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At least 217 records · Page 12

Cassini Observations of Plasmoid Structure and Dynamics: Implications for the Role of Magnetic Reconnection in Magnetospheric Circulation at Saturn

We survey the Cassini magnetometer data during the deep tail orbits in 2006, and find 34 direct encounters with plasmoids. They occur as single, isolated events but also in groups of two or more plasmoids as is frequently observed at Earth . We show a case study example of three such plasmoids over three hours, where we estimate an upper limit of 5.68 GWb of flux closure, and derive a reconnection rate over this interval of 526 kV. We show the results of a superposed epoch analysis of al1 34 plasmoids indicating that, on average, plasmoids at Saturn are approix.8 min in duration and they tend toward a loop-like, as opposed to flux rope-like topology, with little or no axial core magnetic field. Our analysis shows that plasmoids at Saturn are followed by an extended interval of the post-plasmoid plasma sheet (PPPS) lasting approx.58 min. The average open magnetic flux disconnected by the continued reconnet:tion following plasmoid formation that creates the PPPS is approx.3 GWb. We calculate expected recurrence rates for plasmoids, and compare these with a derived observational recurrence rate of one plasmoid every approx.2.4 days, explaining the reasons why the spacecraft has not observed as many plasmoids as we predict will be released. We conclude that the Cassini magnetometer measurements require a combination of Vasyliunas-type closed-flux plasma sheet and Dungey-type open-flux lobe reconnection to account for the observed properties of the plasmoids and PPPS in Saturn's magnetotail.

Jackman, C. M.↗

Comparison Between Path Lengths Traveled by Solar Electrons and Ions in Ground-Level Enhancement Events

We have examined the Wind/3DP/SST electron and Wind/EPACT/LEMT ion data to investigate the path length difference between solar electrons and ions in the ground-level enhancement (GLE) events in solar cycle 23. Assuming that the onset time of metric type II or decameter-hectometric (DH) type III radio bursts is the solar release time of non-relativistic electrons, we have found that within an error range of plus or minus 10% the deduced path length of low-energy (approximately 27 keV) electrons from their release site near the Sun to the 1 AU observer is consistent with the ion path length deduced by Reames from the onset time analysis. In addition, the solar longitude distribution and IMF topology of the GLE events examined are in favor of the coronal mass ejection-driven shock acceleration origin of observed non-relativistic electrons.We have also found an increase of electron path lengths with increasing electron energies. The increasing rate of path lengths is correlated with the pitch angle distribution (PAD) of peak electron intensities locally measured, with a higher rate corresponding to a broader PAD. The correlation indicates that the path length enhancement is due to the interplanetary scattering experienced by first arriving electrons. The observed path length consistency implies that the maximum stable time of magnetic flux tubes, along which particles transport, could reach 4.8 hr.

electrons↗

Predicting Large‐Scale Systematic Missing Pipe Attributes in Water Distribution Networks

Water distribution network (WDN) models are an essential tool used by water utilities for hydraulic analysis. Unfortunately, missing data and insufficient resources often make creating and maintaining these models unfeasible. Existing methods to address missing pipe properties, like sequential imputation for missing values and reconstruction using graph metrics, are designed to accommodate random patterns of missing information and require a significant percentage of the system's attributes to be known. However, these data completeness assumptions do not always align with real‐world scenarios where large sections of the WDN model have missing data. To address this challenge, this study proposes a data‐driven approach for estimating pipe diameter when considering different spatial patterns and degrees of data completeness (i.e., 0%–90%). Using data from 16 WDNs in Kentucky, this study compares the use of machine learning (ML) using topological and geospatial features against an existing deterministic approach. Results demonstrate that WDN models with pipe diameters predicted by the proposed ML method had comparable hydraulic performance to the ground truth models. Moreover, results showed that ML method performance varies between WDNs of differing topological classification. Insights from this study help advance the ability to leverage partial data to create and maintain WDN models amid uncertainty and inadequate resources.

Poff, Jason W. [Oregon State Univ., Corvallis, OR ↗

A Data-Driven Reduced Order Model of an Isolated Rotor

There are numerous conceptual design stage rotorcraft analysis tasks which demand a high-fidelity and low cost method for rotor load distribution predictions. Considering Urban Air Mobility (UAM) vehicles aim to operate in close proximity to buildings and with unique rotor configurations, there is a significant challenge in quickly and accurately modeling rotors operating in complex, turbulent flow fields. One potential path for deriving a high-fidelity, low cost rotor model is with data-driven surrogate modeling. In this study, an initial investigation is taken to apply a proper orthogonal decomposition (POD) based reduced order model (ROM) for the purpose of pressure distribution prediction. In this study, a POD ROM was derived to produce distributed pressure predictions on rotor blades subjected to topology change due to variation in twist and taper ratio. Rotor twist was varied between 0◦, 10◦, 20◦, and 30◦ while taper ratio was varied between 1.0, 0.9, 0.8, and 0.7. All rotors consisted of a single blade. The POD ROM was validated for three demonstration cases; a high thrust rotor in hover, a low thrust rotor in hover, and a rotor in forward flight with a flight speed of M = 0.1. Results showed highly accurate distributed load predictions could be achieved at minimal computational cost. Computational cost for hovering blade surface pressure modeling was reduced from 12 hours on 440 cores to 10−5 seconds on a single core. For blade in forward flight cost was reduced from 20 hours on 440 cores to 0.6 seconds on a single core. For cases of high thrust and low thrust rotors, POD ROM was used to undergo a design optimization of the rotor such that figure of merit was maximized. Total optimization time for each case was 1 minute.

Data-Driven↗

Joint Characterization of Vegetation by Satellite Observations from Visible to Microwave Wavelengths - A Sensitivity Analysis

This study presents an evaluation and comparison of visible, near-infrared, passive, and active microwave observations for vegetation characterization on a global basis for a year, with spatial resolution compatible with climatological studies. Visible and near-infrared observations along with the Normalized Difference Vegetation Index come from the Advanced Very High Resolution Radiometer. An atlas of monthly mean microwave land surface emissivities from 19 to 85 GHz has been calculated from the Special Sensor Microwave/Imager for a year, suppressing the atmospheric problems encountered with the use of simple channel combinations. The active microwave measurements are provided by the ERS-1 scatterometer at 5.25 GHz. The capacity to discriminate between vegetation types and to detect the vegetation phenology is assessed in the context of a vegetation classification obtained from in situ observations. A clustering technique derived from the Kohonen topological maps is used to merge the three data sets and interpret their relative variations. NDVI varies with vegetation density but is not very sensitive in semiarid environments and in forested areas. Spurious seasonal cycles and large spatial variability in several areas suggest that atmospheric contamination and/or solar zenith angle drift still affect the NDVI.

NORMALIZED DIFFERENCE VEGETATIVE INDEX↗

A general multiblock Euler code for propulsion integration. Volume 1: Theory document

A general multiblock Euler solver was developed for the analysis of flow fields over geometrically complex configurations either in free air or in a wind tunnel. In this approach, the external space around a complex configuration was divided into a number of topologically simple blocks, so that surface-fitted grids and an efficient flow solution algorithm could be easily applied in each block. The computational grid in each block is generated using a combination of algebraic and elliptic methods. A grid generation/flow solver interface program was developed to facilitate the establishment of block-to-block relations and the boundary conditions for each block. The flow solver utilizes a finite volume formulation and an explicit time stepping scheme to solve the Euler equations. A multiblock version of the multigrid method was developed to accelerate the convergence of the calculations. The generality of the method was demonstrated through the analysis of two complex configurations at various flow conditions. Results were compared to available test data. Two accompanying volumes, user manuals for the preparation of multi-block grids (vol. 2) and for the Euler flow solver (vol. 3), provide information on input data format and program execution.

Chen, H. C.↗

Model-Based Systems Engineering, Real-Time Operations, and Autonomy

Model-Based Systems Engineering has been enabled by the development of the SysML language and software tools to create systems models. Systems models described in SysML incorporate frames (Diagrams) that represent behaviors (activities, sequences, state machines, use cases), requirements, and structure (definitions, internal structure, parametric formulation, and packaging). The SysML models are, in turn, used by applications to do analysis and studies of the designs and operational capabilities. These uses of the model are based on simulations, and do not include hardware. This paper presents a software environment and processes that enables more comprehensive systems models for MBSE, and use of these rich models for real-time operations. The paper describes a software platform that enables creation of comprehensive models, beyond what is now possible with SysML and related software tools, called the NASA Platform for Autonomous Systems (NPAS). The platform encapsulates a paradigm and infrastructure for creating systems models with complexity levels comparable to the ones handled by SysML software tools, but with additional fidelity that includes detailed design diagrams encompassing sensors, components, and design topologies. Furthermore, NPAS enables incorporation of data, information, and knowledge (DIaK) to implement autonomy and Integrated System Health Management (ISHM) and the inherent integration of content encompassing SysML structure and behavior diagrams throughout the NPAS modelAnd lastly, the NPAS models are used in real-time operations, taking advantage of the fidelity and complexity encompassed in the models in order to implement “thinking” ISHM and/or autonomous operations. . Incorporation of SysML model content into an NPAS model is briefly discussed.

MBSE↗

Cosmology with persistent homology: a Fisher forecast

Abstract Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool to the dark matter halo catalogs from theQuijotesimulations, and build a summary statistic for comparison with the joint power spectrum and bispectrum statistic regarding their information content on cosmological parameters and primordial non-Gaussianity. Through a Fisher analysis, we find that constraints from persistent homology are tighter for 8 out of the 10 parameters by margins of 13–50%. The complementarity of the two statistics breaks parameter degeneracies, allowing for a further gain in constraining power when combined. We run a series of consistency checks to consolidate our results, and conclude that our findings motivate incorporating persistent homology into inference pipelines for cosmological survey data.

Astronomy & Astrophysics↗

Challenges to Computational Aerothermodynamic Simulation and Validation for Planetary Entry Vehicle Analysis

Challenges to computational aerothermodynamic (CA) simulation and validation of hypersonic flow over planetary entry vehicles are discussed. Entry, descent, and landing (EDL) of high mass to Mars is a significant driver of new simulation requirements. These requirements include simulation of large deployable, flexible structures and interactions with reaction control system (RCS) and retro-thruster jets. Simulation of radiation and ablation coupled to the flow solver continues to be a high priority for planetary entry analyses, especially for return to Earth and outer planet missions. Three research areas addressing these challenges are emphasized. The first addresses the need to obtain accurate heating on unstructured tetrahedral grid systems to take advantage of flexibility in grid generation and grid adaptation. A multi-dimensional inviscid flux reconstruction algorithm is defined that is oriented with local flow topology as opposed to grid. The second addresses coupling of radiation and ablation to the hypersonic flow solver - flight- and ground-based data are used to provide limited validation of these multi-physics simulations. The third addresses the challenges of retro-propulsion simulation and the criticality of grid adaptation in this application. The evolution of CA to become a tool for innovation of EDL systems requires a successful resolution of these challenges.

Gnoffo, Peter A.↗

Challenges to Computational Aerothermodynamic Simulation and Validation for Planetary Entry Vehicle Analysis

Challenges to computational aerothermodynamic (CA) simulation and validation of hypersonic flow over planetary entry vehicles are discussed. Entry, descent, and landing (EDL) of high mass to Mars is a significant driver of new simulation requirements. These requirements include simulation of large deployable, flexible structures and interactions with reaction control system (RCS) and retro-thruster jets. Simulation of radiation and ablation coupled to the flow solver continues to be a high priority for planetary entry analyses, especially for return to Earth and outer planet missions. Three research areas addressing these challenges are emphasized. The first addresses the need to obtain accurate heating on unstructured tetrahedral grid systems to take advantage of flexibility in grid generation and grid adaptation. A multi-dimensional inviscid flux reconstruction algorithm is defined that is oriented with local flow topology as opposed to grid. The second addresses coupling of radiation and ablation to the hypersonic flow solver--flight- and ground-based data are used to provide limited validation of these multi-physics simulations. The third addresses the challenges of retro-propulsion simulation and the criticality of grid adaptation in this application. The evolution of CA to become a tool for innovation of EDL systems requires a successful resolution of these challenges.

Gnoffo, Peter A.↗

Topological analysis of the CfA redshift survey

We study the topology of large-scale structure in the Center for Astrophysics Redshift Survey, which now includes approximately 12,000 galaxies with limiting magnitude m(sub B) is less than or equal to 15.5. The dense sampling and large volume of this survey allow us to compute the topology on smoothing scales from 6 to 20/h Mpc; we thus examine the topology of structure in both 'nonlinear' and 'linear' regimes. On smoothing scales less than or equal to 10/h Mpc this sample has 3 times the number of resolution elements of samples examined in previous studies. Isodensity surface of the smoothed galaxy density field demonstrate that coherent high-density structures and large voids dominate the galaxy distribution. We compute the genus-threshold density relation for isodensity surfaces of the CfA survey. To quantify phase correlation in these data, we compare the CfA genus with the genus of realizations of Gaussian random fields with the power spectrum measured for the CfA survey. On scales less than or equal to 10/h Mpc the observed genus amplitude is smaller than random phase (96% confidence level). This decrement reflects the degree of phase coherence in the observed galaxy distribution. In other words the genus amplitude on these scales is not good measure of the power spectrum slope. On scales greater than 10/h Mpc, where the galaxy distribution is rougly in the 'linear' regime, the genus ampitude is consistent with the random phase amplitude. The shape of the genus curve reflects the strong coherence in the observed structure; the observed genus curve appears broader than random phase (94% confidence level for smoothing scales less than or equal to 10/h Mpc) because the topolgoy is spongelike over a very large range of density threshold. This departre from random phase consistent with a distribution like a filamentary net of 'walls with holes.' On smoothing scales approaching approximately 20/h Mpc the shape of the CfA genus curve is consistent with random phase. There is very weak evidence for a shift of the genus toward a 'bubble-like' topology. To test cosmological models, we compute the genus for mock CfA surveys drawn from large (L greater than or approximately 400/h Mpc) N-body simulations of three variants of the cold dark matter (CDM) cosmogony. The genus amplitude of the 'standard' CDM model (omega h = 0.5, b = 1.5) differs from the observations (96% confidence level) on smoothing scales is less than or approximately 10/h Mpc. An open CDM model (omega h = 0.2) and a CDM model with nonzero cosmological constant (omega h = 0.24, lambda (sub 0) = 0.6) are consistent with the observed genus amplitude over the full range of smoothing scales. All of these models fail (97% confidence level) to match the broadness of the observed genus curve on smoothing scales is less than or equal to 10/h Mpc.

Vogeley, Michael S.↗

Flight Readiness of Mochii S: Portable Spectroscopic Scanning Electron Microscope Facility on the International Space Station (ISS)

The ISS (International Space Station) currently lacks the capability to image and chemically analyze nano-to-micron scale particles from numerous engineering systems. To identify these particles, we must wait for a re-entry vehicle to return them from low earth orbit for ground-based SEM (Scanning Electron Microscope) / EDS (Energy Dispersive X-Ray Spectroscopy) analysis. This may take months, potentially delaying the affected system. Having an EDS-equipped SEM (Mochii S) aboard the ISS will accelerate response time thereby enhancing crew and vehicle safety by rapid and accurate identification of microscopic threats, especially in time-critical situations.The Mochii S payload will be stationed in the Japanese Experiment Module (JEM) powered by 120 VAC (Volts Alternating Current) inverter and connected to station Ethernet and WiFi (Fig. 1). To date the Mochii S payload has undergone testing for command and data handling, power quality, flight vibration, and radiation testing at Johnson Space Center (JSC). Mochii's high-RPM (Revolutions Per Minute) rotating vacuum pumps and high voltage systems have been reviewed to meet safety standards by JSC (Johnson Space Center) Engineering. Topology of the system in the JEM module has been baselined by ISS Safety and JAXA (Japan Space Exploration Agency). Digital controls to and from ISS over Joint Station LAN (Local Area Network) uplink have been simulated and the latencies and data rates have been found to be sufficient for successful operation of the payload from ground.Transporting sensitive electron optical instruments aboard a rocket that sustains 7G acceleration for 8 minutes and then operating it the unique microgravity (micro-g) environment is no trivial matter. To meet strict safety requirements and increase robustness for mission success, over 500 unique verifications must be completed before the payload is certified for spaceflight. Two of which will be discussed in detail are: vibroacoustic testing and magnetic susceptibility shielding and validation.

Mochii↗

Analysis and Mitigation of Cascading Failures Using a Stochastic Interaction Graph with Eigen-analysis

In studies on complex network systems using graph theory, eigen-analysis is typically performed on an undirected graph model of the network. However, when analyzing cascading failures in a power system, the interactions among failures suggest the need for a directed graph beyond the topology of the power system to model directions of failure propagation. To accurately quantify failure interactions for effective mitigation strategies, this paper proposes a stochastic interaction graph model and associated eigen-analysis. Different types of modes on failure propagations are defined and characterized by the eigenvalues of a stochastic interaction matrix, whose absolute values are unity, zero, or in between. Finding and interpreting these modes helps identify the probable patterns of failure propagation, either local or widespread, and the participating components based on eigenvectors. Then, by lowering the failure probabilities of critical components highly participating in a mode of widespread failures, cascading can be mitigated. Here, the validity of the proposed stochastic interaction graph model, eigen-analysis and the resulting mitigation strategies is demonstrated using simulated cascading failure data on an NPCC 140-bus system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

HLPW-4: Wall-Modeled LES and Lattice-Boltzmann Technology Focus Group Workshop Summary

A summary of the nine submissions to the Wall-Modeled LES and Lattice-Boltzmann(WMLESLB) Technical Focus Group (TFG) at the 4th High lift Prediction Workshop is provided. The focus of this TFG was to assess the current capabilities of WMLES and LB methods on a complex high-lift configuration across a wide range of angles-of-attack. Analysis of the submitted data suggests that>250𝑀spatial degrees of freedom are needed to accurately predict pitching moments at high angles-of-attack due to large pressure gradients present on the outboard slat and main element for 𝛼 >17◦(corrected for free-air). While some scatter is reported in pitching moment coefficient at the low-angles of attack (𝛼 <11◦) - excellent agreement is observed between submissions near the 𝐶𝐿,max state. Objective superiority of WMLES methods over RANS can be seen in terms of lack of excess outboard separation; a majority of the WMLES and LB submissions predict wedge-shaped separation patterns consistent with the experimental oil flow. The in-tunnel simulations show excellent agreement with the experiment in terms of a) integrated loads, b) surface flow-topology, and c) mechanism for the onset of inboard stall. Further evidence is provided to demonstrate both qualitative and quantitative superiority of the WMLES submissions over RANS.

TTT↗

Detection of Spectral Evolution in the Bursts Emitted During the 2008-2009 Active Episode of SGR J1550 - 5418

In early October 2008, the Soft Gamma Repeater SGRJ1550 - 5418 (1E1547.0 - 5408, AXJ155052 - 5418, PSR J1550 - 5418) became active, emitting a series of bursts which triggered the Fermi Gamma-ray Burst Monitor (GBM) after which a second especially intense activity period commenced in 2009 January and a third, less active period was detected in 2009 March-April. Here we analyze the GBM data of all the bursts from the first and last active episodes. We performed temporal and spectral analysis for all events and found that their temporal characteristics are very similar to the ones of other SGR bursts, as well the ones reported for the bursts of the main episode (average burst durations 170ms). In addition, we used our sample of bursts to quantify the systematic uncertainties of the GBM location algorithm for soft gamma-ray transients to less than or equal to 8 degrees. Our spectral analysis indicates significant spectral evolution between the first and last set of events. Although the 2008 October events are best fit with a single blackbody function, for the 2009 bursts an Optically Thin Thermal Bremsstrahlung (OTTB) is clearly preferred. We attribute this evolution to changes in the magnetic field topology of the source, possibly due to effects following the very energetic main bursting episode.

von Kienlin, Andreas↗

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗

Experimental search for the chiral magnetic effect in relativistic heavy-ion collisions: A perspective

The chiral magnetic effect (CME) refers to generation of the electric current along a magnetic field in a chirally imbalanced system of quarks. The latter is predicted by quantum chromodynamics to arise from quark interaction with nontrivial topological fluctuations of the vacuum gluonic field. The CME has been actively searched for in relativistic heavy-ion collisions, where such gluonic field fluctuations and a strong magnetic field are believed to be present. The CME-sensitive observables are unfortunately subject to a possibly large non-CME background, and firm conclusions on a CME observation have not yet been reached. In this perspective, we review the experimental status and progress in the CME search, from the initial measurements more than a decade ago to the dedicated program of isobar collisions in 2018 and the release of the isobar blind analysis result in 2022 to intriguing hints of a possible CME signal in Au + Au collisions, and discuss future prospects of a potential CME discovery in the anticipated high-statistic Au + Au collision data at the Relativistic Heavy-Ion Collider by 2025. We hope such a perspective will help sharpening our focus on the fundamental physics of the CME and steer its experimental search.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

HLPW-4/GMGW-3: Wall-Modeled LES and Lattice-Boltzmann Technology Focus Group Workshop Summary

A summary of the nine submissions to the Wall-Modeled LES and Lattice-Boltzmann(WMLESLB) Technical Focus Group (TFG) at the 4th High lift Prediction Workshop is provided. The focus of this TFG was to assess the current capabilities of WMLES and Lattice-Boltzmann methods on a complex high-lift configuration across a wide range of angles of attack. Preliminary analysis of the submitted data suggests that>250𝑀spatial degrees of freedom are needed to accurately predict pitching moments at high angles of attack due to large pressure gradients present on the outboard slat and main element for𝛼 >17◦(corrected for free-air).While some scatter is reported in pitching moments at the low-angles of attack (𝛼 <11◦) - likely caused by differences in flap separation possibly due to low Reynolds number effects - excellent agreement is observed between the submissions near the𝐶𝐿,max state. Objective superiority over steady state RANS can be seen in terms of lack of excess outboard separation; a majority of the good quality WMLES and LB submissions predict wedge-shaped separation patterns consistent with the experimental oil flow. Differences in the onset of stall mechanism in the free-air configuration for𝛼 >20◦is reported with two distinct topologies observed. Topology A is characterized by the onset of corner-flow separation which progressively grows to produce a pitch break in free-air with an angle of attack increase from𝛼=20.55◦to𝛼=21.47◦+𝜖where𝜖is a small perturbation (varying between submissions and likely to be within±0.3◦). Topology Bis characterized by boundary layer weakness emanating from the inboard side of the wing-pylon juncture substantially larger than any weakness in the wing-body juncture (due to corner-flow);submissions in this category do not show any tendency for occurrence of a pitch break for the free-air configuration within the vicinity of𝛼=21.47◦. The in-tunnel simulations submitted by3 participants using different discretizations, grids and closure models show excellent agreement with the experiment in terms of a) integrated loads, b) surface flow-topology, and c) mechanism for the onset of inboard stall. Further evidence is provided to demonstrate both qualitative and quantitative superiority of all 3 WMLES submissions over a single steady state RANS submission to the workshop.

TTT↗