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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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Predicting characteristics of minimal total impulse solution of two-terminal, two-impulse orbital transfer problem by using bounding trajectories
Conjugate direction minimization procedure based on sequences and inferred second partial derivative matrix inverse
Minimization of unconstrained function of several variables by gradient dependent techniques, discussing applications to boundary value problems in optimal control
Minimization algorithms unified derivation, using Hessian matrix inverse
Sonic boom minimization including front and rear shocks, exemplified by SST aircraft
Minimal partial realizations of linear input/output map, discussing significance in regard to adaptive dynamics identification procedures
Recorder deficiencies are minimized by using two-channel system to prepare two tapes, each having noise, wow and flutter, and dropout characteristics of channel on which it was made. Processing tapes by computer and combining signals from two channels produce single tape free of dropouts caused by recording process.
A modified Newton-Raphson or quasilinearization minimization technique for determining stability derivatives from flight data was developed and compared with simple-equations, analog-matching, least-squares, and Shinbrot methods of analysis. For the data analyzed, the solutions computed by using the estimates obtained from the Newton-Raphson technique fit the data and determined coefficients adequately. A further modification to include a priori information was found to be useful. A model statistically similar to the flight data was analyzed using the same methods (excluding analog matching), and the Newton-Raphson technique was found to yield superior estimates. An approximate Cramer-Rao bound was compared with the error covariance matrix of the model and was found to provide information about the reliability of the individual estimates obtained. The technique was successfully applied to data obtained from a light airplane, a large supersonic airplane, and a lifting body vehicle. It was shown that the reliability of the estimates of a given coefficient obtained from these vehicles depends upon the data analyzed.
A mathematical expression was derived describing multipacting and corona effects in a coaxial cavity. Both mechanical and electrical design techniques were investigated to minimize the susceptibility of coaxial cavity to corona and multipacting-type breakdown. To assist in the design of a multicoupler free from corona and multipactor breakdown, a flow chart obtained from the derived mathematical expression is included.
The applicability of sonic boom minimization concepts in the design of large supersonic transport airplanes capable of a 2500-nautical-mile range at a cruise Mach number of 2.7 is considered. Aerodynamics, weight and balance, and mission performance as well as sonic boom factors, have been taken into account. The results indicate that shock-strength nominal values of somewhat less than 48 newtons/sq m during cruise are within the realm of possibility. Because many of the design features are in direct contradiction to presently accepted design practices, further study of qualified airplane design teams is required to ascertain sonic boom shock strength levels actually attainable for practical supersonic transports.
CONMIN is a FORTRAN program, in subroutine form, for the solution of linear or nonlinear constrained optimization problems. The basic optimization algorithm is the Method of Feasible Directions. The user must provide a main calling program and an external routine to evaluate the objective and constraint functions and to provide gradient information. If analytic gradients of the objective or constraint functions are not available, this information is calculated by finite difference. While the program is intended primarily for efficient solution of constrained problems, unconstrained function minimization problems may also be solved, and the conjugate direction method of Fletcher and Reeves is used for this purpose. This manual describes the use of CONMIN and defines all necessary parameters. Sufficient information is provided so that the program can be used without special knowledge of optimization techniques. Sample problems are included to help the user become familiar with CONMIN and to make the program operational.
An alternative method for deriving the generalized inverse of an arbitrary rectangular matrix with real or complex coefficients is described. The method applies a classical minimization procedure without iteration processes and is readily applicable in digital computer programming.
The prime power requirements of a coupling-modulated gas laser transmitter are presented. The latter consists of a gas discharge tube and electro-optic modulator inside a laser resonator. In performing the calculations, the laser discharge length and the modulator voltage are simultaneously varied so that the transmitted power remains constant. In this way, tradeoffs can be made between the prime power supplied individually to the discharge tube and to the modulator driver to obtain a transmitter configuration which minimizes the total prime power consumption. An analytical expression is derived which describes the effects of information bandwidth and transmitter output power on the prime power requirements. Specific numerical results are obtained for a CO2 laser transmitter based on presently available experimental data.
A recursive procedure is derived for decoding of rate R=1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e. fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications such as in the inner coding system for concatenated coding.
The use of pendulum dynamic absorbers mounted on the blade root and operating in the vertical plane to minimize helicopter vibratory loads was discussed. A qualitative description was given of the concept of the dynamic absorbers and some results of analytical studies showing the degree of reduction in vibratory loads attainable are presented. Operational experience of vertical plane dynamic absorbers on the OH-6A helicopter is also discussed.
A recursive procedure is derived for decoding of rate R = 1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit, subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e., fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications, such as in the inner coding system for concatenated coding.
A method is described for minimizing the sensitivity of multivariable systems to parameter variations. The variable parameters are considered as random variables and their effect is included in a quadratic performance index. The performance index is a weighted sum of the state and control covariances that stem from both the random system disturbances and the parameter uncertainties. The numerical solution of the problem is described and application of the method to several initially sensitive tracking systems is discussed. The sensitivity factor of reduction was typically 2 or 3 over a system based on random system noise only, and yet resulted in state RMS increases of only about a factor of two.
Technique has been developed for determining values of selected subsets of independent variables in mathematical formulations. Required computation time increases with first power of the number of variables. This is in contrast with classical minimization methods for which computational time increases with third power of the number of variables.