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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 NTRS2024

Intrastep, Stage-Value Predictors for Diagonally-Implicit Runge-Kutta Methods

To better identify the necessary attributes of good stage-value predictors (SVPs), numerous SVPs are designed for an existing: ESDIRK4(3)7L[2]SA [26] and a new: ESDIRK4(3)8L[2]SA scheme.1 Both are stifflyaccurate, stage-order two, explicit, singly-diagonally implicit Runge–Kutta (ESDIRK) schemes. Tradeoffs are studied in the parameter spaces enforcing the constraints on accuracy, linear stability, nonlinear stability and coefficient size to determine which objectives correlate with effective predictors. The SVPs are tested on three challenging external aerodynamics problems [107 − 108 degrees of freedom (DoFs)], each with a different level of stiffness. The problems include two 3D airfoils simulations and one canonical turbulence simulation. All simulations use the compressible Navier-Stokes equations (CNSE). An entropy stable spectral collocation formulation is used for discretizing the spatial terms in the equations. Simulations are performed at a wide variety of temporal error tolerances. Problems that are sufficiently stiff (e.g., lax temporal error tolerances) benefit from SVPs designed with second-order accuracy and stability properties: A-stability, and L-stability, rather than high accuracy constraints. Simulations with modest stiffness (e.g., strict error tolerances) are better suited for SVPs designed using high accuracy constraints. Designing SVPs with enhanced stability properties is tedious but worthwhile. Simulation times are reduced with optimal SVPs by as much as 100% on some stages, with combined stepwise improvements of between 50 − 100% for both methods. A comparative study is performed with the two aforementioned methods as well as four other ESDIRKs. The newly designed ESDIRK4(3)8L[2]SA with γ ≈ 1/10, proves to be the most efficient of the six tested ESDIRK schemes simulating the CNSE.

Diagonally-Implicit Runge-Kutta↗

DOE OSTI2026

Personal and environmental predictors of polycyclic aromatic hydrocarbon exposure identified through repeated silicone wristband sampling

This study integrates quantitative data on personal exposure to polycyclic aromatic hydrocarbons (PAHs) in 162 silicone wristbands with demographics, behavioral information, and housing characteristics to explore contributions to residential exposure in a superfund-adjacent community over the course of a year. Forty-six residents completed questionnaires and wore silicone wristbands as personal passive samplers for seven consecutive days on up to four separate occasions in alternating months between November 2022 and June 2023. It was hypothesized that individual behaviors and housing characteristics are sources of dependence and correlation between personal PAH exposures. 50 PAHs were detected at least once, 17 of which were alkylated PAHs. Exposure to PAHs of similar molecular weight was often correlated, notably between naphthalenes (2-rings) and higher molecular weight PAHs (3 or more rings). Generalized linear mixed models identified flooring type, participant age, and sampling month as important predictors of increased PAH exposure, and flooring type, and use of wood stoves or heavy machinery as predictors of increased naphthalene exposure relative to higher molecular weight PAHs. Individual chemical models based on concentration data and detection frequencies corroborated these findings across multiple PAHs. We demonstrate that personal exposure is not static and the degree of variability in personal exposure is individual. Hence, identification of influential exposure factors through repeated measures of chemical exposure and characterization of variability in personal exposure as performed in this study, is important in the development of exposure mitigation strategies.

Bonner, Emily↗

DOE OSTI2026

Hierarchical-embedding autoencoder with a predictor as efficient architecture for learning time-evolution in multi-scale turbulent flows

We introduce a scale-aware, data-driven deep learning modeling framework for accurately predicting the time evolution of multi-scale turbulent plasma and liquid flows. The approach is motivated by the idea of scale separation. Structures of vastly different length scales emerge in these systems, and interactions between these structures occur only locally. To exploit this structure, the flow state is transformed by a hierarchical, fully convolutional autoencoder, not into a single embedding layer as in conventional convolutional surrogate models, but into a series of embedding layers. A stepwise training strategy ensures that fine-scale features are encoded on a high-resolution grid, while larger structures are represented on progressively coarser layers. The time evolution predictor advances all embedding layers in sync, capturing local interactions between features at the same scale as well as between all scales. This approach enables efficient modeling of multi-scale systems since negligible interactions between distant, small-scale structures do not need to be directly modeled. Our hierarchical-embedding autoencoder with a predictor framework is evaluated on canonical examples of multi-scale turbulence: two-dimensional Kolmogorov flow and Hasegawa–Wakatani plasma turbulence. In both cases, the proposed framework significantly improves predictive accuracy relative to conventional convolutional network architectures. A significant improvement in prediction accuracy was observed for crucial statistical characteristics of the Hasegawa–Wakatani plasma as well as for individual trajectories of the Kolmogorov flow turbulence. Importantly, the model's rollout for the Hasegawa–Wakatani problem demonstrates a four-order-of-magnitude speedup compared to traditional numerical solvers.

Khrabry, Alexander I. [Princeton Univ., NJ (United↗

NASA NTRS1978

Analysis of a VTOL hover task with predictor displays using an optimal control model of the human operator

The influence of different types of predictor displays in a longitudinal VTOL hover task is analyzed in a theoretical study. It was assumed that pitch angle and position are presented to the pilot in separate displays namely the artificial horizon and position display. The predictive information is calculated by means of a Taylor series. From earlier experimental studies it is well known that predictor displays improve human and system performance and result in reducing human workload. In this study, an optimal control model is used to prove this effect theoretically. Several cases with differing amounts of predictive and rate information are compared.

Johannsen, G.↗

NASA NTRS1979

An analysis of the human as a predictor model

A hybrid sampled data-continuous impulse response of a preview tracker using a fast time model predictor aid is derived. The model can accept transient and nontransient imputs and is suitable for studying a human preview tracker using an internalized or externalized predictor display. The model is shown to behave reasonably in a simple example and its implications for modeling studies are discussed.

Kreifeldt, J. G.↗

NASA NTRS1986

An estimator-predictor approach to PLL loop filter design

An approach to the design of digital phase locked loops (DPLLs), using estimation theory concepts in the selection of a loop filter, is presented. The key concept is that the DPLL closed-loop transfer function is decomposed into an estimator and a predictor. The estimator provides recursive estimates of phase, frequency, and higher order derivatives, while the predictor compensates for the transport lag inherent in the loop. This decomposition results in a straightforward loop filter design procedure, enabling use of techniques from optimal and sub-optimal estimation theory. A design example for a particular choice of estimator is presented, followed by analysis of the associated bandwidth, gain margin, and steady state errors caused by unmodeled dynamics. This approach is under consideration for the design of the Deep Space Network (DSN) Advanced Receiver Carrier DPLL.

Statman, J. I.↗

NASA NTRSDate not supplied

Satellite orbit predictor

An analog aid to determine satellite coverage of Emergency Locator Transmitters Emergency Position Indicating Radio Beacon (ELT/EPIRB) distress incidence is discussed. The satellite orbit predictor is a graphical aid for determining the relationship between the satellite orbit, antenna coverage of the spacecraft and coverage of the Local User Terminal. The predictor allows the user to quickly visualize if a selected position will probably be detected and is composed of a base map and a satellite track overlay for each satellite.A table of equator crossings for each satellite is included.

Friedman, Morton l.↗

NASA NTRS1984

COSPAS-SARSAT Satellite Orbit Predictor. Volume 3

The satellite orbit predictor is a graphical aid for determining the relationship between the satellite (SARSAT or COSPAS) orbit, antenna coverage of the spacecraft and coverage of the LUTs. The predictor allows the user to quickly visualize if a selected position will probably be detected and is composed of a base map and a satellite track overlay for each satellite. Additionally, a table of equator crossings for each satellite is included.

Friedman, Morton L.↗

NASA NTRS1984

COSPAS-SARSAT Satellite Orbit Predictor, Vol 4

Friedman, Morton L.↗

NASA NTRS1983

Software development predictors, error analysis, reliability models and software metric analysis

The use of dynamic characteristics as predictors for software development was studied. It was found that there are some significant factors that could be useful as predictors. From a study on software errors and complexity, it was shown that meaningful results can be obtained which allow insight into software traits and the environment in which it is developed. Reliability models were studied. The research included the field of program testing because the validity of some reliability models depends on the answers to some unanswered questions about testing. In studying software metrics, data collected from seven software engineering laboratory (FORTRAN) projects were examined and three effort reporting accuracy checks were applied to demonstrate the need to validate a data base. Results are discussed.

Basili, Victor↗

NASA NTRS1987

COSPAS-SARSAT Satellite Orbit Predictor Volume 10

The satellite orbit predictor is a graphical aid for determining the relationship between the satellite (SARSAT or COSPAS) orbit, antenna coverage of the spacecraft and coverage of the Local User Terminals. The predictor allows the user to quickly visualize if a selected position will be detected and is composed of a base map and satellite track overlay for each satellite. A table of equator crossings for each satellite is included.

Friedman, Morton L.↗

NASA NTRS1988

Digital phase-lock loop having an estimator and predictor of error

A digital phase-lock loop (DPLL) which generates a signal with a phase that approximates the phase of a received signal with a linear estimator. The effect of a complication associated with non-zero transport delays related to DPLL mechanization is then compensated by a predictor. The estimator provides recursive estimates of phase, frequency, and higher order derivatives, while the predictor compensates for transport lag inherent in the loop.

Statman, Joseph I.↗

NASA NTRS1988

A fourth generation reliability predictor

A reliability/availability predictor computer program has been developed and is currently being beta-tested by over 30 US companies. The computer program is called the Hybrid Automated Reliability Predictor (HARP). HARP was developed to fill an important gap in reliability assessment capabilities. This gap was manifested through the use of its third-generation cousin, the Computer-Aided Reliability Estimation (CARE III) program, over a six-year development period and an additional three-year period during which CARE III has been in the public domain. The accumulated experience of the over 30 establishments now using CARE III was used in the development of the HARP program.

Bavuso, Salvatore J.↗

NASA NTRS1990

An estimator-predictor approach to PLL loop filter design

The design of digital phase locked loops (DPLL) using estimation theory concepts in the selection of a loop filter is presented. The key concept, that the DPLL closed-loop transfer function is decomposed into an estimator and a predictor, is discussed. The estimator provides recursive estimates of phase, frequency, and higher-order derivatives, and the predictor compensates for the transport lag inherent in the loop.

Statman, Joseph I.↗

NASA NTRS1993

The piecewise-linear predictor-corrector code - A Lagrangian-remap method for astrophysical flows

We describe a time-explicit finite-difference algorithm for solving the nonlinear fluid equations. The method is similar to existing Eulerian schemes in its use of operator-splitting and artificial viscosity, except that we solve the Lagrangian equations of motion with a predictor-corrector and then remap onto a fixed Eulerian grid. The remap is formulated to eliminate errors associated with coordinate singularities, with a general prescription for remaps of arbitrary order. We perform a comprehensive series of tests on standard problems. Self-convergence tests show that the code has a second-order rate of convergence in smooth, two-dimensional flow, with pressure forces, gravity, and curvilinear geometry included. While not as accurate on idealized problems as high-order Riemann-solving schemes, the predictor-corrector Lagrangian-remap code has great flexibility for application to a variety of astrophysical problems.

Lufkin, Eric A.↗

NASA NTRS1994

HiRel: Hybrid Automated Reliability Predictor (HARP) integrated reliability tool system, (version 7.0). Volume 2: HARP tutorial

The Hybrid Automated Reliability Predictor (HARP) integrated Reliability (HiRel) tool system for reliability/availability prediction offers a toolbox of integrated reliability/availability programs that can be used to customize the user's application in a workstation or nonworkstation environment. The Hybrid Automated Reliability Predictor (HARP) tutorial provides insight into HARP modeling techniques and the interactive textual prompting input language via a step-by-step explanation and demonstration of HARP's fault occurrence/repair model and the fault/error handling models. Example applications are worked in their entirety and the HARP tabular output data are presented for each. Simple models are presented at first with each succeeding example demonstrating greater modeling power and complexity. This document is not intended to present the theoretical and mathematical basis for HARP.

Rothmann, Elizabeth↗

NASA NTRS1998

Numerical Roll Reversal Predictor Corrector Aerocapture and Precision Landing Guidance Algorithms for the Mars Surveyor Program 2001 Missions

This paper describes the development and evaluation of a numerical roll reversal predictor-corrector guidance algorithm for the atmospheric flight portion of the Mars Surveyor Program 2001 Orbiter and Lander missions. The Lander mission utilizes direct entry and has a demanding requirement to deploy its parachute within 10 km of the target deployment point. The Orbiter mission utilizes aerocapture to achieve a precise captured orbit with a single atmospheric pass. Detailed descriptions of these predictor-corrector algorithms are given. Also, results of three and six degree-of-freedom Monte Carlo simulations which include navigation, aerodynamics, mass properties and atmospheric density uncertainties are presented.

Powell, Richard W.↗

NASA NTRS1997

Electrical alternans during rest and exercise as predictors of vulnerability to ventricular arrhythmias

This investigation was performed to evaluate the feasibility of detecting repolarization alternans with the heart rate elevated with a bicycle exercise protocol. Sensitive spectral signal-processing techniques are able to detect beat-to-beat alternation of the amplitude of the T wave, which is not visible on standard electrocardiogram. Previous animal and human investigations using atrial or ventricular pacing have demonstrated that T-wave alternans is a marker of vulnerability to ventricular arrhythmias. Using a spectral analysis technique incorporating noise reduction signal-processing software, we evaluated electrical alternans at rest and with the heart rate elevated during a bicycle exercise protocol. In this study we defined optimal criteria for electrical alternans to separate patients from those without inducible arrhythmias. Alternans and signal-averaged electrocardiographic results were compared with the results of vulnerability to ventricular arrhythmias as defined by induction of sustained ventricular tachycardia or fibrillation at electrophysiologic evaluation. In 27 patients alternans recorded at rest and with exercise had a sensitivity of 89%, specificity of 75%, and overall clinical accuracy of 80% (p <0.003). In this patient population the signal-averaged electrocardiogram was not a significant predictor of arrhythmia vulnerability. This is the first study to report that repolarization alternans can be detected with heart rate elevated with a bicycle exercise protocol. Alternans measured using this technique is an accurate predictor of arrhythmia inducibility.

Clinical Trial↗