University of Nebraska-Lincoln

Research Area

The Moore Dynamics and Analytics Laboratory (MoDAL) synergistically combines theory, mathematical and computational modeling, and experimentation to understand and exploit strongly nonlinear dynamical phenomena. Our vision is to place nonlinear dynamics in the toolbox of every vibration engineer. Our approach is to leverage data, machine learning, and autonomy to remove barriers for utilizing and understanding nonlinearity.

Active Research Directions

Active areas of research include:

1. Physics-based, data-driven modeling and discovery of governing equations directly from measurements.
2. AI-based automated testing of mechanical structures.
3. Reduced-order modeling of nonlinear structures (e.g., reduced-order modeling of bolt loosening).
4. Nonlinear energy flows in mechanical structures.
5. Novel vibration mitigation strategies employing nonlinearities.
6. Applications of nonlinear dynamics and vibrations to novel fields (e.g., wave-induced vibrations of ships).

Equipment

Digital Image Correlation (DIC)

The pair of high-speed digital cameras in MoDAL.

We have a high-speed 3D DIC system for non-contact measurements for systems where discrete sensors affect the dynamics, can't be used due to geometry, or where full-field data is needed. The cameras can record up to 500,000 frames per second (FPS) at reduced resolution and at 4,000 FPS at a 1-megapixel resolution. We typically film vibrations and dynamic responses around 4k to 10k FPS. We have previously performed measurements on strongly nonlinear vibrating structures and high-speed catastrophic failure (e.g., 3D-printed pressure vessel exploding).

Equipment List:

• VIC-3D Digital Image Correlation System (Correlated Solutions)
  • Two Photron AX100 540K-M-32GB (1024 x 1024 @ 4,000 fps) high-speed digital cameras
  • Lenses: two Nikon 24mm wide angle manual focus, two Nikon 50mm, and two Tokina 100mm 1:1 macro lenses
  • One 6000 Lumen High-Speed LED lighting System with Flood Controller
  • Workstation with rackmount Quad-core PC, 64GB RAM, Win 10 64 bit, 1TB SSD, 8TB HD, dual 24" LCD monitors
  • One 8-channel USB analog data acquisition system for high-speed measurements with a maximum sampling rate of 1 MS/s (National Instruments NI 6361)
  • Accompanying accessories (cases, speckle paint, etc.)

Standard Vibration Measurement Equipment

• Thirty-six channel data acquisition and digital signal processing hardware (24 input and 12 programmable channels), 80kHZ bandwidth, 24-bit ADC (Data Physics Abacus 906)
  • Full SignalCalc DP900 software suite for Data Physics DAQ and modal shaker
  • One modal test shaker, 18 lbf (80 N) maximum force, 1 in (25.4 mm) maximum displacement, 60 in/s (1.5 m/s) max velocity, with accompanying amplifier (Data Physics SignalForce GW-M20/PA100EC)
• Thirty-five uniaxial and ten triaxial accelerometers (PCB 353B15 and 356A03)
• Eight-channel, ICP sensor signal conditioner (PCB 483C05)
• Four modally tuned impact hammers of various load ratings (PCB 086E80, 086C03, 086D05, and 086D20)

Current Members

Researcher	Research
Keegan	Focus on nonlinear dynamics and vibrations, data analytics, data-driven modeling, machine learning, reduced-order modeling, passive redirection of mechanical energy, and others.
Cristian López	PhD student studying data-driven nonlinear system identification.
Manal Mustafa	PhD student investigating the effect of mass on energy exchanges in nonlinear oscillators and the passive manipulation of energy flows in nonlinear structures.
Javier Arroyo	PhD student studying the physics of bolted joint loosening.
Felipe Kobayashi	PhD student working on physics-based, reduced-order modeling of bolted joint loosening.
Geoffrey Soneson	PhD student working on solitary wave control using engineered defects in metamaterials.
Mohammad Nasr	MS student working on smart, predictive automatic modal impact hammers.

Summary of our recent work on reduced-order modeling of joint loosening mechanics.

Summary of our recent work on reduced-order modeling of joint loosening mechanics. Sponsored by an NSF CAREER award.