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Modularization of Ceramic Hollow Fiber Membrane Technology for Air Separation
This proposed project is aimed at studying high performance and economically competitive ceramic membrane technology for air separation and high-purity oxygen production using hollow fiber ceramic membrane stack and module technology. The design of the single permeate membrane is a hollow fiber substrate-supported thin tri-layer structure. Radially well-aligned micro-channels are embedded in the thick substrate and open at the inner surface of the substrate, enabling facile air/gas diffusion. The tri-layer structure of thin dense membrane layer (~ 10 µm) sandwiched by porous surface layer on either side is then built on the substrate using advanced fabrication process. The tri-layer structure design allows different materials to be used in different layers, where the materials of surface layers have high surface exchange coefficients while the material of dense layer has high bulk diffusivity. Such a synergetic combination leads to high permeation performance. The focus of the proposed project will be on membrane stack/module development using the developed single hollow fiber membranes, including: 1) fabrication and characterization of novel single hollow fiber membranes; 2) membrane stack design and assembly using fabricated single membranes; 3) stack modeling and analysis to guide membrane stack designs; 4) permeation performance testing and characterization of membrane stacks. The hollow fiber feature and simple sealing requirement enable very compact design of membrane stacks, which have excellent flexibility for further modularizations at different scales. The operations of such membrane stack and module may employ the exhaust heat from other components of Integrated Gasification Combined Cycle and oxy-combustion systems. Therefore, modularization of such an air separation membrane technology can be incorporated into the DOE’s REMS (radically engineered modular systems)-gasification skid and support the oxidant feed of an oxygen-blown REMS gasifier scaled to different ranges.
Thermal Damage Potential of Electric Vehicles
The main objective is to assess the risk that electric vehicle (EV) battery fires pose regarding thermal damage to other vehicles involved in a crash and to compare EV and internal combustion engine vehicle (ICEV) fires. A literature review of experimental data and statistics are used to perform the assessment. The findings indicate: (1) the heat flux emitted from an EV and ICEV fire are similar due to cabin materials being the main contributor to heat flux, (2) for ICEVs involved in a crash with fuel tank leakage, the thermal damage is significantly more than from an EV fire for equivalent fire durations, (3) the thermal damage potential from ICEV pool fires is at least 5 times higher than EV fires, and (4) EV and ICEV crashes resulting in a fire is about 0.002% and 0.2%, respectively. Thus, EV battery fires have a lower risk than ICEV fires.
Transforming Energy Through Sustainable Mobility: Expanding Low-Carbon Transportation R&D Solutions
As the nation's premier laboratory for cutting-edge transportation decarbonization research and development solutions, the National Renewable Energy Laboratory (NREL) pioneers the creation and deployment of sustainable mobility technologies and strategies, with a focus on slashing transportation sector greenhouse gas emissions and combatting climate change. Trucks, planes, cargo ships, and other difficult-to-decarbonize vehicles are part of this essential transition for the transportation sector, which is currently the nation's largest source of the greenhouse gas emissions. NREL provides the scientific building blocks needed to spur innovation through multifaceted analysis, research, and engineering. This work acts as a catalyst to help industry bring affordable, high-performance, energy-efficient, and low-emission modes of transport and related infrastructure to market sooner. Our researchers collaborate closely with academic, government, and industry partners to design better batteries, drivetrains, and engines. They develop technologies for high-power charging, thermal management, energy storage, and power electronics. They are also reimagining fuels and combustion while creating sustainable lightweight materials. Unbiased expert guidance - backed by credible data and analysis, tools, and scientific rigor - empowers partners to make informed decisions about sustainable transportation. NREL recognizes that communities with limited mobility options face reduced access to employment opportunities, health care, and education, lowering overall quality of life. Alongside partners, NREL experts are creating transportation solutions that meet community-identified needs and increase mobility equity in historically underserved and overburdened communities. Rather than providing a one-size-fits-all solution, we take an interdisciplinary approach to mobility equity that considers the needs and challenges of diverse groups, maximizing benefits at the individual, community, and societal levels.
Redefining fuel heating value for engines: Accounting for heat of vaporization
Defining a fuel's heating value (i.e., energy content) is fundamental for calculating engine efficiency and for life cycle analysis comparisons between different fuels. Traditional definitions of lower heating value and higher heating value account for the effect of water vapor versus liquid water in the exhaust, which is important when the fuel is used in a furnace or boiler. In an engine, it is equally important to properly account for the energy required to vaporize liquid fuel. Heat of vaporization has a small effect for common hydrocarbon fuels, typically less than 1% of lower heating value, but the effect is much larger for other important fuels such as ethanol (3.4% of lower heating value) and methanol (5.9% of lower heating value). This paper defines a new type of fuel heating value that more accurately reflects the useful fuel energy content for engines. Vaporized heating value is defined as the heating value when starting with a vaporized fuel instead of a liquid fuel. It can be calculated by adding the fuel's heat of vaporization to the traditional lower heating value. This paper illustrates the rationale and benefits of using vaporized heating value using data from the literature.
Integrated combustor nozzle for a segmented annular combustion system
The present disclosure is directed to an integrated combustor nozzle for a segmented annular combustion system. The integrated combustor nozzle includes an outer liner segment, an inner liner segment, and a fuel injection panel extending radially between the outer liner segment and the inner liner segment. The fuel injection panel includes a first side wall, a second side wall, and a plurality of premixing channels between the first and second side walls, each of the premixing channels having an outlet on one of the first and second side walls. The aft end of the fuel injection panel defines a turbine nozzle.
Characterization of Flex-Fuel Prechamber Enabled Mixing-Controlled Combustion With Gasoline/Ethanol Blends at High Load
This numerical study focuses on the characterization of prechamber-enabled mixing-controlled combustion (PC-MCC) at ~18 bar brake mean effective pressure (BMEP) and 2200 rpm with 10% by volume ethanol-gasoline blend (E10) and pure ethanol (E100). Computational fluid dynamic (CFD) simulations of a stock and prechamber retrofitted single-cylinder Caterpillar C9.3B are carried out using CONVERGE. Prechamber equivalence ratio at spark timing, prechamber spark timing advance, and main chamber injection strategy are assessed with respect to their impact on ignition assistance performance and emissions characteristics relative to a diesel baseline at the same boundary conditions. Simulation results indicate that PC-MCC is flex-fuel capable and operates well for both E10 and E100 at the operating conditions considered. The results demonstrate that the use of a pilot-main injection strategy enables spark timing in the prechamber to be advanced and thus reduces spark plug firing pressure while maintaining robust ignition assistance. Results also indicate that the rich prechamber operation is favored for improved ignition assistance capabilities. Furthermore, the findings of this work suggest that a heavy-duty vehicle using a PC-MCC engine can utilize any blend of gasoline and ethanol, up to including pure ethanol, with no major sacrifices in performance relative to the diesel engine.
Range cost-effectiveness of plug-in electric vehicle for heterogeneous consumers: An expanded total ownership cost approach
Plug-in electric vehicles (PEV) appears to have sales momentum in major personal vehicle markets but are still at the early market stage. Opportunities to accelerate PEV adoption can be discovered through comprehensive total cost of ownership (TCO) analysis. Understanding the cost-effective electric ranges of PEVs for consumers, manufacturers, and the society is critical for any discussion of PEV mass markets. This study expanded the traditional TCO approach by (1) fully considering heterogeneous consumer driving patterns, (2) quantifying the charging inconvenience and range anxiety cost of battery-electric vehicles (BEVs), and (3) monetizing both tangible and intangible PEV policies. Uncertainties were handled through Monte Carlo simulation. The results suggest that BEVs with an electric range of 250–350 km have the lowest TCO in cities with government-enacted purchase limitations, and internal combustion engine vehicles (ICEVs) have the lowest TCO in cities without purchase limitations, even when considering PEV subsidies. The lowest TCO for some consumer groups is obtained by BEVs with an electric range of 400–450 km, especially in northern China, where the weather is colder. The cost-effective all-electric range for BEVs in each city in 2025 will decrease due to improved battery performance in cold environments and an expanded charging infrastructure. Finally, based on TCO, plug-in hybrid electric vehicles (PHEVs) are currently more suitable for drivers with a high average daily mileage or a large mileage variance. However, by 2025, BEVs with a long driving range may become a more cost-effective choice for these drivers.
EVI-Pro for Bogota Columbia [Slides]
The transportation sector is one of the largest producers of greenhouse gas emissions globally, with 37% of global CO 2 emissions in 2021 according to the International Energy Agency. Transitioning from internal combustion engine vehicles powered by fossil fuels to electrified transportation is a critical component in reducing those emissions significantly over the coming decades and avoiding the worst consequences of climate change. With governments and automakers increasingly announcing electrification targets and a progression away from the production and sale of internal combustion engine vehicles, a robust network of charging infrastructure must be built to enable the widespread use of electric vehicles (EVs). Some of the greatest hurdles to EV deployment are linked to the buildout of the required charging infrastructure including where it should be built, what types and how much charging would be optimal given high costs of installation, and the impact on the electrical grid. To this end, the National Renewable Energy Laboratory (NREL) conducts extensive research on EV deployment, including the development of the EVI-Pro model used to plan the future buildout of charging infrastructure given the travel patterns in a region. This document summarizes work done by NREL in the Bogotá, Colombia region to help Colombia plan for its EV deployment goals.
Environmental Protection Coating System for Refractory Metal Alloys (EPCS for RMAs)
As part of ARPA-E’s Ultra High Temperature Impervious Materials Advancing Turbine Efficiency (UITIMATE) program, this project aims to develop an environmental protection coating system (EPCS) for refractory metal alloys (RMAs) – which will provide radical improvement in long term protection for ultra-high temperature refractory metal components in harsh gas-turbine environments. The drive for higher fuel efficiency and higher core power of gas turbines used in electric power generation and in aircraft propulsion requires higher peak operation temperatures. The temperature capability of state-of-the-art materials cannot meet the new requirements. Refractory metal alloys have desirable capabilities for achieving the required peak temperatures, but most of them are subject to oxidation in the gas turbine environment. Thus, there is a strong need to develop novel environmental protective coatings that enable the refractory metals to operate in an ultra-high temperature engine environment. This project is composed of four major technical innovations that can provide a potentially transformational solution in providing environmental protection for refractory metal alloys over a wide range of temperature. 1) Multi-layer self-healing environmental barrier coating (EBC) that provides protection against combustion gas environment. 2) Oxidation resistant diffusion barrier (DB) on the alloy surface to enhance coating stability. 3) Synergistic integration of the multi-layer self-healing EBC with the diffusion barrier to extend coating life. 4) Guidance of physics-based modeling to accelerate coating development and optimization. Our team has successfully developed a multi-layer self-healing environmental protection coating system (EPCS) that can provide oxidation protection for commercially available molybdenum based refractory metal alloys over a wide temperature range of up to 1600 °C for fuel-efficient gas turbine applications. The team also developed a multi-layer high temperature coating design tool to accelerate coating development and optimization based on physics-based modeling. The team also engaged RTX business unite, notable Pratt and Whitney, for future commercialization of this technology. The successful completion of this Phase I effort led to the selection of performing Phase II of the program. In Phase II, the team plans to apply the EPCS in the protection of a newly discovered molybdenum-based metal alloy which has the potential of superior high temperature properties to the commercial products. Th coating will be evaluated under test conditions and environment that mimic gas turbine operation.
Optimal mass evacuation planning for electric vehicles before natural disasters
The electric vehicle (EV) market has significantly expanded because EVs have lower operational costs while leaving less environmental footprint than internal combustion engine vehicles. However, EVs also come with drawbacks, including long charging time and short operational ranges. With these drawbacks and limited charging facilities, efficient long-distance EV evacuation management is challenging and has not been properly addressed. Without an efficient evacuation plan, serious congestion could happen at charging facilities, the evacuation process would be excessively long, and thus human lives may be put at risk. This study is motivated to investigate the optimal mass evacuation planning for EVs considering limited charging facilities. A three-stage method is proposed to efficiently approach this problem. A case study of Florida hurricane evacuation is conducted. Here, the method's effectiveness is verified by comparing it with a benchmark. Management insights and policy indications are drawn through sensitivity analysis of key parameters.
Methods identifying cost reduction potential for water electrolysis systems
The electrochemical reduction of water to form hydrogen is an emerging alternative for energy storage, where hydrogen can be used as a transportation fuel, combusted to generate electricity, utilized in a fuel cell, or used as a feedstock for chemical synthesis. Techno-economic analysis (TEA) is a valuable tool for understanding how to inform research directions that could make hydrogen from electrolysis cost competitive with that produced by conventional means like steam methane reforming. The current state of knowledge on TEA of electrolysis systems suggests cost reductions are likely to result from advances in system design and materials, scale-up of manufacturing processes, and learning by doing effects as electrolysis deployment increases. Future directions and opportunities for TEA of electrolysis systems include dispatchable operation in wholesale power markets, optimization of capital cost and system durability, and analysis of pathways for hydrogen to support economy-wide decarbonization.
Numerical analysis of soot emissions from gasoline-ethanol and gasoline-butanol blends under gasoline compression ignition conditions
In the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine were performed to investigate the impact of blending two biofuels, ethanol and n-butanol, with gasoline on the trade-off between combustion phasing and soot emissions under low load conditions. Here, in order to represent market gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF) + ethanol (ETPRF) surrogate (with 20% ethanol by mole; E20) was formulated using a neural network based octane predictor such that the surrogate had the same ethanol content, Research Octane Number (RON) and Octane Sensitivity (S). In addition, a novel skeletal kinetic mechanism for ETPRF and TPRF + n-butanol (BTPRF) blends, incorporating polycyclic aromatic hydrocarbon (PAH) chemistry, was developed. A three-dimensional (3D) engine CFD formulation employing the skeletal mechanism, adaptive mesh refinement (AMR), finite-rate chemistry approach, and hybrid method of moments (HMOM) was adopted to capture the in-cylinder combustion phenomena and soot emissions. The engine CFD model was validated against RD5-87 experimental data for a broad range of start-of-injection (SOI) timings (-21/-27/-36/-45 crank angle degrees (CAD) after top-dead center (aTDC)), with respect to in-cylinder pressure, heat release rate, combustion phasing, and soot emissions. The closed-cycle simulation results were analyzed to elucidate the non-monotonic trend of soot emissions versus SOI timing: SOI-36 > SOI-45 > SOI-21 > SOI-27. Thereafter, the validated CFD model was employed to simulate the combustion of a gasoline-ethanol blend with 45% (by mole) ethanol (E45) and a gasoline-butanol blend with 45% (by mole) n-butanol (B45) under the same operating conditions to study the effects of fuel composition and SOI timing on combustion phasing and soot emissions. The sooting propensity followed the trend: B45 > E20 > E45 at all SOI timings. Overall, it was observed that the autoignition propensity was primarily related to fuel chemistry. On the other hand, sooting propensity showed strong coupling with both fuel chemistry and physical properties, with greater impact of fuel physical properties at advanced SOI timings.
Co-Design of a Fully Electric Hybrid Hydraulic-Electric Architecture (FE-HHEA) for Off-Road Mobile Machines
Off-road mobile machines, such as excavators and wheel-loaders, are typically actuated by hydraulics using internal combustion engines as their power sources. There is a trend towards fully electrifying these machines and improving their efficiencies due to environmental regulations and concerns. In this paper, a control co-design methodology is used to design a Fully Electrified Hybrid Hydraulic-Electric Architecture (FE-HHEA) for an excavator that drastically reduces energy consumption and minimizes the sizes of costly electric components. By optimizing both control operation and the physical design, the co-design methodology takes into account the interaction between these two aspects. The design methodology also illustrates how the system architecture evolves from the previously developed IC engine powered HHEA with the engine replaced by an electric motor to a seemingly very different architecture with fewer components. The optimized system reduces energy consumption by 71% over the baseline system and uses electrical components that are 1/3 the size of an alternate fully electric architecture.
Direct Numerical Simulation of Partial Fuel Stratification Assisted Lean Premixed Combustion for Assessment of Hybrid G-Equation/Well-Stirred Reactor Model
Partial fuel stratification (PFS) is a promising fuel injection strategy to stabilize lean premixed combustion in spark-ignition (SI) engines. PFS creates a locally stratified mixture by injecting a fraction of the fuel, just before spark timing, into the engine cylinder containing homogeneous lean fuel/air mixture. Further, this locally stratified mixture, when ignited, results in complex flame structure and propagation modes similar to partially premixed flames and allows for faster and more stable flame propagation than a homogeneous lean mixture. This study focuses on understanding the detailed flame structures associated with PFS-assisted lean premixed combustion. First, a two-dimensional direct numerical simulation (DNS) is performed using detailed fuel chemistry, experimental pressure trace, and realistic initial conditions mapped from a prior engine large-eddy simulation (LES), replicating practical lean SI operating conditions. DNS results suggest that the conventional triple flame structure is prevalent during the initial stage of flame kernel growth. Both premixed and nonpremixed combustion modes are present with the premixed mode contributing dominantly to the total heat release. Detailed analysis further reveals the effects of flame stretch and fuel pyrolysis on flame displacement speed. Based on the DNS findings, the accuracy of a hybrid G-equation/well-stirred reactor (WSR) combustion model is assessed for the PFS-assisted lean operation in the LES context. It is found that the G-equation model qualitatively captures the premixed branches of the triple flame, while the WSR model predicts the nonpremixed branch of the triple flame. Finally, potential needs for improvements to the hybrid G-equation/WSR modeling approach are discussed.
Cradle-to-grave mercury emissions of light-duty gasoline and electric vehicles in China
China is actively promoting vehicle electrification, which is deemed to help achieve its ambitious carbon neutrality goal by 2060. Here we show that vehicle electrification in China leads to an increase in automotive emissions of mercury, a persistent, global hazardous pollutant regulated in the United Nations’ Minamata Convention. We found that with current technologies, life-cycle mercury emissions of battery electric vehicles of 300 miles of all-electric range are 92% higher than conventional gasoline internal combustion engine vehicles, primarily due to the high mercury emissions from coal-based electricity generation. Notably different from greenhouse gases, mercury emissions are mainly embedded in vehicular material production and vehicle manufacturing, accounting for 50–60% for electric vehicles and ~90% for gasoline vehicles of their life-cycle mercury emissions. Even with a deeply decarbonized power grid, mercury footprints of electric vehicles would still be higher than those of gasoline vehicles, implying a potential increase in automotive mercury emissions in any countries that promote vehicle electrification. Measures including decarbonizing electric grid, implementing mercury-specific emission control through vehicle supply chain, and increasing metal recycling in electric vehicle batteries will help mitigate the unintended mercury emission increase caused by vehicle electrification.
High Temperature Additive Architectures for 65% Efficiency (Final Technical Report)
This project aimed to develop advanced high-temperature additive components that contribute towards the DOE’s goal for advanced gas turbines that are capable of at least 65% efficiency in combined cycle application. The objective was to leverage state-of-the-art additive manufacturing to develop an innovative stage 1 turbine nozzle (S1N) that can provide cooling flow savings while maintaining the component durability expected in today’s gas turbines. The program had two phases. Phase I was a conceptual phase for novel advanced cooling designs enabled by additive manufacturing, as well as proposals for validation. Phase II included execution of the Phase I conceptual design, including manufacturing of prototype hardware and validation within an environment that is similar to engine operation. During Phase I of the program, the team devised a concept to reduce cooling air usage. The cooling air used in the side walls is filmed out along the side walls, while the cooling air used in the airfoil is eventually directed to near-wall channels and exits holes along the airfoil trailing end. During this program, the team performed additive trials to analyze the geometric limitations of additive manufacturing. This helped the team understand minimum wall thicknesses, hole sizes, and cooling channel dimensions among other limits. Phase II of this program pushed GE Vernova beyond its previous experience of designing and manufacturing an additively manufactured hot gas path component. Modern hot gas path components utilize material chemistries that are traditionally hard to weld, such as cast Renè 108, and exhibit solidification cracking when additively manufactured using Direct Metal Laser Melting (DMLM). Note that AM108 is a powder form of Renè 108. A S1N with advanced cooling is larger and more complex than parts previously built by additive manufacturing and required new learnings to resolve risks around solidification cracking. Finally, the team validated the design in a combustion rig that replicated operation in a gas turbine. In order to properly quantify the benefits of the new additive design, a baseline was also tested in the rig and operated under the same conditions. In addition, an uncertainty analysis was done to quantify any sources of error that could impact the results. At the end of the validation effort, it was determined that the additive nozzle exceeded the 15% reduction in cooling flow goal even with the worst-case assumptions for uncertainty.
Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)
Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.