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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Connecting the Radiative Influences of Aerosol upon the Mass Flux Profiles of Shallow Cumuli across the Southeast Atlantic Ocean Basin and its Boundaries (Final Report)

The Atlantic Ocean covers approximately 25% of Earth’s surface and the atmosphere above it is home to a complex array of clouds and aerosols that have important influences on regional and global weather and climate. These influences must be accurately depicted in short range, medium range, seasonal, and climate forecast models. Conditions over the tropical Atlantic are particularly complex due to continental scale plumes of dust from the Sahara Desert and smoke from agricultural burning in Africa that drift across the Atlantic Ocean basin toward the Americas. These plumes are often found meandering in the lower atmosphere above shallow tropical clouds that form above the ocean surface, presumably mingling with these clouds on occasion due to convective mixing processes. Elevated dust and smoke particles absorb incoming sunlight and substantially warm the marine atmosphere in the layer in which they are present. This warming may alter the thermal stability of the marine atmosphere and may throttle or enhance the development of clouds, change their internal structure and the rate at which they precipitate. Alternatively, it may isolate the lower atmosphere from drier layers above enabling water vapor to accumulate near the ocean surface potentially leading to the development of deeper convection. Our study was organized around the principal concept of determining the impact of African smoke and dust plumes upon cloud development at ASI and understanding how a popular shallow convection parameterization used in models responds to the presence of this aerosol. We analyzed observations collected during the US Department of Energy (DOE) Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign using the Atmospheric Radiation Measurement Program’s Mobile Facility #1 (AMF-1), which was deployed to Ascension Island (ASI) in Southeastern Atlantic for a one-year period. Ascension Island is immediately downwind from an African source of these plumes, but far enough removed to enable the lower atmosphere to have reacted to their presence. A main goal of our study was to compute radiative heating rate profiles over Ascension Island and along the trajectory from the biomass burning regions along coastal Africa to Ascension Island. To compute the radiative heating rate due to aerosols and clouds, we employed observed profiles of temperature, humidity, and clouds from LASIC alongside aerosol optical properties from the Modern-era Retrospective analysis for Research and Applications Version 2 (MERRA-2), as input for the Rapid Radiation Transfer Model (RRTM). Radiative heating was also assessed across the southeast Atlantic Ocean using an ensemble of back trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We were successful in this effort and the resulting publication is already being cited despite its relatively short lifetime in the literature. The second part of our study involved the process-level representation of the clouds observed over the Southeastern Atlantic in models. Our initial task, upon which the balance of this portion of the study depended, was to evaluate the representativeness of the clouds observed by AMF-1. What orographic influence did Ascension Island have on the measured cloud structure? We set out to answer this question by trying to separate observations that were clearly indicative of orographic forcing from those that were representative of open ocean. The siting of AMF-1, which was 340-m above sea-level on the slope of a steep escarpment, proved demonstrably problematic for cloud process measurements. Despite considerable effort using multiple approaches including artificial intelligence (AI), we were unable to successfully compensate for the orographic forcing present at the AMF-1 site on ASI and, hence, produce process-level summaries of the convective mass flux representative of open ocean over the Southeastern Atlantic. Even though the project has officially ended, we are making a final attempt using two new types of clustering algorithm (i.e., AI) on the recommendation of a former student, who is an expert in this area. Since we have only recently begun to test these new AI schemes, the recommendations from the second part of our project outlined below are based on our experience at the time of this report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Terry Turbopump Expanded Operating Band Modeling and Simulation Efforts in Fiscal Year 2020 - Progress Report

The Terry Turbine Expanded Operating Band Project is currently conducting testing at Texas A&M University as part of a revised experimental program meant to supplant previous full-scale testing plans under the headings of Milestone 5 and Milestone 6. In consultation with Sandia National Laboratories technical staff and with modeling and simulation support from the same, the hybrid Milestone 5&6 plan is moving forward with experiments aimed at addressing knowledge gaps regarding scale, working fluid, and turbopump self-regulation. Modeling and simulation efforts at Sandia National Laboratories in FY20 fell under the broad umbrella of Milestone 7 and consisted exclusively of MELCOR-related tasks aimed at: 1) Constructing/improving input models of Texas A&M University experiments, 2) Constructing a generic boiling water reactor input model according to best practices with systems-level Teny turbine capabilities, and 3) Adding code capability in order to leverage experimental data/findings, address bugs, and improve general code robustness Project impacts of the Covid-19 pandemic have fortunately been minimal thus far but are mentioned as necessary when discussing the hybrid Milestone 5&6 progress as well as the corresponding Milestone 7 modeling and simulation progress.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Implementation of a Hybrid Edge Node-Centroid Node Approach for the Generation of Reduced Thermal Models

Reduced thermal models are often required for delivery to organizations that manage observatory or launch models at the highest levels of assembly. However, the effort to generate reduced models, and verify against their detailed counterparts, is a challenge that has not yet been conclusively solved. Higher level organizations often place a limit on the number of nodes for delivered models with the assumption that smaller models generally result in less computation time. However, the burden of producing and verifying the accuracy of the reduced models is placed primarily on the lower-level organizations, which in turn consumes resources needed to produce these models. Limiting the total number of allowable nodes may also prevent users from taking full advantage of software capabilities that allow for faster generation of models, such as finite elements, which generally require more nodes than older centroid based models. A methodology using Thermal Desktop was described in 2010 which used: (1) finite elements and edge nodes for a conduction matrix, (2) centroid nodes for capacitance and radiative computations, and (3) the super network feature to produce a conduction matrix based only on the centroid nodes. At that time, the methodology was clear, but the implementation would have had to be done manually; however, with the inclusion of the OpenTD API, this methodology can now be implemented programmatically and for the first time, be a viable approach for the generation of reduced models. The approach was implemented and developed at the NASA Goddard Space Flight Center (GSFC) for the Capture, Containment, and Return System (CCRS) payload on the Earth Return Orbiter (ERO) as part of the Mars Sample Return (MSR) mission, resulting in the TCYEE tool. ERO features a spacecraft bus provided by Airbus through the European Space Agency (ESA) with node limitations on the delivered CCRS model provided by GSFC. TCYEE was used to generate the reduced model for this delivery and the predictions compared favorably to the detailed model currently in use for the thermal performance evaluation. Furthermore, TCYEE is being explored for potential use on the Roman Space Telescope (RST) for the generation of reduced models for delivery to the launch provider, which also has node limit requirements on the RST observatory model for use in launch simulation analyses. This paper describes the methodology, its implementation, and compares the performance of reduced models generated by TCYEE to their detailed counterparts.

Hume L. Peabody↗
NASA NTRSDate not supplied

Implementation of a Hybrid Edge Node-Centroid Node Approach for the Generation of Reduced Thermal Models

Reduced thermal models are often required for delivery to organizations that manage models at the highest levels of assembly. The effort to generate/verify these models against their detailed counterparts is a challenge not yet conclusively solved. Higher level organizations often place a limit on the node count for delivered models, assuming smaller models result in faster computation. The burden of producing and verifying the accuracy of reduced models is primarily on the lower-level organizations, which consumes resources to produce these models. Limiting the number of allowable nodes may prevent users from taking full advantage of software capabilities that allow for faster generation of models, such as finite elements, which require more nodes than centroid based models. A methodology using Thermal Desktop was described in 2010 using: (1) finite elements and edge nodes for the conduction matrix, (2) centroid nodes for capacitance and radiative computations, and (3) the super network feature to produce a conduction matrix based only on the centroid nodes. While the methodology was clear, the implementation would have had to be done manually; with the inclusion of the OpenTD Application Programming Interface, this methodology can now be implemented programmatically and be a viable approach for the generation of reduced models. The approach was implemented at NASA-Goddard for the Capture-Containment-and-Return-System (CCRS) payload, resulting in the TCYEE tool. CCRS requires delivery with node limitations through the European Space Agency to its contractors. TCYEE generated the reduced model for delivery and the predictions compared favorably to the detailed model. Furthermore, TCYEE is being explored for potential use on the Roman Space Telescope (RST) for the generation of reduced models for delivery to the launch provider, which also has node limit requirements. This paper describes the methodology, implementation, and the performance of reduced models compared to their detailed counterparts.

Computer Programming and Software↗
DOE OSTI2020

Probabilistic modeling and prediction of out-of-plane unidirectional composite lamina properties

Computational simulation provides an efficient means to predict the behavior of customized hybrid material configurations using validated, physics-based models. One limitation to this approach is the quality and quantity of available data to characterize the many constituent input properties. Therefore, a systematic approach to identify the most influential parameters on the hybrid behavior and quantify the corresponding uncertainty in predictive capabilities is required. Here, an approach using Bayesian multimodel inference and imprecise global sensitivity analysis is presented to investigate the effects of sparse constituent data on the prediction of composite material properties. The methodology allows the identification, using quantified uncertainties, of the most influential constituent material parameters for specified homogenized properties. This sensitivity analysis further enables a dimension reduction when assessing the influence of uncertainties on material properties and can be used to inform testing programs of the constituent properties that require additional testing/data collection in order to minimize uncertainty in macro-scale composite properties. The methodology is specifically demonstrated on the prediction and sensitivity analysis of out-of-plane mechanical properties of a unidirectional lamina.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Towards Ultra-high-resolution E3SM Land Modeling on Exascale Computers

Here we present an ultra-high-resolution E3SM land model (uELM) for high-fidelity land simulations targeting new Exascale computers. After considering modeling infrastructure compatibility and ELM software features, we designed a parallel model for the uELM development targeting hybrid architectures of new US Exascale computers. We also described a function unit test framework to expedite the piece-wise code porting (with compiler directives), verification, and global variable management. Furthermore, in this study, we report an early uELM model development using OpenACC within a function unit test framework on a pre-Exascale computer, demonstrate the performance of a uLEM submodel with a 3.0-time speedup, and summarize the code porting experience regarding global variable handling, deepcopy, memory reduction, and parallel loop reconstruction.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1988

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

Juday, Richard D.↗
NASA NTRS1998

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

The goal of this research is the continued development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. This work involves a combination of modeling and analysis efforts involving 4DDA datasets and simulations from the University of Wisconsin (UW) hybrid isentropic-sigma (theta-sigma) coordinate model and the GEOS GCM.

Johnson, Donald R.↗
DOE OSTI2024

ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability

Earth system predictability is challenged by the complexity of environmental dynamics and the multitude of variables involved. Current AI foundation models, although advanced by leveraging large and heterogeneous data, are often constrained by their size and data integration, limiting their effectiveness in addressing the full range of Earth system prediction challenges. To overcome these limitations, we introduce the Oak Ridge Base Foundation Model for Earth System Predictability (ORBIT), an advanced vision transformer model that scales up to 113 billion parameters using a novel hybrid tensor-data orthogonal parallelism technique. As the largest model of its kind, ORBIT surpasses the current climate AI foundation model size by a thousandfold. Performance scaling tests conducted on the Frontier supercomputer have demonstrated that ORBIT achieves 684 petaFLOPS to 1.6 exaFLOPS sustained throughput, with scaling efficiency maintained at 41% to 85% across 49,152 AMD GPUs. These breakthroughs establish new advances in AI-driven climate modeling and demonstrate promise to significantly improve the Earth system predictability.

Wang, Xiao↗
NASA NTRS2011

Lessons Learned from Assimilating Altimeter Data into a Coupled General Circulation Model with the GMAO Augmented Ensemble Kalman Filter

Satellite altimetry measurements have provided global, evenly distributed observations of the ocean surface since 1993. However, the difficulties introduced by the presence of model biases and the requirement that data assimilation systems extrapolate the sea surface height (SSH) information to the subsurface in order to estimate the temperature, salinity and currents make it difficult to optimally exploit these measurements. This talk investigates the potential of the altimetry data assimilation once the biases are accounted for with an ad hoc bias estimation scheme. Either steady-state or state-dependent multivariate background-error covariances from an ensemble of model integrations are used to address the problem of extrapolating the information to the sub-surface. The GMAO ocean data assimilation system applied to an ensemble of coupled model instances using the GEOS-5 AGCM coupled to MOM4 is used in the investigation. To model the background error covariances, the system relies on a hybrid ensemble approach in which a small number of dynamically evolved model trajectories is augmented on the one hand with past instances of the state vector along each trajectory and, on the other, with a steady state ensemble of error estimates from a time series of short-term model forecasts. A state-dependent adaptive error-covariance localization and inflation algorithm controls how the SSH information is extrapolated to the sub-surface. A two-step predictor corrector approach is used to assimilate future information. Independent (not-assimilated) temperature and salinity observations from Argo floats are used to validate the assimilation. A two-step projection method in which the system first calculates a SSH increment and then projects this increment vertically onto the temperature, salt and current fields is found to be most effective in reconstructing the sub-surface information. The performance of the system in reconstructing the sub-surface fields is particularly impressive for temperature, but not as satisfactory for salt.

Keppenne, Christian↗
DOE OSTI2020

Plasmon coupling in topological insulator multilayers

Topological insulators (TIs) house two-dimensional Dirac plasmons on their surfaces. In TI thin films, plasmons on the top and bottom surfaces couple electrostatically, giving rise to an acoustic and an optical plasmon mode. By extension, a superlattice comprising TI layers and trivially-insulating layers could house multiple complex plasmon modes which could be used to create a new type of Dirac metamaterial. In this paper, we synthesize TI superlattices, fabricate them into stripe arrays, characterize their optical and plasmonic properties, and model the samples using transfer matrices. Furthermore, we excite plasmon modes that couple to the phonons in the superlattice, resulting in hybrid plasmon phonon polaritons. These modes are modeled using an analytical Fano resonance model and the extracted resonant positions are reproduced by transfer matrix modeling. We also excite an epsilon-near-zero mode in the top dielectric material (Bi 0.5 In 0.5 ) 2 Se 3 . Understanding the behavior of the polariton modes in this complex system will lend insight into the many-body interaction in low-dimensional systems.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Efficient Computation of Separation-Compliant Speed Advisories for Air Traffic Arriving in Terminal Airspace

A class of problems in air traffic management asks for a scheduling algorithm that supplies the air traffic services authority not only with a schedule of arrivals and departures, but also with speed advisories. Since advisories must be finite, a scheduling algorithm must ultimately produce a finite data set, hence must either start with a purely discrete model or involve a discretization of a continuous one. The former choice, often preferred for intuitive clarity, naturally leads to mixed-integer programs, hindering proofs of correctness and computational cost bounds (crucial for real-time operations). In this paper, a hybrid control system is used to model air traffic scheduling, capturing both the discrete and continuous aspects. This framework is applied to a class of problems, called the Fully Routed Nominal Problem. We prove a number of geometric results on feasible schedules and use these results to formulate an algorithm that attempts to compute a collective speed advisory, effectively finite, and has computational cost polynomial in the number of aircraft. This work is a first step toward optimization and models refined with more realistic detail.

Sadovsky, Alexander V.↗
DOE OSTI2025

Hybrid Simulations of FRC Merging and Compression

An improved understanding of field-reversed configuration (FRC) merging and stability in high acceleration and compression magnetic fields is needed to speed up the development of the pulsed fusion concept developed at Helion Energy. All previous theoretical and simulation work on FRC merging and compression was performed using two-dimensional (2D) magnetohydrodynamic (MHD) models. The results of novel 2D hybrid simulations (fluid electrons and full-orbit kinetic ions) of FRC merging and compression are presented. Results of kinetic and MHD simulations, computed using the HYM code, are compared and analyzed. In cases without axial magnetic compression, both the MHD and hybrid simulations show a high sensitivity to the initial parameters (i.e. FRC separation, velocity, normalized separatrix radius, and plasma viscosity), showing that FRCs with large elongation and separatrix radius either do not merge or merge partially, forming a doublet FRC. In conclusion, application of a mirror coil field at the FRC ends with increasing strength is shown to lead to fast and complete merging of the FRCs in MHD and kinetic simulations.

FRC↗
NASA NTRS2009

Parameter Estimation for a Hybrid Adaptive Flight Controller

This paper expands on the hybrid control architecture developed at the NASA Ames Research Center by addressing issues related to indirect adaptation using the recursive least squares (RLS) algorithm. Specifically, the hybrid control architecture is an adaptive flight controller that features both direct and indirect adaptation techniques. This paper will focus almost exclusively on the modifications necessary to achieve quality indirect adaptive control. Additionally this paper will present results that, using a full non -linear aircraft model, demonstrate the effectiveness of the hybrid control architecture given drastic changes in an aircraft s dynamics. Throughout the development of this topic, a thorough discussion of the RLS algorithm as a system identification technique will be provided along with results from seven well-known modifications to the popular RLS algorithm.

Campbell, Stefan F.↗
DOE OSTI2023

LCA-PyTorch

LCA-PyTorch is a code repository which contains PyTorch implementations of the Locally Competitive Algorithm (LCA), which is a biologically-plausible sparse coding model. LCA-PyTorch allows for the training, testing, and analysis of single layer LCA networks, multi-layer LCA networks, and hybrid LCA-based deep neural network models on a wide variety of applications and data types. LCA-PyTorch was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. LCA-PyTorch interfaces heavily with the open-source PyTorch Python package.

Teti, Michael↗
DOE OSTI2021

Electrical Submersible Pumps: A System Modeling Approach for Power Quality Analysis With Variable Frequency Drives

This article proposes a high-level engineering guide to develop an integrated system model for power quality analysis in electrical submersible pump (ESP) applications with variable frequency drives (VFDs). Such analyses are troublesome in the industry due to the complexity of these systems. In this article, simple steps to perform system integration analyses of such arrangements, including torsional analysis, are developed. A simplified VFD-ESP model suitable for coupled electrical and mechanical analysis in steady state is proposed in all their configurations of practical interest. Such a model can be easily implemented in common simulation software, significantly reducing engineering efforts for implementation and analysis. The focus of the proposed model is the prediction of ESP failures that might result from a poor power quality caused by VFDs. Analytical expressions of different types of harmonics in these systems, as well as their accurate locations in the frequency domain, including their interharmonics and common-mode harmonics, are derived for this purpose. Further, the effectiveness of the proposed model is verified through offline and real-time hybrid simulation results. Finally, a comparison between simulation results obtained using the proposed model and measurements collected on a down-scale laboratory prototype is carried out to demonstrate the accuracy of the suggested modeling approach.

42 ENGINEERING↗
NASA NTRS1993

Hybrid techniques for complex aerospace electromagnetics problems

Important aerospace electromagnetics problems include the evaluation of antenna performance on aircraft and the prediction and control of the aircraft's electromagnetic signature. Due to the ever increasing complexity and expense of aircraft design, aerospace engineers have become increasingly dependent on computer solutions. Traditionally, computational electromagnetics (CEM) has relied primarily on four disparate techniques: the method of moments (MoM), the finite-difference time-domain (FDTD) technique, the finite element method (FEM), and high frequency asymptotic techniques (HFAT) such as ray tracing. Each of these techniques has distinct advantages and disadvantages, and no single technique is capable of accurately solving all problems of interest on computers that are available now or will be available in the foreseeable future. As a result, new approaches that overcome the deficiencies of traditional techniques are beginning to attract a great deal of interest in the CEM community. Among these new approaches are hybrid methods which combine two or more of these techniques into a coherent model. During the ASEE Summer Faculty Fellowship Program a hybrid FEM/MoM computer code was developed and applied to a geometry containing features found on many modern aircraft.

Aberle, Jim↗