Equilibrium Solver Research Articles

Control-Oriented Free-Boundary Equilibrium Solver for Tokamaks

A free-boundary equilibrium solver for an axisymmetric tokamak geometry was developed based on the finite difference method and Picard iteration in a rectangular computational area. The solver can run either in forward mode, where external coil currents are prescribed until the converged magnetic flux function ψ(R,Z) map is achieved, or in inverse mode, where the desired plasma boundary, with or without an X-point, is prescribed to determine the required coil currents. The equilibrium solutions are made consistent with prescribed plasma parameters, such as the total plasma current, poloidal beta, or safety factor at a specified flux surface. To verify the mathematical correctness and accuracy of the solver, the solution obtained using this numerical solver was compared with that from an analytic fixed-boundary equilibrium solver based on the EAST geometry. Additionally, the proposed solver was benchmarked against another numerical solver based on the finite-element and Newton-iteration methods in a triangular-based mesh. Finally, the proposed solver was compared with equilibrium reconstruction results in DIII-D experiments.

Accuracy of kinetic equilibrium reconstruction of NSTX and NSTX-U plasmas and its impact on the transport and stability analysis

Abstract An accurate magnetohydrodynamic (MHD) equilibrium reconstruction is an essential starting point for stability and transport plasma analysis. This work describes an approach for obtaining kinetic equilibrium reconstructions using the OMFIT framework, which has been applied for the first time to spherical tokamak data from NSTX and NSTX-U. The EFIT equilibrium solver is integrated with experimental data analysis procedures and subsequent TRANSP transport simulations to enhance the accuracy of the reconstruction, in particular at the edge region, by adding constraints on the total pressure and current density profiles, based on the transport code solution. The accuracy of the equilibrium depends on the uncertainty and number of constraints, as well as the choice of basis functions to represent the pressure and current density profiles. An improved fidelity of the equilibrium reconstruction is demonstrated by reducing the variability of the magnetic axis and boundary locations from several centimeters for reconstructions based on magnetic and experimental pressure constraints to only several millimeters for kinetic reconstructions based on transport code constraints, when different representations for basis functions were tested. Variability of the safety factor on-axis was reduced ten times in the same sensitivity study. The accuracy of the equilibrium reconstruction and subsequent mapping of experimental kinetic profile data have a significant impact on TGLF and linear CGYRO turbulence simulations, which predict different spectra of unstable modes and turbulent fluxes for cases with different numbers of constraints in the equilibrium reconstruction. Conversely, the stability analysis performed with the GATO code shows plasmas stable to n = 1 MHD modes in both equilibria using magnetic and experimental pressure constraints as well as the transport code constrained equilibrium. However, a scan of parameters away from these conditions shows considerable deviation in the threshold of unstable modes between these reconstructions. Therefore, for reliable plasma analysis and use in turbulence and stability calculations, a high fidelity equilibrium reconstruction with accurate kinetic constraints based on transport code solutions is necessary.

Flat-top plasma operational space of the STEP power plant

Abstract STEP is a spherical tokamak prototype power plant that is being designed to demonstrate net electric power. The design phase involves the exploitation of plasma models to optimise fusion performance subject to satisfying various physics and engineering constraints. A modelling workflow, including integrated core plasma modelling, MHD stability analysis, SOL and pedestal modelling, coil set and free boundary equilibrium solvers, and whole plant design, has been developed to specify the design parameters and to develop viable scenarios. The integrated core plasma model JETTO is used to develop individual flat-top operating points that satisfy imposed criteria for fusion power performance within operational constraints. Key plasma parameters such as normalised beta, Greenwald density fraction, auxiliary power and radiated power have been scanned to scope the operational space and to derive a collection of candidate non-inductive flat-top points. The assumed auxiliary heating and current drive is either from electron cyclotron systems only or a combination of electron cyclotron and electron Bernstein waves. At present stages of transport modelling, there is a large uncertainty in overall confinement for relevant parameter regimes. For each of the two auxiliary heating and current drive systems scenarios, two candidate flat-top points have been developed based on different confinement assumptions, totalling to four operating points. A lower confinement assumption generally suggests operating points in high-density, high auxiliary power regimes, whereas higher confinement would allow access to a broader parameter regime in density and power while maintaining target fusion power performance.

Chemical Kinetics and Thermal Properties of Ablator Pyrolysis Products During Atmospheric Entry

Legacy and modern-day ablation codes typically assume equilibrium pyrolysis gas chemistry. Yet, experimental data suggest that speciation from resin decomposition is far from equilibrium. A thermal and chemical kinetic study was performed on pyrolysis gas advection through a porous char, using the Theoretical Ablative Composite for Open Testing (TACOT) as a demonstrator material. The finite-element tool SIERRA/Aria simulated the ablation of TACOT under various conditions. Temperature and phenolic decomposition rates generated from Aria were applied as inputs to a simulated network of perfectly stirred reactors (PSRs) in the chemical solver Cantera. A high-fidelity combustion mechanism computed the gas composition and thermal properties of the advecting pyrolyzate. The results indicate that pyrolysis gases do not rapidly achieve chemical equilibrium while traveling through the simulated material. Instead, a highly chemically reactive zone exists in the ablator between 1400 and 2500 K, wherein the modeled pyrolysis gases transition from a chemically frozen state to chemical equilibrium. These finite-rate results demonstrate a significant departure in computed pyrolysis gas properties from those derived from equilibrium solvers. Under the same conditions, finite-rate-derived gas is estimated to provide up to 50% less heat absorption than equilibrium-derived gas. This discrepancy suggests that nonequilibrium pyrolysis gas chemistry could substantially impact ablator material response models.

FLIPEC, an ideal MHD free-boundary axisymmetric equilibrium solver in the presence of macroscopic flows

The most relevant features of FLIPEC (Free fLow Iterative Plasma Equilibrium Code) are presented. This new code iteratively calculates free-boundary, axisymmetric ideal MHD equilibria with arbitrary poloidal and toroidal plasma flows. FLIPEC is a mature code that has emerged from a complete overhaul of a previous version (F-Torija Daza 2022 et al Nucl. Fusion 62 126044). It uses a (inverse) curvilinear coordinate representation for the Grad–Shafranov–Bernoulli equation system, which allows FLIPEC to extend its free-boundary capabilities to arbitrary plasma shapes and removes many limitations with regards to the distance between plasma and external coils. Run-time stabilization of vertical modes has also been implemented by means of artificial feedback coils. Finally, active targeting schemes have also been included. These capabilities are illustrated on two very different cases: the ITER tokamak baseline configuration and a NSTX spherical tokamak equilibrium.

Revisiting the Becker-Kistiakowsky-Wilson equation of state

The Jones-Wilkins-Lee (JWL) equation of state (EOS) is the most popular equation of state used in hydrocodes to model detonation products thermodynamics resulting from high explosives. However, the JWL EOS presents several major difficulties. Namely, its range of validity and convexity is limited as its parameters are adjusted on a given reference curve. When used in conditions where the thermodynamic state varies significantly, computational failure may happen. It occurs frequently in multiphase flow computations when heat and mass transfers with other phases are present, as the resulting thermodynamic state is far from the reference curve used for adjustment. Moreover, the detonation products composition is absent in the JWL formulation. This is another important limitation when additional physics are involved, such as post-combustion, phase transition, or when dealing with non-ideal explosives. In this work, the Becker-Kistiakowsky-Wilson (BKW) EOS is considered instead. The BKW EOS is widely used in thermochemical codes, as parent EOS to provide the reference data used to fit JWL EOS parameters. The BKW EOS present several advantages. Its formulation considers variable gas species in the detonation products. No specific adjustment is needed for a given explosive, and only the detonation products composition requires computational efforts. Its range of validity is large, as the various parameters have been adjusted for each gas species separately. However, the BKW EOS also present difficulties which limit its application in hydrocodes. These difficulties are the aim of the present work. The BKW EOS is currently restricted to thermochemical codes as its mathematical formulation is computationally expensive. It also requires the gas chemical composition to be computed via an appropriate chemical equilibrium solver. In the present work, the computational cost of the BKW EOS is reduced thanks to the thermodynamic relaxation method of Neron et al. (2023). The variable composition of the detonation products is accounted for through specific relaxation terms computed once, with the help of conventional thermochemical codes. The condensed species, such as solid carbon, are modelled with the Cochran-Chan (CC) EOS, having a simpler thermodynamic formulation and being thermodynamically consistent compared to usual EOSs used for condensed species. This multiphase formulation made of BKW gas mixture with variable composition and condensed phases is considered in temperature and pressure equilibrium. It is embedded in a multiphase flow formulation, with the help of the thermodynamic relaxation method mentioned above. It shows comparable computational cost as the JWL formulation, with significantly enhanced physics capabilities and improved robustness.

Study of the influence of magnetic shear on the linear MHD instabilities in the pedestal of elongated divertor configurations using CLT code

AbstractEdge localized modes resulted from magnetohydrodynamic (MHD) instabilities in the pedestal region are a significant concern for future tokamaks. In this work, Ci‐Liu‐Ti (CLT), an MHD code in the three‐dimensional toroidal geometry, is applied for the linear simulation of the ideal pedestal MHD instabilities. The simulations are performed for the experimental advanced superconducting tokamak‐like elongated divertor configuration with large triangularity, which is generated by the high‐accuracy free‐boundary equilibrium solver (CLT‐EQuilibrium, i.e., CLT‐EQ) developed recently. The present work focuses on the influence of the magnetic shear, which is scanned by adjusting the pedestal current with a fixed pedestal pressure profile. As the pedestal current increases, both the local (Slocal) and global (Sglobal) magnetic shear decrease. The ballooning mode is destabilized along with the decrease of Slocal, and stabilized when Slocal is negative for the whole region of bad curvature, which implies the access of the second stable region. Further increase of the pedestal current leads to the destabilization of the kink mode, which is stabilized again until Sglobal is negative at the location of significant gradient of current density. The simulated results are consistent with the findings in Radovanovic et al. Nucl. Fusion 62 (2022) 086004 and C. K. Sun et al. Phys. Plasmas 25 (2018) 082106, which indicates the availability of CLT in the linear simulation of the ideal pedestal instabilities.

Deep learning approaches to recover the plasma current density profile from the safety factor based on Grad–Shafranov solutions across multiple tokamaks

Many magnetohydrodynamic stability analyses require generation of a set of equilibria with a fixed safety factor q-profile while varying other plasma parameters. A neural network (NN)-based approach is investigated that facilitates such a process. Both multilayer perceptron (MLP)-based NN and convolutional neural network (CNN) models are trained to map the q-profile to the plasma current density J-profile, and vice versa, while satisfying the Grad–Shafranov radial force balance constraint. When the initial target models are trained, using a database of semi-analytically constructed numerical equilibria, an initial CNN with one convolutional layer is found to perform better than an initial MLP model. In particular, a trained initial CNN model can also predict the q- or J-profile for experimental tokamak equilibria. The performance of both initial target models is further improved by fine-tuning the training database, i.e. by adding realistic experimental equilibria with Gaussian noise. The fine-tuned target models, referred to as fine-tuned MLP and fine-tuned CNN, well reproduce the target q- or J-profile across multiple tokamak devices. As an important application, these NN-based equilibrium profile convertors can be utilized to provide a good initial guess for iterative equilibrium solvers, where the desired input quantity is the safety factor instead of the plasma current density.

FreeGSNKE: A Python-based dynamic free-boundary toroidal plasma equilibrium solver

We present a Python-based numerical solver for the two-dimensional dynamic plasma equilibrium problem. We model the time evolution of toroidally symmetric free-boundary tokamak plasma equilibria in the presence of the non-linear magnetohydrodynamic coupling with both currents in the “active” poloidal field coils, with assigned applied voltages, and eddy currents in the tokamak passive structures. FreeGSNKE (FreeGS Newton–Krylov Evolutive) builds and expands on the framework provided by the Python package FreeGS (Free boundary Grad–Shafranov). FreeGS solves the static free-boundary Grad–Shafranov (GS) problem, discretized in space using finite differences, by means of Picard iterations. FreeGSNKE introduces: (i) a solver for the static free-boundary GS problem based on the Newton–Krylov (NK) method, with improved stability and convergence properties; (ii) a solver for the linearized dynamic plasma equilibrium problem; and (iii) a solver for the non-linear dynamic problem, based on the NK method. We propose a novel “staggered” solution strategy for the non-linear problem, in which we make use of a set of equivalent formulations of the non-linear dynamic problem we derive. The alternation of NK solution steps in the currents and in the plasma flux lends this strategy an increased resilience to co-linearity and stagnation problems, resulting in favorable convergence properties. FreeGSNKE can be used for any user-defined tokamak geometry and coil configuration. FreeGSNKE's flexibility and ease of use make it a suitably robust control-oriented simulator of plasma magnetic equilibria. FreeGSNKE is entirely written in Python and easily interfaced with Python libraries, which facilitates machine learning based approaches to plasma control.

Korg: Fitting, Model Atmosphere Interpolation, and Brackett Lines

We describe several updates to Korg, a package for 1D LTE spectral synthesis of FGKM stars. Built-in functions to fit observed spectra via synthesis or equivalent widths make it easy to take advantage of Korg's automatic differentiation. Comparison to a past analysis of 18 Sco shows that we obtain significantly reduced line-to-line abundance scatter with Korg. Fitting and synthesis are facilitated by a rigorously tested model atmosphere interpolation method, which introduces negligible error to synthesized spectra for stars with T eff ≳ 4000 K. For cooler stars, atmosphere interpolation is complicated by the presence of molecules, though we demonstrate an adequate method for cool dwarfs. The chemical equilibrium solver has been extended to include polyatomic and charged molecules, extending Korg's regime of applicability to M stars. We also discuss a common oversight regarding the synthesis of hydrogen lines in the infrared, and show that Korg's Brackett line profiles are a much closer match to observations than others available. Documentation, installation instructions, and tutorials are available at https://github.com/ajwheeler/Korg.jl.

Neural-Network-Based Free-Boundary Equilibrium Solver to Enable Fast Scenario Simulations

Neural-Network-Based Free-Boundary Equilibrium Solver to Enable Fast Scenario Simulations

Physics basis for the Wisconsin HTS Axisymmetric Mirror (WHAM)

The Wisconsin high-temperature superconductor axisymmetric mirror experiment (WHAM) will be a high-field platform for prototyping technologies, validating interchange stabilization techniques and benchmarking numerical code performance, enabling the next step up to reactor parameters. A detailed overview of the experimental apparatus and its various subsystems is presented. WHAM will use electron cyclotron heating to ionize and build a dense target plasma for neutral beam injection of fast ions, stabilized by edge-biased sheared flow. At 25 keV injection energies, charge exchange dominates over impact ionization and limits the effectiveness of neutral beam injection fuelling. This paper outlines an iterative technique for self-consistently predicting the neutral beam driven anisotropic ion distribution and its role in the finite beta equilibrium. Beginning with recent work by Egedalet al.(Nucl. Fusion, vol. 62, no. 12, 2022, p. 126053) on the WHAM geometry, we detail how the FIDASIM code is used to model the charge exchange sources and sinks in the distribution function, and both are combined with an anisotropic magnetohydrodynamic equilibrium solver method to self-consistently reach an equilibrium. We compare this with recent results using the CQL3D code adapted for the mirror geometry, which includes the high-harmonic fast wave heating of fast ions.

The effects of anisotropic pressure on plasma displacement and its deviation from flux surfaces

A significant impact of pressure anisotropy on the plasma displacement associated with ideal Magnetohydrodynamic (MHD) stability is found. A heliotron plasma, such as a large helical device plasma, is analyzed. Simulations are performed using the equilibrium solver Anisotropic Neumann Inverse Moments Equilibrium Code and the ideal MHD stability code TERPSICHORE. Both codes provide a treatment of the pressure anisotropy by the bi-Maxwellian model. The ratio of hot particle pressure to total pressure <βh>/<β> has been scanned over. Other simulation parameters have been chosen such that the simulations represent an experimentally relevant condition with an external, off-axis heating scheme. The radial location of the peak of the plasma displacement of the n = 1, m = 2 mode number has been compared to the radial location of the ι = 0.5 resonant surface. This comparison shows that this difference in location increases monotonically for increasing <βh>/<β> . These results provide insight on the effect of external heating schemes on MHD stability.

Predictive simulations for plasma scenarios in the SMART tokamak

The SMall Aspect Ratio Tokamak (SMART) is a new spherical machine that is currently being constructed at the University of Seville (Mancini et al., 2021; Agredano-Torres et al., 2021). The operation of SMART will cover three different phases reaching an inductive plasma current (IP) of more than 500 kA, a toroidal magnetic field (BT) of 1 T and a pulse length of 500 ms (Mancini et al., 2021; Agredano-Torres et al., 2021). The main goal of the SMART tokamak is to study high plasma confinement regimes in a broad triangularity range (-0.5≤δ≤0.5) (Doyle et al., 2021; Doyle et al., 2021). While in phase 1 the ohmic heating alone is expected to provide enough power to access the H-mode, in phase 2 and phase 3 the access to the H-mode will be ensured by applying Neutral Beam Injection (NBI) as external heating system. The NBI will consist of one injector at 25 keV and 1 MW of power. The overall design of the NBI, including injection geometry, energy and power have been optimized using the ASCOT5 code (Hirvijoki et al., 2021). The SMART scenarios have been developed with the help of the free boundary equilibrium solver code FIESTA (Cunningham, 2013) coupled to the linear time independent, rigid plasma model RZIP (Lazarus et al., 1990) to calculate the target equilibria for all the different operational phases. To assess the feasibility of those scenarios, predictive modelling needs to be included to evaluate properly the evolution of the temperatures, density profiles for both electrons and ions. To this extent, the 1.5D transport code ASTRA (Pereverzev and Yushmanov, 2002) has been used including models for the ohmic current, bootstrap current and current driven by NBI. This contribution discusses the electron and ion density and temperature profiles obtained for various scenarios for phase 1 and 2 and presents the design study of the NBI.

Solving Chemical Absorption Equilibria using Free Energy and Quantum Chemistry Calculations: Methodology, Limitations, and New Open-Source Software.

We developed an open-source chemical reaction equilibrium solver in Python (CASpy, https://github.com/omoultosEthTuDelft/CASpy) to compute the concentration of species in any reactive liquid-phase absorption system. We derived an expression for a mole fraction-based equilibrium constant as a function of excess chemical potential, standard ideal gas chemical potential, temperature, and volume. As a case study, we computed the CO2 absorption isotherm and speciation in a 23 wt % N-methyldiethanolamine (MDEA)/water solution at 313.15 K, and compared the results with available data from the literature. The results show that the computed CO2 isotherms and speciations are in excellent agreement with experimental data, demonstrating the accuracy and the precision of our solver. The binary absorptions of CO2 and H2S in 50 wt % MDEA/water solutions at 323.15 K were computed and compared with available data from the literature. The computed CO2 isotherms showed good agreement with other modeling studies from the literature while the computed H2S isotherms did not agree well with experimental data. The experimental equilibrium constants used as an input were not adjusted for H2S/CO2/MDEA/water systems and need to be adjusted for this system. Using free energy calculations with two different force fields (GAFF and OPLS-AA) and quantum chemistry calculations, we computed the equilibrium constant (K) of the protonated MDEA dissociation reaction. Despite the good agreement of the OPLS-AA force field (ln[K] = -24.91) with the experiments (ln[K] = -23.04), the computed CO2 pressures were significantly underestimated. We systematically investigated the limitations of computing CO2 absorption isotherms using free energy and quantum chemistry calculations and showed that the computed values of μiex are very sensitive to the point charges used in the simulations, which limits the predictive power of this method.

Development of magnetic control for the EU-DEMO flight simulator and application to transient phenomena

This paper presents a first implementation of DEMO tokamak (Donné, 2019) [1] configuration including CREATE magnetic controllers in the Fenix flight simulator environment. Fenix is based on the 1-D transport code ASTRA (Pereverzev and Yushmanov, 2002 [2] and Fable et al., 2013) [3] , coupled with the 2-D equilibrium solver SPIDER (Ivanov et al., 2005) [4] . Following the successful demonstration on ASDEX Upgrade (Herrmann and Gruber, 2003) [5]) , it was clear that this environment could be fruitfully used to simulate DEMO scenarios including both magnetic and kinetic control strategies. In order to design magnetic controllers, first a systematic validation of the plasma linearized dynamic response has been successfully carried out. This dynamic response has been used to design and tune a first version of magnetic controllers including vertical stability, plasma shape and plasma current control. Simulations of both the plasma flat-top phase including H to L transition, and of the ramp-up phase are presented to show the effectiveness of the proposed simulator and of the magnetic control solution.

Linear simulation of kinetic Peeling-Ballooning mode with bootstrap current under the BOUT++ gyro landau fluid code

The kinetic peeling-ballooning mode (KPBM) plays a crucial role in the edge turbulence and transport in a tokamak plasma. However, the impact of the bootstrap current on KPBM is still unclear. Simulations of KPBM using the BOUT++ gyro-Landau-fluid code are presented in this study. To investigate the KPBM in a real tokamak equilibrium, the global equilibrium solver CORSICA was employed to generate a set of realistic equilibria of shifted circular geometry, including the Shafranov shift, elongation effects and bootstrap current. The linear instability property of the KPBM is observed in a wide range of pressure gradient and parallel current density in the pedestal region. Our results indicate that the bootstrap current has a stabilizing effect on the high-n KPBM over the entire pedestal region. Here, n is the toroidal mode number. In comparison with the ideal magnetohydrodynamic peeling-ballooning mode stability diagram, the unstable KPBM region shrinks and shifts to low ( where denotes the pressure at the peak pressure gradient position) with the increase of the bootstrap current. Moreover, we find that the low-n kink modes are driven unstable by the bootstrap current in the second stable region. With an additional external current drive on top of the bootstrap current, the low-n KPBMs can be stabilized when the total edge current is sufficiently large, although the low-n kink mode is still unstable in the region with .

Neural net modeling of equilibria in NSTX-U

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. 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.

Application of machine learning and artificial intelligence to extend EFIT equilibrium reconstruction

Recent progress in the application of machine learning (ML)/artificial intelligence (AI) algorithms to improve the Equilibrium Fitting (EFIT) code equilibrium reconstruction for fusion data analysis applications is presented. A device-independent portable core equilibrium solver capable of computing or reconstructing equilibrium for different tokamaks has been created to facilitate adaptation of ML/AI algorithms. A large EFIT database comprising of DIII-D magnetic, motional Stark effect, and kinetic reconstruction data has been generated for developments of EFIT model-order-reduction (MOR) surrogate models to reconstruct approximate equilibrium solutions. A neural-network MOR surrogate model has been successfully trained and tested using the magnetically reconstructed datasets with encouraging results. Other progress includes developments of a Gaussian process Bayesian framework that can adapt its many hyperparameters to improve processing of experimental input data and a 3D perturbed equilibrium database from toroidal full magnetohydrodynamic linear response modeling using the Magnetohydrodynamic Resistive Spectrum - Feedback (MARS-F) code for developments of 3D-MOR surrogate models.

Equilibrium reconstruction of DIII-D plasmas using predictive modeling of the pressure profile

New workflows have been developed for predictive modeling of magnetohydrodynamic (MHD) equilibrium in tokamak plasmas. The goal of this work is to predict the MHD equilibrium in tokamak discharges without having measurements of the kinetic profiles. The workflows include a cold start tool, which constructs all the profiles and power flows needed by transport codes; a Grad–Shafranov equilibrium solver; and various codes for the sources and sinks. For validation purposes, a database of DIII-D tokamak discharges has been constructed that is comprised of scans in the plasma current, toroidal magnetic field, and triangularity. Initial efforts focused on developing a workflow utilizing an empirically derived pressure model tuned to DIII-D discharges with monotonic safety factor profiles. This workflow shows good agreement with experimental kinetic equilibrium calculations, but is limited in that it is a single fluid (equal ion and electron temperatures) model and lacks H-mode pedestal predictions. The best agreement with the H-mode database is obtained using a theory-based workflow utilizing pressure profile predictions from a coupled TGLF turbulent transport and EPED pedestal models together with external magnetics and Motional Stark Effect (MSE) data to construct the equilibrium. Here, we obtain an average root mean square error of 5.1% in the safety factor profile when comparing the predicted and experimental kinetic equilibrium. We also find good agreement with the plasma stored energy, internal inductance, and pressure profiles. Including MSE data in the theory-based workflow results in noticeably improved agreement with the q-profiles in high triangularity discharges in comparison with the results obtained with magnetic data only. The predictive equilibrium workflow is expected to have wide applications in experimental planning, between-shot analysis, and reactor studies.