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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Volcanology, Geochemistry, and Petrology Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is composed of a commentary about the state of Integrated, Coordinated, Open, and Networked (ICON) principles in Volcanology, Geochemistry, and Petrology (VGP), and discussion on the opportunities and challenges of adopting them. VGP encompasses a broad field that addresses volcanic, magmatic, hydrothermal, geomicrobial systems; process investigations that span the physical, geochemical and biological realms, including planetary geology; and one that is extensively supported by state-of-the-art research facilities. We suggest that an open, inclusive, collaborative and evolving model of an international coordinated network is critical to answering the most pressing challenges in VGP. In this commentary piece, we begin to discuss the elements of, challenges to, and path forward in developing such a model. For this team, ICON means collaboration, equitable access to data for the entire scientific community, and forging of partnerships that potentially contribute to more innovative ways of coordinating and sharing research. It also means bringing more equity to science, by implementing effective measures which consider access to funding, analytical equipment, resources, and mentors. More importantly, ICON to us means having important conversations around what we value in the advancement of science, perhaps exploring outside the idea of meritocracy and evaluating what individual traits can contribute to science outside what has traditionally been considered the norm.

58 GEOSCIENCES↗
DOE OSTI2022

Predicting the formation of fractionally doped perovskite oxides by a function-confined machine learning method

Abstract Fractionally doped perovskites oxides (FDPOs) have demonstrated ubiquitous applications such as energy conversion, storage and harvesting, catalysis, sensor, superconductor, ferroelectric, piezoelectric, magnetic, and luminescence. Hence, an accurate, cost-effective, and easy-to-use methodology to discover new compositions is much needed. Here, we developed a function-confined machine learning methodology to discover new FDPOs with high prediction accuracy from limited experimental data. By focusing on a specific application, namely solar thermochemical hydrogen production, we collected 632 training data and defined 21 desirable features. Our gradient boosting classifier model achieved a high prediction accuracy of 95.4% and a high F1 score of 0.921. Furthermore, when verified on additional 36 experimental data from existing literature, the model showed a prediction accuracy of 94.4%. With the help of this machine learning approach, we identified and synthesized 11 new FDPO compositions, 7 of which are relevant for solar thermochemical hydrogen production. We believe this confined machine learning methodology can be used to discover, from limited data, FDPOs with other specific application purposes.

08 HYDROGEN↗
DOE OSTI2020

Foreword Special issue on the Kilopower Project, Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Test

This special issue of Nuclear Technology contains full-length, peer-reviewed papers describing the design work leading up to and the results of the Kilowatt Reactor Using Stirling TechnologY (KRUSTY) test. KRUSTY was the centerpiece of the National Aeronautics and Space Administration (NASA) Kilopower Project to design, build, and test a space nuclear reactor. This test was the first such test since the end of the Space Nuclear Auxiliary Power (SNAP) project at the end of the 1960s. In this issue, the introduction paper presents the goals of the Kilopower Project and the potential missions this reactor concept could serve in NASA. Kilopower was intended to serve both human exploration needs on planetary surfaces as well as science needs for deep-space exploration. The design work for the experiment by Poston and the power conversion development by Gibson present the pre-work required to perform the eventual KRUSTY test. A paper on regulatory analysis follows, to show the path used to gain approval of the proposed experiment. Then, the early zero-power critical experiments are presented by Sanchez and Grove. These experiments were essential data used to enhance model predictions prior to the high-temperature test. Next, Poston presents the three experiments (warm criticals) that increase the temperature in an incremental fashion prior to the final experiment. These experiments were used to achieve final regulatory approval of the final high-temperature experiment. The last paper by Poston presents the results of the steady-state and transient testing of the reactor at full power and at the design temperature. These results show that the reactor design and as-built experiment met all of the requirements that NASA had developed for the system. Any experiment of this magnitude was accomplished only because of the hard work and dedication of a large number of people at multiple institutions, including the NASA Glenn Research Center, NASA Marshall Space Flight Center, Y-12 National Security Site, Los Alamos National Laboratory, and the Nevada National Security Site prime contractor (formerly National Security Technologies and now the Mission Support and Test Services). The project was jointly funded by the Space Technology Mission Directorate at NASA and the Criticality Safety Program at the National Nuclear Security Administration (NNSA). A special thanks to Jerry McKamy and Angela Chambers at the NNSA and Lee Mason and Don Palac at NASA for their support and guidance. For the authors and multitude of staff that performed this work, the passion for space nuclear reactors was the key to making this experiment a reality.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Probing New physics with high-redshift quasars: axions and non-standard cosmology

The Hubble diagram of quasars, as candidates to “standardizable” candles, has been used to measure the expansion history of the Universe at late times, up to very high redshifts ( z ~ 7). It has been shown that this history, as inferred from the quasar dataset, deviates at ≳ 3 σ level from the concordance (ΛCDM) cosmology model preferred by the cosmic microwave background (CMB) and other datasets. In this article, we investigate whether new physics beyond ΛCDM (BΛCDM) or beyond the Standard Model (BSM) could make the quasar data consistent with the concordance model. We first show that an effective redshift-dependent relation between the quasar UV and X-ray luminosities, complementing previous phenomenological work in the literature, can potentially remedy the discrepancy. Such a redshift dependence can be realized in a BSM model with axion-photon conversion in the intergalactic medium (IGM), although the preferred parameter space is in tension with various other astrophysical constraints on axions, at a level depending on the specific assumptions made regarding the IGM magnetic field. We briefly discuss a variation of the axion model that could evade these astrophysical constraints. On the other hand, we show that models beyond ΛCDM such as one with a varying dark energy equation of state ( w CDM) or the phenomenological cosmographic model with a polynomial expansion of the luminosity distance, cannot alleviate the tension. The code for our analysis, based on emcee [1] and corner.py [2], is publicly available at github.com/ChenSun-Phys/high_z_candles.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

JGI Plant Gene Atlas: an updateable transcriptome resource to improve functional gene descriptions across the plant kingdom

Abstract Gene functional descriptions offer a crucial line of evidence for candidate genes underlying trait variation. Conversely, plant responses to environmental cues represent important resources to decipher gene function and subsequently provide molecular targets for plant improvement through gene editing. However, biological roles of large proportions of genes across the plant phylogeny are poorly annotated. Here we describe the Joint Genome Institute (JGI) Plant Gene Atlas, an updateable data resource consisting of transcript abundance assays spanning 18 diverse species. To integrate across these diverse genotypes, we analyzed expression profiles, built gene clusters that exhibited tissue/condition specific expression, and tested for transcriptional response to environmental queues. We discovered extensive phylogenetically constrained and condition-specific expression profiles for genes without any previously documented functional annotation. Such conserved expression patterns and tightly co-expressed gene clusters let us assign expression derived additional biological information to 64 495 genes with otherwise unknown functions. The ever-expanding Gene Atlas resource is available at JGI Plant Gene Atlas (https://plantgeneatlas.jgi.doe.gov) and Phytozome (https://phytozome.jgi.doe.gov/), providing bulk access to data and user-specified queries of gene sets. Combined, these web interfaces let users access differentially expressed genes, track orthologs across the Gene Atlas plants, graphically represent co-expressed genes, and visualize gene ontology and pathway enrichments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Effect of High Temperature CO 2 on Haynes 230 Alloy (Updated Jan 2021)

The supercritical carbon dioxide (sCO 2 ) Brayton cycle is a promising candidate for future nuclear reactors due to its ability to improve power cycle energy conversion efficiency. The sCO 2 Brayton cycle can operate with an efficiency of 45-50% at operating temperatures of 550-700 C. One of the greatest hurdles currently faced by sCO 2 Brayton cycles is the corrosivity of sCO 2 and the lack of long-term alloy corrosion and mechanical performance data, as these will be key to enhancing the longevity of the system, and thus the levelized cost of electricity. Past studies have shown that sCO 2 corrosion occurs through the formation of metal carbonates, oxide layers, and carburization, and alloys with Cr, Mo and Ni generally exhibit less corrosion. While stainless steels may offer sufficient corrosion resistance at the lower range of temperatures seen by the sCO 2 Brayton cycles, more expensive nickel-based alloys are typically needed for the higher temperature regions. This study investigates the effects of corrosion on the Haynes 230 alloy, with a preliminary view on changes in the mechanical properties. High temperature CO 2 is used for this study as the corrosion products are similar to that of supercritical CO 2 , allowing for an estimation of the susceptibility towards corrosion without the need for high pressure experimentation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Component Reliability R&D

A review of the work done on the hydrogen Component Reliability R&D project in the last year. The National Renewable Energy Laboratory's (NREL) Hydrogen Safety Research and Development (HSR&D) program in collaboration with the University of Maryland's Systems Risk and Reliability Analysis Laboratory (SyRRA) are working to improve reliability and reduce risk in hydrogen systems through the use of use quantitative data on component leaks and failures, together with Prognosis and Health Management (PHM), and Quantitative Risk Assessment (QRA).

component↗
DOE OSTI2026

Investigation of irradiation damage and heat deposition: a comparative analysis for HEU-to-LEU conversion in HFIR

The planned conversion of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory from highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel requires detailed evaluation of experiment-relevant parameters to ensure continued performance for materials testing and isotope production. Here, this study presents the first comprehensive assessment of displacements per atom (dpa) and heat deposition rates in target materials within the HFIR flux trap with both HEU and candidate LEU core configurations. Seven analyses were conducted to evaluate key performance metrics, including fast neutron flux distribution, cross section response functions, cross section data, and local dpa and heat deposition rates using mesh- and cell-based tallies. Simulations employed Shift, Monte Carlo N-Particle (MCNP), and the HIFR Controller (HFIRCON) tool suite for high-fidelity transport and depletion modeling. The LEU designs—using U 3 Si 2 -Al dispersion fuel and operating at 95 MW—were compared to the current 85 MW HEU configuration. Results show that while the candidate LEU cores exhibit higher dpa rates due to a harder spectrum and extended cycle lengths, they also demonstrate reduced heat deposition rates in irradiation experiments, primarily due to increased gamma self-shielding from higher 238 U content in the core. These findings confirm that LEU conversion can maintain HFIR’s materials irradiation capabilities but may require redesigning existing experimental hardware.

HEU↗
DOE OSTI2023

A Plan to Qualify New Fuel for the High Flux Isotope Reactor for Material Minimization

The High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) is one of five high power research reactors the Office of Material Management and Minimization (M3) Program, Office of Conversion is working to convert from using highly enriched uranium (HEU) fuel to using low-enriched uranium (LEU) fuel. This effort stems from the primary objective within the U.S. Department of Energy (DOE) National Nuclear Security Administration (NNSA) to achieve permanent threat reduction by minimizing, and when possible, eliminating weapon-usable nuclear material around the world. Under M3’s Office of Conversion, the U.S. High Performance Research Reactor (USHPRR) Project is pursuing fuel qualification and licensing of LEU fuels to support the high-performance reactors. All high-performance reactors except HFIR will be converted to LEU monolithic uranium-molybdenum alloy fuel. HFIR will be evaluated for conversion to LEU using a uranium silicide fuel, namely, U3Si2-Al dispersion fuel. The mission of the USHPRR Project is to develop the technology needed to reduce, and eventually eliminate, worldwide use of HEU in civilian applications. The goal is to develop the technical means needed to use low enriched uranium (LEU) instead of HEU fuel in research and test reactors without significant penalties in performance, economics, or safety of the reactors. The USHPRR Project has four major elements, called Pillars: Fuel Qualification (FQ) managed at Idaho National Laboratory (INL), Fuel Fabrication (FF) managed at Pacific Northwest National Laboratory (PNNL), Reactor Conversion (RC) managed at Argonne National Laboratory (Argonne), and Cross-Cutting (CC) managed at Savannah River National Laboratory (SRNL). FQ is responsible for the qualification of the fuel type. RC is responsible for supporting reactor conversion analysis and overseeing licensing submittals leading to conversions of domestic reactors to LEU fuel. For the FQ effort, FQ (INL) worked in collaboration with RC (Argonne) and ORNL to develop the plan for the uranium silicide fuel qualification for HFIR. The resulting HFIR Fuel Qualification Plan provides the general approach for the USHPRR team to move the selected uranium silicide fuel design for HFIR conversion through qualification. Authorization and use in HFIR will be approved through the DOE’s Office of Science. Uranium silicide fuel was previously qualified in NUREG-1313 at an approximate maximum heat flux of 1.4 MW/m2 and a maximum fuel section temperature of about 130°C. In addition to the different regulator process utilized by DOE, these upper limits will be exceeded in HFIR; therefore, further testing will be necessary to ensure the fuel can meet HFIR qualification requirements. The HFIR fuel loading may exceed 4.8 gU/cm3 which was determined in the NUREG-1313 safety evaluation to be acceptable for use in non-power NRC-licensed reactors provided there exist no other safety considerations. In addition, the uranium silicide fuel will need to be qualified in a HFIR-specific design. This plan includes the currently available information from the USHPRR Project Functions and Requirements document and expands these requirements to ensure that planned tests have traceable results providing evidence that the requirements have been met. Data collection methods are discussed as well as the process to show that the requirements have been met. This document is designed to provide a pathway for researchers to obtain data necessary and at the appropriate quality level for HFIR fuel qualification

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Charge separation in the photosystem II reaction center resolved by multispectral two-dimensional electronic spectroscopy

The photosystem II reaction center (PSII RC) performs the primary energy conversion steps of oxygenic photosynthesis. While the PSII RC has been studied extensively, the similar time scales of energy transfer and charge separation and the severely overlapping pigment transitions in the Qy region have led to multiple models of its charge separation mechanism and excitonic structure. Here, we combine two-dimensional electronic spectroscopy (2DES) with a continuum probe and two-dimensional electronic vibrational spectroscopy (2DEV) to study the cyt b559-D1D2 PSII RC at 77 K. This multispectral combination correlates the overlapping Qy excitons with distinct anion and pigment-specific Q x and mid-infrared transitions to resolve the charge separation mechanism and excitonic structure. Through extensive simultaneous analysis of the multispectral 2D data, we find that charge separation proceeds on multiple time scales from a delocalized excited state via a single pathway in which Pheo D1 is the primary electron acceptor, while Chl D1 and P D1 act in concert as the primary electron donor.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Updated neutrino mass constraints from galaxy clustering and CMB lensing-galaxy cross-correlation measurements

In this work, we revisit cosmological constraints on the sum of the neutrino masses Σm v from a combination of full-shape BOSS galaxy clustering [P(k)] data and measurements of the cross-correlation between Planck Cosmic Microwave Background (CMB) lensing convergence and BOSS galaxy overdensity maps [$C_{l}^{kg}$], using a simple but theoretically motivated model for the scale-dependent galaxy bias in auto- and cross-correlation measurements. We improve upon earlier related work in several respects, particularly through a more accurate treatment of the correlation and covariance between P(k) and $C_{l}^{kg}$ measurements. When combining these measurements with Planck CMB data, we find a 95% confidence level upper limit of Σm v sum of neutrino masses < 0.14 eV, while slightly weaker limits are obtained when including small-scale ACTPol CMB data, in agreement with our expectations. We confirm earlier findings that (once combined with CMB data) the full-shape information content is comparable to the geometrical information content in the reconstructed BAO peaks given the precision of current galaxy clustering data, discuss the physical significance of our inferred bias and shot noise parameters, and perform a number of robustness tests on our underlying model. While the inclusion of $C_{l}^{kg}$ measurements does not currently appear to lead to substantial improvements in the resulting Σm v of neutrino mass constraints, we expect the converse to be true for near-future galaxy clustering measurements, whose shape information content will eventually supersede the geometrical one.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Simulation of methanol synthesis in a membrane-contactor reactor

In a recent paper we investigated experimentally in the laboratory the methanol synthesis (MeS) reaction in a novel high-pressure membrane reactor (MR) using tetraethylene glycol dimethyl ether (TGDE) and an ionic liquid (IL) as the sweep liquids. We reported significantly higher carbon conversion (per single-pass) compared to a traditional packed-bed reactor (PBR), as a result of the in-situ removal of methanol by the sweep liquid. Here, in this paper, a steady-state model is developed to simulate the MR behavior during MeS and is validated by the experimental data. The model is then used to study the reactor behavior for a broader range of operating conditions beyond those that can be accessed and studied experimentally in the laboratory-scale reactor. Converting the model equations into their dimensionless form helps to identify the key dimensionless groups determining reactor performance, enables one to better evaluate the efficacy of the MR system, and guides further process design and scale-up.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Controlling Polymer Morphology in Blade-Coated All-Polymer Solar Cells

In this report translating all-polymer solar cells from spin-coating to scalable roll-to-roll-compatible fabrication techniques is a critical step toward the application of organic photovoltaics at a scale. Techniques to control polymer crystallization and phase separation during solution printing are essential to obtain high-performance printed organic solar cells. Here, we demonstrate a novel solvent additive approach employing trace amounts of phthalates as additives to control polymer crystallinity and suppress unfavorable phase separation in a representative PTB7-Th/P(NDI2OD-2T) all-polymer solar cell. The best-performing additive increased the blade-coated device performance from 2.09 to 4.50% power conversion efficiency, an over twofold improvement, mitigating the loss in performance that is typically observed during process transfer from spin-coating to blade-coating. It is suggested that the improved device performance stems from a finer polymer phase-separation size and overall improved active layer morphology, evidenced by device characterization data and indirectly supported by grazing incidence wide-angle X-ray scattering analyses. Real-time X-ray diffraction measurements during blade-coating provide mechanistic insights and suggest that the dioctyl phthalate additive may act as a compatibilizer, reducing the demixing of the donor and acceptor polymer during film formation, enabling a smaller phase separation and improved performance. The structural diversity of the class of phthalate additives makes this simple yet effective concept promising for translating other all-polymer material systems to blade-coating and other scalable printing techniques.

14 SOLAR ENERGY↗
DOE OSTI2025

Tuning Copolymer Microstructure Using Ring-Opening Cross-Metathesis Polymerization

The capability of ring-opening cross-metathesis (RO/CM) polymerization to produce alternating copolymers was studied. By treating commercial polybutadiene (PB) with bulky oxanorbornene monomers and Ru-based olefin metathesis catalysts, alternating copolymers were produced under mild conditions with high sequence fidelities. Here, we found that alternating copolymers could be produced starting from a variety of butadiene sources including PB, cyclooctadiene (COD), or t,t,t-1,5,9-cyclododecatriene (CDT), highlighting for the first time the kinetic pathway independence of this process. Kinetic copolymerization analysis of an oxanorbonene monomer with CDT revealed that much higher monomer conversions were obtained compared with the analogous homopolymerizations and showed evidence of alternating monomer incorporation. Copolymerization of these monomers also enabled good control when targeting different molecular weights. Copolymer thermal analysis revealed a strong correlation between thermal behavior and alternating sequence fidelity, providing a second lever beyond composition to tune thermal behavior. These data demonstrate that a broad variety of polymer microstructures can be accessed via RO/CM polymerization and highlight the potential of CDT in alternating copolymer synthesis.

Foster, Jeffrey C. [Oak Ridge National Laboratory ↗
DOE OSTI2022

Te/CdTe and Al/CdTe Interfacial Energy Band Alignment by Atomistic Modeling

A synergistic approach that incorporates first-principles atomistic modeling with numerical device simulations is used to systematically evaluate the role of heterointerfaces within metal-chalcogenide-based photovoltaic technologies. Two interfaces involving either a tellurium back contact or aluminum back electrode combined with a cadmium telluride absorber layer within cadmium-telluride-based thin-film solar cells are investigated on an atomic scale to determine the mechanisms contributing to variations in device performance. Electronic structures and predicted charge transport behavior with respect to cadmium and tellurium termination of the absorber layer are studied along the polar oriented CdTe{111} facets. The computational methodology reveals a noticeable contrast between the Schottky barrier forming Al/CdTe interface versus the Type I Te/CdTe heterojunction. Greater band bending features are exhibited by the cadmium termination as opposed to the tellurium termination for each interface case. Subsequent device modeling suggests that 3.6% higher photovoltaic conversion efficiency is achievable for the cadmium termination relative to the tellurium termination of the Te/CdTe interface. Based strictly on an idealistic representation, both interface models show the importance of atomic-scale interfacial properties for cadmium telluride solar cell device performance with their bulk properties being validated in comparison to published experimental data. Here, the synergistic approach offers a suitable method to analyze solar cell interfaces through a predictive computational framework for the engineering and optimization of metal-chalcogenide-based thin-film photovoltaic technologies.

Green’s function↗
DOE OSTI2024

Evaluation of Converter Performance Considering Static and Dynamic Device Part-to-Part Variability

This paper presents a methodology to incorporate and analyze the impact of semiconductor device part-to-part variation on power converter performance. By integrating extensive static and dynamic device characterization data with an automated compact model generation process that reflects manufacturing variability, device models with inherent variability features are utilized in converter simulations for a comprehensive assessment of performance impacts. The traditional converter performance evaluation process typically yields fixed efficiency values, often dismissing the inherent part-to-part variability caused by the manufacturing process of semiconductor devices. To address this limitation, a large population of devices was characterized to capture variations in static parameters-such as transfer, output, and capacitance characteristics-as well as dynamic behaviors, including switching losses. This data-driven approach enables the development of individual compact models, which were then integrated into converter simulations to evaluate efficiency ranges rather than single point estimated values. The converter simulation results show that part-to-part component variation can lead to significant efficiency deviations, exceeding several percentage points in high-power conversion applications. By offering a more accurate representation of converter behavior under real-world manufacturing conditions, this methodology enables designers to anticipate performance variability, improving the robustness of power converter designs.

device characterization↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part I: Dynamical Downscaling

Abstract New simulations at 12-km grid spacing with the Weather and Research Forecasting (WRF) Model nested in the MPI Earth System Model (ESM) are used to quantify possible changes in wind power generation potential as a result of global warming. Annual capacity factors (CF; measures of electrical power production) computed by applying a power curve to hourly wind speeds at wind turbine hub height from this simulation are also used to illustrate the pitfalls in seeking to infer changes in wind power generation directly from low-spatial-resolution and time-averaged ESM output. WRF-derived CF are evaluated using observed daily CF from operating wind farms. The spatial correlation coefficient between modeled and observed mean CF is 0.65, and the root-mean-square error is 5.4 percentage points. Output from the MPI-WRF Model chain also captures some of the seasonal variability and the probability distribution of daily CF at operating wind farms. Projections of mean annual CF (CF A ) indicate no change to 2050 in the southern Great Plains and Northeast. Interannual variability of CF A increases in the Midwest, and CF A declines by up to 2 percentage points in the northern Great Plains. The probability of wind droughts (extended periods with anomalously low production) and wind bonus periods (high production) remains unchanged over most of the eastern United States. The probability of wind bonus periods exhibits some evidence of higher values over the Midwest in the 2040s, whereas the converse is true over the northern Great Plains. Significance Statement Wind energy is playing an increasingly important role in low-carbon-emission electricity generation. It is a “weather dependent” renewable energy source, and thus changes in the global atmosphere may cause changes in regional wind power production (PP) potential. We use PP data from operating wind farms to demonstrate that regional simulations exhibit skill in capturing actual power production. Projections to the middle of this century indicate that over most of North America east of the Rocky Mountains annual expected PP is largely unchanged, as is the probability of extended periods of anomalously high or low production. Any small declines in annual PP are of much smaller magnitude than changes due to technological innovation over the last two decades.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Reinforcement learning applied to dilute combustion control for increased fuel efficiency

To reduce the modeling burden for control of spark-ignition engines, reinforcement learning (RL) has been applied to solve the dilute combustion limit problem. Q-learning was used to identify an optimal control policy to adjust the fuel injection quantity in each combustion cycle. A physics-based model was used to determine the relevant states of the system used for training the control policy in a data-efficient manner. The cost function was chosen such that high cycle-to-cycle variability (CCV) at the dilute limit was minimized while maintaining stoichiometric combustion as much as possible. Experimental results demonstrated a reduction of CCV after the training period with slightly lean combustion, contributing to a net increase in fuel conversion efficiency of 1.33%. To ensure stoichiometric combustion for three-way catalyst compatibility, a second feedback loop based on an exhaust oxygen sensor was incorporated into the fuel quantity controller using a slow proportional-integral (PI) controller. The closed-loop experiments showed that both feedback loops can cooperate effectively, maintaining stoichiometric combustion while reducing combustion CCV and increasing fuel conversion efficiency by 1.09%. Finally, a modified cost function was proposed to ensure stoichiometric combustion with a single controller. In addition, the learning period was shortened by half to evaluate the RL algorithm performance on limited training time. Experimental results showed that the modified cost function could achieve the desired CCV targets, however, the learning time was reduced by half and the fuel conversion efficiency increased only by 0.30%.

33 ADVANCED PROPULSION SYSTEMS↗