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DOE OSTI2021

Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data

This study explores the usefulness of machine learning classifiers for modeling freight mode choice. We investigate eight commonly used machine learning classifiers, namely Naïve Bayes, Support Vector Machine, Artificial Neural Network, K-Nearest Neighbors, Classification and Regression Tree, Random Forest, Boosting and Bagging, along with the classical Multinomial Logit model. US 2012 Commodity Flow Survey data are used as the primary data source; we augment it with spatial attributes from secondary data sources. The performance of the classifiers is compared based on prediction accuracy results. The current research also examines the role of sample size and training-testing data split ratios on the predictive ability of the various approaches. In addition, the importance of variables is estimated to determine how the variables influence freight mode choice. The results show that the tree-based ensemble classifiers perform the best. Specifically, Random Forest produces the most accurate predictions, closely followed by Boosting and Bagging. With regard to variable importance, shipment characteristics, such as shipment distance, industry classification of the shipper and shipment size, are the most significant factors for freight mode choice decisions.

42 ENGINEERING↗

DOE OSTI2025

Application of Machine Learning and Data Augmentation Algorithms in the Discovery of Metal Hydrides for Hydrogen Storage

The development of efficient and sustainable hydrogen storage materials is a key challenge for realizing hydrogen as a clean and flexible energy carrier. Among various options, metal hydrides offer high volumetric storage density and operational safety, yet their application is limited by thermodynamic, kinetic, and compositional constraints. In this work, we investigate the potential of machine learning (ML) to predict key thermodynamic properties—equilibrium plateau pressure, enthalpy, and entropy of hydride formation—based solely on alloy composition using Magpie-generated descriptors. We significantly expand an existing experimental dataset from ~400 to 806 entries and assess the impact of dataset size and data augmentation, using the PADRE algorithm, on model performance. Models including Support Vector Machines and Gradient Boosted Random Forests were trained and optimized via grid search and cross-validation. Results show a marked improvement in predictive accuracy with increased dataset size, while data augmentation benefits are limited to smaller datasets and do not improve accuracy in underrepresented pressure regimes. Furthermore, clustering and cross-validation analyses highlight the limited generalizability of models across different material classes, though high accuracy is achieved when training and testing within a single hydride family (e.g., AB2). The study demonstrates the viability and limitations of ML for accelerating hydride discovery, emphasizing the importance of dataset diversity and representation for robust property prediction.

augmentation↗

DOE OSTI2022

Behavior and mechanisms of Doppler wind lidar error in varying stability regimes

Abstract. Wind lidars are widespread and important tools in atmospheric observations. An intrinsic part of lidar measurement error is due to atmospheric variability in the remote-sensing scan volume. This study describes and quantifies the distribution of measurement error due to turbulence in varying atmospheric stability. While the lidar error model is general, we demonstrate the approach using large ensembles of virtual WindCube V2 lidar performing a profiling Doppler-beam-swinging scan in quasi-stationary large-eddy simulations (LESs) of convective and stable boundary layers. Error trends vary with the stability regime, time averaging of results, and observation height. A systematic analysis of the observation error explains dominant mechanisms and supports the findings of the empirical results. Treating the error under a random variable framework allows for informed predictions about the effect of different configurations or conditions on lidar performance. Convective conditions are most prone to large errors (up to 1.5 m s−1 in 1 Hz wind speed in strong convection), driven by the large vertical velocity variances in convective conditions and the high elevation angle of the scanning beams (62∘). Range-gate weighting induces a negative bias into the horizontal wind speeds near the surface shear layer (−0.2 m s−1 in the stable test case). Errors in the horizontal wind speed and direction computed from the wind components are sensitive to the background wind speed but have negligible dependence on the relative orientation of the instrument. Especially during low winds and in the presence of large errors in the horizontal velocity estimates, the reported wind speed is subject to a systematic positive bias (up to 0.4 m s−1 in 1 Hz measurements in strong convection). Vector time-averaged measurements can improve the behavior of the error distributions (reducing the 10 min wind speed error standard deviation to <0.3 m s−1 and the bias to <0.1 m s−1 in strong convection) with a predictable effectiveness related to the number of decorrelated samples in the time window. Hybrid schemes weighting the 10 min scalar- and vector-averaged lidar measurements are shown to be effective at reducing the wind speed biases compared to cup measurements in most of the simulated conditions, with time averages longer than 10 min recommended for best use in some unstable conditions. The approach in decomposing the error mechanisms with the help of the LES flow field could be extended to more complex measurement scenarios and scans.

17 WIND ENERGY↗

NASA NTRS1990

CFD evaluation of an advanced thrust vector control concept

A potential concept that can offer an alternate method for thrust vector control of the Space Shuttle Solid Rocket Booster is the use of a cylindrical probe that is inserted (on demand) through the wall of the rocket nozzle. This Probe Thrust Vector Control (PTVC) concept is an alternate to that of a gimbaled nozzle or a Liquid Injection Thrust Vector (LITVC) system. The viability of the PTVC concept can be assessed either experimentally and/or with the use of CFD. A purely experimental assessment can be time consuming and expensive, whereas a CFD assessment can be very time- and cost-effective. Two key requirements of the proposed concept are PTVC vectoring performance and the active cooling requirements for the probe to maintain its thermal and structural integrity. An active thermal cooling method is the injection of coolant around the pheriphery of the probe. How much coolant is required and how this coolant distributes itself in the flow field is of major concern. The objective of the work reported here is the use of CFD to answer these question and in the design of test hardware to substantiate the results of the CFD predictions.

Tiarn, Weihnurng↗

NASA NTRS1996

Surface Tension Driven Convection Experiment (STDCE)

This document reports the results obtained from the Surface Tension Driven Convection Experiment (STDCE) conducted aboard the USML-1 Spacelab in 1992. The experiments used 10 cSt silicone oil placed in an open circular container that was 10 cm wide and 5 cm deep. Thermocapillary flow was induced by using either a cylindrical heater placed along the container centerline or by a CO2 laser. The tests were conducted under various power settings, laser beam diameters, and free surface shapes. Thermistors located at various positions in the test section recorded the temperature of the fluid, heater, walls, and air. An infrared imager was used to measure the free surface temperature. The flow field was studied by flow visualization and the data was analyzed by a PTV technique. The results from the flow visualization and the temperature measurements are compared with the numerical analysis that was conducted in conjunction with the experiment. The compared results include the experimental and numerical velocity vector plots, the streamline plots, the fluid temperature, and the surface temperature distribution.

Ostrach, S.↗

NASA NTRSDate not supplied

Phase-change Reconfigurable Optical WavEfront Synthesis System (PROWESS)

We report the design, fabrication, and testing of electrically tunable metasurface k-space filters based on the low-loss, high-contrast phase-change material GSST and a transparent Si electrode heating architecture. A 10x10 array of PCM elements integrated with Si heaters was fabricated via foundry processes, and used to actively control the crystallinity of a metasurface consisting of GSST nano antennae. By selectively varying the structural state of individual PCM elements, specific k-vectors of transmitted light can effectively be filtered out, resulting in improved imaging quality by reducing the scattered light that reaches a detector. Optimized doping profiles in the Si heaters allow for uniform, low power, reliable and repeatable switching of the GSST state. Compared to other k-space filters, this new architecture is completely transparent to the wavelength of interest and can be actively reconfigured in real time with high performance, low power consumption and a small footprint. The 10x10 array device is a proof-of-concept demonstration that can enable high-resolution arbitrary wavefront synthesis and correction in the future, with key applications in optical communications, beam steering, remote sensing, and adaptive optics.

phase change material↗

NASA NTRS1977

Subsonic longitudinal aerodynamic characteristics of a vectored-engine-over-wing configuration having spanwise leading-edge vortex enhancement

A configuration which integrates a close coupled canard wing combination, spanwise blowing for enhancement of the wing leading edge vortex, an engine-over-wing concept, and a wing trailing edge coanda-effect flap is studied. The data on the configuration are presented in tabular from without discussion. The investigation was conducted in the Langley 7- by 10-foot high speed tunnel at a Mach number of 0.166 through an angle-of-attack range from -2 to 22 deg. Rectangular main engine nozzles of aspect ratio 4, 6, and 8 were tested over a momentum coefficient range from 1.0 to 1.8.

Huffman, J. K.↗

NASA NTRS2002

Aeroelastic Calculations of Quiet High- Speed Fan Performed

An advanced high-speed fan was recently designed under a cooperative effort between the NASA Glenn Research Center and Honeywell Engines & Systems. The principal design goals were to improve performance and to reduce fan noise at takeoff. Scale models of the Quiet High-Speed Fan were tested for operability, performance, and acoustics. During testing, the fan showed significantly improved noise characteristics, but a self-excited aeroelastic vibration known as flutter was encountered in the operating range. Flutter calculations were carried out for the Quiet High-Speed Fan using a three-dimensional, unsteady aerodynamic, Reynolds-averaged Navier-Stokes turbomachinery code named "TURBO." The TURBO code can accurately model the viscous flow effects that can play an important role in various aeroelastic problems such as flutter with flow separation, flutter at high loading conditions near the stall line (stall flutter), and flutter in the presence of shock and boundary-layer interaction. Initially, calculations were performed with no blade vibrations. These calculations were at a constant rotational speed and a varying mass flow rate. The mass flow rate was varied by changing the backpressure at the exit boundary of the computational domain. These initial steady calculations were followed by aeroelastic calculations in which the blades were prescribed to vibrate harmonically in a natural mode, at a natural frequency, and with a fixed interblade phase angle between adjacent blades. The AE-prep preprocessor was used to interpolate the in-vacuum mode shapes from the structural dynamics mesh onto the computational fluid dynamics mesh and to smoothly propagate the grid deformations from the blade surface to the interior points of the grid. The aeroelastic calculations provided the unsteady aerodynamic forces on the blade surface due to blade vibrations. These forces were vector multiplied with the structural dynamic mode shape to calculate the work done on the blade during one vibration period, then this result was converted to an aerodynamic damping. Flutter occurs when the aerodynamic damping becomes negative, if structural damping is ignored. The results of these aeroelastic calculations are summarized in this plot of aerodynamic damping versus mass flow rate at a constant rotational speed. As the backpressure is increased, the mass flow rate through the fan decreases and the fan operating point moves towards the stall line. The aeroelastic calculations showed that the aerodynamic damping decreases as the stall line is approached, as observed during testing. In addition, the aeroelastic calculations with the TURBO code correctly predicted the aeroelastic parameters: the most unstable vibration mode and interblade phase angle, as observed during testing. The Quiet High-Speed Fan demonstrated significant noise reductions during testing, but flutter imposed limits on its operating range. The accurate calculation of the aeroelastic characteristics using the TURBO code is a significant step toward eliminating flutter from the operating range and toward realizing the benefits of reduced fan noise. The aeroelastic calculations described here were performed under a grant by University of Toledo researchers in collaboration with Glenn's researchers.

Bakhle, Milind A.↗

DOE OSTI2021

Precision test of the muon-Higgs coupling at a high-energy muon collider

We explore the sensitivity of directly testing the muon-Higgs coupling at a high-energy muon collider. This is strongly motivated if there exists new physics that is not aligned with the Standard Model Yukawa interactions which are responsible for the fermion mass generation. We illustrate a few such examples for physics beyond the Standard Model. With the accidentally small value of the muon Yukawa coupling and its subtle role in the high-energy production of multiple (vector and Higgs) bosons, we show that it is possible to measure the muon-Higgs coupling to an accuracy of ten percent for a 10 TeV muon collider and a few percent for a 30 TeV machine by utilizing the three boson production, potentially sensitive to a new physics scale about Λ ~ 30 - 100 TeV.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances

Intensity simulation of X-ray scattering from large twisted cellulose molecular fibrils is important in understanding the impact of chemical or physical treatments on structural properties such as twisting or coiling. This paper describes a highly efficient method for the simulation of X-ray diffraction patterns from complex fibrils using atom-type-specific pair-distance quantization. Pair distances are sorted into arrays which are labelled by atom type. Histograms of pair distances in each array are computed and binned and the resulting population distributions are used to represent the whole pair-distance data set. These quantized pair-distance arrays are used with a modified and vectorized Debye formula to simulate diffraction patterns. This approach utilizes fewer pair distances in each iteration, and atomic scattering factors are moved outside the iteration since the arrays are labelled by atom type. As a result, this algorithm significantly reduces the computation time while maintaining the accuracy of diffraction pattern simulation, making possible the simulation of diffraction patterns from large twisted fibrils in a relatively short period of time, as is required for model testing and refinement.

09 BIOMASS FUELS↗

DOE OSTI2015

SU-E-T-01: (In)dependence of Plan Quality On Treatment Modalities and Target-To-Critical Structure Geometry for Brain Tumor

Purpose: To evaluate and test the hypothesis that plan quality may be systematically affected by treatment delivery techniques and target-tocritical structure geometric relationship in radiotherapy for brain tumor. Methods: Thirty-four consecutive brain tumor patients treated between 2011–2014 were analyzed. Among this cohort, 10 were planned with 3DCRT, 11 with RadipArc, and 13 with helical IMRT on TomoTherapy. The selected dosimetric endpoints (i.e., PTV V100, maximum brainstem/chiasm/ optic nerve doses) were considered as a vector in a highdimensional space. A Pareto analysis was performed to identify the subset of Pareto-efficient plans.The geometric relationships, specifically the overlapping volume and centroid-of-mass distance between each critical structure to the PTV were extracted as potential geometric features. The classification-tree analyses were repeated using these geometric features with and without the treatment modality as an additional categorical predictor. In both scenarios, the dominant features to prognosticate the Pareto membership were identified and the tree structures to provide optimal inference were recorded. The classification performance was further analyzed to determine the role of treatment modality in affecting plan quality. Results: Seven Pareto-efficient plans were identified based on dosimetric endpoints (3 from 3DCRT, 3 from RapicArc, 1 from Tomo), which implies that the evaluated treatment modality may have a minor influence on plan quality. Classification trees with/without the treatment modality as a predictor both achieved accuracy of 88.2%: with 100% sensitivity and 87.1% specificity for the former, and 66.7% sensitivity and 96.0% specificity for the latter. The coincidence of accuracy from both analyses further indicates no-to-weak dependence of plan quality on treatment modality. Both analyses have identified the brainstem to PTV distance as the primary predictive feature for Pareto-efficiency. Conclusion: Pareto evaluation and classification-tree analyses have indicated that plan quality depends strongly on geometry for brain tumor, specifically PTV-tobrain-stem-distance but minimally on treatment modality.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Multi-Gene Detection and Identification of Mosquito-Borne RNA Viruses Using an Oligonucleotide Microarray

Background: Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae), Alphavirus (Togaviridae), Orthobunyavirus (Bunyaviridae), and Phlebovirus (Bunyaviridae). Methodology/Principal Findings: The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. Conclusions/Significance: We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish public health priorities, detect disease outbreaks, and evaluate control programs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Piperitone ( p -Menth-1-En-3-One): A New Repellent for Tea Shot Hole Borer (Coleoptera: Curculionidae) in Florida Avocado Groves

The tea shot hole borer, Euwallacea perbrevis, has been recently established in Florida, USA, where it vectors fungal pathogens that cause Fusarium dieback in avocado. Pest monitoring uses a two-component lure containing quercivorol and α-copaene. Incorporation of a repellent into IPM programs may reduce the incidence of dieback in avocado groves, particularly if combined with lures in a push–pull system. This study evaluated piperitone and α-farnesene as potential repellents for E. perbrevis, comparing their efficacy to that of verbenone. Replicate 12-week field tests were conducted in commercial avocado groves. Each test compared beetle captures in traps baited with two-component lures versus captures in traps containing lures plus repellent. To complement field trials, Super-Q collections followed by GC analyses were performed to quantify emissions from repellent dispensers field-aged for 12 weeks. Electroantennography (EAG) was also used to measure beetle olfactory response to each repellent. Results indicated that α-farnesene was ineffective; however, piperitone and verbenone were comparable in repellency, achieving 50–70% reduction in captures, with longevity of 10–12 weeks. EAG responses to piperitone and verbenone were equivalent, and significantly greater than response to α-farnesene. Since piperitone is less expensive than verbenone, this study identifies a potential new E. perbrevis repellent.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

A Method of Ground-Based Cloud Motion Predict: CCLSTM + SR-Net

Ground-based cloud images can provide information on weather and cloud conditions, which play an important role in cloud cover monitoring and photovoltaic power generation forecasting. However, the cloud motion prediction of ground-based cloud images still lacks advanced and complete methods, and traditional technologies based on image processing and motion vector calculation are difficult to predict cloud morphological changes. In this paper, we propose a cloud motion prediction method based on Cascade Causal Long Short-Term Memory (CCLSTM) and Super-Resolution Network (SR-Net). Firstly, CCLSTM is used to estimate the shape and speed of cloud motion. Secondly, the Super-Resolution Network is built based on perceptual losses to reconstruct the result of CCLSTM and, finally, make it clearer. We tested our method on Atmospheric Radiation Measurement (ARM) Climate Research Facility TSI (total sky imager) images. The experiments showed that the method is able to predict the sky cloud changes in the next few steps.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2006

The Solar-B Mission: First Light, Future Plans and Community Participation

The Solar-B spacecraft was launched from the Uchinoura Space Center into a circular, sun-synchronous, polar orbit by the Japanese Aerospace Exploration Agency in late September 2006. The spacecraft carries thee scientific instruments designed to follow the flow of magnetic energy from the photosphere to the corona to improve our understanding of both steady state and transient energy release. This goal will be achieved through coordinated observations of three highly advanced solar telescopes developed cooperatively by teams from Japan, the United States and the United Kingdom. The three telescopes are a 0.5m aperture, diffraction limited, solar optical telescope (SOT), an X-ray telescope (XRT) designed for full sun imaging with 1.0 arcsec pixels and an EUV imaging spectrometer (EIS) with an order of magnitude improvement in sensitivity over past instruments. The SOT focal plane contains three instruments, a spectropolarimeter for measuring vector magnetic fields, a broadband filter imager for recording images of the photosphere and chromosphere at the highest resolution the telescope is capable of, and a narrow band filter imager that will record Doppler grams and vector magnetograms. The XRT has broad temperature coverage and a spatial a resolution three times as high as Yohkoh. EIS covers a broad range of transition region and coronal temperatures in two spectral bands. Both XRT and EIS have 2 arcsec spatial resolution (1 arcsec pixels). Instrument first light occurred after five weeks on orbit to allow for out gassing and the opening of the telescopes doors. The initial observation sequences are designed to test the functionality of the different operating modes and for calibration. After this commissioning phase is complete a series of observations are planned to demonstrate the ability of the instruments to meet NASA's mission minimum success criteria. Data is downloaded every orbit to the Norwegian high latitude ground station at Svalbard. The data are transmitted to ISAS where they are reformatted into FITS files and archived as Level 0 data on the ISAS DARTS system. Once the initial observation period is complete, approximately six months after launch, the mission data will be open and freely available to researchers shortly after receipt at the DARTS data archive hosted in Japan and at NASA s Solar Data Analysis Center at the Goddard Space Flight Center. Scientific operations will be conducted from the ISAS facility in Sagamihara, Japan and the observatory will become available for performing joint operations with both ground and space based instruments and for conducting observing programs proposed by non-team members. This process will be described together with a status report from the initial operation of the observatory, showing examples of the first observations.

Davis, John M.↗

DOE OSTI2025

Detecting Process Equipment Failures Using Acoustic Data and Machine Learning

Nuclear power plant (NPP) process equipment such as fans, motors, valves, and pumps generate frequent or continuous noise, and deviations from the normal operational sounds made by this equipment can indicate potential issues. These deviations can be identified via automated acoustic anomaly detection, which involves using acoustic sensors (i.e., microphones) alongside detection algorithms to continuously monitor for changes in acoustic signatures. This task is made challenging by the substantial background noise that exists, such as operators opening and closing doors, manipulating valves, and conversing—in addition to typical plant noises. In collaboration with a nuclear power utility partner, this effort assessed the efficacy of acoustic anomaly detection when using a specific acoustic sensor that compresses data into a fixed set of features that are transferable over a standard Internet of Things communication protocol, thereby improving usability but potentially degrading detection performance. Two methods of performing automated acoustic anomaly detection were evaluated: one-class support vector machine (OC-SVM) and isolation forest (iForest). To enable the use of high-quality acoustic data encompassing both normal and anomalous conditions, the study utilized the publicly available Malfunctioning Industrial Machine Investigation and Inspection dataset, which includes real measured acoustic sensor data for a range of equipment types, model numbers, and signal-to-noise ratios (SNRs), along with a benchmark set of detection results. Using this dataset, the methods were tested and then compared against the benchmark results. The results indicated that although the specific acoustic sensor did not enable as rich a feature set extraction, the proposed methods with the limited feature set performed just as well. This provides solid justification for both the methods and the use of the proposed acoustic sensor.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2024

A research program to measure the lifetime of spin polarized fuel

The use of spin polarized fuel could increase the deuterium-tritium (D-T) fusion cross section by a factor of 1.5 and, owing to alpha heating, increase the fusion power by an even larger factor. Issues associated with the use of polarized fuel in a reactor are identified. Theoretically, nuclei remain polarized in a hot fusion plasma. The similarity between the Lorentz force law and the Bloch equations suggests polarization can be preserved despite the rich electromagnetic spectrum present in a magnetic fusion device. The most important depolarization mechanisms can be tested in existing devices. The use of polarized deuterium and 3 He in an experiment avoids the complexities of handling tritium, while encompassing the same nuclear reaction spin-physics, making it a useful proxy to study issues associated with full D-T implementation. 3 He fuel with 65% polarization can be prepared by permeating optically-pumped 3 He into a shell pellet. Dynamically polarized 7 Li-D pellets can achieve 70% vector polarization for the deuterium. Cryogenically-frozen pellets can be injected into fusion facilities by special injectors that minimize depolarizing field gradients. Alternatively, polarized nuclei could be injected as a neutral beam. Once injected, the lifetime of the polarized fuel is monitored through measurements of escaping charged fusion products. Multiple experimental scenarios to measure the polarization lifetime in the DIII-D tokamak and other magnetic-confinement facilities are discussed, followed by outstanding issues that warrant further study.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1982

Tests of a D vented thrust deflecting nozzle behind a simulated turbofan engine

A D vented thrust deflecting nozzle applicable to subsonic V/STOL aircraft was tested behind a simulated turbofan engine in the verticle thrust stand. Nozzle thrust, fan operating characteristics, nozzle entrance conditions, and static pressures were measured. Nozzle performance was measured for variations in exit area and thrust deflection angle. Six core nozzle configurations, the effect of core exit axial location, mismatched core and fan stream nozzle pressure ratios, and yaw vane presence were evaluated. Core nozzle configuration affected performance at normal and engine out operating conditions. Highest vectored nozzle performance resulted for a given exit area when core and fan stream pressure were equal. Its is concluded that high nozzle performance can be maintained at both normal and engine out conditions through control of the nozzle entrance Mach number with a variable exit area.

Watson, T. L.↗