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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.

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At least 1,315 records · Page 73

All sources NASA NTRS DOE OSTI

NASA NTRS1999

Overview of the NASA Wallops Flight Facility Mobile Range Control System

The NASA GSFC's Wallops Flight Facility (WFF) Mobile Range Control System (MRCS) is based on the functionality of the WFF Range Control Center at Wallops Island, Virginia. The MRCS provides real time instantaneous impact predictions, real time flight performance data, and other critical information needed by mission and range safety personnel in support of range operations at remote launch sites. The MRCS integrates a PC telemetry processing system (TELPro), a PC radar processing system (PCDQS), multiple Silicon Graphics display workstations (IRIS), and communication links within a mobile van for worldwide support of orbital, suborbital, and aircraft missions. This paper describes the MRCS configuration; the TELPro's capability to provide single/dual telemetry tracking and vehicle state data processing; the PCDQS' capability to provide real time positional data and instantaneous impact prediction for up to 8 data sources; and the IRIS' user interface for setup/display options. With portability, PC-based data processing, high resolution graphics, and flexible multiple source support, the MRCS system is proving to be responsive to the ever-changing needs of a variety of increasingly complex missions.

Davis, Rodney A.↗

DOE OSTI2021

Investigating the relationship between radial pre-stress magnitude and ballistic projectile dwell in heavy confined ceramic targets

A series of bare silicon carbide ceramic armour disks were manufactured with high-strength steel containment to induce varying magnitudes of radial pre-stress. The induced radial stresses, ranging from 0 to 900 MPa, were measured via neutron diffraction and verified by comparison with numerical calculations. Four targets of each configuration, referred to as slip-fit, moderate pre-stress, and high pre-stress, were subject to ballistic testing with hemispherical-nose, tungsten heavy alloy long rod projectiles to determine the interface defeat transition velocity. In-situ diagnostics were unsuccessful in aiding the identification of interface defeat, necessitating a reliance on post-mortem assessment. A transition velocity of approx. 1000 m/s was identified for the unstressed target, increasing to approx. 1200 m/s for the pre-stressed configurations. No performance effect was discernible between the moderate (372 MPa) and high (899 MPa) pre-stress configurations, suggesting that an optimal performance may be achieved for lower pre-stress levels (i.e., <372 MPa). Additionally, the test results were compared with four semi-analytical predictions of interface defeat performance and good agreement was found, albeit with significant range in the model predictions.

42 ENGINEERING↗

DOE OSTI2025

Predicting the viscoplastic response of a crystallizing fluoropolymer using transient network theory

We employ a molecular theory of dynamic polymer networks to describe the viscoplastic response of rubbery FK-800, a thermoplastic copolymer of chlorotrifluoroethylene and vinylidene fluoride, over a broad range of thermal histories. The kinetics of crystallization at different annealing temperatures was modeled using a modified Avrami equation, whose parameters were found to evolve through simple relationships over the full temperature range of the rubbery state. By fitting experimental compression data, we discovered predictable trends for the physical parameters in our mechanical model over its full range of crystallinities (up to ≈20%) and provided insights based on molecular-level physics to justify them. Using this, an end-to-end model was developed to predict the yielding and post-yield behavior of rubbery FK-800 for arbitrary thermal histories. The model successfully predicted the highly nonlinear evolution of characteristic mechanical signatures (stiffness, yield point, post-yield drop) throughout the crystallization process. A statistical analysis of variance test was employed to determine that the measured variations in the mechanical behavior of rubbery FK-800 are primarily dictated by its fractional crystallinity, regardless of its exact thermal history.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Predicting fatal heat and humidity using the heat index model

A unique wet-bulb temperature of 35°C is often used as the threshold for human survivability, but recent experiments have shown that a person’s core temperature starts to rise at a wide range of critical wet-bulb temperatures. Here, it is shown that the model underlying the heat index correctly predicts those critical wet-bulb temperatures, explaining 95% of the variance in the values observed in laboratory heat-stress experiments. This is the first time the heat-index model has been validated against physiological data from laboratory experiments. For light and moderate exertion in an indoor setting, the heat index model predicts that the critical wet-bulb temperature ranges from 20 to 32°C, depending on the relative humidity, consistent with experimental results. Furthermore, for the same setting and exertion, the heat index model predicts fatal wet-bulb temperatures ranging from 24 to 37°C. Recent experiments have identified the critical combinations of heat and humidity, in an indoor setting, above which an individual is unable to maintain a standard core temperature, indicating severe heat stress. It is shown here why this state of severe heat stress cannot be predicted using the wet-bulb temperature. Instead, it is shown that the recently extended heat index model can explain nearly all of the variance in the observed critical combinations of temperature and humidity, and can be used to calculate fatal combinations.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1973

Elastohydrodynamic film thickness model for heavily loaded contacts

An empirical elastohydrodynamic (EHD) film thickness formula for predicting the minimum film thickness occurring within heavily loaded contacts (maximum Hertz stresses above 1.04 GN/sq m (150,000 psi)) was developed. The formula was based upon X-ray film thickness measurements made with synthetic paraffinic, fluorocarbon, Type II ester, and polyphenyl ether fluids covering a wide range of test conditions. Comparisons were made between predictions from an isothermal EHD theory and the test data. The deduced relationship was found to adequately reflect the high-load dependence exhibited by the measured data. The effects of contact geometry, material, and lubricant properties on the form of the empirical model are also discussed.

Loewenthal, S. H.↗

NASA NTRS2008

Modeling and Prediction of Fan Noise

Fan noise is a significant contributor to the total noise signature of a modern high bypass ratio aircraft engine and with the advent of ultra high bypass ratio engines like the geared turbofan, it is likely to remain so in the future. As such, accurate modeling and prediction of the basic characteristics of fan noise are necessary ingredients in designing quieter aircraft engines in order to ensure compliance with ever more stringent aviation noise regulations. In this paper, results from a comprehensive study aimed at establishing the utility of current tools for modeling and predicting fan noise will be summarized. It should be emphasized that these tools exemplify present state of the practice and embody what is currently used at NASA and Industry for predicting fan noise. The ability of these tools to model and predict fan noise is assessed against a set of benchmark fan noise databases obtained for a range of representative fan cycles and operating conditions. Detailed comparisons between the predicted and measured narrowband spectral and directivity characteristics of fan nose will be presented in the full paper. General conclusions regarding the utility of current tools and recommendations for future improvements will also be given.

Envia, Ed↗

NASA NTRS2000

Measurement and Modeling of Steep Ocean Wave Slopes

Our study emphasizes the importance of identifying and quantifying the distribution variance, skewness and kurtosis from optical and microwave scattering observations. Recent field measurements of the sea slope distribution for intermediate-to-long scale gravity waves will be presented. These data were collected using an airborne laser range system designed to estimate the surface slope vector at horizontal scales of 1-2 m. The observed slope distribution tail indicates that the occurrence of steep waves substantially exceeds a Gaussian prediction. This measured peakedness is present over the wide range of sea state and wind speed conditions encountered. Data are further evaluated within the context of Cox and Munk's well-known sea slope investigations. Based on a re-evaluation of the Cox and Munk's reported parameters, we find a consistent picture develops wherein data are shown to consistently indicate non-Gaussian statistics. One fundamental application of such a non-Gaussian slope observation is its place in modifying predicted wave breaking probability to help to better quantify gas transfer processes at the sea surface.

Chapron, B.↗

DOE OSTI2020

Micromachined Piezoresistive-sensed Diaphragms for Infrasonic Monitoring

Micromachined, piezoresistive-sensed diaphragms are designed and fabricated specifically for infrasound sensing applications. Relatively large diaphragms, up to 6 mm × 6 mm, are fabricated to meet the high sensitivity requirements of infrasonic monitoring. A double-stack SOI wafer process is used, resulting in a streamlined two-mask process without the need for doping or ion-implantation. Pressure-sensitivities of diaphragms are studied using a custom static calibration set-up. Here, the piezoresistance of longitudinal and transverse resistors are studied over a large pressure range of ±5,500 Pa so that the linear and nonlinear response regions of diaphragms are observed. Measurements are compared against a nonlinear finite element simulation—shown to accurately predict the sensor’s behavior over a large response range.

47 OTHER INSTRUMENTATION↗

NASA NTRS2000

The Low Energy Effective Area of the Chandra Low Energy Transmission Grating Spectrograph

The Chandra X-ray Observatory was successfully launched on July 23, 1999, and subsequently began an intensive calibration phase. We present the preliminary results from the in-flight calibration of the low energy response of the High Resolution Camera spectroscopic readout (HRC-S) combined with the Low Energy Transmission Grating (LETG) aboard Chandra. These instruments comprise the Low Energy Transmission Grating Spectrograph (LETGS). For this calibration study, we employ a pure hydrogen non-LTE white dwarf emission model (T = 25000 K and log g = 9.0) for comparison with the Chandra observations of Sirius B. The pre-flight calibration of the LETGS effective area only covered wavelengths shortward of 44 A (E less than 277 eV). Our Sirius B analysis shows that the HRC-S quantum efficiency (QE) model assumed for longer wavelengths leads to an overestimate of the effective area by an average factor of about 1.6. We derive a correction to the low energy HRC-S QE model to match the predicted and observed Sirius B spectra over the wavelength range of 44-185 A. We make an independent test of our results by the comparison of a Chandra LETGS observation of HZ 43 with pure hydrogen model atmosphere predictions and find good agreement.

Pease, D.↗

DOE OSTI2024

Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model

Abstract Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species–environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold‐adapted species was predicted to have high probabilities of extirpation across its current range—with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Evaluating the Future of Lightning in Cloud‐Resolving Models

Abstract Two proxies for lightning predict very different responses to global warming: the CAPE times precipitation proxy predicts a large increase in lightning over both the continental United States and the tropical oceans, while the ice flux proxy predicts a small increase over the United States and a decrease over the tropical oceans. To date, however, these proxies have been studied only in global climate models with parameterized convection. Here, cloud‐resolving simulations are used to assess their predictions of future lightning rates. Over the United States, all proxies predict a large increase in the lightning rate in the range of 8–16%/K. On the other hand, in the tropics as modeled by radiative convective equilibrium, half of the proxies predict an increase (of 5–12%/K), while the other half predict a decrease (of 1–4%/K). The reasons for the different responses of these proxies is explored, but it remains unclear which proxy is best suited to predicting future lightning rates.

Romps, David M.↗

NASA NTRS1997

A Comparison of Measured and Predicted XV-15 Tiltrotor Surface Acoustic Pressures

Predicted XV-15 exterior surface acoustic pressures are compared with previously published experimental data. Surface acoustic pressure transducers were concentrated near the tip-path-plane of the rotor in airplane mode. The comparison emphasized cruise conditions which are of interest for tiltrotor interior noise - level flight for speeds ranging from 72 m/s to 113 m/s. The predictions were produced by components of the NASA Langley Tiltrotor Aeroacoustic Code (TRAC) system of computer codes. Comparisons between measurements and predictions were made in both the time and frequency domains, as well as overall sound pressure levels. In general, the predictions replicated the measured data well. Discrepancies between measurements and predictions were noted. Some of the discrepancies were due to poor correlation of the measured data with the rotor tach signal. In other cases limitations of the predictive methodology have been indicated.

Lyle, Karen H.↗

NASA NTRSDate not supplied

Methods for Analytic Reflected Radiant Flux Modeling in Observing Space Vehicles

During NASA’s Artemis I mission, the Orion Optical Navigation (OpNav) camerawas used in a flight test to capture images of the Interim Cryogenic Propulsion Stage(ICPS) at long range. Novel methods in reflectance modeling were developed to esti-mate the reflected light flux as a function of range to inform the camera settings usedto obtain the images. Postflight analysis was performed with the obtained imagesand telemetry. Techniques were developed using a specialized tool developed fromCOTS star identification and attitude determination software to localize ICPS andpositively identify it. The images were then used to verify the preflight prediction ofreflected radiant flux as a function of range and to provide insight into the vehicle’sattitude dynamics.

Spacecraft↗

NASA NTRSDate not supplied

Methods for Analytic Reflected Radiant Flux Modeling in Observing Space Vehicles

spacecraft↗

NASA NTRS2016

Perceived Noise Analysis for Offset Jets Applied to Commercial Supersonic Aircraft

A systems analysis was performed with experimental jet noise data, engine/aircraft performance codes and aircraft noise prediction codes to assess takeoff noise levels and mission range for conceptual supersonic commercial aircraft. A parametric study was done to identify viable engine cycles that meet NASA's N+2 goals for noise and performance. Model scale data from offset jets were used as input to the aircraft noise prediction code to determine the expected sound levels for the lateral certification point where jet noise dominates over all other noise sources. The noise predictions were used to determine the optimal orientation of the offset nozzles to minimize the noise at the lateral microphone location. An alternative takeoff procedure called "programmed lapse rate" was evaluated for noise reduction benefits. Results show there are two types of engines that provide acceptable mission range performance; one is a conventional mixed-flow turbofan and the other is a three-stream variable-cycle engine. Separate flow offset nozzles reduce the noise directed toward the thicker side of the outer flow stream, but have less benefit as the core nozzle pressure ratio is reduced. At the systems level for a three-engine N+2 aircraft with full throttle takeoff, there is a 1.4 EPNdB margin to Chapter 3 noise regulations predicted for the lateral certification point (assuming jet noise dominates). With a 10% reduction in thrust just after clearing the runway, the margin increases to 5.5 EPNdB. Margins to Chapter 4 and Chapter 14 levels will depend on the cumulative split between the three certification points, but it appears that low specific thrust engines with a 10% reduction in thrust (programmed lapse rate) can come close to meeting Chapter 14 noise levels. Further noise reduction is possible with engine oversizing and derated takeoff, but more detailed mission studies are needed to investigate the range impacts as well as the practical limits for safety and takeoff regulations.

Turbofans↗

DOE OSTI2024

Accurate Machine Learning for Predicting the Viscosities of Deep Eutectic Solvents

Deep eutectic solvents (DESs) are emerging as environmentally friendly designer solvents for mass transport and heat transfer processes in industrial applications; however, the lack of accurate tools to predict and thus control their viscosities under both a range of environmental factors and formulations hinders their general application. While DESs may serve as designer solvents, with nearly unlimited combinations, this unfortunately makes it experimentally infeasible to comprehensively measure the viscosities of all DESs of potential industrial interest. To assist in the design of DESs, we have developed several new machine learning (ML) models that accurately and rapidly predict the viscosities of a diverse group of DESs at different temperatures and molar ratios using, to date, one of the most comprehensive data sets containing the properties of over 670 DESs over a wide range of temperatures (278.15–385.25 K). Three ML models, including support vector regression (SVR), feed forward neural networks (FFNNs), and categorical boosting (CatBoost), were developed to predict DES viscosity as a function of temperature and molar ratio and contrasted with multilinear and two-factor polynomial regression baselines. Further, quantum chemistry-based, COSMO-RS-derived sigma profile (σ-profile) features were used as inputs for the ML models. The CatBoost model is excellent at externally predicting DES viscosity, as indicated by high R 2 (0.99) and low root-mean-square-error (RMSE) and average absolute relative deviations (AARD) (5.22%) values for the testing data sets, and 98% of the data points lie within the 15% of AARD deviations. Furthermore, SHapley additive explanation (SHAP) analysis was employed to interpret the ML results and rationalize the viscosity predictions. The result is an ML approach that accurately predicts viscosity and will aid in accelerating the design of appropriate DESs for industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2001

Investigating Uncertainty in Predicting Carbon Dynamics in North American Biomes: Putting Support-Effect Bias in Perspective

A fundamental strategy in NASA's Earth Observing System's (EOS) monitoring of vegetation and its contribution to the global carbon cycle is to rely on deterministic, process-based ecosystem models to make predictions of carbon flux over large regions. These models are parameterized (that is, the input variables are derived) using remotely sensed images such as those from the Moderate Resolution Imaging Spectroradiometer (MODIS), ground measurements and interpolated maps. Since early applications of these models, investigators have noted that results depend partly on the spatial support of the input variables. In general, the larger the support of the input data, the greater the chance that the effects of important components of the ecosystem will be averaged out. A review of previous work shows that using large supports can cause either positive or negative bias in carbon flux predictions. To put the magnitude and direction of these biases in perspective, we must quantify the range of uncertainty on our best measurements of carbon-related variables made on equivalent areas. In other words, support-effect bias should be placed in the context of prediction uncertainty from other sources. If the range of uncertainty at the smallest support is less than the support-effect bias, more research emphasis should probably be placed on support sizes that are intermediate between those of field measurements and MODIS. If the uncertainty range at the smallest support is larger than the support-effect bias, the accuracy of MODIS-based predictions will be difficult to quantify and more emphasis should be placed on field-scale characterization and sampling. This talk will describe methods to address these issues using a field measurement campaign in North America and "upscaling" using geostatistical estimation and simulation.

Dungan, Jennifer L.↗

DOE OSTI2025

Data-driven organic solubility prediction at the limit of aleatoric uncertainty

Abstract Small molecule solubility is a critically important property which affects the efficiency, environmental impact, and phase behavior of synthetic processes. Experimental determination of solubility is a time- and resource-intensive process and existing methods for in silico estimation of solubility are limited by their generality, speed, and accuracy. This work presents two models derived from the FASTPROP and CHEMPROP architectures and trained on BigSolDB which are capable of predicting solubility at arbitrary temperatures for a wide range of small molecules in organic solvent. Both extrapolate to unseen solutes 2–3 times more accurately than the current state-of-the-art model and we demonstrate that they are approaching the aleatoric limit (0.5–1$$\log S$$ log S ) of available test data, suggesting that further improvements in prediction accuracy require more accurate datasets. The FASTPROP-derived model (called FASTSOLV) and the CHEMPROP-based model are open source, freely accessible via a Python package and web interface, highly reproducible, and up to 2 orders of magnitude faster than current alternatives.

Science & Technology - Other Topics↗