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{ "item_title" : "Model Update of a Micro Air Vehicle (Mav) Flexible Wing Frame with Uncertainty Quantification", "item_author" : [" Nasa Technical Reports Server (Ntrs) "], "item_description" : "This paper describes a procedure to update parameters in the finite element model of a Micro Air Vehicle (MAV) to improve displacement predictions under aerodynamics loads. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with Multidisciplinary Design Optimization (MDO) is used to modify key model parameters. Static test data collected using photogrammetry are used to correlate with model predictions. Results show significant improvements in model predictions after parameters are updated; however, computed probabilities values indicate low confidence in updated values and/or model structure errors. Lessons learned in the areas of wing design, test procedures, modeling approaches with geometric nonlinearities, and uncertainties quantification are all documented.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/1/28/726/945/1287269451_b.jpg", "price_data" : { "retail_price" : "14.75", "online_price" : "14.75", "our_price" : "14.75", "club_price" : "14.75", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Model Update of a Micro Air Vehicle (Mav) Flexible Wing Frame with Uncertainty Quantification|Nasa Technical Reports Server (Ntrs)

Model Update of a Micro Air Vehicle (Mav) Flexible Wing Frame with Uncertainty Quantification

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Overview

This paper describes a procedure to update parameters in the finite element model of a Micro Air Vehicle (MAV) to improve displacement predictions under aerodynamics loads. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with Multidisciplinary Design Optimization (MDO) is used to modify key model parameters. Static test data collected using photogrammetry are used to correlate with model predictions. Results show significant improvements in model predictions after parameters are updated; however, computed probabilities values indicate low confidence in updated values and/or model structure errors. Lessons learned in the areas of wing design, test procedures, modeling approaches with geometric nonlinearities, and uncertainties quantification are all documented.

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Details

  • ISBN-13: 9781287269458
  • ISBN-10: 1287269451
  • Publisher: Bibliogov
  • Publish Date: July 2013
  • Dimensions: 9.69 x 7.44 x 0.05 inches
  • Shipping Weight: 0.13 pounds
  • Page Count: 22

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