Heat transfer of gas-particle flow in a supersonic convergent-divergent nozzle.
Heat transfer rates in turbulent flow of heated gas-solid mixtures through converging-diverging nozzle
Diem, H. G.↗
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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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On the Bhattacharyya distance and the divergence between Gaussian processes.
Divergence and Bhattacharyya distance between Gaussian processes, evaluating filter design and signal selection
Schweppe, F. C.↗
Convergent-divergent nozzle flows.
Convergent-divergent nozzle flow field solution obtained in form of perturbation about one dimensional flow field
Kliegel, J. R.↗
Water flow and cavitation in converging- diverging boiler-inlet nozzle
Water flow and cavitation in convergent-divergent boiler inlet nozzles
Sekas, N. J.↗
Analysis of the aeroelastic divergence of two experimental unguided launch vehicles
Analysis of aeroelastic divergence phenomena in unguided launch vehicles
Young, C. P., Jr.↗
Investigation of a plasma accelerator with magnetic field arranged to produce a divergent-nozzle effect
Plasma accelerator with magnetic field producing divergent-nozzle effect
Beasley, W. D.↗
Effect of induced stress on convergent and divergent thinking.
Psychological stress effect on human convergent and divergent thinking after presentation of disturbing or benign control films
Alegre, C. E.↗
Transonic flow in a converging-diverging nozzle Final report
Computerized solutions to finite difference equations of motion of transonic flow in converging-diverging rocket nozzles
Prozan, R. J.↗
Some performance characteristics of divergent- field bombardment thrusters
Performance characteristics of electron bombardment thrusters using highly divergent magnetic fields and mercury propellant
Kaufman, H. R.↗
Electrostatic Propulsion Beam Divergence Effects on Spacecraft Surfaces, Volume 1 Final Report
Electrostatic propulsion beam divergence effects on spacecraft surfaces - Vol. 1
Hall, D. F.↗
On the divergent growth of molecular fluctuations in classical shear flow
Two point hydrodynamic equation for molecular fluctuations divergent growth in classical shear flow via B-B-G-K-Y procedure and double series moment expansion
Tsuge, S.↗
Transonic flow in a converging-diverging nozzle Final report
Transonic equations of motion for convergent-divergent nozzle
Coats, D. E.↗
Electrostatic propulsion beam divergence effects on spacecraft surfaces Quarterly technical report, 25 Jul. - 23 Oct. 1970
Effects of electrostatic propulsion beam divergence effects on spacecraft surfaces
Source record↗
An experimental investigation of panel divergence at subsonic speeds
Panel flutter and divergence as structural aeroelastic problems leading to fatigue failure
Gislason, T., Jr.↗
Alleviation of divergence during rocket launch Patent
Design and characteristics of linkage to alleviate rocket vehicle divergence during launch
Gillespie, W., Jr.↗
Supersonic asymmetric flutter and divergence of truncated conical shells with ring supported edges
Supersonic asymmetric flutter and divergence characteristics of truncated conical shells with ring-supported edges under three types of flow-induced instabilities
Dixon, S. C.↗
Turbulent boundary layer and heat transfer measurements along a convergent-divergent nozzle
Turbulent boundary layer and heat transfer measurements along cooled conical convergent- divergent nozzle
Back, L. H.↗
Decision-directed adaptive recursive estimators - Divergence prevention.
A method is proposed for dealing with the divergence phenomenon problem encountered in applications of minimum-variance recursive estimators when the error covariance calculated by the estimator becomes inconsistent with the actual error covariance. The proposed method differs from previous ones in that the state model and statistics are accepted as given. The form of the optimal estimator is used, but a constant check is made on the consistency of the calculated and actual error covariances. The method is independent of the source of error, whether it be inaccuracies in the system model, incorrect values of the a priori and random process statistics, approximations required in the case of nonlinear systems, or computational roundoff. Several simulated examples, in which inconsistencies in the calculated and actual error covariances exist, show a significant improvement in the performance of the estimator when the given procedure is applied.
Nahi, N. E.↗