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At least 55 records · Page 3

A reaction–diffusion model for grayscale digital light processing 3D printing

We report that digital light processing (DLP) 3D printing is an additive manufacturing process that utilizes light patterns to photopolymerize a liquid resin into a solid. Due to the accuracy of modern digital micromirror devices (DMD) and recent advances in resin chemistry, it is now possible to create functionally graded structures using different light intensity values, also known as grayscale DLP (g-DLP). Different intensities of light lead to differences in the polymer crosslinking density after curing, which ultimately produces a part with gradients of material properties. However, g-DLP is a complicated process. First, the DLP printing is a highly coupled chemical and physical process that involves light propagation, chemical reactions, species diffusion, heat transfer, volume shrinkage, and changes in mechanical behaviors of the curing resin. Second, in g-DLP, light gradients create strong in plane gradients of chemical species concentrations in the curing liquid resin due to the strong dependence of light intensity on the rate of monomer crosslinking. Furthermore, light gradients through the depth create concentration gradients due to the degree of cure dependent light absorption and the use of photoabsorbers. These complex physical features of the printing process must be understood in order to properly control printing parameters such as light exposure time, printing speed, and grayscale variations to achieve accurate mechanical properties. In this paper, a photopolymerization reaction–diffusion model is developed and used in conjunction with experiments to investigate the coupled effects of light propagation, chemical reaction rates, and species diffusion during g-DLP 3D printing. The model is implemented numerically utilizing the finite difference method and simulation results are compared to experimental findings of simple printed structures. The agreement between experimental and model predictions of simple quantities of interest, such as geometric feature sizes, shows that the model can capture the overcure due to free-radical and other species diffusion during printing when grayscale patterns are employed. This model lays the groundwork for future extensions that can incorporate more complex coupled physics such as heat transfer, volume shrinkage, and material property evolution, which are critically important in utilizing g-DLP 3D printing for the fabrication of high-performance parts which excellent geometric and material property tolerances.

36 MATERIALS SCIENCE↗

Theoretical position-velocity diagrams of flux, electron density, and electron temperature in Herbig-Haro objects

Many features of Herbig-Haro objects can be reproduced using a kinematical bow shock model. We use the model to generate position-velocity (PV) diagrams of flux in H-alpha (O I) lambda lambda 6300+63, (S II) lambda lambda 6716+31, (O III) lambda lambda 4959+5007, and (C I) lambda lambda 9823+50, line ratios of (O I)/H-alpha, (O I)/(S II), (S II)/H-alpha, H-alpha(S II), and (O III)/H-alpha, electron density N(sub e), and electron temperature T(sub e). We show how position-velocity diagrams of N(sub e) and flux vary with shock velocity. By matching the diagrams from single lines, the line ratios, and N(sub e) with observations, we determined a narrow range of shock parameters for HH 1F, 2(A' + H), and 43 (B + C). We model the N(sub e) features of HH 2(A' + H) as a superposition of two bowshocks. We also show that the effects of slight misalignments of the two diagrams to be divided can produce artifacts in the line ratios and N(sub e) which obliterate the physical features. We show that N(sub e) in HH 1 can only be explained using the kinematical model by taking these misalignments into account.

Indebetouw, Remy↗

Neural network denoising of x-ray images from high-energy-density experiments

Noise is a consistent problem for x-ray transmission images of High-Energy-Density (HED) experiments because it can significantly affect the accuracy of inferring quantitative physical properties from these images. We consider experiments that use x-ray area backlighting to image a thin layer of opaque material within a physics package to observe its hydrodynamic evolution. The spatial variance of the x-ray transmission across the system due to changing opacity serves as an analog for measuring density in this evolving layer. The noise in these images adds nonphysical variations in measured intensity, which can significantly reduce the accuracy of our inferred densities, particularly at small spatial scales. Denoising these images is thus necessary to improve our quantitative analysis, but any denoising method also affects the underlying information in the image. In this paper, we present a method for denoising HED x-ray images via a deep convolutional neural network model with a modified DenseNet architecture. In our denoising framework, we estimate the noise present in the real (data) images of interest and apply the inferred noise distribution to a set of natural images. These synthetic noisy images are then used to train a neural network model to recognize and remove noise of that character. We show that our trained denoiser network significantly reduces the noise in our experimental images while retaining important physical features.

47 OTHER INSTRUMENTATION↗

Light scattering by randomly oriented cubes and parallelepipeds

In this paper, the geometric ray tracing theory for the scattering of light by hexagonal cylinders to cubes and parallelepipeds has been modified. Effects of the real and imaginary parts of the refractive index and aspect ratio of the particle on the scattering phase function and the degree of linear polarization are investigated. Causes of the physical features in the scattering polarization patterns are identified in terms of the scattering contribution due to geometric reflections and refractions. The single-scattering phase function and polarization data presented in this paper should be of some use for the interpretation of observed scattering and polarization data from planetary atmospheres and for the physical understanding of the transfer of radiation in an atmosphere containing nonspherical particles.

Liou, K. N.↗

Self-Supervised Learning of Terrain Traversability from Proprioceptive Sensors

Robust and reliable autonomous navigation in unstructured, off-road terrain is a critical element in making unmanned ground vehicles a reality. Existing approaches tend to rely on evaluating the traversability of terrain based on fixed parameters obtained via testing in specific environments. This results in a system that handles the terrain well that it trained in, but is unable to process terrain outside its test parameters. An adaptive system does not take the place of training, but supplements it. Whereas training imprints certain environments, an adaptive system would imprint terrain elements and the interactions amongst them, and allow the vehicle to build a map of local elements using proprioceptive sensors. Such sensors can include velocity, wheel slippage, bumper hits, and accelerometers. Data obtained by the sensors can be compared to observations from ranging sensors such as cameras and LADAR (laser detection and ranging) in order to adapt to any kind of terrain. In this way, it could sample its surroundings not only to create a map of clear space, but also of what kind of space it is and its composition. By having a set of building blocks consisting of terrain features, a vehicle can adapt to terrain that it has never seen before, and thus be robust to a changing environment. New observations could be added to its library, enabling it to infer terrain types that it wasn't trained on. This would be very useful in alien environments, where many of the physical features are known, but some are not. For example, a seemingly flat, hard plain could actually be soft sand, and the vehicle would sense the sand and avoid it automatically.

Bajracharya, Max↗

Interface diagnostics platform for thin-film solid-state batteries

Understanding the impedances of battery materials and their interfaces remains a major challenge, usually addressed by electrochemical impedance spectroscopy (EIS) where frequency-dependent complex impedance of full battery cells is measured and then modeled by a network of connected electrical elements. As conventionally applied, this approach produces ambiguity in that (1) multiple different network configurations may fit the data convincingly and (2) the method offers no direct association of the electrical elements with physical features of the battery. Here we present a new methodology that resolves both sources of ambiguity, enabled by expanding the experimental scope to directly inform the configuration of elements and their parameters in the network model. We demonstrate this methodology using thin film fabrication of solid state battery devices patterned by shadow masked sputter deposition, so that diagnostic devices corresponding to individual interface and material components can be fabricated simultaneously with full cell batteries. EIS models for the diagnostic devices can then be connected to form full cell networks whose topology matches the well-known physical configuration of the battery. When connected in this way, the full network model – made from connecting the diagnostic device EIS models – fits the full cell EIS data. For the case of a thin film solid state battery composed of amorphous silicon anode, lithium phosphorus oxynitride (LiPON) solid electrolyte, and lithium vanadium oxide (Li x V 2 O 5 ) cathode, we show that the approach allows us to identify ionic impedance/conductivity of the cathode/electrolyte as a limiting impedance and the anode/electrolyte interface cycling instability as a primary degradation factor.

25 ENERGY STORAGE↗

Nitrogen-doped graphene nanomaterials for electrochemical catalysis/reactions: A review on chemical structures and stability

The electronic structure of the carbon-based nanomaterials can be modulated by doping heteroatoms into them. When nitrogen is doped into the graphene structure with different bonding configurations, it changes the material's electronic properties in a variety of ways. Because of the tuned electronic properties, nitrogen-doped graphene (N-G) is applicable in electrochemical systems as catalyst. Despite having tremendous prospects, a holistic view of the structural and functional properties of N-G is still unclear. Moreover, to our knowledge, significant findings on the properties of N-G are not well documented yet, which creates an obstacle to the further improvement of this nanomaterial. Keeping our focus on the catalytic activities, in this paper, we presented an in-detailed review of the overall chemical structure and functional properties of N-G nanomaterials. Starting from the structural properties of major precursor materials for N-G synthesis, we reviewed the physical features and its dependence on the synthesis parameters. Also, a detailed study has been conducted on the key nitrogen functional groups' structural properties, favorable formation environment, influence on the electronic structure of N-G, and role in the catalytic activity. Finally, current progress on the stability of N-G nanocatalysts is reported with an insight into the degradation mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of MHD stability properties between QH-mode and ELMy H-mode plasmas by considering plasma rotation and ion diamagnetic drift effects

Magnetohydrodynamic (MHD) stability at tokamak edge pedestal in a quiescent H-mode (QH-mode) and type-I ELMy H-mode plasmas in DIII-D experiment was analyzed by considering plasma rotation and ion diamagnetic drift effects. QH-mode plasma is marginally stable to kink/peeling mode (K/PM), but ELMy H-mode one is almost unstable to peeling-ballooning mode (PBM). It was identified that there are three physics features responsible for the difference in the MHD stability properties between QH-mode plasma and ELMy H-mode one. These are the distance of pedestal foot from the last closed flux surface (LCFS), the amount of the ion diamagnetic drift frequency at pedestal, and impact of coupled rotation and ion diamagnetic drift effects. These features were confirmed through the numerical experiments that the stability properties of the QH-mode plasma can be changed to that of the ELMy H-mode one by shifting the plasma profiles inward in the radial direction and halving the ion diamagnetic drift frequency. The reasons of the change in the stability properties are thought as that K/PM is stabilized due to the inward shift of the bootstrap current profile, and PBM is destabilized due to the reduction of the coupled rotation and ion diamagnetic drift stabilizing effect. Importance of these features was validated through numerical experiments with experimental data of other QH-mode plasmas in DIII-D. All the results show that MHD stability properties of QH-mode plasma can be obtained in case that pedestal foot is close to LCFS, ion diamagnetic drift frequency is large due to high ion temperature, and strong rotation shear exists near pedestal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Power of SS 433's Jets

We observed SS 433 for the third time with RXTE, this time simultaneously with a Nobeyama millimeter band monitoring campaign. These observations extended the RXTE coverage of SS 433's precession phases. and once again monitored the source during a binary eclipse. Our AO-2 campaign of a joint RXTE-VLBA-VLA-MERLIN observation was delayed to little more than a month before the AO-3 observations. We also had an AO-1 observation of SS 433. In each case we observed an eclipse of the compact ob'ect by the companion star, and had contemporaneous optical observations. We are analyzing all three sets of observations together. A publication is in preparation; Its completion will be supported by the remaining AO-2 funds. Here I will summarize the general results and point out the relevant features of the AO-3 observations. The spectrum is detected to approx. 50 keV, which is entirely within the PCA energy band. We find that the HEXTE data do not add significantly to the spectrum, and most of our fits are without HEXTE. We find that the continuum can be fit with a power law with an exponential cutoff; the photon index is usually approx. 1.4. A line at approx. 6.4 keV is definitely required, and the fits improve significant, if we add a second line, also with an energy in the iron K(alpha) complex, and an absorption edge. The edge usually has an energy of approx. 5.8 keV, which does not correspond to any known physical feature. and may be an instrumental artifact. This is under further investigation.

Band, David F.↗

LLNL Explosives Anisotropy Research

Lawrence Livermore National Laboratory scientists and engineers led a multi-institutional team in executing a series of high explosives tests that successfully demonstrated fundamental principles of anisotropy, a possible enabler for improved weapon and munition safety. Working under snowy and frigid conditions on Idaho’s Snake River Plain, a 13-member team from LLNL carried out 52 explosives shots over four days in mid-November at the Idaho National Laboratory’s (INL) National Security Test Range (NSTR) to complete the study. The broader anisotropy (ANISO) team included high explosives handlers and volunteers from INL, Los Alamos National Laboratory, Marine Raiders from the Marine Special Operations Command and members of the U.S. Special Operations Command. The purpose of the study was to explore theoretical methods of creating anisotropic explosives — explosives that perform differently depending on the direction the detonation wave moves through the explosive — by engineering certain physical features in the charges and obtaining basic data from testing. The work is part of an overall effort by the Lab to develop anisotropic explosives that could be used in munitions to reduce the severity and lethality of an unintended detonation without sacrificing performance. The data gathered from the study will be used to design and construct follow-on experiments at LLNL’s High Explosives Applications Facility (HEAF) and validate computer models for future anisotropic assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ground-based tests of hollow cathode plasma contactors

Experimental results are presented which describe operation of and the plasma environment associated with a hollow cathode-based plasma contactor collecting electrons from an ambient, low density Maxwellian plasma when the boundary between the contactor and the ambient plasma is nearly hemispherical. Basic physical features of the process of electron collection identified on the basis of these results include a double-sheath across which a substantial potential difference can develop and substantial ionization of neutral gas coming from the cathode by the electrons being collected. Experimental results obtained when the diameter of the anode is too small to yield a hemispherical double-sheath are shown to induce distortion of this sheath but it is argued that the same basic phenomena are still active in this case. Data obtained in these experiments should serve to validate numerical models of this process that are being developed to predict plasma contactor performance in space. Preliminary performance and plasma property results measured on a contactor emitting electrons are examined and some physical elements of this process are identified.

Williams, John D.↗

Flexible Electrostatic Technology for Capture and Handling Project

To NASA unfunded & planned missions: This new capability to sense proximity, flexibly align to, and attractively grip and capture practically any object in space without any pre-designed physical features or added sensors or actuators will enable or enhance many of MSFC's strategic emphasis areas in space transportation, and space systems such as: 1. A Flexible Electrostatic gripper can enable the capture, gripping and releasing of an extraterrestrial sample of different minerals or a sample canister (metallic or composite) without requiring a handle or grapple fixture.(B) 2. Flexible self-aligning in-space capture/soft docking or berthing of ISS resupply vehicles, pressurized modules, or nodes for in-space assembly and shielding, radiator, and solar Array deployment for space habitats (C) 3. The flexible electrostatic gripper when combined with a simple steerable extendible boom can grip, position, and release objects of various shapes and materials with low mass and power without any prior handles or physical accommodations or surface contamination for ISS experiment experiments and in-situ repair.(F)(G) 4. The Dexterous Docking concept previously proposed to allow simple commercial resupply ships to station-keep and capture either ISS or an Exploration vehicle for supply or fluid transfer lacked a self-sensing, compliant, soft capture gripper like FETCH that could retract and attach to a CBM. (I) 5. To enable a soft capture and de-orbit of a piece of orbital debris will require self-aligning gripping and holding an object wherever possible (thermal coverings or shields of various materials, radiators, solar arrays, antenna dishes) with little or no residual power while adding either drag or active low level thrust.(K) 6. With the scalability of the FETCH technology, small satellites can be captured and handled or can incorporate FETCH gripper to dock to and handle other small vehicles and larger objects for de-orbiting or mitigating Orbital debris (L) 7. Many of previous MSFC and NASA proposals or concepts can now be realized or simplified by the development of the this initial and future FETCH grippers including commercial resupply, Exploration vehicle assembly, Satellite servicing, and orbital debris removal since a major part of these missions is to align to and capture some handle. Completed Project (2013 - 2014) Flexible Electrostatic Technology for Capture & Handling Project Center Innovation Fund: MSFC CIF Program | Space Technology Mission Directorate (STMD) For more information visit techport.nasa.gov Some NASA technology projects are smaller (for example SBIR/STTR, NIAC and Center Innovation Fund), and will have less content than other, larger projects. Newly created projects may not sensors or injection of permanent adhesives. With gripping forces estimated between 0.5 and 2.5 pounds per square inch or 70-300 lb./sq. ft. of surface contact, the FETCH can turn-on and turn-off rapidly and repeatedly to enable sample handling, soft docking, in-space assembly, and precision relocation for accurate anchor adhesion.

Keys, Andrew↗

Topological descendants of a multicritical Dirac semimetal with magnetism and strain

The past decades have witnessed a transformation in characterizing condensed matter systems with topology. Aided by a refined understanding of topological band structures with crystalline symmetries that has emerged recently, many electronic phases have been identified, and a plethora of materials have been predicted to host properties and functionalities. A key underlying question, also with respect to future application, is to what extent the related physical features can be manipulated, especially in the context of magnetic order. Here, we describe a paradigmatic semimetal that simultaneously incorporates multiple and sometimes conflicting topology which guarantees gaplessness and leads to an exceptionally rich family of descendent phases on lowering symmetry. We predict that this multicritical phase is realized in EuTl 2 . Starting from the parent semimetallic state, which already separates two topological insulating regimes, the interplay of inherent magnetism and strain allows for an exceptionally rich phase diagram of topological descendant states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the field of fluid mechanics. Although these methods are proven successful for many applications, there is a grand challenge of improving their generalizability. This is particularly essential when data-driven models are employed within outer-loop applications like optimization. In this work, we put forth a physics-guided machine learning (PGML) framework that leverages the interpretable physics-based model with a deep learning model. Leveraging a concatenated neural network design from multi-modal data sources, the PGML framework is capable of enhancing the generalizability of data-driven models and effectively protects against or inform about the inaccurate predictions resulting from extrapolation. We apply the PGML framework as a novel model fusion approach combining the physics-based Galerkin projection model and long- to short-term memory (LSTM) network for parametric model order reduction of fluid flows. We demonstrate the improved generalizability of the PGML framework against a purely data-driven approach through the injection of physics features into intermediate LSTM layers. Our quantitative analysis shows that the overall model uncertainty can be reduced through the PGML approach, especially for test data coming from a distribution different than the training data. Moreover, we demonstrate that our approach can be used as an inverse diagnostic tool providing a confidence score associated with models and observations. The proposed framework also allows for multi-fidelity computing by making use of low-fidelity models in the online deployment of quantified data-driven models.

42 ENGINEERING↗

Fast and accurate simulations of calorimeter showers with normalizing flows

In this study, we introduce caloflow, a fast detector simulation framework based on normalizing flows. For the first time, we demonstrate that normalizing flows can reproduce many-channel calorimeter showers with extremely high fidelity, providing a fresh alternative to computationally expensive geant4 simulations, as well as other state-of-the-art fast simulation frameworks based on generative adversarial networks (GANs) or variational autoencoders (VAEs). In addition to the usual histograms of physical features and images of calorimeter showers, we introduce a new metric for judging the quality of generative modeling: the performance of a classifier trained to differentiate real from generated images. We show that GAN-generated images can be identified by the classifier with nearly 100% accuracy, while images generated from caloflow are better able to fool the classifier. More broadly, normalizing flows offer several advantages compared to other state-of-the-art approaches (GANs and VAEs), including tractable likelihoods, stable and convergent training, and principled model selection. Normalizing flows also provide a bijective mapping between data and the latent space, which could have other applications beyond simulation, for example, to detector unfolding.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Formation, cooling history and age of impact events on the IIE iron parent body: Evidence from the Miles meteorite

Most iron meteorites formed in planetary cores during differentiation, but the IIE iron meteorites have chemical and physical features that are inconsistent with this origin. By combining mineral chemistry, mineral modes and three-dimensional petrography, we reconstruct the bulk chemistry of the felsic silicate-bearing Miles IIE iron meteorite and demonstrate that the silicate inclusion compositions are similar to partial melts produced experimentally from an H chondrite composition. We use the reconstructed bulk composition, mineralogy and thermodynamic modelling to show that melting above ~ 1200°C under reducing conditions formed metal (Fe-Ni alloy) and felsic silicate partial melts. Upon cooling, the melts crystallized Mg-rich pyroxenes, Na- and K-rich feldspars, and tridymite. Importantly, this mechanism enriches cosmochemically volatile elements (i.e., those with a 50% condensation temperature of ~430–830°C, like Na and K) to the level found in the felsic silicate inclusions. The presence of crystallographically disordered srilankite (only stable above 1160°C) and an absence of Widmanstätten texture require both high peak temperatures and rapid cooling, which cannot be explained by core formation. Instead, they point to small melt volumes, a transient heat pulse, and small thermal mass, and imply efficient physical segregation of silicate and metallic melts through buoyancy separation followed by rapid cooling that arrested the separation of metal and silicate liquid phases. In situ 207 Pb/ 206 Pb age of 4542.3 ± 4.0 Ma in Zr-oxide and phosphate minerals dates the melting event that formed the silicate inclusions. This age aligns with the earliest ages found in other IIE iron meteorite silicates and requires a heating event ~25 million years after the solar system formed. We found 39 Ar/ 40 Ar ages of 3495 ± 52 Ma (low-T) and 4303 ± 7 Ma (high-T) in a K-feldspar grain, with the 3495 Ma age aligning with later thermal events recorded in other IIE iron meteorites. Dating reveals the complex petrogenetic and thermal history of Miles and the IIE iron meteorites. This is the first IIE iron meteorite found to record evidence of heating at 4.5 and 3.5 Ga likely from impact events. We propose that high-velocity impact(s) into an iron-rich, porous chondritic parent body at ~4.54 Ga produced immiscible metal and silicate melts that cooled rapidly and trapped low density silicate inclusions within high density metal. Other IIE irons that formed at lower peak temperatures (900–1000°C) contain chondritic silicate inclusions and relict chondrules, supporting this conceptual model. In conclusion, this petrogenesis is consistent with thermodynamic modelling, experimental data and the wide range of peak temperatures and cooling rates observed in the IIE iron meteorites.

58 GEOSCIENCES↗

A Wrf-Chem Flash Rate Parameterization Scheme and LNO(x) Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were added to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.

Cloud physics↗

A WRF-Chem Flash Rate Parameterization Scheme and LNOx Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were applied to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.

Atmospheric chemistry↗