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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A chain stretch-based gradient-enhanced model for damage and fracture in elastomers

Similar to quasi-brittle materials, it has been recently shown that elastomers can exhibit a macroscopically diffuse damage zone that accompanies the fracture process. In this study, we introduce a stretch-based gradient-enhanced damage (GED) model that allows the fracture to localize and also captures the development of a physically diffuse damage zone. This capability contrasts with the paradigm of the phase field method for fracture, where a sharp crack is numerically approximated in a diffuse manner. Capturing fracture localization and diffuse damage in our approach is achieved by considering nonlocal effects that encompass network topology, heterogeneity, and imperfections. These considerations motivate the use of a statistical damage function dependent upon the nonlocal deformation state. From this model, fracture toughness is realized as an output. While GED models have been classically utilized for damage modeling of structural engineering materials (e.g., concrete), they face challenges when trying to capture the cascade from damage to fracture, often leading to damage zone broadening (de Borst and Verhoosel, 2016). This deficiency contributed to the popularity of the phase-field method over the GED model for elastomers and other quasi-brittle materials. Other groups have proceeded with damage-based GED formulations that prove identical to the phase-field method (Lorentz et al., 2012), but these inherit the aforementioned limitations. To address this issue in a thermodynamically consistent framework, we implement two modeling features (a nonlocal driving force bound and a simple relaxation function) specifically designed to capture the evolution of a physically meaningful damage field and the simultaneous localization of fracture, thereby overcoming a longstanding obstacle in the development of these nonlocal strain- or stretch-based approaches. Here, we discuss several numerical examples to understand the features of the approach at the limit of incompressibility, and compare them to the phase-field method as a benchmark for the macroscopic response and fracture energy predictions.

Elastomers↗
DOE OSTI2014

Probing the mysteries of the X-ray binary 4U 1210-64 with ASM, PCA, MAXI, BAT, and Suzaku

4U 1210-64 has been postulated to be a high-mass X-ray binary powered by the Be mechanism. X-ray observations with Suzaku, the ISS Monitor of All-sky X-ray Image (MAXI), and the Rossi X-ray Timing Explorer Proportional Counter Array (PCA) and All Sky Monitor (ASM) provide detailed temporal and spectral information on this poorly understood source. Long-term ASM and MAXI observations show distinct high and low states and the presence of a 6.7101 ± 0.0005 day modulation, interpreted as the orbital period. Folded light curves reveal a sharp dip, interpreted as an eclipse. To determine the nature of the mass donor, the predicted eclipse half-angle was calculated as a function of inclination angle for several stellar spectral types. The eclipse half-angle is not consistent with a mass donor of spectral type B5 V; however, stars with spectral types B0 V or B0-5 III are possible. The best-fit spectral model consists of a power law with index Γ = 1.85{sub −0.05}{sup +0.04} and a high-energy cutoff at 5.5 ± 0.2 keV modified by an absorber that fully covers the source as well as partially covering absorption. Emission lines from S XVI Kα, Fe Kα, Fe XXV Kα, and Fe XXVI Kα were observed in the Suzaku spectra. Out of eclipse, the Fe Kα line flux was strongly correlated with unabsorbed continuum flux, indicating that the Fe I emission is the result of fluorescence of cold dense material near the compact object. The Fe I feature is not detected during eclipse, further supporting an origin close to the compact object.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Features of Short-Period Oscillations of Microwave Emission from the Solar Active Region before the Flare

The radiation of microwave sources above sunspots at a frequency of 17 GHz gives information about the parameters of solar plasma in the regions where the magneti-field strength is B ~ 2000 G in the transition region between the chromosphere and corona. Short-period oscillations (with a period of several minutes) of microwave emission from solar active regions (ARs) reflect wave processes in magnetic flux tubes of sunspots. Short-period oscillations of microwave emission from AR NOAA 12242 before two flares on December 17, 2014 are analyzed. This analysis is based on solar radio images obtained by means of the Nobeyama Radio Heliograph with a 10″−15″ two-dimensional spatial resolution. The radio maps of the whole solar disk were synthesized in a nonstandard mode with a cadence of 10 s and an averaging time of 10 s. An increase in the power of about ten-minute oscillations of microwave radiation approximately 40 to 50 min before the M1.5 flare (01: 00 UT) is found. On the same day, an increase in the power of ten-minute oscillations is observed about 60 min before the M8.7 flare (04: 42 UT). This effect is similar to the effect found earlier by two groups of authors independently for three-minute oscillations—namely, they observed a sharp increase in three-minute oscillations 15 to 20 min before the radio burst accompanying the flare. The effect in question may be interpreted as an relationship ofMHD waves propagating along the magnetic flux tube of a sunspot and the onset of the solar flare.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Overcharge investigation of large format lithium-ion pouch cells with Li(Ni 0.6 Co 0.2 Mn 0.2 )O 2 cathode for electric vehicles: Thermal runaway features and safety management method

The overcharge-induced thermal runaway features of large format commercial lithium-ion batteries with Li(Ni 0.6 Co 0.2 Mn 0.2 )O 2 (NCM622) cathode for electric vehicles under different current rates (C-rates) have been systematically studied at ambient temperature. The overcharge process is characterized as four stages. The temperature rise and the maximum temperature of the battery surface don't increase in proportion to the applied C-rates. However, with the increase of C-rates, the crest voltage of voltage curve rises linearly. When the voltage reaches approximately 5.1 V, a new voltage plateau appears in the cases below 2C. It is not sufficient that the temperature sensor is placed only near the terminal tab for most battery packs of EVs. In addition, the accumulated heat analysis demonstrates that side reactions dominate the temperature rise and contribute to most of the accumulated heat before thermal runaway. To mitigate the impact of overcharge and avoid the thermal runaway risk, a safety management method is proposed. Furthermore, the sharp drop in voltage before thermal runaway also provides a feasible approach to forewarn the users of the impending risk. These results are important for building safer batteries and providing information for the safety monitoring function of the battery management system (BMS).

25 ENERGY STORAGE↗
DOE OSTI2012

Non-destructive characterisation of polymers and Al-alloys by polychromatic cone-beam phase contrast tomography

X-ray computed tomography (XCT) has become a very important tool for the non-destructive characterisation of materials. Continuous improvements in the quality and performance of X-ray tubes and detectors have led to cone-beam XCT systems that can now achieve spatial resolutions down to 1 {mu}m and even below. Since not only the amplitude but also the phase of an X-ray beam is altered while passing through an object, phase contrast effects can occur even for polychromatic sources when the spatial coherence due to a small focal spot size is high enough. This can lead to significant improvements over conventional attenuation-based X-ray computed tomography. Phase contrast can increase by edge enhancement the visibility of small structures and of features which are only slightly different in attenuation. We report on the possibilities of polychromatic cone-beam phase contrast tomography for non-destructive characterisation of materials. A carbon fibre-reinforced polymer and the Al-alloys AlMg5Si7 and AlSi18 were investigated with high resolution cone-beam X-ray computed tomography with a polychromatic tube source. Under certain conditions strong phase contrast resulting in an upward and downward overshooting of the grey values across edges was observed. The phase effects are much stronger for the polymer than for the Al-alloys. The influence on the phase contrast of the parameters, including source-detector distance, focal spot size and tube acceleration voltage is presented. Maximum phase contrast was observed for a maximum distance between the source and the detector, for a low voltage and a minimum focal spot size at the X-ray source. The detectability of the different phases is improved by the edge enhancement and the resulting improvement of sharpness. Thus, a better segmentation of the carbon fibres in the fibre-reinforced polymer and of the Mg{sub 2}Si-phase in the AlMg5Si7-alloy is achieved. Primary and eutectic Si cannot be detected by attenuation-based X-ray computed tomography due to the small difference in X-ray attenuation between the Si and the Al-matrix in AlSi18. However, phase contrast effects lead to a significant detectability and the large primary Si particles become clearly visible in the tomograms of AlSi18. - Highlights: Black-Right-Pointing-Pointer Phase contrast increases with increasing distance object-detector and with decreasing U, X-ray spot. Black-Right-Pointing-Pointer The detectability of details is improved by the phase contrast. Black-Right-Pointing-Pointer For the carbon fibre-reinforced polymer the visibility of the carbon fibres is improved. Black-Right-Pointing-Pointer For AlMg5Si7 the detectability of the phases Fe-aluminides and Mg{sub 2}Si particles is improved. Black-Right-Pointing-Pointer For AlSi18 primary Si particles with a size > 50 {mu}m become detectable because of the phase contrast.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unusual magnetotransport in twisted bilayer graphene from strain-induced open Fermi surfaces

Anisotropic hopping in a toy Hofstadter model was recently invoked to explain a rich and surprising Landau spectrum measured in twisted bilayer graphene away from the magic angle. Suspecting that such anisotropy could arise from unintended uniaxial strain, we extend the Bistritzer–MacDonald model to include uniaxial heterostrain and present a detailed analysis of its impact on band structure and magnetotransport. We find that such strain strongly influences band structure, shifting the three otherwise-degenerate van Hove points to different energies. Coupled to a Boltzmann magnetotransport calculation, this reproduces previously unexplained nonsaturating B 2 magnetoresistance over broad ranges of density near filling ν = ± 2 and predicts subtler features that had not been noticed in the experimental data. In contrast to these distinctive signatures in longitudinal resistivity, the Hall coefficient is barely influenced by strain, to the extent that it still shows a single sign change on each side of the charge neutrality point—surprisingly, this sign change no longer occurs at a van Hove point. The theory also predicts a marked rotation of the electrical transport principal axes as a function of filling even for fixed strain and for rigid bands. More careful examination of interaction-induced nematic order versus strain effects in twisted bilayer graphene could thus be in order.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Mechanism and Kinetics for Reaction of the Chemical Warfare Agent Simulant, DMMP( g ), with Zirconium(IV) MOFs: An Ultrahigh-Vacuum and DFT Study

The mechanism and kinetics of interactions between dimethyl methylphosphonate (DMMP), a key chemical warfare agent (CWA) simulant, and Zr 6 -based metal organic frameworks (MOFs) have been investigated with in situ infrared spectroscopy (IR), X-ray photoelectron spectroscopy (XPS), powder X-ray diffraction (PXRD), and DFT calculations. DMMP was found to adsorb molecularly to UiO-66 through the formation of hydrogen bonds between the phosphoryl oxygen and the free hydroxyl groups associated with Zr 6 nodes on the surface of crystallites and not within the bulk MOF structure. Unlike UiO-66, the infrared spectra for UiO-67 and MOF-808, recorded during DMMP exposure, suggest that uptake occurs through both physisorption and chemisorption. The XPS spectra of MOF-808 zirconium 3d electrons reveal a charge redistribution following exposure to DMMP. In addition, analysis of the phosphorus 2p electrons following exposure and thermal annealing to 600 K indicates that two types of stable phosphorus-containing species exist within the MOF. DFT calculations, used to guide the IR band assignments and to help interpret the XPS features, suggest that uptake is driven by nucleophilic addition of an OH group to DMMP with subsequent elimination of a methoxy substituent to form strongly bound methyl methylphosphonic acid (MMPA). The rates of product formation indicate that there are likely two distinct uptake processes, requiring rate constants that differ by approximately an order of magnitude. However, the rates of molecular uptake were found to be nearly identical to the rates of reaction, which strongly suggests that the reaction rates are diffusion-limited. Here, the final products were found to inhibit further reactions within the MOFs, and these products could not be thermally driven from the MOFs prior to decomposition of the MOFs themselves.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Fully implicit crystal plasticity models representing orientations with modified Rodrigues parameters

Here, this work describes a crystal plasticity formulation combining several mathematical, numerical, and implementation choices to produce a highly efficient model. Specifically, the key choices in the implementation are (1) representing orientations with modified Rodrigues parameters, (2) implementing a fully coupled implicit time integration for the elastic stretch, the crystal orientations, and the model internal variables, (3) implementing the model in the NEML2 constitutive modeling framework, based on PyTorch, to vectorize the calculations and port the computation to GPUs and other hardware accelerators, and (4) an exact implementation of the consistent tangent matrix, even for arbitrary coupling to other field variables beyond the displacements, like temperature, neutron fluence, etc. The first two features of the model are, to our knowledge, novel. The paper considers each of these choices individually as well as the final model as a whole. This includes a full description of modified Rodrigues parameters, their advantages over other representations of orientations, the mathematical formulae and tools required to implement a model with modified Rodrigues parameters, and a detailed description of the geometry of the space of modified Rodrigues parameters (in an appendix). It also includes a description of a fully implicit time integration scheme for the orientations and the advantages in representing orientations with modified Rodrigues parameters in implementing such a model. The work then assess, via numerical examples, the advantages of fully coupled implicit time integration versus more common decoupled and explicit time integration schemes. These studies demonstrate the computational advantages of fully coupled integration versus other time integration algorithms, though the performance of the competing models depends on the complexity of the underlying single crystal model. The study concludes by demonstrating that the choice of time integration method affects the sharpness of the predicted texture, with explicit methods for integrating the orientations overestimating texture sharpness and implicit methods underestimating texture sharpness.

Crystal plasticity↗
DOE OSTI2014

Particle concentration at planet-induced gap edges and vortices. I. Inviscid three-dimensional hydro disks

We perform a systematic study of the dynamics of dust particles in protoplanetary disks with embedded planets using global two-dimensional and three-dimensional inviscid hydrodynamic simulations. Lagrangian particles have been implemented into the magnetohydrodynamic code Athena with cylindrical coordinates. We find two distinct outcomes depending on the mass of the embedded planet. In the presence of a low-mass planet (8 M {sub ⊕}), two narrow gaps start to open in the gas on each side of the planet where the density waves are shocked. These shallow gaps can dramatically affect particle drift speed and cause significant, roughly axisymmetric dust depletion. On the other hand, a more massive planet (>0.1 M{sub J} ) carves out a deeper gap with sharp edges, which are subject to Rossby wave instability leading to vortex formation. Particles with a wide range of sizes (0.02 < Ωt{sub s} < 20) are trapped and settle to the midplane in the vortex, with the strongest concentration for particles with Ωt{sub s} ∼ 1. The dust concentration is highly elongated in the φ direction, and can be as wide as four disk scale heights in the radial direction. Dust surface density inside the vortex can be increased by more than a factor of 10{sup 2} in a very non-axisymmetric fashion. For very big particles (Ωt{sub s} >> 1) we find strong eccentricity excitation, in particular around the planet and in the vicinity of the mean motion resonances, facilitating gap openings there. Our results imply that in weakly turbulent protoplanetary disk regions (e.g., the {sup d}ead zone{sup )} dust particles with a very wide range of sizes can be trapped at gap edges and inside vortices induced by planets with M{sub p} < M{sub J} , potentially accelerating planetesimal and planet formation there, and giving rise to distinctive features that can be probed by ALMA and the Extended Very Large Array.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Inferring Stochastic Rates from Heterogeneous Snapshots of Particle Positions

Many imaging techniques for biological systems—like fixation of cells coupled with fluorescence microscopy—provide sharp spatial resolution in reporting locations of individuals at a single moment in time but also destroy the dynamics they intend to capture. In this study, these snapshot observations contain no information about individual trajectories, but still encode information about movement and demographic dynamics, especially when combined with a well-motivated biophysical model. The relationship between spatially evolving populations and single-moment representations of their collective locations is well-established with partial differential equations (PDEs) and their inverse problems. However, experimental data is commonly a set of locations whose number is insufficient to approximate a continuous-in-space PDE solution. Here, motivated by popular subcellular imaging data of gene expression, we embrace the stochastic nature of the data and investigate the mathematical foundations of parametrically inferring demographic rates from snapshots of particles undergoing birth, diffusion, and death in a nuclear or cellular domain. Toward inference, we rigorously derive a connection between individual particle paths and their presentation as a Poisson spatial process. Using this framework, we investigate the properties of the resulting inverse problem and study factors that affect quality of inference. One pervasive feature of this experimental regime is the presence of cell-to-cell heterogeneity. Rather than being a hindrance, we show that cell-to-cell geometric heterogeneity can increase the quality of inference on dynamics for certain parameter regimes. Altogether, the results serve as a basis for more detailed investigations of subcellular spatial patterns of RNA molecules and other stochastically evolving populations that can only be observed for single instants in their time evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

OzDES Reverberation Mapping Programme: the first Mg ii lags from 5 yr of monitoring

ABSTRACT Reverberation mapping is a robust method to measure the masses of supermassive black holes outside of the local Universe. Measurements of the radius–luminosity (R−L) relation using the Mg ii emission line are critical for determining these masses near the peak of quasar activity at z ≈ 1−2, and for calibrating secondary mass estimators based on Mg ii that can be applied to large samples with only single-epoch spectroscopy. We present the first nine Mg ii lags from our 5-yr Australian Dark Energy Survey reverberation mapping programme, which substantially improves the number and quality of Mg ii lag measurements. As the Mg ii feature is somewhat blended with iron emission, we model and subtract both the continuum and iron contamination from the multiepoch spectra before analysing the Mg ii line. We also develop a new method of quantifying correlated spectroscopic calibration errors based on our numerous, contemporaneous observations of F-stars. The lag measurements for seven of our nine sources are consistent with both the H β and Mg ii R−L relations reported by previous studies. Our simulations verify the lag reliability of our nine measurements, and we estimate that the median false positive rate of the lag measurements is $4{{\ \rm per\ cent}}$.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

CisSERS: Customizable In Silico Sequence Evaluation for Restriction Sites

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. Cis SERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated to enhance the usefulness of the software. Cis SERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, Cis SERS utilizes the REBASE enzyme database. Results from Cis SERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. Cis SERS is a java based graphical user interface built around a perl backbone. Several of the applications of Cis SERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool Cis SERSand results from in-silico and corresponding wet-lab analyses demonstrating that Cis SERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Enzyme Induced Formation of Monodisperse Hydrogel Nanoparticles Tunable in Size

Here, we report a novel approach to synthesize monodisperse hydrogel nanoparticles that are tunable in size. The distinctive feature of our approach is the use of a multicopper oxidase enzyme, laccase, as both a biocatalyst and template for nanoparticle growth. We utilize the ferroxidase activity of laccase to initiate localized production of iron(III) cations from the oxidation of iron(II) cations. We demonstrate that nanoparticles are formed in a dilute polymer solution of alginate as a result of cross-linking between alginate and enzymatically produced iron(III) cations. Exerting control over the enzymatic reaction allows for nanometer-scale tuning of the hydrogel nanoparticle radii in the range of 30–100 nm. Moreover, the nanoparticles and their growth kinetics were characterized via dynamic light scattering, atomic force microscopy, and UV–vis spectroscopy. Our finding opens up a new avenue for the synthesis of tunable nanoscale hydrogel particles for biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Kinetics of solid–liquid interface motion in molecular dynamics and phase-field models: crystallization of chromium and silicon

The results of molecular dynamics (MD) simulations of the crystallization process in one-component materials and solid solution alloys reveal a complex temperature dependence of the velocity of the crystal–liquid interface featuring an increase up to a maximum at 10–30% undercooling below the equilibrium melting temperature followed by a gradual decrease of the velocity at deeper levels of undercooling. At the qualitative level, such non-monotonous behaviour of the crystallization front velocity is consistent with the diffusion-controlled crystallization process described by the Wilson–Frenkel model, where the almost linear increase of the interface velocity in the vicinity of melting temperature is defined by the growth of the thermodynamic driving force for the phase transformation, while the decrease in atomic mobility with further increase of the undercooling drives the velocity through the maximum and into a gradual decrease at lower temperatures. At the quantitative level, however, the diffusional model fails to describe the results of MD simulations in the whole range of temperatures with a single set of parameters for some of the model materials. The limited ability of the existing theoretical models to adequately describe the MD results is illustrated in the present work for two materials, chromium and silicon. It is also demonstrated that the MD results can be well described by the solution following from the hodograph equation, previously found from the kinetic phase-field model (kinetic PFM) in the sharp interface limit. The ability of the hodograph equation to describe the predictions of MD simulation in the whole range of temperatures is related to the introduction of slow (phase field) and fast (gradient flow) variables into the original kinetic PFM from which the hodograph equation is obtained. The slow phase-field variable is responsible for the description of data at small undercoolings and the fast gradient flow variable accounts for local non-equilibrium effects at high undercoolings. The introduction of these two types of variables makes the solution of the hodograph equation sufficiently flexible for a reliable description of all nonlinearities of the kinetic curves predicted in MD simulations of Cr and Si. This article is part of the theme issue ‘Transport phenomena in complex systems (part 1)’.

Science & Technology - Other Topics↗
DOE OSTI2022

FSISPH: An SPH formulation for impacts between dissimilar materials

Here, we present an SPH formulation with several new features designed to better model the fully-compressible interaction of dissimilar materials. We developed the new method to simulate the atmospheric entry and break-up of small celestial bodies in planetary atmospheres. The formulation uses a unity-based, density-energy discretization of the hydrodynamic conservation laws with linear-corrected kernel gradients. To account for variations in compressibility, we use an HLLC approximate Riemann solver to adjust the velocity gradient at material interfaces. To handle large transverse velocity discontinuities, we introduce a simple slip interface model that limits the artificial viscosity at material interfaces. Diffusion is optionally applied through the velocity gradient and this allows the density and specific thermal energy to evolve in a manner more consistent with the first law of thermodynamics in comparison to other more direct diffusion schemes. We also introduce a material-local second-order artificial conduction scheme used to smooth the specific thermal energy field. Material damage fits neatly under this framework by treating the damage front as a material interface. The method has been implemented as a solver, FSISPH, within the code, Spheral++, and is publicly available on github. We test our new solver on a number of classic shock, mixing, and multi-material problem. The components we outline can significantly improve accuracy of SPH for problems with sharp contact discontinuities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗