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At least 793 records · Page 44

Lunar Outpost Life Support Architecture Study Based on a High Mobility Exploration Scenario

As scenarios for lunar surface exploration and habitation continue to evolve within NASA s Constellation program, so must studies of optimal life support system architectures and technologies. This paper presents results of a life support architecture study based on a 2009 NASA scenario known as Scenario 12. Scenario 12 represents a consolidation of ideas from earlier NASA scenarios and includes an outpost near the Lunar South Pole comprised of three larger fixed surface elements and four attached pressurized rovers. The scenario places a high emphasis on surface mobility, with planning assuming that all four crewmembers spend roughly 50% of the time away from the outpost on 3-14 day excursions in two of the pressurized rovers. Some of the larger elements can also be mobilized for longer duration excursions. This emphasis on mobility poses a significant challenge for a regenerative life support system in terms of cost-effective waste collection and resource recovery across multiple elements, including rovers with very constrained infrastructure resources. The current study considers pressurized rovers as part of a distributed outpost life support architecture in both stand-alone and integrated configurations. A range of architectures are examined reflecting different levels of closure and distributed functionality. Different lander propellant scavenging options are also considered involving either initial conversion of residual oxygen and hydrogen propellants to water or initial direct oxygen scavenging. Monte Carlo simulations are used to assess the sensitivity of results to volatile high-impact mission variables, including the quantity of residual lander propellants available for scavenging, the fraction of crew time away from the outpost on excursions, total extravehicular activity hours, and habitat leakage. Architectures are evaluated by estimating surpluses or deficits of water and oxygen per 180-day mission and differences in fixed and 10-year-total equivalent system mass (ESM) relative to a reference case. Results are presented based on current assumptions for Scenario 12 and based on Monte Carlo simulations with assumed probability distributions for the high-impact mission variables. The calculated probability of no water or oxygen resupply from Monte Carlo simulations provides a quantitative measure of system robustness that can be used for cost/benefit analyses to identify leading architecture candidates. Areas of technology improvement that are likely to have a significant impact are also suggested.

Lange, Kevin E.↗

Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion

The authors built and tested a stochastic simulation to estimate achieved detection probabilities (DPs) on a stratum basis, over a tailorable range of diverted amounts from 0 to 2 significant quantities (SQ), using typical International Atomic Energy Agency (IAEA) inspection data: i.e., SQ in stratum, number of items, number of gross/partial/bias defect measurements conducted, and realistic relative standard deviation (RSD) values for typical IAEA verification measurements. For bulk strata, the model calculates achieved DP at 0.01 SQ diversion increments; for item strata, the model calculates DP using the smallest realistic diversion increment (e.g., a plate, pin, or coupon). After successfully benchmarking against IAEA deterministic models, the simulation was used to test the sensitivity of DP to certain standard assumptions and selected input parameters. First, the equal defect assumption was tested; the results suggest significant complexity in the effectiveness of partial defect measurements. Next, the authors explored the sensitivity of DP to the assumed RSD of attribute tests. Then, the authors compared non-normal models for instrument performance (e.g., logistic, step, or arbitrary functions) to the typical results from a normal distribution (characterized by RSD). This last comparison was supplemented with experimentally derived performance data for an HM-5 gamma spectrometer. The HM-5 was used to make enrichment measurements on both LEU and HEU MTR fuel elements as plates were removed, and the results fit with logistic and step curves and applied in the simulation. These stochastic DP results were compared to DP estimates from a deterministic model assuming a normal curve and typical RSD, yielding insights that could improve effectiveness in the field. These early results illustrate the potential of stochastic models to better understand achieved DP and to improve safeguards effectiveness.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Evaluation of LANDSAT-D Orbit Determination Using a Filter/Smoother (PREFER)

Simulated range and range rate data for five tracking stations were first generated using batch least squares orbit determination (GTDS). Then GTDS was used (in the differential correction mode) to produce a nominal trajectory which was input to PREFER. The GTDS differential correction (DC) run was made using models which differed from those used to produce the simulated data. These model differences were chosen to be fairly realistic approximations to the errors in the models actually used for operational orbit determination. Several different simulation runs were made with different types of model errors in order to determine the sensitivity to these errors. The nominal trajectory and the simulated measurement data were input to PREFER to produce a smoothed ephemeris file. Numerous runs of PREFER were made in which parameters describing the statistics of the model errors were varied. The likelihood function computed by the Kalman filter determined the ""best'' choice of input parameters. There was strong negative correlation between the likelihood function and the errors in the smoothed ephemeris.

Gibbs, B. P.↗

Lunar Outpost Life Support Architecture Study Based on a High-Mobility Exploration Scenario

This paper presents results of a life support architecture study based on a 2009 NASA lunar surface exploration scenario known as Scenario 12. The study focuses on the assembly complete outpost configuration and includes pressurized rovers as part of a distributed outpost architecture in both stand-alone and integrated configurations. A range of life support architectures are examined reflecting different levels of closure and distributed functionality. Monte Carlo simulations are used to assess the sensitivity of results to volatile high-impact mission variables, including the quantity of residual Lander oxygen and hydrogen propellants available for scavenging, the fraction of crew time away from the outpost on excursions, total extravehicular activity hours, and habitat leakage. Surpluses or deficits of water and oxygen are reported for each architecture, along with fixed and 10-year total equivalent system mass estimates relative to a reference case. System robustness is discussed in terms of the probability of no water or oxygen resupply as determined from the Monte Carlo simulations.

Lange, Kevin E.↗

Radiometric calibration of a polarization-sensitive sensor

The radiometric accuracy of a sensor is adversely affected by scene polarization if its optical system is sensitive to polarization. Tests performed on the reflective bands of the NS001 Thematic Mapper simulator, an aircraft multispectral scanner, show that it is very sensitive to the polarization state of the incoming radiations. For 100 percent linearly polarized light, errors in the measured intensity vary from -40 to +40 percent, depending on the scan angle and spectral band. To estimate polarization-induced errors in the intensity measured at aircraft level, the intensity and polarization of the atmospheric radiances were simulated using a realistic earth-atmosphere radiative transfer model. For the polarization of atmospheric radiances in the solar meridian plane over a vegetated target, intensity errors may range from -10 to + 10 percent. The polarization-induced errors are highest in the shortest NS001 spectral band (0.450-0.525 microns) because of large atmospheric polarizations contributed by Rayleigh particles and small diluting effects caused by the small contributions of weakly polarized radiations coming from aerosols and the surface. Depending on the illumination and view angles, the errors in derived surface reflectance due to the radiance errors can be very large. In particular, for large off-nadir view angles in the forward scattered direction when the sun is low, the relative errors in the derived surface reflectance can be as large as 4 to 5 times the relative error in the radiances. Polarization sensitivity errors cannot be neglected for the shorter wavelengths when the surface reflectance contribution to atmospheric radiances is very small.

Ahmad, Suraiya P.↗

End-to-end Modeling of Lyot Coronagraph for LUVOIR: Sensitivity to Segment-Level Aberrations

Direct imaging and spectroscopic characterization of atmospheres of Earth-like exoplanets require starlight suppression to detect a faint planetary signal at small angular separations. Future space telescopes will require segmentation to survey a statistically significant population of nearby stars systems by increasing aperture size beyond the limits set by traditional monolithic apertures; however, segmentation also represents an additional challenge due to the introduction of temporal pupil discontinuities in terms of both phase and amplitude. For this study, a baseline Lyot coronagraph is used with the Large UV / Optical /Infrared (LUVOIR) mission’s 15-m on-axis, segmented optical telescope assembly (OTA). We present a high-fidelity, end-to-end modeling approach developed as part of the Segmented Coronagraph Design and Analysis (SCDA) group that includes diffractive optical propagations at the 1e-10 contrast level across the entire optical train including the OTA and intermediate re-imaging optics inside the coronagraph instrument. We perform a tolerancing analysis to assess the contrast sensitivity to wavefront perturbations for a set of key telescope terms including segment-level low-order and mid-spatial frequency aberrations. As an input to the end-to-end telescope model, we use two industry-provided segment-level wavefront aberration datasets pertaining: (1) thermal gradients and accelerations (courtesy of Ball-Aerospace and L3-Harris), and (2) telescope dynamics including line-of-sight and segment jitter (courtesy of Lockheed-Martin). Contrast performance outputs of the coronagraph are fed into a mission design reference simulator to assess the scientific yield sensitivity. End-to-end modeling will incorporate performance improvements due to active wavefront sensing and control and/or segment-level metrology to improve system performance.

Optics↗

Structure and dynamics of $\mathrm{Fe_{90}}$$\mathrm{Si_3}$$\mathrm{O_7}$ liquids close to Earth's liquid core conditions

Using an artificial neural-network machine learning interatomic potential, we have performed molecular dynamics simulations to study the structure and dynamics of $\mathrm{Fe_{90}}$$\mathrm{Si_3}$$\mathrm{O_7}$ liquid close to the Earth's liquid core conditions. Here, the simulation results reveal that the short-range structural order (SRO) in the $\mathrm{Fe_{90}}$$\mathrm{Si_3}$$\mathrm{O_7}$ liquid is very strong. About 80% of the atoms are arranged in crystallinelike SRO motifs. In particular, ~ $70$% of Fe-centered clusters can be classified as either hexagonal-close-packed-like or icosahedrallike SRO motifs. The SRO clusters centered on Fe, Si, or O atoms are strongly intermixed and homogenously distributed throughout the liquid. The atomic structure of the liquid and the fractions of dominant SRO clusters are not sensitive to pressure/temperature used in the simulations except that the SRO of the O-centered clusters is enhanced close to inner core pressures. The O-diffusion coefficient is about two to three times larger than the Fe and Si ions and increases more rapidly in the deeper core regions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Survey and Method for Determination of Trajectory Predictor Requirements

A survey of air-traffic-management researchers, representing a broad range of automation applications, was conducted to document trajectory-predictor requirements for future decision-support systems. Results indicated that the researchers were unable to articulate a basic set of trajectory-prediction requirements for their automation concepts. Survey responses showed the need to establish a process to help developers determine the trajectory-predictor-performance requirements for their concepts. Two methods for determining trajectory-predictor requirements are introduced. A fast-time simulation method is discussed that captures the sensitivity of a concept to the performance of its trajectory-prediction capability. A characterization method is proposed to provide quicker, yet less precise results, based on analysis and simulation to characterize the trajectory-prediction errors associated with key modeling options for a specific concept. Concept developers can then identify the relative sizes of errors associated with key modeling options, and qualitatively determine which options lead to significant errors. The characterization method is demonstrated for a case study involving future airport surface traffic management automation. Of the top four sources of error, results indicated that the error associated with accelerations to and from turn speeds was unacceptable, the error associated with the turn path model was acceptable, and the error associated with taxi-speed estimation was of concern and needed a higher fidelity concept simulation to obtain a more precise result

Rentas, Tamika L.↗

Model and remote-sensing-guided experimental design and hypothesis generation for monitoring snow-soil–plant interactions

In this study, we develop a machine-learning (ML)-enabled strategy for selecting hillslope-scale ecohydrological monitoring sites within snow-dominated mountainous watersheds, with a particular focus on snow-soil–plant interactions. Data layers rely on spatial data layers from both remote sensing and hydrological model simulations. Specifically, a Landsat-based foresummer drought sensitivity index is used to define the dependency of the annual peak plant productivity on the Palmer drought severity index in the early growing season. Hydrological simulations provide the spatiotemporal dynamics of near-surface soil moisture and snow depth. In this framework, a regression analysis identifies the key hydrological variables relevant to the spatial heterogeneity of drought sensitivity. We then apply unsupervised clustering to these key variables, using the Gaussian mixture model, to group hillslopes into several zones that have divergent relationships regarding soil moisture, snow dynamics, and drought sensitivity. Using the datasets collected in the East River Watershed (Crested Butte, Colorado, United States), results show that drought sensitivity is significantly correlated with model-derived soil moisture and snow-free timing over space and time. The relationship is, however, non-linear, such that the correlation decreases above a threshold elevation and in a heavy snow year due to large snowpacks, lateral flow, and soil storage limitations. Clustering is then able to define the zones that have high or low sensitivity to drought, as well as the mid-elevation regions where sensitivity is associated with the topographic aspect and net potential radiation. In addition, the algorithm identifies the most representative hillslopes with road/trail access within each zone for installing monitoring sites. Our method also aims to significantly increase the use of ML and model-simulation results to guide critical zone and watershed monitoring activities.

54 ENVIRONMENTAL SCIENCES↗

Digital data processing system dynamic loading analysis

Simulation and analysis of the Space Shuttle Orbiter Digital Data Processing System (DDPS) are reported. The mated flight and postseparation flight phases of the space shuttle's approach and landing test configuration were modeled utilizing the Information Management System Interpretative Model (IMSIM) in a computerized simulation modeling of the ALT hardware, software, and workload. System requirements simulated for the ALT configuration were defined. Sensitivity analyses determined areas of potential data flow problems in DDPS operation. Based on the defined system requirements and the sensitivity analyses, a test design is described for adapting, parameterizing, and executing the IMSIM. Varying load and stress conditions for the model execution are given. The analyses of the computer simulation runs were documented as results, conclusions, and recommendations for DDPS improvements.

Lagas, J. J.↗

Model‐Based Approach to Selecting Pegfilgrastim Dose for Pharmacokinetic and Pharmacodynamic Similarity Studies in Biosimilar Development

This study applied modeling and simulation (M&S) approaches to evaluate the sensitivity of pegfilgrastim pharmacokinetics (PKs) and pharmacodynamics (PDs) to changes in dose amount, and linear or nonlinear clearance (CL) over pegfilgrastim subcutaneous dose of 2–6 mg. A previously published model was adapted to better describe pegfilgrastim PK and PD data in healthy subjects and used in simulation. Nonlinear CL accounts for 98% and 77%, respectively, of the total CL of pegfilgrastim at 2 and 6 mg. The sensitivity analyses showed: (i) PK of 2 and 6 mg doses are similarly sensitive to detect differences for a 5% change in dose; (ii) PK of 2 mg dose is more sensitive to changes in receptor binding affinity, a model parameter for nonlinear CL, and a product quality attribute characterized with orthogonal methods as part of demonstrating analytical similarity between products; (iii) PK of approved 6 mg dose is more sensitive to changes in linear CL, which has not been associated with any specific product quality attributes, and (iv) the PDs are not sensitive to changes in linear or nonlinear CL. Taken together, our analyses support that the approved pegfilgrastim dose of 6 mg is appropriate for detecting differences between a biosimilar and the reference products in pegfilgrastim PK and PD similarity studies. The described M&S approaches can be adopted to support dose selection for biosimilars with nonlinear PK and complex PK–PD interplay.

Pharmacology & Pharmacy↗

Direct and semi-direct radiative forcing of biomass-burning aerosols over the southeast Atlantic (SEA) and its sensitivity to absorbing properties: a regional climate modeling study

Simulations are performed for the period 2000-2015 by two different regional climate models, ALADIN and RegCM, to quantify the direct and semi-direct radiative effects of biomass-burning aerosols (BBAs) in the southeast Atlantic (SEA) region. Different simulations have been performed using strongly absorbing BBAs in accordance with recent in situ observations over the SEA. For the July-August-September (JAS) season, the single scattering albedo (SSA) and total aerosol optical depth (AOD) simulated by the ALADIN and RegCM models are consistent with the MACv2 climatology and MERRA-2 and CAMS-RA reanalyses near the biomass-burning emission sources. However, the above-cloud AOD is slightly underestimated compared to satellite (MODIS and POLDER) data during the transport over the SEA. The direct radiative effect exerted at the continental and oceanic surfaces by BBAs is significant in both models and the radiative effects at the top of the atmosphere indicate a remarkable regional contrast over SEA (in all-sky conditions), with a cooling (warming) north (south) of 10°S, which is in agreement with the recent MACv2 climatology. In addition, the two models indicate that BBAs are responsible for an important shortwave radiative heating of ~0.5-1K per day over SEA during JAS with maxima between 2 and 4 km a.m.s.l. (above mean sea level). At these altitudes, BBAs increase air temperature by ~0.2-0.5 K, with the highest values being co-located with low stratocumulus clouds. Vertical changes in air temperature limit the subsidence of air mass over SEA, creating a cyclonic anomaly. The opposite effect is simulated over the continent due to the increase in lower troposphere stability. The BBA semi-direct effect on the lower troposphere circulation is found to be consistent between the two models. Changes in the cloud fraction are moderate in response to the presence of smoke, and the models differ over the Gulf of Guinea. Finally, the results indicate an important sensitivity of the direct and semi-direct effects to the absorbing properties of BBAs. Over the stratocumulus (Sc) region, DRE varies from +0.94 W m -2 (scattering BBAs) to +3.93 W m -2 (most absorbing BBAs).

54 ENVIRONMENTAL SCIENCES↗

Direct and Semi-Direct Radiative Forcing of Biomass-Burning Aerosols Over the Southeast Atlantic (SEA) And Its Sensitivity to Absorbing Properties: A Regional Climate Modeling Study

Simulations are performed for the period 2000–2015 by two different regional climate models, ALADIN and RegCM, to quantify the direct and semi-direct radiative effects of biomass-burning aerosols (BBAs) in the southeast Atlantic (SEA) region. Different simulations have been performed using strongly absorbing BBAs in accordance with recent in situ observations over the SEA. For the July–August–September (JAS) season, the single scattering albedo (SSA) and total aerosol optical depth (AOD) simulated by the ALADIN and RegCM models are consistent with the MACv2 climatology and MERRA-2 and CAMS-RA reanalyses near the biomass-burning emission sources. However, the above-cloud AOD is slightly underestimated compared to satellite (MODIS and POLDER) data during the transport over the SEA. The direct radiative effect exerted at the continental and oceanic surfaces by BBAs is significant in both models and the radiative effects at the top of the atmosphere indicate a remarkable regional contrast over SEA (in all-sky conditions), with a cooling (warming) north (south) of 10 ∘S, which is in agreement with the recent MACv2 climatology. In addition, the two models indicate that BBAs are responsible for an important shortwave radiative heating of ∼0.5–1 K per day over SEA during JAS with maxima between 2 and 4 km a.m.s.l. (above mean sea level). At these altitudes, BBAs increase air temperature by ∼0.2–0.5 K, with the highest values being co-located with low stratocumulus clouds. Vertical changes in air temperature limit the subsidence of air mass over SEA, creating a cyclonic anomaly. The opposite effect is simulated over the continent due to the increase in lower troposphere stability. The BBA semi-direct effect on the lower troposphere circulation is found to be consistent between the two models. Changes in the cloud fraction are moderate in response to the presence of smoke, and the models differ over the Gulf of Guinea. Finally, the results indicate an important sensitivity of the direct and semi-direct effects to the absorbing properties of BBAs. Over the stratocumulus (Sc) region, DRE varies from +0.94 W m−2 (scattering BBAs) to +3.93 W m−2 (most absorbing BBAs).

Marc Mallet↗

Ocean Surface Flux Algorithm Effects on Earth System Model Energy and Water Cycles

Earth system models parameterize ocean surface fluxes of heat, moisture, and momentum with empirical bulk flux algorithms, which introduce biases and uncertainties into simulations. We investigate the atmosphere and ocean model sensitivity to algorithm choice in the Energy Exascale Earth System Model (E3SM). Flux differences between algorithms are larger in atmosphere simulations (where wind speeds can vary) than ocean simulations (where wind speeds are fixed by forcing data). Surface flux changes lead to global scale changes in the energy and water cycles, notably including ocean heat uptake and global mean precipitation rates. Compared to the control algorithm, both COARE and University of Arizona (UA) algorithms reduce global mean precipitation and top of atmosphere radiative biases. Further, UA may slightly reduce biases in ocean meridional heat transport. We speculate that changes seen here, especially in the ocean, could be even larger in coupled simulations.

54 ENVIRONMENTAL SCIENCES↗

Multi-Defect Detection in Additively Manufactured Lattice Structures Using 3D Electrical Resistance Tomography

Cellular lattice structures possess high strength-to-weight ratios suitable for advanced lightweight engineering applications. However, their quality and mechanical performance can degrade because of defects introduced during manufacturing or in-service. Their complexity and small length scale features make defects difficult to detect using conventional nondestructive evaluation methods. Here we propose a current injection-based method, electrical resistance tomography (ERT), that can be used to detect damaged struts in conductive cellular lattice structures with their intrinsic electromechanical properties. The reconstructed conductivity distributions from ERT can reveal the severity and location of damaged struts without having to probe each strut. However, the low central sensitivity of ERT may result in image artifacts and inaccurate localization of damaged struts. To address this issue, this study introduces an absolute, high throughput, conductivity reconstruction algorithm for 3D ERT. The algorithm incorporates a strut-based normalized sensitivity map to compensate for lower interior sensitivity and suppresses reconstruction artifacts. Numerical simulations and experiments on fabricated representative cellular lattice structures were performed to verify the ability of ERT to quantitatively identify single and multiple damaged struts. The improved performance of this method compared with classical ERT was observed, based on greatly decreased imaging and reconstructed value errors.

36 MATERIALS SCIENCE↗

Implementation of Perturbation Theory and Sensitivity Capabilities in Griffin

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor Multiphysics analysis application, jointly developed by Argonne and Idaho National Laboratories under the DOE-NE NEAMS program. This fiscal year, capabilities for reactivity and sensitivity evaluation using perturbation methods were implemented and verified. The First Order Perturbation Method (FOPT) was employed to compute reactivity worth resulting from small perturbations in input parameters, while the Generalized Perturbation Theory (GPT) was used to evaluate sensitivities of a range of response types, including reaction rate ratio, k-eigenvalue, neutron generation time, and effective delayed neutron fraction. These perturbation methods enable users to quantify how response quantities change due to a perturbation in a input parameter without explicitly performing an additional transport simulation for each perturbed state. In particular, the GPT formulation accounts for indirect effects arising from flux changes by solving generalized inhomogeneous equations, for which a Neumann series-based iterative solution method was developed and implemented in Griffin. The implemented reactivity and sensitivity evaluation capabilities were verified using two test problems: an infinite homogeneous system and a two-dimensional hexagonal core. The results showed excellent agreement with reference solutions obtained by a direct method based on finite difference approximation as well as GPT-based results from the PERSENT code, confirming the accuracy of both reactivity and sensitivity evaluations. Additionally, preliminary uncertainty quantification (UQ) results were obtained by combining the sensitivity values computed using GPT and external covariance data, demonstrating that the implemented sensitivity results can be reliably used for uncertainty calculations. To further demonstrate the generality and practical strength of the implementation, the sensitivity evaluation capability was successfully applied to the Empire microreactor with a geometrically complex design that poses significant modeling challenges. The results confirm that Griffin enables sensitivity evaluations even for irregular and highly heterogeneous reactor configurations, thereby establishing a foundation for UQ applications in advanced reactor designs and analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Factors Controlling the Properties of Multi-Phase Arctic Stratocumulus Clouds

The 2004 Multi-Phase Arctic Cloud Experiment (M-PACE) IOP at the ARM NSA site focused on measuring the properties of autumn transition-season arctic stratus and the environmental conditions controlling them, including concentrations of heterogeneous ice nuclei. Our work aims to use a large-eddy simulation (LES) code with embedded size-resolved aerosol and cloud microphysics to identify factors controlling multi-phase arctic stratus. Our preliminary simulations of autumn transition-season clouds observed during the 1994 Beaufort and Arctic Seas Experiment (BASE) indicated that low concentrations of ice nuclei, which were not measured, may have significantly lowered liquid water content and thereby stabilized cloud evolution. However, cloud drop concentrations appeared to be virtually immune to changes in liquid water content, indicating an active Bergeron process with little effect of collection on drop number concentration. We will compare these results with preliminary simulations from October 8-13 during MPACE. The sensitivity of cloud properties to uncertainty in other factors, such as large-scale forcings and aerosol profiles, will also be investigated. Based on the LES simulations with M-PACE data, preliminary results from the NASA GlSS single-column model (SCM) will be used to examine the sensitivity of predicted cloud properties to changing cloud drop number concentrations for multi-phase arctic clouds. Present parametrizations assumed fixed cloud droplet number concentrations and these will be modified using M-PACE data.

Fridlind, Ann↗

Validation of edge turbulence codes against the TCV-X21 diverted L-mode reference case

Self-consistent full-size turbulent-transport simulations of the divertor and scrape-off-layer (SOL) of existing tokamaks have recently become feasible. This enables the direct comparison of turbulence simulations against experimental measurements. In this work, we perform a series of diverted ohmic L-mode discharges on the tokamak à configuration variable (TCV) tokamak, building a first-of-a-kind dataset for the validation of edge turbulence models. This dataset, referred to as TCV-X21, contains measurements from five diagnostic systems from the outboard midplane (OMP) to the divertor targets—giving a total of 45 one- and two-dimensional comparison observables in two toroidal magnetic field directions. The experimental dataset is used to validate three flux-driven 3D fluid-turbulence models—GBS, GRILLIX and TOKAM3X. With each model, we perform simulations of the TCV-X21 scenario, individually tuning the particle and power source rates to achieve a reasonable match of the upstream separatrix value of density and electron temperature. We find that the simulations match the experimental profiles for most observables at the OMP—both in terms of profile shape and absolute magnitude—while a comparatively poorer agreement is found towards the divertor targets. The match between simulation and experiment is seen to be sensitive to the value of the resistivity, the heat conductivities, the power injection rate and the choice of sheath boundary conditions. Additionally, despite targeting a sheath-limited regime, the discrepancy between simulations and experiment also suggests that the neutral dynamics should be included. The results of this validation show that turbulence models are able to perform simulations of existing devices and achieve reasonable agreement with experimental measurements. Where disagreement is found, the validation helps to identify how the models can be improved. By publicly releasing the experimental dataset and validation analysis, this work should help to guide and accelerate the development of predictive turbulence simulations of the edge and SOL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗