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At least 235 records · Page 13

Validation of High-Fidelity CFD/CAA Framework for Launch Vehicle Acoustic Environment Simulation against Scale Model Test Data

A hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) modeling framework has been developed for launch vehicle liftoff acoustic environment predictions. The framework couples the existing highly-scalable NASA production CFD code, Loci/CHEM, with a high-order accurate discontinuous Galerkin solver developed in the same production framework, Loci/THRUST, to accurately resolve and propagate acoustic physics across the entire launch environment. Time-accurate, Hybrid RANS/LES CFD modeling is applied for predicting the acoustic generation physics at the plume source, and a high-order accurate unstructured discontinuous Galerkin (DG) method is employed to propagate acoustic waves away from the source across large distances using high-order accurate schemes. The DG solver is capable of solving 2nd, 3rd, and 4th order Euler solutions for non-linear, conservative acoustic field propagation. Initial application testing and validation has been carried out against high resolution acoustic data from the Ares Scale Model Acoustic Test (ASMAT) series to evaluate the capabilities and production readiness of the CFD/CAA system to resolve the observed spectrum of acoustic frequency content. This paper presents results from this validation and outlines efforts to mature and improve the computational simulation framework.

Liever, Peter A.↗

Validation of High-Fidelity CFD/CAA Framework for Launch Vehicle Acoustic Environment Simulation against Scale Model Test Data

A hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) modeling framework has been developed for launch vehicle liftoff acoustic environment predictions. The framework couples the existing highly-scalable NASA production CFD code, Loci/CHEM, with a high-order accurate Discontinuous Galerkin solver developed in the same production framework, Loci/THRUST, to accurately resolve and propagate acoustic physics across the entire launch environment. Time-accurate, Hybrid RANS/LES CFD modeling is applied for predicting the acoustic generation physics at the plume source, and a high-order accurate unstructured mesh Discontinuous Galerkin (DG) method is employed to propagate acoustic waves away from the source across large distances using high-order accurate schemes. The DG solver is capable of solving 2nd, 3rd, and 4th order Euler solutions for non-linear, conservative acoustic field propagation. Initial application testing and validation has been carried out against high resolution acoustic data from the Ares Scale Model Acoustic Test (ASMAT) series to evaluate the capabilities and production readiness of the CFD/CAA system to resolve the observed spectrum of acoustic frequency content. This paper presents results from this validation and outlines efforts to mature and improve the computational simulation framework.

Liever, Peter A.↗

Wall-modeled LES of the Three-dimensional Speed Bump Experiment

We evaluate the performance of wall-modeled large eddy simulation (WMLES) in predicting smooth-body turbulent flow separation for a three-dimensional Gaussian-shaped speed bump geometry. The Reynolds number based on the bump length is 2 million, and an unstructured compressible finite-volume solver is used with an equilibrium wall model and dynamic subgrid scale model. Spanwise periodic simulations of the centerline two-dimensional bump were used to assess grid resolution requirements, and resolving the thin internal layer in the accelerating region was found to be necessary to correctly capture the downstream separated flow region. Based on these insights, an optimized grid that was smaller by a factor of two provided comparable accuracy to a finer grid that has been used by us and other researchers in past studies. Using insights gained from the spanwise periodic simulation, an unstructured polyhderal grid with about 250 million cells was used for the three-dimensional (3D) configuration with inviscid tunnel side and top walls. Detailed comparisons of wall skin-friction coefficient, wall pressure, velocity and turbulent stresses with available experimental data indicated excellent agreement. While the low-Reynolds Number Spalart-Allmaras RANS model with rotation/curvature correction gave qualitatively good agreement with experiments, WMLES showed significantly more accurate quantitative predictions of the flowfield. The 3D WMLES showed good agreement with experiments in the separated region, and the centerplane results indicated a different separation topology compared to the spanwise periodic simulation.

Computational Fluid Dynamics↗

High-Lift Common Research Model: RANS, HRLES and WMLES Perspectives for CLmax Prediction Using LAVA

A unified assessment of three turbulence treatments: Reynolds Averaged Navier-Stokes(RANS), Hybrid RANS/LES (HRLES) and Equilibrium Wall-Modelled Large Eddy Simulation(WMLES) is presented for the High-Lift Common Research Model (CRM-HL). For the free-air configuration, steady-state RANS simulations show very accurate drag polar predictions in the low-𝛼linear regime. However, strong grid sensitivity is reported near the maximum lift-state(𝐶𝐿max), with finer-grids showing larger errors and predicting erroneous flow topologies on the wing. Our RANS simulations show that several corrections for the Spalart-Allmaras (SA)turbulence model widely used in the community lead to more erroneous results compared to the baseline closure, without exception. Both scale-resolving methods (HRLES and WMLES)address these drawbacks and predict an outboard separation pattern on the main element that is in good agreement with the oil flow photographs taken from the QinetiQ wind tunnel experiments, when LES-appropriate grids and numerical discretizations are used. While RANS simulations with the baseline SA closure do not show any wing-root separation post𝐶𝐿max, both HRLES and WMLES show onset of corner flow separation with varying degrees of progression, along with a weak pitch break in the wing-contribution of the overall pitching moment. This post-𝐶𝐿max pitch break seen in the free-air simulations is weaker than the break observed in experiments, with a weaker break reported in WMLES for each iteration of grid-refinement. In-tunnel simulations using both SA-baseline RANS and WMLES show a much stronger post-𝐶𝐿max break with the WMLES predictions showing excellent agreement with the experiment in terms of both the flow-topology observed and the pressure-coefficients at various spanwise stations. Sensitivity to the tunnel wall boundary layer is characterized via comparisons between viscous and inviscid treatments for the tunnel walls. WMLES predictions show moderate sensitivity at the predicted inboard flow-state at 𝐶𝐿max along with the progression towards a post-𝐶𝐿max stall; however, this stalled state at 𝛼≈20◦(inside the tunnel) obtained with both tunnel wall treatments appears to be largely identical.

TTT↗

The Impact of Model Configuration and Large-Scale, Upper-Level Forcing on CRM-Simulated Convective Systems

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D, see a brief review by Tao 2003). Only recently have 3D experiments been performed for multi-day periods for tropical cloud systems with large horizontal domains at the National Center for Atmospheric Research, at NOAA GFDL, at the U. K. Met. Office, at Colorado State University and at NASA Goddard Space Flight Center (Tao 2003). At Goddard, a 3D Goddard Cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE (December 19-27, 1992), GATE (September 1-7, 1974), SCSMEX (June 2-11, 1998), ARM (June 26-30, 1997) and KWAJEX (August 7-13, August 18-21, and August 29-September 12, 1999) using a 512 km domain (with 2-kilometer resolution). The results indicate that surface precipitation and latent heating profiles are similar between the 2D and 3D GCE model simulations. However, there are difference in radiation, surface fluxes and precipitation characteristics. The 2D GCE model was used to perform a long-term integration on ARM/GCSS case 4 (22 days at the ARM southern Great Plains site in March 2000). Preliminary results showed a large temperature bias in the upper troposphere that had not been seen in previous tropical cases. The major objectives of this paper are: (1) to determine the sensitivities to model configuration (ie., 2D in west-east, south-north or 3D), (2) to identify the differences and similarities in the organization and entrainment rates of convection between 2D- and 3D-simulated ARM cloud systems, and (3) assess the impact of upper tropospheric forcing on tropical and ARM case 4 cases.

Tao, W.-K.↗

Assessing Cloud and Precipitation Properties on Temporal and Spatial Scales Using LASSO Simulations over ENA

Low clouds and precipitation representation remain a major source of uncertainty in Earth System Models (ESMs), particularly due to challenges in representing their sub-grid variability and scale-dependent sampling. This study evaluates the performance of preliminary simulations from the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project over the Eastern North Atlantic (ENA), with a focus on liquid water path (LWP), ice water path (IWP), cloud fraction (CF), and surface precipitation simulated across closed-cell, open-cell, and transitional cloud regimes. Using LES (100 m horizontal grid spacing) driven by ERA5 and MERRA-2 reanalyses, we assess the representativeness of ground-based point observations by analyzing their correspondence to model-resolved spatial and temporal means. Results suggest that observational sampling of at least 6 hours is required to achieve consistency with domain-scale averages, in particular for observations that exhibit pronounced sub-grid heterogeneity, such as precipitation. ERA5-forced simulations exhibit improved spatial coherence and agreement with domain-averaged quantities when compared to MERRA-2 runs, with performance discrepancies largest for convective cloud conditions due to differences in forcing fidelity and temporal resolution. These findings highlight the importance of regime-aware model evaluation strategies and potentially demonstrate how LES can inform observation-model comparison practices and the development of cloud and precipitation parameterizations in ESMs.

Liang, Jiakun [University of Hawai'i at Manoa] (OR↗

The Surface Energy Budget and Precipitation Efficiency for Convective Systems During TOGA, COARE, GATE, SCSMEX and ARM: Cloud-Resolving Model Simulations

A two-dimensional version of the Goddard Cumulus Ensemble (GCE) Model is used to simulate convective systems that developed in various geographic locations. Observed large-scale advective tendencies for potential temperature, water vapor mixing ratio, and horizontal momentum derived from field campaigns are used as the main forcing. By examining the surface energy budgets, the model results show that the two largest terms are net condensation (heating/drying) and imposed large-scale forcing (cooling/moistening) for tropical oceanic cases. These two terms arc opposite in sign, however. The contributions by net radiation and latent heat flux to the net condensation vary in these tropical cases, however. For cloud systems that developed over the South China Sea and eastern Atlantic, net radiation (cooling) accounts for about 20% or more of the net condensation. However, short-wave heating and long-wave cooling are in balance with each other for cloud systems over the West Pacific region such that the net radiation is very small. This is due to the thick anvil clouds simulated in the cloud systems over the Pacific region. Large-scale cooling exceeds large-scale moistening in the Pacific and Atlantic cases. For cloud systems over the South China Sea, however, there is more large-scale moistening than cooling even though the cloud systems developed in a very moist environment. though For three cloud systems that developed over a mid-latitude continent, the net radiation and sensible and latent heat fluxes play a much more important role. This means the accurate measurement of surface fluxes and radiation is crucial for simulating these mid-latitude cases.

Tao, W.-K.↗

Computational Investigation of the Effect of Chemistry on Mars Supersonic Retropropulsion Environments

Retropropulsion ground tests require significant compromises on physical scale, instrumentation, configuration, and environments. Matching the full Martian environment is simply not possible on Earth. Ground tests of retropropulsion configurations thus far have neglected effects of chemistry due to physical constraints of wind tunnel models and facilities; most experiments use inert simulant gases at relatively low temperatures. As such, a strong reliance on high-fidelity computational analyses is required to expand the knowledge of retropropulsion aerodynamics. In this work, we investigate the effects of chemistry using scale-resolving computational fluid dynamics (CFD) with finite-rate chemistry and a graphics processing unit (GPU)-enabled implementation of the NASA FUN3D flow solver on a human-scale Mars lander concept at supersonic freestream conditions. Results are compared to previous perfect gas simulations.

retropropulsion↗

Computational Investigation of the Effect of Chemistry on Mars Supersonic Retropropulsion Environments

Retropropulsion ground tests require significant compromises on physical scale, instrumentation, configuration, and environments. Matching the full Martian environment is simply not possible on Earth. Ground tests of retropropulsion configurations thus far have neglected effects of chemistry due to physical constraints of wind tunnel models and facilities; most experiments use inert simulant gases at relatively low temperatures. As such, a strong reliance on high-fidelity computational analyses is required to expand the knowledge of retropropulsion aerodynamics. In this work, we investigate the effects of chemistry using scale-resolving computational fluid dynamics (CFD) with finite-rate chemistry and a graphics processing unit (GPU)-enabled implementation of the NASA FUN3D flow solver on a human-scale Mars lander concept at supersonic freestream conditions. Results are compared to previous perfect gas simulations.

retropropulsion↗

To Exascale and Beyond—The Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM), a Performance Portable Global Atmosphere Model for Cloud-Resolving Scales

The new generation of heterogeneous CPU/GPU computer systems offer much greater computational performance but are not yet widely used for climate modeling. One reason for this is that traditional climate models were written before GPUs were available and would require an extensive overhaul to run on these new machines. In addition, even conventional “high–resolution” simulations don't currently provide enough parallel work to keep GPUs busy, so the benefits of such overhaul would be limited for the types of simulations climate scientists are accustomed to. The vision of the Simple Cloud-Resolving Energy Exascale Earth System (E3SM) Atmosphere Model (SCREAM) project is to create a global atmospheric model with the architecture to efficiently use GPUs and horizontal resolution sufficient to fully take advantage of GPU parallelism. After 5 years of model development, SCREAM is finally ready for use. In this paper, we describe the design of this new code, its performance on both CPU and heterogeneous machines, and its ability to simulate real-world climate via a set of four 40 day simulations covering all 4 seasons of the year.

54 ENVIRONMENTAL SCIENCES↗

Less Atmospheric Radiative Heating By Dust Due to the Synergy of Coarser Size and Aspherical Shape

Mineral dust aerosols cool and warm the atmosphere by scattering and absorbing solar (shortwave: SW) and thermal (longwave: LW) radiation. However, significant uncertainties remain in dust radiative effects, largely due to differences in the dust size distribution and spectral optical properties simulated in Earth system models. Dust models typically underestimate the coarse dust load (more than 2.5 µm in diameter) and assume a spherical shape, which leads to an overestimate of the fine dust load (less than 2.5 µm) after the dust emissions in the models are scaled to match observed dust aerosol optical depth at 550 nm (DAOD550). Here, we improve the simulated dust properties with data sets that leverage measurements of size-resolved dust concentration, asphericity factor, and refractive index in a coupled global chemical transport model with a radiative transfer module. After the adjustment of size-resolved dust concentration and spectral optical properties, the global and annual average of DAOD550 from the simulation increases from 0.023 to 0.029 and falls within the range of a semi-observationally based estimate (0.030 ± 0.005). The reduction of fine dust load after the adjustment leads to a reduction of the SW cooling at the top of the atmosphere (TOA). To improve agreement against a semi-observationally based estimate of the radiative effect efficiency at TOA, we find that a less absorptive SW dust refractive index is required for coarser aspherical dust. Thus, only a minor difference is estimated for the net global dust radiative effect at TOA (−0.08 vs. −0.00 W m−2 on a global scale). Conversely, our sensitivity simulations reveal that the surface warming is substantially enhanced near the strong dust source regions (less cooling to −0.23 from −0.60 W m−2 on a global scale). Thus, less atmospheric radiative heating is estimated near the major source regions (less heating to 0.15 from 0.59 W m−2 on a global scale), because of enhanced LW warming at the surface by the synergy of coarser size and aspherical shape.

simulated dust properties↗

Applying Corrective Machine Learning in the E3SM Atmosphere Model in C++ (EAMxx)

The Simplified Cloud-Resolving E3SM Atmosphere Model (SCREAM) is the newest addition to the family of Earth System Models capable of explicitly resolving convective systems. SCREAM is a kilometer-scale configuration of the advanced E3SM Atmosphere Model (EAMxx), designed for heterogeneous systems. While the enhanced accuracy of kilometer-scale modeling offers significant benefits, it comes with a substantial computational cost, limiting feasible simulation durations to only a few years, even on the fastest supercomputers. Machine learning presents an opportunity for scientists to achieve the high accuracy of storm-resolving models at a significantly reduced cost. Building on the previous success of applying corrective machine learning (ML) to the FV3 model, this study explores the effects of implementing corrective ML in EAMxx-SCREAM. We also address the computational challenges of integrating the corrective ML, which is written in Python, with the C++/Kokkos EAMxx driver, as well as the potential pitfalls of generalizing an approach that was effective with one atmosphere model to another.

54 ENVIRONMENTAL SCIENCES↗

Efficient Load Balancing and Data Remapping for Adaptive Grid Calculations

Mesh adaption is a powerful tool for efficient unstructured- grid computations but causes load imbalance among processors on a parallel machine. We present a novel method to dynamically balance the processor workloads with a global view. This paper presents, for the first time, the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. Previous results indicated that mesh repartitioning and data remapping are potential bottlenecks for performing large-scale scientific calculations. We resolve these issues and demonstrate that our framework remains viable on a large number of processors.

Oliker, Leonid↗

A Contribution by Ice Nuclei to Global Warming

Ice nuclei (IN) significantly affect clouds via supercooled droplets, that in turn modulate atmospheric radiation and thus climate change. Since the IN effect is relatively strong in stratiform clouds but weak in convective ones, the overall effect depends on the ratio of stratiform to convective cloud amount. In this paper, 10 years of TRMM (Tropical Rainfall Measuring Mission) satellite data are analyzed to confirm that stratiform precipitation fraction increases with increasing latitude, which implies that the IN effect is stronger at higher latitudes. To quantitatively evaluate the IN effect versus latitude, large-scale forcing data from ten field campaigns are used to drive a CRM (cloud-resolving model) to generate longterm cloud simulations. As revealed in the simulations, the increase in the net downward radiative flux at the TOA (top of the atmosphere) from doubling the current IN concentrations is larger at higher latitude, which is attributed to the meridional tendency in the stratiform precipitation fraction. Surface warming from doubling the IN concentrations, based on the radiative balance of the globe, is compared with that from anthropogenic COZ . It is found that the former effect is stronger than the latter in middle and high latitudes but not in the Tropics. With regard to the impact of IN on global warming, there are two factors to consider: the radiative effect from increasing the IN concentration and the increase in IN concentration itself. The former relies on cloud ensembles and thus varies mainly with latitude. In contrast, the latter relies on IN sources (e.g., the land surface distribution) and thus varies not only with latitude but also longitude. Global desertification and industrialization provide clues on the geographic variation of the increase in IN concentration since pre-industrial times. Thus, their effect on global warming can be inferred and then be compared with observations. A general match in geographic and seasonal variations between the inferred and observed warming suggests that IN may have contributed positively to global warming over the past decades, especially in middle and high latitudes.

Zeng, Xiping↗

Higher-Order Methods for Compressible Turbulent Flows Using Entropy Variables

Turbulent flows have a large range of spatial and temporal scales which need to be resolved in order to obtain accurate predictions. Higher-order methods can provide greater efficiency for simulations requiring high spatial and temporal resolution, allowing for solutions with fewer degrees of freedom and lower computational cost than traditional second-order computational fluid dynamics (CFD) methods.1 Higher-order methods have been widely used for turbulent flows. However, the reduced numerical stabilization present in higher-order schemes implies that special care needs to be taken in the development of numerical methods to suppress nonlinear instabilities.2–6 In this work we present the development of a higher-order space-time discontinuous Galerkin method with a focus on the aspects of our numerical scheme required for ensuring nonlinear stability for turbulent simulations at high Reynolds numbers.

Diosady, Laslo T.↗

Numerical Simulations of Homogeneous Turbulence Using Lagrangian-Averaged Navier-Stokes Equations

The Lagrangian-averaged Navier-Stokes (LANS) equations are numerically evaluated as a turbulence closure. They are derived from a novel Lagrangian averaging procedure on the space of all volume-preserving maps and can be viewed as a numerical algorithm which removes the energy content from the small scales (smaller than some a priori fixed spatial scale alpha) using a dispersive rather than dissipative mechanism, thus maintaining the crucial features of the large scale flow. We examine the modeling capabilities of the LANS equations for decaying homogeneous turbulence, ascertain their ability to track the energy spectrum of fully resolved direct numerical simulations (DNS), compare the relative energy decay rates, and compare LANS with well-accepted large eddy simulation (LES) models.

Mohseni, Kamran↗

Applying corrective machine learning in the E3SM atmosphere model in C++ (EAMxx)

The Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) is the newest addition to the family of earth system models capable of explicitly resolving convective systems. SCREAM is a kilometer-scale configuration of the advanced E3SM Atmosphere Model (EAMxx), designed for heterogeneous computing architectures. While the enhanced accuracy of kilometer-scale modeling offers significant benefits, it comes with a substantial computational cost, limiting feasible simulation durations to only a few years to a few decades, even on the fastest supercomputers. Machine learning presents an opportunity for scientists to achieve the high accuracy of storm-resolving models at a significantly reduced cost. Building on the previous success of applying corrective machine learning (ML) to the FV3GFS earth system model, this study explores the effects of implementing corrective-ML in EAMxx-SCREAM. We also address the computational challenges of integrating our implementation of corrective-ML, which is written in Python, with the C++/Kokkos EAMxx driver, as well as potential reasons why this approach has not proved as effective for EAMxx-SCREAM as for FV3GFS.

Environmental sciences↗

On scaling performance operating characteristics - Caveat emptor

Problems associated with scaling and normalizing empirical performance operating characteristics (POCs) are examined. Normalization methods proposed by Wickens (1980) and by Mountford and North (1980) are critically evaluated. Computer simulations are used to generate raw-score and normalized POCs. The interpretation of transformed empirical POCs (Wickens, Mountford, and Schreiner, 1981) is shown to contain inconsistencies. The normalization techniques reviewed fail to resolve POC scaling problems. Caution must be exercised when interpreting transformed POCs.

Kantowitz, B. H.↗