Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “range prediction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,801 records · Page 100
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Diffusion coefficients predicting facet-dependent crystallization in amorphous silicon nitride

Amorphous silicon nitride is a common material in microelectronics devices, which acts as an insulating barrier. Extended annealing times at elevated temperature can initiate crystallization of α-Si 3 ⁢ N 4 , which does not possess the same barrier properties. Molecular dynamics can resolve the fundamental mechanism for α-Si 3 ⁢N 4 crystallization and the influence of local environments. Here, we compare two interatomic potentials and conclude that these models predict structural features (e.g., angular distributions and densities) which span the range of experimental measurements. We confirmed these models reproduce experimental estimates of activation energy and leveraged these models to identify crystallization drivers. We conclude that near-T g , facet-dependent silicon nitride crystal growth rates can be predicted directly by either bulk or interfacial diffusion properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Wave Prediction using X-Band Radar (Final Summary Report)

Model Predictive Control (MPC) is the best controls framework available to wave energy today. It allows for the maximization of energy yield from a WEC system while respecting various constraints and losses in the system. This type of constrained optimization is a critical capability for the techno-economic optimization of WEC devices and is difficult to do effectively with causal controls frameworks. MPC requires a future prediction of wave excitation forces, requiring wave prediction on a future time horizon of up to 30 seconds. The future horizon required is highly dependent on the WEC and PTO type available. To our knowledge no-one has been able to implement MPC on a WEC device at sea, due to the fact that phase-resolved wave-prediction is not a capability that has been sufficiently developed to date. The key objectives of this project are focused on developing “industry-ready” wave prediction technology building blocks that can be applied to a wide range of different wave energy conversion topologies. Our collaborative work with device developers has demonstrated that the level of improvement attainable for any particular device is heavily dependent on the device and PTO topology chosen. The range of annual average power capture improvements is on the order of 10% to over 100%. However, the important aspect is that we can get within about 10% of theoretical upper limits even when considering errors in the wave prediction and more importantly, we can optimize performance while respecting various constraints such as motion amplitude or peak structural loads. The combination of improved performance while limiting structural loads has a net effect of reducing the levelized cost of energy from these emerging technologies and allows us to design control laws that meet an economic optimum. Efforts under a previous project on controls has focused on developing a set of wave-prediction algorithms that work by leveraging a network of wave sensing measurement buoys that are equipped with real-time telemetry. The present work is focusing primarily on using X-band radar to measure the wave-field around the WEC to predict the future excitation forces on the structure and combining the measurements of these different sources to create improvements in the wave-prediction accuracy.

16 TIDAL AND WAVE POWER↗
NASA NTRS1994

Prediction of particulate contamination on aperture window

This paper presents an analysis to predict the effects of light scattering by surface particles on the sensor window of a missile during ascent flight. The particulate contaminant distribution on the window is calculated by tallying the number of particles in a set of size ranges. The particulate contamination at the end of the mission is predicted by adding the contributions from the events of ground and flight operations. The surface particle redistributions caused by vibroacoustically induced surface acceleration was found to contribute the most of the particulate surface contamination. The analytical surface obscuration calculation with a set of particle counts was compared to the results of image analyzer measurement. The analytical results, which were calculated with a given function of particle shape depending on the size, were more conservative than the measurement. A scattering calculation using a verified BSDF model showed that the scattering was less than 0.001 at 20 off the direction of the incident light in the mid IR wavelength when the surfaces were at Level 300 initially.

Lee, Aleck L.↗
NASA NTRS1998

Flight Evaluation of Center-TRACON Automation System Trajectory Prediction Process

Two flight experiments (Phase 1 in October 1992 and Phase 2 in September 1994) were conducted to evaluate the accuracy of the Center-TRACON Automation System (CTAS) trajectory prediction process. The Transport Systems Research Vehicle (TSRV) Boeing 737 based at Langley Research Center flew 57 arrival trajectories that included cruise and descent segments; at the same time, descent clearance advisories from CTAS were followed. Actual trajectories of the airplane were compared with the trajectories predicted by the CTAS trajectory synthesis algorithms and airplane Flight Management System (FMS). Trajectory prediction accuracy was evaluated over several levels of cockpit automation that ranged from a conventional cockpit to performance-based FMS vertical navigation (VNAV). Error sources and their magnitudes were identified and measured from the flight data. The major source of error during these tests was found to be the predicted winds aloft used by CTAS. The most significant effect related to flight guidance was the cross-track and turn-overshoot errors associated with conventional VOR guidance. FMS lateral navigation (LNAV) guidance significantly reduced both the cross-track and turn-overshoot error. Pilot procedures and VNAV guidance were found to significantly reduce the vertical profile errors associated with atmospheric and airplane performance model errors.

Williams, David H.↗
NASA NTRSDate not supplied

CFD and Experimental Data Comparisons for Conventional and AFC-Enabled CRM High-Lift Configurations

Numerical simulations have been performed for a simplified high-lift (SHL) version of the Common Research Model (CRM) configuration, where the Fowler flaps of a representative conventional high-lift (CRM-HL) configuration are replaced by a set of simple hinged flaps. These hinged flaps are equipped with integrated modular active flow control (AFC) cartridges on the suction surface of the flap shoulder, and the resulting geometry is known as the CRM-SHL-AFC configuration. The main objective is to make use of AFC devices on the CRM-SHL-Configuration to produce the aerodynamic performance (lift) comparable to that of the CRM-HL configuration over a large angle of attack range encompassing maximum lift conditions. For comparison purposes, computations are also per-formed for the CRM-HL configuration. In the current paper, PowerFLOWR©, a CFD code based on the Lattice Boltzmann method (LBM), is used to simulate the entire flow field associated with the CRM-SHL-AFC configuration equipped with a combination of two different types of AFC actuators. The transonic version of the PowerFLOWR© code that has been validated for high-speed flows is used to simulate the flow field generated by the high-momentum actuators required to mitigate reversed flow regions on the suction surfaces of the main wing and the flap. This study is focused on the AFC systems and actuator arrangements that had emerged based on the parametric studies conducted previously at the nominal landing condition. Comparisons of the numerical solutions for lift and surface pressures are presented here with the experimental data, demonstrating the usefulness of CFD for predicting the flow field and lift characteristics of AFC-enabled high-lift configurations over a broad angle of attack range. The numerical solutions predict the expected trends in aerodynamic forces with angle of attack variation.

Veer N Vatsa↗
NASA NTRS1999

Flight-Determined, Subsonic, Lateral-Directional Stability and Control Derivatives of the Thrust-Vectoring F-18 High Angle of Attack Research Vehicle (HARV), and Comparisons to the Basic F-18 and Predicted Derivatives

The subsonic, lateral-directional, stability and control derivatives of the thrust-vectoring F-1 8 High Angle of Attack Research Vehicle (HARV) are extracted from flight data using a maximum likelihood parameter identification technique. State noise is accounted for in the identification formulation and is used to model the uncommanded forcing functions caused by unsteady aerodynamics. Preprogrammed maneuvers provided independent control surface inputs, eliminating problems of identifiability related to correlations between the aircraft controls and states. The HARV derivatives are plotted as functions of angles of attack between 10deg and 70deg and compared to flight estimates from the basic F-18 aircraft and to predictions from ground and wind tunnel tests. Unlike maneuvers of the basic F-18 aircraft, the HARV maneuvers were very precise and repeatable, resulting in tightly clustered estimates with small uncertainty levels. Significant differences were found between flight and prediction; however, some of these differences may be attributed to differences in the range of sideslip or input amplitude over which a given derivative was evaluated, and to differences between the HARV external configuration and that of the basic F-18 aircraft, upon which most of the prediction was based. Some HARV derivative fairings have been adjusted using basic F-18 derivatives (with low uncertainties) to help account for differences in variable ranges and the lack of HARV maneuvers at certain angles of attack.

Iliff, Kenneth W.↗
DOE OSTI2021

Overview of symmetric nuclear matter properties from chiral interactions up to fourth order of the chiral expansion

We present and discuss predictions for a cross section of bulk and single-particle properties in symmetric nuclear matter based on recent high-quality nucleon-nucleon potentials at N 3 LO and including all subleading three-nucleon forces. We begin with the equation of state and its saturation properties and proceed to the single-nucleon potential. We also explore short-range correlations as seen through the defect function. The various predictions which we present have a common foundation in an internally consistent ab initio approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1991

Velocity measurements in a turbulent trailing vortex and their application to BWI noise prediction

The objectives were to observe the turbulence structure and spectral characteristics of the trailing vortex shed by a rectangular NACA 0012 wing over a range of conditions and to incorporate these observations into the blade-wake interaction (BWI) noise-prediction method of Glegg (1989). The following sections are presented: (1) measurements performed during the first year of this two year investigation; (2) presentation and discussion of a representative sample of the results; (3) implications for the BWI noise prediction method; and (4) re-evaluation of work planned for the second year.

Devenport, William J.↗
DOE OSTI2022

Elucidation of the physical factors that control activated transport of penetrants in chemically complex glass-forming liquids

Understanding the activated transport of penetrant or tracer atoms and molecules in condensed phases is a challenging problem in chemistry, materials science, physics, and biophysics. Many angstrom- and nanometer-scale features enter due to the highly variable shape, size, interaction, and conformational flexibility of the penetrant and matrix species, leading to a dramatic diversity of penetrant dynamics. Based on a minimalist model of a spherical penetrant in equilibrated dense matrices of hard spheres, a recent microscopic theory that relates hopping transport to local structure has predicted a novel correlation between penetrant diffusivity and the matrix thermodynamic dimensionless compressibility, S 0 ( T ) (which also quantifies the amplitude of long wavelength density fluctuations), as a consequence of a fundamental statistical mechanical relationship between structure and thermodynamics. Moreover, the penetrant activation barrier is predicted to have a factorized/multiplicative form, scaling as the product of an inverse power law of S 0 ( T ) and a linear/logarithmic function of the penetrant-to-matrix size ratio. This implies an enormous reduction in chemical complexity that is verified based solely on experimental data for diverse classes of chemically complex penetrants dissolved in molecular and polymeric liquids over a wide range of temperatures down to the kinetic glass transition. The predicted corollary that the penetrant diffusion constant decreases exponentially with inverse temperature raised to an exponent determined solely by how S 0 ( T ) decreases with cooling is also verified experimentally. Our findings are relevant to fundamental questions in glassy dynamics, self-averaging of angstrom-scale chemical features, and applications such as membrane separations, barrier coatings, drug delivery, and self-healing.

Science & Technology - Other Topics↗
DOE OSTI2025

Estimating soybean yields from high-temporal-resolution multi-source data using deep learning

Accurate and timely crop yield prediction is crucial for ensuring food security and maintaining stable agricultural markets. In recent years, there has been a surge in interest in leveraging high-temporal-resolution, multi-source data for effective crop growth monitoring and yield estimation. A notable challenge arises from the difficulty in capturing the intricate interactions between variables across different time steps within these high-temporal-resolution time series datasets. This complexity hinders the reliable extraction of yield information from voluminous and often noisy datasets, especially during periods of extreme weather events. Here, in this study, we propose an Attention and Graph Isomorphism Network-enhanced Bi-directional Long Short-Term Memory network (AGB-LSTM) for estimating county-level soybean yield in the United States. This model integrates a diverse set of remote sensing data, including Near-Infrared Reflectance of Vegetation (NIRv), Sun-Induced chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP), along with environmental covariates. The AGB-LSTM effectively leverages information related to crop yield from high-temporal-resolution time series data (5-days), achieving an accuracy of R²= 0.67 and rRMSE = 14.46%. This approach significantly outperforms traditional machine learning methods such as Random Forest (RF) (R²= 0.52, rRMSE = 17.36%) and Bi-LSTM (R²= 0.58, rRMSE = 16.17%). Sensitivity experiments with different time steps and ranges demonstrated that our model could accurately and stably predict yields 1 to 2 months before harvest. Moreover, data with a finer temporal resolution consistently improved prediction performance, resulting in an approximately 20% increase in and an approximately 20% decrease in rRMSE compared to using monthly composites. We also evaluated the robustness of the model under extreme climate events and observed strong performance (R²= 0.50, rRMSE = 21.32%). Finally, yield mapping for major soybean-producing regions in North America in 2023 revealed spatial patterns that closely matched USDA yield reports. Our findings suggest that the AGB-LSTM model is a promising and effective method for estimating yield and has notable potential for global crop yield forecasting.

Deep learning↗
DOE OSTI2021

Machine learning-enabled prediction of chemical durability of A 2 B 2 O 7 pyrochlore and fluorite

Pyrochlore-structure type and its derivative in a general formula A 2 B 2 O 7 (A = rare earth elements and actinides; B = Ti, Sn, Zr, Hf, Pb, Si, etc.) display excellent structural flexibility and rich crystal chemistry as promising nuclear waste form materials capable of immobilizing actinides and fission products. It is essential to understand these materials’ chemical durability and element release of radionuclides in order to evaluate their performance in near-field environment. However, it is a formidable grand technological challenge to experimentally perform durability testing across hundreds of thousands of possibilities resulting from their extreme compositional complexities due to cation substitutions at both A and B-sites. In this work, we demonstrate a machine learning approach to determine the key materials parameters and structural characteristics governing the leaching behaviors from a small set of selected compositions as model systems, enabling a science-based prediction of their chemical durability that can be extended to a wide range of chemical compositions. The combination of four key structural characteristics and materials parameters, including ionic radius size difference , ionic potential difference , electronegativity difference , and lattice parameter , creates features an optimized prediction of the chemical durability. Two machine learning models, linear regression and Kernel ridge regression models, are trained on the randomly-split training dataset derived from the experimentally-determined elemental release rates, and subsequently tested on the testing dataset. The predicted leaching rates from both machine learning models show an excellent agreement with the experimental data, demonstrating the feasibility of rapidly evaluating the material properties of new compositions. These results highlight the immense potential of synergizing informatics through machine learning-based models and well-controlled experiments of selected model systems to accelerate materials design and discovery with optimized compositions and performance of promising materials for effective nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1951

Comparison of measured efficiencies of nine turbine designs with efficiencies predicted by two empirical methods

Empirical methods of Ainley and Kochendorfer and Nettles were used to predict performances of nine turbine designs. Measured and predicted performances were compared. Appropriate values of blade-loss parameter were determined for the method of Kochendorfer and Nettles. The measured design-point efficiencies were lower than predicted by as much as 0.09 (Ainley and 0.07 (Kochendorfer and Nettles). For the method of Kochendorfer and Nettles, appropriate values of blade-loss parameter ranged from 0.63 to 0.87 and the off-design performance was accurately predicted.

FLOW-TURBINES↗
NASA NTRS1980

Fabrication of AlGaAs/GaAs cascade solar cell by LPE

Stacking two or more photovoltaic junctions in electrical and optical series results in higher conversion efficiency since each junction can be tailored to respond more efficiently to a smaller range of photon energies. An efficiency of about 30 percent was predicted for a two junction cascade cell having the optimum bandgap values. A number of III-V materials systems were considered for use in fabricating cascade solar cells. The Al-Ga-As system is attractive from a developmental standpoint since it employs a proven materials system that is closely lattice matched throughout its compositional range. This system employs a GaAs low bandgap cell and 1.9 eV AlGaAs high bandgap cell connected by an AlGaAs tunnel junction. Although this cell does not possess the optimum bandgap values, an efficiency of 25 percent was predicted at 300 K under AMO, 1 sun illumination.

Bedair, S. M.↗
NASA NTRS1987

A model for fully developed turbulence

A model for stationary, fully developed turbulence is presented in which the turbulent spectral energy function is completely determined once the time scale for the energy fed into the eddy interaction is known. The form of the eddy correlation time scale determining the turbulent viscosity is suggested by the basic equation of the model itself, up to a dimensionless constant that is fixed by demanding that the coefficient of the spectrum in the Heisenberg-Kolmogoroff inertial range of wavenunmbers be the experimental value. The model makes quantitative predictions that are compared with data on turbulent convection; the k-epsilon and Smagorinsky relations; the spectral function, transfer term, and dissipation term; the skewness factor; the Kolmogoroff and Batchelor constants; and the inertial-conductive and inertial-convective ranges.

Canuto, V. M.↗
NASA NTRS1975

Observations and theory of Mg II lines in early type stars. II - Theory and predicted profiles. III - The observations and a comparison with the predictions

Profiles of the UV Mg II lines in the spectra of early type stars are computed in a grid of model atmospheres with effective temperatures between 8000 and 35,000 K and log g values of 2.5 to 4.0 using the LTE and non-LTE theories of line formation. The theoretical results indicate that the line cores are strengthened by non-LTE effects over the entire temperature range, resonance-line wings are weaker in the cooler models than in the LTE case, and very large deviations from LTE occur in the hot low-gravity models. These predictions are compared with the equivalent widths of the UV Mg II lines in 106 stars and of the visual lines in 48 stars (spectral types O4 to A3). The observed equivalent widths of normal stars in luminosity classes II through V are found to agree with the predictions over the entire range from O8 to A2 if a certain Mg/H abundance is adopted. The line intensities observed in supergiants, Be, Bp, and Ap stars are discussed.

Snijders, M. A. J.↗
NASA NTRS2008

Processing LiDAR Data to Predict Natural Hazards

ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.

Fairweather, Ian↗
NASA NTRS1989

Performance and acoustic prediction of counterrotating propeller configurations

The Davidson (1981) numerical method is used to predict the performance of a counterrotating propeller configuration over a range of different front and back disk rotation speeds with constant-speed propellers; this has yielded such overall performance parameters as integrated thrust, torque, and power, as well as the radial variation of blade torque and thrust. Since the unsteady component of the noise from a counterrotating propeller configuration is minimal in the plane of the propeller disk, this approach is restricted to noise-level predictions for observer locations in this region.

Denner, B. W.↗
NASA NTRS1999

Flight Test Results: CTAS Cruise/Descent Trajectory Prediction Accuracy for En route ATC Advisories

The Center/TRACON Automation System (CTAS), under development at NASA Ames Research Center, is designed to assist controllers with the management and control of air traffic transitioning to/from congested airspace. This paper focuses on the transition from the en route environment, to high-density terminal airspace, under a time-based arrival-metering constraint. Two flight tests were conducted at the Denver Air Route Traffic Control Center (ARTCC) to study trajectory-prediction accuracy, the key to accurate Decision Support Tool advisories such as conflict detection/resolution and fuel-efficient metering conformance. In collaboration with NASA Langley Research Center, these test were part of an overall effort to research systems and procedures for the integration of CTAS and flight management systems (FMS). The Langley Transport Systems Research Vehicle Boeing 737 airplane flew a combined total of 58 cruise-arrival trajectory runs while following CTAS clearance advisories. Actual trajectories of the airplane were compared to CTAS and FMS predictions to measure trajectory-prediction accuracy and identify the primary sources of error for both. The research airplane was used to evaluate several levels of cockpit automation ranging from conventional avionics to a performance-based vertical navigation (VNAV) FMS. Trajectory prediction accuracy was analyzed with respect to both ARTCC radar tracking and GPS-based aircraft measurements. This paper presents detailed results describing the trajectory accuracy and error sources. Although differences were found in both accuracy and error sources, CTAS accuracy was comparable to the FMS in terms of both meter-fix arrival-time performance (in support of metering) and 4D-trajectory prediction (key to conflict prediction). Overall arrival time errors (mean plus standard deviation) were measured to be approximately 24 seconds during the first flight test (23 runs) and 15 seconds during the second flight test (25 runs). The major source of error during these tests was found to be the predicted winds aloft used by CTAS. Position and velocity estimates of the airplane provided to CTAS by the ATC Host radar tracker were found to be a relatively insignificant error source for the trajectory conditions evaluated. Airplane performance modeling errors within CTAS were found to not significantly affect arrival time errors when the constrained descent procedures were used. The most significant effect related to the flight guidance was observed to be the cross-track and turn-overshoot errors associated with conventional VOR guidance. Lateral navigation (LNAV) guidance significantly reduced both the cross-track and turn-overshoot error. Pilot procedures and VNAV guidance were found to significantly reduce the vertical profile errors associated with atmospheric and aircraft performance model errors.

Green, S.↗

Refine your search to explore more results.