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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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Bioaerosol Emission Characteristics from Laboratory Burns
Combustion processes can aerosolize and transport particles both from nonbiological and biological origin, with the latter termed bioaerosol particle (BAP). Previous work has shown an increase in the level of BAP in smoke plumes. The mechanism of their emission, whether from combustion of biological material or coemission with dust and soil from fire-driven winds, has yet to be examined. Here, we carried out a series of controlled combustion experiments to understand the role of vegetation type and combustion conditions in the direct emission of BAP. The fuels we used included broadleaf, evergreen, and grass. We measured the emitted fluorescent BAP using a wideband integrated bioaerosol system (WIBS), and we measured the viability of filter-collected BAP using flow cytometry. Our measurements showed that the size and absolute concentration of the fluorescent BAP, and the viability of the BAP emitted during combustion, depend on the combustion conditions. In addition, the type of fuel impacted the type of emitted fluorescent BAP fraction relative to the total concentration of the emitted aerosol.
Multi-day photochemical evolution of organic aerosol from biomass burning emissions
Our work highlights how organic compounds in smoke particles will undergo physical and chemical transformations in the presence of sunlight as the smoke is transported over long distances.
Comparison of Reactive Burn Equilibrium Closure Assumptions in CTH.
Abstract not provided.
Extension of the xHVRB Reactive Burn Model for Graded Density Explosives.
Abstract not provided.
Uncertainty Quantification for a TNT Equation of State Including the Kinetic Burn Model
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A thermodynamic condition for ignition and burn-propagation in cryogenic layer inertially confined fusion implosions
A Lawson-like criterion for ignition (where self-heating dominates over all energy losses) in a dynamic implosion is developed, which accounts for asymmetry and for differences in an implosion x-ray confinement quality. It is shown that the thermodynamic ignition condition is equivalent to yield amplification levels of 16–32. Since negative pdV work of expansion after stagnation increases energy losses above that of x-ray and electron-conduction losses, the Lawson-like ignition criterion is necessary but not sufficient for igniting the hot spot to propagate into the DT fuel with sufficient vigor to generate high gain. Additionally, a higher dimensional generalization of the Lawson-like criterion, which includes the cooling of the implosion upon disassembly, does provide the needed criteria, and it shows that significantly higher temperature is needed for very high levels of yield amplification compared to what traditional ignition metrics imply.
Reaching a burning plasma and ignition using smaller capsules/ Hohlraums , higher radiation temperatures, and thicker ablator/ice on the national ignition facility
In indirect-drive implosions, the final core hot spot energy and pressure and, hence, neutron yield attainable in 1D increase with increasing laser peak power and, hence, radiation drive temperature at the fixed capsule and Hohlraum size. Here we present simple analytic scalings validated by 1D simulations that quantify the improvement in performance and use this to explain existing data and simulation trends. Extrapolating to the 500 TW National Ignition Facility peak power limit in a low gas-fill 5.4 mm diameter Hohlraum based on existing high adiabat implosion data at 400 TW, 1.3 MJ and 1 × 10 16 yield, we find that a 2–3 × 10 17 yield (0.5–0.7 MJ) is plausible using only 1.8 MJ of laser energy. Based on existing data varying deuterium–tritium (DT) fuel thickness and dopant areal density, further improvements should be possible by increasing DT fuel areal density, and hence confinement time and yield amplification.
The next-generation particle x-ray temporal diagnostic for simultaneous time-resolved measurements of nuclear-burn and x-ray emission histories in support of basic-science and inertial confinement fusion experiments at OMEGA
The next-generation Particle X-ray Temporal Diagnostic (PXTD) has been implemented for simultaneous measurements of x-ray, charged particle, and neutron emission histories from a wide range of inertial confinement fusion and high energy density plasma experiments, demonstrating excellent timing accuracy and greatly improved experimental flexibility. The key changes to the previously fielded system are a redesigned set of thin foil filters in front of the scintillators and individual neutral density filters for each region of the detector. The fully implemented PXTD system can provide unique information about the evolution of ion and electron temperatures in multi-ion and kinetic-physics experiments, proton radiography experiments, and DT experiments executed at the OMEGA facility. The system has 35 ps time resolution and negligible relative timing uncertainty between measured emission history signals. The first use of the upgraded four-channel PXTD system during a set of D 3 He-filled silica-glass implosions on OMEGA captured electron temperatures with a minimum uncertainty of 0.5 keV and resolved both the relative timings and widths of neutron, proton, and x-ray peaks within a single recorded image.
Scoping Studies for a Lead-Lithium-Cooled, Minor-Actinide-Burning, Fission-Fusion Hybrid Reactor Design
Not provided.
Effects of stretch and radiation on the laminar burning velocity of R-32/air flames
Not provided.
Identifying non-performing or dud plasmas for burning plasma control: insights from JET and TFTR deuterium–tritium campaigns
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Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks
Next generation High Performance (HP) tokamaks risk damage from unmitigated disruptions at high current and power. Achieving reliable disruption prediction for a device's HP operation based on its Low Performance (LP) data is a key to its success. In this letter, through explorative data analysis and dedicated numerical experiments on multiple existing tokamaks, we demonstrate how the operational regimes of tokamaks can affect the power of a trained disruption predictor. First, our results suggest data-driven disruption predictors trained on abundant LP discharges work poorly on the HP regime of the same tokamak, which is a consequence of the distinct distributions of the tightly correlated signals related to disruptions in these two regimes. Second, we find that matching operational parameters among tokamaks strongly improves cross-machine accuracy which implies our model learns from the underlying scalings of dimensionless physics parameters like q 95 , β p and confirms the importance of these parameters in disruption physics and cross machine domain matching from the data-driven perspective. Finally, our results show in the absence of HP data from the target devices, the best predictivity of the HP regime for the target machine can be achieved by combining LP data from the target with HP data from other machines. Furthermore, these results provide a possible disruption predictor development strategy for next generation tokamaks, such as ITER and SPARC, and highlight the importance of developing baseline scenario discharges of future tokamaks on existing machines to collect more relevant disruptive data.
Nonlinear gyrokinetic predictions of SPARC burning plasma profiles enabled by surrogate modeling
Multi-channel, nonlinear predictions of core temperature and density profiles are performed for the SPARC tokamak accounting for both kinetic neoclassical and fully nonlinear gyro-kinetic turbulent fluxes. A series of flux-tube, nonlinear, electromagnetic simulations using the CGYRO code with six gyrokinetic species are coupled to a nonlinear optimizer using Gaussian process regression techniques. The simultaneous evolution of energy sources, including alpha heat, radiation, and energy exchange, coupled with these high fidelity models and techniques, leads to a converged solution in electron temperature, ion temperature and electron density channels with a minimal number of expensive gyrokinetic simulations without compromising accuracy.
MHD, disruptions and control physics: Chapter 4 of the special issue: on the path to tokamak burning plasma operation
In this chapter, we review the progress in MHD stability, disruptions and control in magnetic fusion research that has occurred over the past (more than) one and a half decades since the publication by Hender et al in 2007 on the same topic as part of the update of ITER Physics Basis. During this period, remarkable progress has been achieved in the understanding of the basic physics and overall control of MHD instabilities through a wide spectrum of dedicated experiments, theory and modeling. The sawtooth activities are probably today one of the best understood of MHD events and very robust control schemes have been developed for reliable operation of tokamaks through core heating. Similarly, significant improvements have been achieved in understanding and control of neoclassical tearing modes, resistive wall modes or locked modes and their control through ECCD or error field control. The field of disruption prediction through application of artificial intelligence, machine learning or deep learning methods, which had already started at the time of the 2007 review, has progressed significantly due to general progress in these fields and application of newer, more sophisticated algorithms. However, although remarkable progress has been achieved in the field of Disruptions, their understanding, prediction, possible avoidance and mitigation still remain probably the most active fields of R&D globally in this field. This is especially because reactor grade machines like ITER and DEMO will be much less tolerant in respect of disruptions and runaway currents, and their occurrences must be either avoided altogether or minimized to an acceptable value without causing any significant hindrance to robust machine operations. This review is intended to present a broad spectrum of the R&D that has occurred in this field in support of ITER, which will also be of immense significance for all future machines, especially reactors like DEMO.
Burning questions for a warming and changing world: 15 unknowns in plant abiotic stress
Abstract We present unresolved questions in plant abiotic stress biology as posed by 15 research groups with expertise spanning eco-physiology to cell and molecular biology. Common themes of these questions include the need to better understand how plants detect water availability, temperature, salinity, and rising carbon dioxide (CO2) levels; how environmental signals interface with endogenous signaling and development (e.g. circadian clock and flowering time); and how this integrated signaling controls downstream responses (e.g. stomatal regulation, proline metabolism, and growth versus defense balance). The plasma membrane comes up frequently as a site of key signaling and transport events (e.g. mechanosensing and lipid-derived signaling, aquaporins). Adaptation to water extremes and rising CO2 affects hydraulic architecture and transpiration, as well as root and shoot growth and morphology, in ways not fully understood. Environmental adaptation involves tradeoffs that limit ecological distribution and crop resilience in the face of changing and increasingly unpredictable environments. Exploration of plant diversity within and among species can help us know which of these tradeoffs represent fundamental limits and which ones can be circumvented by bringing new trait combinations together. Better defining what constitutes beneficial stress resistance in different contexts and making connections between genes and phenotypes, and between laboratory and field observations, are overarching challenges.
Laser-enhanced fusion burn fractions for advanced fuels
Not Available
Calibration of reactive burn and Jones-Wilkins-Lee parameters for simulations of a detonation-driven flow experiment with uncertainty quantification
Here, uncertainties in the explosive-specific parameters of the Jones-Wilkins-Lee (JWL) equation of state (EOS) are carefully considered in hydrodynamic simulations of an explosive experiment to minimize the error in the flow prediction. Experimental data of the leading shock position in the transverse direction over time serves as the prediction metric for quantifying simulation prediction error. The uncertainty quantification technique, global sensitivity analysis, is utilized to determine the JWL parameters to which the transverse shock propagation is most sensitive. A polynomial response surface (PRS) is constructed in the space of the most influential JWL parameters, and the point of minimum error between the experimental data and the PRS yields calibrated JWL parameters for the experimental flow. The simulation results following the parameter calibration show good agreement with the experimental data. It was found that two significant parameters, the heat release per unit mass of reactant Q and JWL model exponent R 1 are strongly related, which makes it difficult to identify accurate values.