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A Multi-Gravity Docking and Utilities Transfer System for a Common Habitat Architecture

The Common Habitat architecture, a study architecture based on a large habitat derived from the SLS Core Stage Liquid Oxygen tank and designed to operate in microgravity, lunar surface, and Mars surface environments, requires a pressurized docking and berthing system that also works in all three domains. Prior flown docking systems have only been designed for microgravity, but a prototype suit port-derived docking system was developed under the Constellation program for the lunar surface. This system employed an active-active mating adapter approach consisting of a simplistic passive docking system on all spacecraft and a pressurized mating adapter with active systems on each end to form the docking connection. Derived from this approach, the Common Habitat architecture will use a multi-gravity active-active mating adapter (MGAAMA) to perform this function on the Moon, Mars, and in microgravity, connecting the various pressurized elements needed for surface base camps or deep space habitation. Design aspects and open trades of the MGAAMA system will be described. In addition to forming a structural connection and enabling the transfer of crew and equipment, the MGAAMA must also transfer utilities in the form of gases, fluids, power, and data. The MGAAMA is also designed with a degree of articulation in order to accommodate significant angular misalignment. Due to the environmental conditions the MGAAMA will experience, dust and thermal protection systems are discussed. Because the MGAAMA involves docking to spacecraft with different docking systems of different sizes, the MGAAMA is a family of docking systems with interfaces compatible with current and legacy spacecraft docking systems.

Docking↗

DOE OSTI2023

Exascale Multiphysics Nuclear Reactor Simulations for Advanced Designs

ENRICO is a coupled application developed under the U.S. Department of Energy's Exascale Computing Project (ECP) targeting the modeling of advanced nuclear reactors. It couples radiation transport with heat and fluid simulation, including the high-fidelity, highresolution Monte-Carlo code Shift and the Computational fluid dynamics code NekRS. NekRS is a highly-performant open-source code for simulation of incompressible and low-Mach fluid flow, heat transfer, and combustion with a particular focus on turbulent flows in complex domains. It is based on rapidly convergent high-order spectral element discretizations that feature minimal numerical dissipation and dispersion. State-of-the-art multilevel preconditioners, efficient high-order time-splitting methods, and runtime-adaptive communication strategies are built on a fast OCCA-based kernel library, libParanumal, to provide scalability and portability across the spectrum of current and future high-performance computing platforms. On Frontier, Nek5000/RS has recently achieved an unprecedented milestone in breaching over 1 billion spectral elements and 350 billion degrees of freedom. Shift has demonstrated the capability to transport upwards of 1 billion particles per second in full core nuclear reactor simulations featuring complete temperature-dependent, continuous-energy physics on Frontier. Shift achieved a weak-scaling efficiency of 97.8% on 8192 nodes of Frontier and calculated 6 reactions in 214,896 fuel pin regions below 1% statistical error yielding first-of-a-kind resolution for a Monte Carlo transport application.

Hamilton, Steven P.↗

DOE OSTI2025

A Block-Structured Adaptive Mesh Framework to Solve Radiation Transfer Equation in Irregular Embedded Geometries

Radiation transport arises in various scientific, industrial, and medical fields, and understanding its effect in applications is needed to make accurate predictions, safety assessments and performance optimizations. Solving the Radiation Transport Equation (RTE) is challenging due to its integro-differential nature, which involves both differential and integral terms. The differential term describes the change in radiation intensity due to absorption and emission, while the integral term accounts for scattering. The accurate modeling of radiation is further complicated in many applications due to the complex, irregular geometries. Various methods exist for solving the RTE, including the zonal, Monte Carlo, spherical harmonics, discrete ordinates, and finite volume methods. Traditional mesh-based approaches, which rely on structured or unstructured meshes, struggle with irregular geometries due to: a) the difficulty of conforming structured grids to irregular domains, b) challenges in enforcing boundary conditions correctly, and c) the additional computational cost of unstructured mesh methods. This work presents a second-order accurate method for solving the RTE in irregular geometries. The radiation intensity is discretized using the finite-volume method in both spatial and angular directions on regular Cartesian grid blocks. Leveraging the block-structured adaptive mesh refinement (AMR) framework provided by AMReX, our method refines the grid locally to reduce spatial discretization error, ensuring a converged numerical solution while minimizing computational costs elsewhere. A two-stage deferred correction approach is employed: First, a first-order discretization on grid blocks is solved using an algebraic multigrid method in HYPRE. Second, a correction term is applied explicitly to achieve second-order accuracy. The correction term is calculated by approximating the radiation flux on cell faces using a Total Variation Diminishing (TVD) scheme. This approach ensures quick convergence of the multigrid method while preserving higher-order accuracy of the numerical solution. Irregular geometries are resolved as embedded boundaries (EB), resulting in both cut cells and regular cells. In cut cells, we modify the fluxes using face fractions and incorporate additional contributions from EB boundary conditions. To ensure higher-order convergence near the EB interface, the correction term is modified by interpolating the radiation intensity to fictitious ghost points. The implementation takes advantage of modern supercomputers by leveraging AMReX’sMPI/X parallelization strategy where X can be MPI or a GPU accelerator including CUDA, HIP and DPC++. We validate our solver using classical test cases, both with and without EB, demonstrating accuracy and efficiency. Additionally, we analyze the impact of adaptive mesh refinement on solution accuracy and computational cost, highlighting the advantages of our approach for high-resolution radiation transport simulations.

computational fluid dynamics (CFD)↗

DOE OSTI2021

Volumetric Density-Equalizing Reference Map with Applications

The density-equalizing map, a technique developed for cartogram creation, has been widely applied to data visualization but only for 2D applications. Here, we propose a novel method called the volumetric density-equalizing reference map (VDERM) for computing density-equalizing map for volumetric domains. Given a prescribed density distribution in a volumetric domain in $\mathbb{R}^3$, the proposed method continuously deforms the domain, with different volume elements enlarged or shrunk according to the density distribution. With the aid of the proposed method, medical and sociological data can be visualized via deformations of 3D objects. The method can also be applied to adaptive remeshing and shape modeling. Furthermore, by exploiting the time-dependent nature of the proposed method, applications to shape morphing can be easily achieved. Experimental results are presented to demonstrate the effectiveness of the proposed method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Structural basis for selective modification of Rho and Ras GTPases by Clostridioides difficile toxin B

Toxin B (TcdB) is a primary cause of Clostridioides difficile infection (CDI). This toxin acts by glucosylating small GTPases in the Rho/Ras families, but the structural basis for TcdB recognition and selectivity of specific GTPase substrates remain unsolved. Here, we report the cocrystal structures of the glucosyltransferase domain (GTD) of two distinct TcdB variants in complex with human Cdc42 and R-Ras, respectively. These structures reveal a common structural mechanism by which TcdB recognizes Rho and R-Ras. Furthermore, we find selective clustering of adaptive residue changes in GTDs that determine their substrate preferences, which helps partition all known TcdB variants into two groups that display distinct specificities toward Rho or R-Ras. Mutations that selectively disrupt GTPases binding reduce the glucosyltransferase activity of the GTD and the toxicity of TcdB holotoxin. These findings establish the structural basis for TcdB recognition of small GTPases and reveal strategies for therapeutic interventions for CDI.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Distributed Embedded Energy Converter Technologies for Marine Renewable Energy (A Technical Report)

The domain of distributed embedded energy converter technologies (DEEC-Tec) is a nascent and underexplored paradigm for harvesting and converting marine renewable energy. The paradigm distinguishes itself through its use of many small distributed embedded energy converters (DEECs) that, ultimately, are assembled through the creation of "DEEC-Tec metamaterials" to create an overall larger marine renewable energy harvesting and converting structure. As an example, such a structure could be an ocean wave energy converter - a converter whose structure is made from various types of DEEC-Tec metamaterials that harvests ocean wave energy and converts that energy into something more useful such as electricity. To that end, DEEC-Tec can be viewed at three different technology levels: (1) individual distributed embedded energy converters, also known as DEECs; (2) DEEC-Tec metamaterials-essentially, pseudo-materials made from the interconnection of many DEECs; and (3) overall larger complete marine renewable energy harvesting-converting structures-these structures being made from DEEC-Tec metamaterials. Arising directly from the application of DEEC-Tec to harvest and convert ocean wave energy are several noteworthy benefits, some of which include: (1) the lack of load concentrations into singular components or subsystems, (2) broad-banded ocean wave energy frequency harvesting and conversion, and (3) inherent redundancy-failure of some individual DEECs does not represent a failure of an entire DEEC-Tec-based WEC. This report describes DEEC-Tec by way of descriptions of those three technology levels: individual DEECs, DEEC-Tec metamaterials, and DEEC-Tec-based WECs. Moreover, the report describes corresponding research approaches and methodologies for related concepts such as DEEC-Tec-based WEC topologies and morphologies in addition to manufacturing and fabrication techniques found suitable for the application of DEEC-Tec within the general domain of marine renewable energy-moving beyond only ocean wave energy conversion.

16 TIDAL AND WAVE POWER↗

NASA NTRS1998

In-Flight System Identification

A method is proposed and studied whereby the system identification cycle consisting of experiment design and data analysis can be repeatedly implemented aboard a test aircraft in real time. This adaptive in-flight system identification scheme has many advantages, including increased flight test efficiency, adaptability to dynamic characteristics that are imperfectly known a priori, in-flight improvement of data quality through iterative input design, and immediate feedback of the quality of flight test results. The technique uses equation error in the frequency domain with a recursive Fourier transform for the real time data analysis, and simple design methods employing square wave input forms to design the test inputs in flight. Simulation examples are used to demonstrate that the technique produces increasingly accurate model parameter estimates resulting from sequentially designed and implemented flight test maneuvers. The method has reasonable computational requirements, and could be implemented aboard an aircraft in real time.

Morelli, Eugene A.↗

NASA NTRS2008

Direct Solve of Electrically Large Integral Equations for Problem Sizes to 1M Unknowns

Matrix methods for solving integral equations via direct solve LU factorization are presently limited to weeks to months of very expensive supercomputer time for problems sizes of several hundred thousand unknowns. This report presents matrix LU factor solutions for electromagnetic scattering problems for problem sizes to one million unknowns with thousands of right hand sides that run in mere days on PC level hardware. This EM solution is accomplished by utilizing the numerical low rank nature of spatially blocked unknowns using the Adaptive Cross Approximation for compressing the rank deficient blocks of the system Z matrix, the L and U factors, the right hand side forcing function and the final current solution. This compressed matrix solution is applied to a frequency domain EM solution of Maxwell's equations using standard Method of Moments approach. Compressed matrix storage and operations count leads to orders of magnitude reduction in memory and run time.

Shaeffer, John↗

NASA NTRS2015

High-Speed On-Board Data Processing for Science Instruments: HOPS

The project called High-Speed On-Board Data Processing for Science Instruments (HOPS) has been funded by NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) program during April, 2012 â€" April, 2015. HOPS is an enabler for science missions with extremely high data processing rates. In this three-year effort of HOPS, Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) and 3-D Winds were of interest in particular. As for ASCENDS, HOPS replaces time domain data processing with frequency domain processing while making the real-time on-board data processing possible. As for 3-D Winds, HOPS offers real-time high-resolution wind profiling with 4,096-point fast Fourier transform (FFT). HOPS is adaptable with quick turn-around time. Since HOPS offers reusable user-friendly computational elements, its FPGA IP Core can be modified for a shorter development period if the algorithm changes. The FPGA and memory bandwidth of HOPS is 20 GB/sec while the typical maximum processor-to-SDRAM bandwidth of the commercial radiation tolerant high-end processors is about 130-150 MB/sec. The inter-board communication bandwidth of HOPS is 4 GB/sec while the effective processor-to-cPCI bandwidth of commercial radiation tolerant high-end boards is about 50-75 MB/sec. Also, HOPS offers VHDL cores for the easy and efficient implementation of ASCENDS and 3-D Winds, and other similar algorithms. A general overview of the 3-year development of HOPS is the goal of this presentation.

Beyon, Jeffrey↗

NASA NTRS2022

Migration Theory in Climate Mobility Research

The purpose of this article is to explore how migration theory is invoked in empirical studies of climate-related migration, and to provide suggestions for engagement with theory in the emerging field of climate mobility. Theory is critical for understanding processes we observe in social-ecological systems because it points to a specific locus of attention for research, shapes research questions, guides quantitative model development, influences what researchers find, and ultimately informs policies and programs. Research into climate mobility has grown out of early studies on environmental migration, and has often developed in isolation from broader theoretical developments in the migration research community. As such, there is a risk that the work may be inadequately informed by the rich corpus of theory that has contributed to our understanding of who migrates; why they migrate; the types of mobility they employ; what sustains migration streams; and why they choose certain destinations over others. On the other hand, there are ways in which climate and broader environment migration research is enriching the conceptual frameworks being employed to understand migration, particularly forced migration. This paper draws on a review of 75 empirical studies and modeling efforts conducted by researchers from a diversity of disciplines, covering various regions, and using a variety of data sources and methods to assess how they used theory in their research. The goal is to suggest ways forward for engagement with migration theory in this large and growing research domain.

migration theory↗

NASA NTRS2024

Starling Formation-Flying Optical Experiment: Initial Operations and Flight Results

This paper presents initial flight results for angles-only navigation of a swarm of small spacecraft, conducted during the Starling Formation-Flying Optical Experiment (StarFOX). StarFOX is one of four experiments aboard the NASA Starling mission, which consists of four CubeSats launched in July 2023. Angles-only methods apply inter-satellite bearing angles obtained by on-board cameras for navigation, increasing satellite autonomy and enabling new mission concepts. Nevertheless, prior flight demonstrations have only featured one observer and target and have relied upon a-priori target orbit knowledge for initialization, translational maneuvers to resolve target range, and external absolute orbit updates to maintain convergence. StarFOX overcomes these limitations by applying the angles-only Absolute and Relative Trajectory Measurement System (ARTMS), which integrates three novel algorithms. Image Processing detects and tracks multiple targets in images, using multi-hypothesis methods and domain-specific kinematic modeling, and computes target bearing angles. Batch Orbit Determination computes initial swarm orbit estimates from bearing angle batches, via iterative batch least squares and sampling of the weakly observable target range. Sequential Orbit Determination leverages an adaptive, efficient unscented Kalman filter with nonlinear models to refine swarm state estimates over time. Multi-observer measurements shared over an intersatellite link are seamlessly fused to enable robust absolute and relative orbit determination. Initial StarFOX experiments are the first demonstrations of autonomous angles-only navigation for a satellite swarm, including multi-target and multi-observer relative navigation; autonomous initialization of navigation for unknown targets; and simultaneous absolute and relative orbit determination. Relative navigation accuracy of 1% (single observer) and 0.2% (multi-observer) of the inter-satellite range is achieved under challenging measurement conditions. Results demonstrate promising performance with regards to ongoing StarFOX campaigns and the application of angles-only navigation to future distributed missions.

Relative Navigation↗

NASA NTRS2026

Adaptation and Response in Drylands (ARID): A Dryland Research Agenda and Campaign Strategy

Dryland ecosystems cover 41% of Earth’s land surfaces, account for 44% of cultivated lands and 60% of food sources, and make large contributions to the global water and carbon cycles. However, these ecosystems are experiencing unprecedented extremes including heatwaves, floods, and droughts as well as hotter temperatures and often declining water resource availability. These ecosystems are some of the most challenging to monitor given their high temporal variability with rapid response to their environment as well as vast spatial variability with intermixing of different plant species and life forms amongst bare soil coverage. The Adaptation and Response in Drylands (ARID) campaign was selected by National Aeronautics and Space Administration (NASA) as a scoping study to develop a research agenda for a dryland field campaign. Here, we detail our ARID science research agenda and implementation plan that were developed based on an extensive community engagement effort in over 160 events with over a thousand scientists, land managers, and Tribal communities between 2023 and 2024. The selected science themes cover drought and climate variability, ecosystem structure, function, and biodiversity, carbon cycle interannual variability and trends, and social ecological systems (land management and adaptation). We then detail our remote sensing, modeling, and field-based strategies to capture high temporal and high spatial resolution processes. Finally, our implementation strategy is presented which includes focus area selections in a core intensive western U.S. domain and distributed international domains. This strategy includes our overarching guiding principles of using multi-temporal airborne acquisitions and super sites as well as enhancing land management in co-development with end-user partners. While originally developed for NASA, our ARID report creates a blueprint for any future dryland field campaign, at any scale, that can be implemented widely for foundational and applied science objectives.

drylands↗

DOE OSTI2020

1D to 2D Transition in Tellurium Observed by 4D Electron Microscopy

A new microwave-enhanced synthesis method for the production of tellurium nanostructures is reported here—with control over products from the 1D regime (sub-5 nm diameter nanowires), to nanoribbons, to the 2D tellurene regime—along with a new methodology for local statistical quantification of the crystallographic parameters of these materials at the nanometer scale. Using a direct electron detector and image-corrected microscope, large and robust 4D scanning transmission electron microscopy datasets for accurate structural analysis are obtained. These datasets allow the adaptation of quantitative techniques originally developed for X-ray diffraction (XRD) refinement analyses to transmission electron microscopy, enabling the first demonstration of sub-picometer accuracy lattice parameter extraction while also obtaining both the size of the coherent crystallite domains and the nanostrain, which is observed to decrease as nanowires transition to tellurene. This new local analysis is commensurate with global powder XRD results, indicating the robustness of both the new synthesis approach and new structural analysis methodology for future scalable production of 2D tellurene and characterization of nanomaterials.

2D materials↗

DOE OSTI2022

Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources

We live in momentous times. The science community is empowered with an arsenal of cosmic messengers to study the universe in unprecedented detail. Gravitational waves, electromagnetic waves, neutrinos, and cosmic rays cover a wide range of wavelengths and timescales. Combining and processing these datasets that vary in volume, speed, and dimensionality requires new modes of instrument coordination, funding, and international collaboration with a specialized human and technological infrastructure. In tandem with the advent of large-scale scientific facilities, the last decade has experienced an unprecedented transformation in computing and signal-processing algorithms. The combination of graphics processing units, deep learning, and the availability of open source, high-quality datasets has powered the rise of artificial intelligence. This digital revolution now powers a multibillion dollar industry, with far-reaching implications in technology and society. In this chapter, we describe pioneering efforts to adapt artificial intelligence algorithms to address computational grand challenges in multi-messenger astrophysics. We review the rapid evolution of these disruptive algorithms, from the first class of algorithms introduced in early 2017 to the sophisticated algorithms that now incorporate domain expertise in their architectural design and optimization schemes. We discuss the importance of scientific visualization and extreme-scale computing in reducing time-to-insight and obtaining new knowledge from the interplay between models and data.

Artificial Intelligence↗

DOE OSTI2020

Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models

Software flaw detection using multimodal deep learning models has been demonstrated as a very competitive approach on benchmark problems. In this work, we demonstrate that even better performance can be achieved using neural architecture search (NAS) combined with multimodal learning models. We adapt a NAS framework aimed at investigating image classification to the problem of software flaw detection and demonstrate improved results on the Juliet Test Suite, a popular benchmarking data set for measuring performance of machine learning models in this problem domain.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1998

Automating Mission Scheduling for Space-Based Observatories

In this paper we describe the use of our planning and scheduling framework, HSTS, to reduce the complexity of science mission planning. This work is part of an overall project to enable a small team of scientists to control the operations of a spacecraft. The present process is highly labor intensive. Users (scientists and operators) rely on a non-codified understanding of the different spacecraft subsystems and of their operating constraints. They use a variety of software tools to support their decision making process. This paper considers the types of decision making that need to be supported/automated, the nature of the domain constraints and the capabilities needed to address them successfully, and the nature of external software systems with which the core planning/scheduling engine needs to interact. HSTS has been applied to science scheduling for EUVE and Cassini and is being adapted to support autonomous spacecraft operations in the New Millennium initiative.

Pell, Barney↗

NASA NTRS1999

"Novel Techniques in Non-Stationary Analysis of Rotorcraft Vibration Signitures"

This research effort produced new methods to analyze the performance of linear predictors that track non-stationary processes. Specifically, prediction methods have been applied to the vibration pattern of rotorcraft drivetrains. This analysis is part or a larger rotorcraft Health and Usage Monitoring System (HUMS) that can diagnose immediate failures of the subsystems, as indicated by abrupt change in the vibration signature, and prognosticate future health, by examining the vibration patterns against long-term trends. This problem is described by a earlier joint paper co-authored by members of the funding agency and the recipient institutions prior to this grant effort. Specific accomplishments under this grant include the following: (1) Definition of a framework for analysis of non-stationary time-series estimation using the coefficients of an adaptive filter. (2) Description of a novel method of combining short-term predictor error and long-term regression error to analyze the performance of a non-stationary predictor. (3) Formulation of a multi-variate probability density function that quantifies the performance of a adaptive predictor by using the short- and long-term error variables in a Gamma function distribution. and (4) Validation of the mathematical formulations with empirical data from NASA flight tests and simulated data to illustrate the utility beyond the domain of vibrating machinery.

Meng, Teresa↗