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DOE OSTI2021

The Interaction between the Nocturnal Amazonian Low-Level Jet and Convection in CESM

A nocturnal Amazonian low-level jet (ALLJ) was recently diagnosed using reanalysis data. This work assesses the ability of CESM1.2.2 to reproduce the jet and explores the mechanisms by which the ALLJ influences convection in the Amazon. The coupled CESM simulates the nocturnal ALLJ realistically, while CAM5 does not. A low-level cold air temperature bias in the eastern Amazon exists in CAM5, and thus the ALLJ is weaker than observed. However, a cold SST bias over the equatorial North Atlantic in the coupled model offsets the cold air temperature bias, producing a realistic ALLJ. Climate models significantly underestimate March–May (MAM) precipitation over the eastern Amazon. Here, we ran two sensitivity experiments using the coupled CESM by adding bottom-heavy diabatic heating at noon and midnight for 2.5 h along the coastal Amazon during MAM to mimic the occurrence of shallow precipitating convection. When heating is added during the early afternoon, coastal convection deepens and the ALLJ transports moisture inland from the ocean, preconditioning the environment for deep convective development during the ensuing hours. The increased convection over the eastern Amazon also moderately alleviates the equatorial Atlantic westerly wind bias, leading to deepening of the east Atlantic thermocline in the following months and partially improving the simulated June–August (JJA) Atlantic cold tongue in the coupled model. When heating is added at night, coastal convection does not strengthen as much and the ALLJ transports less moisture. Improvements in the simulated Atlantic winds and SST are negligible. Therefore, diurnal circulations matter to the organization of convection and rain across the Amazon, with impacts over the equatorial Atlantic.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Detached-Eddy Simulations of Separated Flow Around Wings With Ice Accretions: Year One Report

A computational investigation was performed to assess the effectiveness of Detached-Eddy Simulation (DES) as a tool for predicting icing effects. The AVUS code, a public domain flow solver, was employed to compute solutions for an iced wing configuration using DES and steady Reynolds Averaged Navier-Stokes (RANS) equation methodologies. The configuration was an extruded GLC305/944-ice shape section with a rectangular planform. The model was mounted between two walls so no tip effects were considered. The numerical results were validated by comparison with experimental data for the same configuration. The time-averaged DES computations showed some improvement in lift and drag results near stall when compared to steady RANS results. However, comparisons of the flow field details did not show the level of agreement suggested by the integrated quantities. Based on our results, we believe that DES may prove useful in a limited sense to provide analysis of iced wing configurations when there is significant flow separation, e.g., near stall, where steady RANS computations are demonstrably ineffective. However, more validation is needed to determine what role DES can play as part of an overall icing effects prediction strategy. We conclude the report with an assessment of existing computational tools for application to the iced wing problem and a discussion of issues that merit further study.

Choo, Yung K.↗

DOE OSTI2019

Modeling Complex Relationships in Large-Scale Data using Hypergraphs (LDRD Final Report)

This SAND report documents the findings of the LDRD project, "Modeling Complex Relationships in Large-Scale Data using Hypergraphs". The project ran from October 2017 through September 2019. The focus of the project was the development and application of hypergraph data analytics to Sandia relational data applications. In this project, we attempted to apply a hypergraph data analysis method—specifically, hypergraph eigenvector centrality—to Sandia mission problems to identify influential entities (people, location, times, etc.) in the data. Unfortunately, the application data led to graph and hypergraph representations containing disconnected components. To date, there are no well-established techniques for applying eigenvector centrality to such graphs and hypergraphs. In this report, we present several heuristics for computing eigenvector centrality for disconnected graphs. We believe this is an important start to understanding how to approach the similar problem for hypergraphs, but this project concluded before we made progress on that problem. The ideas, methods, and suggestions presented here can be used for further research into this challenging problem. We also present our ideas for generating graphs with known degree and centrality distributions. The goal in presenting this work is to identify a procedure for analyzing such graphs once the problem of addressing disconnected components has been addressed. When working with a single data set, this generator can be used to create many instances of graphs that can be used to analyze the robustness of the centrality computations for the original data set. Although the results did not match perfectly in the case of the Facebook Ego dataset used in the experiments presented here, this again represents a good start in the direction of a graph generator for such problems. We note that there are potential trade-offs between how the degree and centrality distributions are fit to the original data and suggested several possible avenues for follow-on research efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

UAS remote sensing (Osprey platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance, Seward Peninsula, Alaska, 2018

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group. This package includes data from 34 flights flown over the NGEE-Arctic Council Mile Maker 72 (MM72), Kougarok MM64, Kougarok MM80, and Teller MM27 sites in July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. This package provide the Level 0 (raw, unprocessed) data collected by the Osprey platform. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), tabular (*.dat, *.csv, *.waypoint), and image (*.jpg) formats. This metadata document contains flight campaign, instrument and file metadata, along with a description of the L0 data, and file naming scheme. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1978

Real time digital propulsion system simulation for manned flight simulators

A real time digital simulation of a STOL propulsion system was developed which generates significant dynamics and internal variables needed to evaluate system performance and aircraft interactions using manned flight simulators. The simulation ran at a real-to-execution time ratio of 8.8. The model was used in a piloted NASA flight simulator program to evaluate the simulation technique and the propulsion system digital control. The simulation is described and results shown. Limited results of the flight simulation program are also presented.

Mihaloew, J. R.↗

NASA NTRS2004

Highlights of Project Accomplishments (2000-2004): Redshift Dependence of the Interaction-Activity Connection

We completed this project by developing the new galaxy-galaxy collision simulation code that we originally proposed. We included star formation heuristically, along with gas recycling and energetic feedback into the interstellar medium of the galaxies. We ran several test simulations. And we finally validated the code by running models to emulate the double-ring galaxy AM 0644-741. Most of the exotic and unique features of this collisional ring galaxy were matched by our models, thereby validating our algorithm, which may now be used by us and by the community for additional dynamic studies of galaxies. A paper has been submitted to the Astrophysical Journal describing our algorithm and the results of the AM 0644-741 modeling.

Borne, Kirk D.↗

NASA NTRS2018

Aeroacoustic Validation of Installed Low Noise Propulsion for NASA's N+2 Supersonic Airliner

An aeroacoustic test was conducted at NASA Glenn Research Center on an integrated propulsion system designed to meet noise regulations of ICAO Chapter 4 with 10EPNdB cumulative margin. The test had two objectives: to demonstrate that the aircraft design did meet the noise goal, and to validate the acoustic design tools used in the design. Variations in the propulsion system design and its installation were tested and the results compared against predictions. Far-field arrays of microphones measured the acoustic spectral directivity, which was transformed to full scale as noise certification levels. Phased array measurements confirmed that the shielding of the installation model adequately simulated the full aircraft and provided data for validating RANS-based noise prediction tools. Particle image velocimetry confirmed that the flow field around the nozzle on the jet rig mimicked that of the full aircraft and produced flow data to validate the RANS solutions used in the noise predictions. The far-field acoustic measurements confirmed the empirical predictions for the noise. Results provided here detail the steps taken to ensure accuracy of the measurements and give insights into the physics of exhaust noise from installed propulsion systems in future supersonic vehicles.

aeroacousti↗

NASA NTRS2018

Aeroacoustic Validation of Installed Low Noise Propulsion for NASA's N+2 Supersonic Airliner

supersonic↗

NASA NTRSDate not supplied

Performance Analysis of Optimized STARC-ABL Designs Across the Entire Mission Profile

Boundary layer ingestion (BLI) offers the potential for significant fuel burn reduction by exploiting strong aeropropulsive interactions. NASA’s STARC–ABL concept uses an electri- cally powered BLI tail cone thruster on what is otherwise a traditional airframe. Despite the traditional airframe of this configuration, aeropropulsive integration is critical to the perfor- mance of the BLI propulsor. Furthermore, due to being electrically powered, the fan pressure ratio and efficiency of the BLI tail cone thruster vary widely across the flight envelope, and this variation in fan performance must be accounted for with the aeropropulsive integration of the BLI system. Thus, accurate performance prediction for this novel propulsion configu- ration requires the use of a coupled aeropropulsive model across the flight envelope. In this work, we analyze the off-design performance of 18 optimized designs using an aeropropulsive model that is built with the OpenMDAO framework to couple 3-D RANS CFD simulations to 1-D thermodynamic cycle analyses. The designs are created via high-fidelity aeropropulsive design optimizations that span a range of fan pressure ratio and thrust values at the cruise conditions for the STARC-ABL concept, which was chosen as the aerodynamic design point for the propulsor. Performance analyses we present herein are then performed at a range of off-design flight conditions that span the flight envelope, including low-speed and low-altitude flight conditions. This study provides the first set of high-fidelity data for the STARC–ABL configuration at off-design conditions, and the results quantify the power savings through BLI compared to a traditional propulsion system across the entire mission profile.

optimization↗

NASA NTRSDate not supplied

Graphical User Interface (GUI) Implementation for Agent-Based Microbial Radiobiology Model

Sending human life past the Low Earth Orbit (LEO) to explore the Moon and Mars will be challenging. The Earth’s magnetic field naturally protects life from deep-space particle radiation such as Galactic Cosmic Rays (GCR) and Solar Particle Events (SPE); these will pose health risks to humans in deep space. Research has been done to investigate these effects, like BioSentinel, the first biological CubeSat to fly beyond the LEO, designed to culture yeast in a microfluidic device and record optical measurements of growth and metabolism. However, experiments can only report cell damage as bulk growth curves, while deep-space radiation causes damage that is heterogeneous among individual cells. AMMPER is an open-source, agent-based, computational model coded in Python to simulate the effects of deep-space radiation on individual yeast cells (Saccharomyces cerevisiae) to facilitate interpretation of biological radiation experiments. Version 1.0 of the code ran in a command line interface (CLI), limiting use to those familiar with modularization, object-oriented programming, and computational models. Here we present a graphical user interface (GUI) for AMMPER to increase its accessibility. GUI development included converting input points and UI files, designing an application and logo, and expanding program packages. Additionally, we added optical assistance that corresponded with simulation parameters, which included simulation type, cell type, ROS model, and radiation dosage, as well as customizable display and file exportation features. Following a pilot testing period, its structure was updated further to enhance abilities, adding increased runs, video visualization, data plotting, and an educational/tutorial component. Future work will include creating a bit installer and runtime environment for AMMPER. Ultimately, the creation of the GUI has two main goals: to facilitate the integration of computational models into the work of researchers in microbial radiobiology, and to act as an interactive and visual resource for space biology education.

yeast↗

NASA NTRS2014

Flutter Analysis for Turbomachinery Using Volterra Series

The objective of this paper is to describe an accurate and efficient reduced order modeling method for aeroelastic (AE) analysis and for determining the flutter boundary. Without losing accuracy, we develop a reduced order model based on the Volterra series to achieve significant savings in computational cost. The aerodynamic force is provided by a high-fidelity solution from the Reynolds-averaged Navier-Stokes (RANS) equations; the structural mode shapes are determined from the finite element analysis. The fluid-structure coupling is then modeled by the state-space formulation with the structural displacement as input and the aerodynamic force as output, which in turn acts as an external force to the aeroelastic displacement equation for providing the structural deformation. NASA's rotor 67 blade is used to study its aeroelastic characteristics under the designated operating condition. First, the CFD results are validated against measured data available for the steady state condition. Then, the accuracy of the developed reduced order model is compared with the full-order solutions. Finally the aeroelastic solutions of the blade are computed and a flutter boundary is identified, suggesting that the rotor, with the material property chosen for the study, is structurally stable at the operating condition, free of encountering flutter.

computational fluid dynamics↗

NASA NTRS2018

Improved Hydrology over Peatlands in a Global Land Modeling System

Peatlands of the Northern Hemisphere represent an important carbon pool that mainly accumulated since the last ice age under permanently wet conditions in specific geological and climatic settings. The carbon balance of peatlands is closely coupled to water table dynamics. Consequently, the future carbon balance over peatlands is strongly dependent on how hydrology in peatlands will react to changing boundary conditions, e.g. due to climate change or regional water level drawdown of connected aquifers or streams. Global land surface modeling over organic-rich regions can provide valuable global-scale insights on where and how peatlands are in transition due to changing boundary conditions. However, the current global land surface models are not able to reproduce typical hydrological dynamics in peatlands well. We implemented specific structural and parametric changes to account for key hydrological characteristics of peatlands into NASA's GEOS-5 Catchment Land Surface Model (CLSM, Koster et al. 2000). The main modifications pertain to the modeling of partial inundation, and the definition of peatland-specific runoff and evapotranspiration schemes. We ran a set of simulations on a high performance cluster using different CLSM configurations and validated the results with a newly compiled global in-situ dataset of water table depths in peatlands. The results demonstrate that an update of soil hydraulic properties for peat soils alone does not improve the performance of CLSM over peatlands. However, structural model changes for peatlands are able to improve the skill metrics for water table depth. The validation results for the water table depth indicate a reduction of the bias from 2.5 to 0.2 m, and an improvement of the temporal correlation coefficient from 0.5 to 0.65, and from 0.4 to 0.55 for the anomalies. Our validation data set includes both bogs (rain-fed) and fens (ground and/or surface water influence) and reveals that the metrics improved less for fens. In addition, a comparison of evapotranspiration and soil moisture estimates over peatlands will be presented, albeit only with limited ground-based validation data. We will discuss strengths and weaknesses of the new model by focusing on time series of specific validation sites.

Bechtold, M.↗

NASA NTRS2015

A Model for Effective Professional Development of Formal Science Educators

The Lunar Workshops for Educators (LWE) series was developed by the Lunar Reconnaissance Orbiter (LRO) education team in 2010 to provide professional development on lunar science and exploration concepts for grades 6-9 science teachers. Over 300 educators have been trained to date. The LWE model incorporates best practices from pedagogical research of science education, thoughtful integration of scientists and engineer subject matter experts for both content presentations and informal networking with educators, access to NASA-unique facilities, hands-on and data-rich activities aligned with education standards, exposure to the practice of science, tools for addressing common misconceptions, follow-up with participants, and extensive evaluation. Evaluation of the LWE model via pre- and post-assessments, daily workshop surveys, and follow-up surveys at 6-month and 1-year intervals indicate that the LWE are extremely effective in increasing educators' content knowledge, confidence in incorporating content into the classroom, understanding of the practice of science, and ability to address common student misconceptions. In order to address the efficacy of the LWE model for other science content areas, the Dynamic Response of Environments at Asteroids, the Moon, and moons of Mars (DREAM2) education team, funded by NASA's Solar System Exploration Research Virtual Institute, developed and ran a pilot workshop called Dream2Explore at NASA's Goddard Space Flight Center in June, 2015. Dream2Explore utilized the LWE model, but incorporated content related to the science and exploration of asteroids and the moons of Mars. Evaluation results indicate that the LWE model was effectively used for educator professional development on non-lunar content. We will present more detail on the LWE model, evaluation results from the Dream2Explore pilot workshop, and suggestions for the application of the model with other science content for robust educator professional development.

Orbiter↗

NASA NTRSDate not supplied

On Generalizably Improving RANS Predictions of Flow Separation and Reattachment

This work presents progress in an ongoing data-driven turbulence modeling effort at NASA Langley Research Center to improve predictions for separated flows. Two augmentation strategies are presented – one to improve predictions for the point of reattachment after smooth-body separation, and another to improve predictions for flow separation due to prolonged adverse pressure gradients. The reattachment augmentation was inspired from lessons learned during attempts at using field inversion and machine learning (FIML); however, it is prescribed as a conventional analytic closed-form expression. Results show that, when introduced into the SST k-w model, it shortens the otherwise overpredicted separation bubble length for three cases characterized by different Reynolds numbers and flow geometries. The second augmentation, which addresses flow separation under prolonged adverse pressure gradients, is inferred via FIML and applied as a neural network within the Spalart-Allmaras model. It uses features that are chosen such that the presented results show an improved predictive accuracy for the training case without affecting other cases where the augmentation is not needed. Further testing is required to establish the generalizability of this augmentation. The rationale behind the chosen features that serve as inputs to both these augmentations is also presented for the benefit of the reader.

machine learning↗

NASA NTRS2018

Generating a Grid for Unstructured RANS Simulations of Jet Flows

A study has been performed to determine best practices for generating unstructured grids for Reynolds-Averaged Navier-Stokes (RANS) simulations of jet flows. The Axisymmetric Near-Sonic Jet Case from the Turbulence Modeling Resource was used for this study: a Mach 0.985 flow through the 2-in. diameter Acoustic Reference Nozzle (ARN2). Simulations were run with FUN3D and used the Menter Shear Stress Transport (SST-V), Spalart-Allmaras (S-A), and k-kL turbulence models. The axial velocity and turbulent kinetic energy fields in the jet plume of the unstructured grid solutions were compared to those of the baseline structured grid solution provided by the Turbulence Modeling Resource. Only solutions using grids with structured-like elements in the jet plume showed good agreement with the baseline structured grid solution. Using the SST-V turbulence model, the fully unstructured grid solutions predicted the jet potential core to decay upstream of the baseline solution. With the S-A turbulence model, the unstructured grid solutions predicted the jet potential core to decay upstream of the baseline solution. The solutions using the k-kL turbulence model seemed less sensitive to grid topology. Nozzle massflow and thrust performance were also compared for all simulations. Based on the results of this study, it is currently recommended that structured-like grid elements are used in the plumes of jet flows; unstructured grid elements can be used elsewhere.

RANS Simulations; Unstructured Grids; Jet Flows↗

NASA NTRSDate not supplied

Unsteady CFD Simulations of a Compression Corner Geometry Using Wall-Modeled LES Methods in Loci/CHEM

Several wall-modeled large eddy simulation (WMLES) methods are tested by simulating an unsteady Mach 2.0 compression corner geometry in Mississippi State’s Loci/CHEM solver. This study is conducted to evaluate the usage and requirements of these WMLES methods for applications regarding fluctuating pressure environments on launch vehicles with computational fluid dynamics (CFD). Two hybrid Reynolds-averaged Navier-Stokes (RANS)-large eddy simulation (LES) methods, Dynamic Hybrid RANS-LES (DHRL) and Improved Delayed Detached Eddy Simulation (IDDES), and one wall-stress-model, the Algebraic Wall Model for Wall-Modeled LES (AWMLES), are tested on varying grid and timestep refinement levels. These grid and timestep sizes are chosen to test the minimum requirements for successfully running these WMLES methods. The simulations are evaluated based on turbulent boundary layer properties in the developed boundary layer as well as unsteady quantities relating to fluctuating pressure environments in the region of the compression corner. The DHRL method shows good agreement with the comparison wind tunnel data and shows good grid and timestep convergence. The results from the IDDES and WMLES simulations show good agreement for several quantities with some discrepancies regarding others. The results presented in this paper will be used to inform further studies in predicting unsteady environments on higher-complexity geometries.

Bryson Frank↗

DOE OSTI2019

MULTIDIMENSIONAL NUMERICAL SIMULATIONS OF REACTING FLOW IN A NON-PREMIXED ROTATING DETONATION ENGINE

Over the last two decades, detonation based propulsion has received a great deal of attention as a potential means to achieve significant improvement in the performance of air-breathing and rocket engines. Detonative combustion mode is particularly interesting due to the resulting pressure gain from reactants to products, faster heat release, decreased entropy generation, more available work and higher thrust compared to conventional deflagrative combustion. Rotating detonation engine (RDE) is one such novel combustor concept. Realistic RDE configurations utilize separate fuel and air injection schemes, hence are not perfectly premixed. Moreover, RDE performance is governed by a large number of design parameters and operating conditions. In this context, computational fluid dynamics (CFD) has the potential to enhance the understanding of RDE combustion and aid future development/optimization of this technology. In the present work, a CFD model was developed to simulate a representative non-premixed RDE combustor. Unsteady Reynolds-Averaged Navier-Stokes (RANS) simulations were performed for the full combustor geometry (including the separate fuel and air injection ports), with hydrogen as fuel and air as the oxidizer. Adaptive mesh refinement (AMR) was incorporated to achieve a trade-off between model accuracy and computational expense. A finite-rate chemistry model along with a 10-species detailed kinetic mechanism was employed to describe the H2-Air combustion chemistry. Two operating conditions were simulated, corresponding to the same global equivalence ratio of unity but different fuel and air mass flow rates. For both conditions, the capability of the model to capture the essential detonation wave dynamics was assessed. A validation study was performed against experimental data available on detonation wave frequency/height, reactant fill height, oblique shock angle, axial pressure distribution in the channel, and fuel/air plenum pressure. The CFD model predicted the sensitivity of these wave characteristics to the operating conditions with good accuracy, both qualitatively and quantitatively. The present CFD model offers a potential capability to perform rapid design space exploration and/or performance optimization studies for realistic full-scale RDE configurations.

Pal, Pinaki↗

DOE OSTI2019

Flow Characteristics of a Medium–High Carbon Mn-Si-Cr Alloyed Steel at High Temperatures

This study investigates the deformation behavior of a medium–high carbon Mn-Si-Cr alloyed steel using hot compression tests. The tests were performed on a Gleeble 1500D thermomechanical simulator with a temperature range of 950–1150 °C and a strain rate range of 0.005–5 s{sup −1}. The processing parameters (i.e., temperature T, strain rate ε-dot , and strain ε) influenced the flow softening behavior of the material. The dynamic recrystallization occurred during hot deformation. Correlations between the Zener–Hollomon parameter and the size and the volume fraction of new recrystallized grains were developed. These findings are described using mathematical models. The strain-compensated Arrhenius-type constitutive model and the multiple-linear model were developed based on the true stress–strain curves we obtained. A comparative study was performed in order to measure the validity of the two models in representing hot deformation behavior. Both models were shown to accurately predict flow stress across a range of conditions, reflecting the characteristics of true stress–strain curves by exhibiting work hardening, dynamic recovery, and dynamic recrystallization. The empirical multiple-linear mathematical model was shown to be more efficient and accurate when calculating the hot deformation behavior of steel at elevated temperatures.

36 MATERIALS SCIENCE↗