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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Comparative Study for Pressure Gain Combustion-Gas Turbine System Performance in NGCC Configurations

The Department of Energy (DOE) has a goal to increase natural gas combined cycle (NGCC) plant efficiency to greater than 70 percent on a lower heating value (LHV) basis. Improvement in gas turbine (GT) efficiency is key achieving this goal. While many of the traditional improvement methods (higher firing temperature, advanced materials, improved cooling methods, etc.) may increase current GT and NGCC efficiencies incrementally, combining these traditional advancements with breakthrough technologies such as pressure gain combustion (PGC) may provide significant system efficiency gains. PGC is a combustion process that results in a net pressure increase across the combustor (up to pressure ratio of 2.2) rather than the traditional (<5%) pressure drop. There are multiple PGC technologies being developed that create the pressure rise phenomena, including resonant pulse combustors (RPCs), pulse detonation engines (PDEs), wave rotor combustor (WRC) engines and rotating detonation engines (RDEs). In this study, scoping analyses of PGC concepts applied to NGCC power plants were performed by combining simplified analytical models for the RPC, PDE, WRC, and RDE types of pressure gain processes with a GT model to evaluate impacts of using each of the PGC technologies on key GT performance parameters. Sensitivity analyses were also performed. Ultimately, the PGC technologies were found to have the potential to increase simple cycle efficiency by 4–6 percent (absolute) and NGCC efficiency by 2–3 percent (absolute) based on the results of the current study.

03 NATURAL GAS↗
DOE OSTI2022

Hydration of alumina (Al 2 O 3 ) toward advancing aluminum particles for energy generation applications

Transforming metal particle combustion may require alteration of the metal oxide passivation shell surrounding the metal core. One approach for aluminum (Al) relies on the hydrated form of the metal oxide to incite surface reactions. Here, this study explores the conditions required for hydrating alumina (Al 2 O 3 ) particles and then extends those conditions toward hydration of the Al 2 O 3 passivation layer surrounding an Al core particle. By raising the pH of the water slurry to 11 and controlling temperature and time in slurry (i.e., aging), aluminum hydroxide Al(OH) 3 formation from Al 2 O 3 particles was optimized. The procedure was then extended to Al nanoparticles (nAl). Even though heating and extended aging time in slurry proved advantageous for Al 2 O 3 particles, these conditions were discarded for nAl particles because they favored formation of AlOOH, a less desirable hydrate. Through microscopy, spectroscopy, X-ray diffraction, and thermal analyses, results indicate that for a pH range of 11.26–11.56, the original Al 2 O 3 shell on Al particles transformed into Al(OH) 3 . Results indicate a feasible path forward towards producing new shell chemistries that may result in more directed energy from metal particle combustion.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Improved Chemical Kinetics and Algorithms for More Accurate, Faster Simulations

Internal combustion engine design is increasingly driven by computational models used to predict change in performance due to change of design. The design process previously depended on limited intuition and expensive and time-consuming physical testing. Improved model capabilities shorten design cycles and enable the production of cleaner and more efficient engines. This project focuses on advancing the state of the art in internal combustion engine simulations. The overarching goal is to enable predictive models and reduced time to solution for simulations that impact combustion engine design.

02 PETROLEUM↗
DOE OSTI2021

Advances in imaging of chemically reacting flows

Many important chemically reacting systems are inherently multi-dimensional with spatial and temporal variations in the thermochemical state, which can be strongly coupled to interactions with transport processes. Fundamental insights into these systems require multi-dimensional measurements of the thermochemical state as well as fluid dynamics quantities. Laser-based imaging diagnostics provide spatially and temporally resolved measurements that help address this need. The state of the art in imaging diagnostics is continually progressing with the goal of attaining simultaneous multi-parameter measurements that capture transient processes, particularly those that lead to stochastic events, such as localized extinction in turbulent combustion. Development efforts in imaging diagnostics benefit from advances in laser and detector technology. This article provides a perspective on the progression of increasing dimensionality of laser-based imaging diagnostics and highlights the evolution from single-point measurements to 1D and 2D multi-parameter imaging and 3D high-speed imaging. This evolution is demonstrated using highlights of laser-based imaging techniques in combustion science research as an exemplar of a complex multi-dimensional chemically reacting system with chemistry–transport coupling. Imaging diagnostics impact basic research in other chemically reacting systems as well, such as measurements of near-surface gases in heterogeneous catalysis. The expanding dimensionality of imaging diagnostics leads to larger and more complex datasets that require increasingly demanding approaches to data analysis and provide opportunities for increased collaboration between experimental and computational researchers in tackling these challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Soot Formation and Ignition Characteristics of Ethanol/Gasoline Blends in a Rapid Compression Machine

With the ever-increasing demand for sustainable energy, alcohol fuels have garnered interest for use in heavy duty engines. The significant infrastructure for ethanol production and blending of ethanol with gasoline make these fuels/fuel blends desirable candidates. However, development of heavy duty engine technology that is capable of burning alcohol fuels while retaining the advantages of traditional diesel combustion requires an improved understanding of the soot formation for these fuels under conditions relevant to mixing-controlled combustion. This work uses an extinction diagnostic to study the sooting tendency of ethanol and gasoline/ethanol blends ranging from E10 to E98 during ignition in a homogeneous environment. Experiments were conducted in a rapid compression machine (RCM) for compressed conditions of 20 ± 1 bar and an approximately constant temperature (± 10K) which was unique for each fuel. For a given soot volume fraction, a linear relationship was observed between ethanol content and the equivalence ratio in which that soot volume fraction was formed. Accounting for the oxygenated nature of ethanol, E85 and E98 fuels produced similar amounts of soot at a given Φ ox, , suggesting other factors outside of fuel oxygen content, such as fuel morphology, impact soot formation. Ignition delay data is reported for compressed pressures of 20 ± 1 bar and compressed temperatures ranging from 633 – 670 K for E10 and 771 – 789 K for E98. Varying pressures for E10 and E98 at conditions producing similar soot volume fractions demonstrated a linear dependence of soot formation on pressure, regardless of if the pressure considered was at top dead center or peak combustion pressure. Furthermore, the data gleaned from this work will be used to select soot models and chemical kinetic mechanisms for RCM simulations to ultimately model heavy duty engine technology with the studied fuels.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Advanced Cost-Effective Coal-Fired Rotating Detonation Combustor for High Efficiency Power Generation

Coal-based detonation as a means of heat addition in power generation devices is a revolutionary “out of the box” technology concept, wherein it is theoretically possible to achieve an increase in total pressure across the combustor as opposed to a loss of available energy as is the case in conventional combustion systems. Detonation is a revolutionary technology concept of pressure gain combustion that exploits pressure rise from the combustion process to augment high flow momentum and pressures. Recognizing that pressure gain combustion has become a topic of elevated national interest, high energetic modes (exergy) pressure gain combustion (PGC) systems are required. Pressure gain combustion is a key enabling technology for maintaining technological superiority in the development of advanced power generation systems. Pressure gain combustion is an innovative scheme of turbulent combustion that considerably increases thermodynamic cycle efficiencies (~10-20%). This project extends the State-of-the-Art by providing the first direct experimental and computational data of operability dynamics and performance characterization data and create the first validated Coal-Fired RDC investigations. Coal-based RDC is an innovative revolutionary technology that would result in high efficiency power generation and reduced of harmful emissions. Also, the fundamental and open source nature of the project will benefit a broader scientific and industry audience who will be able to utilize the outcomes of this project for advancing the coal-fired RDC power generation development.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Techno-Economic Impact Assessments of Energy Efficiency Improvements in the Industrial Combustion Systems

Industrial energy efficiency assessments not only provide benefits to manufacturers but also generate significant economic and environmental benefits to localities, states, and the nation through indirect and induced benefits. Quantifying these benefits requires a systematic economic framework for capturing these interactions. This article employs methodologies for improving the energy efficiency of small- and medium-sized industry through their combustion systems. Combustion systems offer large opportunities to enhance energy efficiency through adopting advanced technologies and better-informed operations. The case studies presented illuminate the potential savings and impacts from implementing energy-efficient combustion recommendations and the importance of energy audits and energy efficiency in the fight against climate change. This study describes and quantifies the cascading economic and environmental impacts of implementing the industrial energy efficiency recommendations offered by an energy auditing program by participating facilities over a 10-year period. Results showed that it is expected that a total of $185 M would be saved in energy costs, and 2.3 million metric tons of carbon dioxide emissions would be avoided annually, and about 972 jobs could be created in the studied region if all the combustion recommendations would be implemented. Furthermore, the broader view afforded by the proposed study can be used to support better energy-efficient practices in manufacturing facilities, communities, and states.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

High BMEP and High Efficiency Micro-Pilot Ignition Natural Gas Engine (Final Project Report)

The project objectives were to develop demonstrate a high-efficiency high-output natural gas diesel micro-pilot stoichiometric engine operating with diesel pilot contribution of less than 5% on a medium duty engine. The program’s outcomes achieve in a partnership between Michigan Technological University and Westport Power Inc. were very successful. The engine platform was a 6.7L I6 engine with a compression ratio of 15:1 and achieved 24 bar BMEP and 41% brake thermal efficiency at lambda. Simulation and modeling with an improved turbocharger and combustion chamber improvements demonstrated a clear path to 43% BTE. The operational stoichiometric range was from 5 to 24 bar with minimal throttling. Diesel contribution over the cycle was 4.6%. The results achieved in this program are well above the best in-class baseline natural gas spark ignition engines of 19.5 bar BMEP and 40% BTE.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Influence of functional groups on low-temperature combustion chemistry of biofuels

Ongoing progress in synthetic biology, metabolic engineering, and catalysis continues to produce a diverse array of advanced biofuels with complex molecular structure and functional groups. In order to integrate biofuels into existing combustion systems, and to optimize the design of next-generation combustion systems, understanding connections between molecular structure and ignition at low-temperature conditions (< 1000 K) remains a priority that is addressed in part using chemical kinetics modeling. The development of predictive models relies on detailed information, derived from experimental and theoretical studies, on molecular structure and chemical reactivity, both of which influence the balance of chain reactions that occur during combustion – propagation, termination, and branching. In broad context, three main categories of reactions affect ignition behavior: (i) initiation reactions that generate a distribution of organic radicals, ; (ii) competing unimolecular decomposition of and bimolecular reaction of with O2; (iii) decomposition mechanisms of peroxy radical adducts (RO), including isomerization via RO ⇌ OOH. Furthermore, all three categories are influenced by functional groups in different ways, which causes a shift in the balance of chain reactions that unfold over complex temperature- and pressure-dependent mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

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↗
DOE OSTI2022

Grand challenges in low temperature plasmas

Low temperature plasmas (LTPs) enable to create a highly reactive environment at near ambient temperatures due to the energetic electrons with typical kinetic energies in the range of 1 to 10 eV (1 eV = 11600K), which are being used in applications ranging from plasma etching of electronic chips and additive manufacturing to plasma-assisted combustion. LTPs are at the core of many advanced technologies. Without LTPs, many of the conveniences of modern society would simply not exist. New applications of LTPs are continuously being proposed. Researchers are facing many grand challenges before these new applications can be translated to practice. In this paper, we will discuss the challenges being faced in the field of LTPs, in particular for atmospheric pressure plasmas, with a focus on health, energy and sustainability.

atmospheric pressure plasmas↗
DOE OSTI2023

Plasma-based global pathway analysis to understand the chemical kinetics of plasma-assisted combustion and fuel reforming

The Global Pathway Analysis (GPA) algorithm helps analyze the chemical kinetics of complex combustion systems by identifying important global reaction pathways connecting a source species to a sink species through various important intermediate species (i.e., hub species). Here, the present work aims to extend GPA algorithm to plasma-assisted combustion and fuel reforming systems to identify the dominant global pathways in such systems at various conditions. In addition, the present study extends the ability of GPA algorithm to identify reaction cycles involving the excitation of high-concentration species (e.g., O 2 , N 2 , and fuel) to their vibrational and electronic states and the subsequent de excitation to their ground state, based on their significance on the reactivity of plasma-assisted systems in terms of gas heating and radical production. Provisions are made in the GPA algorithm to evaluate the reactivity of identified re action pathways and cycles based on the element-flux transfer (i.e., dominance), heat release, and radical production rate. The newly developed Plasma-based Global Pathway Analysis (PGPA) algorithm is then used to analyze the plasma assisted combustion of ammonia and reforming of methane. The PGPA analyses elucidated the significance of vibrational-translational cycles on the reactivity of NH 3 /air mixtures. Further, analyses on the production of NO ascribed the early reforming of NH 3 to N 2 and H 2 in impeding the production of NO during plasma-assisted NH 3 ignition. Lastly, the enhanced reforming of CH 4 /N 2 mixtures using plasma has been attributed to electron impact dissociation of CH 4 when compared to thermal reforming. In contrast, conventional path-Flux analysis (PFA) was found to require significant manual effort and pre-analysis intuitions from expert knowledge, making it arduous to provide valuable in sights into plasma chemistry. The user-friendly and automated nature of PGPA thus provides a valuable tool for assessing the kinetics of plasma-assisted systems helpful in analyzing and, further, a foundation in reducing plasma-assisted chemistry, without the needs of expert knowledge.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

AOI [1] Advanced Manufacturing of Ceramic Anchors with Embedded Sensors for Process and Health Monitoring of Coal Boilers

Researchers at West Virginia University (WVU) developed methods to fabricate and test ceramic anchors with an embedded sensor technology for monitoring the health and processing conditions within pulverized coal (PC) and fluidized-bed combustion (FBC) boiler systems. The technology included the development of advanced manufacturing processes for 2D/3D printing electroceramic (conductive ceramic) sensor designs within the ceramic anchor microstructure during the manufacturing process. This advanced manufacturing process would allow for the precise control of local microstructure and composition in order to engineer layer-by-layer any protective and electrically active materials within the refractory anchor. This 3D printing technology would permit the rapid and controlled design of the refractory microstructure and embedded sensor design throughout the volume of the ceramic anchor. The work also included a method to interconnect the sensors to boiler shell through the anchor clamp, where the sensor signals will be processed by low-power electronics and transmitted wirelessly to a central processing hub. The end-goal of the program was to produce a ceramic anchor sensor system which would be ready for implementation within a coal boiler, and/or other similar refractory liner systems (such as that in the glass and metal manufacturing areas). The project objectives were to: 1) Define the chemical and microstructural stability, in addition to the electrical properties, of oxide and non-oxide ceramic composites to be embedded within the ceramic anchor compositions that may operate up to 1400ºC; 2) Develop and implement the 2D/3D printing technology to pattern and control the microstructure of the ceramic anchor and embedded sensor circuits; 3) Develop an interconnect technology which will permit easy installation of the ceramic anchors and signal collection at the boiler shell; 4) Develop low power analog electronics and wireless communication hardware to efficiently collect the sensor signal at each processing unit and transmit data to a central hub for data analysis; 5) Demonstrate the smart ceramic anchor system for temperature and liner fracture within a high-temperature processing unit, such as a boiler furnace or glass melting furnace floor/wall liner.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Improved Chemical Kinetics and Algorithms for More Accurate, Faster Simulations

Internal combustion engine design is increasingly driven by computational models used to predict change in performance as a result of design changes, which previously would have been made by limited intuition or expensive and time-consuming physical testing. Improved model capabilities shorten design cycles and enable the production of cleaner and more efficient engines. This project focuses on advancing the state-of-the-art in internal combustion engine simulations. The overarching goal is to enable predictive models and reduced time to solution for simulations that impact combustion engine design.

02 PETROLEUM↗
DOE OSTI2020

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. Here, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

CRN Modeling of Ammonia RQL Combustion using a Partially-Stirred Reactor Approach

Ammonia is a promising alternative to hydrogen with high energy density and favorable storage and transport characteristics. However low flammability and a propensity for high nitrogen oxide (NOx) emissions make direct utilization challenging. Recently, two-stage rich-quench-lean (RQL) combustion strategies have shown promise in achieving low NOx emissions with ammonia. In this approach, the rich stage serves to oxidize a portion of the fuel, while thermally decomposing as much of the remaining ammonia as possible, generating hydrogen. In the second (lean) stage, air is rapidly introduced, burning out the hydrogen and residual ammonia. Two-stage RQL combustion of ammonia has been investigated in the open literature both experimentally and numerically. In general, idealized chemical reactor network (CRN) models predict NOx concentrations below that of 2D/3D computational fluid dynamics models and experiments. The primary drivers of these discrepancies may be largely attributed to finite rate mixing non-adiabatic operation. The typical CRN model is comprised of a perfectly-stirred-reactor (PSR), followed by a plug-flow-reactor (PFR), meant to represent the flame, and post-flame zones, respectively. In the two-stage RQL approach two PSR-PFR networks are arranged sequentially, corresponding to the rich and lean stages, with secondary air injection in between. In the authors’ past work, this arrangement has demonstrated the significant sensitivity of exit NOx to the rich stage equivalence ratio, while the amount of secondary air injection was shown to be less critical. In this paper, the CRN model is extended to (1) include the impacts of heat loss and (2) utilize a partially-stirred-reactor (PaSR) approach to study the impacts of mixing on emissions performance. Varying amounts of heat loss are applied to the rich relaxation zone to understand emissions performance and changes to optimization of equivalence ratio and residence time. Premixed and non-premixed configurations are considered in the rich stage PaSR, with varying degrees of mixing intensity to study the interaction between mixing, transport, and kinetic timescales. Critically, the impact of mixing between hot products and secondary air injection is studied to understand practical injector needs. Results show unburnt ammonia leaving the rich stage as a primary contributor to NOx emissions – driven both by increased heat loss and reduced mixing rates. Furthermore, heat losses have shown to create conditions which are conducive to increased N2O formation in the lean stage. The results of this study will be considered in the context of developing optimized two-stage RQL combustors for ammonia..

advanced gas turbines↗
DOE OSTI2025

Predicting Fuel Properties and Emissions for Advanced Biofuels for Diesel Engines (CRADA Final Report)

The project will investigate variations in biofuel composition and optimize performance in combustion for conventional and future compression ignition engines. It will evaluate a variety of bio-derived molecules in the diesel range that can be produced using technology in ExxonMobil’s portfolio as well as fuels that cover the range of potential molecular structures for robust model development. Changes in fuel/air premixing and stratification in advanced engines could alter the relationship between fuel properties and performance in comparison to current generation spray combustion approaches. NREL experience in fuel and combustion modeling will enable development of general rules for predicting performance of a wide range of biofuel options.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Accelerating Innovative Energy Solutions Using Combustion Simulations

Combustion-based transportation, electricity generation, and industrial heating in manufacturing constitute the three largest sectors of energy demand. Some of the recent technology development in these sectors are: switching to low-carbon fuels for the transportation sector, increasing energy efficiency in the power sector, and capturing carbon emissions from conventional power generators. Several teams at the National Renewable Energy Laboratory have been actively advancing research in these areas by leveraging computational modeling of combustion processes across the heavy-duty land based transportation, aviation, and power generation sectors. This article summarizes some of these efforts, demonstrating the potential of advanced computational techniques to generate technological solutions that will transform the global energy system.

08 HYDROGEN↗