A bibliography of six years (1951-1956) research in arithmetic

Thesis (Ed.M.)--Boston Universit

Multivariate Analysis, Retrieval, and Storage System (MARS). Volume 6: MARS System - A Sample Problem (Gross Weight of Subsonic Transports)

The Mars system is a tool for rapid prediction of aircraft or engine characteristics based on correlation-regression analysis of past designs stored in the data bases. An example of output obtained from the MARS system, which involves derivation of an expression for gross weight of subsonic transport aircraft in terms of nine independent variables is given. The need is illustrated for careful selection of correlation variables and for continual review of the resulting estimation equations. For Vol. 1, see N76-10089

Angle-of-attack analysis of a spinning slender cone with slight aerodynamic and mass asymmetries /reentry F/

Angle of attack analysis of spinning slender reentry cone with slight aerodynamic and mass asymmetrie

Multivariate Analysis, Retrieval, and Storage System (MARS). Volume 1: MARS System and Analysis Techniques

A method for rapidly examining the probable applicability of weight estimating formulae to a specific aerospace vehicle design is presented. The Multivariate Analysis Retrieval and Storage System (MARS) is comprised of three computer programs which sequentially operate on the weight and geometry characteristics of past aerospace vehicles designs. Weight and geometric characteristics are stored in a set of data bases which are fully computerized. Additional data bases are readily added to the MARS system and/or the existing data bases may be easily expanded to include additional vehicles or vehicle characteristics

A diagnostic model for studying daytime urban air quality trends

A single cell Eulerian photochemical air quality simulation model was developed and validated for selected days of the 1976 St. Louis Regional Air Pollution Study (RAPS) data sets; parameterizations of variables in the model and validation studies using the model are discussed. Good agreement was obtained between measured and modeled concentrations of NO, CO, and NO2 for all days simulated. The maximum concentration of O3 was also predicted well. Predicted species concentrations were relatively insensitive to small variations in CO and NOx emissions and to the concentrations of species which are entrained as the mixed layer rises

Multivariate Analysis, Retrieval, and Storage System (MARS). Volume 4: Turbojet and Turbofan Data Base (By Engine)

A partial listing of turbojet and turbofan engine specifications data, as provided by the MARS (Multivariable Data Analysis, Retrieval, and Storage) system, was given for a number of engines

Minimum relative entropy, bayes and kapur

The focus of this paper is to illustrate important philosophies on inversion and the 6 similarly and differences between Bayesian and minimum relative entropy (MRE) 7 methods. The development of each approach is illustrated through the general-8 discrete linear inverse. MRE differs from both Bayes and classical statistical meth-9 ods in that knowledge of moments are used as "data" rather than sample values. 10 MRE, like Bayes, presumes knowledge of a prior probability distribution (pdf) and 11 produces the posterior pdf itself. MRE attempts to produce this pdf based on the 12 information provided by new moments. It will use moments of the prior distribution 13 only if new data on these moments is not available. It is important to note that MRE 14 makes a strong statement that the imposed constraints are are exact and complete. 15 In this way, MRE is maximally uncommitted with respect to unknown information. 16 In general, since input data are known only to within a certain accuracy, it is im-17 portant that any inversion method should allow for errors in the measured data. 18 The MRE approach can accommodate such uncertainty and in new work describe