Particle Simulation in Magnetorheological Flows Norman M. Wereley - PowerPoint PPT Presentation

University of Maryland GPU Summit Particle Simulation in Magnetorheological Flows Norman M. Wereley Minta Martin Professor and Department Chair wereley@umd.edu + contributions from graduate students, research staff, and collaborators Smart Structures Laboratory Dept. of Aerospace Engineering University of Maryland

Adaptive Energy Absorption Systems Using MR Fluids Objective: To dissipate energy in vehicle systems in order to protect occupants and payloads from injurious vibration, repetitive shock, crash and blast loads . Sponsors: General Motors, Boeing-Mesa US Army, US Navy

Protective Seating: Impact, Crash, Blast Events are rapid (< 50 ms) q Flight qualification of SH-60 seat with q MR vibration control and deploy Develop lightweight compact MREAs for q adaptive crash safety Verify MREA control strategies via test q Other vehicle applications q – Expeditionary Fighting Vehicle (EFV) semi- active seat technology • Automatic adaptation b/w water-mode shock and ground-mode vibrations • Sea trials completed in 9/09 – Adaptive high speed watercraft seats • Mark V SOC sea trials completed – Adaptive Mine-blast attenuating seats • Best “dynamic response index”

MR Fluids: Phase Transformation Recipe Magnetorheological Fluid 1 cup of oil (hydraulic)  1/2 cup of carbonyl iron powder  (heavy) Mix well  Properties of MR Fluid:  High specific gravity  Yield stress: 60-100 kPa at full field  for high solids loading Full Field: 1 Tesla, 1 Amp in coil at 2-  3 Volts (under 3 Watts) Temperature insensitive 

Microstructure of MR fluids MR Fluid: Bingham Plastic Behavior Ferrous particle Carrier fluid N S Shear Stress, τ > τ y Shear Stress, τ > 0 N v S Optical Micrograph Image of Ferrous No Field Condition Field Applied Particle Chains in MR Fluid

Dimorphic MR Fluids (Collaboration: R. Bell, & D. Zimmerman, PSU) Morphology q Microwires with fixed diameter and q distribution of lengths (2-20 microns) Spheres with narrow distribution of q diameters Magnetic dipole reorients with q magnetic field Key physics q – Yield stress – Viscosity – Sedimentation • Smart Materials Structures (3/09) – Elastic percolation • Appl. Physics Letters (7/01/09)

Magnetorheology Shear Stress kPa 60 wt% Iron with 15% Nanometer Scale Particles

MR Fluids - Too Simple a Model? (Bingham Plastic Model) Bingham plastic MR fluid behavior q – Newtonian in absence of field – Bingham plastic in presence of field Apparent Viscosity ( µ ) independent of field q Viscosity Yield Stress ( τ y ) dependent on field q Newtonian Fluid Bingham Plastic

MR Dampers MR fluids exhibit shear thinning at high shear rates q Yield stress changes as a function of magnetic field q MR fluid behaves approximately as a q – Bingham-plastic – Field dependent yield force – plus a viscous stress that is the product of viscosity and velocity Use nondimensional analysis q – Ndim plug thickness as independent variable – Ndim dynamic range as dependent variable – Damper performance

MR Fluid Damper Spring Configuration: Coil-over damper Pneumatic Reservoir Pneumatic Reservoir: N 2 1.7 MPa Floating Piston Maximum Stroke: 9 cm Spring Retainer Overall Length: 8 cm Bore Diameter: 4 cm Piston Head Piston Rod Flux Return Coils Steel Core

Damper Performance is Controllable Plug thickness varies q as a function of field and yield stress Change in plug q thickness is akin to opening and closing a mechanical valve Leakage is added to q the flow path to smoothen damper response hence the finite damping at plug thicknesses approaching the gap in the valve

Protective Seating: Impact, Crash, Blast Flight qualification of SH-60 seat with q MR vibration control and deploy Develop lightweight compact MREAs for q adaptive crash safety Verify MREA control strategies via test q Other vehicle applications q – Expeditionary Fighting Vehicle (EFV) semi- active seat technology • Automatic adaptation b/w water-mode shock and ground-mode vibrations • Sea trials completed in 9/09 – Adaptive high speed watercraft seats • Mark V SOC sea trials completed – Adaptive Mine-blast attenuating seats • Best “dynamic response index”

Control of Impact Loads payload mass V 0 Want to use all available stroke for neutral line q every impact speed or payload mass δ S Payload mass varies from 105 lbs x q (5th %tile female) to 225 lbs (95th reference line %tile male) magnetorheological f d energy absorbers Impact speed varies from 0-15 mph q (MREAs) (airbags take over at higher speeds) Must use an adaptive device like an q MREA Impact Plane

Magnetorheological Energy Absorber (MREA) Can Adapt Passive energy absorbers (EAs) cannot accommodate different occupant q weights (Left) Use simple optimal control of a terminal trajectory to achieve soft landing for q every occupant weight (right) Solution requires Lambert W functions q – Schottke diode equation – MREA utilizes entire stroke – Minimizes stroking load to the occupant

Extensive Sled Tests at GM Optimal control technique uses all available q stroke (2 inches) regardless of impact speed or occupant weight Implemented in dSpace q MREA sized to accommodate stroking loads q needed for 5th female to 95th male Speeds up to 15 mph q

Flight Qualification Ground Testing Seat was tested to ensure that vibration q isolation system did not hinder seat integrity during high onset rate crash events – Seat maintained structural integrity during tests Seat has been qualified for flight test in SH-60 q Seahawk Flight test completed… q

Challenge Level of Current Design Max Field-On Force vs. Max Velocity 21000 Carlson et al, 2006 for Seismic Dampers UMD Maximum Field-On Force (lb) 18000 Other Researchers Aft MD-500 Forward and Aft Damper 15000 Dampers at High at Low Sink Rate Sink Rate 12000 9000 Forward Damper at Wereley et al , 2005 for Low Sink Impact Dampers 6000 Rate Wereley et al , 2009 for Energy Absorbers 3000 Ahmadian et al , 2004 for Impact Dampers 0 0 5 10 15 20 25 Maximum Piston Velocity (ft/s) The dampers we are designing will require combinations of high force and high velocity that have not been attempted in known past research.

MR Fluid Characterization: High Shear Rates Need data at high q shear rates up to 100K /s Virtually all studies q < 1K /s Lab-built Searle cell q magnetorheometer can measure up to 25K / s Apparent viscosity q vs. shear rate Is the data good? q

MR Fluid Characterization for Shear Rates > 1000 / s Exploit the Mason q number – Ratio of viscous to magnetic stress – Klingenberg showed curves collapse for low shear rates Do apparent viscosity vs. q Mason number curves should collapse onto a single curve? Data is good q We are on the right track q to provide design data for high shear rate devices

MR Fluid Characterization Yield stress persists at 25K /s

Microstructures at High Shear Rate Bulk material perspective works for many applications q Need simulation capabilities at high shear q – Need CFD for pressure driven flow – Need CFD for direct shear flow Current state of the art simulates a few hundred to a few q thousand particles

CFD with MR Particle Interactions q Most simulations limited to particle counts in the low thousands q To simulate practical flow volumes, we need millions of particles q Need a three order of magnitude increase in particle count!!!

CFD with MR Fluids Dynamic simulation allows q for insight into chain formation under shear Goal: Simulate at q experimental volume scales – Need N=1,000,000 particles but state of the art is N<10,000 Use Nvidia’s CUDA q environment to run code on desktop GPU – Delivers 100x increase in computing performance

Chain Metrics q Visual observation of chain formation is difficult q Developed simulation scale independent chain metrics – Chain length – Connectivity q Demonstrated scale independence q Shown shear response of metrics is a function of Mason number

Lamellar Sheet Formation q Static equilibrium structure for MR fluids are chains Lamellar Sheet Formation q Under shear, particles of an ER fluid Cao, J., Huang J., & Zhou, L. form lamellar sheets (2006). q Experimentally demonstrated in MR fluids q Requires large volume Simulation Output Sherman, S. & Wereley, size to simulate N.M. (INTERMAG, 2012).

Million Particle Parallelized Simulations Using CUDA

Future Challenges in MR – Still a Rich Field of Research 20 years of MR fluid Research q – Still many problems to solve! Demonstrate MR energy absorbers for crash protection systems q – General Motors – U.S. Navy Air Warfare Center (H60 crew seat in 40 ft/s crash) – US Army Research Lab (HDL) Blast mitigation (against IEDs) – US ARMY AATD Active Crash Protection Systems in Rotorcraft GPU simulations using CUDA enabled understanding of high shear rate q MR fluid behavior – Typically measured up to 1000 /s – Want up to 100,000 /s (we have measured to 25,000 /s) – Need GPU simulation because experiments are difficult at high shear rate – Need a full CFD capability in GPU • Adaptive meshing for complex geometry • Axisymmetric geometry • Determine impacts of device on fluid flows