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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dilute Combustion Control Using Spiking Neural Networks

Dilute combustion with exhaust gas recirculation (EGR) in spark-ignition engines presents a cost-effective method for achieving higher levels of engine efficiency. At high levels of EGR, however, cycle-to-cycle variability (CCV) of the combustion process is exacerbated by sporadic occurrences of misfires and partial burns. Previous studies have shown that temporal deterministic patterns emerge at such conditions and certain combustion cycles have a significant influence over future events. Due to the complexity of the combustion process and the nature of CCV, harnessing all the deterministic information for control purposes has remained challenging even with physics based 0-D, 1-D, and high-fidelity computational fluid dynamics (CFD) models. In this study, we present a data-driven approach to optimize the combustion process by controlling CCV adjusting the cycle-to-cycle fuel injection quantity. Readily available data from in-cylinder pressure was used to train a spiking neural network (SNN) which learns the optimal way to manage fuel injection in order to reduce CCV while maintaining acceptable levels of fuel consumption. SNNs are particularly well suited for powertrain control applications due to their ability to be deployed on FPGA-based neuromorphic hardware which are small, inexpensive, and have a low power demand. The high-performance computing (HPC) resources of Oak Ridge National Laboratory were used to run an evolutionary-based training approach for choosing the best SNN configuration that minimizes the size of the network while achieving the desired goal. The neuromorphic hardware with the optimized SNN deployed was connected to the rapid prototyping engine control system for real-time control implementation and tested on a single cylinder version of a GM LNF 4-cylinder engine. The results show a significant reduction of CCV with a small percentage of additional fuel used to stabilize the charge.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1987

STS propellant scavenging systems study. Part 2, volume 2: Cost and WBS/dictionary

Presented are the results of the cost analysis performed to update and refine the program phase C/D cost estimates for a Shuttle Derived Vehicle (SDV) tanker. The SDV tanker concept is an unmanned cargo vehicle incorporating a set of propellant tanks in the vehicle's payload module. The tanker will be used to meet the demand for a cryogenic propellant supply in orbit. The propellant tanks are delivered to a low Earth orbit or to an orbit in the vicinity of the Space Station. The intent of the economic analysis is to provide NASA with economic justification for the propellant scavenging concept that minimizes the total Space Transportation System life cycle cost. The detailed costs supporting the concept selection process are presented with descriptive text to aid in forecasting the phase C/D project and program planning. Included are all propellant scavenging costs as well as all SDV, STS and Orbital Maneuvering Vehicle charges to deliver the propellants to the Space Station.

Williams, Frank L.↗
DOE OSTI2022

NIF-TAS Miniature Calibration Station

“On Aug. 8, 2021, an experiment at Lawrence Livermore National Laboratory’s (LLNL’s) National Ignition Facility (NIF) made a significant step toward ignition, achieving a yield of more than 1.3 megajoules (MJ). This advancement puts researchers at the threshold of fusion ignition, an important goal of the NIF, and opens access to a new experimental regime.” NIF experiments are conducted by symmetrically focusing 192 laser beams from NIF (three football fields in length) into the Target Chamber (10-meter diameter sphere) onto a target 2mm in size. The reaction produces a hot spot the diameter of a human hair, generating more than 10 quadrillion watts of fusion power for 100 trillionths of a second. These high pressures and temperatures created by the NIF have only been seen on the surface of the sun. To achieve fusion ignition, the target must be compressed to high pressures and temperatures, which requires symmetric compression. This symmetry requires precise alignment of the laser beams to the target. To achieve this precise symmetry a Target Alignment System (TAS) was developed to aid in aligning the beams to the target. The accomplishment on Aug 8 th could not have been accomplished without the TAS. TAS has proven to be a critical contributor to the success of NIF experiments. Each TAS is composed of several Charge Couple Device (CCD) sensors and various support electronics. Unfortunately, these CCDs are no longer available in industry as they have become outdated and obsolete. There is a limited amount of spare CCDs in the facility. As the NIF continues to increase its energy output of its fusion ignition shot experiments (heigh yield shots), more neutrons are being emitted from the Target Chamber. These neutrons are very damaging to the TAS electronics and its sensors, thus degrading and reducing its life expectancy dramatically. The increase of neutrons exceeds the damage threshold of the CCDs. This would increase the demand for more frequent TAS refurbishments and calibrations. The increase in resources to perform these refurbishments and calibrations would not be sustainable. In efforts to prolong the life of each TAS system it was determined that the TAS should be removed for every High Yield Shot and then reinstalled. The high precision fully calibrated TAS can easily be knocked out of alignment during these installs and reinstall exchanges and being transported in and out of the NIF. The Miniature Calibration Station System was developed to verify that the critical calibration parameters have been preserved during every TAS exchange. The Miniature Calibration Station System (Mini-Cal) would need to be a scaled down (in size and scope), portable version of the offline TAS calibration station to verify the critical TAS parameters are still within tolerances.

42 ENGINEERING↗
NASA NTRS2003

Auction Mechanism to Allocate Air Traffic Control Slots

This article deals with an auction mechanism for airspace slots, as a means of solving the European airspace congestion problem. A disequilibrium, between Air Traffic Control (ATC) services supply and ATC services demand are at the origin of almost one fourth of delays in the air transport industry in Europe. In order to tackle this congestion problem, we suggest modifying both pricing and allocation of ATC services, by setting up an auction mechanism. Objects of the auction will be the right for airlines to cross a part of the airspace, and then to benefit from ATC services over a period corresponding to the necessary time for the crossing. Allocation and payment rules have to be defined according to the objectives of this auction. The auctioneer is the public authority in charge of ATC services, whose aim is to obtain an efficient allocation. Therefore, the social value will be maximized. Another objective is to internalize congestion costs. To that end, we apply the principle of Clarke-Groves mechanism auction: each winner has to pay the externalities imposed on other bidders. The complex context of ATC leads to a specific design for this auction.

Raffarin, Marianne↗
DOE OSTI2025

An electro-optical Mott neuron based on niobium dioxide

Various applications—including brain-like computing and on-chip artificial vision—increasingly demand a combination of electronic and photonic techniques. However, integrating both approaches on a single chip is challenging, and solutions typically rely on disparate components with power-hungry signal conversions. Here, in this paper, we report electro-optical Mott neurons that combine visible light emission with electrical threshold switching, as well as neuron-like oscillations. The devices are based on thin films of sputtered niobium dioxide (NbO 2 ), a Mott insulator–metal transition material, operating at room temperature and emitting light that peaks around 810 nm. Operando measurements reveal an electronic origin to the light emission: charge carrier relaxation initiated by high-field transport in the NbO 2 . Our devices combine electrical and optical functions within a single material, thereby expanding the options available for future artificial intelligence hardware.

electrical engineering↗
DOE OSTI2025

Distinct Dynamics of Lithium Intercalation and Plating on Graphite Anode for Li‐Ion Batteries in eVTOL Applications

In the absence of viable high-energy-density battery alternatives, lithium-ion (Li-ion) batteries remain essential for enabling electric vertical take-off and landing (eVTOL) platforms in advanced air mobility. Unlike Li-ion batteries used in electric vehicles and portable electronics, eVTOL battery systems operate under distinct high-power demands, which necessitate an independent assessment of material degradation mechanisms. This study presents a case analysis of graphite anode evolution under high-power cycling conditions. The findings reveal lithium entrapment within graphite particles, potentially resulting from incomplete Li-ion de-intercalation during a high-rate discharge event that is characteristic of eVTOL take-off and landing. This phenomenon leads to a progressive reduction in graphite-specific capacity and, over time, promotes lithium metal plating on the anode. Notably, the Li-metal plating observed in this study differs from that associated with fast-charging conditions, as it is primarily governed by concentration polarization-induced overpotential in the latter case. In conclusion, these findings highlight the inherent challenges of utilizing graphite in high-power Li-ion battery applications and elucidate the unique degradation mechanisms that arise due to the sluggish reaction kinetics of Li-ion intercalation and de-intercalation within graphite.

Li plating↗
DOE OSTI2021

Numerical Analysis of Fuel Effects on Advanced Compression Ignition Using a Cooperative Fuel Research Engine Computational Fluid Dynamics Model

Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1971

Economic utilization of general aviation airport runways

The urban general aviation airport economics is studied in detail. The demand for airport services is discussed, and the different types of users are identified. The direct cost characteristics of the airport are summarized; costs to the airport owner are largely fixed, and, except at certain large airports, weight is not a significant factor in airport costs. The efficient use of an existing airport facility is explored, with the focus on the social cost of runway congestion as traffic density at the airport build up and queues form. The tradeoff between aircraft operating costs and airport costs is analyzed in terms of runway length. The transition from theory to practice is treated, and the policy of charging prices only on aircraft storage and fuel is felt likely to continue. Implications of the study from the standpoint of public policy include pricing that spreads traffic peaks to improve runway utilization, and pricing that discriminates against aircraft requiring long runways and causes owners to adopt V/STOL equipment.

Piper, R. R.↗
DOE OSTI2020

Optimal Efficiency and Operational Cost Savings: A Framework for Automated Rooftop PV Placement

Residential energy consumers are charged based on a utility rate structure, such as net metering or feed-in tariff. To lower consumers' electricity bills, expensive batteries are deployed to reduce the electricity fed from the grid during peak hours. However, strategic photovoltaic (PV) panel placement enables the reduction of operational energy cost while considering the spatial feasibility and efficiency for hosting rooftop PV. In this paper, we present a framework to automatically identify the optimal location of rooftop PV panels on residential buildings. Our framework integrates multiple workflows, including energy and environmental simulation, parametric modeling, and optimization to identify the ideal location of PV panels to balance the demand and supply at a building and community scale. These workflows are linked using the Grasshopper plug-in for Rhinoceros CAD software. The framework includes two different workflows, each satisfying a target for optimal PV placement: (a) maximizing PV panel efficiency, where users aim to maximize energy generation, and (b) minimizing operational energy cost, where "best'' panels are selected considering utility rates for operational energy cost. Our framework is demonstrated in a residential community in Fort Collins, Colorado, to generate the optimal PV placement for each of the two aforementioned targets. Results from the two workflows are compared to illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost. The developed workflows are introduced as tools within the Grasshopper plug-in to investigate the solar potential of rooftop PV panels while taking into account factors such as contextual shading, utility rate structures, and buildings' energy demand profiles.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Elucidating the Origins of High Capacity in Iron-Based Conversion Materials: Benefit of Complementary Advanced Characterization toward Mechanistic Understanding

Lithium-ion batteries are recognized as an important electrochemical energy storage technology due to their superior volumetric and gravimetric energy densities. Graphite is widely used as the negative electrode, and its adoption enabled much of the modern portable electronics technology landscape. However, developing markets, such as electric vehicles and grid-scale storage, have increased demands, including higher energy content and a diverse materials supply chain. Alternatives that provide the opportunity to increase capacity and address supply chain concerns are of interest. Understanding the fundamental mechanisms that govern battery function is crucial to driving further improvements in the field. Advanced characterization techniques, such as those enabled by synchrotron light sources and high-resolution electron microscopes, that can uncover these mechanisms have become a necessity for elucidating structural evolution upon electrochemical conversion at the nano- to mesoscales. Performing these experiments with relevant electrochemistry using in situ and operando experiments imparts the ability to identify critical reaction pathways and capture intermediate (dis)charge products not discernible by traditional experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identification of localized radiation damage in power MOSFETs using EBIC imaging

The rapidly increasing use of electronics in high-radiation environments and the continued evolution in transistor architectures and materials demand improved methods to characterize the potential damaging effects of radiation on device performance. Here, electron-beam-induced current is used to map hot-carrier transport in model metal-oxide semiconductor field-effect transistors irradiated with a 300 KeV focused He + beam as a localized line spanning across the gate and bulk Si. By correlating the damage to the electronic properties and combining these results with simulations, the contribution of spatially localized radiation damage on the device characteristics is obtained. Furthermore, this identified damage, caused by the He + beam, is attributed to localized interfacial P b centers and delocalized positive fixed-charges, as surmised from simulations. Comprehension of the long-term interaction and mobility of radiation-induced damage are key for future design of rad-hard devices.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Comparative analysis of plasmon modes in layered Lindhard metals and strange metals

The enigmatic strange metal remains one of the central unsolved problems of 21st century science. Understanding this phase of matter requires knowledge of the momentum- and energy-resolved dynamic charge susceptibility 𝜒⁡(𝑞,𝜔), especially at finite momentum. Inelastic electron scattering (EELS), performed in either transmission or reflection geometry, is a powerful probe of 𝜒⁡(𝑞,𝜔). For the prototypical strange metal Bi 2 ⁢Sr 2 ⁢CaCu 2 ⁢O 8+𝑥 , transmission- and reflection EELS, and infrared (IR) spectroscopy agree at 𝑞∼0, all revealing a highly damped plasmon near 1 eV. At larger 𝑞, however, EELS results show unresolved discrepancies. Since IR data are highly reproducible, it is advantageous to use IR data to calculate what the expected EELS response should be at modest 𝑞. Building on prior momentum-resolved reflection geometry M-EELS work [Chen et al., Phys. Rev. B 109, 045108 (2024)], we extend this approach to transmission EELS for finite stacks of metallic layers, comparing a “textbook” Lindhard metal to a strange metal. In the Lindhard case, the low-𝑞 response is dominated by long-lived, standing wave plasmon modes arising from interlayer Coulomb coupling, with in-plane dispersions that resemble the well-known Fetter modes of layered metals. This behavior depends only on the geometry and the long-range nature of the Coulomb interaction and is largely insensitive to layer details. At larger 𝑞, the response reflects the microscopic properties of individual layers. For the strange metal, calculations based on IR data predict a highly damped plasmon with weak dispersion and no distinct surface mode. While our results match IR and M-EELS at low 𝑞, they do not reproduce any published EELS spectra at large 𝑞, highlighting unresolved discrepancies that demand further experimental investigation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A dynamic 2D Borehole Thermal Energy Storage (BTES) model for enhanced computational efficiency

Progressing toward a future increasingly reliant on renewable energy sources, the development of effective, durable energy storage solutions becomes essential to balance supply and demand fluctuations. Borehole Thermal Energy Storage (BTES) is a long-duration thermal energy storage technology that captures excess heat generated from renewable energy sources and stores it underground for later use, enabling the efficient utilization of sustainable energy. This approach is particularly valuable in district energy networks when integrated with Ground Source Heat Pumps (GSHP) to provide stable heating and cooling. However, traditional three-dimensional (3D) numerical models of BTES systems demand extensive computational resources, limiting their practicality for real-time and large-scale applications. This study introduces a novel two-dimensional (2D) modeling approach that reduces computational costs while maintaining high accuracy. By employing a radial ring-based discretization method, the model simulates heat injection, retention, and retrieval dynamics over seasonal cycles. A new thermal-mass weighted-average temperature parameter is introduced to evaluate the performance of BTES systems. Model validation against FEFLOW simulations demonstrates a 17-fold improvement in computational speed compared to traditional Computational Fluid Dynamics (CFD) models while achieving a mean absolute percentage error (MAPE) of 2 % during charging and 4 % during discharging. Additionally, a trade-off analysis between computational efficiency and accuracy is conducted, ensuring the model's applicability for real-world scenarios. The findings of this research contribute to the development of computationally efficient BTES models, facilitating better optimization, control, and integration into renewable energy systems. This work provides a foundation for further studies in techno-economic analysis, multi-year performance evaluation, and real-time operational strategies for BTES applications, supporting a more sustainable energy future.

2D modeling↗
DOE OSTI2022

Promoting Reversibility of Multielectron Redox in Alkali-Rich Sulfide Cathodes through Cryomilling

We report conventional cathodes for Li-ion batteries (LIBs) are reaching their theoretical capacity limits. One way to meet the growing demands for high-capacity LIBs is by developing so-called Li-rich cathode materials that greatly benefit from additional capacities from anionic moieties in the structure. Li-rich materials are intrinsically subject to higher degrees of (de)intercalation, leaving the particles more prone to fractures and thus rapid capacity fade. Alkali-rich LiNaFeS 2 reversibly cycles with capacities exceeding 300 mAh g -1 , but its capacity fades faster than an isostructural material Li 2 FeS 2 . Using synchrotron-based transmission X-ray microscopy (TXM), we demonstrate that the capacity fade of LiNaFeS 2 stems from particle fractures in the first charge cycle. We improve the cycling performance of LiNaFeS 2 by means of cryomilling, which enhances capacity retention at cycle 50 by 76%. Through crystallographic and morphological characterization techniques, we confirm that cryomilling not only decreases particle and crystallite size while increasing microstrain but also prevents particles from fracturing. Cryomilling is a powerful tool to engineer nanoscale battery materials, and TXM allows the direct observation of morphological changes of the particles, which can be leveraged to develop next-generation cathode materials for LIBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗
DOE OSTI2024

From Bulk to Interface: Solvent Exchange Dynamics and Their Role in Ion Transport and the Interfacial Model of Rechargeable Magnesium Batteries

Multivalent battery chemistries have been explored in response to the increasing demand for high-energy rechargeable batteries utilizing sustainable resources. Solvation structures of working cations have been recognized as a key component in the design of electrolytes; however, most structure–property correlations of metal ions in organic electrolytes usually build upon favorable static solvation structures, often overlooking solvent exchange dynamics. We here report the ion solvation structures and solvent exchange rates of magnesium electrolytes in various solvents by using multimodal nuclear magnetic resonance (NMR) analysis and molecular dynamics/density functional theory (MD/DFT) calculations. These magnesium solvation structures and solvent exchange dynamics are correlated to the combined effects of several physicochemical properties of the solvents. Moreover, Mg 2+ transport and interfacial charge transfer efficiency are found to be closely correlated to the solvent exchange rate in the binary electrolytes where the solvent exchange is tunable by the fraction of diluent solvents. Our primary findings are (1) most battery-related solvents undergo ultraslow solvent exchange coordinating to Mg 2+ (with time scales ranging from 0.5 μs to 5 ms), (2) the cation transport mechanism is a mixture of vehicular and structural diffusion even at the ultraslow exchange limit (with faster solvent exchange leading to faster cation transport), and (3) an interfacial model wherein organic-rich regions facilitate desolvation and inorganic regions promote Mg 2+ transport is consistent with our NMR, electrochemistry, and cryogenic X-ray photoelectron spectroscopy (cryo-XPS) results. In conclusion, this observed ultraslow solvent exchange and its importance for ion transport and interfacial properties necessitate the judicious selection of solvents and informed design of electrolyte blends for multivalent electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2024

Plasma–liquid interactions in the presence of organic matter—A perspective

As investigations in the biomedical applications of plasma advance, a demand for describing safe and efficacious delivery of plasma is emerging. It is quite clear that not all plasmas are “equal” for all applications. This Perspective discusses limitations of the existing parameters used to define plasma in context of the need for the “right plasma” at the “right dose” for each “disease system.” The validity of results extrapolated from in vitro studies to preclinical and clinical applications is discussed. We make a case for studying the whole system as a single unit, in situ. Furthermore, we argue that while plasma-generated chemical species are the proposed key effectors in biological systems, the contribution of physical effectors (electric fields, surface charging, dielectric properties of target, changes in gap electric fields, etc.) must not be ignored.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Demonstration of Better than Diesel Efficiency and Soot Emissions using Gasoline Compression Ignition in a Light Duty Engine with a Fuel Pressure Limitation

Increasing regulatory demand to reduce CO2 emissions has led to a focus on advanced combustion strategy development to improve overall engine efficiency. Gasoline compression ignition (GCI) has been demonstrated by others to have the potential to meet future CO2 regulations and emissions while achieving comparable to better efficiency than conventional diesel compression ignition (DCI). Soot and NOx emissions are also reduced significantly by using gasoline instead of diesel in compression ignition engines due to differences in composition, fuel properties, and reactivity. In comparison with diesel fuel, gasoline has a higher volatility and more resistance to autoignition, therefore, its longer ignition delay time will allow for better mixing of the air-fuel charge before combustion. In this study, a GCI combustion system has been tested in a Hyundai 2.2L engine as part of a US Department of Energy funded project. A double-injection strategy was tested from mid-to-high loads (5-20 bar BMEP) and for engine speeds in the range of 1200-3000 rpm. Up to 43.4% brake thermal efficiency was achieved using the GCI mode versus 41% using DCI mode. The GCI mode has demonstrated two distinct strategies that work at different load ranges, partially premixed compression ignition (PPCI) and mixing-controlled compression ignition (MCCI). Overall, this study shows that for similar engine-out NOx levels, GCI mode had higher brake thermal efficiency than DCI with lower fuel pressure and EGR required.

02 PETROLEUM↗