Power, Efficiency, and Emissions Optimization of a Single Cylinder Direct-Injected Diesel Engine for Testing of Alternative Fuels through Heat Release Modeling

The increasing dependency of the global economy on mineral fuels necessitates the investigation and future implementation of renewable fuels. Within the spectrum of compression ignition engines, this requires an understanding of the differences in combustion of alternative fuels (including biodiesels) from mineral diesel fuel oil, and requires an environment conducive to the experimentation necessary for future research. This thesis is a work in four parts, and gives much of the perspective necessary to empirically correlate the changes caused by differing fuel inputs. The first chapter provides a background as to the motivation of the work, its component sections, and a description of the work done previously and in parallel with the thesis. Finally, the focus of the thesis is given in order to relate the components to each other. The second chapter takes the form of a thorough review of hydrocarbon emissions from the perspective of compression-ignition engines, including a description of the variance in emissions when switching between diesel fuels from mineral or biological sources. The broad field of hydrocarbon emissions is broken down into subspecies of the group, and a recommendation as the future catalytic aftertreatment modeling using these subspecies is given. In chapter three, the basis of a thermodynamic equilibrium-based heat release model is given. In particular, this model is set up to use an Arrhenius-based rate of combustion calibrated to the emission profile recorded during experimentation. The model is subsequently tested and validated against previously acquired data, in order to highlight the model's ability to cope with varying testing modes, including variable fuels, Exhaust Gas Recirculation, or changing aspiration techniques. The final chapter describes the experimental procedure used to find the proper injection timings to trigger the Maximum Brake Torque condition at a given engine speed as a function of engine load, with the goal of accelerating future calibration of the improved test cell. These timings are also compared to the emissions profile of the engine, with the goal of linking variations in efficiency and emissions composition to variable injection timings

Modeling of Compression Ignition Engines for Advanced Engine Operation and Alternative Fuels by the Second Law of Thermodynamics

With the advent of modern engine control strategies, and particularly electronic common-rail injection, the scope and scale of what is achievable and controllable in compression-ignition engines has exploded quite rapidly in recent years. The potential marriage of electronically-controlled and multi-point fuel injection, dual fuel combustion, variable exhaust gas recirculation, exhaust waste heat recovery, low-temperature combustion, and the immense variety of potential liquid and gaseous fuels available means that the older understanding of compression ignition engine combustion is incomplete and inadequate to explain, predict, control, and optimize more novel engine combustion and operational regimes. This mandates that new models, both diagnostic and theoretical, be developed to explore engine combustion and pick apart the various phenomena that result, and includes revisiting models that previously have been sidelined for a lack of usefulness. To that end, this work details the construction, validation, and usage of a diagnostic heat release model focused on the application of the 2nd Law of Thermodynamics and the phenomena associated with entropy generation and availability destruction from the accumulated test data of numerous fuels and engine operational modes. A critical aspect of this research includes the marriage of this model with a suite of emissions analysis technologies, allowing for a complete characterization of engine-out regulated and unregulated emissions species, as well as a thoroughly instrumented and highly modified single-cylinder compression-ignition engine. This combined test apparatus for novel fuels and engine operational modes, in combination with the models described herein, serve as a means to collect and dissect engine performance, in-cylinder pressure, engine knock and noise, emissions, heat release, and availability release and consumption, and the interrelationships between these characteristics The experimental results of this work showcase both the direct usage of the 2nd Law Analysis (both alongside and separate from the more traditional 1st Law Heat Release Analysis), and also the potential usage of this model for the exploration of engine operational modes. In particular, the 2nd Law analysis appears to be of immense importance to the exploration of low temperature combustion regimes, as well as the usage of exhaust waste heat recovery systems

The Smart Grid, A Scale Demonstration Model Incorporating Electrified Vehicles

This article was published in the Spring 2011 issue of the Journal of Undergraduate Researc

Influence of Fuel Injection System and Engine-Timing Adjustments on Regulated Emissions from Four Biodiesel Fuels

The use of biofuels for transportation has grown substantially in the past decade in response to federal mandates and increased concern about the use of petroleum fuels. As biofuels become more common, it is imperative to assess their influence on mobile source emissions of regulated and hazardous pollutants. This assessment cannot be done without first obtaining a basic understanding of how biofuels affect the relationship between fuel properties, engine design, and combustion conditions. Combustion studies were conducted on biodiesel fuels from four feedstocks (palm oil, soybean oil, canola oil, and coconut oil) with two injection systems, mechanical and electronic. For the electronic system, fuel injection timing was adjusted to compensate for physical changes caused by different fuels. The emissions of nitrogen oxides (NOx) and partial combustion products were compared across both engine injection systems. The analysis showed differences in NOx emissions based on hydrocarbon chain length and degree of fuel unsaturation, with little to no NOx increase compared with ultra-low sulfur diesel fuel for most conditions. Adjusting the fuel injection timing provided some improvement in biodiesel emissions for NOx and particulate matter, particularly at lower engine loads. The results indicated that the introduction of biodiesel and biodiesel blends could have widely dissimilar effects in different types of vehicle fleets, depending on typical engine design, age, and the feedstock used for biofuel production

Distributed subglacial discharge drives significant submarine melt at a Greenland tidewater glacier

Submarine melt can account for substantial mass loss at tidewater glacier termini. However, the processes controlling submarine melt are poorly understood due to limited observations of submarine termini. Here at a tidewater glacier in central West Greenland, we identify subglacial discharge outlets and infer submarine melt across the terminus using direct observations of the submarine terminus face. We find extensive melting associated with small discharge outlets. While the majority of discharge is routed to a single, large channel, outlets not fed by large tributaries drive submarine melt rates in excess of 3.0 m d−1 and account for 85% of total estimated melt across the terminus. Nearly the entire terminus is undercut, which may intersect surface crevasses and promote calving. Severe undercutting constricts buoyant outflow plumes and may amplify melt. The observed morphology and melt distribution motivate more realistic treatments of terminus shape and subglacial discharge in submarine melt models

Diel variations of H2O2 in Greenland: A discussion of the cause and effect relationship

Atmospheric hydrogen peroxide (H2O2) measurements at Summit, Greenland, in May–June, 1993 exhibited a diel variation, with afternoon highs typically 1–2 parts per billion by volume (ppbv) and nighttime lows about 0.5 ppbv lower. This variation closely followed that for temperature; specific humidity exhibited the same general trend. During a 17-day snowfall-free period, surface snow was accumulating H2O2, apparently from nighttime cocondensation of H2O and H2O2. Previous photochemical modeling (Neftel et al., 1995) suggests that daytime H2O2 should be about 1 ppbv, significantly lower than our measured values. Previous equilibrium partitioning measurements between ice and gas phase (Conklin et al., 1993) suggest that air in equilibrium with H2O2 concentrations measured in surface snow (15–18 μM) should have an H2O2 concentration 2–3 times what we measured 0.2–3.5 m above the snow surface. A simple eddy diffusion model, with vertical eddy diffusion coefficients calculated from balloon soundings, suggested that atmospheric H2O2 concentrations should be affected by any H2O2 degassed from surface snow. However, field measurements showed the absence of either high concentrations of H2O2 or a measurable concentration gradient between inlets 0.2 and 3 m above the snow. A surface resistance to degassing, that is, slow release of H2O2 from the ice matrix, is a plausible explanation for the differences between observations and modeled atmospheric profiles. Degassing of H2O2 at a rate below our detection limit would still influence measured atmospheric concentrations and help explain the difference between measurements and photochemical modeling. The cumulative evidence suggests that surface snow adjusts slowly to drops in atmospheric H2O2 concentration, over timescales of at least weeks. The H2O2 losses previously observed in pits sampled over more than 1 year are thought to have occurred later in the summer or fall, after the May–July field season

Evolutionary public health: introducing the concept.

The emerging discipline of evolutionary medicine is breaking new ground in understanding why people become ill. However, the value of evolutionary analyses of human physiology and behaviour is only beginning to be recognised in the field of public health. Core principles come from life history theory, which analyses the allocation of finite amounts of energy between four competing functions-maintenance, growth, reproduction, and defence. A central tenet of evolutionary theory is that organisms are selected to allocate energy and time to maximise reproductive success, rather than health or longevity. Ecological interactions that influence mortality risk, nutrient availability, and pathogen burden shape energy allocation strategies throughout the life course, thereby affecting diverse health outcomes. Public health interventions could improve their own effectiveness by incorporating an evolutionary perspective. In particular, evolutionary approaches offer new opportunities to address the complex challenges of global health, in which populations are differentially exposed to the metabolic consequences of poverty, high fertility, infectious diseases, and rapid changes in nutrition and lifestyle. The effect of specific interventions is predicted to depend on broader factors shaping life expectancy. Among the important tools in this approach are mathematical models, which can explore probable benefits and limitations of interventions in silico, before their implementation in human populations

Evolutionary public health: introducing the concept.

The emerging discipline of evolutionary medicine is breaking new ground in understanding why people become ill. However, the value of evolutionary analyses of human physiology and behaviour is only beginning to be recognised in the field of public health. Core principles come from life history theory, which analyses the allocation of finite amounts of energy between four competing functions-maintenance, growth, reproduction, and defence. A central tenet of evolutionary theory is that organisms are selected to allocate energy and time to maximise reproductive success, rather than health or longevity. Ecological interactions that influence mortality risk, nutrient availability, and pathogen burden shape energy allocation strategies throughout the life course, thereby affecting diverse health outcomes. Public health interventions could improve their own effectiveness by incorporating an evolutionary perspective. In particular, evolutionary approaches offer new opportunities to address the complex challenges of global health, in which populations are differentially exposed to the metabolic consequences of poverty, high fertility, infectious diseases, and rapid changes in nutrition and lifestyle. The effect of specific interventions is predicted to depend on broader factors shaping life expectancy. Among the important tools in this approach are mathematical models, which can explore probable benefits and limitations of interventions in silico, before their implementation in human populations

Evolutionary public health: introducing the concept.

The emerging discipline of evolutionary medicine is breaking new ground in understanding why people become ill. However, the value of evolutionary analyses of human physiology and behaviour is only beginning to be recognised in the field of public health. Core principles come from life history theory, which analyses the allocation of finite amounts of energy between four competing functions-maintenance, growth, reproduction, and defence. A central tenet of evolutionary theory is that organisms are selected to allocate energy and time to maximise reproductive success, rather than health or longevity. Ecological interactions that influence mortality risk, nutrient availability, and pathogen burden shape energy allocation strategies throughout the life course, thereby affecting diverse health outcomes. Public health interventions could improve their own effectiveness by incorporating an evolutionary perspective. In particular, evolutionary approaches offer new opportunities to address the complex challenges of global health, in which populations are differentially exposed to the metabolic consequences of poverty, high fertility, infectious diseases, and rapid changes in nutrition and lifestyle. The effect of specific interventions is predicted to depend on broader factors shaping life expectancy. Among the important tools in this approach are mathematical models, which can explore probable benefits and limitations of interventions in silico, before their implementation in human populations