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Mass prediction models for air cargo challenge aircraft

Published online by Cambridge University Press:  10 August 2021

G.L. Garcia
Affiliation:
Centre for Mechanical and Aerospace Science and Technologies (C-MAST-UBI), Universidade da Beira Interior, Covilhã, Portugal
P.V. Gamboa*
Affiliation:
Centre for Mechanical and Aerospace Science and Technologies (C-MAST-UBI), Universidade da Beira Interior, Covilhã, Portugal
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Abstract

Design/Build/Fly competitions are attracting increased interest in the training of aerospace engineers at academic level worldwide. These competitions entail fundamental activities in aircraft design, optimization and manufacturing which foster student knowledge not possible in classical academic activities. Over the years, the competitiveness of these contests has increased due to the ever-increasing performance that the aircraft exhibit in the flight event. Mass prediction models, specific for competitions such as Air Cargo Challenge (ACC), are presented in this paper. These models are divided into two development methods: statistical and structure-based equations.

The statistical mass models are developed based on data collected from past ACC editions where model accuracy is mainly dependent on the amount of data available. Three models are derived, one containing all available aircraft and two more obtained by dividing the aircraft into balsa- or composite-dominated structures.

Using the structure-based equations method, where the amount of material required to withstand the stresses that the airplane is subjected to is determined, a model is developed for each one of the three considered wing structural concepts, namely two-cell Carbon-Fibre-Reinforced Plastic (CFRP), CFRP D-box and CFRP tube spar. The tail boom component equation is created independently, while the remaining components masses are determined from coefficients based on geometric characteristics and the computed wing or total masses. The average error associated with these models is inferior to 2% for the total mass.

The results obtained from the application to the considered study cases are also presented, and the validity, accuracy, and application in terms of the design phase for each method are discussed.

Information

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society
Figure 0

Figure 1. Typical ACC aircraft geometry.

Figure 1

Figure 2. Wing planform shapes: (a) constant-chord (single panel) wing example and (b) tapered (multiple panels) wing example.

Figure 2

Figure 3. Structural wing concepts representation: (a) load-bearing skin wing, (b) D-box wing and (c) circular tube spar wing.

Figure 3

Figure 4. Further geometric parameters for the composite sandwich skin concepts: (a) load-bearing skin wing and (b) D-box wing.

Figure 4

Figure 5. Wing loading conditions: (a) spanwise lift distribution and (b) ground test loads.

Figure 5

Figure 6. Wing and tail boom deflections: (a) wing tip deflection due to bending and (b) wing tip twist due to torsion and tail boom rotation due to bending.

Figure 6

Figure 7. Real and approximate aerofoil lift distribution(1).

Figure 7

Table 1 Aircraft data collected from ACC design reports used to build the statistical mass models

Figure 8

Figure 8. Statistical mass model results: (a) all aircraft, (b) balsa aircraft and (c) composite aircraft. Symbols: square – 2007; delta – 2009; gradient – 2011; right-triangle – 2013; diamond – 2015; circle – 2017; hollow – mostly balsa; solid – mostly composite.

Figure 9

Table 2 Aircraft data collected from ACC design reports used to validate the statistical mass models

Figure 10

Figure 9. Statistical mass model validation results: (a) all aircraft, (b) balsa aircraft and (c) composite aircraft. Symbols: delta – 2009; right-triangle – 2013; diamond – 2015; left-triangle – 2019; hollow – mostly balsa; solid – mostly composite.

Figure 11

Figure 10. Aircraft used to adjust the structure-based mass model correction factors: (a–c) load-bearing skin wing concept, (d, e) D-box wing concept and (f–h) circular tube spar wing concept for the (a) AKAModell13 – AKA13, (b) AERO@UBI_MARS – MAR17, (c) AERO@UBI_2019 – UBI19, (d) TIGERS – TIG13, (e) AERO@UBI_PVG – PVG17, (f) Portugal_Team – UBI11, (g) Beihang GRAVITY – GRA13 and (h) AERO@UBI_Team – UBI15.

Figure 12

Table 3 General input parameters

Figure 13

Table 4 Specific inputs for carbon fibre load-bearing skin wing concept

Figure 14

Table 5 Material properties for carbon fibre load-bearing skin wing concept

Figure 15

Figure 11. General mass correction factors: (a) horizontal tail, (b) vertical tail, (c) cargo bay and (d) landing gear.

Figure 16

Table 6 Correction factors for carbon fibre load-bearing skin wing concept

Figure 17

Table 7 AKAModell13, AERO@UBI_MARS and AERO@UBI_2019 real/reported and calculated masses

Figure 18

Table 8 Specific inputs for D-box wing concept

Figure 19

Table 9 Material properties for D-box concept

Figure 20

Table 10 Correction factors for D-box wing concept

Figure 21

Table 11 TIGERS and AERO@UBI_PVG real/reported and calculated masses

Figure 22

Table 12 Specific inputs for circular tube spar wing concept

Figure 23

Table 13 Material properties for circular tube spar wing concept

Figure 24

Table 14 Correction factors for circular spar tube wing concept

Figure 25

Table 15 Portugal_Team, GRAVITY and AERO@UBI_Team real/reported and calculated masses

Figure 26

Figure 12. Structure-based mass model results: (a) empty mass and (b) total mass. Symbols: delta – two-cell load-bearing skin wing concept; diamond – D-box wing concept; circle – tube spar wing concept.