John W. Vinti Particle Tracker Final Presentation

ME 501: Particle Tracker

Particle Tracking in the PIVOTProject Lead: John W. VintiProject Advisor: Derek TrethewayDepartment of Mechanical & Materials Engineering, Portland State University, P.O. Box 751, Portland, OR 97201, USAJune 10th 2015

Questions DuringAbout Me:BS ME from University at Buffalo 2012Lean Six Sigma Black Belt 2014Worked at ITT Enidine Design Team, DoD Contract for missle isolation systemsWorked at Welch Allyn Manufacturing Med Devices,In killer rock and roll bandHopefully Be awake at the end and Ill be granted a mastersStarted Spring 2014Project Started in Summer 20144 prior revisions 1 finalAcknowledgements1

Presentation StructureIntroduction to PIVOTPurposePrinciplesSample Past Experiment

Project GoalsBottlenecks of PIVOTDefinition of GoalsSystem Limitations

Introduction to PIVOTProject GoalsParticle TrackerBenefitsParticle TrackerLayoutMinimization of Operator ErrorKey Design AdvantagesDemonstrations

Benefits Solution to BottlenecksOther Benefits

Introduction

Introduction to PIVOTProject GoalsParticle TrackerBenefits

Purpose of PIVOTUsed to study particle(s) suspended in both Newtonian and Non-Newtonian FluidsTheoretical particle-particle interactions in Non-Newtonian Fluids is limitedDue to establishing proper constitutive equationUsed to Validate existing theoretical models and further develop models for bulk flowComputational models of particle suspension are neededIntroduction to PIVOTProject GoalsParticle TrackerBenefits

Principles of PIVOTPIVOT functionsManipulates isolated particle/cell in microfluidic environmentImages the particle/cellCharacterizes the influential microfluidic environmentQuantifies applied stresses and induced strains


OT Wavelength 1064nmOT Beam is passed through a lens and is focus on diffraction limited spotOT Delta X is particle displacement from trap center, k is trap stiffnessmPIV It images the emitted light with filtering techniquesmPIV- Lasers Synced with Charged Coupled Device CameramPIV Can be 3-D if scan layer planes and applying continuity equation5

The PIVOT

Introduction to PIVOTProject GoalsParticle TrackerBenefitsHardware

SoftwareGeviCam Coyote

NASA Spotlight

Red Lines are the position of OT Beam

Describe and Picture, picture first Velcoties, how to calibrate process, Non Newtonian preface oscilating flow time delay (phase Shift)

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Sample Past ExperimentManipulation of Suspended Single Cells by Microfluidics and Optical TweezersNathalie Nve, Sean S. Kohles, Shelly R. Winn, and Derek C. TrethewayUses the PIVOT to examine the viability and trap stiffness of cartilage cells, identify the maximum fluid-induced stresses possible in uniform and extensional flows, and to compare the deformation characteristics of bone and muscle cells.


Gives an idea of how powerful this system can be and what it can acomplish7

Project Goals

So The PIVOT System is without flaw?


First Identify the Bottlenecks of the system8

Bottlenecks of PIVOT - Calibration


Configure PIVOTCapture ImagesExport ImagesImport Images to Post Process SoftwarePerform Post Processing of Each FrameCollect DataInterpret DataApply to ExperimentLONG

Want drag force equal to Trap Force for equilibriumDrag Force Easiest MethodFor highly nonspherical and/or biological objects, the drag force method alone may not be sufficient, therefore additional trap calibration methods may be necessary. Takes a full day

A is the radius of the spherical particle, l is the half height of the channel, is the fluid viscosity, and v is the fluid velocity experienced by the sphere.9

Bottlenecks of PIVOT Cell Movement

Trapped particles/cells are ideally static and are stabilized by inflow outflow saddle pointSmall uncontrollable perturbations can cause the particle/cell to become unstable and move around within the saddle pointOT imparts continuous laser to keep the particle/cell stabilized within the flowConsequence: Too much energy can cause cell degradation and death

Introduction to PIVOTProject GoalsParticle TrackerBenefits*

Cross Flow Scenario10

Bottlenecks of PIVOT Post ProcessingAll data analysis of PIVOT experiments are done post-process Coyote and SpotlightLimited useable data can be extracted instantaneously during experiments

Introduction to PIVOTProject GoalsParticle TrackerBenefitsLONG

Now that we understand these bottlenecks, we can generate design requirements for a new software application to help circumvent these issues11

Definition of GoalsProvide a reliable system to perform the following functions for the PIVOT System:Real Time Video FeedEfficient Real Time Image ProcessingReliable Real Time Tracking InformationReliable Real Time Deformation AnalysisVersatile Software for Numerous ApplicationsVariable Output CapabilityCompatible with current systemIncorporate Same Functionalities of Post Processing SoftwareSimple to Use (for undergraduates)


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System LimitationsCurrently installed programs SOFTWAREREAL TIME FEEDREAL TIME IMAGE PROCESSINGTRACKING CAPABILITYDEFORMATION ANALYSISVERSATILITYVARIABLEOUPUT CAPABILITYSIMPLICITY(Subjective)SPOTLIGHTXXXXCOYOTEXXXPARTICLE TRACKERXXXXXXX

Combine the features of both programs into one


Discuss Specifics for each system MoreTwo things go to one13

Particle TrackerAs you can see this project is a big deal


Layout (a) Real time video feed(b) Real time filtered video feed(c) Start video feed pushbutton(d) Stop video feed pushbutton(e) Threshold filter slider(f) Area filter slider

(g) Frames to track popup(h) Track real time feed pushbutton*(j) Tracking status indicator**(k) Tracking location indicators**(m) Length indicators**(n) Breadth indicators**(a)(b)(c)(d)(e)(f)(g)(h)(j)(k)(m)(n)


Minimization of Operator Error*(h) Track real time feed pushbuttonDependent upon input of (c) Start video feed pushbutton

**(j) Tracking status indicatorDependent upon input of (h) Track real time feed pushbuttonDisappears after the specified number of frames are tracked

**(k) Tracking, (m) Length, and (n) Breadth location indicators Dependent upon input of (h) Track real time feed pushbuttonDisappears after the specified number of frames are trackedServes as verification that track is accurate via superimposing


Key Design AdvantagesMATLAB Based SystemThe University has a license for MATLAB and the Image Acquisition ToolboxLikely to retain MATLAB for the futureControl friendly environmentGraphical User InterfaceProvides a simple to use environment for operatorsAllows for operator control over processingLimited Toolbox Use No need for the University to purchase any other toolboxes for MATLABPrevious versions of the Particle Tracker used Toolboxes not available to University


Reinforce Barbones MATLAB can run with toolbox, 17

Demonstration


BenefitsIntroduction to PIVOTProject GoalsParticle TrackerBenefits

Hes right! When you look at it that way, its not so bad!

*Solution to BottlenecksCalibration

Cell Movement Pulse (Opportunity)


Configure PIVOTCapture ImagesExport ImagesImport Images to Post Process SoftwarePerform Post Processing of Each FrameCollectDataInterpret DataApply to ExperimentConfigure PIVOTRun SoftwareCollect/Analyze DataApply to Experiment

Real Time ProcessingCentroidArea LengthBreadthOrientation

Calibration Shortened Process. Saves Time and MoneyCross Flow Longer cell life less usage of OTReal time No more post processing20

Other BenefitsWithin the PIVOT SystemNon-Newtonian Fluid StudiesCapable of performing multiple particle analysis

Outside PIVOT SystemIncorporation into other systems that require trackingLimited MATLAB Toolbox UsageNon-Engineering based SystemsEducational ToolFully annotated MATLAB CodeFully customizableFor Other Experiments


Limit Energy input21

Thank You!Questions?

Why not PIV for Tracking Slow Framerate, not really real time, and image correlation, used for groups of particles not single particle

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John W. Vinti Particle Tracker Final Presentation

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