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At least 847 records · Page 47

Structure refinement and anisotropic atomic displacement parameters of 1M Illite: Rietveld and pair distribution function analysis using synchrotron X-ray radiation

Illite, a widespread clay mineral, plays a pivotal role in geological processes, notably as an indicator in diagenetic and hydrothermal alteration environments, and possesses significant industrial relevance in applications including ceramics, construction and catalysis. However, challenges including its nanoscale crystallinity, structural disorder and frequent interstratification with other clay minerals have hindered detailed structural characterization using conventional X-ray diffraction (XRD) techniques. This study employs integrated synchrotron XRD and pair distribution function (PDF) analysis to elucidate the crystal structure of the 1M illite polytype, yielding the first determination of its anisotropic atomic displacement parameters (U aniso ). TheseU aniso parameters provide critical insights into atomic dynamics and static disorder within the structure, enabling a more refined understanding of structure–property relationships. This integrated approach, combining synchrotron XRD, Rietveld refinement and PDF analysis, yields a comprehensive structural characterization, capturing both average crystallographic and local atomic arrangements. Considering illite's widespread geological occurrence and industrial importance, this high-precision structural dataset, especially the determinedU aniso values, provides a crucial benchmark for future modeling and simulation efforts targeting accurate prediction of its physicochemical behavior.

Chemistry↗

An experimental study of characteristic combustion-driven flows for CFD validation

The application of laser-based diagnostic techniques has become commonplace to a wide variety of combustion problems. New insights into combustion phenomena at a level previously unattainable has been made possible by non-intrusive measurements of velocity, temperature, and species. However, due to the adverse conditions which exist inside rocket engines, relatively few studies have addressed these combustion environments. The high pressure, high speed, combusting environment in a rocket engine prohibits the application of several measurement techniques. However, in the rocket community, there is a critical need for rocket flow field data to validate computational fluid dynamic (CFD) codes. Currently at Penn State, there is an effort to obtain flowfield measurements inside a rocket engine. Velocity measurements have been made inside the combustion chamber of a uni-element (shear coaxial injector) optically accessible rocket chamber at several axial locations downstream of the injector. These measurements, combined with future measurements, will provide benchmark data for CFD code validation.

Pal, S.↗

Estimating List-Mode Data Sensitivities to Nuclear Data with MCNP6

Nuclear data are a vital component of predictive simulations used in applications like experiment design, stockpile stewardship, nuclear nonproliferation/safeguards, health physics, and criticality safety. A singular simulation requires the coalescence of different areas of nuclear data such as cross sections, angular distributions, and energy distributions of emitted neutrons for different materials and energy ranges. Improving nuclear data and thus reducing the uncertainty in simulated parameters could enable smaller, better-informed safety factors and ultimately reduce operational and procedural costs. There is a constant effort to garner a better understanding of the physical quantities represented by nuclear data through experiments. Integral experiment benchmarks use simulated and measured results to validate current nuclear data values. In the past, benchmarks primarily focused on the effective multiplication factor (k eff ); however, this limited scope has caused compensating errors and areas of nuclear data that lack validation. Compensating errors are inaccuracies in nuclear data that are obfuscated by cancellation when observing integrated values such as k eff . Diverse integral benchmark experiments that look for quantities of interest other than k eff and include multiple responses minimize the possibility of compensating errors and provides validation to areas of nuclear data previously lacking experimental validation. Benchmark experiments can be optimized during the design process to be highly dependent on specific areas of nuclear data. The dependence of a response in an experiment to a specific area/type of nuclear data is defined as sensitivity. A larger sensitivity means that nuclear data uncertainties will play a larger role in the response(s) resulting in larger bias. Currently, the sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®1 ) transport code are limited to responses of k eff and tallied values (e.g., flux, surface current). As a part of the EUCLID project, this work explores estimating list-mode nuclear data sensitivities that can be used to design experiments aimed to constrain and reduce compensating errors in nuclear data by focusing on responses other than k eff . Tallied values are ideal quantities that are estimated with detectors during experiments. List-mode data (a list of neutron collection times) are the direct output of detector systems in subcritical neutron noise experiments. Expanding MCNP sensitivity capabilities to include the sensitivity of responses estimated from list-mode data, such as the prompt neutron decay constant (α) and multiplicity estimates (S and D), enables more direct comparison of simulated and measured experimental quantities. Additionally, deterministic tools such as SENSMG are capable of obtaining sensitivities to a wide variety of responses; however, these tools cannot handle complex geometries due to the assumptions made in discretizing the phase-space variables of the Boltzman transport equation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Neutron Pulsed Die-Away Experiments at LLNL [Slides]

This presentation discusses why PNDA is ideal for TSL validations as it does not require fissile material, it has very simple target shapes and compositions, it is only sensitive to absorption and scattering of target medium, and that well conducted experiments have uncertainties of 0.1% - 0.5%. The presentation concludes by examining PNDA’s advantages and its role in nuclear data validations as it offers a cost-effective experiment for an integral benchmark, it provides the ability to focus on specific cross section data validation including thermal neutron absorption and thermal scattering laws, and the low experimental uncertainty makes it an excellent benchmark candidate. Additionally, it is easily tunable and can facilitate temperature dependent cross section validation by cooling or heating up targets.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Investigation of the approach used in the unresolved resonance region

The typical practice used in Monte Carlo neutron transport codes in the unresolved resonance region (URR) is to take advantage of the probability table (PT) approach. Cross sections are sampled from PTs and used as needed, along with generated average cross sections. The PTs are generated based on cross-section calculations performed using the single-level Breit–Wigner approximation. Although the approach used in the URR seems plausible, a detailed examination was needed to understand the benchmark results obtained using specific tests.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Completing the Feedback Loop: The Impact of Chlorophyll Data Assimilation on the Ocean State

In anticipation of the integration of a full biochemical model into the next generation GMAO coupled system, an intermediate solution has been implemented to estimate the penetration depth (1Kd_PAR) of ocean radiation based on the chlorophyll concentration. The chlorophyll is modeled as a tracer with sources-sinks coming from the assimilation of MODIS chlorophyll data. Two experiments were conducted with the coupled ocean-atmosphere model. In the first, climatological values of Kpar were used. In the second, retrieved daily chlorophyll concentrations were assimilated and Kd_PAR was derived according to Morel et al (2007). No other data was assimilated to isolate the effects of the time-evolving chlorophyll field. The daily MODIS Kd_PAR product was used to validate the skill of the penetration depth estimation and the MERRA-OCEAN re-analysis was used as a benchmark to study the sensitivity of the upper ocean heat content and vertical temperature distribution to the chlorophyll input. In the experiment with daily chlorophyll data assimilation, the penetration depth was estimated more accurately, especially in the tropics. As a result, the temperature bias of the model was reduced. A notably robust albeit small (2-5 percent) improvement was found across the equatorial Pacific ocean, which is a critical region for seasonal to inter-annual prediction.

MERRA-OCEAN↗

Effectively Using Remote I/O For Work Composition in Distributed Workflows

Distributed scientific workflows are becoming more important with the interest in incorporating AI into their loops. A critical programming and performance question is how to compose workflow tasks when data is produced on one system but must be consumed on another. Since the dominant technique is composition with remote I/O, this paper explores its performance expectations. We describe BigFlowSim, a workflow I/O simulator that captures key implementation choices for remote I/O, including intensity, reuse, locality, access pattern, and data movement.With BigFlowSim, we generate a synthetic benchmark. We quantify the effects of each parameter with a performance sensitivity study. We explain trends in terms of data movement reduction and show that, under certain conditions, it is possible to establish a total order among most parameters. We apply these insights to a high energy physics workflow, Belle II Monte Carlo and simulate several I/O optimizations. Speedups range from 5% to 2×, without changing compute time.

Friese, Ryan D.↗

Fast and deep phosphoproteome analysis with the Orbitrap Astral mass spectrometer

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method, we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology is benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We apply this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detect 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of phosphorylation events relevant to mitochondrial and brain biology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the accuracy of time-fraction and ductility exhaustion approaches for creep-fatigue damage prediction through feature-test validation

Determining creep-fatigue damage formation is critical for elevated temperature components integrity. This study evaluates creep-fatigue assessments with emphasis on differences between creep damage models. Evaluated are the time-fraction model and the classical and stress-modified ductility exhaustion creep damage models. This work extends the domain of stress-modified ductility exhaustion models by introducing and validating such formalism to Ni-based alloys. The fidelity of the assessments was benchmarked against uniaxial creep-fatigue and multiaxial feature tests of Alloy 617. For uniaxial specimens, best estimate predictions rank ductility exhaustion as the most accurate and precise and time-fraction as markedly conservative. For feature tests, ductility exhaustion predictions are within < 4.0 times difference, whereas time-fraction underpredicts life by factors of 7–14. The observations suggest ductility exhaustion models as alternative to time-fraction models in design codes for situations requiring characterization of the design margin. Further work in employing such models to assess other relevant phenomena (e.g., stress relaxation cracking) is discussed.

creep-fatigue↗

Autonomous Medical Care for Exploration

The goal of Autonomous Medical Care (AMC) is to ensure a healthy, well-performing crew which is a primary need for exploration. The end result of this effort will be the requirements and design for medical systems for the CEV, lunar operations, and Martian operations as well as a ground-based crew health optimization plan. Without such systems, we increase the risk of medical events occurring during a mission and we risk being unable to deal with contingencies of illness and injury, potentially threatening mission success. AMC has two major components: 1) pre-flight crew health optimization and 2) in-flight medical care. The goal of pre-flight crew health optimization is to reduce the risk of illness occurring during a mission by primary prevention and prophylactic measures. In-flight autonomous medical care is the capability to provide medical care during a mission with little or no real-time support from Earth. Crew medical officers or other crew members provide routine medical care as well as medical care to ill or injured crew members using resources available in their location. Ground support becomes telemedical consultation on-board systems/people collect relevant data for ground support to review. The AMC system provides capabilities to incorporate new procedures and training and advice as required. The on-board resources in an autonomous system should be as intelligent and integrated as is feasible, but autonomous does not mean that no human will be involved. The medical field is changing rapidly, and so a challenge is to determine which items to pursue now, which to leverage other efforts (e.g. military), and which to wait for commercial forces to mature. Given that what is used for the CEV or the Moon will likely be updated before going to Mars, a critical piece of the system design will be an architecture that provides for easy incorporation of new technologies into the system. Another challenge is to determine the level of care to provide for each mission type. The level of care refers to the amount and type of care one will render based on perceived need and ability. This is in contrast to the standard of care which is the benchmark by which that care is provided. There are certainly some devices and procedures that have unique microgravity or partial gravity requirements such that terrestrial methods will not work. For example, performing CPR on Mars cannot be done in exactly the same way as on Earth because the reduced gravity causes too large a reduction in the forces available for effective compression of the chest. Likewise, fluid behavior in microgravity may require a specialized water filtration and mixing system for the creation of intravenous fluids. This paper will outline the drivers for the design of the medical care systems, prioritization and planning techniques, key system components, and long term goals.

Johnson-Throop, Kathy A.↗

Assessing synergies and trade-offs of diverging Paris-compliant mitigation strategies with long-term SDG objectives

The Sustainable Development Goals (SDGs) and the Paris Agreement are the two transformative agendas, which set the benchmarks for nations to address urgent social, economic and environmental challenges. Aside from setting long-term goals, the pathways followed by nations will involve a series of synergies and trade-offs both between and within these agendas. Since it will not be possible to optimise across the 17 SDGs while simultaneously transitioning to low-carbon societies, it will be necessary to implement policies to address the most critical aspects of the agendas and understand the implications for the other dimensions. Here, we rely on a modelling exercise to analyse the long-term implications of a variety of Paris-compliant mitigation strategies suggested in the recent scientific literature on multiple dimensions of the SDG Agenda. The strategies included rely on technological solutions such as renewable energy deployment or carbon capture and storage, nature-based solutions such as afforestation and behavioural changes in the demand side. Results for a selection of energy-environment SDGs suggest that some mitigation pathways could have negative implications on food and water prices, forest cover and increase pressure on water resources depending on the strategy followed, while renewable energy shares, household energy costs, ambient air pollution and yield impacts could be improved simultaneously while reducing greenhouse gas emissions. Overall, results indicate that promoting changes in the demand side could be beneficial to limit potential trade-offs.

54 ENVIRONMENTAL SCIENCES↗

Dynamically robust coordinated set point tracking of distributed DERs at point of common coupling

Low-inertia operation of small-scale power systems, such as a microgrid or a portion of a long feeder, requires careful coordination of the controller performance of the constituting devices. This challenge is exacerbated in microgrids serving the functionalities of a conventional synchronous-based generation unit while comprised of smaller DERs operating mainly interfaced through power electronics converters. This paper builds on the idea of set point modulation and proposes a two-level control strategy that aims to achieve superior performance at the point of common coupling (PCC) of microgrids by combining a local control level with a distributed and coordinated level. Several case studies on both AC and DC systems, the CIGRE low-voltage benchmark system as the AC system and a test DC microgrid, validate the performance of the proposed approach. The real-world applicability of the approach is established via a high-fidelity power hardware-in-the-loop (PHIL) experimental setup and an application case study on grid frequency regulation. The proposed approach enables a microgrid to participate in ancillary service provisions where speed and quality of regulation are critical.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling of resistive plasma response in toroidal geometry using an asymptotic matching approach

The method of solving linear resistive plasma response, based on the asymptotic matching approach, is developed for full toroidal tokamaks by upgrading the Resistive DCON code [A.H. Glasser, Z.R. Wang and J.-K. Park, Physics of Plasmas, \textbf{23}, 112506 (2016)]. The derived matching matrix, asymptotically matching the outer and inner regions, indicates that the applied three dimension (3-D) magnetic perturbations contribute additional small solutions at each resonant surface due to the toroidal coupling of poloidal modes. In contrast, the resonant harmonic only affects the corresponding resonant surface in the cylindrical plasma. Since the solution of ideal outer region is critical to the asymptotic matching and is challenging to be solved in the toroidal geometry due to the singular power series solution at the resonant surfaces, systematic verification of the outer region $\Delta^\prime$ matrix is made by reproducing the well known analytical $\Delta^{\prime}$ result in [H.P. Furth, P.H. Rutherford and H. Selberg, The Physics of Fluids, \textbf{16}, 1054-1063 (1073)] as well as by making a quantitative benchmark with the PEST3 code [A. Pletzer and R.L. Dewar, J. Plasma Physics, \textbf{45}, 427-451 (1991)]. Finally, the reconstructed numerical solution of resistive plasma response from the toroidal matching matrix is presented. Comparing with the ideal plasma response, the global structure of the response can be affected by the small finite island at the resonant surfaces.

MHD simulation↗

HyMARC Seedling: Optimized Hydrogen Adsorbents via Machine Learning and Crystal Engineering

This final report is presented in two parts: In Part 1, the H 2 capacities of a diverse set of 918,734 metal-organic frameworks (MOFs) sourced from 19 databases is predicted via machine learning (ML). Using only 7 structural features as input, ML identifies 8,282 MOFs with the potential to exceed the capacities of state-of-the-art materials. The identified MOFs are predominantly hypothetical compounds having low densities (<0.31 g/cm3) in combination with high surface areas (>5,300 m2/g), void fractions ($0.90), and pore volumes (>3.3 cm3/g). The relative importance of the input features are characterized, and dependencies on the ML algorithm and training set size are quantified. The most important features for predicting H 2 uptake are pore volume (for gravimetric capacity) and void fraction (for volumetric capacity). The ML models are available on the web, allowing for rapid and accurate predictions of the hydrogen capacities of MOFs from limited structural data; the simplest models require only a single crystallographic feature. In part 2, ways to improve the poor powder packing density of MOFs is discussed. More specifically, a strategy that improves packing efficiency and volumetric hydrogen gas storage density dramatically through engineered morphologies and controlled-crystal size distributions is presented that holds promise for maximizing storage capacity for a given MOF. The packing density improvement, demonstrated for the benchmark sorbent MOF-5, leads to a significant enhancement of volumetric hydrogen storage performance relative to commercial MOF-5. System model projections demonstrate that engineering of crystal morphology/size or use of a bimodal distribution of cubic crystal sizes in tandem with system optimization can surpass the 25 g/L volumetric capacity of a typical 700 bar compressed storage system and exceed the DOE targets 2020 volumetric capacity (30 g/L). Finally, a critical link between improved powder packing density and reduced damage upon compaction is revealed leading to sorbents with both high surface area and high density.

08 HYDROGEN↗

Summary Report Of The FY25 Computational Fluid Dynamics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Verification and Validation (V&V) of numerical tools is critical for ensuring reasonable predictions during design, safety analysis, and licensing. Recent work in the Advanced Reactor Technologies - Gas-cooled Reactor (ART-GCR) program has focused on V&V of common Computational Fluid Dynamics (CFD) tools that are used within the Untied States. This report presents an update on these CFD V&V activities. These Generation IV Forum (GIF) Very High Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) is an international organization dedicated to the verification and validation of High Temperature Gas-Cooled Reactor (HTGR) simulation tools. Participation in the CMVB provides additional value to the V&V activities, as it allows for access to a wider range of data, and provides valuable benchmarking exercises. Three HTGR phenomena are targeted: Reactor Cavity Cooling System (RCCS) performance, core bypass flow, and lower plenum mixing. Simulations of the University of Wisconsin-Madison (UW-Madison) RCCS facilities are performed with Reynolds Averaged Navier-Stokes (RANS) in StarCCM+. Results are compared for both forced and natural convection conditions, with both exhibiting good agreement with experimental measurements. The Idaho National Laboratory (INL) matched index of refraction (MIR) and Korean Atomic Energy Research Institute (KAERI) bypass flow expeirments are used to validation CFD predictions of bypass flow. Simulations are performed with RANS in StarCCM+ and with Large Eddy Simulation (LES) in NekRS. Finally, preliminary simulations of the Institute of Nuclear and New Energy Technology (INET) lower plenum mixing facilities are presented. Initial work has developed models with LES, RANS, and porous media models. These preliminary models are presented and compared to each other to gauge differences in predictions with each of the three methods.

and Benchmarking (CMVB)↗

A study on the impact of using a subchannel resolution for modeling of large break loss of coolant accidents

The nuclear industry is investigating the feasibility of transitioning from 18- to 24-month fuel cycles because of the positive impact it would have on the operational costs for the current fleet of light-water reactors. A challenge to making this change is the increased risk of fuel fragmentation, relocation, and dispersal (FFRD) due to the known potential for ceramic fuel to pulverize into fine particles at the higher discharge burnups. Previous work has been performed by the Nuclear Energy Advanced Modeling and Simulation program to assess FFRD risk in high-burnup cores using the BISON fuel performance code and a coarse mesh thermal hydraulics (T/H) solution for a loss-of-coolant accident (LOCA) using the TRACE system T/H code. Because of the importance of the T/H solution for FFRD assessment, this study seeks to investigate the impact of using higher-fidelity subchannel techniques for modeling of the LOCA transient. CTF was used to model a subregion of a high-burnup core that was depleted by the Virtual Environment for Reactor Applications (VERA) multiphysics core simulator. Both coarse-mesh and pin-resolved models were created in CTF, and a consistent coarse-mesh TRACE model was also developed to allow for benchmarking the code results. Further, a large-break loss-of-coolant accident (LBLOCA) reflood transient was simulated using these three models, and results were compared. Results showed some consistent differences between the CTF and TRACE coarse models, including a higher peak cladding temperature (PCT) prediction in CTF and later quenching in CTF; however, the transient clad temperature behavior was similar, and these differences are likely due to post-critical heat flux heat transfer modeling differences and minimum film boiling temperature model differences. The pin-resolved results indicate that the PCT in the lumped model is often under-predicted by as much as 70 °C and that PCT occurs at a different location than the high-power pin in the assembly. The lumped model predicts a difference of 10 °C or less between the average and hot pins in the assembly, whereas the pin-resolved model predicts a range of over 100 °C. These results indicate that higher-fidelity T/H results may have an impact on predicted core behavior during LOCA, which may be important to consider when assessing FFRD risk.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Models implemented in the methodological approach to design the initial STEP first wall contour

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is managing the loads on the first wall within acceptable limits. Therefore, the conceptual design development of the STEP Prototype Power plant needs to be based on load estimates derived using legitimate plasma physics assumptions through dynamic and flexible tools. The current design foresees the STEP main chamber first wall to withstand steady-state heat loads of up to ~1 MW/m 2 , excluding critical regions expected to receive higher heat loads such as the baffle regions approaching the divertors. These critical areas will require ad hoc assessments and will be designed with the presence of limiters. This article focuses on the models and methodology adopted for designing the 2-D poloidal contour of the STEP first wall, based on the anticipated charged particle and radiation heat loads during normal operation. Firstly, the models adopted for calculating the charged particle and radiation heat loads are introduced. The first model is validated through benchmarking against the particle tracing code SMARDDA, while the second model is verified by comparing it with data from the MAST-U experiment. Secondly, the model used to design the 2-D first wall contour according to the heat loads is explained. We acknowledge that this preliminary design stage assumes certain simplifications, notably an axisymmetric geometry, for computational efficiency and clarity in presentation. It is understood that subsequent design phases will address the complexities of real-world engineering, including non-axisymmetric effects, transient plasma scenarios, and the impact of disruptions on the first wall design. Finally, an automatic procedure based on these models is presented for defining the 2-D poloidal contour of the STEP first wall to minimize heat loads, taking into account the need to radiate most of the alpha-particle and auxiliary heating power. Here, by providing an overview of the models, methodology, and an automatic procedure, this paper contributes to the design process of the STEP first wall, addressing the engineering challenges associated with fusion power plant development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Benchmarking core turbulence and transport predictions for an inductive compact tokamak reactor plasma

Motivated by the need for accurate, timely, and efficient calculations of plasma transport, predictions of plasma turbulence properties made using different TGLF saturation rules are benchmarked against corresponding predictions from linear and nonlinear gyrokinetic CGYRO simulations. This benchmarking is carried out using parameters taken from an inductive burning plasma scenario in a hypothetical compact high-field (R maj = 4 m, B T = 8 T) tokamak, lying in a much different regime of parameter space than either the TGLF calibration regime or current-day experiments. The core turbulent transport in this scenario is predicted to be dominated by ion temperature gradient (ITG) turbulence. In general, the ITG critical gradients predicted by various TGLF saturation rules are quite close to the CGYRO predictions. Both codes predict similar linear ITG growth rates and frequency spectra, as well as their scaling with R/L T i = −Rd ln(T i )/dr. However, TGLF systematically predicts unstable trapped-electron modes (TEMs) above k y ρ s ≃ 0.5 not seen by CGYRO for the same parameters, due to TGLF predicting a lower threshold in R/L T e than CGYRO for TEM onset. It is shown that for this scenario, nonlinear CGYRO simulations predict stiffer ITG turbulence than the TGLF SAT0 and SAT1 saturation rules, with energy fluxes close in magnitude and scaling with R/L T i to what is predicted by the SAT2 saturation rule. Self-consistent core profiles calculated using nonlinear CGYRO flux predictions and the PORTALS transport solver are shown to agree fairly well with corresponding predictions made using the TGLF SAT2 model, including a similar level of density peaking.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗