Research ambitions in experimental mechanics Department of Applied - - PowerPoint PPT Presentation

research ambitions in experimental mechanics
SMART_READER_LITE
LIVE PREVIEW

Research ambitions in experimental mechanics Department of Applied - - PowerPoint PPT Presentation

Research ambitions in experimental mechanics Department of Applied Physics and Mechanical Engineering Division of Experimental Mechanics Chair: Professor Mikael Sjdahl, mikael.sjodahl@ltu.se Research areas Applications Physically based


slide-1
SLIDE 1

Research ambitions in experimental mechanics

Department of Applied Physics and Mechanical Engineering Division of Experimental Mechanics Chair: Professor Mikael Sjödahl, mikael.sjodahl@ltu.se

slide-2
SLIDE 2

Research areas

Applications Physically based estimation Robust field information extraction 3D and 4D metrology Other methods

slide-3
SLIDE 3

Research area: 3D and 4D metrology

Research challenge: how to fill the (k,ω) space to reach a sufficient resolution and reliability in (x,t) space without being prone to environmental disturbances

  • Phase objects
  • Particles
  • Multiple scattering objects
  • Surfaces
slide-4
SLIDE 4

Phase objects (1)

Quantitative laser ablation, 835 ns after interaction

Challenges: mapping

( ) ( ) ( )

ω ω ω , , , ˆ x x x ik n n + =

Tools:

  • Digital holography
  • Projection tomography
  • Deflectometry

Contact Per Gren and Eynas Amer for more information

slide-5
SLIDE 5

Particles (2) Laser

Particle distance > Airy spot size Challenges:

  • position
  • size
  • (motion)
  • (interaction)

Tool: Digital holography

slide-6
SLIDE 6

Multiple scattering objects / imaging w ithin opaque objects (3)

Tools:

  • Digital holography/tomography
  • OCT
  • Multiphysical imaging:
  • Optical-acoustical-optical
  • Optical-heat-optical

Contact Erik Olsson for more information

slide-7
SLIDE 7

Surfaces / 2.5D (4)

Challenges:

  • Rapidly, typically one frozen image
  • High spatial resolution

Methods:

  • Projected fringes
  • Projected speckles
  • Interferometry
  • Wave-front sensor
  • Phase-coding

Contact Sara Rosendahl and Emil Hällstig for more information

slide-8
SLIDE 8

Research area: Robust field information extraction

Research challenge: set up a general framework in which distributed optical complex signals may be analysed in a robust way without deteriorating the resolution in the signals acquired

  • Field approach; i. e. FEM
  • Noise immune
  • Amplitude
  • Phase
  • Deformation
  • Polarization
slide-9
SLIDE 9

”FEM” – approach 1, 2 , 3 D

  • Correlation optimization
  • Continuous within each element
  • Continuous between elements
  • Remeshing
  • Enrichment functions for discontinuities
slide-10
SLIDE 10

Example 1D deformation

200 400 600 800 1000 1200

  • 2
  • 1.5
  • 1
  • 0.5

0.5 1 1.5 2 Piecewise Chebyshev polynomials, marked interval centres Position [pixels] Displacement [pixels] 200 400 600 800 1000 1200

  • 2
  • 1.5
  • 1
  • 0.5

0.5 1 1.5 2 Estimated piecewise Chebyshev polynomials, marked interval centres Position [pixels] Displacement [pixels]

200 400 600 800 1000 1200
  • 2
  • 1.5
  • 1
  • 0.5
0.5 1 1.5 2 Global optimization Position [pixels] Displacement [pixels] 200 400 600 800 1000 1200
  • 2
  • 1.5
  • 1
  • 0.5
0.5 1 1.5 2 Estimated piecewise Chebyshev polynomials, marked interval centres Position [pixels] Displacement [pixels] 200 400 600 800 1000 1200
  • 2
  • 1.5
  • 1
  • 0.5
0.5 1 1.5 2 Estimated piecewise Chebyshev polynomials, marked interval centres Position [pixels] Displacement [pixels]
slide-11
SLIDE 11

Separating medium and information Digital filter

+ = ≈

Reference noise Measured phase Plate variation Noise

Contact Henrik Lycksam for more information!!!!

slide-12
SLIDE 12

Research area: Physically based estimation

Research challenge: How to combine observables with verified physical relations to

  • btain new information

Tools:

  • Highly resolved measurements
  • Physical model
  • Optimization/fitting
slide-13
SLIDE 13

Example: Laser ablation – point explosion model

  • Released energy
  • Density, pressure, temperature
  • Electron density
  • Recombination rate
  • Conversion efficiency

Contact Per Gren and Eynas Amer for more information

slide-14
SLIDE 14

Example: Friction estimation

The plot to the left shows a comparison between estimated road friction based on a forward looking

  • ptical sensor and measured

friction. Contact Johan Casselgren for more information

slide-15
SLIDE 15

Automatic comparison betw een CAD model and measurement

  • Applied mathematics, LTU
  • ”Iterative closest point”
  • Focus on speed, ~1 sec
  • Measurands: edges, holes,

surface defects, angles, … Contact Sara Rosendahl for more information