Expectations You will understand how

1

• Lesson objective - to show how individual air
  vehicle design variables can be integrated into
  an overall .
• Optimized air vehicle
• for ...
• Breguet range and endurance type designs

• Expectations - You will understand how
• To apply the air vehicle performance spreadsheet
  to design optimization, trade studies and
  configuration exploration

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Design objectives

• During pre-concept design, the objective is not
  to select the best design but rather to explore a
  range of concepts and (1) select the best overall
  approach and (2) to define achievable
  requirements
• If we do not employ a reasonably accurate and
  consistent comparison process, invalid selections
  could be made on the basis of inconsistent, hasty
  or immature assessments
• During conceptual design, the objective is
  similar but focuses on finding the best design
  and design features
• This also requires use of an accurate and
  consistent comparison process to ensure viable
  design decisions
• We now have the data and component methodologies
  to do this for subsonic ICProp, TBProp and TBFan
  UAVs
• Including simple geometry models that integrate
  key configuration design features with the
  performance models to ensure physical constraints
  are not violated

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Concept exploration
Exploring a design space is an important part of
the concept evaluation process - Typically, a
wide range of concepts are drawn, analyzed and
compared and a few are selected for more study -
Configuration designers sit in the middle of this
process and are skilled at laying out
configuration study matrices to explore the most
important design and operational issues - They
typically use specialized design and analysis
tools that minimize the hand labor required to
explore these options - Students, however,
seldom have such tools and configuration
exploration becomes a time consuming process of
draw-analyze-discover problems-redraw-reanalyze
and very few options are really explored We can
bypass this laborious process by applying
spreadsheet analysis tools to concept exploration
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Sizing vs. exploration
The term sizing is typically used to describe
the process one goes through to determine the air
vehicle size required to meet design
requirements - This is basically what an
integrated spreadsheet model will do - We input
requirements and it outputs size and weight - But
because it rigorously maintains proper geometric
relationships as it adjusts to changing
requirements, it can also be used to explore a
wide range of concepts - Most sizing programs
dont do this, most are based on parametric
inputs that do not capture subtle geometry
changes as designs scale up and down in size
and/or inputs change
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Comparison approach

• Configuration comparisons need to be based on
  accurate and consistent data
• - We have data of both types
• - Our methodologies are rigorously consistent but
  of unknown accuracy
• - Our parametric data is accurate by definition
  but of questionable consistency
• - A combination of the two will give us what we
  need to compare the candidate configurations
• We will start by calculating performance against
  a consistent set of requirements
• - Range, takeoff distance, rate of climb at
  altitude, etc.
• Then we compare our results to parametrics
• - There will always be differences or issues to
  resolve
• Finally we will go back to our models to assess
  the impact of the differences or issues on the
  concepts

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Configuration optimization

• Many design and performance variable to trade
• Thrust or Horsepower-to weight a design
  variable but primarily driven by requirements
• Fuel fraction another requirement driven
  variable
• Engine type and/or BPR a design option that is
  heavily influenced by design (speed and altitude)
  requirements
• Wing loading a true optimization variable (but
  not exactly straight-forward)
• Aspect ratio a true optimization variable
• Fuselage L/D another true optimization variable
• Speed/altitude yet another true optimization
  variable
• Technology level an independent design variable
  that may or may not be a cost effective trade

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Power or Thrust-to weight

• Engines are sized to meet performance
  requirements
• Takeoff
• Rate of climb
• Acceleration
• Specific excess power (Ps)
• Vmax
• Growth considerations
• Etc.
• Any more than minimum size engine is a size
  penalty
• More engine than minimum required adds weight
• And may require it to operate at throttle
  settings less than optimum for SFC/TSFC
• But future growth or reliability considerations
  can result in selection of an oversized engine
• Engines that dont have to work hard, last longer

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Fuel fraction

• Fuel fraction (FF) is also driven by performance
  requirements
• Cruise range
• Operational endurance
• Growth
• Reserves
• Etc.
• Any more than minimum required is a size penalty
• Always
• Having more fuel than required simply adds weight
• And may make it more difficult to stay within
  center of gravity (c.g.) limits throughout the
  mission
• But again, future growth considerations can
  offset decision to minimize size

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Engine type and/or BPR

• Engine selection is driven by speed, altitude and
  cost/reliability/availability considerations
• ICProp engines are relatively inexpensive but
  heavy and constrained by size (lt400 hp), fuel
  type (AvGas), reliability (lt2000 hour Mean Time
  Between Overhaul) and speed (typically 250 kts)
• TBProps are more expensive but use less volatile
  fuels (Jet A), are lighter weight, more reliable
  and operate at higher speeds (typically 350
  kts)
• TBFans have benefits similar to TBProps but are
  even lighter and more reliable and operate at
  higher speeds (High BPR _at_ 350-500 kts, Low BPR
  w/o after burner _at_ 500-600 kts, Low BPR with
  after burner _at_ 600 to more than 1000 kts)

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Wing loading

• Wing loading (W0/Sref) would appear to be a
  straight-forward design variable
• Increased wing loading ? smaller wing, reduced
  drag, higher takeoff and landing speeds and
  higher cruise/loiter lift coefficients
• W0/Sref, however, drives fundamental geometry
• Primarily Swet/Sref, a LoDmax driver
• For a given fuselage size, therefore, increasing
  W0/Sref reduces LoDmax
• The benefits of operating closer to Cl for LoDmax
  can be offset by LoDmax reduction
• Best way to optimize W0/Sref is to do integrated
  mission level performance trades
• - Known as carpet plots (see RayAD Fig 19.6)

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Aspect ratio

• For given wing area, Aspect Ratio (AR) drives
  wing span and, consequently, LoDmax
• This is moderated, however, by a reduction in
  Oswald wing efficiency (see chart 16-6)
• Nonetheless, increased AR increased LoDmax
• There are, however, other high AR considerations
• Primarily wing bending moment (a weight driver),
  maneuverability and flutter
• Wing bending moment drives wing weight
• Not captured by our simple unit wing weight (UWW)
  methodology (See RayAD Eq 15.1, 15.25, 15.46)
• Wing span increases roll inertia and damping,
  roll performance suffers except at low speed
• Flutter speed decreases, a problem for High AR
  wings

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Flutter concerns

• Our example TBProp UAV has a relatively high AR
  for an air vehicle that flies at an equivalent
  air speed (EAS) of 242 Kts (282 KTAS _at_ 10Kft )
• It could flutter (a catastrophic failure mode) at
  this speed
• We have options for dealing with the risk
• Assume we can solve the problem later, e.g. use
  new

• materials or active flutter suppression
• Reduce AR to lower value (12? or 15?)
• Design a fix (e.g., a quick change wing or
  removable outer wing panel for the ID mission)

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Practical constraints

• Aerodynamics
• Our spreadsheet model keeps fuselage size and/or
  payload fixed
• - When we try to optimize a configuration by
  increasing wing loading, we change fundamental
  area ratios
• - For example, if we increase W0/Sref by 50 on
  our example TBProp Swet will drop by 25,
  Swet/Sref will increase by 28 and LoDmax will
  decrease by 12
• - To maintain LoD as Sref is reduced, AR has to
  increase
• - Another constraint is lift coefficient for
  LoDmax. When we increase AR to maintain LoD,
  we can reach a point where the Cl required gets
  too close to Cl-stall (1.2)
• LoDmax 0.5sqrt((?eAR/Cfe)(Swet/Sref))
• Cl(LoDmax) sqrt (?AReCfe(Swet/Sref))

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Constraints contd

• Airframe weight
• - When we try to reduce wing area while keeping
  fuselage size fixed, we also change fundamental
  weight drivers
• - Recall that wing weights per unit reference
  area (Sref) run about two times fuselage unit
  weights per unit Swet
• - As we reduce wing size relative to the
  fuselage, therefore,

overall airframe unit weight increases. For
example . - If we increase W0/Sref by 50, the
spreadsheet model Waf/Sref increases about 30 -
The parametric weight data shows a similar effect
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Speed and altitude optimization

• RayAD (Chapter 5) differentiates between best
  cruise speeds for propeller powered aircraft and
  jets
• Jets cruise at speed where Cdmin 3?Cdi
• Prop powered aircraft cruise at Cdmin Cdi
  (LoDmax)
• We will simply solve numerically for the speed
  that yields best range and/or endurance
• Depending on mission requirements
• Cruise altitude can be optimized in a similar
  manner but generally
• ICProps (un turbocharged) cruise best at 8-12 Kft
• TBProps cruise best at 15-25 Kft
• TBFans and TBJets cruise best at gt 36 Kft

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Fuselage Lf/Df

• Increased Lf/Df drives fuselage weight and drag
• Profile drag decreases (inversely ? to wetted
  area)
• Weight (? to wetted area) increases
• Friction drag (? to wetted area) also increases
• Weight and friction drag (wetted area) effects
  are captured by our parametric geometry model
  approach
• With reasonable accuracy
• Profile drag effects are not captured
• RayAD (Eq 12.31) component drag Form Factors
  (ff), however, do capture the effects where
• Form Factor (fuse) 160/(Lf/Df)3(Lf/Df)/4
  00
• Cdmin ?Cfe(i)?ff(i)?Swet(i)/Sref
• So that
• Fuselage drag ?? ff?Swet(fuse)/Swet

and
Lf/DF basically reduces to a trade of fuselage
weight vs. drag
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Technology considerations

• We can also use our spreadsheet methods to
  evaluate technology impacts, e.g. using
  composites to reduce airframe weight (which cost
  more) to see if we get payback in terms of
  reduced overall empty weight
• - Example 25 airframe weight reduction at 35
  cost increase (Project RAND, Advanced Airframe
  Structural Materials, R-4016-AF)

• - We can capture this effect by putting a 0.75
  multiplier on airframe unit weight and a 1.35
  multiplier on airframe cost per pound
• We can also see a small cross functional impact
• - Propulsion
• - Aero

Aluminum
Composites
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Spreadsheet example
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Results - Initial WAS baseline
W0 2907 lbm EW 1504 lbm W0/Sref 30 AR
20 Sref 97sqft Swet 454 sqft Payload 720
lbm Fuel 654 lbm Power 306 Bhp TBProp Max
endurance 15.5 hrs Max speed 280 kts
Approximately to scale
44
This air vehicle can stay on station at 17Kft for
12 hours at an operating radius of 255 nm or
perform 1.97 IDs at 10Kft at an operating radius
of 200 nm and speed of 282 kts
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Results - Initial ID baseline
W0 25221 lbm EW 10852 lbm W0/Sref 30 AR
20 Sref 840sqft Swet 2902 sqft Payload 720
lbm Fuel 13362 lbm Power 2308 Bhp TBProp Max
endurance 15.5 hrs Max speed 280 kts
Approximately to scale
130
This air vehicle can perform 12 IDs at 10Kft for
12 hours at an operating radius of 200 nm and
speed of 282 kts or stay on station at 17Kft for
12 hours at an operating radius of 255 nm
D
4.8
33.5
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Results Trade studies

• Wing loading
• 175 lbm EW sensitivity
• Optimum at 33
• With Vcr optimization
• Aspect Ratio
• ? 125 lbm EW sensitivity
• Weight may optimize above reasonable AR for max
  speed
• EW penalty at AR 15 reduces to 67 lbm with
  cruise speed optimization

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Results Trade studies

• WAS Cruise speed
• 5 lbm EW sensitivity
• Optimum at 153 kts
• Airframe Technology
• ? 370 lbm EW sensitivity
• EW optimizes at lightest airframe technology
  value
• If airframe /lb increases more than weight
  decreases (25), cost trade will be unfavorable

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Results Trade studies

• Fuselage Lf/DF
• Higher Lf/Df reduces fuselage profile drag
• Friction drag (Swet) increases
• Fuselage weight too
• Overall drag drops by 3.5
• Overall effect
• ? 115 lbm EW sensitivity
• Optimizes at minimum value
• Intuitively looks low for 282 kt dash speed
  requirement
• 65 lbm penalty if have to go to next higher Lf/DF

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Results - Optimized WAS baseline
W0 2837 lbm EW 1432 lbm W0/Sref 33.1 AR
20 Sref 86sqft Swet 424 sqft Payload 720
lbm Fuel 657 lbm Power 287 Bhp TBProp Max
endurance 15.2 hrs Max speed 280 kts
Approximately to scale
44
This air vehicle can stay on station at 17Kft for
12 hours at an operating radius of 255 nm or
perform 2.33 IDs at 10Kft at an operating radius
of 200 nm and speed of 282 kts
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Results - Optimized WAS, AR 15
W0 3050 lbm EW 1521 lbm W0/Sref 32.6 AR
15 Sref 93sqft Swet 448 sqft Payload 720
lbm Fuel 778 lbm Power 304 Bhp TBProp Max
endurance 15.0 hrs Max speed 280 kts
Approximately to scale
37.4
This air vehicle can stay on station at 17Kft for
12 hours at an operating radius of 255 nm or
perform 2.63 IDs at 10Kft at an operating radius
of 200 nm and speed of 282 kts
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Parametrics AR 15
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Expectations

• You should now understand
• Overall air vehicle optimization
• How its done
• How to test the validity of the results

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Homework

• Use your spreadsheet to evaluate (plot) EW
  sensitivity to the following and select the best
  overall design
• Wing loading (select best of 3)
• (c) Aspect ratio (select best of 3)
• (d) Fuselage fineness ratio (compare 3)
• (e) Cruise speed (solve for optimum)
• 2. For 1x extra credit, if your concept is a
  ICProp, compare EW vs. TBProp and select best
  option (dont forget engine size effects per
  chart 18-13), if TBProp, compare to ICProp and
  select, if TBFan, plot/select best of 3 BPRs
  (dont forget to adjust Fan Fsp per chart 18-38)
• 3. For .5x extra credit, evaluate 2 airframe
  weight reduction technology levels (10 weight
  reduction at 10 higher cost and 25 weight
  reduction at 35 higher cost) and explain which
  is most cost effective and why

Make sure (1) all aero-propulsion reqments are
satisfied and (2) consistent performance criteria
are used by the entire team
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Intermission
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