Thermodynamic analysis and comparison of downdraft gasifiers integrated with gas turbine, spark and compression ignition engines for distributed power generation

The objective of the present article is to assess and compare the performance of electricity generation systems integrated with downdraft biomass gasifiers for distributed power generation. A model for estimating the electric power generation of internal combustion engines and gas turbines powered by syngas was developed. First, the model determines the syngas composition and the lower heating value; and second, these data are used to evaluate power generation in Otto, Diesel, and Brayton cycles. Four synthesis gas compositions were tested for gasification with: air; pure oxygen; 60% oxygen with 40% steam; and 60% air with 40% steam. The results show a maximum power ratio of 0.567 kWh/Nm(3) for the gas turbine system, 0.647 kWh/Nm(3) for the compression ignition engine, and 0.775 kWh/Nm(3) for the spark-ignition engine while running on synthesis gas which was produced using pure oxygen as gasification agent. When these three systems run on synthesis gas produced using atmospheric air as gasification agent, the maximum power ratios were 0.274 kWh/Nm(3) for the gas turbine system, 0.302 kWh/Nm(3) for CIE, and 0.282 kWh/Nm(3) for SIE. The relationship between power output and synthesis gas flow variations is presented as is the dependence of efficiency on compression ratios. Since the maximum attainable power ratio of CIE is higher than that of SIE for gasification with air, more research should be performed on utilization of synthesis gas in CIE. (C) 2014 Elsevier Ltd. All rights reserved.

Pb0.90Ba0.10Zr0.40Ti0.60O3 Nanostructured Ferroelectric Ceramics Prepared by Spark Plasma Sintering

Nanostructured Pb0.90Ba0.10Zr0.40Ti0.60O3 dense ceramics presenting an average grain size of 62 +/- 5 nm was prepared by the polymeric precursor method and using the spark plasma sintering technique. The dielectric permittivity curves versus temperature exhibit broad anomaly, indicative of a diffuse phase transition. This result can be explained by the spread of Curie temperatures which are expected to depend on the degree of tetragonality related to the grain size distribution. A pronounced decrease in the maximum of the dielectric permittivity value is attributed to the existence of a large amount of grain boundaries which are non-ferroelectric regions.

Consolidation of Bi-2223 superconducting powders by spark plasma sintering

The spark plasma sintering (SPS) technique, by using a compacting pressure of 50 MPa, was used to consolidate pre-reacted powders of Bi1.65Pb0.35Sr2Ca2Cu3O10+delta (Bi-2223). The influence of the consolidation temperature, T-D, on the structural and electrical properties has been investigated and compared with those of a reference sample synthesized by the traditional solid-state reaction method and subjected to the same compacting pressure. From the X-ray diffraction patterns, performed in both powder and pellet samples, we have found that the dominant phase is the Bi-2223 in all samples but traces of the Bi2Sr2CaCu2O8+x (Bi-2212) were identified. Their relative density were similar to 85% of the theoretical density and the temperature dependence of the electrical resistivity, rho(T), indicated that increasing T-D results in samples with low oxygen content because the SPS is performed in vacuum. Features of the rho(T) data, as the occurrence of normal-state semiconductor-like behavior of rho(T) and the double resistive superconducting transition, are consistent with samples comprised of grains with shell-core morphology in which the shell is oxygen deficient. The SPS samples also exhibited superconducting critical current density at 77 K, J(c)(77K), between 2 and 10A/cm(2), values much smaller than similar to 22A/cm(2) measured in the reference sample. Reoxygenation of the SPS samples, post-annealed in air at different temperatures and times, was found to improve their microstructural and transport properties. Besides the suppression of the Bragg peaks belonging to the Bi-2212 phase, the superconducting properties of the post-annealed samples and particularly J(c)(77K) were comparable or better than those corresponding to the reference sample. Post-annealed samples at 750 degrees C for 5min exhibited J(c)(77K) similar to 130A/cm(2) even when uniaxially pressed at only 50 MPa. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4768257]

Bone tissue, cellular, and molecular responses to titanium implants treated by anodic spark deposition

A myriad of titanium (Ti) surface modifications has been proposed to hasten the osseointegration. In this context, the aim of this study was to perform histomorphometric, cellular, and molecular analyses of the bone tissue grown in close contact with Ti implants treated by anodic spark deposition (ASD-AK). Acid-etched (AE) Ti implants either untreated or submitted to ASD-AK were placed into dog mandibles and retrieved at 3 and 8 weeks. It was noticed that both implants, AE and ASD-AK, were osseointegrated at 3 and 8 weeks. Histomorphometric analysis showed differences between treatments only for bone-to-implant contact, being higher on AE implants. Although not backed by histomorphometric results, gene expression of key bone markers was higher for bone grown in close contact with ASD-AK and for cells harvested from these fragments and cultured until subconfluence. Cell proliferation at days 7 and 10 and alkaline phosphatase activity at day 10 was higher on AE surfaces. No statistical significant difference was noticed for extracellular matrix mineralization at 17 days. Our results have shown that the Ti fixtures treated by ASD-AK allowed in vivo osseointegration and induced higher expression of key markers of osteoblast phenotype, suggesting that this surface treatment could be considered to produce implants for clinical applications. (c) 2012 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 100A:30923098, 2012.

Spark Plasma Sintering of Si3N4-based Ceramics : Sintering mechanism-Tailoring microstructure-Evaluationg properties

Spark Plasma Sintering (SPS) is a promising rapid consolidation technique that allows a better understanding and manipulating of sintering kinetics and therefore makes it possible to obtain Si3N4-based ceramics with tailored microstructures, consisting of grains with either equiaxed or elongated morphology. The presence of an extra liquid phase is necessary for forming tough interlocking microstructures in Yb/Y-stabilised α-sialon by HP. The liquid is introduced by a new method, namely by increasing the O/N ratio in the general formula RExSi12-(3x+n)Al3x+nOnN16-n while keeping the cation ratios of RE, Si and Al constant. Monophasic α-sialon ceramics with tailored microstructures, consisting of either fine equiaxed or elongated grains, have been obtained by using SPS, whether or not such an extra liquid phase is involved. The three processes, namely densification, phase transformation and grain growth, which usually occur simultaneously during conventional HP consolidation of Si3N4-based ceramics, have been precisely followed and separately investigated in the SPS process. The enhanced densification is attributed to the non-equilibrium nature of the liquid phase formed during heating. The dominating mechanism during densification is the enhanced grain boundary sliding accompanied by diffusion- and/or reaction-controlled processes. The rapid grain growth is ascribed to a dynamic ripening mechanism based on the formation of a liquid phase that is grossly out of equilibrium, which in turn generates an extra chemical driving force for mass transfer. Monophasic α-sialon ceramics with interlocking microstructures exhibit improved damage tolerance. Y/Yb- stabilised monophasic α-sialon ceramics containing approximately 3 vol% liquid with refined interlocking microstructures have excellent thermal-shock resistance, comparable to the best β-sialon ceramics with 20 vol% additional liquid phase prepared by HP. The obtained sialon ceramics with fine-grained microstructure show formidably improved superplasticity in the presence of an electric field. The compressive strain rate reaches the order of 10-2 s-1 at temperatures above 1500oC, that is, two orders of magnitude higher than that has been realised so far by any other conventional approaches. The high deformation rate recorded in this work opens up possibilities for making ceramic components with complex shapes through super-plastic forming.

Analisi e valutazione della piattaforma Spark

Negli ultimi anni i dati, la loro gestione e gli strumenti per la loro analisi hanno subito una trasformazione. Si è visto un notevole aumento dei dati raccolti dagli utenti, che si aggira tra il 40 e il 60 percento annuo, grazie ad applicazioni web, sensori, ecc.. Ciò ha fatto nascere il termine Big Data, con il quale ci si riferisce a dataset talmente grandi che non sono gestibili da sistemi tradizionali, come DBMS relazionali in esecuzione su una singola macchina. Infatti, quando la dimensione di un dataset supera pochi terabyte, si è obbligati ad utilizzare un sistema distribuito, in cui i dati sono partizionati su più macchine. Per gestire i Big Data sono state create tecnologie che riescono ad usare la potenza computazionale e la capacità di memorizzazione di un cluster, con un incremento prestazionale proporzionale al numero di macchine presenti sullo stesso. Il più utilizzato di questi sistemi è Hadoop, che offre un sistema per la memorizzazione e l’analisi distribuita dei dati. Grazie alla ridondanza dei dati ed a sofisticati algoritmi, Hadoop riesce a funzionare anche in caso di fallimento di uno o più macchine del cluster, in modo trasparente all’utente. Su Hadoop si possono eseguire diverse applicazioni, tra cui MapReduce, Hive e Apache Spark. É su quest’ultima applicazione, nata per il data processing, che è maggiormente incentrato il progetto di tesi. Un modulo di Spark, chiamato Spark SQL, verrà posto in confronto ad Hive nella velocità e nella flessibilità nell’eseguire interrogazioni su database memorizzati sul filesystem distribuito di Hadoop.

Sviluppo di un modello di costo per Spark Sql

La quantità di dati che vengono generati e immagazzinati sta aumentando sempre più grazie alle nuove tecnologie e al numero di utenti sempre maggiore. Questi dati, elaborati correttamente, permettono quindi di ottenere delle informazioni di valore strategico che aiutano nell’effettuare decisioni aziendali a qualsiasi livello, dalla produzione fino al marketing. Sono nati soprattutto negli ultimi anni numerosi framework proprietari e open source che permettono l'elaborazione di questi dati sfruttando un cluster. In particolare tra i più utilizzati e attivi in questo momento a livello open source troviamo Hadoop e Spark. Obiettivo di questa tesi è realizzare un modello di Spark per realizzare una funzione di costo che sia non solo implementabile all’interno dell’ottimizzatore di Spark SQL, ma anche per poter effettuare delle simulazioni di esecuzione di query su tale sistema. Si è quindi studiato nel dettaglio con ducumentazione e test il comportamento del sistema per realizzare un modello. I dati ottenuti sono infine stati confrontati con dati sperimentali ottenuti tramite l'utilizzo di un cluster. Con la presenza di tale modello non solo risulta possibile comprendere in maniera più approfondita il reale comportamento di Spark ma permette anche di programmare applicazioni più efficienti e progettare con maggiore precisione sistemi per la gestione dei dataset che sfruttino tali framework.

Novel approach to complex pulmonary arteriovenous malformation embolization using detachable coils and Amplatzer vascular plugs

We evaluated the feasibility of a modified embolization technique of pulmonary arteriovenous malformations (PAVM) using venous sac embolization with detachable coils combined with the feeding artery embolization with the Amplatzer vascular plug (AVP).

Stochastic knock detection model for spark ignited engines

This report presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. Knock Signal Simulator (KSS) was developed as the plant model for the engine. The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies. The SKD method is implemented in Knock Detection Module (KDM) which processes the knock intensities generated by KSS with a stochastic distribution estimation algorithm and outputs estimates of high and low knock intensity levels which characterize knock and reference level respectively. These estimates are then used to determine a knock factor which provides quantitative measure of knock level and can be used as a feedback signal to control engine knock. The knock factor is analyzed and compared with a traditional knock detection method to detect engine knock under various engine operating conditions. To verify the effectiveness of the SKD method, a knock controller was also developed and tested in a model-in-loop (MIL) system. The objective of the knock controller is to allow the engine to operate as close as possible to its border-line spark-timing without significant engine knock. The controller parameters were tuned to minimize the cycle-to-cycle variation in spark timing and the settling time of the controller in responding to step increase in spark advance resulting in the onset of engine knock. The simulation results showed that the combined system can be used adequately to model engine knock and evaluated knock control strategies for a wide range of engine operating conditions.

Parametric combustion modeling for ethanol-gasoline fuelled spark ignition engines

Ethanol-gasoline fuel blends are increasingly being used in spark ignition (SI) engines due to continued growth in renewable fuels as part of a growing renewable portfolio standard (RPS). This leads to the need for a simple and accurate ethanol-gasoline blends combustion model that is applicable to one-dimensional engine simulation. A parametric combustion model has been developed, integrated into an engine simulation tool, and validated using SI engine experimental data. The parametric combustion model was built inside a user compound in GT-Power. In this model, selected burn durations were computed using correlations as functions of physically based non-dimensional groups that have been developed using the experimental engine database over a wide range of ethanol-gasoline blends, engine geometries, and operating conditions. A coefficient of variance (COV) of gross indicated mean effective pressure (IMEP) correlation was also added to the parametric combustion model. This correlation enables the cycle combustion variation modeling as a function of engine geometry and operating conditions. The computed burn durations were then used to fit single and double Wiebe functions. The single-Wiebe parametric combustion compound used the least squares method to compute the single-Wiebe parameters, while the double-Wiebe parametric combustion compound used an analytical solution to compute the double-Wiebe parameters. These compounds were then integrated into the engine model in GT-Power through the multi-Wiebe combustion template in which the values of Wiebe parameters (single-Wiebe or double-Wiebe) were sensed via RLT-dependence. The parametric combustion models were validated by overlaying the simulated pressure trace from GT-Power on to experimentally measured pressure traces. A thermodynamic engine model was also developed to study the effect of fuel blends, engine geometries and operating conditions on both the burn durations and COV of gross IMEP simulation results.

EFFECT OF ELECTRICAL DISCHARGE PATTERN ON SPARK IGNITED FLAME KERNEL DEVELOPMENT

Fuel-lean combustion and exhaust gas recirculation (EGR) in spark ignition engines improve engine efficiency and reduce emission. However, flame initiation becomes more difficult in lean and dilute fuel-air mixture with traditional spark discharge. This research proposal will first provide an intensive review on topics related to spark ignition including properties of electrical discharge, flame kernel behavior and spark ignition modeling and simulation. Focus will be laid on electrical discharge pattern effect as it is showing prospect in extending ignition limits in SI engines. An experimental setup has been built with an optically accessible constant volume combustion vessel. Multiple imaging techniques as well as spectroscopy will be applied. By varying spark discharge patterns, preliminary test results are available on consequent flame kernel development. In addition to experimental investigation of spark plasma and flame kernel development, spark ignition modeling with detailed description of plasma channel is also proposed for this study.

DEVELOPMENT OF A PREDICTIVE COMBUSTION MODEL OF A SPARK IGNITED ENGINE WITH GASOLINE DIRECT INJECTION, VARIABLE VALVE TIMING, DURATION AND LIFT TECHNOLOGIES

There is a need by engine manufactures for computationally efficient and accurate predictive combustion modeling tools for integration in engine simulation software for the assessment of combustion system hardware designs and early development of engine calibrations. This thesis discusses the process for the development and validation of a combustion modeling tool for Gasoline Direct Injected Spark Ignited Engine with variable valve timing, lift and duration valvetrain hardware from experimental data. Data was correlated and regressed from accepted methods for calculating the turbulent flow and flame propagation characteristics for an internal combustion engine. A non-linear regression modeling method was utilized to develop a combustion model to determine the fuel mass burn rate at multiple points during the combustion process. The computational fluid dynamic software Converge ©, was used to simulate and correlate the 3-D combustion system, port and piston geometry to the turbulent flow development within the cylinder to properly predict the experimental data turbulent flow parameters through the intake, compression and expansion processes. The engine simulation software GT-Power © is then used to determine the 1-D flow characteristics of the engine hardware being tested to correlate the regressed combustion modeling tool to experimental data to determine accuracy. The results of the combustion modeling tool show accurate trends capturing the combustion sensitivities to turbulent flow, thermodynamic and internal residual effects with changes in intake and exhaust valve timing, lift and duration.

STUDY OF SPARK IGNITION ENGINE COMBUSTION MODEL FOR THE ANALYSIS OF CYCLIC VARIATION AND COMBUSTION STABILITY AT LEAN OPERATING CONDITIONS

A fundamental combustion model for spark-ignition engine is studied in this report. The model is implemented in SIMULINK to simulate engine outputs (mass fraction burn and in-cylinder pressure) under various engine operation conditions. The combustion model includes a turbulent propagation and eddy burning processes based on literature [1]. The turbulence propagation and eddy burning processes are simulated by zero-dimensional method and the flame is assumed as sphere. To predict pressure, temperature and other in-cylinder variables, a two-zone thermodynamic model is used. The predicted results of this model match well with the engine test data under various engine speeds, loads, spark ignition timings and air fuel mass ratios. The developed model is used to study cyclic variation and combustion stability at lean (or diluted) combustion conditions. Several variation sources are introduced into the combustion model to simulate engine performance observed in experimental data. The relations between combustion stability and the introduced variation amount are analyzed at various lean combustion levels.

IMPROVING STARTABILITY AND REDUCING EMISSIONS IN FLEXFUEL SPARK IGNITION DIRECT INJECTION VARIABLE CAM TIMING ENGINE

Experimental work and analysis was done to investigate engine startup robustness and emissions of a flex-fuel spark ignition (SI) direct injection (DI) engine. The vaporization and other characteristics of ethanol fuel blends present a challenge at engine startup. Strategies to reduce the enrichment requirements for the first engine startup cycle and emissions for the second and third fired cycle at 25°C ± 1°C engine and intake air temperature were investigated. Research work was conducted on a single cylinder SIDI engine with gasoline and E85 fuels, to study the effect on first fired cycle of engine startup. Piston configurations that included a compression ratio change (11 vs 15.5) and piston geometry change (flattop vs bowl) were tested, along with changes in intake cam timing (95,110,125) and fuel pressure (0.4 MPa vs 3 MPa). The goal was to replicate the engine speed, manifold pressure, fuel pressure and testing temperature from an engine startup trace for investigating the first fired cycle for the engine. Results showed bowl piston was able to enable lower equivalence ratio engine starts with gasoline fuel, while also showing lower IMEP at the same equivalence ratio compared to flat top piston. With E85, bowl piston showed reduced IMEP as compression ratio increased at the same equivalence ratio. A preference for constant intake valve timing across fuels seemed to indicate that flattop piston might be a good flex-fuel piston. Significant improvements were seen with higher CR bowl piston with high fuel pressure starts, but showed no improvement with low fuel pressures. Simulation work was conducted to analyze initial three cycles of engine startup in GT-POWER for the same set of hardware used in the experimentations. A steady state validated model was modified for startup conditions. The results of which allowed an understanding of the relative residual levels and IMEP at the test points in the cam phasing space. This allowed selecting additional test points that enable use of higher residual levels, eliminating those with smaller trapped mass incapable of producing required IMEP for proper engine turnover. The second phase of experimental testing results for 2nd and 3rd startup cycle revealed both E10 and E85 prefer the same SOI of 240°bTDC at second and third startup cycle for the flat top piston and high injection pressures. E85 fuel optimal cam timing for startup showed that it tolerates more residuals compared to E10 fuel. Higher internal residuals drives down the Ø requirement for both fuels up to their combustion stability limit, this is thought to be direct benefit to vaporization due to increased cycle start temperature. Benefits are shown for an advance IMOP and retarded EMOP strategy at engine startup. Overall the amount of residuals preferred by an engine for E10 fuel at startup is thought to be constant across engine speed, thus could enable easier selection of optimized cam positions across the startup speeds.