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.

COMBUSTION INITIATION BY ELECTRICAL-DISCHARGE-INDUCED PLASMA IN LEAN AND DILUTE METHANE-AIR MIXTURE: EXPERIMENTAL AND MODELING INVESTIGATION

This dissertation represents experimental and numerical investigations of combustion initiation trigged by electrical-discharge-induced plasma within lean and dilute methane air mixture. This research topic is of interest due to its potential to further promote the understanding and prediction of spark ignition quality in high efficiency gasoline engines, which operate with lean and dilute fuel-air mixture. It is specified in this dissertation that the plasma to flame transition is the key process during the spark ignition event, yet it is also the most complicated and least understood procedure. Therefore the investigation is focused on the overlapped periods when plasma and flame both exists in the system. Experimental study is divided into two parts. Experiments in Part I focuses on the flame kernel resulting from the electrical discharge. A number of external factors are found to affect the growth of the flame kernel, resulting in complex correlations between discharge and flame kernel. Heat loss from the flame kernel to code ambient is found to be a dominant factor that quenches the flame kernel. Another experimental focus is on the plasma channel. Electrical discharges into gases induce intense and highly transient plasma. Detailed observation of the size and contents of the discharge-induced plasma channel is performed. Given the complex correlation and the multi-discipline physical/chemical processes involved in the plasma-flame transition, the modeling principle is taken to reproduce detailed transitions numerically with minimum analytical assumptions. Detailed measurement obtained from experimental work facilitates the more accurate description of initial reaction conditions. The novel and unique spark source considering both energy and species deposition is defined in a justified manner, which is the key feature of this Ignition by Plasma (IBP) model. The results of numerical simulation are intuitive and the potential of numerical simulation to better resolve the complex spark ignition mechanism is presented. Meanwhile, imperfections of the IBP model and numerical simulation have been specified and will address future attentions.

PROBABILISTIC MODELING OF RAINFALL INDUCED LANDSLIDE HAZARD ASSESSMENT IN SAN JUAN LA LAGUNA, SOLOLÁ, GUATEMALA

The municipality of San Juan La Laguna, Guatemala is home to approximately 5,200 people and located on the western side of the Lake Atitlán caldera. Steep slopes surround all but the eastern side of San Juan. The Lake Atitlán watershed is susceptible to many natural hazards, but most predictable are the landslides that can occur annually with each rainy season, especially during high-intensity events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the Atitlán region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. This study used data from multiple attributes, at every landslide and non-landslide point, and applied different multivariate analyses to optimize a model for landslides prediction during high-intensity precipitation events like Hurricane Stan. The attributes considered in this study are: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The attributes were pre-evaluated for their ability to predict landslides using four different attribute evaluators, all available in the open source data mining software Weka: filtered subset, information gain, gain ratio and chi-squared. Three multivariate algorithms (decision tree J48, logistic regression and BayesNet) were optimized for landslide prediction using different attributes. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points. The probability map developed in this study was also compared to the results of a bivariate landslide susceptibility analysis conducted for the watershed, encompassing Lake Atitlán and San Juan. Landslides from Tropical Storm Agatha 2010 were used to independently validate this study’s multivariate model and the bivariate model. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.

Inhibition of integrin alphavbeta6 on cholangiocytes blocks transforming growth factor-beta activation and retards biliary fibrosis progression

BACKGROUND ; AIMS: Integrin alphavbeta6 is highly expressed on certain activated epithelia, where it mediates attachment to fibronectin and serves as coreceptor for the activation of latent transforming growth factor (TGF)-beta1. Because its role in liver fibrosis is unknown, we studied alphavbeta6 function in vitro and explored the antifibrotic potential of the specific alphavbeta6 antagonist EMD527040. METHODS: Experimental liver fibrosis was studied in rats after bile duct ligation (BDL) and in Mdr2(abcb4)(-/-) mice. Different doses of EMD527040 were given to rats from week 2 to 6 after BDL and to Mdr2(-/-) mice from week 4 to 8. Liver collagen was quantified, and expression of alphavbeta6 and fibrosis-related transcripts was determined by quantitative reverse-transcription polymerase chain reaction. alphavbeta6-expressing cells, bile duct proliferation, and apoptosis were assessed histologically. The effect of EMD527040 on cholangiocyte adhesion, proliferation, apoptosis, and TGF-beta1 activation was studied in vitro. RESULTS: alphavbeta6 was highly expressed on proliferating bile duct epithelia in fibrosis, with 100-fold increased transcript levels in advanced fibrosis. EMD527040 attenuated bile ductular proliferation and peribiliary collagen deposition by 40%-50%, induced down-regulation of fibrogenic and up-regulation of fibrolytic genes, and improved liver architecture and function. In vitro alphavbeta6 inhibition reduced activated cholangiocyte proliferation, their adhesion to fibronectin, and endogenous activation of TGF-beta1 by 50% but did not affect bile duct apoptosis. CONCLUSIONS: Integrin alphavbeta6 is strongly up-regulated in proliferating bile duct epithelia and drives fibrogenesis via adhesion to fibronectin and auto/paracrine TGF-beta1 activation. Pharmacologic inhibition of alphavbeta6 potently inhibits the progression of primary and secondary biliary fibrosis.

Growth curves for cardio-metabolic risk factors in children and adolescents

OBJECTIVE: This study developed percentile curves for anthropometric (waist circumference) and cardiovascular (lipid profile) risk factors for US children and adolescents. STUDY DESIGN: A representative sample of US children and adolescents from the National Health and Nutrition Examination Survey from 1988 to 1994 (NHANES III) and the current national series (NHANES 1999-2006) were combined. Percentile curves were constructed, nationally weighted, and smoothed using the Lambda, Mu, and Sigma method. The percentile curves included age- and sex-specific percentile values that correspond with and transition into the adult abnormal cut-off values for each of these anthropometric and cardiovascular components. To increase the sample size, a second series of percentile curves was also created from the combination of the 2 NHANES databases, along with cross-sectional data from the Bogalusa Heart Study, the Muscatine Study, the Fels Longitudinal Study and the Princeton Lipid Research Clinics Study. RESULTS: These analyses resulted in a series of growth curves for waist circumference, total cholesterol, LDL cholesterol, triglycerides, and HDL cholesterol from a combination of pediatric data sets. The cut-off for abnormal waist circumference in adult males (102 cm) was equivalent to the 94(th) percentile line in 18-year-olds, and the cut-off in adult females (88 cm) was equivalent to the 84(th) percentile line in 18-year-olds. Triglycerides were found to have a bimodal pattern among females, with an initial peak at age 11 and a second at age 20; the curve for males increased steadily with age. The HDL curve for females was relatively flat, but the male curve declined starting at age 9 years. Similar curves for total and LDL cholesterol were constructed for both males and females. When data from the additional child studies were added to the national data, there was little difference in their patterns or rates of change from year to year. CONCLUSIONS: These curves represent waist and lipid percentiles for US children and adolescents, with identification of values that transition to adult abnormalities. They could be used conditionally for both epidemiological and possibly clinical applications, although they need to be validated against longitudinal data.

Incorporating Latent Variables into Discrete Choice Models - A Simultaneous Estimation Approach Using SEM Software

Integrated choice and latent variable (ICLV) models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM) for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.

Modeling Framework for the Establishment of the Apical-Basal Embryonic Axis in Plants

The apical-basal axis of the early plant embryo determines the body plan of the adult organism. To establish a polarized embryonic axis, plants evolved a unique mechanism that involves directional, cell-to-cell transport of the growth regulator auxin. Auxin transport relies on PIN auxin transporters 1], whose polar subcellular localization determines the flow directionality. PIN-mediated auxin transport mediates the spatial and temporal activity of the auxin response machinery 2-7] that contributes to embryo patterning processes, including establishment of the apical (shoot) and basal (root) embryo poles 8]. However, little is known of upstream mechanisms guiding the (re)polarization of auxin fluxes during embryogenesis 9]. Here, we developed a model of plant embryogenesis that correctly generates emergent cell polarities and auxin-mediated sequential initiation of apical-basal axis of plant embryo. The model relies on two precisely localized auxin sources and a feedback between auxin and the polar, subcellular PIN transporter localization. Simulations reproduced PIN polarity and auxin distribution, as well as previously unknown polarization events during early embryogenesis. The spectrum of validated model predictions suggests that our model corresponds to a minimal mechanistic framework for initiation and orientation of the apical-basal axis to guide both embryonic and postembryonic plant development.

Comparing growth trajectories of risk behaviors from late adolescence through young adulthood: An accelerated design

Risk behaviors such as substance use or deviance are often limited to the early stages of the life course. Whereas the onset of risk behavior is well studied, less is currently known about the decline and timing of cessation of risk behaviors of different domains during young adulthood. Prevalence and longitudinal developmental patterning of alcohol use, drinking to the point of drunkenness, smoking, cannabis use, deviance, and HIV-related sexual risk behavior were compared in a Swiss community sample (N = 2,843). Using a longitudinal cohort-sequential approach to link multiple assessments with 3 waves of data for each individual, the studied period spanned the ages of 16 to 29 years. Although smoking had a higher prevalence, both smoking and drinking up to the point of drunkenness followed an inverted U-shaped curve. Alcohol consumption was also best described by a quadratic model, though largely stable at a high level through the late 20s. Sexual risk behavior increased slowly from age 16 to age 22 and then remained largely stable. In contrast, cannabis use and deviance linearly declined from age 16 to age 29. Young men were at higher risk for all behaviors than were young women, but apart from deviance, patterning over time was similar for both sexes. Results about the timing of increase and decline as well as differences between risk behaviors may inform tailored prevention programs during the transition from late adolescence to adulthood.

Identifying Distinct Quitting Trajectories after an Unassisted Smoking Cessation Attempt: An Ecological Momentary Assessment Study

Objectives: This study aimed at identifying distinct quitting trajectories over 29 days after an unassisted smoking ces- sation attempt by ecological momentary assessment (EMA). In order to validate these trajectories we tested if they predict smoking frequency up to six months later. Methods: EMA via mobile phones was used to collect real time data on smoking (yes/no) after an unassisted quit attempt over 29 days. Smoking frequency one, three and six months after the quit attempt was assessed with online questionnaires. Latent class growth modeling was used to analyze the data of 230 self-quitters. Results: Four different quitting trajectories emerged: quitter (43.9%), late quitter (11.3%), returner (17%) and persistent smoker (27.8%). The quitting trajectories predicted smoking frequency one, three and six months after the quit attempt (all p < 0.001). Conclusions: Outcome after a smoking cessation attempt is better described by four distinct trajectories instead of a binary variable for abstinence or relapse. In line with the relapse model by Marlatt and Gordon, late quitter may have learned how to cope with lapses during one month after the quitting attempt. This group would have been allocated to the relapse group in traditional outcome studies.

Current and future variations of nutrient depositions and influences on tree growth

Current nutrient deposition shows episodic variations which likely may impact the local nutrient cycle at the RBSF. Comparing analyses of deposition data during present-day atmospheric circulation and phases of high biomass burning in the Amazon, characteristic relationships between remote emissions and local deposition are determined. By using projections drawn from the special report on emission scenarios (SRES) in combination with a trajectory modeling tool, future nutrient deposition conditions of the mountain ecosystem are assessed. Observations of relations between climatic variables, current time series of nutrient deposition, and tree growth point to an impact of the remote fertilization effect of atmospheric matters, emitted primarily by human activities like biomass burning and agricultural and industrial sources. The increasing emissions in the future may have adverse effects on the ecosystem in the long run.

MODELING SPORADIC TUMOR FORMATION DRIVEN BY TELOMERE DYSFUNCTION IN THE GASTROINTESTINAL TRACT

Colorectal cancer is a complex disease that is thought to arise when cells accumulate mutations that allow for uncontrolled growth. There are several recognized mechanisms for generating such mutations in sporadic colon cancer; one of which is chromosomal instability (CIN). One hypothesized driver of CIN in cancer is the improper repair of dysfunctional telomeres. Telomeres comprise the linear ends of chromosomes and play a dual role in cancer. Its length is maintained by the ribonucleoprotein, telomerase, which is not a normally expressed in somatic cells and as cells divide, telomeres continuously shorten. Critically shortened telomeres are considered dysfunctional as they are recognized as sites of DNA damage and cells respond by entering into replicative senescence or apoptosis, a process that is p53-dependent and the mechanism for telomere-induced tumor suppression. Loss of this checkpoint and improper repair of dysfunctional telomeres can initiate a cycle of fusion, bridge and breakage that can lead to chromosomal changes and genomic instability, a process that can lead to transformation of normal cells to cancer cells. Mouse models of telomere dysfunction are currently based on knocking out the telomerase protein or RNA component; however, the naturally long telomeres of mice require multiple generational crosses of telomerase null mice to achieve critically short telomeres. Shelterin is a complex of six core proteins that bind to telomeres specifically. Pot1a is a highly conserved member of this complex that specifically binds to the telomeric single-stranded 3’ G-rich overhang. Previous work in our lab has shown that Pot1a is essential for chromosomal end protection as deletion of Pot1a in murine embryonic fibroblasts (MEFs) leads to open telomere ends that initiate a DNA damage response mediated by ATR, resulting in p53-dependent cellular senescence. Loss of Pot1a in the background of p53 deficiency results in increased aberrant homologous recombination at telomeres and elevated genomic instability, which allows Pot1a-/-, p53-/- MEFs to form tumors when injected into SCID mice. These phenotypes are similar to those seen in cells with critically shortened telomeres. In this work, we created a mouse model of telomere ysfunction in the gastrointestinal tract through the conditional deletion of Pot1a that recapitulates the microscopic features seen in severe telomere attrition. Combined intestinal loss of Pot1a and p53 lead to formation of invasive adenocarcinomas in the small and large intestines. The tumors formed with long latency, low multiplicity and had complex genomes due to chromosomal instability, features similar to those seen in sporadic human colorectal cancers. Taken together, we have developed a novel mouse model of intestinal tumorigenesis based on genomic instability driven by telomere dysfunction.

Structural equation modeling of the medical outcome study: Short Form 36 (SF-36)

The factorial validity of the SF-36 was evaluated using confirmatory factor analysis (CFA) methods, structural equation modeling (SEM), and multigroup structural equation modeling (MSEM). First, the measurement and structural model of the hypothesized SF-36 was explicated. Second, the model was tested for the validity of a second-order factorial structure, upon evidence of model misfit, determined the best-fitting model, and tested the validity of the best-fitting model on a second random sample from the same population. Third, the best-fitting model was tested for invariance of the factorial structure across race, age, and educational subgroups using MSEM.^ The findings support the second-order factorial structure of the SF-36 as proposed by Ware and Sherbourne (1992). However, the results suggest that: (a) Mental Health and Physical Health covary; (b) general mental health cross-loads onto Physical Health; (c) general health perception loads onto Mental Health instead of Physical Health; (d) many of the error terms are correlated; and (e) the physical function scale is not reliable across these two samples. This hierarchical factor pattern was replicated across both samples of health care workers, suggesting that the post hoc model fitting was not data specific. Subgroup analysis suggests that the physical function scale is not reliable across the "age" or "education" subgroups and that the general mental health scale path from Mental Health is not reliable across the "white/nonwhite" or "education" subgroups.^ The importance of this study is in the use of SEM and MSEM in evaluating sample data from the use of the SF-36. These methods are uniquely suited to the analysis of latent variable structures and are widely used in other fields. The use of latent variable models for self reported outcome measures has become widespread, and should now be applied to medical outcomes research. Invariance testing is superior to mean scores or summary scores when evaluating differences between groups. From a practical, as well as, psychometric perspective, it seems imperative that construct validity research related to the SF-36 establish whether this same hierarchical structure and invariance holds for other populations.^ This project is presented as three articles to be submitted for publication. ^

Modeling Responses of Diatom Productivity and Biogenic Silica Export to Iron Enrichment in the Equatorial Pacific Ocean

Using a three-dimensional physical-biogeochemical model, we have investigated the modeled responses of diatom productivity and biogenic silica export to iron enrichment in the equatorial Pacific, and compared the model simulation with in situ (IronEx II) iron fertilization results. In the eastern equatorial Pacific, an area of 540,000 km(2) was enhanced with iron by changing the photosynthetic efficiency and silicate and nitrogen uptake kinetics of phytoplankton in the model for a period of 20 days. The vertically integrated Chl a and primary production increased by about threefold 5 days after the start of the experiment, similar to that observed in the IronEx II experiment. Diatoms contribute to the initial increase of the total phytoplankton biomass, but decrease sharply after 10 days because of mesozooplankton grazing. The modeled surface nutrients (silicate and nitrate) and TCO(2) anomaly fields, obtained from the difference between the "iron addition'' and "ambient'' (without iron) concentrations, also agreed well with the IronEx II observations. The enriched patch is tracked with an inert tracer similar to the SF6 used in the IronEx II. The modeled depth-time distribution of sinking biogenic silica (BSi) indicates that it would take more than 30 days after iron injection to detect any significant BSi export out of the euphotic zone. Sensitivity studies were performed to establish the importance of fertilized patch size, duration of fertilization, and the role of mesozooplankton grazing. A larger size of the iron patch tends to produce a broader extent and longer-lasting phytoplankton blooms. Longer duration prolongs phytoplankton growth, but higher zooplankton grazing pressure prevents significant phytoplankton biomass accumulation. With the same treatment of iron fertilization in the model, lowering mesozooplankton grazing rate generates much stronger diatom bloom, but it is terminated by Si(OH)(4) limitation after the initial rapid increase. Increasing mesozooplankton grazing rate, the diatom increase due to iron addition stays at minimum level, but small phytoplankton tend to increase. The numerical model experiments demonstrate the value of ecosystem modeling for evaluating the detailed interaction between biogeochemical cycle and iron fertilization in the equatorial Pacific.

Modeling tree water deficit from microclimate: an approach to quantifying drought stress

Tree water deficit estimated by measuring water-related changes in stem radius (DeltaW) was compared with tree water deficit estimated from the output of a simple, physiologically reasonable model (DeltaW(E)), with soil water potential (Psi(soil)) and atmospheric vapor pressure deficit (VPD) as inputs. Values of DeltaW were determined by monitoring stem radius changes with dendrometers and detrending the results for growth, We followed changes in DeltaW and DeltaW(E) in Pinus sylvestris L. and Quercus pubescens Willd. over 2 years at a dry site (2001-2002; Salgesch, Wallis) and in Picea abies (L.) Karst. for 1 year at a wet site (1998; Davos, Graubuenden) in the Swiss Alps. The seasonal courses of DeltaW in deciduous species and in conifers at the same site were similar and could be largely explained by variation in DeltaW(E). This finding strongly suggests that DeltaW, despite the known species-specific differences in stomatal response to microclimate, is mainly explained by a combination of atmospheric and soil conditions. Consequently, we concluded that trees are unable to maintain any particular DeltaW. Either Psi(soil) or VPD alone provided poorer estimates of AWthan a model incorporating both factors. As a first approximation of DeltaW(E), Psi(soil) can be weighted so that the negative mean Psi(soil) reaches 65 to 75% of the positive mean daytime VPD over a season (Q. pubescens: similar to65%, P abies: similar to70%, P sylvestris: similar to75%). The differences in DeltaW among species can be partially explained by a different weighting of Psi(soil) against VPD. The DeltaW of P. sylvestris was more dependent on Psi(soil) than that of Q. pubescens, but less than that of P. abies, and was less dependent on VPD than that of P. abies and Q. pubescens. The model worked well for P. abies at the wet site and for Q. pubescens and P. sylvestris at the dry site, and may be useful for estimating water deficit in other tree species.

The relation between cognitive and motor performance and their relevance for children’s transition to school: A latent variable approach

Both theoretically and empirically there is a continuous interest in understanding the specific relation between cognitive and motor development in childhood. In the present longitudinal study including three measurement points, this relation was targeted. At the beginning of the study, the participating children were 5-6-year-olds. By assessing participants' fine motor skills, their executive functioning, and their non-verbal intelligence, their cross-sectional and cross-lagged interrelations were examined. Additionally, performance in these three areas was used to predict early school achievement (in terms of mathematics, reading, and spelling) at the end of participants' first grade. Correlational analyses and structural equation modeling revealed that fine motor skills, non-verbal intelligence and executive functioning were significantly interrelated. Both fine motor skills and intelligence had significant links to later school achievement. However, when executive functioning was additionally included into the prediction of early academic achievement, fine motor skills and non-verbal intelligence were no longer significantly associated with later school performance suggesting that executive functioning plays an important role for the motor-cognitive performance link.