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At least 343 records · Page 19

Heavy-Duty Nonroad Material Handler Electrification Part 2: Energy Efficiency and Performance Evaluation

Decarbonization efforts achieved through electrification in nonroad mobile machinery can realize a reduction in fuel consumption of more than 20%, thanks to concepts familiar to light-duty passenger vehicles. This case study compares the results of a hybrid-electric material handler to its conventional counterpart, utilizing machine-specific drive cycles presented in part one of this paper series. The hybrid prototype features an extended-range electric vehicle (EREV) powertrain that demonstrated substantial energy efficiency improvements. Specifically, there was a reduction in equivalent fuel consumption of 75% when operating in electric-only mode, and 33% when maintaining the battery by charging with an on-board generator. Together, the efficiency improvements can be extrapolated over a low-intensity, 8-h shift characterized by significant idle time and highly dynamic engine load for a 47% reduction in net energy consumption. Key technologies that led to this improvement included engine downsizing and decoupling, regenerative braking, and an electrohydraulic pump unit with advanced controls. Finally, his study explains details of the powertrain architecture and subsystems that were implemented on a demonstration vehicle, control strategies used to meet project goals, and an analysis of energy consumption from testing on a closed course. Also included in this study is a discourse on comparison metrics that can be used for quantifying the energy consumption differences between hybrid-electric and conventional diesel powertrains in nonroad mobile machinery.

25 ENERGY STORAGE↗

Comparative Techno-economic Analysis and Life Cycle Assessment of Producing High-Value Chemicals and Fuels from Waste Plastic via Conventional Pyrolysis and Thermal Oxo-degradation

The rapid rise in global plastic production in recent decades has resulted in the massive generation of plastic waste. Over 75% of the plastic waste generated in the United States was sent to landfills, with a meager 8.7% recycled. Plastics are valuable feedstocks for platform chemicals and fuels. Chemical upcycling of waste high-density polyethylene (HDPE) is gaining more attention as a potentially feasible and environmentally friendly plastic waste management technology. Conventional pyrolysis (CPY) and thermal oxo-degradation (TOD) are two chemical upcycling technologies actively researched for decomposing waste HDPE into valuable chemicals and fuels. However, there are few studies on the techno-economic analysis (TEA) and life cycle assessment (LCA) of these technologies for converting waste HDPE to valuable products. This study conducts a comparative TEA and LCA study of the thermochemical decomposition of waste HDPE to produce gaseous (ethylene and propylene) and liquid (naphtha, diesel, and wax) products by CPY and TOD. The study elucidates and compares the impact of hydrocracking longer chain hydrocarbons to produce more valuable products on the TEA and LCA. The TEA showed that the fixed capital investment could range from $\$32.5$ million for TOD without hydrocracking to $\$244$ million for CPY with hydrocracking scenarios. Annual revenues range from $\$28.1$ million to $\$71.5$ million in favor of scenarios with hydrocracking. However, the net present value ranges from $\$1.4$ million to $\$265.8$ million in favor of scenarios without hydrocracking. Sensitivity analysis showed that fixed capital cost, facility capacity, and product prices have the biggest impact on the process economics of the facilities, while utilities and waste transportation to refineries have the biggest impact on environmental impacts. Here, the LCA showed that primary products from scenarios without hydrocracking can be more environmentally friendly than virgin products from petroleum processes. However, TOD and CPY with hydrocracking primary products have more emissions than those of virgin products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-driven selection of stiff chemistry ODE solver in operator-splitting schemes

Most computational fluid dynamics simulations of practical combustion applications employ operator-splitting schemes, where chemistry and transport are separated and integrated with distinct numerical methods. The changes in composition due to chemistry are evaluated by solving ordinary differential equations (ODE) in each cell of the computational domain, which typically dominates the computational cost when detailed chemistry is considered. In this work, a data-driven approach for the selection of chemistry ODE solvers in operator-splitting schemes is presented. Neural networks are used to predict the ODE solvers CPU times and errors for a given thermochemical state. This allows the selection of an optimal ODE solver on a cell-by-cell, timestep-by-timestep basis. The models are trained using a wide set of thermochemical states generated through partially-stirred reactors and flames simulations. The methodology is validated by quantifying the prediction errors, the classification accuracy, and the computational speedup. The model predicts the optimal ODE solver for 70 to 95% of the validation cases and decreases the computional cost by a factor of 3 or more. The generalizability of the methodology to different chemical mechanisms and different fuels is assessed and it is shown that the model’s performance is only slightly degraded and its applicability is significantly enhanced if the inputs to the neural networks are restricted to a small set of thermochemical state variables present in most chemical mechanisms. In conclusion, the models are used in an homogeneous reactor case and a multi-dimensional CFD simulation of a diesel spray at high pressure where a speedup of more than 3 is achieved.

42 ENGINEERING↗

Diesel engine catalytic combustor system

A low compression turbocharged diesel engine is provided in which the turbocharger can be operated independently of the engine to power auxiliary equipment. Fuel and air are burned in a catalytic combustor to drive the turbine wheel of turbine section which is initially caused to rotate by starter motor. By opening a flapper value, compressed air from the blower section is directed to catalytic combustor when it is heated and expanded, serving to drive the turbine wheel and also to heat the catalytic element. To start, engine valve is closed, combustion is terminated in catalytic combustor, and the valve is then opened to utilize air from the blower for the air driven motor. When the engine starts, the constituents in its exhaust gas react in the catalytic element and the heat generated provides additional energy for the turbine section.

Ream, L. W.↗

A Powerful New Engine

Through Small Business Innovation Research (SBIR) funding from NASA's Glenn Research Center, Moller International created a new coating for rotary engines, which significantly improves the fuel consumption of a vehicle while reducing emissions. The new coatings are offered in the new Rotapower(R) engine, which is produced and distributed by Moller subsidiary, Freedom Motors, Inc. The coating allows the Rotapower engine to function smoother than other models, reducing wear and protecting the engine. The Rotapower engine has the ability to operate on a variety of fuels, including gasoline, natural gas, diesel, alcohol, and kerosene. A small and lightweight engine, it is projected to replace many of today's bulkier versions. The 10 horsepower model fits in the palm of one's hand, while the 160 horsepower model fits into a 5-gallon bucket. The clean running Rotapower engine is environmentally appealing, because it eliminates over 98 percent of the total emissions given off by traditional piston engines. Fewer pollutants are spewed into the air, making it especially attractive in areas where air pollution is a major problem. Due to the clean-burning nature of the engine, it meets the stringent standards set by the California Air Resources Board. The engine also has numerous commercial benefits in several types of recreational, industrial, and transportation applications, including personal watercraft, snowmobiles, portable generators. and pumps.

Source record↗

No Need to Wait for the Clean Air Dividend

Controlling smog and soot is the classic win-win situation, so it's great that the world is finally waking up to the idea. WHAT if there was a way to simultaneously slow down climate change, save millions of lives, improve crop yields and contribute to sustainable development and energy security? It sounds too good to be true, but it is possible. It won't be free or easy, but with some effort and moderate investment, it can be done. The way to do it is to reduce emissions leading to two types of pollution: black carbon and ozone. These are the only pollutants that we know contribute to both global warming and poor air quality. Black carbon is essentially soot, emitted from incomplete combustion of fossil fuels and biomass. It warms the climate in two ways: by absorbing heat in the atmosphere - similar to the greenhouse effect - and by reducing Earth's albedo, or ability to reflect sunlight. Inhaled into the lungs, it leads to cancer and cardiovascular disease. Ozone in the atmosphere also acts as a greenhouse gas, while ground-level ozone is toxic to humans and plants, so leads to both premature death and reduced crop yields. Ozone is not emitted directly but is produced by the action of sunlight on other pollutants, which are known as ozone precursors. Since black carbon and ozone are important components of soot and smog, a great deal of effort has already been put into developing methods to reduce emissions. So effective technology is available, but needs wider implementation. The recommended control measures for black carbon include widespread and tight emission standards on diesel cars and trucks; improved solid fuel cooking stoves, brick kilns and coke ovens in the developing world; and a ban on the open burning of agricultural waste. Implementation of these measures would have a rapid impact on the climate and human health, and also have the added benefit of greatly reducing emissions of carbon monoxide, an important ozone precursor. A second key ozone precursor is methane, which is also a powerful greenhouse gas in its own right. Control measures include reducing leaks from natural gas pipelines and storage tanks, and capturing it from coal, gas and oil extraction, landfills and wastewater treatment plants. Aeration of rice paddies and manure management can also reduce methane releases. Captured methane can often be sold or turned into power. In Monterrey, Mexico, for example, electricity generated from methane collected from the city landfill powers the public transportation system. So such measures can be beneficial even when ignoring the health and climate effects, as they can contribute to energy security and often pay for themselves. According to calculations by me and my colleagues, phasing in all these measures over the next 20 years would reduce global warming by about 0.5 degC in 2050, half of the projected increase between now and then (Science, vol 335, p 183). Regional benefits would be even greater, as black carbon disrupts rainfall patterns and magnifies warming and melting of snow and ice in parts of the world including the Arctic and the Himalayas. On top of the climate benefits, cutting black carbon and ozone would prevent over 3 million premature deaths from air pollution, and increase yields of staple crops by roughly 50 million tonnes a year. Improved cooking stoves would also decrease the demand for firewood in the developing world, reducing deforestation and freeing up time for those who collect wood - primarily women and children - to pursue other activities such as education. Similarly, improved brick kilns now being used in parts of Latin America and Asia require half as much fuel as traditional ones and are less time-intensive for the operators. This means that in addition to their environmental benefits, these measures can contribute to sustainable and human development. Tackling black carbon and methane is clearly a great idea, so why hasn't it been done already? There are many barriers. The upfront costs of some measures can be prohibitive even when they eventually pay for themselves. But this can be overcome by mechanisms such as international financing of capital costs. For other measures, the costs are typically borne by a few while the benefits accrue to everybody. In such cases civil society and governments must get involved. Governments are starting to act. In February, the US, Canada, Sweden, Bangladesh, Ghana and Mexico launched the Climate and Clean Air Coalition to support implementation of measures like these. This coalition will hopefully expand and achieve rapid, widespread adoption of measures to cut black carbon and ozone. While the climate benefits will be substantial, it is important to note that these measures cannot substitute for cuts in carbon dioxide. Black carbon, ozone, carbon monoxide and methane stay in the atmosphere for a fairly short time - a few days for black carbon and about a decade for methane. They thus respond quickly to emissions changes and give us substantial leverage over near-term climate change. In contrast, carbon dioxide is very long-lived and so responds slowly to emissions changes. This means that cuts have little immediate impact, but it also means they must be made now to avoid disastrous changes later on. Controlling short-lived climate pollutants is thus an issue of fairness. Much as failure to reduce carbon dioxide emissions soon would condemn future generations to disastrous change, failure to reduce near-term climate change condemns those alive today to suffer worsening effects of the sort already seen. Some wonder if we really can do both. We can, and we must.

Shindell, Drew↗

Model-Based Framework to Optimize Charger Station Deployment for Battery Electric Vehicles

The development of battery electric vehicles (BEVs) is accelerating due to their environmental advantages over gasoline and diesel-powered vehicles, including a decrease in air pollution and an increase in energy efficiency. The deployment of charging infrastructure will need to increase to keep pace with demand, especially for large commercial vehicles for which few public chargers currently exist. In this paper, a new flexible framework is proposed for optimizing the placement of charging stations for BEVs, within which different physical models and optimization techniques may be used. Furthermore, a set of metrics is suggested to help enforce complex constraints and facilitate direct comparison between different optimization techniques. Unlike many existing charger placement techniques, the proposed method directly considers the historical driving patterns on a vehicle-by-vehicle basis, using transparent models to assess impacts of candidate charger placements, thus improving the explainability of the results. In the developed framework, modeled BEVs are first generated along the road network to mimic historical traffic data and are simulated traveling along a given route according to a simplified vehicle model. During the simulation, the charger placement problem is initially relaxed to allow vehicles to charge at any node along the road network, and vehicle states are tracked to assess areas of high charging demand. Charging stations are then placed based on the results of the relaxed simulation, and suggested placements are evaluated via road network simulation with fixed charger locations. This proposed framework is applied to a sample problem of placing charging stations along five major highway corridors for Class 8 over-the-road electric trucks. A novel mixed integer programming (MIP) formulation is proposed to optimize charger placements based upon the expected charging demand. Constraints were imposed on the final placement results to limit expected wait times at each station and ensure a minimum threshold of trucking routes are viable for BEVs. The results demonstrate the flexibility and potential effectiveness of the developed model-based framework for scalable charger station deployment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Mobilizing mine lands for biobased decarbonization strategies

Over 163 000 ha of mine lands in Pennsylvania (PA) have the potential to produce willow as a feedstock for renewable energy generation. Each year these lands could produce between 454 000 and 907 000 dry Mg of willow, which can be a feedstock for bioenergy (i.e., biopower) with carbon capture and sequestration (BECCS) or sustainable aviation fuel (SAF) production. We used a spatially explicit model to explore cost-minimized allocation of willow biomass from abandoned mine lands (AML) to be used for BECCS or SAF production and to abate carbon dioxide. The results suggest that between 454 000 and 907 000 dry Mg of biomass can be produced on AML in PA at costs from $94 to $250 per dry Mg. This AML willow biomass could be combined with other available biomass and aggregated to ten facilities to produce 17.9 TWh of power; alternatively, it could produce 958 million liters of jet fuel, 638 million liters of renewable diesel, and 1.289 billion liters of naphtha, along with 0.735 TWh of electricity. From this analysis, in PA, under the BECCS pathway, up to 36 million Mg per year of CO2 could be abated at costs of up to $134 per Mg; under the SAF pathway, up to 17.5 million Mg per year of CO2 could be abated at costs up to $150 per Mg of CO2. The use of mine land willow as a supplemental feedstock for SAF and BECCS would need strong incentive programs if costs of production are to be comparable with production on agricultural land.

Wahlstrom, Mallory [Pennsylvania State University]↗

Performance and cost analysis of liquid fuel production from H 2 and CO 2 based on the Fischer-Tropsch process

Electro-fuels can be produced from concentrated sources of carbon dioxide and hydrogen using electricity generated from renewable sources; this process enables energy storage at high volumetric energy density. Among the electro-fuels options, FT (Fischer-Tropsch) fuel is attractive for heavy-duty trucks and non-road transportation applications. This study conducts a techno-economic analysis of FT liquid fuel production from H 2 and CO 2 using a detailed performance analysis. Minimum fuel selling price is estimated for a broad range of H 2 and CO 2 prices and for a range of potential CO 2 credits. The analysis indicates that H 2 price has the largest impact on the minimum selling price of FT fuel. FT fuel production with a CO 2 price of $17.3/metric ton requires an H 2 price of $0.8/kg to be cost-competitive with the pre-tax petroleum diesel price of $3.1/gal in 2050 (before the application of any CO 2 credits). When the H 2 price is $2.0/kg from central water electrolysis (2020 target), the minimum selling price of the FT fuel is $5.4–5.9/gal. A sensitivity analysis shows that future system optimization of FT fuel production could focus on improving the H 2 and CO 2 recycle contributions and FT fuel conversion ratio. The analysis results can be combined with various upstream systems for H 2 and CO 2 production.

08 HYDROGEN↗

A Novel Catalytic Membrane Reactor for DME Synthesis from Renewable Resources

Production of liquid fuels or chemicals from CO 2 (captured from the air or flue gases) and renewable hydrogen presents a new approach to producing clean fuels domestically. While significant progress has been made in the area of renewable electricity generation from solar and wind, a large gap remains with respect to the production of renewable liquid fuels/chemicals. Other processes for producing liquid fuels/chemicals from renewable electricity are constrained by thermodynamic limitations, making them prohibitively expensive and impractical. The team is overcoming these limitations and developing catalytic membrane reactor processes with high yields and low energy penalties. Supported by the Advanced Research Projects Agency-Energy (ARPA-E) of the US Department of Energy (DOE), GTI Energy and partners have been developing a technology for the production of renewable dimethyl ether (DME) from carbon dioxide (CO 2 ) and renewable hydrogen (H 2 ) using a novel catalytic membrane reactor and demonstration of this system at a scale of 1 kg/day. DME is a clean-burning, non-toxic fuel with a high cetane value (55-60), making it an excellent diesel alternative. DME can be stored as a liquid under moderate pressure, eliminating the need for the high-pressure containers used for CNG or cryogenics, as in the case of LNG. DME is also approved as a renewable fuel under the U.S. Environmental Protection Agency’s Renewable Fuels Standard (RFS), making it eligible for Renewable Identification Numbers (RINs) credits. By producing DME through the catalytic conversion of captured CO 2 and renewable H 2 , this process will produce renewable liquid transportation fuel and a means of large-scale utilization of captured CO 2 . In the DME synthesis process, CO 2 and H 2 are fed to a hollow fiber catalytic membrane reactor at 300-600 psig that contains a bi-functional catalyst that combines two reactions, methanol synthesis (CO 2 + 3H 2 → CH 3 OH + H 2 O) and methanol dehydration (2CH 3 OH → CH 3 OCH 3 + H 2 O), into a one-step process to produce DME. The bifunctional catalyst converts methanol to DME, enabling higher overall CO 2 conversion. A Cu/ZnO/ZrO 2 /Al 2 O 3 (CZZA) catalyst is used for methanol synthesis and is coupled with a zeolite catalyst H-ZSM-5 for dehydration. This one-step process intensifies a process that would otherwise require multiple reaction steps. However, combining these two reactions results in increased water production which inhibits catalytic activity. Here, the Na + -gated, water-transport membrane (Science, vol. 367, pp. 667, 2020), removes water in situ, shifting the thermodynamic equilibrium towards product formation while decreasing kinetic inhibition from water adsorption onto the catalyst surface. The Na + gated, water-transport nanochannel membrane showed H 2 O/CO 2 selectivity of 560 at 250 °C and 300 psig for H 2 O/CO 2 /CO/H 2 /MeOH gas mixtures. The selectivities of H 2 O/H 2 , H 2 O/CO, and H 2 O/MeOH were 190, 170, and 80, respectively. In a laboratory-scale membrane reactor, DME synthesis testing using this membrane, a DME production rate of 440 g DME /kg cat /h was achieved at 260 °C and 550 psig. Compared to the packed bed reactor, the CO 2 conversion and DME production rate in the membrane reactor were 80% and three times higher, respectively. A prototype test system (1 kg/day) was designed, constructed, and tested. A DME production rate of 1.31 kg/day and a DME productivity of 360 g/h/kg were achieved in the prototype membrane reactor. Good stability was demonstrated during 150-h continuous operation and multiple startups/shutdowns tests.

10 SYNTHETIC FUELS↗

Effects of Port Angle on Scavenging of an Opposed Piston Two-Stroke Engine

Opposed-piston 2-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a typical diesel engine. However, the uniflow scavenging process is difficult to control over a wide range of speeds and loads. Scavenging performance is highly sensitive to pressure dynamics, port timings, and port design. This study proposes an analysis of the effects of port vane angle on the scavenging performance of an opposed-piston 2-stroke engine via simulation. A CFD model of a three-cylinder opposed-piston 2-stroke was developed and validated against experimental data collected by Achates Power Inc. One of the three cylinders was then isolated in a new model and simulated using cycle-averaged and cylinder-averaged initial/ boundary conditions. This isolated cylinder model was used to efficiently sweep port angles from 12 degrees to 29 degrees at different pressure ratios. Results indicate that scavenging performance is correlated with the bulk swirl ratio generated by these port angles. Scavenging performance is also sensitive to the pressure ratio across the engine. It was concluded that, for a given pressure ratio, the smallest port angle produces the best scavenging; however, previous work indicates lower bulk swirl ratio during combustion can have an impact on emissions formation.

33 ADVANCED PROPULSION SYSTEMS↗

Analyzing School Bus Electrification in Richmond, Virginia

School buses are an essential component of the transportation infrastructure, serving as a lifeline for students across the globe. However, the widespread use of diesel school buses has raised concerns about the health impact on millions of students exposed to harmful emissions daily. Recognizing this issue, school districts worldwide are urgently seeking cleaner energy alternatives. Electric school buses emerge as an environmentally friendly and sustainable option, fostering a healthier environment for both students and communities. However, school bus electrification faces the challenges of high upfront cost, cumbersome charging management, and constraints from power grids. To help school bus operators address those challenges, this study presents a data-driven analysis for school bus electrification. This study considered a real-world school bus system in Richmond, VA, and developed a mathematical programming model to analyze the system design, charging strategies, and charging load profiles for the electrification scenario. The study evaluated different charging strategies based on model outcomes, aiming to optimize efficiency and effectiveness. Ultimately, this research generated electric school bus charging demand profiles under various scenarios, shedding light on the feasibility and implications of transitioning to electric-powered school buses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Computational analysis of flame initiation, quenching, and re-ignition in a prechamber natural gas engine under varying EGR-dilution levels

The on-road natural-gas (NG) fueled transportation relies on stoichiometric spark-ignition engines for the advantages of simple after-treatment system despite the efficiency penalty relative to lean-burn combustion strategies. Exhaust gas recirculation (EGR) has the potential to reduce this efficiency gap at low to moderate loads without the need for complex lean-exhaust aftertreatment systems. However, EGR dilution leads to reduced combustion stability and increased cycle-to-cycle variability. A promising technology that has the potential to achieve reliable operation under diluted conditions is the prechamber ignition (or turbulent jet ignition) which uses chemically active turbulent jets generated from combustion inside a prechamber to initiate, stabilize and accelerate combustion of the mixture inside the main chamber. The present work focusses on developing a RANS-based CFD approach to accurately reproduce in-cylinder phenomena in a stoichiometric NG prechamber-assisted heavy-duty engine without relying on complex combustion models that account for turbulence-chemistry interactions. This is necessary because reactive prechamber jets at high EGR dilution tend to extinguish while emerging into the main chamber, which is followed by a phase of re-ignition — a phenomenon that conventional G-equation or well-stirred reactor combustion models cannot reproduce. With addition of a damping multiplier to the well-stirred reactor model, the predictions are seen to show good agreement with experimental pressure evolution and combustion images acquired from a single cylinder Cummins N-14 optical diesel engine retrofitted with a prechamber ignition system. Model predictions of local heat release in the flame and temperature evolution inside the flame are used to investigate combustion dynamics in the prechamber and the main chamber. It is seen that the well-stirred reactor model with the inclusion of damping is able to reproduce the temporary reduction in heat release within the flame, which can be considered equivalent to quenching of jets, and the subsequent re-ignition of the flame inside the main chamber. The delay between quenching and re-ignition depends on the amount of dilution, as explained by an illustration of flame evolution in a Borghi diagram.

Prechamber ignition↗

A novel method for co-optimizing battery sizing and charging strategy of battery electric bus fleets: An application to the city of Paris

Battery-electric buses (BEBs) are a promising technology for replacing diesel buses and reducing their environmental burden. However, their charging process can take several hours, depending on the charging technique and strategy, making them susceptible to schedule disruptions. Furthermore, the selection of the charging strategy and battery size can increase the total capital investment and operational expenses of a BEB fleet, which is a major obstacle to its adoption. Therefore, to minimize the total cost of ownership (TCO) and prevent schedule disruptions, it is essential to establish a well-defined approach to determine an appropriate battery size and charging strategy for BEB fleets. This paper presents a method for reducing the TCO of BEB by determining the optimal battery size and charging strategy for each bus while satisfying operating constraints. The method involves a two-step optimization algorithm that uses Dynamic Programming and Genetic Algorithm. Further, the study applies this approach to the bus fleet serving line 21 in Paris and generates the optimal battery sizing, charging strategy, and required charging infrastructure. The results indicate that 100 kWh batteries offer the best trade-off between capital and operational expenditure for the fleet deployment if used with 65–85 kW chargers at bus terminals.

33 ADVANCED PROPULSION SYSTEMS↗

Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) - Predictive Data-Driven Vehicle Dynamics and Powertrain Control: from ECU to the Cloud (Final Scientific/Technical Report)

This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.

33 ADVANCED PROPULSION SYSTEMS↗

Status Report 2: Advanced Nuclear Reactors Utilized for Synthetic Fuel Creation

Synthetic fuels (synfuels) are hydrocarbon fuels that source energy from electricity. Synfuels have the potential to significantly reduce greenhouse gas emissions throughout the transportation sector. To achieve this substantial reduction in greenhouse gas emissions, the electricity must be sourced from zero- or near-zero-carbon fuel sources such as solar, wind, hydroelectricity, and nuclear power. Synfuels are produced from a combination of carbon and hydrogen sources. Hydrogen can be sourced from water electrolysis with near-zero-carbon electricity and heat (e.g., nuclear), while carbon dioxide can be sourced from ethanol and ammonia plants. In the hydrocarbon fuel synthesis process, hydrogen and carbon dioxide can be reacted to produce carbon monoxide and water, via the so-called reverse watergas shift reaction. Carbon monoxide can then react with additional hydrogen to form hydrocarbons, with carbon chains ranging from C1–C30 in the reaction known as the Fischer-Tropsch (F-T) synthesis reaction. The synthesized hydrocarbon molecules can then be hydro-processed with additional hydrogen and distilled into different carbon chain lengths so as to be compatible with existing conventional gasoline, jet, and diesel fuels. Carbon-free synfuel production comes with a “green premium” over the manufacture of identical products via conventional fossil fuels. Reports from Argonne National Laboratory (ANL) reveal that hydrogen costs dominate the cost of carbon-free synfuel production. This suggests that for the cost of green synfuel to approach that of conventional petroleum fuel, the cost of hydrogen must be approximately $\$1$/kg. Of the primary low-carbon energy sources, only nuclear carries the potential to produce hydrogen at below $\$2$/kg. (Still a bit above the lofty $\$1$/kg goal, but perhaps manageable). To further identify the potential for creating low-cost synfuels capable of competing with legacy technologies, the Department of Energy Office of Nuclear Energy has funded a multi-program, multi-lab effort among ANL, Idaho National Laboratory (INL), the Integrated Energy Systems (IES) program, and the Light Water Reactor Sustainability (LWRS) program. This collaboration effort will determine the possibility of using current and next generation nuclear reactors to create low-cost carbon-free synfuels for sale in the U.S. energy and commodities market.

10 SYNTHETIC FUELS↗

Criterion for Identifying Vortices in High-Pressure Flows

A study of four previously published computational criteria for identifying vortices in high-pressure flows has led to the selection of one of them as the best. This development can be expected to contribute to understanding of high-pressure flows, which occur in diverse settings, including diesel, gas turbine, and rocket engines and the atmospheres of Jupiter and other large gaseous planets. Information on the atmospheres of gaseous planets consists mainly of visual and thermal images of the flows over the planets. Also, validation of recently proposed computational models of high-pressure flows entails comparison with measurements, which are mainly of visual nature. Heretofore, the interpretation of images of high-pressure flows to identify vortices has been based on experience with low-pressure flows. However, high-pressure flows have features distinct from those of low-pressure flows, particularly in regions of high pressure gradient magnitude caused by dynamic turbulent effects and by thermodynamic mixing of chemical species. Therefore, interpretations based on low-pressure behavior may lead to misidentification of vortices and other flow structures in high-pressure flows. The study reported here was performed in recognition of the need for one or more quantitative criteria for identifying coherent flow structures - especially vortices - from previously generated flow-field data, to complement or supersede the determination of flow structures by visual inspection of instantaneous fields or flow animations. The focus in the study was on correlating visible images of flow features with various quantities computed from flow-field data.

Bellan, Josette↗

MACHINE LEARNING-ENABLED PREDICTION OF TRANSIENT INJECTION MAP IN AUTOMOTIVE INJECTORS WITH UNCERTAINTY QUANTIFICATION

Accurate prediction of injection profiles is a critical aspect of linking injector operation with engine performance and emissions. However, highly resolved injector simulations can take one to two weeks of wall-clock time, which is incompatible with engine design cycles with desired turnaround times of less than a day. Hence, it is important to reduce the time-to-solution of the internal flow simulations by several orders of magnitude to make it compatible with engine simulations. This work demonstrates a data-driven approach for tackling the computational overhead of injector simulations, whereby the transient injection profiles are emulated for a side-oriented, single-hole diesel injector using a Bayesian machine-learning framework. First, an interpretable Bayesian learning strategy was employed to understand the effect of design parameters on the total void fraction field. Then, autoencoders are utilized for efficient dimensionality reduction of the flowfields. Gaussian process models are finally used to predict the spatiotemporal void fraction field at the injector exit for unknown operating conditions. The Gaussian process models produce principled uncertainty estimates associated with the emulated flowfields, which provide the engine designer with valuable information of where the data-driven predictions can be trusted in the design space. The Bayesian flowfield predictions are compared with the corresponding predictions from a deep neural network, which has been transfer-learned from static needle simulations from a previous work by the authors. The emulation framework can predict the void fraction field at the exit of the orifice within a few seconds, thus achieving a speed-up factor of up to 38 x 10(6) over the traditional simulation-based approach of generating transient injection maps.

machine learning↗