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At least 181 records · Page 10

Experimental Investigation of the Effect of Air-Handling and DME-Propane Blends on the Performance and Emissions of a 4-Cylinder CI Engine

Dimethyl ether (DME) is considered an excellent alternative to diesel because of its higher cetane number and lower carbon content. Additionally, DME can be blended with abundantly available propane with minimal modifications to the propane infrastructure. This paper focuses on an experimental investigation of the effect of air-handling i.e., boost pressure and exhaust gas recirculation (EGR), and DME-propane blends on the combustion and emissions performance of a light-duty, four-cylinder, compression ignition (CI) engine. Here, the boost pressure and EGR sweeps were carried out and showed that higher boost pressures resulted in increased brake thermal efficiencies (BTE) at the expense of higher NOx emissions which could be reduced by an increase in EGR. The fuel sweeps were carried out at 0, 15 and 25% propane (neat, 85% and 75% DME) with 0% and 25% EGR. The fuel sweeps indicated that the ignition delay (ID) increased and burn duration (BD) decreased monotonically when the blend increased to 25% propane/75% DME. The results suggest optimum engine performance with neat DME at 105 kPa boost pressure and 25% EGR with propane addition improving the BTE with negligible increase in emissions. Higher contents of Propane, up to 25%, did not affect the variability of combustion, with standard deviations of burn duration and peak cylinder pressures below 1% for all test cases.

air-handling↗

BlendPATH (Blending Pipeline Analysis Tool for Hydrogen) [SWR-24-10]

BlendPATH provides case-by-case techno-economic analysis for potential projects where hydrogen is blended into a natural gas transmission pipeline. BlendPATH estimates 1) the transmission pipeline modifications and operating conditions necessary to blend hydrogen to a user specified volume faction of hydrogen in pipeline gas and 2) the incremental capital and operating expenses to prepare said transmission pipeline for hydrogen blending. BlendPATH is developed in Python and requires SAInt, a underlying commercial natural gas pipeline network modeling software, to run. Pipeline modification and operation condition estimation is guided by ASME B31.12. The intent of this software is to target application for projects in the initial project assessment stage and provide the user with the capability of assess promising opportunities before the use proceeds with further detailed pipeline evaluation based on a probable economic outcome.

Kee, Jamie↗

Cesium Exchange onto Crystalline Silicotitanate from Blended Hanford Tank Wastes

The Tank Side Cesium Removal (TSCR) system was developed to filter and remove cesium (Cs and 137 Cs) from Hanford tank waste supernate in preparation for vitrification. The Cs removal will be conducted with crystalline silicotitanate (CST) ion exchange media. Under the planned waste-processing strategy, the tank waste supernate will be queued for TSCR processing in tank 241-AP-107 (AP-107). Once AP-107 tank waste volume is sufficiently depleted, the waste supernate from tank 241-AP-105 (AP-105, the holding tank before transfer to AP-107) will be transferred to tank AP-107. Supernate from another tank will be transferred to the holding tank, AP-105, for eventual transfer to tank AP-107. These supernate streams will undergo blending in tanks AP-107 and AP-105; the volume blend ratios will be driven by how much the tank waste supernate volumes are depleted before the next tank waste is added. The consequence of tank waste blending on Cs uptake by CST was of interest and was tested via batch contacts; results are reported herein.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Enabling Entrained-Flow Gasification of Blends of Coal, Biomass and Plastics (Final Report)

This project demonstrated the technical feasibility of gasifying blends of coal, biomass and mixed waste plastics in a high pressure entrained-flow gasifier for production of hydrogen. This was achieved by creating slurries of coal, biomass pyrolysis liquids and liquefied plastic oil. Specific objectives of the project included (1) determining compositions of coal-biomass-plastic mixtures that produce a stable slurry suitable for pumping to high pressure, (2) designing and testing a novel burner to effectively atomize the mixed feedstock slurry in a pressurized gasifier, and (3) acquiring first-of-a-kind performance data for pressurized, oxygen-blown entrained-flow gasification of slurried blends of coal, biomass and plastic. A key focus of the project was preparation of mixtures of coal, biomass and plastic. To facilitate easy pumping to high pressure, slurries were created using (i) bioliquid resulting from a well-established rapid thermal treatment pyrolysis process, (ii) oil produced from waste plastic via an available thermal conversion process, and (iii) ground coal. Lab-scale tests were conducted to evaluate viscosity and stability/propensity for the mixtures to separate over time. Larger batches of the most promising slurry compositions were prepared and subjected to pumping studies. It was found that mixtures containing less than about 40% coal and less than about 30% plastic oil were stable and of low enough viscosity to facilitate pumping to high pressure. A high-performance hot oxygen burner (HOB) was designed and fabricated for use in an existing 1 ton/day pressurized entrained-flow gasifier. Ex-situ testing demonstrated that the HOB provides excellent atomization of the slurries and creates a very uniform and robust flame. Performance of the HOB in the gasifier was exceptional and resulted in better conversion to syngas than any previous generation of burner. Fabricating the HOB for this project was challenging due to the relatively small scale of the gasifier. Performance in larger-scale systems is expected to be even better. Gasification of mixtures of coal, bioliquid and plastic oil proved to be relatively easy. The gasifier was able to be started up, pressurized and transitioned to the blended slurry feedstock with no technical difficulty. Syngas rich in CO and H 2 , with relatively low concentrations of CO 2 , was produced. During startup and at low gasification temperatures, soot formation was observed, as is typical for gasification of petroleum-based feedstocks. No slag buildup was observed under the conditions tested. The project was successful in demonstrating the technical feasibility of the concept. Future development should broaden the range of feedstocks under consideration, more deeply explore performance of the gasifier, and evaluate scale-up and implementation strategies.

08 HYDROGEN↗

Electrocatalytic alkene epoxidation at disrupted metal ensembles in blended electrolytes

The project aims to achieve a molecular understanding of oxygen-atom transfer from water to alkenes at electrocatalytic interfaces. Molecular oxygen is the most common oxygen-atom source for epoxidations, and our group is developing sustainable routes through which epoxidation of olefins is achieved using water as the oxygen source. This route can improve the safety of the reaction while also co-producing hydrogen, demonstrating the relevance of this reaction to the energy transition. If successful in our efforts, we may enable oxygen-atom transfer reactions at the anode of water electrolyzers in the place of conventional oxygen evolution, allowing for the synthesis of sustainable value-added co-products. In this vein, we explore several approaches to acquiring high selectivity toward epoxidation over competing reactions, such as oxygen evolution. One of our aims is to allow for rational control of epoxide selectivity by disrupting contiguous metal ensembles at the surface of catalytic metal oxide nanoparticles. Specifically, we aim to synthesize single-atom, few-atom, and many-atom clusters supported on metal oxides and study the mechanism of oxygen evolution and alkene epoxidation on these materials. Thus, this approach will determine the impact of disrupting metal ensembles on the selectivity for alkene epoxidation versus oxygen evolution in blended electrolytes. Another aim is to develop a molecular-level understanding of how a blended electrolyte (i.e., a mixture of aqueous and organic solvents) influences rates of alkene epoxidation versus oxygen evolution. In other words, we are interested in understanding the catalytic influence of the solvent, as our preliminary work shows that the selectivity and reactivity of epoxidation depend strongly on the solvent composition. This investigation includes blended electrolytes and electrolytes containing redox mediator species that improve selectivity toward the desired epoxidation reaction. Overall, our proposed work will help to provide a detailed molecular-level picture of how solvents interact with substrates at the electrode-electrolyte interface, including their involvement in proton transfer reactions and screening of electric fields.

14 SOLAR ENERGY↗

Blending as an In-Tank Waste Processing Strategy: Year 1 Progress Report

The Hanford Site stores approximately 56 million gallons of radioactive legacy defense waste in underground tanks. Direct feed of southeast quadrant tank waste to a high-level waste treatment facility is currently being explored to accelerate tank treatment activities. This study seeks to de-risk waste transfers by favorably altering the resuspension and critical velocities of wastes through strategic waste blending. Wastes rich in aluminum- and zirconium-bearing solids pose significant risks due to their high settled strength and density. A series of tests explores how solid phase particle size and suspending phase chemistry alter waste transport properties, quantified through the just-suspended mixing speed (NJS), for pure and blended aluminum- and zirconium-bearing waste solid simulants. The study utilizes a range of gibbsites (three sizes spanning 10 to 90 µm) and zirconia solids (three sizes spanning 10 to 100 µm). As expected, the NJS of pure solids largely follows predictions based on literature correlations; blends of gibbsite and zirconium-bearing solids of differing particle sizes exhibit NJS maxima attributed to dense packing of the mixed-size settled solids. The findings of this study will assist in developing strategies to optimize the transport of waste solids for the safe and efficient delivery of tank waste.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Error quantification of the Arrhenius blending rule for viscosity of hydrocarbon mixtures

Six hundred and seventy-five measurements of dynamic viscosity and density have been used to assess the prediction error of the Arrhenius blending rule for kinematic viscosity of hydrocarbon mixtures. Major trends within the data show that mixture complexity–binary to hundreds of components—and temperature are more important determinants of prediction error than differences in molecular size or hydrogen saturation between the components of the mixtures. Over the range evaluated, no correlation between prediction error and mole fractions was observed, suggesting the log of viscosity truly is linear in mole fraction, as indicated by the Arrhenius blending rule. Mixture complexity and temperature also impact molar volume and its prediction. However, a linear regression between the two model errors explains less than 20% of the observed variation, indicating that mixture viscosity and/or molar volume are not linear with respect to temperature and/or mixture complexity. Extensive discussion of the intermolecular forces and the geometric arrangement of molecules and vacancies in liquids, which ultimately determines its viscosity, is brought into context with the implicit approximations behind the Arrhenius blending rule. The complexity of this physics is not compatible with a simple algebraic correction to the model. However, sufficient data is now available to determine confidence intervals around the prediction of fuel viscosity based on its component mole fractions and viscosities. At -40°C, when all identified components are pure molecules the modeling error is 13.2% of the predicted (nominal) viscosity times the root mean square of the component mole fractions.

10 SYNTHETIC FUELS↗

Reburning of Animal Waste Based Biomass with Coal for NO x Reduction, Part I: Feedlot Biomass (FB) and Coal:FB Blends

Cattle biomass (CB or manure from cattle) is proposed as reburn fuel under slightly fuel-rich conditions. The CB includes wastes from cattle feedlots (cattle grown in feedlots to slaughter weights of 450–640 kg) termed as Feedlot Biomass (FB) and cattle wastes from dairy farms termed as Dairy Biomass (DB). NOx emissions from coal-fired power plants can be reduced by using pure CB and Coal:CB mixtures as reburn fuels (10~30% by heat) injected after the primary combustion region. Experiments with Coal:CB mixtures as reburn fuels were performed using the 30 kW burner facility. Part I deals with results from experiments using pure FB and Coal:FB blends as reburn fuels while Part II presents results on extent of NOx reduction using pure DB and Coal:DB blends as reburn fuels (RF). In the current work, results on NOx emission are presented with FB and Coal:FB blends as RF. The parametric studies include: equivalence ratio in reburn zone (ERRBZ), vitiated air, angle of reburn nozzles, presence and absence of heat exchangers (HEXs), and baseline NOx concentration. The optimum operating conditions for FB reburning were found to be conditions with vitiation at ERRBZ = 1.1 with 45° upward counter-current injection in the presence of HEXs. NOx emissions were reduced by as much as 96%.

09 BIOMASS FUELS↗

Soot Formation and Ignition Characteristics of Ethanol/Gasoline Blends in a Rapid Compression Machine

With the ever-increasing demand for sustainable energy, alcohol fuels have garnered interest for use in heavy duty engines. The significant infrastructure for ethanol production and blending of ethanol with gasoline make these fuels/fuel blends desirable candidates. However, development of heavy duty engine technology that is capable of burning alcohol fuels while retaining the advantages of traditional diesel combustion requires an improved understanding of the soot formation for these fuels under conditions relevant to mixing-controlled combustion. This work uses an extinction diagnostic to study the sooting tendency of ethanol and gasoline/ethanol blends ranging from E10 to E98 during ignition in a homogeneous environment. Experiments were conducted in a rapid compression machine (RCM) for compressed conditions of 20 ± 1 bar and an approximately constant temperature (± 10K) which was unique for each fuel. For a given soot volume fraction, a linear relationship was observed between ethanol content and the equivalence ratio in which that soot volume fraction was formed. Accounting for the oxygenated nature of ethanol, E85 and E98 fuels produced similar amounts of soot at a given Φ ox, , suggesting other factors outside of fuel oxygen content, such as fuel morphology, impact soot formation. Ignition delay data is reported for compressed pressures of 20 ± 1 bar and compressed temperatures ranging from 633 – 670 K for E10 and 771 – 789 K for E98. Varying pressures for E10 and E98 at conditions producing similar soot volume fractions demonstrated a linear dependence of soot formation on pressure, regardless of if the pressure considered was at top dead center or peak combustion pressure. Furthermore, the data gleaned from this work will be used to select soot models and chemical kinetic mechanisms for RCM simulations to ultimately model heavy duty engine technology with the studied fuels.

33 ADVANCED PROPULSION SYSTEMS↗

Parameter-dependent model-blending with multi-expert based machine learning and proxy sites

A parameter-based multi-model blending method and system are described. The method includes selecting a parameter of interest among parameters estimated by each of a set of individual models, running the set of individual models with a range of inputs to obtain a range of estimates of the parameters from each of the set of individual models, and identifying, for each of the set of individual models, critical parameters among the parameters estimated, the critical parameters exhibiting a specified correlation with an error in estimation of the parameter of interest. For each subspace of combinations of the critical parameters, obtaining a parameter-based blended model is based on blending the set of individual models in accordance with the subspace of the critical parameters, the subspace defining a sub-range for each of the critical parameters.

97 MATHEMATICS AND COMPUTING↗

Parameter-dependent model-blending with multi-expert based machine learning and proxy sites

A parameter-based multi-model blending method and system are described. The method includes selecting a parameter of interest among parameters estimated by each of a set of individual models, running the set of individual models with a range of inputs to obtain a range of estimates of the parameters from each of the set of individual models, and identifying, for each of the set of individual models, critical parameters among the parameters estimated, the critical parameters exhibiting a specified correlation with an error in estimation of the parameter of interest. For each subspace of combinations of the critical parameters, obtaining a parameter-based blended model is based on blending the set of individual models in accordance with the subspace of the critical parameters, the subspace defining a sub-range for each of the critical parameters.

97 MATHEMATICS AND COMPUTING↗

Parameter-dependent model-blending with multi-expert based machine learning and proxy sites

A parameter-based multi-model blending method and system are described. The method includes selecting a parameter of interest among parameters estimated by each of a set of individual models, running the set of individual models with a range of inputs to obtain a range of estimates of the parameters from each of the set of individual models, and identifying, for each of the set of individual models, critical parameters among the parameters estimated, the critical parameters exhibiting a specified correlation with an error in estimation of the parameter of interest. For each subspace of combinations of the critical parameters, obtaining a parameter-based blended model is based on blending the set of individual models in accordance with the subspace of the critical parameters, the subspace defining a sub-range for each of the critical parameters.

97 MATHEMATICS AND COMPUTING↗

Shape memory polymer blend materials

An object comprising: a blend of (i) a phenol-containing polymer and (ii) a nitrile butadiene rubber; wherein the phenol-containing polymer is present in an amount of at least 5 wt % and up to about 95 wt % by total weight of components (i) and (ii). The object may further contain an electrically conducting component dispersed within the blend or on a surface of the blend. Also described is a method of thermal-activated reversible mechanical deformation of the object by (i) deforming the object at a first temperature, which is at or above the glass transition temperature of the object, and applying a stress on the object; (ii) fixing the deformed state by cooling the object to a second temperature of no more than 0° C. while under stress, and removing the stress; and (iii) recovering the object to the original shape by raising the temperature of the object to the first temperature.

Naskar, Amit K.↗

A comparison of mechanical properties from natural and process-induced interfaces in filament extrusion AM of polymer blends

Polymer blends are commonly tuned for specific applications to achieve desired properties otherwise inaccessible or prohibitively expensive to obtain via homopolymers. The interfacial characteristics of the polymer A-polymer B interface and resultant domain sizes govern key performance properties. Micro- and meso-scale morphology forms through the interplay of surface forces between the polymers and between each polymer and the surrounding atmosphere. Analogously, the layer-layer and road-road interfaces of material extrusion (MEX) additive manufacturing (AM) govern key performance properties of printed parts. This work explores the effect of layer height on the thermomechanical performance of polystyrene (PS)-polycarbonate (PC) blends. Filament is prepared from a 50/50 weight ratio of the two polymers and compared against dual-nozzle printing where every layer alternates between PS or PC homopolymer forming a part with an overall 50/50 polymer ratio. Typical indicators of polymer blend compatibility are also studied.

Chatham, Camden A.↗

Tradeoff between Intermolecular Interaction and Backbone Disorder by High Molecular Dipole Block for Improving Blend Morphology of Polymer Solar Cells

Constructing terpolymer has attracted increasing attention as a strategy to improve the performance of polymer solar cell. Terpolymer usually offers an opportunity to lower the frontier molecular orbital energy level, introduces additional absorption band and sometimes optimizes the morphology of the active blend. Generally, the additional segment in terpolymer backbone inevitably introduces backbone disorder, which causes entropy rises. However, selecting a suitable dipole unit introduces extra driving forces for crystallization by enhancing intermolecular interactions. This provides a handy knob for tradeoff between intermolecular interaction and backbone disorder, thus regulating the blend morphology. In this study, a high dipole and electron-deficient group of pyrrolo[3,4-f ]benzotriazole-5,7(6H)-dione (TzBI) is incorporated into the high-performance donor polymer and a series of terpolymers with different content of TzBI are designed. As expected, the morphology is optimized gradually for improving charge generation and charge transport, also suppressing charge recombination. The champion device with 10% TzBI exhibited a power conversion efficiency (PCE) of 18.36%, which is 5% increase compared to the controlled device. This study presents a charming terpolymer strategy by highly electron-deficient and high dipole segment to realize a tradeoff between intermolecular interaction and backbone disorder, facilitating the optimization of morphology and elevation of fill factor and device efficiency.

36 MATERIALS SCIENCE↗

Heterogeneous oxidation of hydrogen-natural gas blends in a safe, clean, and efficient burner design

The growth of hydrogen as an alternative clean fuel for fulfilling thermal energy needs of multiple economic sectors globally requires access to reliable, safe, energy efficient, emission free combustion technology. The work described in this short communication shows the applicability of a novel heterogeneous combustion design in utilizing a wide range of hydrogen blended methane concentrations to cleanly and safely generate thermal energy. The utilization of a simple first principles design approach along with engineered materials yielded a fuel-flexible hybrid infrared-convection burner design capable of lowering NOx emissions by more than 95% while simultaneously improving the heat transfer efficiency by 15% with a wide range of hydrogen concentrations. Here, the safety and performance of the combustion design was demonstrated in an burner at capacities of up to 12,000 Btu/h in producing temperatures of 900 °C. The atmospheric burner concept was integrated in a cooktop configuration with combined thermal power rating of 30,000 Btu/h and operated with hydrogen blended natural gas.

08 HYDROGEN↗

Optimization of Graphite–SiO blend electrodes for lithium-ion batteries: Stable cycling enabled by single-walled carbon nanotube conductive additive

Lithium-alloying materials are of great interest to improve the gravimetric and volumetric energy density of lithium-ion batteries, though their associated volume fluctuation with cycling often leads to poor cycling performance. Active-inactive alloys and blending alloys with carbon materials are common strategies to accommodate volume fluctuation. Herein we set out to optimize graphite-SiO blend electrode formulations to eliminate rapid capacity fade. Electrodes with highly stable cycling were prepared by simple planetary mixing procedures, enabled by the use of just a fraction of a weight percent of commercial SWCNTs as the only conductive additive, and by the appropriate choice of binder/stabilizing agent. In fact, the use of SWCNTs allowed for graphite-free SiO electrodes with approximately 74% higher volumetric energy density relative to traditional graphite electrodes, and superior capacity retention in coin-type full-cell testing versus NMC532 cathodes.

25 ENERGY STORAGE↗

Thermal diffusion, exhaust gas recirculation and blending effects on lean premixed hydrogen flames

Thermodiffusively-unstable lean premixed hydrogen flames are investigated using two-dimensional direct numerical simulation employing finite-rate chemical kinetics. Three databases are generated focussing on the inclusion of the Soret effect, the recirculation of exhaust gas, and blending with methane. A simple rescaling of a classic thermal diffusion model is presented and shown to mimic multicomponent diffusion with very low computational cost and little-to-no loss in accuracy. It is also shown that a previously developed model for mean local flame speeds in lean premixed hydrogen flames can still be used provided Soret effects are taken into account in one-dimensional calculations. The addition of exhaust gas to the unburned mixture is found to enhance thermodiffusive instability; the primary mechanism for this was shown to be the highly-efficient third-body nature of water, with the reduction of adiabatic flame temperature a second-order effect. Again, the existing mean local flame speed model proved sufficient. Finally, blending with methane was found to reduce the thermodiffusive response of the flame, more so than the existing model suggests, despite adjustment of the fuel Lewis number; an adapted model is presented to account for this.

08 HYDROGEN↗