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DOE OSTI2024

Electric Vehicle Charging for Residential and Commercial Energy Codes: Technical Brief

Numerous studies show that sales of electric vehicles (EVs) have grown consistently over recent years in the U.S. The U.S. Energy Information Administration (EIA) estimated 3 million EVs were on the road in 2022, and the Edison Electric Institute (EEI) forecasts a total of 26.4 million EVs on the road by 2030. Based on this forecast, EEI projects the need for an additional 12.9 million EV charge ports by 2030. If EV charging infrastructure fails to keep pace with sales of EVs it could result in consumers stranded without options to power their vehicles. EVs are capable of providing substantial benefits to the consumers. EVs are less expensive to operate than conventional internal combustion engine vehicles, have lower maintenance costs, and have the convenience of fueling (charging) at home or work. Studies conducted in California show that costs associated with installing EV charging infrastructure can be substantially more expensive for retrofit scenarios compared to new construction, making inclusion of EV infrastructure in new construction codes a cost-effective policy option to increase infrastructure to meet growing demands. PNNL tracks adoption of mandatory EV provisions across the U.S. As of December 20, 2024, 12 states (California, Oregon, Washington, Colorado, New Mexico, Illinois, Maryland, Delaware, New Jersey, Rhode Island, Massachusetts and Vermont) and 53 local governments have added EV provisions to their building codes, local ordinances and zoning requirements. Originally published in 2022, this tech brief has been revised to align with recent model energy code committee discussions and published EV infrastructure code language. This technical brief summarizes market trends, costs and benefits, and provides sample code language for EV charging infrastructure for consideration to be included in model codes, such as the International Energy Conservation Code (IECC) and ANSI/ASHRAE/IES Standard 90.1, as well as directly by states and local governments in their building codes. The technical brief summarizes related efforts undertaken by states and local governments, and builds upon language considered during the 2021 and 2024 IECC development cycles.

2021 IECC↗
DOE OSTI2023

Computational study of the ECN spray C via one-way coupling of internal nozzle flow and ensuing spray

Here, in this study, computational fluid dynamics simulations of the Engine Combustion Network Spray C injector were performed to investigate the effect of the internal nozzle flow on the development of the ensuing spray in automotive fuel injectors. A set of simulation best practices was first developed to achieve an accurate representation of the internal nozzle flow. Detailed, spatiotemporally defined information was extracted at the injector’s orifice exit and stored in maps that were subsequently employed to initialize a Lagrangian spray by means of a static, one-way coupling (OWC) approach. To highlight the impact of the in-nozzle flow on the spray, the OWC approach was compared with the conventional rate-of-injection (ROI) approach, for which the spray parcels are commonly initialized using a blob injection model. The results indicated that, using the ROI approach, considerable evaporation was observed within the plume in the near-nozzle region. On the other hand, the OWC approach showed evidence of evaporation farther downstream and at the plume periphery. The different behavior observed with the two approaches was mostly due to substantial differences in fuel mass distribution. The liquid fuel concentration predicted by the OWC approach matched well with X-ray tomography measurements of projected fuel mass per unit volume, in terms of both magnitude and distribution. In contrast, an unphysical distribution of fuel mass characterized by an extremely low liquid concentration was predicted by the ROI approach. In the far-field, the effect of the in-nozzle flow was found to be weaker as the spray penetrated and interacted with the ambient gas. In this region, the OWC and ROI approaches provided similar predictions of vapor penetration, spray morphology, and mixing-related characteristics.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Detailed chemistry modeling of rotating detonations with dilute n -heptane sprays and preheated air

Utilization of liquid fuels is crucial to enabling commercialization of rotating detonation engines (RDE) in the near future. In this study, Eulerian-Lagrangian simulations are conducted for rotating detonative combustion with dilute n-heptane sprays and preheated air. Two-dimensional flattened configuration is used and a skeletal chemical mechanism with 44 species and 112 elementary reactions for n-heptane combustion is adopted. The flow structure, droplet distribution, and thermochemical parameters in the refill zone are first analyzed. It is shown that the mixture in the refill zone is heterogeneous, including evaporating droplets, vapor, and air. When the total temperature is below 950 K, the average equivalence ratio increases with the total temperature. When it is higher than 950 K, the average equivalence ratio is almost constant. Subsequently, the chemical explosive mode analysis is applied to identify the controlling reactions and dominant combustion modes in the fuel refill zone and reaction fronts. Results demonstrate that the initiation reaction (R104: n-C 7 H 16 + O 2 2-C 7 H 15 + HO 2 ) and low-temperature reaction (R107: RO 2 R'O 2 H) are dominant in the upstream and downstream of the refill zone, respectively. The intermediate species from low-temperature chemistry, R'O 2 H, is found to be important for the chemical explosive mode in the undetonated mixture. The influence of species diffusion and dispersed droplets is further analyzed. Results show that vapor autoignition facilitated by droplet evaporation occurs in the refill zone. Finally, the effects of the air total temperature on the detonation propagation speed and RDE propulsion performance are investigated. Further, it is found that the detonation propagation speed and specific impulse increase with air total temperature. The total pressure ratio first increases and then decreases as the air total temperature increases. Moreover, when the total temperature of the preheated air is above 1,300 K, the effects of low-temperature chemistry are negligible.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Modeling of the effects of non-equilibrium excitation and electrode geometry on H 2 /air ignition in a nanosecond plasma discharge

In this work, we present the results of two-dimensional modeling of the effects of non-equilibrium excitation and electrode geometry on H 2 /air ignition in a nanosecond plasma discharge. A multiscale adaptive reduced chemistry solver for plasma assisted combustion (MARCS-PAC) based on PASSKEy discharge modeling package and compressible multi-component reactive flow solver ASURF+ is developed and validated. This model is applied to simulate the impact of non-equilibrium plasma excitation and electrode geometry and heat loss on the dynamics of the discharge from streamer to spark and ignition kernel development in a H 2 /air mixture with a pair of cylindrical electrodes. The results show that the plasmagenerated species (N 2 (A), N 2 (B), N 2 (a'), N 2 (C), O( 1 D), O and H) in the spark and afterglow significantly accelerate the ignition kernel development. The increase of discharge voltage at the same total discharge energy promotes the non-equilibrium active species production. It is found that the production of electronically excited species at higher reduced electric field strength is more efficient in enhancing ignition in comparison to the vibrational excitation and heating. Moreover, the 2D simulation clearly reveals that the electric field and active species distribution are highly non-uniform. The streamers are initiated at the sharp outer edges of the negative and positive electrodes by a strong electric field while the electric field is much weaker at the centerline of the electrodes. Furthermore, the simulations reveal that the ignition enhancement is sensitive to the variation of electrode shape, diameter, and gap size due to the changes of electric field distribution and location of streamer formation. A cylindrical electrode produces a larger discharge volume and ignition kernel than the parabolic and spherical electrodes, when the discharge is localized near the axis of the gap. It is found that there is a non-monotonic dependence of ignition kernel size on the electrode diameter and inter-electrode distance. The increase of electrode diameter and gap size above the optimal conditions leads to the reduction of ignition kernel volume, due to the decrease of active species concentration and gas temperature. At a larger electrode surface area and electrode diameter as well as smaller electrode gap size, the heat loss to electrode plays a greater role in reducing the ignition kernel size and slowing ignition kernel development. This work provides insights and guidance to understand the kinetic enhancement of non-equilibrium plasma and the effects of electrode geometries on ignition for the optimization ignitors in advanced engines.

42 ENGINEERING↗
DOE OSTI2021

Aerosol emissions from water-lean solvents for post-combustion CO 2 capture

Advanced water-lean solvents (WLS) for post-combustion CO 2 capture have been gaining interest due to their ability to reduce the parasitic penalty from energy needed for solvent regeneration. Commercial implementation of these novel CO 2 capture technologies hinges on successful control of amine emissions. RTI conducted a parametric study of fundamental and operational variables influence on overall amine aerosol and vapor emissions from our water-lean solvent eCO 2 Sol™ using our 6-kW equivalent bench-scale gas absorption system. The parametric testing used a simulated flue gas with 15 % CO 2 , 2.3–4.2 % H 2 O, and 0–6 ppm sulfite (SO 3 ) to examine the impact of the presence of aerosols to the capture performance and amine emissions from the system. The SO 3 reacts with water in the flue gas to create H 2 SO 4 , which forms liquid aerosol droplets and provide nucleation sites for growth of aerosols. Scanning Mobility Particle Sizer and Aerodynamic Particle Sizer instruments monitored the aerosol particle size distribution. Parametric testing results suggested that the presence of the aerosols in the flue gas could increase the overall amine emissions by 10X compared to the baseline emissions from WLS’s vapor pressure. Principal component analysis (PCA) and projection to latent squares (PLS) developed models to predict the aerosol-based amine emissions from process data. The predictive PLS model had a correlation coefficient (Q 2 ) of 0.92 and could predict the aerosol-based emissions from the NAS process with ±15 % accuracy (average absolute deviation, AAD). The PLS regression model also identified key variables affecting aerosol-based emissions from WLS.

42 ENGINEERING↗
DOE OSTI2020

Hybrid Ceramic-CMC Vane with EBC for Future Coal Derived Syngas Fired 65% Efficient Turbine Combined Cycle

The efficiency of both simple cycle and combined cycle power generation systems scale with the peak temperature at which the gas exits the combustor to drive the turbine. In conventional systems, a substantial fraction of the total turbine core flow exiting the compressor is diverted downstream to cool metallic turbine hardware rather than power the turbine, much of which is used to cool the first-stage turbine vane. The use of coal derived syngas fuels provides an additional challenge to the lifetime of materials utilized in the turbine, as particulate byproducts created in the coal gasification process melt in the combustion gas, and can subsequently deposit and interact with the turbine hardware. The development of durable hot-section materials capable of operating at temperature well above that of single crystal superalloy airfoil/zirconia based thermal barrier coatings is critical to realizing 65% efficient coal derived syngas fired gas turbine based power systems. To enable higher turbine inlet temperatures while lowering cooling air requirements, United Technologies Research Center (UTRC), the central R&D laboratory supporting UT Pratt & Whitney, led the conceptual design of a new type of ceramic composite turbine hot section materials system. The design focused on a novel hybrid monolithic ceramic-fiber reinforced ceramic matrix composite (CMC) first stage turbine vane having an environmental barrier coating. By utilizing ceramic construction in the turbine hot-section, the core flow normally used to cool metallic components will be substantially reduced, increasing efficiency and reducing emissions. To provide the framework for future demonstration testing, UTRC partnered with University of North Dakota Energy and Environmental Research Center (UNDEERC) to provide a conceptual design for a gasified coal fed high-pressure turbine combustor system designed to mimic the conditions expected in a future 65% fuel to busbar efficient syngas fueled gas turbine based combined cycle. The UNDEERC and UTRC collaborated on characterizing dusts from coal gasifier filtration systems.

10 SYNTHETIC FUELS↗
DOE OSTI2025

Vehicle-Cycle Inventory for Type C School Buses & Intra-City Transit Buses

This report documents the new inventory incorporated into the Research and Development version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) 2025 model for the vehicle cycle of Type C school buses and intracity transit buses. The transportation sector contributes significantly to the United States’ energy consumption and resultant emissions (EPA, 2025a). However, public transit plays an important role in mitigating these impacts because it consumes a relatively low amount of energy per passenger (Congressional Budget Office, 2022). Public transit is widely used in the United States; more than 500,000 school buses (EPA, 2025b) and ~75,000 service buses (American Public Transportation Association, 2025) operate in the nation. These are primarily internal combustion engine vehicles (ICEVs) powered by diesel. Original equipment manufacturers (OEMs) are making efforts to electrify U.S. bus fleets by using batteries as a propulsion system to replace internal combustion engines. Electrification can reduce tailpipe emissions, such as particulate matter (with a diameter ≤10 µm [PM 10 ] and with a diameter ≤2.5 µm [PM 2.5 ]) and nitrogen oxides (Jonas et al., 2025; Martinez and Samaras, 2024; EPA, 2025b; Wayne et al., 2009). Hence, any energy and emission impact analysis of public transit must consider both conventional ICEVs and upcoming electric vehicle (EV) options for the school and transit buses that dominate this landscape. To understand the detailed environmental impact profiles of ICEV and EV school and transit buses, it is necessary to conduct a thorough analysis covering both vehicle manufacturing and vehicle use stages. The current literature lacks a detailed vehicle-cycle inventory for school and transit buses, which makes this kind of comparison difficult. To overcome this gap, we developed a comprehensive vehicle-cycle model for school and transit buses in Argonne’s R&D GREET 2025 model. The model is flexible in handling user inputs for key assumptions, such as component weights and material compositions, upstream energy sources for material processing, and vehicle operating parameters, to understand their impacts on energy use and emissions for both school and transit buses. This report is organized as follows: Section 2 provides details on the modeling approach and vehicle specifications (weights and composition of different vehicle components, and vehicle operating parameters) for both school and transit buses. Section 3 provides details on vehicle assembly, disposal, and recycling (ADR) approaches for the two buses. Section 4 includes details about their incorporation into the R&D GREET model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Numerical and experimental investigation of the flame kernel growth in a methane/air mixture near the lean flammability limit

Lean combustion has the potential to improve the thermal efficiency of spark-ignition engines, but it faces the significant challenge of increased cycle-to-cycle variation due to low mixture reactivity and unstable flame dynamics. Computational fluid dynamics (CFD) employing predictive models can guide engine design and optimize operating strategies for lean combustion. However, ignition and combustion models have rarely been validated at fuel-lean conditions, and a fundamental understanding of the early flame kernel growth process is also lacking for a successful sub-model development. Here, the present study develops a numerical simulation framework used to investigate early flame kernel growth in methane/air mixtures. A nanosecond-pulsed discharge (NPD) approach is employed to effectively decouple the flame kernel growth from the electrical discharge due to their difference in timescales, and equivalence ratios near the experimentally measured lean flammability limit (LFL) are selected to focus on challenging mixture conditions. Three numerical investigations, such as the choice of turbulence modeling, grid size, and grid control strategies, are examined to match both LFL and flame kernel structure measured from experiments. It is demonstrated that a quasi-direct numerical simulation (QDNS) with a fixed grid embedding of 10 μm can predict the LFL as φ CFD =0.61 and match the displacement speed of the kernel’s boundary marked in schlieren images. To predict the LFL and flame kernel shape, a fine grid (Δ≤12.5 μm) is needed to capture the consumption of formaldehyde (CH 2 O) in kernel’s reaction branches attached to the anode, and adaptive mesh refinement is replaced with the fixed embedding due to loss of simulation accuracy. Also, it is found that a large-eddy simulation (LES) using the Dynamic Structure model is not suitable for the NPD-induced flame kernel simulation because artificial sub-grid turbulent kinetic energy induced by shock dynamics alters the flow velocity calculation, resulting in divergence of LES from QDNS. Lastly, the simulation well matches the experimental data for the flame kernel evolution in three mixture conditions (φ = 0.7, 0.61, 0.55), showing toroidal flame kernel expansion and flame kernel growth/extinction.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Understanding how chemical structure affects ignition-delay-time $\phi$-sensitivity

$\phi$-sensitivity is the change in ignition delay time (IDT) with respect to the fuel-to-air equivalence ratio ($\phi$). High $\phi$-sensitivity is a desirable fuel property for applications in advanced compression ignition and multi-mode engine designs. Understanding how $\phi$-sensitivity depends on chemical structure is essential for selecting promising biofuels from the ever-growing list of proposed candidates. Here, we investigate the effect of chemical structure on $\phi$-sensitivity with experiment, simulation, and theory. Experimental Advanced Fuel Ignition Delay Analyzer (AFIDA) measurements for 2,4-dimethylpentane and diisopropyl ether provide evidence that branching and functional groups strongly impact $\phi$-sensitivity. Further insights into this dependence are obtained with 0-D kinetic simulations with existing mechanisms for n-pentane, diethyl ether, 3-pentanone, n-heptane, 2-methylhexane, 2,4-dimethylpentane, and 2,2,3-trimethylbutane. Quantum mechanical (QM) G4 calculations of low-temperature reactions help explain the observed experimental and simulation trends. Specifically, these QM calculations provide theoretical estimates of the ketohydroperoxide (KHP) dissociation rates, the HO 2 formation rates from peroxy radical (ROO), and the “cross-over” temperatures, i.e., the temperature at which ROO dissociation is favored compared to hydroperoxyl radical (QOOH) formation. Each of these reaction rates is compared to the n-alkane reference point to determine the impact of branching and different functional groups. Although kinetic mechanisms typically assume that KHP dissociation rates are invariant of chemical environment, our QM results suggest that this rate can span a range of roughly two orders of magnitude. We also discuss the importance of including the peroxy-hydroperoxy (OO-OOH) hydrogen transfer reaction for branched ethers. Finally, the insights gained assist in proposing a highly $\phi$-sensitive compound, namely, isopropyl propyl ether.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

INVESTIGATION OF TURBULENT JETS, SPRAYS, AND SUPERCRITICAL MIXING BY TIME RESOLVED RAINBOW SCHLIEREN DEFLECTOMETRY

As technological advancements have enabled higher efficiency compression ignition (CI) engines (diesel engines) by operating at higher pressures and temperatures, the mechanisms of fuel-air mixing are postulated to change. Thus, there is a greater need for experimental data to develop and verify new phenomena. However, the fast time scales and harsh environments associated with CI engines present many experimental difficulties and requires high quality non-intrusive diagnostics to obtain useful data. The diagnostics itself must be validated prior to its implementation in an engine environment. The purpose of this research is to advance rainbow schlieren deflectometry (RSD) to study turbulent fuel sprays including the effects of supercritical mixing in CI engine environments. This objective is met by developing and applying quantitative RSD, for the first time, to three separate aspects of fuel sprays: 1) turbulent mixing, 2) phase boundaries, and 3) non-ideal gas mixing. First, quantitative RSD is demonstrated for turbulent mixing in a canonical helium jet. Rayleigh scattering data in the literature is used to validate the concentration measurements obtained by RSD. The results also provide explanations for phenomena occurring in the helium jet and provide data not yet present in the literature. Second, RSD is applied to high pressure multi-phase fuel sprays and new methodologies are developed to distinguish the liquid region from the vapor region and to quantify the in-between region on a probabilistic basis. Isolating liquid and vapor regions generally requires two separate diagnostics, e.g., Mie scattering (liquid region) and Rayleigh scattering (vapor region). However, the results of this study demonstrate that RSD can be used as a single diagnostic to measure both liquid and vapor boundaries. Third, the optical-to-thermodynamic relations associated with refrac-tometry are investigated under non-ideal gas mixing conditions to develop a generalized relationship valid for both ideal or non-ideal gas mixing. The last part of this research develops the theoretical tools to understand and experimentally realize supercritical mixing at diesel conditions. Guided by the theoretical analysis, RSD is applied to compare supercritical versus transcritical mixing at CI conditions using a constant pressure test rig. It is found that while fully supercritical mixing ers benefits in diesel engines, i.e, faster mixing times (50% higher velocities), the absence of droplets which cause high levels of particulate emissions, etc., it would be difficult to achieve in practice because of the requirements of fuels with low critical temperature and/or substantial fuel preheating.

02 PETROLEUM↗
DOE OSTI2022

What Makes You Hold on to That Old Car? Joint Insights From Machine Learning and Multinomial Logit on Vehicle-Level Transaction Decisions

What makes you hold on to that old car? While the vast majority of household vehicles are still powered by conventional internal combustion engines, the progress of adopting emerging vehicle technologies will critically depend on how soon the existing vehicles are transacted out of the household fleet. Leveraging a nationally representative longitudinal data set, the Panel Study of Income Dynamics, this study examines how household decisions to dispose of or replace a given vehicle are: 1) influenced by the vehicle’s attributes, 2) mediated by households’ concurrent socio-demographic and economic attributes, and 3) triggered by key life cycle events. Coupled with a newly developed machine learning interpretation tool, TreeExplainer, we demonstrate an innovative use of machine learning models to augment traditional logit modeling to both generate behavioral insights and improve model performance. We find the two gradient-boosting-based methods, CatBoost and LightGBM, are the best performing machine learning models for this problem. The multinomial logistic model can achieve similar performance levels after its model specification is informed by TreeExplainer. Both machine learning and multinomial logit models suggest that while older vehicles are more likely to be disposed of or replaced than newer ones, such probability decreases as the vehicles serve the family longer. Pickup trucks and sport utility vehicles are less likely to be disposed of or replaced than cars, and leased vehicles are more likely to be transacted than owned vehicles. We find that married families, families with higher education levels, homeowners, and older families tend to keep their vehicles longer. Life events such as childbirth, residential relocation, and change of household composition and income are found to increase vehicle disposal and/or replacement. We provide additional insights on the timing of vehicle replacement or disposal, in particular, the presence of children and childbirth events are more strongly associated with vehicle replacement among younger parents.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Breakup dynamics in a pressure-swirl injector for urea-water solution applications: A computational study

The co-optimization of in-cylinder combustion and after-treatment technology has become a major aspect in engine design and development, with the goal of meeting the increasingly restrictive emission regulations in the transportation industry. Selective Catalytic Reduction is a robust technology to control the emission of NO x , and the injection of urea in water solution is the exhaust tailpipe is a key aspect of its operation. The proposed work uses high-fidelity Computational Fluid Dynamics to characterize the atomization dynamics of the liquid jet in relevant cross-flow conditions. The study focuses on a commercial low-pressure (9 bar) pressure-swirl injector which is characterized in its internal geometry through high-resolution X-ray micro-computational tomography. The internal two-phase flow has been modeled according to the volume-of-fluid approach in a large eddy simulation framework and validated against near-nozzle X-ray radiography measurement. Moreover, characterizing the breakup dynamics for the swirling hollow cone formation, and assessing the influence of the cross-flow in the breakup dynamics was completed. The results have been reported proposing Re-Oh maps and probability density functions of the spray kinematics. Higher cross-flow momentum generates an increase in the jet intact length and a reduction of the liquid droplet diameters. The axial momentum of the jet is affected by the cross-flow already in the near-nozzle region, determining a relevant deviation of the spray velocities. In conclusion, this work aims to inform the initialization of Eulerian-Lagrangian spray models through the assignment of droplet kinematics and static one-way coupling between volume-of-fluid results and Lagrangian spray parcels, to be used for system-size domain simulations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Pressure effects on reactivity and extinction of n -dodecane diffusion cool flame

Low-temperature combustion at high pressure has gained increasing interest owing to the growing demand for clean and efficient propulsion and energy systems. In particular, cool flame structure, extinction limits, and fuel reactivities at high pressure are critical in affecting the engine performance at near-limit conditions. Here, this paper investigates the effects of pressure on the cool flame extinction limit, structure, radical index, reactivity, and oxygen concentration dependence by experiments, analysis, and modeling. A large n-alkane, namely n-dodecane (n C 12 H 26 ), is selected to study its diffusion cool flame dynamics and reactivity in a high-pressure counterflow burner up to 10 atm. The experimental results show that higher pressure increases the cool flame extinction strain rates, and that the pressure-weighted extinction strain rate (aP) is proportional to the square of pressure, P 2 . A scaling analysis explains the relationship between the dependence of flame structure, heat release rate, and pressure-weighted cool flame strain rate on pressure. Furthermore, radical indexes at different pressures are measured by isolating the thermal and transport effects from the chemical contribution to diffusion cool flame extinction. The radical index clearly shows that the low-temperature reactivity increases with pressure. In addition, due to the critical role of multiple oxygen addition reactions in low-temperature chemistry, the relationship between the cool flame extinction limit and the oxygen concentration is explored. It is found that the cool flame extinction limits are proportional to the n th power of the oxygen concentration, [O 2 ] n , and increasing pressure leads to stronger extinction limit dependence (larger n) on the oxygen concentration. The present experiment and detailed kinetic analysis show clearly that increasing pressure promotes the low-temperature chemistry including the oxygen addition reactions, while the scaling analysis explains well the experimental results.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Use of Convolutional Neural Network Image Classification and High-Speed Ion Probe Data Toward Real-Time Detonation Characterization in a Water-Cooled Rotating Detonation Engine

As rotating detonation engines (RDEs) progress in maturity, the importance of monitoring advancements toward development of active control becomes more critical. Experimental RDE data processing at time scales which satisfy real-time diagnostics will likely require the use of machine learning. This study aims to develop and deploy a novel real-time monitoring technique capable of determining detonation wave number, direction, frequency, and individual wave speeds throughout experimental RDE operational windows. To do so, the diagnostic integrates image classification by a convolutional neural network (CNN) and ionization current signal analysis. Wave mode identification through single-image CNN classification bypasses the need to evaluate sequential images and offers instantaneous identification of the wave mode present in the RDE annulus. Here, real-time processing speeds are achieved due to low data volumes required by the methodology, namely one short-exposure image and a short window of sensor data to generate each diagnostic output. The diagnostic acquires live data using a modified experimental setup alongside Pylon and PyDAQmx libraries within a python data acquisition environment. Lab-deployed diagnostic results are presented across varying wave modes, operating conditions, and data quality, currently executed at 3–4 Hz with a variety of iteration speed optimization options to be considered as future work. These speeds exceed that of conventional techniques and offer a proven structure for real-time RDE monitoring. The demonstrated ability to analyze detonation wave presence and behavior during RDE operation will certainly play a vital role in the development of RDE active control, necessary for RDE technology maturation toward industrial integration.

42 ENGINEERING↗
DOE OSTI2023

Development and Bench-Scale Testing of a Novel Biphasic Solvent-Enabled Absorption Process for Post-Combustion Carbon Capture (Final Technical Report)

A new class of biphasic solvents was developed, and the concept of the enabled carbon dioxide (CO 2 ) absorption process was tested for post-combustion carbon capture in our previous lab-scale research. The primary goals of this project were to advance the development of the novel biphasic CO 2 absorption process (BiCAP) and validate its technical advantages by testing the integrated technology at a 40 kWe bench-scale with actual coal-derived flue gas in a power plant environment. The project was led by the University of Illinois at Urban-Champaign (UIUC), and Trimeric Corporation served as a sub-awardee providing support in basic design and techno-economic studies. To achieve the project goals and objectives, solvent management studies, process modeling and optimization, bench-scale equipment design, construction and testing, and technical, economic and environmental assessments have been conducted. The two top-performing biphasic solvents developed in our previous research were used in this project. Biphasic solvent emissions and control were investigated in the laboratory. The emissions of the biphasic solvents from the absorber were comparable to or lower than the reference 30 wt% monoethanolamine (MEA) solution, while they could be more effectively removed in the water wash column. Lab-scale testing of solvent degradation reclamation has revealed that vacuum distillation was feasible for biphasic solvent reclamation. Aspen Plus models were used to optimize the BiCAP, and a CO 2 stripping configuration introducing a secondary cold solvent feed to the stripper was identified to be the most energy efficient. A 40 kWe bench-scale, integrated BiCAP system was successfully designed, fabricated, and installed at the UIUC’s Abbott Power Plant. Parametric testing with synthetic flue gas has demonstrated that the two biphasic solvents required a more than 40% lower heat duty for CO 2 desorption as compared to the reference MEA tested on the same bench-scale skid. Slipstream testing with actual coal flue gas for a total of 31 days in two test campaigns has further demonstrated stable operation of the bench-scale skid. During the first campaign targeting 90% CO 2 removal, the heat duty averaged at 2,183 MJ/tonne of CO 2 captured and during the second campaign targeting 95% removal, the heat duty averaged at 2,450 MJ/tonne of CO 2 captured. A techno-economic analysis has revealed that for integration of the BiCAP into a 650-MWe pulverized coal-fired power plant, the parasitic power loss was reduced by ~20%, and the cost of CO 2 capture was reduced by ~21% ($36.3/tonne on a December 2018 dollar basis) compared to the U.S. Department of Energy (DOE)’s baseline Case B12B. As progression from this bench-scale development effort, a new project “Engineering-Scale Testing of the Biphasic Solvent Based CO 2 Absorption Capture Technology at a Covanta Waste-to-Energy Facility” was awarded by the DOE, launched in February 2023, to allow the team to further test the technology and demonstrate its technical and economic advantages at a pilot scale.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Integrated Methane Monitoring Platform Extension, Volume I: Final Technical Report

The IMMPE project, DE-FE0032284, was to enhance methane monitoring technologies and their applications across various natural gas asset classes. The scope included deploying advanced methane detection and monitoring technologies to identify and mitigate fugitive methane emissions, measuring emission rates, and assessing impacts. The findings included the successful mitigation of identified emissions and quantification of emission rates. A key outcome was the development of a comprehensive template and summary of recommendations for methane emissions monitoring, which is replicable for both upstream and downstream applications. Furthermore, the project emphasized the importance of education by providing training opportunities for technicians and regulators, thereby fostering awareness and promoting the adoption of cost-effective methane emissions monitoring and management techniques.

02 PETROLEUM↗
DOE OSTI2022

Unraveling the role of EGR olefins at advanced combustion conditions in the presence of nitric oxide: Ethylene, propene and isobutene

We report the role of EGR (exhaust gas recirculation) olefinic constituents at advanced combustion conditions in the presence of nitric oxide is unraveled in this study through experimental and modeling efforts using a twin-piston rapid compression machine operating at a stochiometric fuel loading with 20% EGR by mass, pressures of 20 and 40 bar, and temperatures from 680 to 950 K. Five different levels of olefin addition, focusing on ethylene, propene and isobutene, with a fixed amount of NO at 70 ppm are doped into test mixtures of PACE-20, a multi-component gasoline surrogate, where olefin addition effects are characterized through changes in ignition times and heat release rates. Experiments indicate that all three EGR olefins inhibit autoignition reactivity and low-temperature heat release at Tc < 850 K, with isobutene exhibiting the greatest impact, while at Tc > 850 K, low ethylene and propene additions promote reactivity. A recently updated chemical kinetic model, with detailed gasoline/NO x interacting and olefin/NO x interacting chemistry incorporated, is adopted to simulate the experiments. Simulation results are somewhat inconsistent with the experiments, where the model captures the inhibiting effects of all olefins on first-stage ignition reactivity, while consistently predicting a promoting effect on main ignition reactivity. Sensitivity and rate of production analyses reveal that adding olefins greatly alters the role of the consuming pathways for the olefins and their primary derivatives at the initial stage of the oxidation process, particularly with the presence of NO, where the olefins and their derivatives interact with both NO x species such as NO 2 and other species such as OH and HO 2 . The olefin/NO x interactions are particularly pronounced with propene and isobutene addition, where these lead to increased ignition reactivity by facilitating NO production and are mostly responsible for the disagreement between the model and experiments. Further investigations of olefin interacting chemistry, particularly those with NOx species, are needed for chemistry models to accurately predict the complicated effects of EGR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Connected and Learning Based Optimal Freight Management for Efficiency

The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.

33 ADVANCED PROPULSION SYSTEMS↗