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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2002

Description and Sensitivity Analysis of the SOLSE/LORE-2 and SAGE III Limb Scattering Ozone Retrieval Algorithms

The SOLSE (Shuttle Ozone Limb Sounding Experiment) and LORE (Limb Ozone Retrieval Experiment) instruments are scheduled for reflight on Space Shuttle flight STS-107 in July 2002. In addition, the SAGE III (Stratospheric Aerosol and Gas Experiment) instrument will begin to make limb scattering measurements during Spring 2002. The optimal estimation technique is used to analyze visible and ultraviolet limb scattered radiances and produce a retrieved ozone profile. The algorithm used to analyze data from the initial flight of the SOLSE/LORE instruments (on Space Shuttle flight STS-87 in November 1997) forms the basis of the current algorithms, with expansion to take advantage of the increased multispectral information provided by SOLSE/LORE-2 and SAGE III. We also present detailed sensitivity analysis for these ozone retrieval algorithms. The primary source of ozone retrieval error is tangent height misregistration (i.e., instrument pointing error), which is relevant throughout the altitude range of interest, and can produce retrieval errors on the order of 10-20 percent due to a tangent height registration error of 0.5 km at the tangent point. Other significant sources of error are sensitivity to stratospheric aerosol and sensitivity to error in the a priori ozone estimate (given assumed instrument signal-to-noise = 200). These can produce errors up to 10 percent for the ozone retrieval at altitudes less than 20 km, but produce little error above that level.

Loughman, R.↗

NASA NTRS2013

Texturecam: A Smart Camera for Microscale, Mesoscale, and Deep Space Applications

The TextureCam project is developing a 'smart camera' that can classify geologic surfaces in planetary images. This would allow autonomous spacecraft to collect data opportunisitcally during intervals between communications with Earth, such as during long traverses. Its surface classifications can identify new targets that were not anticipated in advance. The spacecraft might use this information to target these features with high-resolution instruments such as spectrometers nd narrow-field cameras. Classifications could also inform data 'triage' decisions, identifying high value images for prioritized downlink. Finally, the surface classification can serve as compressed maps of image content. Each of these strategies can improve the science data returned at each command cycle and speed reconnaissance during site survey and astrobiology investigation. Our first year of development has completed the image analysis algorithms and validated them in software tests. Here we survey these initial results and explore several application areas relevant to Mars and beyond.

Hyperspectral imagery↗

DOE OSTI2025

Using a Large Language Model for Accurate Technical Language Generation in the Predictive Maintenance of Circulating Water Systems in Nuclear Power Plants

Machine learning (ML) methods for predictive maintenance (PdM) are emerging as effective proactive strategies for diagnosing equipment degradation and enabling effective decision-making. However, explainability and trustworthiness of artificial intelligence are two salient challenges that need to be addressed for wider deployment of these technologies in nuclear power plants (NPPs). Large language models (LLMs) offer a unique approach to tackle these challenges by explaining PdM, work orders, diagnosis results, and ML algorithms to users, who may not be familiar with ML and PdM in general. Moreover, by dynamically retrieving relevant information from technical documents and evaluating factuality of LLM generation, the accuracy and relevance of LLM generations can be improved. This work demonstrates using LLMs to explain the causes and consequences of circulating water system failures based on multiyear NPP work orders. This work tests the capability of multimodal LLM approaches in explaining the differences in the circulating water system from both the Salem and Hope Creek NPPs using both text and image resources. This work also demonstrates the use of multimodal LLMs in describing the diagnosis tab of a predictive maintenance software named VIsualization for PrEdictive maintenance Recommendation (VIPER) to users.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

NASA Armstrong Flight Research Center Dynamics and Controls (530)

AFRC Controls and Dynamics Branch - Research Areas: - Traditional GN&C - Classical and advanced control algorithms - Risk based approaches for safety critical applications - Integration of novel sensors and sensor fusion (FOSS, LIDAR, etc.) - Trajectory optimization and control - Flight/System Dynamics - Equations of Motion and integrated modeling of vehicles and vehicle systems - Unique and novel vehicle dynamics - Methods for extracting relevant vehicle dynamic information from flight data - Human and vehicle interfaces and interactions - Handling Qualities and Pilot-in-the-loop oscillations (PIO) predictions and design metrics - Ride quality research - Autonomy - Novel algorithms, sensors, and sensor fusion - Bounding risk for testing automated systems - Pilot/Operator interactions - Engineering Support and Airworthiness Assessments - Aircraft modifications and experimental configurations

Chris Miller↗

NASA NTRS1999

Remote Sensing May Provide Unprecedented Hydrological Data

Basic hydrological research and water resources management may reap tremendous benefits from remote sensing technology, studies are showing. Satellite coverage may allow unprecedented accuracy in the quantification of the global hydrological cycle, for example. Yet despite such benefits, few hydrologists currently use such data. This is partly because the needed tools and algorithms are not fully developed. Such development requires field experiments that combine remotely sensed data with detailed in situ observations. AGU's Remote Sensing in Hydrology Committee has constructed a Web site (http://Iand.gsfc.nasa.gov/RSHC.html) that gives an overview of many such experiments. Included on the site is information on each experiment's overall goal, the types of in situ and remotely sensed measurements taken, relevant climate and vegetation conditions, and so forth. Links to additional relevant Web sites are included. The site is designed to be a suitable starting point for those interested in learning more about remote sensing in hydrology. It lists members of the committee who can be contacted for further information. Hydrologists have recognized the potential of remote sensing technology since the 1970s. It offers a way to avoid the logistical and economic difficulties associated with obtaining continuous in situ measurements of various hydrological variables, difficulties that are particularly pronounced in remote regions. Microwave instruments in particular can potentially provide all-weather, areally averaged estimates of certain variables (such as precipitation, soil moisture, and snow water content) that have been essentially unattainable in the past. In remote sensing, the conversion of emitted and reflected radiances into useful hydrological data is a complex problem. The measured radiances, for example, reflect the integrated character of a pixel area, a scale inconsistent with the point measurements of traditional hydrology. To develop the needed algorithms, field experiments must be designed that combine relevant satellite measurements with traditional in situ measurements in regions that are al- ready well understood hydrologically. Such field experiments can lead to the development of hydrological models that are driven with remotely sensed data. Once the performance of these models is deemed acceptable in the heavily monitored basins, they can be "transported" for use in regions having little or no in situ measurement system. Author,5: Randal D. Koster, Paul R. Houser and Edwin T. Engman, Hydrological Sciences Branch, Laboratory for Hydrospheric Process, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA; William P. Kustas, Hydrology Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, Maryland, USA.

Koster, R.↗

NASA NTRS1985

Numerical Experimentation with Maximum Likelihood Identification in Static Distributed Systems

Many important issues in the control of large space structures are intimately related to the fundamental problem of parameter identification. One might also ask how well this identification process can be carried out in the presence of noisy data since no sensor system is perfect. With these considerations in mind the algorithms herein are designed to treat both the case of uncertainties in the modeling and uncertainties in the data. The analytical aspects of maximum likelihood identification are considered in some detail in another paper. The questions relevant to the implementation of these schemes are dealt with, particularly as they apply to models of large space structures. The emphasis is on the influence of the infinite dimensional character of the problem on finite dimensional implementations of the algorithms. Those areas of current and future analysis are highlighted which indicate the interplay between error analysis and possible truncations of the state and parameter spaces.

Scheid, R. E., Jr.↗

DOE OSTI2025

Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles

Iron carbide (Fe x C y ) nanoparticles (NPs) are promising candidates for replacing platinum group metals in industrial applications, such as high-temperature Fischer–Tropsch synthesis. However, due to their amorphous nature, characterization of the active sites has been challenging experimentally and computationally. Here, using a combined density functional theory (DFT), neural network interatomic potential-assisted global optimization, and ensemble learning study, we evaluate dynamic surface changes associated with syngas (H and CO) interactions. For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe 182 C 88 NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). Once generated, the Fe 182 C 88 NP active sites and particle morphology are thoroughly characterized before the effects of syngas adsorbate interactions are explored by using DFT and molecular dynamics simulations. Lastly, we explore correlations between geometric and electronic features of the active sites and the adsorption of H (H ads ), using a regularized random forest machine learning algorithm. In doing so, we identified the Fe–C coordination number and p orbital occupancy as the most important descriptors affecting H ads . Furthermore, using a combined ML and quantum chemistry approach, our work demonstrates a general and efficient procedure for generating and probing complex surface phenomena on binary nanoparticles.

Adsorption↗

DOE OSTI2026

Simple algorithm for polarized parton evolution

We present an algorithm to include the correlation between the production and decay planes of gluons in a parton-shower simulation. The technique is based on identifying the charge currents responsible for the creation and annihilation of the vector field. It is applicable in both the hard-collinear and the soft wide-angle region. As a function of the number of particles, the algorithm scales linear in computing time and memory. We demonstrate agreement with fixed-order perturbative calculations in the relevant kinematical limits, and present a new observable that can be used to probe correlations beyond current-current interactions.

Höche, Stefan [Fermi National Accelerator Laborato↗

DOE OSTI2022

Quantum Circuits for the Preparation of Spin Eigenfunctions on Quantum Computers

The application of quantum algorithms to the study of many-particle quantum systems requires the ability to prepare wave functions that are relevant in the behavior of the system under study. Hamiltonian symmetries are important instruments used to classify relevant many-particle wave functions and to improve the efficiency of numerical simulations. In this work, quantum circuits for the exact and approximate preparation of total spin eigenfunctions on quantum computers are presented. Two different strategies are discussed and compared: exact recursive construction of total spin eigenfunctions based on the addition theorem of angular momentum, and heuristic approximation of total spin eigenfunctions based on the variational optimization of a suitable cost function. The construction of these quantum circuits is illustrated in detail, and the preparation of total spin eigenfunctions is demonstrated on IBM quantum devices, focusing on three- and five-spin systems on graphs with triangle connectivity.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1987

Implementation of a block Lanczos algorithm for Eigenproblem solution of gyroscopic systems

The details of implementation of a general numerical procedure developed for the accurate and economical computation of natural frequencies and associated modes of any elastic structure rotating along an arbitrary axis are described. A block version of the Lanczos algorithm is derived for the solution that fully exploits associated matrix sparsity and employs only real numbers in all relevant computations. It is also capable of determining multiple roots and proves to be most efficient when compared to other, similar, exisiting techniques.

Gupta, Kajal K.↗

NASA NTRS1987

Implementation of a block Lanczos algorithm for eigenproblem solution of gyroscopic systems

This paper describes the details of implementation of a general numerical procedure developed for the accurate and economical computation of natural frequencies and associated modes of any elastic structure rotating along an arbitrary axis. A block version of the Lanczos algorithm is derived for the solution that fully exploits associated matrix sparsity and employs only real numbers in all relevant computations. It is also capable of determining multiple roots and proves to be most efficient when compared to other, similar, existing techniques.

Gupta, K. K.↗

NASA NTRS1991

Fuzzy geometry, entropy, and image information

Presented here are various uncertainty measures arising from grayness ambiguity and spatial ambiguity in an image, and their possible applications as image information measures. Definitions are given of an image in the light of fuzzy set theory, and of information measures and tools relevant for processing/analysis e.g., fuzzy geometrical properties, correlation, bound functions and entropy measures. Also given is a formulation of algorithms along with management of uncertainties for segmentation and object extraction, and edge detection. The output obtained here is both fuzzy and nonfuzzy. Ambiguity in evaluation and assessment of membership function are also described.

Pal, Sankar K.↗

NASA NTRSDate not supplied

Validation of the Hypersolve CFD Solver for Entry Descent and Landing Applications

The functional equivalence of the HyperSolve unstructured edge-based, finite-volume computational fluid dynamics code to the Langley Aerothermodynamic Upwind Relaxation Algorithm multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing community. A suite of cases using a range of thermochemical gas models on relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flowfield quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. The functional equivalence of the HyperSolve unstructured edge-based finite-volume computational fluid dynamics (CFD) code to the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) multiblock structured grid code is documented for applications of interest to the Entry, Descent, and Landing (EDL) community. A suite of cases using a range of thermochemical gas models on EDL-relevant vehicle configurations were analyzed with both codes and the results compared. A tolerance of ±4% difference in surface pressure and surface heat flux from a benchmark LAURA solution was used as the criterion for functional equivalence, and comparisons of flow field quantities are also included to verify that the thermochemical nonequilibrium capabilities in HyperSolve match those of the LAURA code. In general, HyperSolve predictions for surface pressure and surface heat flux are in close agreement with those predicted by LAURA.

hypersolve↗

NASA NTRSDate not supplied

Validation of the HyperSolve CFD Solver for Entry Descent and Landing Applications

hypersolve↗

NASA NTRS1993

Algorithmic trends in computational fluid dynamics; The Institute for Computer Applications in Science and Engineering (ICASE)/LaRC Workshop, NASA Langley Research Center, Hampton, VA, US, Sep. 15-17, 1991

The purpose here is to assess the state of the art in the areas of numerical analysis that are particularly relevant to computational fluid dynamics (CFD), to identify promising new developments in various areas of numerical analysis that will impact CFD, and to establish a long-term perspective focusing on opportunities and needs. Overviews are given of discretization schemes, computational fluid dynamics, algorithmic trends in CFD for aerospace flow field calculations, simulation of compressible viscous flow, and massively parallel computation. Also discussed are accerelation methods, spectral and high-order methods, multi-resolution and subcell resolution schemes, and inherently multidimensional schemes.

Hussaini, M. Y.↗

DOE OSTI2024

GX: a GPU-native gyrokinetic turbulence code for tokamak and stellarator design

GX is a code designed to solve the nonlinear gyrokinetic system for low-frequency turbulence in magnetized plasmas, particularly tokamaks and stellarators. In GX, our primary motivation and target is a fast gyrokinetic solver that can be used for fusion reactor design and optimization along with wide-ranging physics exploration. Here, this has led to several code and algorithm design decisions, specifically chosen to prioritize time to solution. First, we have used a discretization algorithm that is pseudospectral in the entire phase space, including a Laguerre–Hermite pseudospectral formulation of velocity space, which allows for smooth interpolation between coarse gyrofluid-like resolutions and finer conventional gyrokinetic resolutions and efficient evaluation of a model collision operator. Additionally, we have built GX to natively target graphics processors (GPUs), which are among the fastest computational platforms available today. Finally, we have taken advantage of the reactor-relevant limit of small $\rho _*$ by using the radially local flux-tube approach. In this paper we present details about the gyrokinetic system and the numerical algorithms used in GX to solve the system. We then present several numerical benchmarks against established gyrokinetic codes in both tokamak and stellarator magnetic geometries to verify that GX correctly simulates gyrokinetic turbulence in the small $\rho _*$. Moreover, we show that the convergence properties of the Laguerre–Hermite spectral velocity formulation are quite favourable for nonlinear problems of interest. Coupled with GPU acceleration, which we also investigate with scaling studies, this enables GX to be able to produce useful turbulence simulations in minutes on one (or a few) GPUs and higher fidelity results in a few hours using several GPUs. GX is open-source software that is ready for fusion reactor design studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1990

Tornadogenesis via squall line and supercell interaction revisited - The 15 November 1989 Huntsville tornado

A case study analyzing the environmental setting and storm system morphology that provides observational evidence of a mechanism involving the interaction of a gust front with a preexisting mesocyclone is presented. This case serves to reemphasize the existence of a high conditional probability of tornado occurrence, given the merger of a gust front (or storm outflow) with a moderate to strong thunderstorm ahead of it. The resultant data serve to illustrate some important unresolved issues relevant to the severe weather warning system that involve the present and planned local warning and network radars, and future algorithms that might intelligently integrate other data sources and models with the radar data.

Goodman, Steven J.↗

NASA NTRS2000

Obstacle Detection Algorithms for Aircraft Navigation: Performance Characterization of Obstacle Detection Algorithms for Aircraft Navigation

The research reported here is a part of NASA's Synthetic Vision System (SVS) project for the development of a High Speed Civil Transport Aircraft (HSCT). One of the components of the SVS is a module for detection of potential obstacles in the aircraft's flight path by analyzing the images captured by an on-board camera in real-time. Design of such a module includes the selection and characterization of robust, reliable, and fast techniques and their implementation for execution in real-time. This report describes the results of our research in realizing such a design. It is organized into three parts. Part I. Data modeling and camera characterization; Part II. Algorithms for detecting airborne obstacles; and Part III. Real time implementation of obstacle detection algorithms on the Datacube MaxPCI architecture. A list of publications resulting from this grant as well as a list of relevant publications resulting from prior NASA grants on this topic are presented.

Kasturi, Rangachar↗