First integrated core-edge fluid simulation of ITER’s Limiter–Divertor transition with SolEdge-HDG
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Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflow that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. Finally, the NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.
Long time geodetic observation records show that the orientation of the Earth's rotation axis with respect to the terrestrial reference frame, or polar motion, changes on a broad range of timescales. Apart from external torques from the luni-solar tides, these changes are excited by interactions among different components of the Earth system. The convective fluid outer core has long been conjectured a likely contributor to the observed polar motion on timescales upward of decades, such as the 30 year Markowitz wobble. We investigated the electromagnetic coupling scenario across the core-mantle boundary via numerical geodynamo simulation for different geodynamo parameters (Rayleigh numbers and magnetic Rossby numbers). Our simulated polar motion varies strongly with the dynamo parameters, while its excitation on decadal timescales appear to converge asymptotically within the adopted range of numerical Rossby numbers. Three strongest asymptotic modes emerge from numerical results, with periods around 30, 40, and 60 years for the prograde excitation and around 24, 30, and 60 years for the retrograde excitation. Their amplitudes are all larger than 5 times 10 (sup minus 8), or approximately 10 milliseconds of arc.The results suggest that the electromagnetic core-mantle coupling could explain a substantial portion, if not all, of the observed decadal polar motion. In particular, the predicted 60 year polar motion deserves special attention for future observations and studies.
Ice core measurements in conjunction with climate model simulations are of tremendous value when examining anthropogenic and natural aerosol loads and their role in past and future climates. Refractory black carbon (BC) records from the Arctic, the Antarctic, and the Himalayas are analyzed using three transient climate simulations performed with the Goddard Institute for Space Studies ModelE. Simulations differ in aerosol schemes (bulk aerosols vs. aerosol microphysics) and ocean couplings (fully coupled vs. prescribed ocean). Regional analyses for past (1850-2005) and future (2005-2100) carbonaceous aerosol simulations focus on the Antarctic, Greenland, and the Himalayas. Measurements from locations in the Antarctic show clean conditions with no detectable trend over the past 150 years. Historical atmospheric deposition of BC and sulfur in Greenland shows strong trends and is primarily influenced by emissions from early twentieth century agricultural and domestic practices. Models fail to reproduce observations of a sharp eightfold BC increase in Greenland at the beginning of the twentieth century that could be due to the only threefold increase in the North American emission inventory. BC deposition in Greenland is about 10 times greater than in Antarctica and 10 times less than in Tibet. The Himalayas show the most complicated transport patterns, due to the complex terrain and dynamical regimes of this region. Projections of future climate based on the four CMIP5 Representative Concentration Pathways indicate further dramatic advances of pollution to the Tibetan Plateau along with decreasing BC deposition fluxes in Greenland and the Antarctic.
The small energy exchange via nucleon recoils in neutrino–nucleon scattering is now supposed to be one of the important factors for successful explosions of core-collapse supernovae (CCSNe), as they can change neutrino spectra through accumulation of a large number of scatterings. In deterministic methods employed for neutrino transport in CCSN simulations, we normally cannot afford to deploy a large enough number of energy bins needed to resolve this small energy exchange, and subgrid techniques are employed one way or another. In this paper, we study quantitatively with the Monte Carlo (MC) method how well such a treatment performs. We first investigate the effects of nucleon recoils on the neutrino spectra and confirm that the average energy is reduced by ~15% for heavy-lepton neutrinos and much smaller amounts for other types of neutrinos in a typical postbounce situation. It is also observed that the nucleon scattering dominates the electron scattering in the thermalization of neutrino spectra in all flavors. We then study possible artifacts that the coarse energy grid may produce in the deterministic methods. In order to mimic the latter calculation, we redistribute MC particles in each energy bin after a certain interval in a couple of ways and study how the results are affected, depending on the energy resolution. We also discuss the possible implications of our results for the deterministic methods.
Aqua-planet simulations using the Community Atmosphere Model version 4 (CAM4) with the Model for Prediction Across Scales Atmosphere (MPAS-A) and Higher Order Method Modeling Environment (HOMME) dynamical cores and zonally symmetric sea surface temperature (SST) structure are studied to understand the dependence of the inter-tropical convergence zone (ITCZ) structure on resolution and dynamical core. While all resolutions in HOMME and the low-resolution MPAS-A simulations give a single equatorial peak in zonal mean precipitation, the high-resolution MPAS-A simulations give a double ITCZ with precipitation peaking around 2° to 3° on either side of the equator. This study reveals that the structure of ITCZ is dependent on the feedbacks among convection and large-scale circulation and surface heat fluxes. We show that, by increasing convective available potential energy (CAPE) off the equator, the simulations with higher wind induced surface heat fluxes result in double ITCZ structure. This in turn leads to stronger convection and positive feedback with the large-scale circulation. We further show that the dominance of anti-symmetric waves in a model is not enough to cause double ITCZ, and the lateral extent of equatorial waves does not play an important role in determining the width of the ITCZ but rather the latter may influence the former.
ABSTRACT This paper presents the first systematic study of proto-neutron star (PNS) convection in three dimensions (3D) based on our latest numerical fornax models of core-collapse supernova (CCSN). We confirm that PNS convection commonly occurs, and then quantify the basic physical characteristics of the convection. By virtue of the large number of long-term models, the diversity of PNS convective behaviour emerges. We find that the vigour of PNS convection is not correlated with CCSN dynamics at large radii, but rather with the mass of PNS − heavier masses are associated with stronger PNS convection. We find that PNS convection boosts the luminosities of νμ, ντ, $\bar{\nu }_{\mu }$, and $\bar{\nu }_{\tau }$ neutrinos, while the impact on other species is complex due to a competition of factors. Finally, we assess the consequent impact on CCSN dynamics and the potential for PNS convection to generate pulsar magnetic fields.
ABSTRACT There are now 20 multidimensional core-collapse supernova (CCSN) simulations that explode. However, these simulations have explosion energies that are a few times 1050 erg, not 1051 erg. In this manuscript, we compare the inferred explosion energies of these simulations and observations of 40 SN IIP. Assuming a lognormal distribution, the mean explosion energy for these observations is $\mu _{\rm obs} = -0.23^{+0.08}_{-0.12}$ ($\log _{10}(E/10^{51}\, {\rm erg})$) and the width is $\sigma _{\rm obs} = 0.52^{+0.09}_{-0.08}$. Only three CCSN codes have sufficient simulations to compare with observations: CHIMERA, CoCoNuT-FMT, and FORNAX. Currently, FORNAX has the largest sample of simulations. The two-dimensional FORNAX simulations show a correlation between explosion energy and progenitor mass, ranging from linear to quadratic, Esim ∝ M1 − 2; this correlation is consistent with inferences from observations. In addition, we infer the ratio of the observed-to-simulated explosion energies, Δ = log10(Eobs/Esim). For the CHIMERA set, Δ = 0.25 ± 0.07; for CoCoNuT-FMT, Δ = 0.49 ± 0.07; for FORNAX2D, Δ = 0.62 ± 0.06, and for FORNAX3D, Δ = 0.85 ± 0.07. On average, the simulations are less energetic than inferred energies from observations (Δ ≈ 0.6), but we also note that the variation among the simulations [max(Δ) − min(Δ) ≈ 0.6] is as large as this average offset. This suggests that further improvements to the simulations could resolve the discrepancy. Furthermore, both the simulations and observations are heavily biased. In this preliminary comparison, we model these biases, but to more reliably compare the explosion energies, we recommend strategies to unbias both the simulations and observations.
The relevance of the standing accretion shock instability (SASI) compared to neutrino-driven convection in three-dimensional (3D) supernova-core environments is still highly controversial. Studying a 27 M{sub Sun} progenitor, we demonstrate, for the first time, that violent SASI activity can develop in 3D simulations with detailed neutrino transport despite the presence of convection. This result was obtained with the PROMETHEUS-VERTEX code with the same sophisticated neutrino treatment so far used only in one-dimensional and two-dimensional (2D) models. While buoyant plumes initially determine the nonradial mass motions in the postshock layer, bipolar shock sloshing with growing amplitude sets in during a phase of shock retraction and turns into a violent spiral mode whose growth is only quenched when the infall of the Si/SiO interface leads to strong shock expansion in response to a dramatic decrease of the mass accretion rate. In the phase of large-amplitude SASI sloshing and spiral motions, the postshock layer exhibits nonradial deformation dominated by the lowest-order spherical harmonics (l = 1, m = 0, {+-}1) in distinct contrast to the higher multipole structures associated with neutrino-driven convection. We find that the SASI amplitudes, shock asymmetry, and nonradial kinetic energy in three dimensions can exceed those of the corresponding 2D case during extended periods of the evolution. We also perform parameterized 3D simulations of a 25 M{sub Sun} progenitor, using a simplified, gray neutrino transport scheme, an axis-free Yin-Yang grid, and different amplitudes of random seed perturbations. They confirm the importance of the SASI for another progenitor, its independence of the choice of spherical grid, and its preferred growth for fast accretion flows connected to small shock radii and compact proto-neutron stars as previously found in 2D setups.
Yamaguchi and Feingold (2012) note that the cloud fields in their Weather Research and Forecasting (WRF) large-eddy simulations (LESs) of marine stratocumulus exhibit a strong sensitivity to time stepping choices. In this study, we reproduce and analyze this sensitivity issue using two stratocumulus cases, one marine and one continental. Results show that (1) the sensitivity is associated with spurious motions near the moisture jump between the boundary layer and the free atmosphere, and (2) these spurious motions appear to arise from neglecting small variations in water vapor mixing ratio (qv) in the pressure gradient calculation in the acoustic substepping portion of the integration procedure. We show that this issue is remedied in the WRF dynamical core by replacing the prognostic equation for the potential temperature θ with one for the moist potential temperature θm=θ(1+1.61qv), which allows consistent treatment of moisture in the calculation of pressure during the acoustic substeps. With this modification, the spurious motions and the sensitivity to the time stepping settings (i.e., the dynamic time step length and number of acoustic substeps) are eliminated in both of the example stratocumulus cases. This modification improves the applicability of WRF for LES applications, and possibly other models using similar dynamical core formulations, and also permits the use of longer time steps than in the original code.
Core-collapse supernovae (CCSNe), the culmination of massive stellar evolution, are the principle actors in the story of our elemental origins. Our understanding of these events, while still incomplete, centers around a neutrino-driven central engine which is highly hydrodynamically-unstable. Simulations of increasing sophistication show a shock that stalls for hundreds of milliseconds before reviving. Though brought back to life by neutrino heating, the development of the supernova explosion is inextricably linked to three dimensional fluid flows. Regrettably, much of our understanding of the nucleosynthesis that occurs in these explosions, and their impact on galactic chemical evolution, is based on spherically symmetric simulations with parameterized explosions, ignoring much that has been learned about the central engine of these supernovae over the past two decades. Here in this paper we discuss recent results from two-dimensional CCSN simulations using our CHIMERA code, as well as ongoing three-dimensional simulations, and discuss how the multidimensional character of the explosions directly impacts the nucleosynthesis and other observables of core-collapse supernovae.
A new direct numerical simulation (DNS) code for multi-component gaseous reacting flows has been developed at KAUST, with the state-of-the-art programming model for next generation high performance computing platforms. The code, named KAUST Adaptive Reacting Flows Solver (KARFS), employs the MPI+X programming, and relies on Kokkos for “X” for performance portability to multi-core, many-core and GPUs, providing innovative software development while maintaining backward compatibility with established parallel models and legacy code. The capability and potential of KARFS to perform DNS of reacting flows with large, detailed reaction mechanisms is demonstrated with various model problems involving ignition and turbulent flame propagations with varying degrees of chemical complexities.
Abstract Recent studies have highlighted the sensitivity of core-collapse supernovae (CCSNe) models to electron-capture (EC) rates on neutron-rich nuclei near the N = 50 closed-shell region. In this work, we perform a large suite of one-dimensional CCSN simulations for 200 stellar progenitors using recently updated EC rates in this region. For comparison, we repeat the simulations using two previous implementations of EC rates: a microphysical library with parametrized N = 50 rates (LMP), and an older independent-particle approximation (IPA). We follow the simulations through shock revival up to several seconds post-bounce, and show that the EC rates produce a consistent imprint on CCSN properties, often surpassing the role of the progenitor itself. Notable impacts include the timescale of core collapse, the electron fraction and mass of the inner core at bounce, the accretion rate through the shock, the success or failure of revival, and the properties of the central compact remnant. We also compare the observable neutrino signal of the neutronization burst in a DUNE-like detector, and find consistent impacts on the counts and mean energies. Overall, the updated rates result in properties that are intermediate between LMP and IPA, and yet slightly more favorable to explosion than both.
Supercritical carbon dioxide (sc-CO 2 ) is an alternative to water for stimulation of low permeability systems such as shale gas and geothermal resources. Previously core-scale experimental studies have compared the behavior of CO 2 to water injection for sample breakdown. Due to differences in experimental setup and core sample preparation, inconsistent or even apparently contradictory conclusions have resulted. To reconcile this contradiction, a phase-field numerical model is applied to understand hydraulic fracturing experiments using Green River shale found in the literature. The finite element numerical model incorporates a rate-dependent phase-field fracture model developed separately to describe fracture initiation and growth. We investigate the impact of various material and fluid properties on the resulting fractures. Most importantly, we study the effect of fluid properties and boundary conditions on the breakdown pressure, including the direction of the resulting fracture plane. Model results predict that (1) sc-CO 2 injection in the laboratory may result in greater breakdown pressure than that of water under no-flow boundary conditions because lower viscosity sc-CO 2 may result in pressure build up at the core boundary that opposes fracture initiation and (2) lower viscosity sc-CO 2 also produces fast-propagating fractures that are less influenced by the bedding plane on their resulting fracture topology. Here our model offers a straightforward explanation and reconciliation of existing experimental observations, as well as a means to extrapolate to new conditions. Exploration of field-scale conditions suggests less pronounced or no elevation in breakdown pressure when sc-CO 2 is injected because the pressure build up effect at the system boundary is significantly less or absent at field length scales.
A central problem in performing accurate nuclear reactor simulations is the ability to capture the changes in the few group microscopic cross sections as functions of system state, e.g. moderator density, fuel temperature, or neutron spectrum, and time and/or burnup of the fuel. For most reactor simulation scenarios, this results in huge data stream, which must be interpolated as needed by downstream calculations (e.g., core-wide simulation). This is typically accomplished by using sophisticated interpolating functions to capture the few-group variations over the wide range of conditions expected during operation. To address handling this big data, this paper explores the use of dimensionality reduction (DR) techniques to identify the true dimensionality of the data prior to its use in the calculations. This could significantly reduce the computational cost required for data processing/manipulation, thus reducing a significant portion of the total calculations time. By way of an example, in the current version of the ORIGEN-ARP module, the assembly-averaged microscopic cross sections at different conditions, e.g., fuel enrichments, irradiation history and water density, which are calculated using the TRITON sequence and interpolated on-demand by the ARP module to model assembly depletion for a wide range of assembly types (e.g. Westinghouse 17x17 and GE 9x9) over a wide range of conditions. This approach typically results in ∼1 GB per assembly type, which although not insurmountable, can be impractical for distribution. and it is the premise of this paper that most of this data is heavily correlated and hence can take great benefit of condensation via DR. To demonstrate DR, the proposed algorithm is applied to the nuclear data streams generated by SCALE 6.1. Using the depletion sequence (TRITON), microscopic cross sections are calculated for a mixed oxide (MOX) fuel assembly design at a representative range of fuel enrichments and fuel burnup. In conventional core simulators, multi dimensional interpolation of these cross sections is used to provides neutronics feedback due to local conditions without returning to expensive TRITON calculations for every change. This paper shows that dimensionality reduction can help compress the size of the cross section data without sacrificing the accuracy of their reconstruction at all conditions of interest. This work explores the application of dimensionality reduction algorithms to nuclear data streams typically employed in support of conventional full-core reactor calculations which rely on interpolation of pre-calculated microscopic cross sections. In particular, analysis of the few group MOX cross sections revealed that a large degree of dependencies exist between the few-group cross sections, which can be revealed via range-finding algorithms. Specifically, correlations between different reaction types for the same isotope have been identified, and correlations between different enrichments and correlations across different isotopes have been identified. This paper demonstrates that the reduction errors can be quantified, and they are uncorrelated with the range of variations for the various cross sections. In future work, we will focus on identifying the smallest rank that takes into account all types of correlations across the range of conditions used to model cross section variations. (authors)
While there are multiple sources of error that are introduced into the standard computational regime for simulating reactor cores, rigorous uncertainty analysis methods are available primarily for quantifying the effects of cross section uncertainties. Two methods for propagating cross section uncertainties through core simulators are the XSUSA statistical approach and the 'Two-Step' method. The XSUSA approach, which is based on the SUSA code package, is fundamentally a stochastic sampling method. Alternatively, the Two-Step method utilizes generalized perturbation theory in the first step and stochastic sampling in the second step. The consistency of these two methods in quantifying uncertainties in the multiplication factor and in the core power distribution will be examined in the framework of phase 1-3 of the UAM Benchmark. Using the TMI core as a base model for analysis, the XSUSA and Two-Step methods are applied with certain limitations and the results are compared to those produced by other stochastic sampling-based codes. Based on the uncertainty analysis results, conclusions are made for which method is currently a more viable option for computing uncertainties in burnup and transient calculations. (authors)
Ascertaining the core-collapse supernova mechanism is a complex, and yet unsolved, problem dependent on the interaction of general relativity, hydrodynamics, neutrino transport, neutrino-matter interactions, and nuclear equations of state and reaction kinetics. Ab initio modeling of core-collapse supernovae and their nucleosynthetic outcomes requires care in the coupling and approximations of the physical components. We have built our multi-physics CHIMERA code for supernova modeling in 1-, 2-, and 3-D, using ray-by-ray neutrino transport, approximate general relativity, and detailed neutrino and nuclear physics. We discuss some early results from our current series of exploding 2D simulations and our work to perform computationally tractable simulations in 3D using the ``Yin--Yang'' grid.
The desire to accurately model the heterogeneity of the nuclear reactor environment combined with the ever more powerful computational resources have made in recent years the use of Monte Carlo method more attractive and feasible (if challenging) even for 3-D full core depletion simulation. However, in this case statistical uncertainty is combined with error propagating through the calculation from previous steps. In an effort to understand this error propagation, a numerical study was undertaken and previously reported modeling depletion of a four fuel assemblies (a 'quad'). This work extends results and analysis on a full nuclear reactor core depletion simulation where isotopics of individual fuel pins is tracked. By changing the code's initial random number seed, the data produced by a series of 19 replica runs was used to investigate the true and apparent variance in k{sub eff} and pin powers. It is hoped that this results can help to identify some common regularities in the behavior of uncertainty in several key parameters, and ultimately develop a predictive model. (authors)