Comparison of a Full-Scale and a 1:10 Scale Low-Speed Two-Stroke Marine Engine Using Computational Fluid Dynamics
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Dal Forno Chuahy, Flavio↗
Engineering topics
Kaul, Brian
Publications and source records attributed to Kaul, Brian.
Biofuels as Heavy Fuel Oil Substitutes in the Maritime Sector: Findings and Potential Pathways
The United States Department of Energy has commissioned four national laboratories to evaluate the feasibility of biofuels in the maritime sector. This effort is briefly described including the overall project goals, structure and aims. The large two-stroke crosshead engines used to power large merchant vessels were of particular interest since they can burn lower combustion quality fuels relative to four-stroke engines. This characteristic allows for consideration of pyrolysis oils and hydrothermal liquefaction (HTL) oils which are feedstock agnostic and, in the raw state, are more economical compared to distillate drop-in fuels. Pyrolysis and HTL oils are collectively known as bio-intermediates since they require additional processing for use in distillate fuel systems. The key limiting feature is that these bio-intermediate fuels will cause asphaltene precipitation when blended with heavy fuel oils (HFOs) such as very low sulfur fuel oil (VLSFO) unless they are upgraded to remove water and oxygenates. Economics are the key driver at this point in time, and preliminary techno-economic analyses (TEAs) indicate that bio-intermediates have potentially lower cost relative to other biofuels such as biodiesel and renewable diesel. Additionally, life cycle analyses (LCAs) of feedstocks and pathways show the life cycle carbon reduction benefit relative to heavy fuel oils. In addition to TEA and LCA results, we also present on the technical feasibility of these fuels. These studies have focused on the properties of biofuel blends with VLSFO that are critical to the fuel systems of maritime vessels fueled with HFOs. These properties include the compatibility with fuel system metals, viscosity, and blend stability. Aging studies with blends of VLSFO with biodiesel, HTL, and pyrolysis oils are also presented. Future efforts being planned to conduct additional biofuel testing, including the use of biofuels as pilot fuels in zero carbon shipping options fueled with ammonia and methanol, ship-based demonstrations, and bioresource competition studies.
Kass, Michael↗
Analysis of Real-World Preignition Data Using Neural Networks
Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubricant properties as well as calibration strategies, but the causal factors behind an individual preignition cycle remain elusive. If actionable precursors could be identified, mitigation through active control strategies would be possible. This paper uses artificial neural networks to search for identifiable precursors in the cylinder pressure data from a large real-world data set containing many preignition cycles. It is found that while follow-up preignition cycles in clusters can be readily predicted, the initial preignition cycle is not predictable based on features of the cylinder pressure. Further, this indicates that the alternating pattern of preignition cycles within clusters is influenced by the thermodynamic state as reflected in the pressure, but that the trigger for the initial preignition cycle is not thermodynamic in nature, but more likely tied to a critical threshold in the chemistry of the fuel/lubricant mixture in the upper crevice or other factors related to the presence of an ignition source.
33 ADVANCED PROPULSION SYSTEMS↗
The future of ship engines: Renewable fuels and enabling technologies for decarbonization
Shipping is one of the most efficient transportation modes for moving freight globally. International regulations concerning decarbonization and emission reduction goals drive rapid innovations to meet the 2030 and 2050 greenhouse gas reduction targets. The internal combustion engines used for marine vessels are among the most efficient energy conversion systems. Internal combustion engines dominate the propulsion system architectures for marine shipping, and current marine engines will continue to serve for several decades. However, to meet the aggressive goals of low-carbon-intensity shipping, there is an impetus for further efficiency improvement and achieving net zero greenhouse gas emissions. These factors drive the advancements in engine technologies, low-carbon fuels and fueling infrastructure, and emissions control systems. This editorial presents a perspective on the future of ship engines and the role of low-life cycle-carbon-fuels in decarbonizing the marine shipping sector. A selection of zero-carbon, net-zero carbon, and low-lifecycle-carbon-fuels are reviewed. This work focuses on the opportunities and challenges of displacing distillate fossil fuels for decarbonizing marine shipping. In conclusion, enabling technologies such as next-generation air handling, fuel injection systems, and advanced combustion modes are discussed in the context of their role in the future of low-CO 2 intensity shipping.
33 ADVANCED PROPULSION SYSTEMS↗
Hazard and Operability Study for the Ammonia Fuel Systems at the National Transportation Research Center
Oak Ridge National Laboratory’s (ORNL’s) Buildings and Transportation Science Division (BTSD) plans to operate research engines fueled by ammonia in two engine test cells at the National Transportation Research Center (NTRC). A scientific need has recently emerged to evaluate the suitability of liquid anhydrous ammonia as a low-lifecycle-carbon fuel source for difficult-to-electrify transportation sectors, including the marine sector. Therefore, BTSD plans to install an ammonia storage and delivery system to 2360 HVC engine research labs L125 (Cell 3) and L111 (Cell 7) capable of delivering 35 and 75 lb/h, respectively. These laboratories are specifically designed to allow for engine and fuels research and development, and they have existing safety systems for mitigating risks associated with toxics and flammables. Anhydrous ammonia is toxic and flammable, and the system will use relatively large quantities compared with standard gas bottles. Ammonia is one of the most widely produced chemicals in the world, and the hazards associated with toxicity and flammability are well understood. Ammonia storage for use in engine research at NTRC is anticipated to take the form of an ammonia tank with capacity of 1,000 water gallons; this quantity will remain below the threshold quantity of 10,000 lb (~2,000 gal) used both by the US Environmental Protection Agency for reporting under the Emergency Planning and Community Right to Know Act and for Risk Management Program requirements, and also by the US Occupational Safety and Health Administration for Process Safety Management requirements. ORNL’s Environmental Protection Services Division was also consulted to verify that the quantities of ammonia anticipated to be used would be in compliance with environmental regulations. The Environmental Protection Services Division staff confirmed that the anticipated quantities fall below ORNL’s permit thresholds. However, because of the hazards associated with anhydrous ammonia, the quantities to be used, and the limited experience with similar quantities of ammonia at ORNL, BTSD decided to perform a hazard and operability (HazOp) study on the ammonia storage and delivery system.
33 ADVANCED PROPULSION SYSTEMS↗
Lubricant impacts on piston deposit formation in the Enterprise marine diesel research engine
The impact of lubricant formulation on piston deposits was studied using the Enterprise, a reduced-scale, single-cylinder, two-stroke crosshead marine diesel research engine. The Enterprise engine was specially designed for marine diesel lubricant research, with a custom reduced-scale cylinder lubricant injection system and extensive instrumentation of thermal boundary conditions on both the liner and piston. Lubricant conditions typical of full-scale marine diesel engines are obtained by matching mean piston speed, liner temperature profile, and combustion metrics to realistic values.Piston deposit thicknesses were measured after a set period of operation, with a focus on lubricant-based deposits on the lands and ring grooves, using both optical and contact-based measurement techniques. Engine operation for each lubricant was conducted according to a standardized protocol, with precise control of engine speed and load, cylinder lubricant injection rate, coolant temperatures, and system oil temperature; the liner and piston temperatures are continuously monitored during operation. After operation with each lubricant was completed, the engine was disassembled, and the piston and ring deposits were characterized. The piston was then thoroughly cleaned, and the lubricant system flushed, between each lubricant formulation being evaluated. The impacts on piston deposits of the lubricants being evaluated can thus be accurately quantified and are described herein.
Kaul, Brian↗
Computational Requirements in Clean Energy and Manufacturing: Summary report of the virtual workshop held on June 28-29, 2021
On June 28–29, 2021, the US Department of Energy’s (DOE’s) Advanced Scientific Computing Research (ASCR) program in the Office of Science convened a workshop with the Energy Efficiency and Renew able Energy (EERE) program offices to assess the future need for advanced computing resources in the areas of clean energy and advanced manufacturing. In part, this discussion served as an update to earlier workshops and townhalls. ASCR is guided by DOE mission needs as it develops research programs, computers, and networks at the leading edge of technologies. As the exascale computing era dawns, technology changes are creating new opportunities for those who must use high-performance computing (HPC) and data systems effectively. The ASCR computing facilities are augmenting their strategy to adapt to changing science needs and emerging technologies and to leverage the utility of exascale computing across the federal government.
97 MATHEMATICS AND COMPUTING↗
Stability, rheological and combustion properties of biodiesel blends with a very-low sulfur fuel oil (VLSFO)
Not Available
09 BIOMASS FUELS↗
Artificial Neural Networks for In-Cycle Prediction of Knock Events
Downsized turbocharged engines have been increasingly popular in modern light-duty vehicles due to their fuel efficiency benefits. However, high power density in such engines is achieved thanks to high in-cylinder pressure and temperature conditions that increase knock propensity. Next-cycle control has been studied as a method to reduce the damaging effects of knock by operating the engine in a low knock probability condition. This exploratory study looks at the feasibility of in-cycle knock prediction as a tool for advanced knock control algorithms. A methodology is proposed to 1) choose in-cycle features of the pressure trace that highly correlate with knock events and 2) train artificial neural networks to predict in-cycle knock events before knock onset. The methodology was validated at different operating conditions and different levels of generalization. Precision and recall were used as metrics to evaluate the binary classifier. However, the Fowlkes-Mallows (FM) index was used to compare the result of the clustering algorithm at different operating conditions. The results showed a maximum FM index of 0.7 when the prediction was done at knock onset and a minimum FM index of 0.45 when the prediction was done at spark timing.
42 ENGINEERING↗
Biofuel Viability for the Ocean-Going Marine Sector
Marine transport contributes significantly to global carbon dioxide emissions but is one of the most difficult sectors to decarbonize because full electrification is infeasible. Renewable, low–carbon biofuels offer a potential path to decarbonization of the marine sectors but the understanding of the effects of new biofuels on engine performance and emissions is limited. In this document we report on the results of a series of studies on the techno-economic, life cycle and technical feasibility of biofuels as replacements for heavy fuel oils currently used to fuel large ocean-going vessels.
09 BIOMASS FUELS↗
Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators
Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.
33 ADVANCED PROPULSION SYSTEMS↗
Artificial-intelligence-based prediction and control of combustion instabilities in spark-ignition engines
In recent years, as engine control strategies have grown increasingly sophisticated in a continued drive for increasing efficiency and reducing emissions, engine operation has been pushed into regimes that are limited by combustion instabilities. These instabilities produce undesirable abnormal combustion events, which pose barriers to further improvement in engine efficiency. Many of the phenomena involved are difficult to model or control using traditional, purely physics-based models and reactive control approaches. Artificial intelligence (AI) techniques offer some promise for achieving more effective combustion stability control, especially when appropriately applied within a physics-informed framework. This chapter illustrates the current state-of-the-art in applying AI to combustion stability control and examines three case studies with application to the dilute stability limit in spark-ignition engines to illustrate the utility and limitations of AI in these applications.
Maldonado Puente, Bryan↗
Real-Time Evolution and Deployment of Neuromorphic Computing at The Edge
Extremely low power neuromorphic systems are well-suited for deployment to the edge for many applications. In many use cases of neuromorphic computing for control, a spiking neural network is trained off-line using a simulation and then deployed to a neuromorphic system at the edge, where it will operate without ongoing training or learning. However, it may be desirable to continue training or learning at the edge to refine or adapt to the real-world system. In this work, we propose an approach for performing real-time evolutionary optimization for spiking neural networks for neuromorphic deployment at the edge. In particular, we propose a combination of simulation and real-world evaluations, along with feedback from the real-world environment, to train spiking neural networks for continuous deployment to the edge. We show that the real-time evolution at the edge approach achieves comparable performance to an evolution approach that requires constant evaluation in the realworld environment.
Schuman, Catherine↗
Hardware-in-the-Loop Investigation of Emissions Challenges in Hybrid Medium- and Heavy-Duty Powertrains Using a Pre-Production Diesel-Electric Parallel Hybrid System With and Without Stop-Start Operation
Hybrid electric powertrains are a growing market in medium- and heavy-duty applications. There is a lack of available information to understand the challenges in the integration of engine platforms into electrified powertrains, such as cold-start, restart, and load-reduction effects on emissions and emission control devices. Results from the Heavy Heavy-Duty Diesel Truck (HHDDT) cycle using a conventional medium-duty diesel engine were compared with those of a parallel hybrid architecture. Oak Ridge National Laboratory in collaboration with the US Department of Energy and Odyne Systems, LLC developed a powertrain in a hardware-in-the-loop environment, integrating the Odyne Systems, LLC medium-duty parallel hybrid system, which was used for the hybrid portion of this study. Experiments under the HHDDT cycle showed increasing improvements in fuel consumption and engine-out emissions with the integration of stop/start, hybrid, and hybrid with stop/start. However, the effects of load reduction and exhaust temperature on the thermal management strategy have shown an increase in fueling in the second part of the HHDDT cycle. Four configurations of medium-duty electrification were studied and contributed to building a unique data set containing combustion, emissions, and system integration data. Each electrification level was compared with the conventional baseline. The calibration of the conventional engine was not altered for this study. Opportunities to tailor the combustion process were identified with the stop/start strategy.
Lerin, Chloe↗
Fuel Stratification Effects on Gasoline Compression Ignition with a Regular-Grade Gasoline on a Single-Cylinder Medium-Duty Diesel Engine at Low Load
Prior research studies have investigated a wide variety of gasoline compression ignition (GCI) injection strategies and the resulting fuel stratification levels to maintain control over the combustion phasing, duration, and heat release rate. Previous GCI research at the US Department of Energy’s Oak Ridge National Laboratory has shown that for a combustion mode with a low degree of fuel stratification, called “partial fuel stratification” (PFS), gasoline range fuels with anti-knock index values in the range of regular-grade gasoline (~87 anti-knock index or higher) provides very little controllability over the timing of combustion without significant boost pressures. On the contrary, heavy fuel stratification (HFS) provides control over combustion phasing but has challenges achieving low temperature combustion operation, which has the benefits of low NOX and soot emissions, because of the air handling burdens associated with the required high exhaust gas recirculation rates. Furthermore, this work investigates HFS and PFS combustion, efficiency, and emissions performance on a single-cylinder, medium-duty engine with a regular-grade gasoline (91 research octane number) at 1,200 rpm, 4.3 bar, and 3.0 nominal gross indicated mean effective pressure operating points with boost levels similar to those in a medium-duty diesel application. Authority of combustion phasing with main injection timing sweeps for HFS and second injection timing sweeps and fuel split sweeps for PFS are shown. In addition, this work is discussed in the context of previous findings with a light-duty diesel platform, and next steps and future direction for this work are presented.
33 ADVANCED PROPULSION SYSTEMS↗
Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion
In this simulation study, cycle-to-cycle fuel control was used to reduce CCV by injecting additional fuel in operating conditions with sporadic misfires and partial burns. An optimal control policy was proposed that utilizes 1) a physics-based model that tracks in-cylinder gas composition and 2) a one-step-ahead prediction of the combustion efficiency based on a kernel density estimator. The optimal solution, however, presents a tradeoff between the reduction in combustion CCV and the increase in fuel injection quantity required to stabilize the charge. Such a tradeoff can be ad- just by a single parameter embedded in the cost function.
Maldonado, BryanP. [Oak Ridge National Lab. (ORNL)↗
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↗
Cyclic dynamics of misfires and partial burns in a dilute spark-ignition engine
Here, this study investigates the cyclic dynamics of cumulative heat release data past the edge of stability in a dilute spark-ignition engine. Emphasis is placed on analyzing the cyclic dynamics near the dilute limit where partial burns and misfires are frequent. These events are often followed by a higher-energy cycle due to the feed-forward mechanism present in the residual gases. These patterns are deterministic and increase the coefficient of variation to undesirable levels. Symbol sequence analysis was used to investigate the cyclic dynamics of these low–high patterns. The heat release was partitioned on an energy basis to give physical meaning to each partition and each sequence created when analyzing the symbol sequence results. This partitioning method provided insight into the differences in the dynamics when operating in the misfire or partial burn regime. These differences could impact the control method used.
42 ENGINEERING↗