Conversion of a Micro, Glow-Ignition, Two-Stroke Engine from Nitromethane-Methanol Blend Fuel to Military Jet Propellant (JP-8)

The goal of the thesis "Conversion of a Micro, Glow-Ignition, Two-Stroke Engine from Nitromethane-Methanol Blend Fuel to Military Jet Propellant (JP-8)" was to demonstrate the ability to operate a small engine on JP-8 and was completed in two phases. The first phase included choosing, developing a test stand for, and baseline testing a nitromethane-methanol-fueled engine. The chosen engine was an 11.5 cc, glow-ignition, two-stroke engine designed for remote-controlled helicopters. A micro engine test stand was developed to load and motor the engine. Instrumentation specific to the low flow rates and high speeds of the micro engine was developed and used to document engine behavior. The second phase included converting the engine to operate on JP-8, completing JP-8-fueled steady-state testing, and comparing the performance of the JP-8-fueled engine to the nitromethane-methanol-fueled engine. The conversion was accomplished through a novel crankcase heating method; by heating the crankcase for an extended period of time, a flammable fuel-air mixture was generated in the crankcase scavenged engine, which greatly improved starting times. To aid in starting and steady-state operation, yttrium-zirconia impregnated resin (i.e. ceramic coating) was applied to the combustion surfaces. This also improved the starting times of the JP-8-fueled engine and ultimately allowed for a 34-second starting time. Finally, the steady-state data from both the nitromethane-methanol and JP-8-fueled micro engine were compared. The JP-8-fueled engine showed signs of increased engine friction while having higher indicated fuel conversion efficiency and a higher overall system efficiency. The minimal ability of JP-8 to cool the engine via evaporative effects, however, created the necessity of increased cooling air flow. The conclusion reached was that JP-8-fueled micro engines could be viable in application, but not without additional research being conducted on combustion phenomenon and cooling requirements.

Development of a 1-D Catalyzed Diesel Particulate Filter Model for Simulation of the Performance and the Oxidation of Particulate Matter and Nitrogen Oxides Using Passive Oxidation and Active Regeneration Engine Experimental Data

Back-pressure on a diesel engine equipped with an aftertreatment system is a function of the pressure drop across the individual components of the aftertreatment system, typically, a diesel oxidation catalyst (DOC), catalyzed particulate filter (CPF) and selective catalytic reduction (SCR) catalyst. Pressure drop across the CPF is a function of the mass flow rate and the temperature of the exhaust flowing through it as well as the mass of particulate matter (PM) retained in the substrate wall and the cake layer that forms on the substrate wall. Therefore, in order to control the back-pressure on the engine at low levels and to minimize the fuel consumption, it is important to control the PM mass retained in the CPF. Chemical reactions involving the oxidation of PM under passive oxidation and active regeneration conditions can be utilized with computer numerical models in the engine control unit (ECU) to control the pressure drop across the CPF. Hence, understanding and predicting the filtration and oxidation of PM in the CPF and the effect of these processes on the pressure drop across the CPF are necessary for developing control strategies for the aftertreatment system to reduce back-pressure on the engine and in turn fuel consumption particularly from active regeneration. Numerical modeling of CPF's has been proven to reduce development time and the cost of aftertreatment systems used in production as well as to facilitate understanding of the internal processes occurring during different operating conditions that the particulate filter is subjected to. A numerical model of the CPF was developed in this research work which was calibrated to data from passive oxidation and active regeneration experiments in order to determine the kinetic parameters for oxidation of PM and nitrogen oxides along with the model filtration parameters. The research results include the comparison between the model and the experimental data for pressure drop, PM mass retained, filtration efficiencies, CPF outlet gas temperatures and species (NO2) concentrations out of the CPF. Comparisons of PM oxidation reaction rates obtained from the model calibration to the data from the experiments for ULSD, 10 and 20% biodiesel-blended fuels are presented.

A Metadata Thesaurus: Report on the Knowledge Organization of the Dublin Core Metadata Initiative Conference Proceedings

2003 Dublin Core Metadata Initiative Proceedings appear in both print and online form. In order to aid search and retrieval of this growing body of research a researchers at the University of Washington and Siderean Software have started a metadata thesaurus. This poster reports on those efforts.

Role of the human chymase (CMA1) in the conversion of big-endothelin-1 to endothelin-1 (1-31)

Abstract : The chymase-dependant pathway responsible for converting Big ET-1 to ET-1 was established in vitro. It has only been recently, in 2009, that our group demonstrated that the conversion of Big ET-1 to ET-1 (1-31) can occur in vivo in mice (Simard et al., 2009), knowing that ET-1 (1-31) is converted to ET-1 via NEP in vivo (Fecteau et al., 2005). In addition, our laboratory demonstrated in 2013 that mMCP-4, the murine analogue of human chymase, produces ET-1 (1-31) from the Big ET-1 precursor (Houde et al. 2013). Thus far, in the literature, there are no specific characterizations of recombinant chymases (human or murine). In fact, the group of Murakami published in 1995 a study characterizing the CMA1 (human chymase) in a chymostatin-dependent fashion, using Angiotensin I as a substrate (Murakami et al., 1995). However, chymostatin is a non-specific inhibitor of chymase. It has been shown that chymostatin can inhibit elastase, an enzyme that can convert Angiotensin I to Angiotensin II (Becari et al., 2005). Based on these observations, the proposed hypothesis in the present study suggests that recombinant as well as extracted CMA1 from LUVA (human mast cell line), in addition to soluble fractions of human aortas, convert Big ET-1 into ET-1 (1-31 ) in a TY-51469 (a chymase-specific inhibitor) sensitive manner. In a second component, we studied the enzyme kinetics of CMA1 with regard to the Big ET-1 and Ang I substrate. The affinity of CMA1 against Big ET-1 was greater compared to Ang I (KM Big ET- 1: 12.55 μM and Ang I: 37.53 μM). However, CMA1 was more effective in cleaving Ang I compared to Big ET-1 (Kcat / KM Big ET-1: 6.57 x 10-5 μM-1.s-1 and Ang I: 1.8 x 10-4 ΜM-1.s- 1). In a third component involving in vivo experiments, the pressor effects of Big ET-1, ET-1 and Ang I were tested in conscious mMCP-4 KO mice compared to wild-type mice. The increase in mean arterial pressure after administration of Big ET-1 was greater in wild-type mice compared to mMCP- 4 KO mice. This effect was not observed after administration of ET-1 and / or Ang I.

One-dimensional Model for Fluids of Third-grade in Tubes with Constant Radius

Our goal in this paper is to extend previous results obtained for Newtonian and secondgrade fluids to third-grade fluids in the case of an axisymmetric, straight, rigid and impermeable tube with constant cross-section using a one-dimensional hierarchical model based on the Cosserat theory related to fluid dynamics. In this way we can reduce the full threedimensional system of equations for the axisymmetric unsteady motion of a non-Newtonian incompressible third-grade fluid to a system of equations depending on time and on a single spatial variable. Some numerical simulations for the volume flow rate and the the wall shear stress are presented.

Single diode model parameters analysis of photovoltaic cell

In this paper it is proposed to obtain enhanced and more efficient parameters model from generalized five parameters (single diode) model of PV cells. The paper also introduces, describes and implements a seven parameter model for photovoltaic cell (PV cell) which includes two internal parameters and five external parameters. To obtain the model the mathematical equations and an equivalent circuit consisting of a photo generated current source, a series resistor, a shunt resistor and a diode is used. The fundamental equation of PV cell is used to analyse and best fit the observation data. Especially bisection iteration method is used to obtain the expected result and to understand the deviation of changes in different parameters situation at various conditions respectively. The produced model can be used of measuring and understanding the actions of photovoltaic cells for certain changes and parameters extraction. The effect is also studied with I-V and P-V characteristics of PV cells though it is a challenge to optimize the output with real time simulation. The working procedure is also discussed and an experiment presented to get the closure and insight about the produced model and to decide upon the model validity. At the end, we observed that the result of the simulation is very close to the produced model.

Open-cell Metallic Foams for the Electrochemical Conversion of Biomass-derived Compounds

The electrochemical conversion is a sustainable way for the production of added-value products, operating in mild conditions, using in-situ generated hydrogen/oxygen by water and avoiding the use of high H2/O2 pressures. The aim of this work is to investigate the electrocatalytic conversion of 5-hydroxymetilfurfural (HMF) and D-glucose, in alkaline media, using metallic open-cell foams based-catalysts. The electrochemical hydrogenation of HMF to 2,5-bis(hydroxymethyl)furan (BHMF) was performed using nanostructured Ag, deposited by galvanic displacement (GD) or electrodeposition (ED), on Cu foam, obtaining AgCu bimetallic nanoparticles (ED) or dendrites (GD) which enhanced electroactive surface area, charge and mass transfer, than bare foams. In diluted 0.02M HMF solutions, Ag/Cu samples selectively produce BHMF; the large surface area enhanced the productivity, compared to their 2D counterparts. Furthermore, at more concentrated solutions (0.05 – 0.10M) a gradually decrease of selectivity is observed. The performances of the electrodes is stable during the catalytic tests but a Cu-enrichment of particles occurred. The performances of Ni foam-based catalysts, obtained by calcination of Ni foam or by electrodeposition of Ni-hydroxide/Ni and Ni particle/Ni, were firstly investigated for the selective electrochemical oxidation of D-glucose toward gluconic acid (GO) and glucaric acid (GA). Then, the calcined catalyst was chosen to study the influence of the reaction conditions on the reaction mechanism. The GO and GA selectivities increase with the charge passed, while the formation of by-products from C-C cleavage/retro-aldol process is maximum at low charge. The fructose obtained from glucose isomerization favours the formation of by-products. The best glucose/NaOH ratio is between 0.5 and 0.1: higher values suppress the OER, while lower values favour the formation of low molecular weight products. The increases of the potential enhance the GO selectivity, nevertheless higher GA selectivity is observed at 0.6 – 0.7V vs SCE, confirmed by catalytic test performed in gluconate (30-35% GA selectivity).

Model-Based validation of Driver Drowsiness Detection System for ADAS

The work described in this Master’s Degree thesis was born after the collaboration with the company Maserati S.p.a, an Italian luxury car maker with its headquarters located in Modena, in the heart of the Italian Motor Valley, where I worked as a stagiaire in the Virtual Engineering team between September 2021 and February 2022. This work proposes the validation using real-world ECUs of a Driver Drowsiness Detection (DDD) system prototype based on different detection methods with the goal to overcome input signal losses and system failures. Detection methods of different categories have been chosen from literature and merged with the goal of utilizing the benefits of each of them, overcoming their limitations and limiting as much as possible their degree of intrusiveness to prevent any kind of driving distraction: an image processing-based technique for human physical signals detection as well as methods based on driver-vehicle interaction are used. A Driver-In-the-Loop simulator is used to gather real data on which a Machine Learning-based algorithm will be trained and validated. These data come from the tests that the company conducts in its daily activities so confidential information about the simulator and the drivers will be omitted. Although the impact of the proposed system is not remarkable and there is still work to do in all its elements, the results indicate the main advantages of the system in terms of robustness against subsystem failures and signal losses.

Aquivion-based spray freeze-dried composite catalysts for the cascade conversion of furfural to γ-valerolactone

Furfural is one of the most promising biomass derived platform molecules. It is to this day produced in volumes above 300 ktons per year from the hydrolysis and dehydration of hemicellulose, one of the main components of lignocellulosic biomass. While the majority of the yearly production is destined to selective reduction to furfuryl alcohol for the production of furan resins, these molecules hold great potential for the production of more valuable chemicals, fuels, fuel additives and solvents. Among these products are alkyl levulinates and γ-valerolactone. To convert furfural to these target products, a cascade process involving Lewis acidity-catalysed reduction steps and Brønsted acidity-catalysed steps. In order to develop catalysts capable of promoting the one-pot domino reaction from furfural to γ-valerolactone, the two kinds of acidity must both be present. To this end, in this work, the spray freeze-drying technique is employed to combine the high activity and strong Brønsted acidity of Aquivion with the structural properties and Lewis acidity of different supporting metal oxide, forming composite catalysts. The flexibility of the spray freeze-drying technique and the modulable composition of the catalysts allowed a thorough study of the complex network of equilibria underlying the cascade reaction, while achieving high selectivities towards the final product.

Modeling and Model Predictive Control of an Industrial Hydraulic System

This thesis aims to illustrate the construction of a mathematical model of a hydraulic system, oriented to the design of a model predictive control (MPC) algorithm. The modeling procedure starts with the basic formulation of a piston-servovalve system. The latter is a complex non linear system with some unknown and not measurable effects that constitute a challenging problem for the modeling procedure. The first level of approximation for system parameters is obtained basing on datasheet informations, provided workbench tests and other data from the company. Then, to validate and refine the model, open-loop simulations have been made for data matching with the characteristics obtained from real acquisitions. The final developed set of ODEs captures all the main peculiarities of the system despite some characteristics due to highly varying and unknown hydraulic effects, like the unmodeled resistive elements of the pipes. After an accurate analysis, since the model presents many internal complexities, a simplified version is presented. The latter is used to linearize and discretize correctly the non linear model. Basing on that, a MPC algorithm for reference tracking with linear constraints is implemented. The results obtained show the potential of MPC in this kind of industrial applications, thus a high quality tracking performances while satisfying state and input constraints. The increased robustness and flexibility are evident with respect to the standard control techniques, such as PID controllers, adopted for these systems. The simulations for model validation and the controlled system have been carried out in a Python code environment.

Root cause analysis applied to a finite element model's refinement of a negative stiffness structure

Negative Stiffness Structures are mechanical systems that require a decrease in the applied force to generate an increase in displacement. They are structures that possess special characteristics such as snap-through and bi-stability. All of these features make them particularly suitable for different applications, such as shock-absorption, vibration isolation and damping. From this point of view, they have risen awareness of their characteristics and, in order to match them to the application needed, a numerical simulation is of great interest. In this regard, this thesis is a continuation of previous studies in a circular negative stiffness structure and aims at refine the numerical model by presenting a new solution. To that end, an investigation procedure is needed. Amongst all of the methods available, root cause analysis was the chosen one to perform the investigation since it provides a clear view of the problem under analysis and a categorization of all the causes behind it. As a result of the cause-effect analysis, the main causes that have influence on the numerical results were obtained. Once all of the causes were listed, solutions to them were proposed and it led to a new numerical model. The numerical model proposed was of nonlinear type of analysis with hexagonal elements and a hyperelastic material model. The results were analyzed through force-displacement curves, allowing for the visualization of the structure’s energy recovery. When compared to the results obtained from the experimental part, it is evident that the trend is similar and the negative stiffness behaviour is present.

Conversão de registros em XML para MARC 21: um modelo baseado em folhas de estilo XSLT

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Factores de riesgo preoperatorios asociados a conversión a técnica abierta en colecistectomía laparoscópica de urgencia

Introducción: la colecistectomía laparoscópica es la técnica de elección en pacientes con indicación de extracción quirúrgica de la vesícula; sin embargo, en promedio 20% de éstos requieren conversión a técnica abierta. En este estudio se evaluaron los factores de riesgo preoperatorios para conversión en colecistectomía laparoscópica de urgencia. Metodología: se realizó un estudio de casos y controles no pareado. Se obtuvo información sociodemográfica y de variables de interés de los registros de historias clínicas de pacientes operados entre el 2013 y 2016. Se identificaron los motivos de conversión de técnica quirúrgica. Se caracterizó la población de estudio y se estimaron asociaciones según la naturaleza de las variables. Mediante un análisis de regresión logística se ajustaron posibles variables de confusión. Resultados: se analizaron los datos de 444 pacientes (111 casos y 333 controles). La causa de conversión más frecuente fue la dificultad técnica (50,5%). Se encontró que la mayor edad, el sexo masculino, el antecedente de cirugía abierta en hemiabdomen superior, el signo de Murphy clínico positivo, la dilatación de la vía biliar, la leucocitosis y la mayor experiencia del cirujano, fueron factores de riesgo para conversión. Se encontró un área bajo la curva ROC= 0,743 (IC95% 0,692–0,794, p= <0,001). Discusión: existen unos factores que se asocian a mayor riesgo de conversión en colecistectomía laparoscópica. La mayoría se relacionan con un proceso inflamatorio más severo, por lo que se debe evitar la prolongación del tiempo de espera entre el inicio de los síntomas y la extirpación quirúrgica de la vesícula.

Knowledge Licensing in a Model of R&D-driven Endogenous Growth

In this paper I present an endogenous growth model where the engine of growth is in-house R&D performed by high-tech firms. I model knowledge (patent) licensing among high-tech firms. I show that if there is knowledge licensing, high-tech firms innovate more and economic growth is higher than in cases when there are knowledge spillovers or there is no exchange of knowledge among high-tech firms. However, in case when there is knowledge licensing the number of high-tech firms is lower than in cases when there are knowledge spillovers or there is no exchange of knowledge.