP-CEPH panel and 1000 Genomes databases with a special emphasis on admixed American populations similar to those of the study samples.

Neck Circumference As A New Anthropometric Indicator For Prediction Of Insulin Resistance And Components Of Metabolic Syndrome In Adolescents: Brazilian Metabolic Syndrome Study.

To evaluate the correlation between neck circumference and insulin resistance and components of metabolic syndrome in adolescents with different adiposity levels and pubertal stages, as well as to determine the usefulness of neck circumference to predict insulin resistance in adolescents. Cross-sectional study with 388 adolescents of both genders from ten to 19 years old. The adolescents underwent anthropometric and body composition assessment, including neck and waist circumferences, and biochemical evaluation. The pubertal stage was obtained by self-assessment, and the blood pressure, by auscultation. Insulin resistance was evaluated by the Homeostasis Model Assessment-Insulin Resistance. The correlation between two variables was evaluated by partial correlation coefficient adjusted for the percentage of body fat and pubertal stage. The performance of neck circumference to identify insulin resistance was tested by Receiver Operating Characteristic Curve. After the adjustment for percentage body fat and pubertal stage, neck circumference correlated with waist circumference, blood pressure, triglycerides and markers of insulin resistance in both genders. The results showed that the neck circumference is a useful tool for the detection of insulin resistance and changes in the indicators of metabolic syndrome in adolescents. The easiness of application and low cost of this measure may allow its use in Public Health services.

Influence Of Delivery Method On Neuroprotection By Bone Marrow Mononuclear Cell Therapy Following Ventral Root Reimplantation With Fibrin Sealant.

The present work compared the local injection of mononuclear cells to the spinal cord lateral funiculus with the alternative approach of local delivery with fibrin sealant after ventral root avulsion (VRA) and reimplantation. For that, female adult Lewis rats were divided into the following groups: avulsion only, reimplantation with fibrin sealant; root repair with fibrin sealant associated with mononuclear cells; and repair with fibrin sealant and injected mononuclear cells. Cell therapy resulted in greater survival of spinal motoneurons up to four weeks post-surgery, especially when mononuclear cells were added to the fibrin glue. Injection of mononuclear cells to the lateral funiculus yield similar results to the reimplantation alone. Additionally, mononuclear cells added to the fibrin glue increased neurotrophic factor gene transcript levels in the spinal cord ventral horn. Regarding the motor recovery, evaluated by the functional peroneal index, as well as the paw print pressure, cell treated rats performed equally well as compared to reimplanted only animals, and significantly better than the avulsion only subjects. The results herein demonstrate that mononuclear cells therapy is neuroprotective by increasing levels of brain derived neurotrophic factor (BDNF) and glial derived neurotrophic factor (GDNF). Moreover, the use of fibrin sealant mononuclear cells delivery approach gave the best and more long lasting results.

Uv-vis Spectra As An Alternative To The Lowry Method For Quantify Hair Damage Induced By Surfactants.

It is well known that long term use of shampoo causes damage to human hair. Although the Lowry method has been widely used to quantify hair damage, it is unsuitable to determine this in the presence of some surfactants and there is no other method proposed in literature. In this work, a different method is used to investigate and compare the hair damage induced by four types of surfactants (including three commercial-grade surfactants) and water. Hair samples were immersed in aqueous solution of surfactants under conditions that resemble a shower (38 °C, constant shaking). These solutions become colored with time of contact with hair and its UV-vis spectra were recorded. For comparison, the amount of extracted proteins from hair by sodium dodecyl sulfate (SDS) and by water were estimated by the Lowry method. Additionally, non-pigmented vs. pigmented hair and also sepia melanin were used to understand the washing solution color and their spectra. The results presented herein show that hair degradation is mostly caused by the extraction of proteins, cuticle fragments and melanin granules from hair fiber. It was found that the intensity of solution color varies with the charge density of the surfactants. Furthermore, the intensity of solution color can be correlated to the amount of proteins quantified by the Lowry method as well as to the degree of hair damage. UV-vis spectrum of hair washing solutions is a simple and straightforward method to quantify and compare hair damages induced by different commercial surfactants.

Refractive Error In School Children In Campinas, Brazil.

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Trichomes Related To An Unusual Method Of Water Retention And Protection Of The Stem Apex In An Arid Zone Perennial Species.

It is well known that trichomes protect plant organs, and several studies have investigated their role in the adaptation of plants to harsh environments. Recent studies have shown that the production of hydrophilic substances by glandular trichomes and the deposition of this secretion on young organs may facilitate water retention, thus preventing desiccation and favouring organ growth until the plant develops other protective mechanisms. Lychnophora diamantinana is a species endemic to the Brazilian 'campos rupestres' (rocky fields), a region characterized by intense solar radiation and water deficits. This study sought to investigate trichomes and the origin of the substances observed on the stem apices of L. diamantinana. Samples of stem apices, young and expanded leaves were studied using standard techniques, including light microscopy and scanning and transmission electron microscopy. Histochemical tests were used to identify the major groups of metabolites present in the trichomes and the hyaline material deposited on the apices. Non-glandular trichomes and glandular trichomes were observed. The material deposited on the stem apices was hyaline, highly hydrophilic and viscous. This hyaline material primarily consists of carbohydrates that result from the partial degradation of the cell wall of uniseriate trichomes. This degradation occurs at the same time that glandular trichomes secrete terpenoids, phenolic compounds and proteins. These results suggest that the non-glandular trichomes on the leaves of L. diamantinana help protect the young organ, particularly against desiccation, by deposition of highly hydrated substances on the apices. Furthermore, the secretion of glandular trichomes probably repels herbivore and pathogen attacks.