Performance evaluation and characterization of symmetric capacitors with carbon black, and asymmetric capacitors using a carbon foam supported nickel electrode

This thesis evaluates a novel asymmetric capacitor incorporating a carbon foam supported nickel hydroxide positive electrode and a carbon black negative electrode. A series of symmetric capacitors were prepared to characterize the carbon black (CB) negative electrode. The influence of the binder, PTFE, content on the cell properties was evaluated. X-ray diffraction characterization of the nickel electrode during cycling is also presented. The 3 wt% and 5 wt% PTFE/CB symmetric cells were examined using cyclic voltammetry (CV) and constant current charge/discharge measurements. As compared with symmetric cells containing more PTFE, the 3 wt% cell has the highest average specific capacitance, energy density and power density over 300 cycles, 121.8 F/g, 6.44 Wh/kg, and 604.1 W/kg, respectively. Over the 3 to 10 wt% PTFE/CB range, the 3 wt% sample exhibited the lowest effective resistance and the highest BET surface area. Three asymmetric cells (3 wt% PTFE/CB negative electrode and a nickel positive) were fabricated; cycle life was examined at 3 current densities. The highest average energy and power densities over 1000 cycles were 20 Wh/kg (21 mA/cm2) and 715 W/kg (31 mA/cm2), respectively. The longest cycle life was 11,505 cycles (at 8 mA/cm2), with an average efficiency of 79% and an average energy density of 14 Wh/kg. The XRD results demonstrate that the cathodically deposited nickel electrode is a typical α-Ni(OH)2 with the R3m structure (ABBCCA stacking); the charged electrodes are 3γ-NiOOH with the same stacking as the α-type; the discharged electrodes (including as-formed electrode) are aged to β’-Ni(OH)2 (a disordered β) with the P3m structure (ABAB stacking). A 3γ remnant was observed.

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.

Implementation of a Variable Compression Ratio Mechanism in a Four Cylinder Engine

Ever since the invention of the internal combustion engine, generating more power and achieving better efficiency has been a major goal for the designers. Variable compression ratio technology is way to achieve those goals. This paper will discuss the method of varying the compression ratio of an inline 4-cylinder engine through the use of a 4-bar linkage and gear mechanism. This mechanism was proven to easily vary the compression ratio of the engine and shows promise of becoming a technology used for future engine designer.

Optimal current control for sub-unity power factor correction

Switching mode power supplies (SMPS) are subject to low power factor and high harmonic distortions. Active power-factor correction (APFC) is a technique to improve the power factor and to reduce the harmonic distortion of SMPSs. However, this technique results in double frequency output voltage variation which can be reduced by using a large output capacitance. Using large capacitors increases the cost and size of the converter. Furthermore, the capacitors are subject to frequent failures mainly caused by evaporation of the electrolytic solution which reduce the converter reliability. This thesis presents an optimal control method for the input current of a boost converter to reduce the size of the output capacitor. The optimum current waveform as a function of weighing factor is found by using the Euler Lagrange equation. A set of simulations are performed to determine the ideal weighing which gives the lowest possible output voltage variation as the converter still meets the IEC-61000-3-2 class-A harmonics requirements with a power factor of 0.8 or higher. The proposed method is verified by the experimental work. A boost converter is designed and it is run for different power levels, 100 W, 200 W and 400 W. The desired output voltage ripple is 10 V peak to peak for the output voltage of 200 Vdc. This ripple value corresponds to a ± 2.5% output voltage ripple. The experimental and the simulation results are found to be quite matching. A significant reduction in capacitor size, as high as 50%, is accomplished by using the proposed method.

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.

COMPUTATIONAL ANALYSIS OF THE AEROELASTIC DYNAMICS OF A WIND TURBINE BLADE WITH VARIABLE-SPEED STALL CONTROL

The accuracy of simulating the aerodynamics and structural properties of the blades is crucial in the wind-turbine technology. Hence the models used to implement these features need to be very precise and their level of detailing needs to be high. With the variety of blade designs being developed the models should be versatile enough to adapt to the changes required by every design. We are going to implement a combination of numerical models which are associated with the structural and the aerodynamic part of the simulation using the computational power of a parallel HPC cluster. The structural part models the heterogeneous internal structure of the beam based on a novel implementation of the Generalized Timoshenko Beam Model Technique.. Using this technique the 3-D structure of the blade is reduced into a 1-D beam which is asymptotically equivalent. This reduces the computational cost of the model without compromising its accuracy. This structural model interacts with the Flow model which is a modified version of the Blade Element Momentum Theory. The modified version of the BEM accounts for the large deflections of the blade and also considers the pre-defined structure of the blade. The coning, sweeping of the blade, tilt of the nacelle and the twist of the sections along the blade length are all computed by the model which aren’t considered in the classical BEM theory. Each of these two models provides feedback to the other and the interactive computations lead to more accurate outputs. We successfully implemented the computational models to analyze and simulate the structural and aerodynamic aspects of the blades. The interactive nature of these models and their ability to recompute data using the feedback from each other makes this code more efficient than the commercial codes available. In this thesis we start off with the verification of these models by testing it on the well-known benchmark blade for the NREL-5MW Reference Wind Turbine, an alternative fixed-speed stall-controlled blade design proposed by Delft University, and a novel alternative design that we proposed for a variable-speed stall-controlled turbine, which offers the potential for more uniform power control and improved annual energy production.. To optimize the power output of the stall-controlled blade we modify the existing designs and study their behavior using the aforementioned aero elastic model.

INTERACTIVE CONTROLS OF WATER TABLE POSITION AND PLANT FUNCTIONAL TYPES ON PEAT POREWATER CHARACTER IN NORTHERN BOG ECOSYSTEMS: IMPLICATIONS FOR CARBON CYCLING DYNAMICS

Northern wetlands, and particularly peatlands, have been shown to store around 30% of the world's soil carbon and thus play a significant role in the carbon cycle of our planet. Changes in climate are altering peatland hydrology and vegetation communities. These changes are possibly resulting in declines in the ability of peatlands to sequester carbon because losses through carbon oxidation and mineralization are likely to increase relative to C inputs from net primary production in a warmer, drier climate. However, the consequences of interactive effects of altered hydrology and vegetation on carbon storage are not well understood. This research evaluated the importance of plant species, water table, and their interactive effects on porewater quality in a northern peatland with an average pH of 4.54, ranging from 4.15 to 4.8. We assessed the effects of plant functional group (ericaceous shrubs, sedges, and bryophytes) and water table position on biogeochemical processes. Specifically, we measured dissolved organic carbon (DOC), total dissolved nitrogen (TDN), potential enzyme activity, organic acids, anions and cations, spectral indexes of aromaticity, and phenolic content. Our results indicate that acetate and propionate concentrations in the sedge-dominated communities declined with depth and water table drawdown, relative to the control and ericaceous treatments. DOC increased in the lowered water table treatments in all vegetation community types, and the peat porewater C:N ratio declined in the sedge-dominated treatments when the water table was lowered. The relationship between DOC and ferrous iron showed significant responses to vegetation type; the exclusion of Ericaceae resulted in less ferrous iron per unit DOC compared to mixed species treatments and Ericaceae alone. This observation was corroborated with higher mean oxidation redox potential profiles (integrating 20, 40, and 70 cm) measured in the sedge treatments, compared with the mixed and Ericaceae species treatments over a growing season. Enzymatic activities did not show as strong of a response to treatments as expected; the oxidative enzyme peroxidase and the hydrolytic enzyme phosphatase were the only enzymes to respond to water table, where the potential activity of both enzymes increased with water table drawdown. Overall, there were significant interactive effects between changes in vegetation and water table position on peat porewater composition. These data suggest that vegetation effects on oxidation reduction potentials and peat porewater character can be as important as water table position in northern bog ecosystems.

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

Imminent ocean acidification in the Arctic projected with the NCAR global coupled carbon cycle-climate model

Ocean acidification from the uptake of anthropogenic carbon is simulated for the industrial period and IPCC SRES emission scenarios A2 and B1 with a global coupled carbon cycle-climate model. Earlier studies identified seawater saturation state with respect to aragonite, a mineral phase of calcium carbonate, as a key variable governing impacts on corals and other shell-forming organisms. Globally in the A2 scenario, water saturated by more than 300%, considered suitable for coral growth, vanishes by 2070 AD (CO2≈630 ppm), and the ocean volume fraction occupied by saturated water decreases from 42% to 25% over this century. The largest simulated pH changes worldwide occur in Arctic surface waters, where hydrogen ion concentration increases by up to 185% (ΔpH=−0.45). Projected climate change amplifies the decrease in Arctic surface mean saturation and pH by more than 20%, mainly due to freshening and increased carbon uptake in response to sea ice retreat. Modeled saturation compares well with observation-based estimates along an Arctic transect and simulated changes have been corrected for remaining model-data differences in this region. Aragonite undersaturation in Arctic surface waters is projected to occur locally within a decade and to become more widespread as atmospheric CO2 continues to grow. The results imply that surface waters in the Arctic Ocean will become corrosive to aragonite, with potentially large implications for the marine ecosystem, if anthropogenic carbon emissions are not reduced and atmospheric CO2 not kept below 450 ppm.

Global biomass burning: a synthesis and review of Holocene paleofire records and their controls

We synthesize existing sedimentary charcoal records to reconstruct Holocene fire history at regional, continental and global scales. The reconstructions are compared with the two potential controls of burning at these broad scales – changes in climate and human activities – to assess their relative importance on trends in biomass burning. Here we consider several hypotheses that have been advanced to explain the Holocene record of fire, including climate, human activities and synergies between the two. Our results suggest that 1) episodes of high fire activity were relatively common in the early Holocene and were consistent with climate changes despite low global temperatures and low levels of biomass burning globally; 2) there is little evidence from the paleofire record to support the Early Anthropocene Hypothesis of human modification of the global carbon cycle; 3) there was a nearly-global increase in fire activity from 3 to 2 ka that is difficult to explain with either climate or humans, but the widespread and synchronous nature of the increase suggests at least a partial climate forcing; and 4) burning during the past century generally decreased but was spatially variable; it declined sharply in many areas, but there were also large increases (e.g., Australia and parts of Europe). Our analysis does not exclude an important role for human activities on global biomass burning during the Holocene, but instead provides evidence for a pervasive influence of climate across multiple spatial and temporal scales.

The end of the corporate life cycle

This paper asks how takeover and failure hazards change as listed firms get older. The hypothesis is that they increase because firms gradually run out of growth opportunities. We find the opposite. Both takeover and failure hazard drop significantly with age. The decline in takeover hazard can be explained with Loderer, Stulz, and Waelchli’s (2013) “buggy whip makers” hypothesis: Because old firms are comparatively well-managed and are affected by limited agency problems, on average, they offer little value added potential to acquirers. Failure hazard drops because to learning. The results are robust to various alternative interpretations and cannot be explained by unobserved heterogeneity. While hazards decline with age, they do not go to zero. This explains why, eventually, all listed firms disappear

The end of the corporate life cycle

This paper asks how takeover and failure hazards change as listed firms get older. The hypothesis is that they increase because firms gradually run out of growth opportunities. We find the opposite. Both takeover and failure hazard drop significantly with age. The decline in takeover hazard can be explained with Loderer, Stulz, and Waelchli’s (2013) “buggy whip makers” hypothesis: Because old firms are comparatively well-managed and are affected by limited agency problems, on average, they offer little value added potential to acquirers. Failure hazard drops because to learning. The results are robust to various alternative interpretations and cannot be explained by unobserved heterogeneity. While hazards decline with age, they do not go to zero. This explains why, eventually, all listed firms disappear

The end of the corporate life cycle

This paper asks how takeover and failure hazards change as listed firms get older. The hypothesis is that they increase because firms gradually run out of growth opportunities. We find the opposite. Both takeover and failure hazard drop significantly with age. The decline in takeover hazard can be explained with Loderer, Stulz, and Waelchli’s (2013) “buggy whip makers” hypothesis: Because old firms are comparatively well-managed and are affected by limited agency problems, on average, they offer little value added potential to acquirers. Failure hazard drops because to learning. The results are robust to various alternative interpretations and cannot be explained by unobserved heterogeneity. While hazards decline with age, they do not go to zero. This explains why, eventually, all listed firms disappear

Understanding the role of argininosuccinate lyase transcript variants in the clinical and biochemical variability of the urea cycle disorder argininosuccinic aciduria

Argininosuccinic aciduria (ASA) is an autosomal recessive urea cycle disorder caused by deficiency of argininosuccinate lyase (ASL) with a wide clinical spectrum from asymptomatic to severe hyperammonemic neonatal onset life-threatening courses. We investigated the role of ASL transcript variants in the clinical and biochemical variability of ASA. Recombinant proteins for ASL wild type, mutant p.E189G, and the frequently occurring transcript variants with exon 2 or 7 deletions were (co-)expressed in human embryonic kidney 293T cells. We found that exon 2-deleted ASL forms a stable truncated protein with no relevant activity but a dose-dependent dominant negative effect on enzymatic activity after co-expression with wild type or mutant ASL, whereas exon 7-deleted ASL is unstable but seems to have, nevertheless, a dominant negative effect on mutant ASL. These findings were supported by structural modeling predictions for ASL heterotetramer/homotetramer formation. Illustrating the physiological relevance, the predominant occurrence of exon 7-deleted ASL was found in two patients who were both heterozygous for the ASL mutant p.E189G. Our results suggest that ASL transcripts can contribute to the highly variable phenotype in ASA patients if expressed at high levels. Especially, the exon 2-deleted ASL variant may form a heterotetramer with wild type or mutant ASL, causing markedly reduced ASL activity.

The nitrogen cycle of tropical montane forest in Ecuador turns inorganic under environmental change

Water-bound nitrogen (N) cycling in temperate terrestrial ecosystems of the Northern Hemisphere is today mainly inorganic because of anthropogenic release of reactive N to the environment. In little-industrialized and remote areas, in contrast, a larger part of N cycling occurs as dissolved organic N (DON). In a north Andean tropical montane forest in Ecuador, the N cycle changed markedly during 1998–2010 along with increasing N deposition and reduced soil moisture. The DON concentrations and the fractional contribution of DON to total N significantly decreased in rainfall, throughfall, and soil solutions. This inorganic turn of the N cycle was most pronounced in rainfall and became weaker along the flow path of water through the system until it disappeared in stream water. Decreasing organic contributions to N cycling were caused not only by increasing inorganic N input but also by reduced DON production and/or enhanced DON decomposition. Accelerated DON decomposition might be attributable to less waterlogging and higher nutrient availability. Significantly increasing NO3-N concentrations and NO3-N/NH4-N concentration ratios in throughfall and litter leachate below the thick organic layers indicated increasing nitrification. In mineral soil solutions, in contrast, NH4-N concentrations increased and NO3-N/NH4-N concentration ratios decreased significantly, suggesting increasing net ammonification. Our results demonstrate that the remote tropical montane forests on the rim of the Amazon basin experienced a pronounced change of the N cycle in only one decade. This change likely parallels a similar change which followed industrialization in the temperate zone of the Northern Hemisphere more than a century ago.