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At least 523 records · Page 29

Electrified vapour deposition at ultrahigh temperature and atmospheric pressure for nanomaterials synthesis

Vapour-phase synthesis methods have shown promise for the scalable synthesis of nanomaterials and coatings. However, the vaporization of different precursors for the synthesis of a broad nanomaterial space, particularly at atmospheric pressure, while maintaining compositional and structural control of the final product is challenging. Here we report the generation of an ultrahigh-temperature atomic vapour at atmospheric pressure based on electrified heating, for the growth of multi-elemental nanomaterials and thin films. This process relies on a reactor design whereby solid-state precursors are vaporized within a semi-confined space beneath an electrified heater that can reach ~3,000 K. The proximity of the heater rapidly breaks down the bonds of metal salt precursors and decomposes them into an atomic vapour that expands into a high-temperature (>2,000 K), highly reactive and high-flux vapour (10 21 –10 22 atoms per cm 2 per second) that travels upwards in a directional flow. When mixed with entrained ambient gases, the highly reactive atomic species rapidly nucleate and grow into the desired final products, including alloys, oxides, sulfides and thin films, which can be deposited on a low-temperature substrate. This EVD approach can synthesize a broad range of functional nanomaterials at atmospheric pressure, including single-phase multi-elemental nanomaterials formed under thermodynamically non-equilibrium conditions.

36 MATERIALS SCIENCE↗

SU-D-18A-02: Towards Real-Time On-Board Volumetric Image Reconstruction for Intrafraction Target Verification in Radiation Therapy

Purpose: To expedite on-board volumetric image reconstruction from limited-angle kV—MV projections for intrafraction verification. Methods: A limited-angle intrafraction verification (LIVE) system has recently been developed for real-time volumetric verification of moving targets, using limited-angle kV—MV projections. Currently, it is challenged by the intensive computational load of the prior-knowledge-based reconstruction method. To accelerate LIVE, we restructure the software pipeline to make it adaptable to model and algorithm parameter changes, while enabling efficient utilization of rapidly advancing, modern computer architectures. In particular, an innovative two-level parallelization scheme has been designed: At the macroscopic level, data and operations are adaptively partitioned, taking into account algorithmic parameters and the processing capacity or constraints of underlying hardware. The control and data flows of the pipeline are scheduled in such a way as to maximize operation concurrency and minimize total processing time. At the microscopic level, the partitioned functions act as independent modules, operating on data partitions in parallel. Each module is pre-parallelized and optimized for multi-core processors (CPUs) and graphics processing units (GPUs). Results: We present results from a parallel prototype, where most of the controls and module parallelization are carried out via Matlab and its Parallel Computing Toolbox. The reconstruction is 5 times faster on a data-set of twice the size, compared to recently reported results, without compromising on algorithmic optimization control. Conclusion: The prototype implementation and its results have served to assess the efficacy of our system concept. While a production implementation will yield much higher processing rates by approaching full-capacity utilization of CPUs and GPUs, some mutual constraints between algorithmic flow and architecture specifics remain. Based on a careful analysis of the prototype performance, it will be feasible to resolve such issues through appropriate algorithmic modifications or special-purpose hardware, thus enabling target verification in seconds with the LIVE system. This work was partially supported by a research grant from Varian Medical Systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Reaction Rover

Reaction Rover is a software application designed to enable reaction optimization with little or no human intervention and to provide a flexible platform to facilitate rapid testing, automation, and implementation of new reaction optimization algorithms. Toward these goals, Reaction Rover is designed to be modular, allowing the optimization algorithm, analyzer, and reactor components to be changed for any given process using easily integrated plugins. The Reaction Rover platform is a key development that enables the testing, use, and automation of machine learning (ML) and non-ML optimizers in a variety of laboratory situations.

Windus, Theresa↗

Equilipy: a python package for calculating phase equilibria

The CALPHAD (CALculation of PHAse Diagram) approach (Nigel Saunders & Miodownik, 1998) provides predictions for thermodynamically stable phases in multicomponent-multiphase materials across a wide range of temperatures. Consequently, the CALPHAD calculations became an essential tool in materials and process design (Luo, 2015). Such design tasks frequently require navigating a high-dimensional space due to multiple components involved in the system. This increasing complexity demands high-throughput CALPHAD calculations, especially in the rapidly evolving field of alloy design. In response to the need, we developed Equilipy an open-source Python package designed for calculating phase equilibria of multicomponent-multiphase systems. Equilipy is specifically tailored for high-throughput CALPHAD calculations, offering parallel computations across multiple processors and nodes with the given NPT input conditions namely elemental compositions (N), pressure (P), and temperature (T). Equilipy utilizes the program structure and Gibbs energy functions from the Fortran-based program, Thermochimica (Piro et al., 2013), with incorporating a new Gibbs energy minimization algorithm. This algorithm, originally developed by Capitani and Brown in 1987 (Capitani & Brown, 1987), has been revised and implemented to enhance the stability and performance of calculations. The Fortran codes are precompiled and interfaced with Python via F2PY, ensuring high computation speed. Benchmark tests shown in Figure 1 demonstrate that Equilipy’s computation speed is comparable to those of established commercial software, TC-Python and PanPython. This result highlights its efficiency and potential applications in various scientific and industrial fields.

97 MATHEMATICS AND COMPUTING↗

Ceramic Waste Form Data Package

The purpose of this data package is to provide information about simulated crystalline waste forms that can be used to select an appropriate composition for a Cold Crucible Induction Melter (CCIM) proof of principle demonstration. Melt processing, viscosity, electrical conductivity, and thermal analysis information was collected to assess the ability of two potential candidate ceramic compositions to be processed in the Idaho National Laboratory (INL) CCIM and to guide processing parameters for the CCIM operation. Given uncertainties in the CCIM capabilities to reach certain temperatures throughout the system, one waste form designated 'Fe-MP' was designed towards enabling processing and another, designated 'CAF-5%TM-MP' was designed towards optimized microstructure. Melt processing studies confirmed both compositions could be poured from a crucible at 1600°C although the CAF-5%TM-MP composition froze before pouring was complete due to rapid crystallization (upon cooling). X-ray diffraction measurements confirmed the crystalline nature and phase assemblages of the compositions. The kinetics of melting and crystallization appeared to vary significantly between the compositions. Impedance spectroscopy results indicated the electrical conductivity is acceptable with respect to processing in the CCIM. The success of processing either ceramic composition will depend on the thermal profiles throughout the CCIM. In particular, the working temperature of the pour spout relative to the bulk melter which can approach 1700°C. The Fe-MP composition is recommended to demonstrate proof of principle for crystalline simulated waste forms considering the current configuration of INL's CCIM. If proposed modifications to the CCIM can maintain a nominal temperature of 1600°C throughout the melter, drain, and pour spout, then the CAF-5%TM-MP composition should be considered for a proof of principle demonstration.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

First-Principles Cost Estimation of a Sodium Fast Reactor Nuclear Plant

A multi-tiered cost analysis is performed to estimate full costs of a nuclear power plant (NPP) based on sodium-cooled fast reactor (SFR) technology. To address the lack of fully transparent cost estimations from past undertakings for NPPs, we have developed a detailed and first-principles-based cost estimate for a generalized SFR NPP. Our intent is to achieve a high degree of transparency with our cost assumptions and develop a cost model that is flexible and easily extendable to variations in NPP design and other nuclear reactor types. Furthermore, we strive to achieve a clear organization of costs and complete identification of key cost drivers based on first principles. To this end, the cost results of our analysis as given in Table 24 and Table 25 are organized and categorized into a code of accounts (COA) under development at Idaho National Laboratory (INL). Varying degrees of first-principles methods are employed, such as design for manufacture and assembly® (DFMA® ), to elucidate costs in all process levels of the plant equipment, buildings and site structures, personnel, and other miscellaneous but significant cost elements. These approaches have been successfully applied in past cost analysis projects and are designed to enable rapid and flexible cost estimation. Application of these techniques for evaluating NPP costs is similar in concept to the full, detailed estimation of construction and fabrication costs determined in a later stage of NPP development. Note that our approach tries to avoid use of other past analysis results and data such as those from the legacy Energy Economic Data Base (EEDB) Program, as these resources are based on historical NPP costs and thus may not be indicative of new reactor technologies or construction and fabrication/manufacturing techniques. However, we provide a comparison of our SFR NPP cost results in Table 90 against those included in the EEDB for a representative pressurized water reactor (PWR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A generic interface between COSMIC/NASTRAN and PATRAN (R)

Despite its powerful analytical capabilities, COSMIC/NASTRAN lacks adequate post-processing adroitness. PATRAN, on the other hand is widely accepted for its graphical capabilities. A nonproprietary, public domain code mnemonically titled CPI (for COSMIC/NASTRAN-PATRAN Interface) is designed to manipulate a large number of files rapidly and efficiently between the two parent codes. In addition to PATRAN's results file preparation, CPI also prepares PATRAN's P/PLOT data files for xy plotting. The user is prompted for necessary information during an interactive session. Current implementation supports NASTRAN's displacement approach including the following rigid formats: (1) static analysis, (2) normal modal analysis, (3) direct transient response, and (4) modal transient response. A wide variety of data blocks are also supported. Error trapping is given special consideration. A sample session with CPI illustrates its simplicity and ease of use.

Roschke, Paul N.↗

Advancements in Binder Systems for Solid Freeform Fabrication

Paper will present recent developments in advanced material binder systems for solid freeform fabrication (SFF) technologies. The advantage of SFF is the capability to custom fabricate complex geometries directly from computer aided design data in layer- by-layer fashion, eliminated the need for traditional fixturing and tooling. Binders allow for the low temperature processing of 'green' structural materials, either metal, ceramic or composite, in traditional rapid prototyping machines. The greatest obstacle comes when green parts must then go through a sintering or burnout process to remove the binders and fully densify the parent material, without damaging or distorting the original part geometry. Critical issues and up-to-date assessments will be delivered on various material systems.

Cooper, Ken↗

Electron Beam Freeform Fabrication (EBF3) for Cost Effective Near-Net Shape Manufacturing

Manufacturing of structural metal parts directly from computer aided design (CAD) data has been investigated by numerous researchers over the past decade. Researchers at NASA Langley Research Center are developing a new solid freeform fabrication process, electron beam freeform fabrication (EBF3), as a rapid metal deposition process that works efficiently with a variety of weldable alloys. EBF3 deposits of 2219 aluminium and Ti-6Al-4V have exhibited a range of grain morphologies depending upon the deposition parameters. These materials have exhibited excellent tensile properties comparable to typical handbook data for wrought plate product after post-processing heat treatments. The EBF3 process is capable of bulk metal deposition at deposition rates in excess of 2500 cubic centimeters per hour (150 in3/hr) or finer detail at lower deposition rates, depending upon the desired application. This process offers the potential for rapidly adding structural details to simpler cast or forged structures rather than the conventional approach of machining large volumes of chips to produce a monolithic metallic structure. Selective addition of metal onto simpler blanks of material can have a significant effect on lead time reduction and lower material and machining costs.

Taminger, Karen M.↗

Electron Beam Freeform Fabrication for Cost Effective Near-Net Shape Manufacturing

Manufacturing of structural metal parts directly from computer aided design (CAD) data has been investigated by numerous researchers over the past decade. Researchers at NASA Langley Research Center are developing a new solid freeform fabrication process, electron beam freeform fabrication (EBF3), as a rapid metal deposition process that works efficiently with a variety of weldable alloys. EBF3 deposits of 2219 aluminium and Ti-6Al-4V have exhibited a range of grain morphologies depending upon the deposition parameters. These materials have exhibited excellent tensile properties comparable to typical handbook data for wrought plate product after post-processing heat treatments. The EBF3 process is capable of bulk metal deposition at deposition rates in excess of 2500 cm3/hr (150 in3/hr) or finer detail at lower deposition rates, depending upon the desired application. This process offers the potential for rapidly adding structural details to simpler cast or forged structures rather than the conventional approach of machining large volumes of chips to produce a monolithic metallic structure. Selective addition of metal onto simpler blanks of material can have a significant effect on lead time reduction and lower material and machining costs.

Taminger, Karen M.↗

Simulating Humans as Integral Parts of Spacecraft Missions

The Collaborative-Virtual Environment Simulation Tool (C-VEST) software was developed for use in a NASA project entitled "3-D Interactive Digital Virtual Human." The project is oriented toward the use of a comprehensive suite of advanced software tools in computational simulations for the purposes of human-centered design of spacecraft missions and of the spacecraft, space suits, and other equipment to be used on the missions. The C-VEST software affords an unprecedented suite of capabilities for three-dimensional virtual-environment simulations with plug-in interfaces for physiological data, haptic interfaces, plug-and-play software, realtime control, and/or playback control. Mathematical models of the mechanics of the human body and of the aforementioned equipment are implemented in software and integrated to simulate forces exerted on and by astronauts as they work. The computational results can then support the iterative processes of design, building, and testing in applied systems engineering and integration. The results of the simulations provide guidance for devising measures to counteract effects of microgravity on the human body and for the rapid development of virtual (that is, simulated) prototypes of advanced space suits, cockpits, and robots to enhance the productivity, comfort, and safety of astronauts. The unique ability to implement human-in-the-loop immersion also makes the C-VEST software potentially valuable for use in commercial and academic settings beyond the original space-mission setting.

Bruins, Anthony C.↗

Modeling-Driven Damage Tolerant Design of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composite Panels for Full-Scale Aerospace Structures

The objective of this study is to design a new nano graphenecarbon fiberpolymer hybrid composite that can be used for the NASA SLS Composite Exploration Upper Stage (CEUS) forward skirt structure. The new material will improve the resistance to open-hole compression failure of the structure relative to traditional polymer fiber composites. The material is designed rapidly and with little cost using the Integrated Computational Materials Engineering (ICME) approach. Multiscale modeling and experiments are used to synergistically optimize the material design to yield improved properties and performance by controlling key processing parameters for manufacturing nano-enhanced materials. Specifically, the nanocomposite panel showed a 22 reduction in mass relative to the traditional composite panel, while both designs are equal in terms of ease of manufacture. This potential mass savings corresponds to an estimated 45 savings in materials and manufacturing costs. The multiscale ICME workflow developed for this project can be readily applied to the development of nano-enhanced composite materials and large aerospace structures. In addition, all key aspects of ICME were employed to complete this project including multiscale modeling, experimental characterization and visualization, data management, visualization, error and uncertainty quantification, and education. The results presented herein indicate a dramatic level of success, as well as the power and potential of ICME approach and multiscale modeling for composite materials.

computational mechanics↗

Design of the Lanthanum hexaboride based plasma source for the large plasma device at UCLA

The Large Plasma Device (LAPD) at UCLA (University of California, Los Angeles) produces an 18 m long, magnetized, quiescent, and uniform plasma at a high repetition rate to enable studies of fundamental plasma physics. Here, we report on a major upgrade to the LAPD plasma source that allows for more robust operation and significant expansion of achievable plasma parameters. The original plasma source made use of a heated barium oxide (BaO) coated nickel sheet as an electron emitter. This source had a number of drawbacks, including a limited range of plasma density (≲4.0 × 10 12 cm −3 ), a limited discharge duration (∼10 ms), and susceptibility to poisoning following oxygen exposure. Further, the new plasma source utilizes a 38 cm diameter lanthanum hexaboride (LaB 6 ) cathode, which has a significantly higher emissivity, allowing for a much larger discharge power density, and is robust to exposure to air. Peak plasma density of up to 3.0 × 10 13 cm −33 in helium gas has been achieved. The typical operating pressure is ∼10 −5 Torr, while dynamic pressure can be achieved through the gas-puffing technique. Discharges as long as 70 ms have been produced, enabling a variety of long-time-scale studies of processes, such as turbulent particle transport. The new source has been in continuous operation for 14 months, having survived air leaks, power outages that led to rapid temperature changes on the cathode and heater, and planned machine openings. We describe the design, construction, and initial operation of this novel new large-area LaB6 plasma source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accelerating Discovery of Solid‐State Thin‐Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment

Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.

36 MATERIALS SCIENCE↗

A New Concurrent Engineering Tool for the New Mission Design Center at NASA Ames Research Center

The NASA Ames Mission Design Center (MDC) has undergone a significant transformation process in recent years, culminating in becoming a true Concurrent Engineering Center. The underlying goal of this transformation is to better serve the Ames PI community in a cost-effective and rapidly-responsive way, providing quality products pivotal to the decision-making proposal strategy of our center. The four pillars of the change focus on four areas: personnel, physical places, tools, and training. Personnel: the MDC switched from using a dedicated pool of engineers—mostly entry-level career—for a matrixed approach with more experienced Subject Matter Experts, usually involved in spaceflight projects. These SMEs get detailed to the MDC for the duration of the study on a part-time or full-time basis. Physical places: The physical aspect pertains mostly to the layout of the new Engineering building and the dedicated concurrent engineering layout to foster collaboration. The current plan includes a dedicated space for concurrent engineering sessions as well as dedicated project rooms for concept studies. Tool: the MDC team is developing a new in-house concurrent engineering tool to facilitate concurrent engineering sessions. The team leveraged the many lessons learned and insight gained from using the current concurrent engineering tool, in use since 2007. SMEs have been involved throughout its design and development, ensuring accuracy and providing validity to the implementation approach. This new tool is database-driven and allows a team to work concurrently on the same model of a mission concept. “Workspaces” are provided for each of the traditional spacecraft mission design disciplines, including cost accounting and systems engineering. There are multiple tiers of fidelity available within each workspace, which can be completed parametrically or independently from the other disciplines as needed or synchronously with the other disciplines. A “commit” step synchronizes a workspace with the mission database and identifies any potential conflicts, along with the user who entered the conflicting data. A Mission Summary workspace enables a Study Lead to run an effective CE session, displaying key graphics, workspace status information, and technical and monetary budget information. This new CE tool will be undergoing Beta Testing with its primary user base and a limited Parts database in the summer of 2020. The team plans to release the first fully operational version in December 2020. Training: working in early concept development and maturation for a space mission requires a unique mindset and being comfortable with uncertainties in an environment where requirements are not yet fully developed, and where changes and trade-offs happen at a high tempo. The MDC started a weekly training program to ensure a common knowledge base on how do develop and mature early concept studies, as well as how to operate in a concurrent engineering environment. In conclusion, the MDC transformation will provide the overall PI community focused on cost-effective small satellite scientific missions with a powerful tool to address and mature early concepts more effectively and efficiently.

David Mauro↗

A Machine Learning-Genetic Algorithm (ML-GA) Approach for Rapid Optimization Using High-Performance Computing

A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC). The outputs (targets) of interest from these simulations included five metrics related to engine performance and emissions. Over 2000 samples generated from CFD were then used to train an ML model that could predict these five targets based on the nine input features. A robust super learner approach was employed to build the ML model, where results from a collection of different ML algorithms were pooled together. Thereafter, a stochastic global optimization genetic algorithm (GA) was used, with the ML model as the objective function, to optimize the input parameters based on a merit function so as to minimize fuel consumption while satisfying CO and NOx emissions constraints. The optimized configuration from ML-GA was found to be very close to that obtained from a sequentially performed CFD-GA approach, where a CFD simulation served as the objective function. In addition, the overall turnaround time was (at least) 75% lower with the ML-GA approach, as the training data was generated from concurrent CFD simulations and employing the ML model as the objective function significantly accelerated the GA optimization. Finally, this study demonstrates the potential of ML-GA and high-performance computing (HPC) to reduce the number of CFD simulations to be performed for optimization problems without loss in accuracy, thereby providing significant cost savings compared to traditional approaches.

97 MATHEMATICS AND COMPUTING↗

Improving Flexibility and Performance of Staged Pressurized Oxy-Combustion

Staged pressurized oxy-combustion (SPOC) is a novel coal combustion power technology being developed by Washington University in St. Louis (WUSTL) that offers the potential to deliver low-carbon power at a reduced cost. Oxy-combustion plants operate by removing most of the nitrogen contained in air prior to combustion, thereby burning fuel in a near-pure oxygen stream instead of air. This combustion produces a flue gas containing primarily carbon dioxide (CO 2 ) and water vapor that allows relatively straightforward CO 2 capture. First-generation, atmospheric oxy-combustion technology relies on a flue gas recycle (FGR) diluent to reduce the peak temperatures achieved and the resulting high thermal radiation levels that would otherwise occur in a fuel/oxygen only flame. In contrast, by staging the combustion in several steps, SPOC reduces the peak temperatures of combustion without resorting to a high degree of FGR to control flame temperatures. The SPOC process operates by utilizing two or more pressurized boiler modules connected in series to produce fuel staging; hence, only a portion of the fuel is combusted in any given combustion module. Subsequently the thermal energy released at each stage can be captured and removed from the gases prior to subsequent stages, when more fuel is introduced. This allows the SPOC process to operate with minimal FGR, avoiding the associated efficiency losses and additional costs. While the staging controls the heat release profile in SPOC, operating in a pressurized condition yields a more compact system, reducing modular boiler size and delivering enhanced heat transfer. Additionally, operating at elevated pressures ensures that the latent heat of moisture available from moisture in the fuel and generated by the combustion of the hydrogen content in the fuel can be captured as useful thermal energy for steam turbine integration. This is possible due to elevated dew point from the high partial pressure of the moisture generated in this process, which allows substantial feedwater heater bypassing to be achieved. The inclusion of this thermal energy, normally lost to the atmosphere in traditional combustion processes or to cooling systems in atmospheric oxy-combustion, allows the resultant net efficiency of the SPOC system to be up to 6 percentage points greater than first-generation systems. To begin the process of developing this technology for full-scale application, the Electric Power Research Institute, Inc. teamed up with WUSTL, American Air Liquide, Doosan Babcock, and the U.S. Department of Energy to investigate a practical and workable boiler design concept that would minimize process risks where possible. The SPOC system offers unique process flexibility opportunities due to the staged nature of the combustion, making it a prime candidate for future primary energy delivery where the ability to operate at reduced load in an efficient manner and ramp rapidly will be valuable for balancing intermittent renewable electricity generation. The efficiency of traditional coal-fired power plants is lower at reduced loads below the steam temperature control range due to the challenges in balancing the heat pickup between radiative and convective superheater and reheater surface. Introducing additional heating surface for optimal extended controlled low load operation will likely lead to excessive attemperation at high loads, ultimately leading to a poorer overall cycle efficiency. The SPOC process can facilitate the adjustment of fuel firing rates between stages, targeting heat pickup to where it is most needed and potentially can shut down stages for low-load operation, facilitating an increased steam temperature control range on turndown. The boiler design concept assessment is being carried out to identify the maximum permissible compactness of the SPOC boiler heating surfaces. The assessment will determine the minimum overall height that will deliver appropriate tube operating metal temperatures at full load and achieve rated reheat steam temperatures at low operating loads, balanced against the needs of efficient coal combustion, and the potential resultant slagging and ash environments. The design parameters are being validated by combustion testing in the 100-kWth pressurized combustion test rig at WUSTL. Parameters being investigated include flame stability, fuel burnout, ash composition, radiative heat flux, and temperature profiles. These are being carried out for a range of inlet gas conditions and compositions and at multiple load conditions to investigate combustion stability at reduced load. The results of this testing inform the modeling of the large-scale system, that was sized at 550 MWe to allow direct comparison with the National Energy Technology Laboratory baseline cases for atmospheric oxy-combustion, air firing, and air firing with post-combustion capture.

20 FOSSIL-FUELED POWER PLANTS↗

Expanding the Time Dimension of Hyperspectral Infrared Sounding Observations: Designing the NUCAPS-Forecast System

Low Earth orbit (LEO) hyper-spectral infrared (IR) sounders have significant yet untapped potential for characterizing thermodynamic environments of convective initiation and ongoing convection. While LEO soundings are of enormous value to weather forecasters, they cannot provide the temporal resolution needed to resolve the rapidly evolving thermodynamics of the convective environment. A novel methodology was developed to extend snapshots of LEO soundings forward in time up to six hours into the future and has been made available within the NOAA National Weather Service Advanced Weather Interactive Processing System (AWIPS) for testing in a quasi-operational setting. This methodology is based on parcel forward-trajectory calculations from the satellite observing time to recreate future soundings of temperature and moisture at regularly gridded intervals in space and time. The soundings are based on NOAA-Unique Combined Atmospheric Processing System (NUCAPS) retrievals from the Suomi NPP and NOAA-20 satellite platforms to allow for rapid near-real time product processing. Science code was transitioned to operational production in 2019 and the product, NUCAPS-Forecast, was tested at the NOAA Hazardous Weather Testbed Spring Experiment in 2019 and 2021. Forecaster feedback has led to improving the product and processing system to address product limitations and improve its applicability for pre-convective forecasting. This presentation highlights the design of the NUCAPS-Forecast system. Solutions were tested and implemented to remove excess moisture and conjoin forward-trajected parcels into vertical profiles for calculating grids of stability indices. Additionally, use cases that explore the tendencies of derived convective available potential energy (CAPE) and convective inhibition (CIN) were investigated. When evaluated against gridded, hourly accumulated rainfall obtained from the Multi-Radar Multi-Sensor (MRMS) observational data set areas with elevated CAPE (reduced CIN) are shown to be associated with areas of precipitation and increase confidence the LEO soundings advected forward in time physically represent atmospheric processes. These results suggest that adiabatic parcel advection of LEO satellite sounding snapshots forward in time exhibits skill in discriminating locations and times that are more likely to lead to convective initiation. Leveraging trajectory modeling to increase the spatial and temporal resolution of LEO IR sounding observations today demonstrates the value of these observations from the future constellation of JPSS satellites and GeoXO mission.

weather↗