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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Rotary-wing aerodynamics. Volume 1 - Basic theories of rotor aerodynamics (With application to helicopters). Volume 2 Performance prediction of helicopters (2nd revised and enlarged edition)

Basic theories of rotor aerodynamics are presented and applied to the performance prediction of helicopters. The very simple physicomathematical model of the rotor offered by momentum theory is addressed first, followed by the combined blade-element and momentum theory. Vortex theory is discussed, and a rotor blade is modeled by means of a vortex filament or vorticity surface. Considerations of airfoil sections suitable for rotors are examined. Detailed performance techniques for a single-rotor helicopter in hover, vertical ascent, and forward flight are described, and winged and tandem-rotor helicopter performance calculations are presented as extensions and modifications of single-rotor methodology. Computer data based on the vortex theory are compared with approximate results obtained from the simplified momentum theory and the blade element solution.

Stepniewski, W. Z.↗
NASA NTRS1976

Image processing system performance prediction and product quality evaluation

The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

Stein, E. K.↗
DOE OSTI2021

Early Battery Performance Prediction for Mixed Use Charging Profiles Using Hierarchal Machine Learning

A key step limiting how fast batteries can be deployed is the time necessary to provide evaluation and validation of performance. Using data analysis approaches, such as machine learning, the validation process can be accelerated. However, questions on the validity of projecting models trained on limited data or simple cycling profiles, such as constant current cycling, to real-world scenarios with complex loads remains. Here, we present the ability to predict performance with less than 1.2% mean absolute percent error when trained on cells aged using complex electric vehicle discharge profiles, and either AC Level 2 charge or DC Fast charge profiles, using only the first 45 cycles, namely 5% of the total testing time. While error is low across the projections, this study also highlights that battery lifetime analysis using only cycling data may not extrapolate safely to certain real-world conditions due to the impact of calendar degradation.

25 ENERGY STORAGE↗
DOE OSTI2023

Design and implementation of I/O performance prediction scheme on HPC systems through large-scale log analysis

Abstract Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units used by hundreds to thousands of users simultaneously. Applications from large numbers of users have diverse characteristics, such as varying computation, communication, memory, and I/O intensity. A good understanding of the performance characteristics of each user application is important for job scheduling and resource provisioning. Among these performance characteristics, I/O performance is becoming increasingly important as data sizes rapidly increase and large-scale applications, such as simulation and model training, are widely adopted. However, predicting I/O performance is difficult because I/O systems are shared among all users and involve many layers of software and hardware stack, including the application, network interconnect, operating system, file system, and storage devices. Furthermore, updates to these layers and changes in system management policy can significantly alter the I/O behavior of applications and the entire system. To improve the prediction of the I/O performance on HPC systems, we propose integrating information from several different system logs and developing a regression-based approach to predict the I/O performance. Our proposed scheme can dynamically select the most relevant features from the log entries using various feature selection algorithms and scoring functions, and can automatically select the regression algorithm with the best accuracy for the prediction task. The evaluation results show that our proposed scheme can predict the write performance with up to 90% prediction accuracy and the read performance with up to 99% prediction accuracy using the real logs from the Cori supercomputer system at NERSC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows (IPPD) (Final Report)

This report details the accomplishments from the ASCR funded project “Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows” under the award numbers FWP-66406 and DE-SC0012630, with a focus on the UC San Diego (Award No. DE-SC0012630) part of the accomplishments. We refer to the project as IPPD. The main activities of IPPD were centered on the development and integration of provenance information to capture empirically workflow information and identify the sources of bottlenecks as well as variability, and modeling and simulation to provide insights and predictively explore multiple scenarios for development of advanced techniques for optimization of resources and workflow execution. After a Phase I of the project, a Phase II effort focused on three major aspects: a) observe how data is generated, distributed, and used; b) analyze how data is (repeatedly) consumed with a focus both on repeated patterns and anomalies; and c) explore how to optimize data motion. The project leveraged and extended our existing tools with new research and demonstrated our work on the Belle II workflow suite as well as on workflows from NSLS-II.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Program Predicts Performance of Optical Parametric Oscillators

A computer program predicts the performances of solid-state lasers that operate at wavelengths from ultraviolet through mid-infrared and that comprise various combinations of stable and unstable resonators, optical parametric oscillators (OPOs), and sum-frequency generators (SFGs), including second-harmonic generators (SHGs). The input to the program describes the signal, idler, and pump beams; the SFG and OPO crystals; and the laser geometry. The program calculates the electric fields of the idler, pump, and output beams at three locations (inside the laser resonator, just outside the input mirror, and just outside the output mirror) as functions of time for the duration of the pump beam. For each beam, the electric field is used to calculate the fluence at the output mirror, plus summary parameters that include the centroid location, the radius of curvature of the wavefront leaving through the output mirror, the location and size of the beam waist, and a quantity known, variously, as a propagation constant or beam-quality factor. The program provides a typical Windows interface for entering data and selecting files. The program can include as many as six plot windows, each containing four graphs.

Cross, Patricia L.↗
NASA NTRS1993

Accuracy of Tilt Rotor Hover Performance Predictions

The accuracy of various methods used to predict tilt rotor hover performance was established by comparing predictions with large-scale experimental data. A wide range of analytical approaches were examined. Blade lift was predicted with a lifting line analysis, two lifting surface analyses, and by a finite-difference solution of the full potential equation. Blade profile drag was predicted with two different types of airfoil tables and an integral boundary layer analysis. The inflow at the rotor was predicted using momentum theory, two types of prescribed wakes, and two free wake analyses. All of the analyses were accurate at moderate thrust coefficients. The accuracy of the analyses at high thrust coefficients was dependent upon their treatment of high sectional angles of attack on the inboard sections of the rotor blade. The analyses which allowed sectional lift coefficients on the inboard stations of the blade to exceed the maximum observed in two-dimensional wind tunnel tests provided better accuracy at high thrust coefficients than those which limited lift to the maximum two-dimensional value. These results provide tilt rotor aircraft designers guidance on which analytical approaches provide the best results, and the level of accuracy which can be expected from the best analyses.

Felker, Fort F.↗
NASA NTRS1991

Geoscience Laser Ranging System design and performance predictions

The Geoscience Laser System (GLRS) will be a high-precision distance-measuring instrument planned for deployment on the EOS-B platform. Its primary objectives are to perform ranging measurements to ground targets to monitor crustal deformation and tectonic plate motions, and nadir-looking altimetry to determine ice sheet thicknesses, surface topography, and vertical profiles of clouds and aerosols. The system uses a mode-locked, 3-color Nd:YAG laser source, a Microchannel Plate-PMT for absolute time-of-flight (TOF) measurement (at 532 nm), a streak camera for TOF 2-color dispersion measurement (532 nm and 355 nm), and a Si avalanche photodiode for altimeter waveform detection (1064 nm). The performance goals are to make ranging measurements to ground targets with about 1 cm accuracy, and altimetry height measurements over ice with 10 cm accuracy. This paper presents an overview of the design concept developed during a phase B study. System engineering issues and trade studies are discussed, with particular attention to error budgets and performance predictions.

Anderson, Kent L.↗
NASA NTRS2000

Performance prediction of the Planck sorption cooler and initial validation

Two continuous operation 18 K/20 K sorption coolers are being developed by JPL for the ESA Planck mission to provide about 200 mW of cooling at 18 K and 1.4 W at 20 K. A detailed performance prediction model has been developed to support the design process and to evaluate the results of a prototype testing.

sorption cryocoolers thermal model analyses metal ↗
DOE OSTI2026

Variations in lithium vapor cave performance predictions due to radial transport and recycling assumptions

The lithium vapor cave is a detached divertor design that uses a single private flux region baffle to contain a dense cloud of lithium vapor to dissipate heat flux. Plasma flows are created via fuel gas puffing in order to minimize lithium contamination of the main plasma. Significant modeling using the 2D edge code SOLPS-ITER has already been performed, predicting that sufficient target heat flux reductions (q$^{max}_{Target}$ MW m −2 ) with ( $n$ Li /$n$ e ) LCFS < 0.05 is possible in a case with 90 MW m −2 unmitigated heat flux in NSTX-U. Low heat flux and low upstream concentration was found with a variety of combinations of divertor geometries, target recycling coefficients, upstream plasma parameters, lithium evaporation locations and deuterium fueling locations, with variations in performance found for each design choice. However, the most universal uncertainty of SOLPS-ITER simulations has until now remained unaddressed systematically, namely the cross-field anomalous particle and heat diffusivities. This article aims to bound the uncertainty in lithium concentration prediction as a result of the assumed deuterium cross-field transport and recycling. For the simulations presented here, a factor of 2.1 increase in the upstream lithium density prediction across a factor of four decrease to the assumed deuterium radial particle diffusivity is found. This result is compared across different assumed deuterium recycling coefficients, known to reduce with lithium injection. Upstream lithium density is found to vary by a factor of 2.4 across a feasible range of recycling coefficients at similar $n$$^{OMP,sep}_{e}$.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1979

Thematic mapper design description and performance prediction

The new generation of satellite-borne earth resources scanners, the Thematic Mapper, is being built for launch on the Landsat-D spacecraft. It will gather data for applications such as crop inventory, land use planning, forest management, and geology. This paper gives an overall design description, further discussion of principal design features, performance achievements where data are available, and system performance predictions.

Lansing, J. C., Jr.↗
NASA NTRS1992

Ski jump takeoff performance predictions for a mixed-flow, remote-lift STOVL aircraft

A ski jump model was developed to predict ski jump takeoff performance for a short takeoff and vertical landing (STOVL) aircraft. The objective was to verify the model with results from a piloted simulation of a mixed flow, remote lift STOVL aircraft. The prediction model is discussed. The predicted results are compared with the piloted simulation results. The ski jump model can be utilized for basic research of other thrust vectoring STOVL aircraft performing a ski jump takeoff.

Birckelbaw, Lourdes G.↗
NASA NTRSDate not supplied

Kinetic Model Development of the Carbon Vapor Deposition Reactor to Predict Performance Versus Design

To enable complete closure of a Sabatier-based atmosphere revitalization system where oxygen recovery is predicated by carbon dioxide reduction to methane and water, there must be a means of recovering the hydrogen from the byproduct methane. Honeywell’s carbon vapor deposition (CVD) reactor is a potential technology that provides a thermochemical means by which methane decomposes at high temperatures (> 1,000 °C) into hydrogen, solid carbon, and a small percentage of hydrocarbons. This advanced methane pyrolysis reactor utilizes a carbon fiber substrate to capture and immobilize the solid pyrolytic carbon rather than allowing continuation toward undesirable soot. The CVD reactor is a highly dynamic system whose characteristic geometry changes while operating. The reactor model was developed to provide predictive performance assessment capabilities at different operating conditions, geometries, and configurations to aid in technology development. Modeling of the CVD reactor considered the multitude of simultaneous and interdependent physicochemical processes that are entailed, including: (1) the homogeneous gas-phase pyrolysis reactions, (2) the heterogeneous deposition reactions, and (3) the transport of gaseous species in the reactor domains. A 1-D CVD reactor model was developed based on a general packed-bed, axial-dispersion plug flow reactor model with a solid substrate balance to account for carbon deposition. The model includes 59 species and 243 reactions constituting the methane pyrolysis reaction network, carbon deposition, and interconversions of oxygenate species. The reactor model was compared to brassboard test data, where it was shown to be able to capture the pertinent physicochemical phenomena as evidenced by its agreement with short-duration run data (i.e., looking at different temperature and flow rate conditions), as well as trend agreement with the brassboard reactor’s long-duration test data. Recommendations are provided on further model development steps as well as its use cases.

Air Revitalization↗
NASA NTRS1990

Predicting performance of parallel computations

An accurate and computationally efficient method for predicting the performance of a class of parallel computations running on concurrent systems is described. A parallel computation is modeled as a task system with precedence relationships expressed as a series-parallel directed acyclic graph. Resources in a concurrent system are modeled as service centers in a queuing network model. Using these two models as inputs, the method outputs predictions of expected execution time of the parallel computation and the concurrent system utilization. The method is validated against both detailed simulation and actual execution on a commercial multiprocessor. Using 100 test cases, the average error of the prediction when compared to simulation statistics is 1.7 percent, with a standard deviation of 1.5 percent; the maximum error is about 10 percent.

Mak, Victor W.↗