Aeronautical Engineering: A special bibliography, supplement 60

This bibliography lists 284 reports, articles, and other documents introduced into the NASA scientific and technical information system in July 1975

Aeronautical Engineering: A special bibliography with indexes, supplement 67, February 1976

This bibliography lists 341 reports, articles, and other documents introduced into the NASA scientific and technical information system in January 1976

Automatic, computer aided geometric design of free-knot, regression splines

A new algorithm for Computer Aided Geometric Design of least squares (LS) splines with variable knots, named GeDS, is presented. It is based on interpreting functional spline regression as a parametric B-spline curve, and on using the shape preserving property of its control polygon. The GeDS algorithm includes two major stages. For the first stage, an automatic adaptive, knot location algorithm is developed. By adding knots, one at a time, it sequentially "breaks" a straight line segment into pieces in order to construct a linear LS B-spline fit, which captures the "shape" of the data. A stopping rule is applied which avoids both over and under fitting and selects the number of knots for the second stage of GeDS, in which smoother, higher order (quadratic, cubic, etc.) fits are generated. The knots appropriate for the second stage are determined, according to a new knot location method, called the averaging method. It approximately preserves the linear precision property of B-spline curves and allows the attachment of smooth higher order LS B-spline fits to a control polygon, so that the shape of the linear polygon of stage one is followed. The GeDS method produces simultaneously linear, quadratic, cubic (and possibly higher order) spline fits with one and the same number of B-spline regression functions. The GeDS algorithm is very fast, since no deterministic or stochastic knot insertion/deletion and relocation search strategies are involved, neither in the first nor the second stage. Extensive numerical examples are provided, illustrating the performance of GeDS and the quality of the resulting LS spline fits. The GeDS procedure is compared with other existing variable knot spline methods and smoothing techniques, such as SARS, HAS, MDL, AGS methods and is shown to produce models with fewer parameters but with similar goodness of fit characteristics, and visual quality

Aeronautical engineering: A continuing bibliography, supplement 122

This bibliography lists 303 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1980

Aeronautical Engineering: A continuing bibliography with indexes, supplement 99

This bibliography lists 292 reports, articles, and other documents introduced into the NASA scientific and technical information system in July 1978

Interference Drag Associated with Engine Locations for Multidisciplinary Design Optimization

This research aims to quantify the interference drag for various engine locations on a traditional tube and wing, 150-passenger commercial aircraft flying at 35,000 ft and Mach 0.8. Engine locations are varied in the chord wise, span wise, and vertical directions near the wing, both under and above the wing, as well as along the fuselage. Euler simulations are performed with representative powered modern engines. The results are intended to supplement empirical drag estimates suitable for multidisciplinary design environments. Large interference drag increases, as compared to the isolated air frame and engine geometry, are found to occur when the engine is placed directly above or below the wing. Interference effects are significantly reduced, and in some instances result in benefits compared to the isolated bodies, when the engines are placed fore or aft of the wing. Interference drag increases are partially explained by flow channels leading to choked flow and shock interactions between bodies

Covariate assisted screening and estimation

Consider a linear model $Y=X\beta+z$, where $X=X_{n,p}$ and $z\sim N(0,I_n)$. The vector $\beta$ is unknown but is sparse in the sense that most of its coordinates are $0$. The main interest is to separate its nonzero coordinates from the zero ones (i.e., variable selection). Motivated by examples in long-memory time series (Fan and Yao [Nonlinear Time Series: Nonparametric and Parametric Methods (2003) Springer]) and the change-point problem (Bhattacharya [In Change-Point Problems (South Hadley, MA, 1992) (1994) 28-56 IMS]), we are primarily interested in the case where the Gram matrix $G=X'X$ is nonsparse but sparsifiable by a finite order linear filter. We focus on the regime where signals are both rare and weak so that successful variable selection is very challenging but is still possible. We approach this problem by a new procedure called the covariate assisted screening and estimation (CASE). CASE first uses a linear filtering to reduce the original setting to a new regression model where the corresponding Gram (covariance) matrix is sparse. The new covariance matrix induces a sparse graph, which guides us to conduct multivariate screening without visiting all the submodels. By interacting with the signal sparsity, the graph enables us to decompose the original problem into many separated small-size subproblems (if only we know where they are!). Linear filtering also induces a so-called problem of information leakage, which can be overcome by the newly introduced patching technique. Together, these give rise to CASE, which is a two-stage screen and clean [Fan and Song Ann. Statist. 38 (2010) 3567-3604; Wasserman and Roeder Ann. Statist. 37 (2009) 2178-2201] procedure, where we first identify candidates of these submodels by patching and screening, and then re-examine each candidate to remove false positives.Comment: Published in at http://dx.doi.org/10.1214/14-AOS1243 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Aeronautical Engineering: A special bibliography with indexes, supplement 62

This bibliography lists 306 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1975