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Tadanaga Takahashi, Advisor: Dr. Lou Kondic Analyzing Force Networks in Granular Systems using Persistent Homology Abstract Introduction Results Conclusion Method References Department of Mathematical Sciences and Center for Applied Mathematics and Statistics, NJIT We present novel approach that allows to correlate in precise terms the dynamics of an intruder falling on a granular system and the material response. Our results are obtained using topological data analysis method, persistent homology, for analysis of the results of experiments that involve impact on a system of granular photoelastic particles. The photoelasticity illuminates the forces that develop in the two dimensional granular system. These forces form a complex network that evolves as the intruder penetrates the system. Persistent homology allows us to quantify the topological features of the force network based on the experimental images. We cross validate the information obtained from the images to the physical measurements from the experiment. We find, for multiple experimental settings, that the total persistence of topological generators is highly correlated with the acceleration of the intruder thus showing direct connection between the topological properties and the material response. We study the force propagation that occurs in granular systems after experiencing impact. This has applications in missile defense and terrestrial locomotion over granular terrain. The images that we use are from the granular impact experiments conducted at Duke University [1]. In the experiments, intruders of different sizes were dropped onto a system of photoelastic particles of varying stiffness to determine a relation between the physical parameters of granular systems and force propagation speed. Our analysis of the granular system is centered around the topology of the force network. For each experiment, we are given a set of grayscale images ∈ℕ × 0≤ ≤ 255}, where is a discrete time index and × is the resolution of the image. Each image is represented by a matrix of integers ranging from 0 to 255, where 0 is black and 255 is white. We start by applying image processing techniques to reduce noise in the images. Then we apply super level persistent homology to the image to decompose it into a table of topological generators: consider a Boolean matrix consisting only of 1s and 0s. We call any adjacent cluster of 1s a component and any cluster of 0s surrounded by 1s a hole. They are collectively called generators. The method performs a continuous mapping of to a simplicial complex for the threshold = 255 0, where =൝ 1 > 0 . Persistent homology tabulates the thresholds at which holes and components appear and disappear on the matrix as is swept from 255 to 0. For a given image , we have a set of generators described by their birth and death thresholds, PD k = ∈ℤ 2×1 =1 , and we call this the persistence diagram of the image. There are several ways to analyze persistence diagrams, see [2-4] for more details: Death vs. Birth plot Distribution of lifespan (birth – death) Betti numbers (count of components and holes) Total persistence (sum of lifespans) We ask whether there is a connection between these measures and the dynamics of the system. The experimental data for the base case is plotted below. We have found across several experiments that the acceleration of the intruder and the photoelastic response follow the same trend as the total persistence and Betti numbers. The results were normalized and plotted in a single window for 6 different impact experiments. We observe good correlation between various measures, particularly for the particles of the smaller stiffness. The research in the direction of comparing the results to the dynamics is in progress. Another direction currently being studied is the relation between the evolution of persistence diagrams and the speed of information propagation through granular particles. [1] Clark, A.H., Petersen, A.J., Kondic, L., Behringer, R.P.: Nonlinear Force Propagation During Granular Impact. Physical Review Letters. 114, (2015). [2] Kondic, L., Kramár, M., Pugnaloni, L.A., Carlevaro, C.M., Mischaikow, K.: Structure of force networks in tapped particulate systems of disks and pentagons. II. Persistence analysis. Physical Review E. 93, (2016). [3] Kramar, M., Goullet, A., Kondic, L., Mischaikow, K.: Persistence of force networks in compressed granular media. Physical Review E. 87, (2013). [4] Kramár, M., Goullet, A., Kondic, L., Mischaikow, K.: Evolution of force networks in dense particulate media. Physical Review E. 90, (2014). This figure shows the grayscale images from the impact experiment; from top to bottom the stiffness of the photoelastic particles decreases. The camera captures optical properties of the particles, related to the stress that they experience. From [1]. Processed Images Base experiment: medium stiffness, small intruder size, and high impact speed. Images were processed to isolate the force network. 5 frames were chosen. __________________________________________________________________________ Birth vs. Death Plot The scatter plot of generators for 0 and 1 is plotted for the five frames shown above. __________________________________________________________________________ Lifespan Distribution Histogram of the lifespan of generators is plotted for the five frames shown above. __________________________________________________________________________ Betti Numbers The number of generators above and below the average generator birth threshold. The counts correspond to strong and weak forces in the network. __________________________________________________________________________ Total Persistence The sum of the generator lifespans. We consider the case with medium particle stiffness, high impact speed (4.0 m/s), and small intruder size (2.5 in). The velocity and acceleration of the intruder are recorded. The acceleration and brightness are closely related because the amount of light refracted by the particles is proportional to the amount of stress exerted onto them. Acknowledgements Supported by NSF grant No. DMS- 1521717 and DARPA contract No. HR0011-16-2- 0033.

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Page 1: Analyzing Force Networks in Granular Systems using Persistent …cfsm.njit.edu/capstone/publications/slides/takahashi2017... · 2017-06-21 · granular system and the material response

Tadanaga Takahashi, Advisor: Dr. Lou Kondic

Analyzing Force Networks in Granular Systemsusing Persistent Homology

Abstract

Introduction

Results ConclusionMethod

References

Department of Mathematical Sciences and Center for Applied Mathematics and Statistics, NJIT

We present novel approach that allows to correlate inprecise terms the dynamics of an intruder falling on agranular system and the material response. Ourresults are obtained using topological dataanalysis method, persistent homology, for analysisof the results of experiments that involve impacton a system of granular photoelastic particles. Thephotoelasticity illuminates the forces that develop inthe two dimensional granular system. Theseforces form a complex network that evolves as theintruder penetrates the system. Persistent homologyallows us to quantify the topological features ofthe force network based on the experimental images.We cross validate the information obtained from theimages to the physical measurements from theexperiment. We find, for multiple experimentalsettings, that the total persistence of topologicalgenerators is highly correlated with theacceleration of the intruder thus showing directconnection between the topological properties andthe material response.

We study the force propagation that occurs ingranular systems after experiencing impact. Thishas applications in missile defense and terrestriallocomotion over granular terrain. The images that weuse are from the granular impact experimentsconducted at Duke University [1]. In theexperiments, intruders of different sizes weredropped onto a system of photoelastic particles ofvarying stiffness to determine a relation betweenthe physical parameters of granular systems andforce propagation speed. Our analysis of thegranular system is centered around the topologyof the force network.

For each experiment, we are given a set of grayscaleimages 𝐴𝑘 ∈ ℕ𝑚×𝑛 0 ≤ 𝑎𝑖𝑗 ≤ 255}, where 𝑘 is a

discrete time index and 𝑚 × 𝑛 is the resolution of theimage. Each image is represented by a matrix ofintegers ranging from 0 to 255, where 0 is black and255 is white. We start by applying image processingtechniques to reduce noise in the images. Then weapply super level persistent homology to the image 𝐴to decompose it into a table of topologicalgenerators: consider a Boolean matrix 𝐵 consistingonly of 1s and 0s. We call any adjacent cluster of 1s acomponent and any cluster of 0s surrounded by 1s ahole. They are collectively called generators. Themethod performs a continuous mapping of 𝐴 to asimplicial complex 𝐵𝜌 for the threshold 𝜌 =

255 𝑡𝑜 0, where

𝐵𝜌 𝑖𝑗= ൝

1 𝑎𝑖𝑗 > 𝜌

0 𝑎𝑖𝑗 ≤ 𝜌.

Persistent homology tabulates the thresholds 𝜌 atwhich holes and components appear and disappearon the 𝐵𝜌 matrix as 𝜌 is swept from 255 to 0. For a

given image 𝐴𝑘 , we have a set of generatorsdescribed by their birth and death thresholds, PDk =

𝑝𝑑𝑖 ∈ ℤ2×1 𝑖=1𝑛𝑘 , and we call this the persistence

diagram of the image.

There are several ways to analyze persistencediagrams, see [2-4] for more details:• Death vs. Birth plot• Distribution of lifespan (birth – death)• Betti numbers (count of components and holes)• Total persistence (sum of lifespans)

We ask whether there is a connection between thesemeasures and the dynamics of the system. Theexperimental data for the base case is plotted below.

We have found across several experiments that theacceleration of the intruder and the photoelasticresponse follow the same trend as the totalpersistence and Betti numbers.The results were normalized and plotted in a singlewindow for 6 different impact experiments. Weobserve good correlation between various measures,particularly for the particles of the smaller stiffness.

The research in the direction of comparing theresults to the dynamics is in progress. Anotherdirection currently being studied is the relationbetween the evolution of persistence diagramsand the speed of information propagationthrough granular particles.

[1] Clark, A.H., Petersen, A.J., Kondic, L., Behringer, R.P.: Nonlinear Force

Propagation During Granular Impact. Physical Review Letters. 114, (2015).

[2] Kondic, L., Kramár, M., Pugnaloni, L.A., Carlevaro, C.M., Mischaikow, K.:

Structure of force networks in tapped particulate systems of disks and

pentagons. II. Persistence analysis. Physical Review E. 93, (2016).

[3] Kramar, M., Goullet, A., Kondic, L., Mischaikow, K.: Persistence of force

networks in compressed granular media. Physical Review E. 87, (2013).

[4] Kramár, M., Goullet, A., Kondic, L., Mischaikow, K.: Evolution of force

networks in dense particulate media. Physical Review E. 90, (2014).

This figure shows the

grayscale images

from the impact

experiment; from top

to bottom the

stiffness of the

photoelastic particles

decreases. The

camera captures

optical properties of

the particles, related

to the stress that

they experience.

From [1].

Processed Images

Base experiment: medium stiffness, small intruder size, and high impact speed.Images were processed to isolate the force network. 5 frames were chosen.

__________________________________________________________________________

Birth vs. Death Plot

The scatter plot of generators for 𝛽0 and 𝛽1 is plotted for the five frames shown above.__________________________________________________________________________

Lifespan Distribution

Histogram of the lifespan of generators is plotted for the five frames shown above.__________________________________________________________________________

Betti Numbers

The number of generators above and below the average generator birth threshold.The counts correspond to strong and weak forces in the network.

__________________________________________________________________________

Total Persistence

The sum of the generator lifespans.

We consider the case with

medium particle stiffness,

high impact speed (4.0

m/s), and small intruder

size (2.5 in). The velocity

and acceleration of the

intruder are recorded. The

acceleration and brightness

are closely related because

the amount of light refracted

by the particles is

proportional to the amount

of stress exerted onto them.

AcknowledgementsSupported by NSF grant No. DMS- 1521717 and DARPA contract

No. HR0011-16-2- 0033.