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At least 325 records · Page 18

A comprehensive model to capture electrical discharge and spark channel evolution during spark-ignition processes

Emissions reduction through engine efficiency improvements is a priority for automakers who have turned to unconventional engine operation such as highly dilute, boosted, and stratified charge. Given its importance to flame initiation and sustained turbulent flame propagation, reliable and accurate spark ignition models are necessary to design ignition systems that reduce cyclic indicated mean effective pressure (IMEP) variability and increase engine efficiency in these operation modes. In this paper, secondary electric circuit, short-circuit, blowout, and re-strike sub-models are added to the Lagrangian-Eulerian spark ignition (LESI) model to simulate electrical discharge and spark channel elongation in an inert cross-flow combustion vessel. First, the physics of the underlying sub-models are described and the governing equations discussed with the spark channel voltage expression playing a critical role. Then, the experimental and simulations setups are presented. The results section begins with the derivation of spark channel voltage from experimental results. Then, electrical discharge and spark channel elongation simulations in inert flows are carried out using LESI and compared against experimental results. Finally, the results validate the model's ability to accurately predict spark channel elongation, as well as the occurrence of short-circuits, blowouts, re-strikes, and end of discharge.

42 ENGINEERING↗

Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation

Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materials or manufacturing techniques. Large language models (LLMs) could potentially bridge the gap. Their capacity to store and retrieve data from large databases provides them with a breadth of knowledge across disciplines. However, their generalized knowledge base can lack targeted, industry-specific knowledge. To this end, we present two LLM-based applications based on the GPT-4 architecture: (1) The Composites Guide: a system that provides expert knowledge on composites material and connects users with research and industry professionals who can provide additional support and (2) The Equipment Assistant: a system that provides guidance for manufacturing tool operation and material characterization. By combining the knowledge of general AI models with industry-specific knowledge, both applications are intended to provide more meaningful information for engineers. In this paper, we discuss the development of the applications and evaluate it through a benchmark and two informal user studies. The benchmark analysis uses the Rouge and Bertscore metrics to evaluate our models’ performance against GPT-4o. The results show that GPT-4o and the proposed models perform similarly or better on the ROUGE and BERTScore metrics. The two user studies supplement this quantitative evaluation by asking experts to provide qualitative and open-ended feedback about our model’s performance on a set of domain-specific questions. The results of both studies highlight a potential for more detailed and specific responses with the Composites Guide and the Equipment Assistant.

Kapoor, Gunnika [Oak Ridge National Laboratory (OR↗

Design of Novel Hot Gas Path Component for Gas Turbine Engines Enabled by Materials and Additive Manufacturing Process Development

This report covers the activities associated with the development and evaluation of two high-γ’ superalloys that were designed by external partners on this project, namely Carpenter Technologies Corporation and the University of California-Santa Barbra. One alloy was GammaPrint-700, a cobalt-base superalloy, and the other a nickel-base (Ni-base) superalloy GammaPrint-1100. Both were found to be printable through laser powder bed fusion (LPBF) additive manufacturing, with optimal process parameter sets being identified for each alloy. Further, high temperature mechanical testing was conducted on each alloy that showed both materials performed better than the comparative baseline (LPBF Hastelloy X), with the Ni-base superalloy being down-selected for scaling and printing of the tip shoe components.

36 MATERIALS SCIENCE↗

Spray Combustion and Soot Formation

Mitigating particulate matter (PM) emissions while simultaneously controlling nitrogen oxide and hydrocarbon emissions is critical for both gasoline and diesel engines. The problem is especially critical during cold-start cycles where aftertreatment devices are less effective. Understanding how liquid sprays and films form PM and designing to change the outcome requires advanced combustion concepts developed through joint experimental and computational efforts. However, existing spray and soot computational models are oversimplified and non-physical, and are therefore unable to reliably capture quantitative or even qualitative trends over a wide range of engine operating conditions. This task involves the development and application of advanced optical diagnostics and high-pressure gas and particle sampling/analysis in unique high-temperature, high-pressure vessels to investigate spray dynamics and soot formation with the objective of providing fundamental understanding about soot processes under relevant engine conditions to aid the development of improved soot models for commercial CFD codes

02 PETROLEUM↗

Flowability of Crumbler Rotary Shear Size-Reduced Granular Biomass: An Experiment-Informed Modeling Study on the Angle of Repose

Biomass has potential as a carbon-neutral alternative to petroleum for chemical and energy products. However, complete replacement of fossil fuel is contingent upon efficient processes to eliminate undesirable characteristics of biomass, e.g., low bulk density, variability, and storage-induced quality problems. Mechanical size reduction via comminution is a processing operation to engineer favorable biomass flowability in handling. Crumbler rotary shear mill has been empirically demonstrated to produce more uniformly shaped particles with higher flowability than hammermilled biomass. This study combines modeling and experimentation to unveil fundamental understandings of the relation between granular particle characteristics and biomass flow behavior, which elucidate underlying mechanisms and guide selection of critical processing parameters. For this purpose, the impact of critical material attributes, including particle size (2–6 mm), particle shape (briquette, chip, clumped-sphere, cube, etc.), and surface roughness, on the angle of repose (AOR) of milled pine chips were investigated using discrete element method (DEM) simulations. Forest Concepts Crumbler rotary shear system is used to produce milled pine particles within the same size range considered in DEM simulations. AOR of different sets of these particles were measured experimentally to benchmark DEM results against experimental data. Specific energy consumption for the comminution of biomass with different particle size and moisture content are measured for technoeconomic analysis. Our results show that the smaller size (2 mm) of pine particle achieves better followability (i.e., smaller AOR) while the energy cost of comminution is significantly higher and bulk density is almost the same as the 6-mm pine particles. For the 2-mm particle size, Crumbles from veneer have better flow properties than Crumbles from chips. Contrarily, no significant difference was observed between the AOR of the two materials for the 6-mm particle size. Furthermore, from DEM simulations, mechanical interlocking between particles was found as a dominant factor in determining AOR of complex-shaped particles such as milled pine, which cannot be accurately captured by using simple particle shapes (e.g., mono-sphere) with a rolling resistance model. Conversely, clumped-sphere model alleviates this limitation without increasing computational cost significantly and can be used for accurate representation of biomass granular particles when simulating free-flow behavior.

09 BIOMASS FUELS↗

Water treatment based on atomically engineered materials: Atomic layer deposition and beyond

Global water stress and challenges for producing sufficient supplies of fit-for-purpose water are amplifying. Atomically engineered interfaces are emerging as a powerful tool in the fabrication of advanced water treatment materials. Atomic layer deposition (ALD) and recently developed related methods, such as sequential infiltration synthesis (SIS), offer a tremendously diverse library of chemistries for interface functionalization. Thickness, stoichiometry, and physicochemical properties can be manipulated with precision. We review their fundamental physical chemistry and processing factors. ALD/SIS engineering strategies, including direct deposition, growth with intermediate layers, and secondary treatment are presented with realization of efficient water treatment. We lay out a pathway to establishing an ALD/SIS-based universal functionalization platform for water treatment, including sensitization strategies, in situ regulation, secondary reactions, and simulation/machine learning. Furthermore, we also provide a perspective on ALD/SIS-based interface engineering via synergy with other widely used interface engineering techniques to develop facile, versatile, and energy-efficient strategies for tackling increasingly complex water challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A fast reduced model for a shell-and-tube based latent heat thermal energy storage heat exchanger and its application for cost optimal design by nonlinear programming

Numerical simulation of latent heat thermal energy storage (LHTES) systems plays a fundamental role in studying the physical process and guiding the engineering design. Discretization of the PDEs describing the nonlinear solidification/melting process of phase change materials (PCMs) leads to a large-scale complex dynamics system, where the system behavior depends on a set of parameters. In a design setting, repeated model evaluations are required over the set of parameters results in significant computational burden. In this paper, an explicit analytic solution was built for the propagation of the solidification front in a cylindrical coordinate. The analytic solution approach is further employed to develop a low computational reduced model (RM) as a module for a shell-and-tube based LHTES heat exchanger. The levelized Cost of Energy (LCOE) is used as a design metric and the RM model is used to apply system-level constraints in the nonlinear programming formulation that facilitates efficient global optimal design of the PCM properties, flow conditions and tube geometries. The use of LCOE as the design metric prevents over design of the heat transfer rate and also establishes a fair ground for evaluation of different thermal storage technologies and their integrated applications with other systems. Optimal results showed that a higher effectiveness results in a higher LCOE; the velocity of the HTF and the length of the channel are highly correlated with each other; both larger PCM latent energy and conductivity result in lower LCOE.

25 ENERGY STORAGE↗

Operation of internal combustion engine with improved fuel efficiency

A process of operating a spark-ignited internal combustion engine (SI-ICE) with improved fuel efficiency and reduced emissions including under steady state and under lean-operating conditions at high overall air to fuel (AFR) ratios. A first supply of high octane hydrocarbon fuel, such as gasoline or natural gas, and a first supply of oxidant are fed to a fuel reformer to produce a gaseous reformate with a reforming efficiency of greater than 75 percent relative to equilibrium. The gaseous reformate is mixed with a second supply of oxidant, after which the resulting reformate blended oxidant is fed with a second supply of high octane hydrocarbon fuel to the SI-ICE for combustion. Steady state fuel efficiency is improved by more than 3 percent, when the reformate comprises from greater than about 1 to less than about 18 percent of the total volume of reformate blended oxidant fed to the engine.

33 ADVANCED PROPULSION SYSTEMS↗

Bioblendstocks to Optimize Mixing Controlled Compression Ignition (MCCI) Engines

In this project, a team of researchers from the University of Massachusetts Lowell, the University of Maine, and Mainstream Engineering developed an integrated process for the product of bioblendstocks to optimize mixing controlled compression ignition (MCCI) engines. The objective was to improve the energy density, sooting propensity, and cetane number of base diesel fuel while maintaining cold weather behavior. The process converts woody biomass (e.g. sawmill residues) into bio-oil through selective fast pyrolysis; the bio-oil is then selectively upgraded to form selectively oxygenated, minimally-branched hydrocarbons using non-noble metal catalysts in combination with metal-catalyzed hydrogenation. Advanced predictive models, in conjunction with existing property databases, and experimental testing are used to evaluate overall bioblendstock properties and their impact on base diesel fuel. An iterative, targeted upgrading approach was implemented to optimize the proposed bioblendstock’s properties. Assessment methodologies included techno-economic analysis, life-cycle assessment, property testing, and engine testing. Ultimately, the project team successfully produced a viable bioblendstock while identifying critical process points related to scale-up efforts. It was found that producing pyrolysis oils at 500 degrees C and with pine particle sizes of 1-2 mm led to bio-oil with a higher yield (of approximately 45 wt%) and rich amounts of aromatic alcohols. The resultant pyrolysis oil was then upgraded using a sequence of mild hydrotreating, followed by catalytic etherification and esterification, followed by another final mild hydrotreating to produce a blendstock containing saturated species with a limited, but non-zero, amount of oxygen. The aromatic alcohols produced by pyrolysis were especially helpful in this regard, as the resulting bicycloethers and derivatives exhibited high cetane numbers. While most bulk properties of the bioblendstock met or exceeded targeted thresholds, viscosity and cloud point notably fell outside the expected range; this could be addressed by blending limits and/or through the use of additives that are commonplace in current refinding practices. Identification of a bioblendstock that can be produced economically at scale while improving the performance and emissions characteristics of internal combustion engines positively affects the economy by boosting domestic fuel production and the environment by decreasing harmful emissions and increasing efficiency.

09 BIOMASS FUELS↗

CO 2 Capture Using Electrochemically Mediated Amine Regeneration

We describe the current status of our research on, and the development of, the Electrochemically Mediated Amine Regeneration (EMAR) process for the capture of CO2 from flue gases. The absorption step in the EMAR process is the same as in the widely used amine process, but the desorption step is accomplished electrochemically as opposed to by a thermal swing used in the amine process. Our laboratory unit has operated continuously for over 200 h, spanning 130 absorption/desorption cycles. We have established an understanding of the thermodynamics of the EMAR process and provided engineering estimates of key features (energetics and sizing) of this technology. The EMAR system does not rely on steam integration, making it a truly plug-and-play unit that can be easily deployed for a range of applications. The EMAR system can also be scaled-down for distributed, modular, and small-scale operations (e.g., stainless steel mini-mills, etc.). Here, results to date indicate that the EMAR process has the potential to be a viable option for post-combustion CO2 capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. Here, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

33 ADVANCED PROPULSION SYSTEMS↗

Reflection on the Challenges, Accomplishments, and New Frontiers of Gene Drives

Ongoing pest and disease outbreaks pose a serious threat to human, crop, and animal lives, emphasizing the need for constant genetic discoveries that could serve as mitigation strategies. Gene drives are genetic engineering approaches discovered decades ago that may allow quick, super-Mendelian dissemination of genetic modifications in wild populations, offering hopes for medicine, agriculture, and ecology in combating diseases. Following its first discovery, several naturally occurring selfish genetic elements were identified and several gene drive mechanisms that could attain relatively high threshold population replacement have been proposed. This review provides a comprehensive overview of the recent advances in gene drive research with a particular emphasis on CRISPR-Cas gene drives, the technology that has revolutionized the process of genome engineering. Herein, we discuss the benefits and caveats of this technology and place it within the context of natural gene drives discovered to date and various synthetic drives engineered. Later, we elaborate on the strategies for designing synthetic drive systems to address resistance issues and prevent them from altering the entire wild populations. Lastly, we highlight the major applications of synthetic CRISPR-based gene drives in different living organisms, including plants, animals, and microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

Ethanol to diesel: a sustainable alternative for the heavy-duty transportation sector

The combustion of middle distillates (diesel and jet fuel) is responsible for the emission of more than 2 GTon of CO 2 per year worldwide. While sustainable alternatives exist for gasoline and jet fuel, we still lack sustainable alternatives for diesel. This fact is especially relevant if we consider that electrification of sectors where diesel is used is challenging. One sustainable approach for diesel production is the catalytic upgrading of ethanol. While most work in this field has focused on the dehydration/oligomerization of ethanol, this approach is limited to producing fuels that have a high degree of branching and low cetane number. Another approach is the sequential use of ethanol Guerbet coupling, leading to higher alcohols, followed by etherification, leading to large ethers which, importantly, result in a product with high cetane number. In this work, we explore the catalytic upgrading of ethanol into diesel following an approach based on the initial Guerbet coupling of ethanol followed by etherification. The results presented are a collaborative and synergic effort among process and systems engineers, experimentalist in the area of catalysis, and fuel property modelers. Here, we demonstrate experimentally the feasibility of upgrading ethanol into a diesel fuel with properties that surpass its fossil counterpart. The diesel produced has a predicted cetane number of ~70 and outstanding cold flow properties, while maintaining other properties (viscosity, density, and flash point) within expected ranges. A technoeconomic analysis performed based on a detailed biorefinery model shows that the MFSP is ~5.89$ per Gal in 2021 dollars when lignocellulosic ethanol is used, with the most relevant economic driver the cost of the ethanol feedstock. The upgrading process can be performed with a net energy gain (EROI = 1.49 > 1). An LCA analysis of greenhouse gas (GHG) emissions reveals that the use of lignocellulosic ethanol may lead to more than 50% reduction in GHG emissions compared to fossil diesel. Depending on the CO 2 emissions associated with the production of ethanol we show that in some instances the production of carbon neutral diesel fuel is possible.

09 BIOMASS FUELS↗

Project Development of an Electrochemical Denitration and Caustic Generation System for HLW Pretreatment at Hanford - 26350

An engineering-scale electrochemical processing skid is proposed to perform the denitration of Hanford tank waste, which would help to mitigate a key process concern with the direct feed processing of the Hanford Tank Waste Treatment and Immobilization Plant (WTP). The reduction of nitrates and organic compounds in the waste feed will directly reduce hazardous NOx and ammonia gases generated during the vitrification process, which in turn will aid in addressing potential regulatory and safety challenges associated with processing large volumes of tank waste. This paper highlights the past legacy work, project layout, accomplishments from Phase 1 and research and development envisioned for Phase 2. An innovative electrochemical denitration and caustic generation (EDCGe) process was demonstrated for the pretreatment of tank waste at the Savannah River Site (SRS) in the early 2000s. The denitration electrolyzer, off-gas abatement system, and caustic generator electrolyzer are being developed with the intent that the denitration electrolyzer will convert nitrate and nitrite anions to nitrogen gas while also yielding other gaseous byproducts, which may include N2O, NH3, VOCs, and H2. The gaseous byproducts will be managed via a tandem off-gas catalyst-bed treatment system. The caustic generation electrolyzer will recycle NaOH from the feed to produce a clean caustic stream for use within the batching tanks at Hanford, aiding in the preparation of waste for WTP. The reduction in hazardous emissions and improved waste treatment processes provides a robust solution for nuclear waste management, contributing to environmental safety and regulatory compliance. The EDCGe technology is being adapted, modified, and updated for the preparation of the Direct Feed-High Level Waste (DF-HLW) flowsheet at Hanford. Phase 1 demonstrated a bench-scale proof-of-concept for reactions involving the denitration electrolyzer and gas phase abatement of ammonia. The electrochemical technology is drawing on the scientific outcomes that were reported in the legacy work. The results from Phase 1 demonstrated the viability of the EDCGe system in reducing the nitrogen species of simple non-radioactive waste simulants. Commercially available alloys used as electrode materials and membranes are being studied for the denitration and caustic generation electrolyzers. The continuation of this project holds promise for broader applications, such as energy-efficient ammonia production, and contributes significant advancements in nuclear waste management. Additional material discovery has been investigated into ceramic Na super ion conductive (NaSICON) materials and off-gas abatement catalyst discovery. NaSICON is of interest for selective transport of Na within the electrolyzers to make a clean caustic stream. Future integration and optimization efforts, informed by Phase 1 results and ongoing research, will continue to drive advancements in nuclear waste management technology. The technology developed for the EDCGe treatment of tank waste will also have broader potential to inform other fields, such as energy-efficient ammonia production, as well as ammonia abatement catalysis through the lessons learned in electrochemical nitrate reduction. The applications and benefits of this research extend beyond Hanford and the Savannah River Site, supported by a collaborative team of scientists and engineers from national labs, academia, and industry, ensuring a comprehensive approach to solving complex waste treatment challenges. The team is leveraging advanced electrochemical technologies, machine learning, novel catalysts tailored for gaseous nitrogen species, and cutting-edge reactor systems to enhance the process efficiency and effectiveness of the denitration process.

Rodene, Dylan [Savannah River National Laboratory ↗

Thermodynamic and Kinetic Transitions of Liquids in Nanoconfinement

Core principles of chemistry are ubiquitously invoked to shed light on the nature of molecular level interactions in nanoconfined fluids, which play a pivotal role in a wide range of processes in geochemistry, biology, and engineering. A detailed understanding of the physicochemical processes involved in the flow, structural transitions, and freezing or melting behavior of fluids confined within nanometer-sized pores of solid materials is thus of enormous importance for both basic research and technological applications. This Account provides a perspective on new insights into the thermodynamic and kinetic transitions of nanoconfined fluids in their stable and metastable forms. After briefly introducing the unique properties of mesoporous silicas from the SBA, MCM, and FDU families that serve as the confinement matrices, combining highly ordered single and bimodal mesopore architectures with tunable pore sizes in the ~2-15 nm range and narrow size distributions, recent studies on melting/freezing behavior of water confined in these host matrices are reviewed. While differential scanning calorimetry (DSC) reveals a linear relationship between melting point depression and pore size (independent of the pore shape), as predicted by the Gibbs-Thomson relation, variable temperature 2 H wide-line nuclear magnetic resonance (NMR) spectroscopy studies confirm the core-shell model of water and give evidence for a layer-by-layer freezing mechanism, which gives rise to an apparent fragile-to-strong transition in the solidification dynamics. In contrast to the freezing/melting behavior of water, the effect of nanoconfinement on the glass transition of supercooled liquids is nonuniversal and the glass transition temperature T g can either increase or decrease with the dimensionality and extent of confinement. This nonuniversal behavior is exemplified by the two glass-forming molecular liquids, glycerol and ortho-terphenyl (OTP). While glycerol shows an increase in T g and a pronounced slowdown of the rotational dynamics of the constituent molecules due to a change in the molecular packing between the bulk and the confined liquid, OTP displays a linear and confining-media-dependent depression of T g with increased confinement that is strongly influenced by the pore-liquid interface characteristics. This Account concludes with a focus on recent experimental evidence of extreme spatial and dynamical heterogeneity in both freezing and glass transition processes. This discovery was enabled by the unique mesoporous structures of SBA-16 and FDU-5, possessing bimodal architectures with two interconnected pore types of different size and shape (spherical and cylindrical). For the very first time, two melting points for water and two glass transitions for supercooled OTP, corresponding to a specific pore type, were observed. Collectively, these observations strongly suggest a close mechanistic connection between the local fluctuations in the structure and dynamics of nanoconfined liquids. Finally, while the findings reviewed in this Account provide new insights into thermodynamic and kinetic transitions of fluids, there remain many unanswered questions regarding the effects of nanoconfinement on the fundamental properties of fluids, which offer exciting future opportunities in chemical research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fuel Property Effects on Knock Propensity and Thermal Efficiency in a Direct-Injection Spark-Ignition Engine

Engine knock remains one of the major barriers to further improvement in thermal efficiency of Direct-Injection Spark-Ignition (DISI) engines. While Research Octane Number and Motor Octane Number are often used as standard rating methods for knock resistance of fuels, the impacts of other fuel properties on knock propensity in modern engines such as heat of vaporization (HoV) and laminar flame speed (LFS) require better understanding in order to co-optimize fuels and engine designs to achieve higher thermal efficiency and lower CO2 emission. In the present study, computational fluid dynamics (CFD) is used to model a boosted DISI engine with a focus on knock prediction and fuel property effects. A level-set G-equation model is employed to capture turbulent premixed combustion, and is coupled with a transported Livengood-Wu (L-W) integral approach to predict autoignition in the unburnt region. A criterion associated with the L-W integral is developed to accurately predict knock onset and knock-limited spark-advance. This model is then applied to a sensitivity analysis of HoV and LFS on knock tendency and thermal efficiency. The pressure-temperature trajectory framework is applied and extended to study the fuel effects on auto-ignition process in the engine. An existing efficiency-based merit function, which is derived from experiments for boosted SI engines, is evaluated and improved based on the current CFD results.

DISI↗