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Thermodynamic properties of a Ga-doped La–Sr–Mn perovskite are experimentally extracted and used to compare its water splitting behavior to ceria.
Tokamak plasmas often exhibit self-organizing behavior in which internal modes shape the toroidal current density profile, a common example being the sawtooth instability. However, such behavior has not been studied in detail for edge safety factor below 2 due to disruptive kink instabilities that typically prevent operation in this regime. Now, steady tokamak plasmas with an edge safety factor down to 0.8 have been created in the Madison Symmetric Torus, where disruptions are prevented due to a thick, conductive wall and a feedback power supply that sustains the plasma current. Internal measurements and nonlinear magnetohydrodynamic modeling reveal a family of safety factor profiles with a central value clamped near unity as the edge safety factor decreases, indicating current profile broadening through a relaxation process. Furthermore, as the safety factor decreases, the magnetic fluctuations become irregular, and the electron energy confinement time decreases.
A large number of magnetohydrodynamic (MHD) equilibrium calculations are often required for uncertainty quantification, optimization, and real-time diagnostic information, making MHD equilibrium codes vital to the field of plasma physics. In this paper, we explore a method for solving the Grad–Shafranov equation by using physics-informed neural networks (PINNs). For PINNs, we optimize neural networks by directly minimizing the residual of the partial differential equation as a loss function. We show that PINNs can accurately and effectively solve the Grad–Shafranov equation with several different boundary conditions, making it more flexible than traditional solvers. This method is flexible as it does not require any mesh and basis choice, thereby streamlining the computational process. We also explore the parameter space by varying the size of the model, the learning rate, and boundary conditions to map various tradeoffs such as between reconstruction error and computational speed. Additionally, we introduce a parameterized PINN framework, expanding the input space to include variables such as pressure, aspect ratio, elongation, and triangularity in order to handle a broader range of plasma scenarios within a single network. Parameterized PINNs could be used in future work to solve inverse problems such as shape optimization.
We use the 3D magnetohydrodynamic (MHD) code M3D-C1 [Jardin et al., Comput. Sci. Discovery 5, 014002 (2012)] to examine the MHD stability and subsequent evolution of NSTX shot 129169. This discharge had a period with a non-monotonic safety factor profile, q (reversed shear), which was terminated by a MHD event that abruptly lowered the central safety factor, q0, and greatly reduced the peakedness of the pressure profile. We show that the equilibrium just before the MHD event occurred was linearly unstable to many pressure-driven infernal modes. Modes with toroidal mode number n≥3 all had rational surfaces very close to the minimum value of q. However, a non-resonant pressure-driven (1, 1) mode was also present, and this dominated the nonlinear evolution. The final state in the simulation, after the MHD activity subsided, had a reduced and flattened pressure profile and a nearly monotonic q-profile, in qualitative agreement with experimental results. The initial state was also unstable to the resistive interchange criteria in the reversed-shear region, but the final state was stable everywhere. The “double tearing mode” (DTM) does not appear to play a role in the MHD activity of this discharge. In Appendix A, we show that in a torus, the DTM is strongly stabilized by pressure, but it is destabilized in cylindrical geometry (which has been the most extensively analyzed in the literature).
Following Greene et al. [Phys. Fluids 14, 671 (1971)] and Connor et al. [Phys. Plasmas 31, 577 (1988); Plasma Phys. Control. Fusion 34, 161 (1992); and Nucl. Fusion 33, 1533 (1993)], the Grad-Shafranov equation for an axisymmetric tokamak plasma equilibrium is solved via an expansion in the, supposedly small, inverse aspect-ratio of the plasma, ϵ. The displacements of equilibrium magnetic flux-surfaces due to plasma shaping are assumed to be $\mathcal{O}$(ϵ) smaller than the minor radii of the surfaces, but no other restriction is placed on the nature of the shaping. The solution of the Grad-Shafranov equation is matched to a vacuum solution that extends to infinity, and consists of an expansion in toroidal functions. The external poloidal magnetic field generated by a finite set of discrete external poloidal magnetic field-coils is calculated, and incorporated into the toroidal function expansion. In this manner, the shape of a large aspect-ratio tokamak plasma is directly related to the currents flowing in the external poloidal field-coils. Finally, a pedestal in the plasma pressure, and the associated spike in the bootstrap current, are incorporated into the model.
Stellarator vacuum fields are designed to have a dense set of nested flux surfaces, with only small islands and stochastic regions in the interior of the confinement region. As the plasma pressure is increased, pressure driven currents appear, and they can significantly modify the vacuum field. The question arises whether pressure driven currents can cause significant flux surface breakage. Both the Wendelstein 7-AS and large helical device stellarators had dedicated experimental campaigns to study the β limit in those devices. In this paper, we review the evidence that the flux surfaces in a significant fraction of the plasma volume were stochastized by the pressure-driven currents in the highest β experiments. That phenomenon appears to have been the dominant source of pressure-driven flux surface loss in these experiments.
Rigid electron rotation of a Rotamak-FRC produces a pressure flux function that is more peaked than the Solov'ev flux function. This paper explores the implications of this peaked pressure flux function, including the isothermal case, which appear when the temperature profile is broader than the density profile, creating both benefits and challenges to a Rotamak-FRC based fusion reactor. In this regime, the density distribution becomes very peaked, enhancing the fusion power. The separatrix has a tendency to become oblate, which can be mitigated by flux conserving current loops. Plasma extends outside the separatrix, notably in the open field line region. Furthermore, this model does not apply to very kinetic FRCs or FRCs in which there are significant ion flows, but it may have some applicability to their outer layers.
Neural networks (NNs) offer a path towards synthesizing and interpreting data on faster timescales than traditional physics-informed computational models. In this work we develop two NNs relevant to equilibrium and shape control modeling, which are part of a suite of tools being developed for the National Spherical Torus Experiment-Upgrade for fast prediction, optimization, and visualization of plasma scenarios. The networks include Eqnet, a free-boundary equilibrium solver trained on the EFIT01 (Equilibrium FITtting 01) reconstruction algorithm, and Pertnet, which is trained on the Gspert code and predicts the non-rigid plasma response, a nonlinear term that arises in shape control modeling. The NNs are trained with different combinations of inputs and outputs in order to offer flexibility in use cases. In particular, Eqnet can use magnetic diagnostics as inputs and act as an EFIT-like reconstruction algorithm, or, by using pressure and current profile information the NN can act as a forward Grad–Shafranov equilibrium solver. This forward-mode version is envisioned to be implemented in the suite of tools for simulation of plasma scenarios. The reconstruction-mode version gives some performance improvements compared to the online reconstruction code real-time EFIT, especially when vessel eddy currents are significant. Here, we report strong performance for all NNs indicating that the models could reliably be used within closed-loop simulations or other applications. Some limitations are discussed.
Abstract In ITER, tritium retention primarily occurs through co-deposition with beryllium. To avoid exceeding the strict tritium inventory limit, efficient tritium recovery techniques are essential. Baking is the ITER baseline for tritium recovery, but its effectiveness in removing tritium from thick beryllium layers is limited. A raised strike point scenario is considered an alternative method for removing tritium from the ITER inner vertical divertor target by heating components via plasma flux. This paper presents SOLPS-ITER code simulations conducted under various conditions, assessing the divertor performance and tritium outgassing of the raised strike point scenario. As the strike point is raised, recycled neutrals are not efficiently baffled by the dome and scrape-off layer, significantly changing the neutral trajectory and ionization source distribution. This improves detachment accessibility but worsens core-edge compatibility compared to the baseline scenario. However, in the partially detached condition, the impact of raising the strike point, perpendicular transport, and q 95 on target heat flux is not significant, as it primarily scales with the input power. Target heat flux is translated to target surface temperature using a simplified heat transfer model that considers the 3D target monoblock geometry and active cooling condition, excluding Be layer thermal properties. For partially detached divertor conditions, the bulk tungsten monoblock surface temperature remains below the baking temperature, which is insufficient for efficient tritium outgassing under the actively cooled ITER divertor condition. However, considering the potential thermal contact resistance between the beryllium and tungsten layers, which may significantly impact temperature distribution, the temperature of the beryllium layer can be raised to a level sufficient for efficient tritium outgassing. Therefore, the raised strike point scenario can be considered as an alternative in-vessel tritium removal technique.
Here, this study investigates the thermal properties of the repulsive Fermi-Hubbard model with chemical potential using variational quantum algorithms, crucial in comprehending particle behaviour within lattices at heightened temperatures in condensed matter systems. Conventional computational methods encounter challenges, especially in managing chemical potential, prompting exploration into Hamiltonian approaches. Despite the promise of quantum algorithms, their efficacy is hampered by coherence limitations when simulating extended imaginary time evolution sequences. To overcome these constraints, this research focuses on optimizing variational quantum algorithms to probe the thermal properties of the Fermi-Hubbard model. Physics-inspired circuit designs are tailored to alleviate coherence constraints, facilitating a more comprehensive exploration of materials at elevated temperatures. Our study demonstrates the potential of variational algorithms in simulating the thermal properties of the Fermi-Hubbard model while acknowledging limitations stemming from error sources in quantum devices and encountering barren plateaus.
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Achieving the goal of developing advanced fuel concepts that meet the DOE objectives of being robust, demonstrating high performance, and are more tolerant of accident conditions than current fuel systems will require a thorough understanding of the thermophysical and thermochemical properties of the constituent materials. Non-oxide fuel systems are being explored under the Advanced Fuels Program that hold significant promise for improved performance and accident tolerance, including the uranium silicide-based system considered in the current work. Prospective cladding materials currently considered that contribute to improved accident tolerance include silicon carbide composites and ferritic alloys (Fe-Cr-Al base compositions). Thus, the effort developed thermochemical models and values, supported with targeted experiments, to evaluate the ferritic alloy and silicon carbide composite cladding systems in contrast to current zirconium alloy cladding. The developed detailed understanding will serve to aid in relatively early screening of candidate systems to avoid wasted effort, guide development of new fuel forms, and to provide a basis for predicting and modeling fuel performance. Major deliverables for the project included: Thermochemical assessment and models of phases in the U-Si and U-Si-N systems; thermochemical evaluation supported by experimental measurements of fuel-cladding interactions of silicide fuel with baseline zirconium, ceramic composite, and ferritic alloy cladding; thermochemical assessment and models of phases supported by experimental measurements for silicide fuel with key fission products provided in a dataset and reported in refereed publications. Within the project a significantly refined U-Si phase diagram was developed and reported that now includes homogeneity ranges for key phases, such at the U 3 Si 2 proposed fuel phase, and settles issues with regard to uncertainty in the stability of some phases. Computational efforts together with key experiments has determined phase formation in interactions between U 3 Si 2 and Zircaloy-4 cladding material, a ferritic FeCrAlY alloy of interest as an advanced cladding material, and silicon carbide, also of interest as a fiber-reinforced composite cladding. As expected, very significant reactions occur between U3Si2 and Zircaloy-4, with much less interaction at higher temperatures for the ferritic alloy, and finally interactions with SiC only in the region of contact. A potentially major issue is the stability of U 3 Si 2 fuel that has undergone significant burnup. The result is the loss of the uranium metal, liberating silicon, and the formation of concomitant fission product elements that either dissolve in the U 3 Si 2 phase or form independent, and possibly silicide phases. A combination of experimental determinations of phase formation of U 3 Si 2 reacted with representative fission products yttrium, gadolinium, cerium, zirconium, and molybdenum and first principles calculations has helped understand the fuel chemistry. The behavior of the U 3 Si 2 phase and the partitioning of silicon to possible fission product phases with burnup was thus determined, with significant dissolution in U 3 Si 2 of cerium, gadolinium, zirconium, and plutonium predicted along with independent phase formation of a U-Mo-Si ternary phase, yttrium silicide, and elemental selenium. It can be concluded that at significant burnup there will be a very minor amount of the U 3 Si 2 fuel phase that will decompose to a lower silicide or a uranium alloy as silicon preferentially forms a secondary phase.
This is the Final Progress Report of the Helicity Injected Torus (HIT) program covering May 2016 through December 2020. During this final period the HIT program continued to make advancements in computational modeling, theory, and experimental studies of global self-organization and inductively sustained spheromaks. This included many valuable contributions to the fusion, plasma and physics community, through peer-reviewed publications, PhD theses and conference presentations and posters.
A simple thermodynamic model for the uranium-niobium (U-Nb) system was created using a Calphad-type approach, circa 2002. Only the liquid and gamma-BCC phases were modeled, with their subregular solution mixing terms optimized by trial and error. The custom (user-defined) database file (.tdb) and experimental data file (.exp) are listed, both of which are compatible with Thermo-Calc software. This model is used to calculate the solidus, liquidus, miscibility gap on the U-Nb phase diagram and also the enthalpy of melting in the U-6Nb alloy.
The overarching goal of this research project is quantitative microscopic modeling of phase diagrams and solubility of actinides and lanthanide-fission products in molten salts for molten salt reactors. Application of molten salts as coolants and liquid fuels for next-generation reactors requires quantitative understanding of phase diagrams, equations of state and transport properties of binary and ternary molten salt mixtures, as well as solubility of fuel, fission products and reactor-wall corrosion products, but these remain beyond the reach of current first-principles computational techniques. We will address this fundamental capability gap using a novel hybrid framework for thermodynamic integration to directly predict absolute free energies of solid and molten salts at any specified conditions of composition, temperature and pressure. This framework will combine a hierarchy of first-principles, molecular dynamics and continuum techniques to deliver first-principles-level accuracy at a fraction of the computational cost of conventional ab initio molecular dynamics approaches. In particular, this technique is expected to provide first-principles accuracy, while off-loading most of the computational work on much less expensive classical molecular dynamics and continuum techniques.
Abstract not provided.
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