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At least 325 records · Page 18

Hydrogen turbine power conversion system assessment

A three part technical study was conducted whereby parametric technical and economic feasibility data were developed on several power conversion systems suitable for the generation of central station electric power through the combustion of hydrogen and the use of the resulting heat energy in turbogenerator equipment. The study assessed potential applications of hydrogen-fueled power conversion systems and identified the three most promising candidates: (1) Ericsson Cycle, (2) gas turbine, and (3) direct steam injection system for fossil fuel as well as nuclear powerplants. A technical and economic evaluation was performed on the three systems from which the direct injection system (fossil fuel only) was selected for a preliminary conceptual design of an integrated hydrogen-fired power conversion system.

Wright, D. E.↗

Engine System Loads Analysis Compared to Hot-Fire Data

Early implementation of structural dynamics finite element analyses for calculation of design loads is considered common design practice for high volume manufacturing industries such as automotive and aeronautical industries. However with the rarity of rocket engine development programs starts, these tools are relatively new to the design of rocket engines. In the NASA MC-1 engine program, the focus was to reduce the cost-to-weight ratio. The techniques for structural dynamics analysis practices, were tailored in this program to meet both production and structural design goals. Perturbation of rocket engine design parameters resulted in a number of MC-1 load cycles necessary to characterize the impact due to mass and stiffness changes. Evolution of loads and load extraction methodologies, parametric considerations and a discussion of load path sensitivities are important during the design and integration of a new engine system. During the final stages of development, it is important to verify the results of an engine system model to determine the validity of the results. During the final stages of the MC-1 program, hot-fire test results were obtained and compared to the structural design loads calculated by the engine system model. These comparisons are presented in this paper.

Frady, Gregory P.↗

Diffusion Flame Stabilization

Diffusion flames are commonly used for industrial burners in furnaces and flares. Oxygen/fuel burners are usually diffusion burners, primarily for safety reasons, to prevent flashback and explosion in a potentially dangerous system. Furthermore, in most fires, condensed materials pyrolyze, vaporize, and burn in air as diffusion flames. As a result of the interaction of a diffusion flame with burner or condensed-fuel surfaces, a quenched space is formed, thus leaving a diffusion flame edge, which plays an important role in flame holding in combustion systems and fire spread through condensed fuels. Despite a long history of jet diffusion flame studies, lifting/blowoff mechanisms have not yet been fully understood, compared to those of premixed flames. In this study, the structure and stability of diffusion flames of gaseous hydrocarbon fuels in coflowing air at normal earth gravity have been investigated experimentally and computationally. Measurements of the critical mean jet velocity (U(sub jc)) of methane, ethane, or propane at lifting or blowoff were made as a function of the coflowing air velocity (U(sub a)) using a tube burner (i.d.: 2.87 mm) (Fig. 1, left). By using a computational fluid dynamics code with 33 species and 112 elementary reaction steps, the internal chemical-kinetic structures of the stabilizing region of methane and propane flames were investigated (Fig. 1, right). A peak reactivity spot, i.e., reaction kernel, is formed in the flame stabilizing region due to back-diffusion of heat and radical species against an oxygen-rich incoming flow, thus holding the trailing diffusion flame. The simulated flame base moved downstream under flow conditions close to the measured stability limit.

Takahashi, Fumiaki↗

Diffusion Flame Stabilization

Diffusion flames are commonly used for industrial burners in furnaces and flares. Oxygen/fuel burners are usually diffusion burners, primarily for safety reasons, to prevent flashback and explosion in a potentially dangerous system. Furthermore, in most fires, condensed materials pyrolyze, vaporize, and burn in air as diffusion flames. As a result of the interaction of a diffusion flame with burner or condensed-fuel surfaces, a quenched space is formed, thus leaving a diffusion flame edge, which plays an important role in flame holding in combustion systems and fire spread through condensed fuels. Despite a long history of jet diffusion flame studies, lifting/blowoff mechanisms have not yet been fully understood, compared to those of premixed flames. In this study, the structure and stability of diffusion flames of gaseous hydrocarbon fuels in coflowing air at normal earth gravity have been investigated experimentally and computationally. Measurements of the critical mean jet velocity (U(sub jc)) of methane, ethane, or propane at lifting or blowoff were made as a function of the coflowing air velocity (U(sub a)) using a tube burner (i.d.: 2.87 mm). By using a computational fluid dynamics code with 33 species and 112 elementary reaction steps, the internal chemical-kinetic structures of the stabilizing region of methane and propane flames were investigated. A peak reactivity spot, i.e., reaction kernel, is formed in the flame stabilizing region due to back-diffusion of heat and radical species against an oxygen-rich incoming flow, thus holding the trailing diffusion flame. The simulated flame base moved downstream under flow conditions close to the measured stability limit.

Takahashi, Fumiaki↗

Bridging the Energy Future: The Role and Potential of Hydrogen Co-Firing with Natural Gas

In the transition toward sustainable energy systems, the co-firing of hydrogen (H2) with natural gas emerges as a critical technology for cleaner power generation. This study examines its benefits, including emissions reduction, enhanced efficiency, and compatibility with existing infrastructure. Concurrently, it addresses the inherent challenges, such as combustion dynamics, necessary infrastructure modifications, and economic considerations. Incorporating global case studies, the review explores recent advancements in hydrogen production and co-firing, evaluating their practicality and operational efficiency. It also provides a critical examination of the economic implications and societal acceptance, which are crucial for the adoption of hydrogen technologies. Moreover, the review investigates the synergy between hydrogen and renewable energy technologies, assessing potential impacts on energy policy and regulation. Ultimately, this comprehensive analysis underscores the essential role of hydrogen co-firing in the energy sector and advocates for a comprehensive strategy that synergizes technological progress, economic viability, regulatory support, and public engagement to promote a resilient and sustainable energy future.

hydrogen co-firing↗

Energy Conversion Alternatives Study (ECAS)

ECAS compared various advanced energy conversion systems that can use coal or coal-derived fuels for baseload electric power generation. It was conducted in two phases. Phase 1 consisted of parametric studies. From these results, 11 concepts were selected for further study in Phase 2. For each of the Phase 2 systems and a common set of ground rules, performance, cost, environmental intrusion, and natural resource requirements were estimated. In addition, the contractors defined the state of the associated technology, identified the advances required, prepared preliminary research and development plans, and assessed other factors that would affect the implementation of each type of powerplant. The systems studied in Phase 2 include steam systems with atmospheric- and pressurized-fluidized-bed boilers; combined cycle gas turbine/steam systems with integrated gasifiers or fired by a semiclean, coal derived fuel; a potassium/steam system with a pressurized-fluidized-bed boiler; a closed-cycle gas turbine/organic system with a high-temperature, atmospheric-fluidized-bed furnace; a direct-coal-fired, open- cycle magnetohydrodynamic/steam system; and a molten-carbonate fuel cell/steam system with an integrated gasifier. The sensitivity of the results to changes in the ground rules and the impact of uncertainties in capital cost estimates were also examined.

Source record↗

Deep Analysis Net with Causal Embedding for Coal-fired Power Plant Fault Detection and Diagnosis (DANCE4CFDD)

Fault detection and diagnosis is critical to power plant operation to ensure attaining high reliability while reducing operation cost. As more renewable power is introduced to the power grid, traditional fossil power plants take on the extra burden of excessive load cycling to compensate the generation variability from renewable power. Such load cycling will pose more reliability challenges to power plant operation. There are a number of challenges faced by today’s asset health management system in coal- fired (or gas) power plants: 1) high-dimensional nonlinear interaction among multiple time series measurements; 2) high measurement variance induced by operational conditions/modes; 3) variation among asset types and plant configurations; and 4) a small number of faulty events to learn from. To cope with these challenges, today’s fielded asset health management systems rely heavily on manual efforts from domain experts and hand-crafted features or rules based on domain knowledge. Despite its role in plant reliability, such a practice is costly and hinders its scalability and sustainability, particularly when a plant undergoes modifications. The objective of this project is to develop a novel end-to-end AI learning system that is trainable (i.e., the AI representation of a complex system behavior can be directly learned from properly labeled data) for accurate fault detection and root cause analysis. The ability to create a fault detection model directly from time series could alleviate the efforts associated with today’s asset management solution development. In the course of this project, we have achieved the following: Created an AI model development environment incorporating state-of-the-art neural network architectures for rapid model development and evaluation; Developed novel learning strategies for training of fault detection model; Developed special-purpose neural network architecture embedded with variable association graph aiming for better interpretability; Developed a learning strategy to leverage a small number of faulty events for enhanced fault detection capability; Conducted detailed experimental study based on public benchmark datasets and demonstrated the effectiveness of the proposed solution; and Validated the developed system with data from both a coal-fired plant boiler dynamic simulation model and real-world coal-fired power plant covering multiple asset and fault types. Overall, the project attained a technology readiness level of TRL 5 from TRL 2 at the beginning of the project.

20 FOSSIL-FUELED POWER PLANTS↗

Reviews and syntheses: Arctic fire regimes and emissions in the 21st century

In recent years, the pan-Arctic region has experienced increasingly extreme fire seasons. Fires in the northern high latitudes are driven by current and future climate change, lightning, fuel conditions, and human activity. In this context, conceptualizing and parameterizing current and future Arctic fire regimes will be important for fire and land management as well as understanding current and predicting future fire emissions. The objectives of this review were driven by policy questions identified by the Arctic Monitoring and Assessment Programme (AMAP) Working Group and posed to its Expert Group on Short-Lived Climate Forcers. This review synthesizes current understanding of the changing Arctic and boreal fire regimes, particularly as fire activity and its response to future climate change in the pan-Arctic have consequences for Arctic Council states aiming to mitigate and adapt to climate change in the north. The conclusions from our synthesis are the following. (1) Current and future Arctic fires, and the adjacent boreal region, are driven by natural (i.e. lightning) and human-caused ignition sources, including fires caused by timber and energy extraction, prescribed burning for landscape management, and tourism activities. Little is published in the scientific literature about cultural burning by Indigenous populations across the pan-Arctic, and questions remain on the source of ignitions above 70_ N in Arctic Russia. (2) Climate change is expected to make Arctic fires more likely by increasing the likelihood of extreme fire weather, increased lightning activity, and drier vegetative and ground fuel conditions. (3) To some extent, shifting agricultural land use and forest transitions from forest–steppe to steppe, tundra to taiga, and coniferous to deciduous in a warmer climate may increase and decrease open biomass burning, depending on land use in addition to climate-driven biome shifts. However, at the country and landscape scales, these relationships are not well established. (4) Current black carbon and PM2:5 emissions from wildfires above 50 and 65_ N are larger than emissions from heanthropogenic sectors of residential combustion, transportation, and flaring. Wildfire emissions have increased from 2010 to 2020, particularly above 60_ N, with 56% of black carbon emissions above 65_ N in 2020 attributed to open biomass burning – indicating how extreme the 2020 wildfire season was and how severe future Arctic wildfire seasons can potentially be. (5) What works in the boreal zones to prevent and fight wildfires may not work in the Arctic. Fire management will need to adapt to a changing climate, economic development, the Indigenous and local communities, and fragile northern ecosystems, including permafrost and peatlands. (6) Factors contributing to the uncertainty of predicting and quantifying future Arctic fire regimes include underestimation of Arctic fires by satellite systems, lack of agreement between Earth observations and official statistics, and still needed refinements of location, conditions, and previous fire return intervals on peat and permafrost landscapes. This review highlights that much research is needed in order to understand the local and regional impacts of the changing Arctic fire regime on emissions and the global climate, ecosystems, and pan-Arctic communities.

Arctic↗

Screenable all-metal solar cell electrodes of nickel and copper

Screenable thick film solar cell electrodes are made using the all-metal electrode system, which eliminates the commonly used glass frit and substitutes an oxide scavenger such as silver fluoride. The low temperature firing copper metal systems give good results on solar cells obtaining cell efficiencies of 13% AM1, and adhering sintered structures are demonstrated with nickel systems. The potential effect of copper upon cell performance at elevated temperatures over long periods of time is determined, and it is found that the formation of a copper-silicon eutectic at 550 C produces needle-like structures with broad bases on the silicon, extending into and occasionally through the metallization layer.

Ross, B.↗

Improved Airborne System for Sensing Wildfires

The Wildfire Airborne Sensing Program (WASP) is engaged in a continuing effort to develop an improved airborne instrumentation system for sensing wildfires. The system could also be used for other aerial-imaging applications, including mapping and military surveillance. Unlike prior airborne fire-detection instrumentation systems, the WASP system would not be based on custom-made multispectral line scanners and associated custom- made complex optomechanical servomechanisms, sensors, readout circuitry, and packaging. Instead, the WASP system would be based on commercial off-the-shelf (COTS) equipment that would include (1) three or four electronic cameras (one for each of three or four wavelength bands) instead of a multispectral line scanner; (2) all associated drive and readout electronics; (3) a camera-pointing gimbal; (4) an inertial measurement unit (IMU) and a Global Positioning System (GPS) receiver for measuring the position, velocity, and orientation of the aircraft; and (5) a data-acquisition subsystem. It would be necessary to custom-develop an integrated sensor optical-bench assembly, a sensor-management subsystem, and software. The use of mostly COTS equipment is intended to reduce development time and cost, relative to those of prior systems.

McKeown, Donald↗

(abstract) ARGOS: a System to Monitor Ulysses Nutation and Thruster Firings from Variations of the Spacecraft Radio Signal

Ulysses is a spin-stabilized spacecraft that experienced significant nutation after its launch in October 1990. This was due to the Sun-spacecraft-Earth geometry, and a study of the phenomenon predicted that the nutation would again be a problem during 1994-95. The difficulty of obtaining nutation estimates in real time from the spacecraft telemetry forced the ESA/NASA Ulysses Team to explore alternative information sources. The work performed by the ESA Operations Team provided a model for a system that uses the radio signal strength measurements to monitor the spacecraft dynamics. These measurements (referred to as AGC) are provided once per second by the tracking stations of the DSN. The system was named ARGOS (Attitude Reckoning from Ground Observable Signals) after the ever-vigilant, hundred-eyed giant of Greek Mythology. The ARGOS design also included Doppler processing, because Doppler shifts indicate thruster firings commanded by the active nutation control carried out onboard the spacecraft. While there is some visibility into thruster activity from telemetry, careful processing of the high-sample-rate Doppler data provides an accurate means of detecting the presence and time of thruster firings. DSN Doppler measurements are available at a ten-per-second rate in the same tracking data block as the AGC data.

Ulysses nutation Doppler radio signal strength mea↗

Incorporating UAS Traffic Management into Wildland Firefighting Operations: Initial Findings of Subject Matter Expert Interviews

Uncrewed Aircraft Systems (UASs) are being utilized throughout the disaster and emergency response domain, including in wildland firefighting operations. While UASs can offer safety benefits in comparison to crewed aircraft, such as removing the human pilot from the vehicle so that they are not exposed to the same risks and the ability to operate in low-visibility conditions, they are not without tradeoffs. For example, it can be challenging for UAS pilots (UASPs) to build situation awareness of the airspace in which their UAS is operating. In order to address some of the challenges associated with using UASs and provide greater assistance to the firefighters and incident personnel in the wildland firefighting environment, the National Aeronautics and Space Administration (NASA) launched the Advanced Capabilities for Emergency Response Operations (ACERO) project. Building on previous NASA research, ACERO will explore the implementation of a traffic management system in the wildland fire environment to enhance safety and support situation awareness. ACERO draws on the UAS Traffic Management (UTM) system previously demonstrated in an urban environment. However, a traffic management system implemented in the wildland fire environment is expected to look and function much differently in order to meet the unique needs of this domain. At the outset of the ACERO project, interviews were conducted with five UASPs who operate UASs at wildland fire incidents. The interviews focused on exploring UASPs’ initial insights about the application of a traffic management system in wildland firefighting and understanding the unique needs of this environment. The UASPs discussed a range of topics including, the shape, size, and organization of UAS operations in the wildland fire environment, information needs for a user interface, such as traffic and map information, an alerting function when other traffic nears their operation area, and the importance of conformance monitoring. The UASPs also discussed their willingness to share operational information to support safety. In this paper, we describe the foundational work upon which ACERO will build and summarize the information and insights gathered during the UASP interviews, some of which have already informed the development of the ACERO work.

Uncrewed Aircraft System (UAS)↗

Incorporating UAS Traffic Management into Wildland Firefighting Operations: Initial Findings of Subject Matter Expert Interviews

Uncrewed Aircraft Systems (UASs) are being utilized throughout the disaster and emergency response domain, including in wildland firefighting operations. While UASs can offer safety benefits in comparison to crewed aircraft, such as removing the human pilot from the vehicle so that they are not exposed to the same risks and the ability to operate in low-visibility conditions, they are not without tradeoffs. For example, it can be challenging for UAS pilots (UASPs) to build situation awareness of the airspace in which their UAS is operating. In order to address some of the challenges associated with using UASs and provide greater assistance to the firefighters and incident personnel in the wildland firefighting environment, the National Aeronautics and Space Administration (NASA) launched the Advanced Capabilities for Emergency Response Operations (ACERO) project. Building on previous NASA research, ACERO will explore the implementation of a traffic management system in the wildland fire environment to enhance safety and support situation awareness. ACERO draws on the UAS Traffic Management (UTM) system previously demonstrated in an urban environment. However, a traffic management system implemented in the wildland fire environment is expected to look and function much differently in order to meet the unique needs of this domain. At the outset of the ACERO project, interviews were conducted with five UASPs who operate UASs at wildland fire incidents. The interviews focused on exploring UASPs’ initial insights about the application of a traffic management system in wildland firefighting and understanding the unique needs of this environment. The UASPs discussed a range of topics including, the shape, size, and organization of UAS operations in the wildland fire environment, information needs for a user interface, such as traffic and map information, an alerting function when other traffic nears their operation area, and the importance of conformance monitoring. The UASPs also discussed their willingness to share operational information to support safety. In this presentation, we describe the foundational work upon which ACERO will build and summarize the information and insights gathered during the UASP interviews, some of which have already informed the development of the ACERO work.

Uncrewed Aircraft Systems (UAS)↗

Additive Manufacturing of Low Cost Upper Stage Propulsion Components

NASA is currently developing Additive Manufacturing (AM) technologies and design tools aimed at reducing the costs and manufacturing time of regeneratively cooled rocket engine components. These Low Cost Upper Stage Propulsion (LCUSP) tasks are funded through NASA's Game Changing Development Program in the Space Technology Mission Directorate. The LCUSP project will develop a copper alloy additive manufacturing design process and develop and optimize the Electron Beam Freeform Fabrication (EBF3) manufacturing process to direct deposit a nickel alloy structural jacket and manifolds onto an SLM manufactured GRCop chamber and Ni-alloy nozzle. In order to develop these processes, the project will characterize both the microstructural and mechanical properties of the SLMproduced GRCop-84, and will explore and document novel design techniques specific to AM combustion devices components. These manufacturing technologies will be used to build a 25K-class regenerative chamber and nozzle (to be used with tested DMLS injectors) that will be tested individually and as a system in hot fire tests to demonstrate the applicability of the technologies. These tasks are expected to bring costs and manufacturing time down as spacecraft propulsion systems typically comprise more than 70% of the total vehicle cost and account for a significant portion of the development schedule. Additionally, high pressure/high temperature combustion chambers and nozzles must be regeneratively cooled to survive their operating environment, causing their design to be time consuming and costly to build. LCUSP presents an opportunity to develop and demonstrate a process that can infuse these technologies into industry, build competition, and drive down costs of future engines.

Protz, Christopher↗

Ultrasonic Imaging System

An imaging system is described which can be used to either passively search for sources of ultrasonics or as an active phase imaging system. which can image fires. gas leaks, or air temperature gradients. This system uses an array of ultrasonic receivers coupled to an ultrasound collector or lens to provide an electronic image of the ultrasound intensity in a selected angular region of space. A system is described which includes a video camera to provide a visual reference to a region being examined for ultrasonic signals.

Youngquist, Robert C.↗

Solutions to time variant problems of real-time expert systems

Real-time expert systems for monitoring and control are driven by input data which changes with time. One of the subtle problems of this field is the propagation of time variant problems from rule to rule. This propagation problem is even complicated under a multiprogramming environment where the expert system may issue test commands to the system to get data and to access time consuming devices to retrieve data for concurrent reasoning. Two approaches are used to handle the flood of input data. Snapshots can be taken to freeze the system from time to time. The expert system treats the system as a stationary one and traces changes by comparing consecutive snapshots. In the other approach, when an input is available, the rules associated with it are evaluated. For both approaches, if the premise condition of a fired rule is changed to being false, the downstream rules should be deactivated. If the status change is due to disappearance of a transient problem, actions taken by the fired downstream rules which are no longer true may need to be undone. If a downstream rule is being evaluated, it should not be fired. Three mechanisms for solving this problem are discussed: tracing, backward checking, and censor setting. In the forward tracing mechanism, when the premise conditions of a fired rule become false, the premise conditions of downstream rules which have been fired or are being evaluated due to the firing of that rule are reevaluated. A tree with its root at the rule being deactivated is traversed. In the backward checking mechanism, when a rule is being fired, the expert system checks back on the premise conditions of the upstream rules that result in evaluation of the rule to see whether it should be fired. The root of the tree being traversed is the rule being fired. In the censor setting mechanism, when a rule is to be evaluated, a censor is constructed based on the premise conditions of the upstream rules and the censor is evaluated just before the rule is fired. Unlike the backward checking mechanism, this one does not search the upstream rules. This paper explores the details of implementation of the three mechanisms.

Yeh, Show-Way↗

Deep Learning Provides Substantial Improvements to County‐Level Fire Weather Forecasting Over the Western United States

Abstract The recent wildfires in the western United States during 2018 and 2020 caused record‐breaking fire damage and casualties. Despite remarkable advances in fire modeling and weather forecasting, it remains challenging to anticipate catastrophic wildfire events and associated damage. One key missing component is a fire weather prediction system with sufficiently long lead time capable of providing useful regional details. Here, we develop a hybrid prediction model of wildfire danger called CFS with super resolution (CFS‐SR) as a proof of concept to fill that void. The CFS‐SR model is constructed by integrating the Climate Forecast System version 2 with a deep learning (DL) technique from Single Image Super Resolution, a method widely used in enhancing image resolution. We show that for the 2018–2019 fire season, the CFS‐SR model significantly improves accuracy in forecasting fire weather at lead times of up to 7 days with an enhanced spatial resolution up to 4 km. This level of high resolution provides county‐level fire weather forecast, making it more practical for allocating resources to mitigate wildfire danger. Our study demonstrates that a proper combination of ensemble climate predictions with DL techniques can boost predictability at finer spatial scales, increasing the utility of fire weather forecasts for practical applications.

54 ENVIRONMENTAL SCIENCES↗