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NASA Scientific and Technical Aerospace Reports

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spatial ability (Waller, 1999), several additional st<strong>and</strong>ardized metrics were utilized to assess process measures, including<br />

spatial ability (Ekstrom, French, &amp; Harman, 1976), navigation skill (Hegarty, Richardson, Montello, Lovelace, &amp;<br />

Subbiah, 2002) , workload (Hart &amp; Stavel<strong>and</strong>, 1988) , self-efficacy (Scott, 2000) <strong>and</strong> simulator sickness (Kennedy, Lane,<br />

Serbaum, &amp; Lilienthal, 1993). To assess terrain association skill, a test was developed in which participants were asked<br />

to correlate out- the-window views with topographical maps <strong>and</strong> vice versa.<br />

DTIC<br />

Air Navigation; Education; Navigation; Space Perception; Spatial Distribution<br />

05<br />

AIRCRAFT DESIGN, TESTING AND PERFORMANCE<br />

Includes all stages of design of aircraft <strong>and</strong> aircraft structures <strong>and</strong> systems. Also includes aircraft testing, performance, <strong>and</strong> evaluation,<br />

<strong>and</strong> aircraft <strong>and</strong> flight simulation technology. For related information see also 18 Spacecraft Design, Testing <strong>and</strong> Performance; <strong>and</strong> 39<br />

Structural Mechanics. For l<strong>and</strong> transportation vehicles see 85 Technology Utilization <strong>and</strong> Surface Transportation.<br />

20040068163 <strong>NASA</strong> Langley Research Center, Hampton, VA, USA<br />

Wind Tunnel to Atmospheric Mapping for Static Aeroelastic Scaling<br />

Heeg, Jennifer; Spain, Charles V.; Rivera, J. A.; [2004]; 12 pp.; In English; 45th AIAA/ASME/ASCE/AHS/ASC Structures,<br />

Structural Dynamics <strong>and</strong> Materials Conference, 19-22 Apr. 2004, Palm Springs, CA, USA<br />

Contract(s)/Grant(s): 23-762-20-31<br />

Report No.(s): AIAA Paper 2004-2044; No Copyright; Avail: CASI; A03, Hardcopy<br />

Wind tunnel to Atmospheric Mapping (WAM) is a methodology for scaling <strong>and</strong> testing a static aeroelastic wind tunnel<br />

model. The WAM procedure employs scaling laws to define a wind tunnel model <strong>and</strong> wind tunnel test points such that the<br />

static aeroelastic flight test data <strong>and</strong> wind tunnel data will be correlated throughout the test envelopes. This methodology<br />

extends the notion that a single test condition - combination of Mach number <strong>and</strong> dynamic pressure - can be matched by wind<br />

tunnel data. The primary requirements for affecting this extension are matching flight Mach numbers, maintaining a constant<br />

dynamic pressure scale factor <strong>and</strong> setting the dynamic pressure scale factor in accordance with the stiffness scale factor. The<br />

scaling is enabled by capabilities of the <strong>NASA</strong> Langley Transonic Dynamics Tunnel (TDT) <strong>and</strong> by relaxation of scaling<br />

requirements present in the dynamic problem that are not critical to the static aeroelastic problem. The methodology is<br />

exercised in two example scaling problems: an arbitrarily scaled wing <strong>and</strong> a practical application to the scaling of the Active<br />

Aeroelastic Wing flight vehicle for testing in the TDT.<br />

Author<br />

Wind Tunnel Models; Atmospheric Models; Aeroelasticity; Wind Tunnel Tests<br />

20040068182 <strong>NASA</strong> Ames Research Center, Moffett Field, CA, USA<br />

CAD-Based Aerodynamic Design of Complex Configurations using a Cartesian Method<br />

Nemec, Marian; Aftosmis, Michael J.; Pulliam, Thomas H.; December 15, 2003; 13 pp.; In English; 42nd AIAA <strong>Aerospace</strong><br />

Sciences Conference, 5-8 Jan. 2004, Reno, NV, USA<br />

Report No.(s): AIAA Paper 2004-0113; No Copyright; Avail: CASI; A03, Hardcopy<br />

A modular framework for aerodynamic optimization of complex geometries is developed. By working directly with a<br />

parametric CAD system, complex-geometry models are modified nnd tessellated in an automatic fashion. The use of a<br />

component-based Cartesian method significantly reduces the dem<strong>and</strong>s on the CAD system, <strong>and</strong> also provides for robust <strong>and</strong><br />

efficient flowfield analysis. The optimization is controlled using either a genetic or quasi-Newton algorithm. Parallel efficiency<br />

of the framework is maintained even when subject to limited CAD resources by dynamically re-allocating the processors of<br />

the flow solver. Overall, the resulting framework can explore designs incorporating large shape modifications <strong>and</strong> changes in<br />

topology.<br />

Author<br />

Computer Aided Design; Aerodynamic Configurations; Optimization; Mathematical Models; Cartesian Coordinates;<br />

Automatic Control<br />

20040068309, Boeing Co., Wichita, KS, USA<br />

Bonded Repair of Aircraft Composite S<strong>and</strong>wich Structures<br />

Tomblin, J. S.; Salah, L.; Welch, J. M.; Borgman, M. D.; Feb. 2004; In English<br />

Report No.(s): PB2004-105463; No Copyright; Avail: National <strong>Technical</strong> Information Service (NTIS)<br />

8

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