An Improved Process for Mapping Aeroelastic Loads Across Structural Meshes

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An Improved Process for Mapping Aeroelastic Loads
Across Structural Meshes

• Douglas J. Neill,
• Jack F. Castro, Patricia E. Jones
• MSC.Software Corporation

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Agenda

• Typical loads processes and issues
• Proposed process
• The ADB/AEDB collections
• Methodology
• Results
• Summary

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An Aeroelastic Loads Process
Critical Loads Survey Stress Group Other tools
Rigid Aero Loads AIC
Corrected Loads On Internal Loads FE
Flexibility FE
Aeroelastic Solver
Loads Transfer Tools
Corrected Loads On Coarse FE
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Issues with Typical Process

• 2 common approaches to transfer coarse loads to
  the internal loads model
• Smearing component integrated loads
• Heuristic
• Prone to error
• Slow, engineer-in-the-loop
• Loss of balance during smear
• Re-balancing is itself heuristic and slow
• Common Loads Points
• Difficult to coordinate
• Tends to degrade FE model quality
• Degrades computational performance

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Issues with Typical Process

• The outlined approach works, but its a problem
  in many organizations
• Too slow
• Cannot keep up with critical loads survey needs
• Too easy to make mistakes
• Cannot be repeated reliably
• Too many engineer-in-the-loop heuristics
• Too easy to lose the association of loading event
  (on coarse FE) to critical load (on internal
  loads FE).

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The Proposed Process

• Remember the elastically corrected loads on the
  aerodynamic mesh
• As MSC.FlightLoads does now on the ADB and AEDB
• Re-evaluate the mapping of these load increments
  onto the new structural FE
• Re-use standard coupling methods
• Gather the loads onto an updated AEDB for use
  downstream
• Downstream tools dont realize a two-step process
  was applied upstream

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The Proposed Process
Critical Loads Survey Stress Group Other tools
MSC.FlightLoads ADB
MSC.FlightLoads AEDB (Internal Loads FE)
Aeroelastic Solver
Can be applied recursively
New Mapping Tool
Flexibility FE
Spline To New FE
MSC.FlightLoads AEDB (Coarse FE)
Internal Loads FE
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The ADB/AEDB Collections

• The ADB contains the aerodynamic model
• Mesh topology
• Rigid aerodynamic loads
• The AEDB contains the ADB and flexible
  increments (FI)
• FI include forces and displacements
• Forces arise from rigid and from the
  displacements passing thru the AIC
• All forces (except rigid inertial) are on both
  the aero and structural meshes
• These are unbalanced, but all balanced states
  are a linear combination

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Mapping Methodology

• From equations of motion for static
  aeroelasticity
• 1. rigid load AIC ? deformation
• 2. AIC deformation ? elastic increment force
• 3. rigid load elastic force ? corrected load
• From 2 on the aero mesh, we map to the new
  structural FE via DMAP alter (for now)
• From these loads, a statics solution on new FE
  yields deformations on new FE
• Restore inertial loads (rigid) from new FE
• Proceed with normal AEDB creation to complete the
  AEDB collection

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Advantages

• No heuristic methods
• Two mappings of the same kind
• Repeatable
• Recursively applicable
• Full vehicle balanced loads are immediately
  available
• Trim on the new structure
• Using mass of the new structure
• BUT using inertial aeroelastic correction of the
  original FE
• FASTER for superior FIDELITY

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An Example
The built-up structure
The common aero mesh
The beam-stick structure
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Cases

• All analyses represent a 1g Level Flight Trim at
  M0.4, Sea Level
• 3 variants were run
• Aero Beam FE
• Aero Built-up FE
• Starting with Aero Beam, Map to Built-up FE and
  then trim
• Model Sizes
• Aero 554 Boxes
• Beam FE 141 nodes
• Built-up FE 3171 nodes
• All runs were made on NEC laptop, Pentium II

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Results and Timing Summary
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Results and Timing Summary
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Qualitative Results
Trimmed Forces On Aero Mesh
Trimmed Forces On Beam Mesh
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Qualitative Results (cont.)
Trimmed Forces On Aero Mesh
Trimmed Forces On Built-up Mesh
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Quantitative Results
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Quantitative Results
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Summary of New Approach

• Costs
• It approximates the inertial aeroelastic effect
• It requires two spline models
• Benefits
• It is computational (not heuristic)
• It preserves full-vehicle balance
• It is faster (process) and uses less CPU, too
• CPU savings accumulate as more Mach/Q pairs are
  used
• It creates fully reusable databases
• easy to generate new trim states
• able to recursively map the mapped solution to
  other models