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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Extending the Licklider Transmission Protocol to Multi-Band Links

Most deep space missions return data to Earth using links operating at a single frequency band. Indeed, their data requirements are low enough that bandwidth regulations do not constrain the system. In contrast, spacecraft such as Kepler or Europa Clipper are transitioning to a new operational paradigm where engineering and science data are transmitted through simultaneous links operating at different frequency bands (henceforth termed multi-band links). This ensures, for instance, that critical data is correctly received using a well characterized X-band link, while science data at a much larger data rate can be returned efficiently (both in terms of bandwidth and energy) through a Ka-band link.Having a spacecraft establish two simultaneous links with a ground station opens a large span of potential improvements for space communications and mission operations. In this paper, we consider the problem of running a Licklider Transmission Protocol (LTP) session over a multi-band link. LTP is an implementation of a selective Automatic Repeat reQuest (ARQ) protocol, i.e. it ensures correct delivery of data over an error prone link with potentially long propagation delays. To maximize its efficiency in deep space environments, LTP operates in deferred-ACK mode and is typically included as one of the core protocols in the Delay Tolerant Networking (DTN) suite.The contributions of this paper are as follows: First, we propose an extension to LTP for multi-band links (denoted MBLTP) and sketch how it can be implemented without modifying the current definition of LTP data units. Next, we develop bounds on the performance of MBLTP when transmitting a single data file over a multi-band link. Three metrics are considered, file expected delivery time, total energy spent and bundle jitter. The results of the analytic model are first benchmarked against simulations to ensure validity, and then compared against the performance of both traditional LTP and Parallel LTP (PLTP).We demonstrate that MBLTP can significantly reduce the latency and jitter with which data products are delivered to destination over a deep space link compared to LTP at moderate energy cost. Similarly, we also demonstrate that MBLTP outperforms PLTP in all considered metrics.

Sanchez Net, Marc↗
NASA NTRS1998

Weather Avoidance Using Route Optimization as a Decision Aid: An AWIN Topical Study

The aviation community is faced with reducing the fatal aircraft accident rate by 80 percent within 10 years. This must be achieved even with ever increasing, traffic and a changing National Airspace System. This is not just an altruistic goal, but a real necessity, if our growing level of commerce is to continue. Honeywell Technology Center's topical study, "Weather Avoidance Using Route Optimization as a Decision Aid", addresses these pressing needs. The goal of this program is to use route optimization and user interface technologies to develop a prototype decision aid for dispatchers and pilots. This decision aid will suggest possible diversions through single or multiple weather hazards and present weather information with a human-centered design. At the conclusion of the program, we will have a laptop prototype decision aid that will be used to demonstrate concepts to industry for integration into commercialized products for dispatchers and/or pilots. With weather a factor in 30% of aircraft accidents, our program will prevent accidents by strategically avoiding weather hazards in flight. By supplying more relevant weather information in a human-centered format along with the tools to generate flight plans around weather, aircraft exposure to weather hazards can be reduced. Our program directly addresses the NASA's five year investment areas of Strategic Weather Information and Weather Operations (simulation/hazard characterization and crew/dispatch/ATChazard monitoring, display, and decision support) (NASA Aeronautics Safety Investment Strategy: Weather Investment Recommendations, April 15, 1997). This program is comprised of two phases, Phase I concluded December 31, 1998. This first phase defined weather data requirements, lateral routing algorithms, an conceptual displays for a user-centered design. Phase II runs from January 1999 through September 1999. The second phase integrates vertical routing into the lateral optimizer and combines the user interface into a prototype software testbed. Phase II concludes with a dispatcher and pilot evaluation of the route optimizer decision aid. This document describes work completed in Phase I in contract with NASA Langley August 1998 - December 1998. This report includes: (1) Discuss how weather hazards were identified in partnership with experts, and how weather hazards were prioritized; (2) Static representations of display layouts for integrated planning function (3) Cost function for the 2D route optimizer; (4) Discussion of the method for obtaining, access to raw data of, and the results of the flight deck user information requirements definition; (5) Itemized display format requirements identified for representing weather hazards in a route planning aid.

Source record↗
DOE OSTI2022

DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials

Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as density functional theory (DFT) at the meta-GGA level and/or with exact exchange, quantum Monte Carlo, etc., generating a sufficient amount of data for training an ML potential has remained computationally challenging due to their high cost. In this work, we demonstrate that this issue can be largely alleviated with Deep Kohn–Sham (DeePKS), an ML-based DFT model. DeePKS employs a computationally efficient neural network-based functional model to construct a correction term added upon a cheap DFT model. Upon training, DeePKS offers closely matched energies and forces compared with high-level QM method, but the number of training data required is orders of magnitude less than that required for training a reliable ML potential. As such, DeePKS can serve as a bridge between expensive QM models and ML potentials: one can generate a decent amount of high-accuracy QM data to train a DeePKS model and then use the DeePKS model to label a much larger amount of configurations to train an ML potential. Further, this scheme for periodic systems is implemented in a DFT package ABACUS, which is open source and ready for use in various applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1988

NESSUS (Numerical Evaluation of Stochastic Structures Under Stress)/EXPERT: Bridging the gap between artificial intelligence and FORTRAN

The development of a probabilistic structural analysis methodology (PSAM) is described. In the near-term, the methodology will be applied to designing critical components of the next generation space shuttle main engine. In the long-term, PSAM will be applied very broadly, providing designers with a new technology for more effective design of structures whose character and performance are significantly affected by random variables. The software under development to implement the ideas developed in PSAM resembles, in many ways, conventional deterministic structural analysis code. However, several additional capabilities regarding the probabilistic analysis makes the input data requirements and the resulting output even more complex. As a result, an intelligent front- and back-end to the code is being developed to assist the design engineer in providing the input data in a correct and appropriate manner. The type of knowledge that this entails is, in general, heuristically-based, allowing the fairly well-understood technology of production rules to apply with little difficulty. However, the PSAM code, called NESSUS, is written in FORTRAN-77 and runs on a DEC VAX. Thus, the associated expert system, called NESSUS/EXPERT, must run on a DEC VAX as well, and integrate effectively and efficiently with the existing FORTRAN code. This paper discusses the process undergone to select a suitable tool, identify an appropriate division between the functions that should be performed in FORTRAN and those that should be performed by production rules, and how integration of the conventional and AI technologies was achieved.

Fink, Pamela K.↗
NASA NTRS1991

Identification of linear multivariable systems from a single set of data by identification of observers with assigned real eigenvalues

A formulation is presented for identification of linear multivariable from a single set of input-output data. The identification method is formulated with the mathematical framework of learning identifications, by extension of the repetition domain concept to include shifting time intervals. This method contrasts with existing learning approaches that require data from multiple experiments. In this method, the system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded real eigenvalue assignment procedure. Through this relationship, the Markov parameters of the observer are identified. The Markov parameters of the actual system are recovered from those of the observer, and then used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and numerical examples presented to illustrate.

Phan, Minh↗
NASA NTRS2002

The Overgrid Interface for Computational Simulations on Overset Grids

Computational simulations using overset grids typically involve multiple steps and a variety of software modules. A graphical interface called OVERGRID has been specially designed for such purposes. Data required and created by the different steps include geometry, grids, domain connectivity information and flow solver input parameters. The interface provides a unified environment for the visualization, processing, generation and diagnosis of such data. General modules are available for the manipulation of structured grids and unstructured surface triangulations. Modules more specific for the overset approach include surface curve generators, hyperbolic and algebraic surface grid generators, a hyperbolic volume grid generator, Cartesian box grid generators, and domain connectivity: pre-processing tools. An interface provides automatic selection and viewing of flow solver boundary conditions, and various other flow solver inputs. For problems involving multiple components in relative motion, a module is available to build the component/grid relationships and to prescribe and animate the dynamics of the different components.

Chan, William M.↗
DOE OSTI2021

Toward Guided Mutagenesis: Gaussian Process Regression Predicts MHC Class II Antigen Mutant Binding

Antigen-specific immunotherapies (ASI) require successful loading and presentation of antigen peptides into the major histocompatibility complex (MHC) binding cleft. One route of ASI design is to mutate native antigens for either stronger or weaker binding interaction to MHC. Exploring all possible mutations is costly both experimentally and computationally. To reduce experimental and computational expense, here we investigate the minimal amount of prior data required to accurately predict the relative binding affinity of point mutations for peptide-MHC class II (pMHCII) binding. Using data from different residue subsets, we interpolate pMHCII mutant binding affinities by Gaussian process (GP) regression of residue volume and hydrophobicity. We apply GP regression to an experimental data set from the Immune Epitope Database, and theoretical data sets from NetMHCIIpan and Free Energy Perturbation calculations. We find that GP regression can predict binding affinities of nine neutral residues from a six-residue subset with an average R 2 coefficient of determination value of 0.62 ± 0.04 (±95% CI), average error of 0.09 ± 0.01 kcal/mol (±95% CI), and with an receiver operating characteristic (ROC) AUC value of 0.92 for binary classification of enhanced or diminished binding affinity. Similarly, metrics increase to an R2 value of 0.69 ± 0.04, average error of 0.07 ± 0.01 kcal/mol, and an ROC AUC value of 0.94 for predicting seven neutral residues from an eight-residue subset. Our work finds that prediction is most accurate for neutral residues at anchor residue sites without register shift. This work holds relevance to predicting pMHCII binding and accelerating ASI design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

LLM-Based Adaptive Distribution Voltage Regulation Under Frequent Topology Changes: An In-Context MPC Framework

This paper proposes a large language model (LLM) based adaptive inverter control for distribution voltage regulation under frequent topology changes. We leverage the ability of the LLM to perform in-context learning and create a topology-adaptive surrogate model for power flow calculation. The surrogate model is then integrated with a long short-term memory-based load forecaster and a model predictive control (MPC) scheme to achieve the optimal inverter control that adapts to frequent topology changes. Unlike many existing works that assume fixed-topology grids or require the knowledge of all possible topologies when training a model, the proposed in-context MPC method tackles the distribution voltage control problem under various topologies and adapts to unknown topologies with limited data requirement for fine-tuning. The effectiveness of our method is demonstrated on a modified IEEE 123-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1984

Durability and damage tolerance of Large Composite Primary Aircraft Structure (LCPAS)

Analysis and testing addressing the key technology areas of durability and damage tolerance were completed for wing surface panels. The wing of a fuel-efficient, 200-passenger commercial transport airplane for 1990 delivery was sized using graphite-epoxy materials. Coupons of various layups used in the wing sizing were tested in tension, compression, and spectrum fatigue with typical fastener penetrations. The compression strength after barely visible impact damage was determined from coupon and structural element tests. One current material system and one toughened system were evaluated by coupon testing. The results of the coupon and element tests were used to design three distinctly different compression panels meeting the strength, stiffness, and damage-tolerance requirements of the upper wing panels. These three concepts were tested with various amounts of damage ranging from barely visible impact to through-penetration. The results of this program provide the key technology data required to assess the durability and damage-tolerance capability or advanced composites for use in commercial aircraft wing panel structure.

Mccarty, John E.↗
NASA NTRS1989

Context dependent prediction and category encoding for DPCM image compression

Efficient compression of image data requires the understanding of the noise characteristics of sensors as well as the redundancy expected in imagery. Herein, the techniques of Differential Pulse Code Modulation (DPCM) are reviewed and modified for information-preserving data compression. The modifications include: mapping from intensity to an equal variance space; context dependent one and two dimensional predictors; rationale for nonlinear DPCM encoding based upon an image quality model; context dependent variable length encoding of 2x2 data blocks; and feedback control for constant output rate systems. Examples are presented at compression rates between 1.3 and 2.8 bits per pixel. The need for larger block sizes, 2D context dependent predictors, and the hope for sub-bits-per-pixel compression which maintains spacial resolution (information preserving) are discussed.

Beaudet, Paul R.↗
NASA NTRS1993

Nonthermal processes around collapsed objects: High energy gamma ray sources in the radio sky

In our proposal responding to the initial Guest Observer NRA for the Compton Gamma Ray Observatory, 'Nonthermal Processes Around Collapsed Objects: High Energy Gamma Ray Sources in the Radio Sky', we stated that 'At high energies - the identity of the principal Galactic source population remains unknown' although the 'one certain source of high energy emission is young radio pulsars'. These two statements remain true, although at this writing, eighteen months after the beginning of the Compton allsky survey, much of the gamma-ray data required to greatly extend our knowledge of the Galaxy's high energy emission has been collected. The thrust of the program supported by our grant was to collect and analyze a complementary set of data on the Milky Way at radio wavelengths in order to help identify the dominant Pop 1 component of the Galaxy's gamma ray sources, and to pursue theoretical investigations on the origins and emission mechanisms of young pulsars, the one component of this population identified to date. We summarize here our accomplishments under the grant. In Section 2, we describe our VLA surveys of the Galactic Plane along with the current status of the radio source catalogs derived therefrom; unfortunately, owing to the TDRSS antenna problem and subsequent extension of the Sky Survey, we were not able to carry out a comparison with the EGRET data directly, although everything is now in place to do so as soon as it becomes available. In Section 2, we summarize our progress on the theoretical side, including the substantial completion of a dissertation on pulsar origins and work on the high energy emission mechanisms of isolated pulsars. We list the personnel supported by the grant in section 4 and provide a complete bibliography of publications supported in whole or in part by the grant in the final section.

Helfand, David J.↗
NASA NTRS2010

Simulation Modeling for Off-Nominal Conditions - Where Are We Today?

The modeling of aircraft flight characteris4cs in off-nominal or otherwise adverse conditions has become increasingly important for simulation in the loss-of-control arena. Adverse conditions include environmentally-induced upsets such as wind shear or wake vortex encounters; off-nominal flight conditions, such as stall or departure; on-board systems failures; and structural failures or aircraft damage. Spirited discussions in the research community are taking place as to the fidelity and data requirements for adequate representation of vehicle dynamics under such conditions for a host of research areas, including recovery training, flight controls development, trajectory guidance/planning, and envelope limiting. The increasing need for multiple sources of data (empirical, computational, experimental) for modeling across a larger flight envelope leads to challenges in developing methods of appropriately applying or combining such data, particularly in a dynamic flight environment with a physically and/or aerodynamically asymmetric vehicle. Traditional simplifications and symmetry assumptions in current modeling methodology may no longer be valid. Furthermore, once modeled, challenges abound in the validation of flight dynamics characteristics in adverse flight regimes

Shah, Gautam H.↗
DOE OSTI2022

Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.

42 ENGINEERING↗
NASA NTRS1976

Recent research related to prediction of stall/spin characteristics of fighter aircraft

The NASA Langley Research Center is currently engaged in a stall/spin research program to provide the fundamental information and design guidelines required to predict the stall/spin characteristics of fighter aircraft. The prediction methods under study include theoretical spin prediction techniques and piloted simulation studies. The paper discusses the overall status of theoretical techniques including: (1) input data requirements, (2) math model requirements, and (3) correlation between theoretical and experimental results. The Langley Differential Maneuvering Simulator (DMS) facility has been used to evaluate the spin susceptibility of several current fighters during typical air combat maneuvers and to develop and evaluate the effectiveness of automatic departure/spin prevention concepts. The evaluation procedure is described and some of the more significant results of the studies are presented.

Nguyen, L. T.↗
NASA NTRS1982

Research advances in satellite-aided crop forecasting

The underlying concept of the technology is to estimate crop area and yield for specified regions and to multiply the two to obtain production at the regional level. The treatment here is mainly of area estimation. The approach to non-U.S. crop forecasting does not require ground observations. Among the problems hampering development are the need to estimate crop areas much earlier in the season and the need for information extraction methods that reduce the quantity and quality of the data required.

Erickson, J.↗
NASA NTRSDate not supplied

Characterization of CO 4th Positive Radiation in CO2-Ar Mixtures

This paper presents measurements and simulations of CO 4th Positive spectra obtained in NASA Ames Research Center's Electric Arc Shock Tube (EAST) and CentraleSupelec's Plasma Torch. The experiments were aimed at measuring optically thin emission for the main band features of CO 4th Positive by using test gas mixtures of CO2 and Ar. By using mixtures of CO2 and Ar, the temperature of the flow (and consequently black-body curve) is increased compared to using pure CO2 (or CO2 / N2 mixtures). This temperature increase allows for emission spectroscopy of features that would nominally be black-body limited for conditions relevant to Mars entry. The CO 4th Positive system is the focus of this study as it accounts for a large percentage of the emitted radiation for Martian entry, and also due to the difficulties of obtaining experimental validation data due to the emission appearing in the Vacuum Ultraviolet (VUV) spectral range. The focus of this paper is to provide a comprehensive comparison between the EAST and plasma torch data along with various CO 4th Positive databases available in the literature. Previously reported VUV CO2 / N2 EAST data required a larger temperature than would be predicted based upon equilibrium shock relations. The need for the temperature increase implies that the EAST experiment did not fully equilibrate. Thus, it is presumed that the EAST data did not obtain an equilibrium condition. The plasma torch data, on the other hand, is very consistent with equilibrium assumptions. Thus, the equilibrium data obtained in the plasma torch is utilized to construct the CO 4th Positive emission model, which is then applied to the EAST data with a non-equilibrium interpretation.

A. M. Brandis↗
NASA NTRS1991

GLObal Backscatter Experiment (GLOBE) Pacific survey mission

NASA conducted the GLObal Backscatter Experiment (GLOBE) Survey Mission over the near coastal and remote Pacific Ocean during 6 to 30 Nov. 1989 (GLOBE 1) and 13 May to 5 Jun. 1990 (GLOBE 2). These missions studied the optical, physical, and chemical properties of atmospheric aerosols. Particular emphasis was given to the magnitude and spatial variability of aerosol backscatter coefficients at mid-infrared wavelengths, and to the remote middle and upper troposphere, where these aerosol properties are poorly understood. Survey instruments were selected to provide either direct beta measurements at the key wavelengths, empirical links with long term or global scale aerosol climatologies, or aerosol microphysics data required to model any of these quantities. The survey deployment included both long distance 6 to 8 hour transit flights and detailed 4 to 6 hour local flights. Several general features were observed from preliminary Survey data analyses. Validation and intercomparison results have shown good agreement, usually better than a factor of two. Atmospheric aerosols frequently exhibited a three layer vertical structure, with (1) high and fairly uniform backscatter in the shallow cloud capped marine boundary layer; (2) moderate and highly variable backscatter in a deeper overlaying cloud pumped layer; and (3) low, regionally uniform, but seasonally and latitudinally variable backscatter in the middle and upper troposphere. The survey missions represent two isolated snapshots of a small portion of the global aerosol system. Consequently, Survey results can best be understood by synthesizing them with the more comprehensive GLOBE data base, which is being compiled at NASA-Marshall.

Bowdle, David A.↗
DOE OSTI2023

Constraining neutrino oscillation and interaction parameters with the NOvA Near Detector and Far Detector data using Markov Chain Monte Carlo

This thesis reports a constraint of the neutrino oscillation parameters $\Delta m^{2}_{32}$, $\sin^2 \theta_{23}$, and $\delta_{CP}$ using the NuMI Off-Axis $\nu$ Appearance (NOvA) experiment's Near Detector (ND) data and Far Detector (FD) fake data set simultaneously. This thesis also reports a constraint on NOvA's systematic uncertainty model solely with its Near Detector data. The Hamiltonian Monte Carlo algorithm is used to estimate Bayesian Credible Intervals for the oscillation and interaction parameters. The $1\sigma$ Credible Intervals for $\sin^2 \theta_{23}$ are $(0.44, 0.512)$ $\cup$ $(0.536, 0.56)$, for $\Delta m^{2}_{32}$ $(2.41 \times 10^{-3}$ eV$^2,\ 2.52 \times 10^{-3}$ eV$^2)$, and for $\delta_{CP}$ $(0.74\pi,\ 1.1\pi)$ $\cup$ $(1.38\pi,\ 1.58\pi)$. The statistical power of the ND data constrains NOvA's interaction parameters, while the FD fake data constrains the oscillation parameters. This is the first analysis within NOvA to constrain the ND and FD prediction sim ultaneously, and to investigate the neutrino interaction modeling in the context of constraining the oscillation parameters. To constrain the ND data requires a sophisticated understanding of the neutrino interaction modeling and its uncertainties. The interested reader is advised to focus on Chapters 4 and 6, which discuss the ND selection, uncertainties, and ND-only fits to data. The reader interested in oscillation parameter constraints will find this in Chapter 7.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗