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At least 1,009 records · Page 56

Predicting resistive wall mode stability in NSTX through balanced random forests and counterfactual explanations

Abstract Recent progress in the disruption event characterization and forecasting framework has shown that machine learning guided by physics theory can be easily implemented as a supporting tool for fast computations of ideal stability properties of spherical tokamak plasmas. In order to extend that idea, a customized random forest (RF) classifier that takes into account imbalances in the training data is hereby employed to predict resistive wall mode (RWM) stability for a set of high beta discharges from the NSTX spherical tokamak. More specifically, with this approach each tree in the forest is trained on samples that are balanced via a user-defined over/under-sampler. The proposed approach outperforms classical cost-sensitive methods for the problem at hand, in particular when used in conjunction with a random under-sampler, while also resulting in a threefold reduction in the training time. In order to further understand the model’s decisions, a diverse set of counterfactual explanations based on determinantal point processes (DPP) is generated and evaluated. Via the use of DPP, the underlying RF model infers that the presence of hypothetical magnetohydrodynamic activity would have prevented the RWM from concurrently going unstable, which is a counterfactual that is indeed expected by prior physics knowledge. Given that this result emerges from the data-driven RF classifier and the use of counterfactuals without hand-crafted embedding of prior physics intuition, it motivates the usage of counterfactuals to simulate real-time control by generating the β N levels that would have kept the RWM stable for a set of unstable discharges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Energy and particle balance during plasma detachment in a long-leg divertor configuration

Abstract Comprehensive studies of energy and particle balances in the transition to plasma detachment in an alternative divertor configuration with long outer legs are shown. Numerical simulations are performed with the 2D code suite SOLPS 4.3, using a disconnected double null grid with narrow, tightly baffled long poloidal leg divertors at the outer lower target and outer upper target. A particle count scan is performed using the ‘closed gas box’ model, where the tunable parameter in the simulations is the total number of deuterium particles in the simulation space and all other parameters are held fixed, including a constant input power and trace neon impurity radiation, to assess the physics of the transition to detachment in the system as the particle count increases. Three main aspects of the physics of divertor detachment are addressed: the criteria for the local onset of divertor detachment in each of the divertors, the distribution of heat flux and other plasma parameters between the four divertors as each divertor transitions to detachment, and the role of perpendicular transport in the transition to the detached regime. A synergistic mechanism by which the cross-field transport is reduced by factors associated with the onset of plasma recombination effects is identified. These results are compared to the existing understanding of the physics of the transition to plasma detachment in standard divertors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Investigation of performance enhancement by balanced double-null shaping in KSTAR

We report experimental observations on the effect of plasma boundary shaping towards balanced double-null (DN) configuration on the plasma performance in KSTAR. The transition from a single-null to a DN configuration resulted in improved plasma performance, manifested through changes in the pedestal region, decreased density, and core MHD activity variation. Specifically, the DN transition led to a wider and higher pedestal structure, accompanied by grassy edge-localized modes (ELMs) characteristics. The density decrease was a prerequisite for performance enhancement during DN shaping, increasing fast ion confinement. Optimizing the plasma near the core region was associated with the suppression of sawtooth instabilities and the occurrence of fishbone modes during the DN transition. Integrated modeling demonstrated that secondary effects of the DN shaping could increase core thermal energy confinement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Power balance and divertor asymmetries in the Super-X divertors of MAST-U using SOLPS-ITER

Spherical tokamaks (STs) present unique challenges and opportunities in the area of particle and power exhaust, intensified due to their more compact sizes. Substantial efforts are underway in STs to determine the limits in dissipative operational regimes and advanced divertor solutions, including at MAST-U which provides access to the Super-X divertor configuration. Power balance, and upper/lower divertor asymmetries have been studied using SOLPS-ITER simulations of the MAST-U Super-X divertor. A set of simulations with experimentally inferred transport coefficients with E x B and diamagnetic drifts activated, consisting of density and power scans, and high field side vs low field side gas puff locations, have been used for code experimentation to uncover trends beyond the current experimental parameter space. The upper biased asymmetry (U:L > 1) of the ratio of the peaks of the plasma energy flux densities at the outer targets increases with heating power and decreases with gas puff strength, going from symmetric to up to a factor of 15. The upper target electron temperature has been found to be a good ordering quantity for the magnitude of this asymmetry for all heating powers, gas puff strength, and gas puff locations. The lower divertor biased asymmetry (U:L < 1) of the radiation patterns processed through SOLPS-based bolometry synthetic diagnostics is in qualitative agreement with resistive bolometry experimental results, and it is in quantitative agreement with the trend of the total volume radiation within the divertors of SOLPS. However, radiation measurements alone are not sufficient to infer the magnitude of the asymmetry of the peaks of the power loads at the targets.

MAST-U↗

A simple model of hohlraum power balance and mitigation of SRS

A simple energy balance model has been obtained for laser-plasma heating in indirect drive hohlraum plasma that allows rapid temperature scaling and evolution with parameters such as plasma density and composition. Furthermore, this model enables assessment of the effects on plasma temperature of, e.g., adding high-Z dopant to the gas fill or magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spectroscopy can predict key leaf traits associated with source–sink balance and carbon–nitrogen status

Approaches that enable high-throughput, non-destructive measurement of plant traits are essential for programs seeking to improve crop yields through physiological breeding. However, many key traits still require measurement using slow, labor intensive and destructive approaches. We investigated the potential to retrieve key traits associated with leaf source–sink balance and carbon–nitrogen status from leaf optical properties. Structural and biochemical traits and leaf reflectance (500–2400 nm) of eight crop species were measured and used to develop predictive “spectra–trait” models using partial least squares regression. Independent validation data demonstrated that the models achieved very high predictive power for C, N, C:N ratio, leaf mass per area, water content and protein content (R 2 > 0.85), good predictive capability for starch, sucrose, glucose and free amino acids (R 2 = 0.58–0.80) and some predictive capability for nitrate (R 2 = 0.51) and fructose (R 2 = 0.44). As a result, our spectra–trait models were developed to cover the trait space associated with food or biofuel crop plants and can therefore be applied in a broad range of phenotyping studies.

54 ENVIRONMENTAL SCIENCES↗

Energy balance and Alfvén Mach numbers in compressible magnetohydrodynamic turbulence with a large-scale magnetic field

Energy equipartition is a powerful theoretical tool for understanding astrophysical plasmas. It is invoked, for example, to measure magnetic fields in the interstellar medium (ISM), as evidence for small-scale turbulent dynamo action, and, in general, to estimate the energy budget of star-forming molecular clouds. Here, in this study, we motivate and explore the role of the volume-averaged root-mean-squared (rms) magnetic coupling term between the turbulent, δB , and large-scale, B 0 , fields, $\langle$(δB·B 0 ) 2 $\rangle$$_{V}^{1/2}$. By considering the second moments of the energy balance equations we show that the rms coupling term is in energy equipartition with the volume-averaged turbulent kinetic energy for turbulence with a sub-Alfvénic large-scale field. Under the assumption of exact energy equipartition between these terms, we derive relations for the magnetic and coupling term fluctuations, which provide excellent, parameter-free agreement with time-averaged data from 280 numerical simulations of compressible magnetohydrodynamic (MHD) turbulence. Furthermore, we explore the relation between the turbulent mean field and total Alfvén Mach numbers, and demonstrate that sub-Alfvénic turbulence can only be developed through a strong, large-scale magnetic field, which supports an extremely super-Alfvénic turbulent magnetic field. This means that the magnetic field fluctuations are significantly subdominant to the velocity fluctuations in the sub-Alfvénic large-scale field regime. Throughout our study, we broadly discuss the implications for observations of magnetic fields and understanding the dynamics in the magnetized ISM.

79 ASTRONOMY AND ASTROPHYSICS↗

Living with high potassium: Balance between nutrient acquisition and K-induced salt stress signaling

High potassium (K) in the growth medium induces salinity stress in plants. However, the molecular mechanisms underlying plant responses to K-induced salt stress are virtually unknown. We examined Arabidopsis (Arabidopsis thaliana) and its extremophyte relative Schrenkiella parvula using a comparative multiomics approach to identify cellular processes affected by excess K and understand which deterministic regulatory pathways are active to avoid tissue damages while sustaining growth. Arabidopsis showed limited capacity to curb excess K accumulation and prevent nutrient depletion, contrasting to S. parvula which could limit excess K accumulation without restricting nutrient uptake. A targeted transcriptomic response in S. parvula promoted nitrogen uptake along with other key nutrients followed by uninterrupted N assimilation into primary metabolites during excess K-stress. This resulted in larger antioxidant and osmolyte pools and corresponded with sustained growth in S. parvula. Antithetically, Arabidopsis showed increased reactive oxygen species levels, reduced photosynthesis, and transcriptional responses indicative of a poor balance between stress signaling, subsequently leading to growth limitations. Furthermore, our results indicate that the ability to regulate independent nutrient uptake and a coordinated transcriptomic response to avoid nonspecific stress signaling are two main deterministic steps toward building stress resilience to excess K + -induced salt stress.

59 BASIC BIOLOGICAL SCIENCES↗

Selection Metric for Photovoltaic Materials Screening Based on Detailed-Balance Analysis

The success of recently discovered absorber materials for photovoltaic applications has been generating increasing interest in systematic materials screening over the last years. However, the key for a successful materials screening is a suitable selection metric that goes beyond the Shockley-Queisser theory that determines the thermodynamic efficiency limit of an absorber material solely by its band-gap energy. Here, we develop a selection metric to quantify the potential photovoltaic efficiency of a material. Our approach is compatible with detailed balance and applicable in computational and experimental materials screening. We use the complex refractive index to calculate radiative and nonradiative efficiency limits and the respective optimal thickness in the high mobility limit. We also compare our model to the widely applied selection metric by Yu and Zunger [Phys. Rev. Lett. 108, 068701 (2012)] with respect to their dependence on thickness, internal luminescence quantum efficiency, and refractive index. Finally, the model is applied to complex refractive indices calculated via electronic structure theory.

14 SOLAR ENERGY↗

Nonadiabatic quantum molecular dynamics with detailed balance

In this paper, we present an approach for carrying out nonadiabatic molecular dynamics simulations of systems in which nonadiabatic transitions arise from the coupling between the classical atomic motions and a quasicontinuum of electronic quantum states. Such conditions occur in many research areas, including chemistry at metal surfaces, radiation damage of materials, and warm-dense-matter physics. The classical atomic motions are governed by stochastic Langevin-like equations, while the quantum electron dynamics is described by a master equation for the populations of the electronic states. These working equations are obtained from a first-principles derivation. Remarkably, unlike the widely used Ehrenfest and surface-hopping methods, the approach naturally satisfies the principle of detailed balance at equilibrium and therefore can describe the evolution to thermal equilibrium from an arbitrary initial state. Lastly, a practical algorithm is cast in the form of the widely used fewest-switches surface-hopping algorithm but with switching probabilities that are not specified ad hoc like in the standard algorithm but are instead derived.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Internal energy balance and aerodynamic heating predictions for hypersonic turbulent boundary layers

The elemental equation governing heat transfer in aerodynamic flows is the internal energy equation. For a boundary layer flow, a double integration of the Reynolds-averaged form of this equation provides an expression of the wall heat flux in terms of the integrated effects, over the boundary layer, of various physical processes: turbulent dissipation, mean dissipation, turbulent heat flux, etc. Recently available direct numerical simulation data for a Mach 11 cold-wall turbulent boundary layer allows a comparison of the exact contributions of these terms in the energy equation to the wall heat flux with their counterparts modeled in the Reynolds-averaged Navier-Stokes (RANS) framework. Various approximations involved in RANS, both closure models as well as approximations involved in adapting incompressible RANS models to a compressible form, are assessed through examination of the internal energy balance. There are a number of potentially problematic assumptions and terms identified through this analysis. Here, the effect of compressibility corrections of the dilatational dissipation type is explored, as is the role of the modeled turbulent dissipation, in the context of wall heat flux predictions. The results indicate several potential avenues for RANS model improvement for hypersonic cold-wall boundary-layer flows.

42 ENGINEERING↗

Spectral Filtering Induced by Non-Hermitian Evolution with Balanced Gain and Loss: Enhancing Quantum Chaos

Here, the dynamical signatures of quantum chaos in an isolated system are captured by the spectral form factor, which exhibits as a function of time a dip, a ramp, and a plateau, with the ramp being governed by the correlations in the level spacing distribution. While decoherence generally suppresses these dynamical signatures, the nonlinear non-Hermitian evolution with balanced gain and loss (BGL) in an energy-dephasing scenario can enhance manifestations of quantum chaos. In the Sachdev-Ye-Kitaev model and random matrix Hamiltonians, BGL increases the span of the ramp, lowering the dip as well as the value of the plateau, providing an experimentally realizable physical mechanism for spectral filtering. The chaos enhancement due to BGL is optimal over a family of filter functions that can be engineered with fluctuating Hamiltonians.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dynamics and Power Balance of Near Unity Target Gain Inertial Confinement Fusion Implosions

The change in the power balance, temporal dynamics, emission weighted size, temperature, mass, and areal density of inertially confined fusion plasmas have been quantified for experiments that reach target gains up to 0.72. It is observed that as the target gain rises, increased rates of self-heating initially overcome expansion power losses. This leads to reacting plasmas that reach peak fusion production at later times with increased size, temperature, mass and with lower emission weighted areal densities. Analytic models are consistent with the observations and inferences for how these quantities evolve as the rate of fusion self-heating, fusion yield, and target gain increase. At peak fusion production, it is found that as temperatures and target gains rise, the expansion power loss increases to a near constant ratio of the fusion self-heating power. Finally, this is consistent with models that indicate that the expansion losses dominate the dynamics in this regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Zonal magnetic fields regulate nonlinear edge-localized-mode dynamics via self-consistent force balance

Edge-localized modes (ELMs) eject intense bursts of heat and particles that threaten plasma-facing components in fusion reactors. Nonlinear full-torus BOUT++ simulations show that turbulence-driven zonal magnetic fields (ZMFs) play an essential role in nonlinear ELM evolution by maintaining self-consistent force balance. Zonal flows mitigate the initial crash through shear but do not prevent continued radial transport. When ZMFs are self-consistently included, turbulence-driven zonal currents modify the parallel current distribution and magnetic tension and are associated with a reduction of the axisymmetric (𝑛 = 0) perturbed radial force imbalance. This coincides with a transition from convective, bursty propagation to more localized, diffusive transport. Similar behavior is observed across the regimes considered, including both resistive-ballooning and peeling-ballooning cases. Finally, associated signatures, including radial electric field shear and parallel current redistribution, provide experimentally accessible diagnostics for present devices and ITER-relevant conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

(NH 4 ) 2 [UO 2 Cl 4 ]·2H 2 O, a new uranyl tetrachloride with ammonium charge-balancing cations

A new uranyl tetrachloride salt with chemical formula, (NH 4 ) 2 [UO 2 Cl 4 ]·2H 2 O, namely, diammonium uranyl tetrachloride dihydrate, 1 , was prepared and crystallized via slow evaporation from a solution of 2 M hydrochloric acid. As confirmed by powder X-ray diffraction, the title compound crystallizes with an ammonium chloride impurity that formed as a result of the breakdown of a triazine precursor. The (UO 2 Cl 4 ) 2− dianion is charge balanced by ammonium cations, while an extensive hydrogen-bond network donated from structural water molecules stabilize the overall assembly. Compound 1 adds to the extensive collection of actinyl tetrachloride salts, but it represents the first without an alkali cation for purely inorganic compounds. Diffuse reflectance and luminescence spectra show typical absorption and emission behavior, respectively, of uranyl materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Transformer Flux Balancing Scheme Based on Magnetizing Current Harmonic in Dual-Active-Bridge Converters

The Dual-Active-Bridge (DAB) converter transformer flux unbalance, or dc bias, could be a critical issue due to the mismatches of converter circuit parameters and control transients. In this paper, a steady-state flux balancing scheme, based on the second-order harmonic of magnetizing current has been proposed. The relationship between steady-state flux/magnetizing current unbalance and its harmonic contents has been analyzed, with which a new current sensing method and control strategy are introduced. The proposed magnetizing current sensing method can be implemented for both unity and complicated fractional turns ratios, without high sensitivity to dc offset from the analog circuitry. The proposed scheme has been validated with experimental results on 850-V/850-V DAB converters within a system, as well as in an 850-V/6700-V medium voltage DAB unit.

Gao, Zihan↗

SHMEMGraph: Efficient and Balanced Graph Processing Using One-Sided Communication

State-of-the-art synchronous graph processing frameworks face both inefficiency and imbalance issues that cause their performance to be suboptimal. These issues include the inefficiency of communication and the imbalanced graph computation/communication costs in an iteration. We propose to replace their conventional two-sided communication model with the one-sided counterpart. Accordingly, we design SHMEMGraph, an efficient and balanced graph processing framework that is formulated across a global memory space and takes advantage of the flexibility and efficiency of one-sided communication for graph processing. Through an efficient one-sided communication channel, SHMEMGraph utilizes the high-performance operations with RDMA while minimizing the resource contention within a computer node. In addition, SHMEMGraph synthesizes a number of optimizations to address both computation imbalance and communication imbalance. By using a graph of 1 billion edges, our evaluation shows that compared to the state-of-the-art Gemini framework, SHMEMGraph achieves an average improvement of 35.5% in terms of job completion time for five representative graph algorithms.

Fu, Huansong↗

Optimal Balance of Privacy and Utility with Differential Privacy Deep Learning Frameworks

As the number of online services has increased, the amount of sensitive data being recorded is rising. Simultaneously, the decision-making process has improved by using the vast amounts of data, where machine learning has transformed entire industries. This paper addresses the development of optimal private deep neural networks and discusses the challenges associated with this task. We focus on differential privacy implementations and finding the optimal balance between accuracy and privacy, benefits and limitations of existing libraries, and challenges of applying private machine learning models in practical applications. Our analysis shows that learning rate, and privacy budget are the key factors that impact the results, and we discuss options for these settings.

Kotevska, Olivera↗