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This paper proposes a simple, generic and robust method to extract the grains from experimental tridimensionnal images of granular materials obtained by X-ray tomography. This extraction has two steps: segmentation and splitting. For the…

Computer Vision and Pattern Recognition · Computer Science 2008-07-23 Vincent Tariel

We study the filling process of a two-dimensional silo with inelastic particles by simulation of a granular media lattice gas (GMLG) model. We calculate the surface shape and flow profiles for a monodisperse system and we introduce a novel…

Disordered Systems and Neural Networks · Physics 2009-10-31 Antal Károlyi , János Kertész , Shlomo Havlin , Hernán A. Makse , H. Eugene Stanley

A new computational method is presented for study suspensions of charged soft particles undergoing fluctuating hydrodynamic and electrostatic interactions. The proposed model is appropriate for polymers, proteins and porous particles…

Soft Condensed Matter · Physics 2015-04-14 Juan P. Hernandez-Ortiz , Juan J. de Pablo

We use a macromodel of a flow-driven deterministic lateral displacement (DLD) microfluidic system to investigate conditions leading to size-separation of suspended particles. This model system can be easily reconfigured to establish an…

Fluid Dynamics · Physics 2016-04-27 Siqi Du , German Drazer

Particle-wall interactions play a crucially important role in various applications such as microfluidic devices for cell sorting, particle separation, entire class of hydrodynamic filtration and its derivatives, etc. Yet, accurate…

Fluid Dynamics · Physics 2025-03-18 Aryan Mehboudi , Shrawan Singhal , S. V. Sreenivasan

Very soft grain assemblies have unique shape-changing capabilities that allow them to be compressed far beyond the rigid jammed state by filling void spaces more effectively. However, accurately following the formation of these systems by…

We study the mechanisms of slip transfer at a grain boundary, in titanium, using Differential Aperture X-ray Laue Micro-diffraction (DAXM). This 3D characterization tool enables measurement of the full (9-component) Nye lattice curvature…

Materials Science · Physics 2020-12-08 Yi Guo , David M. Collins , Edmund Tarleton , Felix Hofmann , Angus J. Wilkinson , T. Ben Britton

A multi-phase field model is employed to study the microstructural evolution of an alloy undergoing liquid dealloying. The model proposed extends upon the original approach of Geslin et al. to consider dealloying in the presence of grain…

Materials Science · Physics 2023-08-07 Nathan Bieberdorf , Mark D. Asta , Laurent Capolungo

We develop, discuss, and compare several inference techniques to constrain theory parameters in collider experiments. By harnessing the latent-space structure of particle physics processes, we extract extra information from the simulator.…

High Energy Physics - Phenomenology · Physics 2018-09-19 Johann Brehmer , Kyle Cranmer , Gilles Louppe , Juan Pavez

We introduce a system of shallow water-type equations to model laboratory experiments of particle-laden flows. We explore homogeneous liquid-solid suspensions of fine, non-cohesive, monodisperse glass beads which propagate as an equivalent…

Fluid Dynamics · Physics 2025-02-11 Andrea Bondesan , Laurence Girolami , François James , Loïc Rousseau

We develop coarse-grained particle approaches for studying the elastic mechanics of vesicles with heterogeneous membranes having phase-separated domains. We perform simulations both of passive shape fluctuations and of active systems where…

Soft Condensed Matter · Physics 2023-02-28 David A. Rower , Paul J. Atzberger

Discrete particle simulation methods have been used to study axial segregation in a horizontal rotating cylinder that is partially filled with a mixture of two different kinds of granular particles. Under suitable conditions segregation was…

Soft Condensed Matter · Physics 2016-08-31 D. C. Rapaport

Our understanding of the elasticity and rheology of disordered materials, such as granular piles, foams, emulsions or dense suspensions relies on improving experimental tools to characterize their behaviour at the particle scale. While 2D…

Soft Condensed Matter · Physics 2010-09-24 Mohammad Saadatfar , Adrian P. Sheppard , Tim J. Senden , Alexandre J. Kabla

The determination of the mechanical properties of soils containing particles larger than the allowable size of standard laboratory equipments is complex. It is indeed necessary to remove the coarsest fraction to carry out the tests. This…

We propose a new metric called s-LID based on the concept of Local Intrinsic Dimensionality to identify and quantify hierarchies of kinematic patterns in heterogeneous media. s-LID measures how outlying a grain's motion is relative to its s…

Materials Science · Physics 2021-04-06 Shuo Zhou , Antoinette Tordesillas , Mehdi Pouragha , James Bailey , Howard Bondell

Convolutional neural networks can provide a potential framework to characterize groundwater storage from seismic data. Estimation of key components such as the amount of groundwater stored in an aquifer and delineate water-table level, from…

Blasted rock material serves a critical role in various engineering applications, yet the phenomenon of segregation-where particle sizes vary significantly along the gradient of a quarry pile-presents challenges for optimizing quarry…

Image and Video Processing · Electrical Eng. & Systems 2024-06-07 Chengeng Liu , Sihong Liu , Chaomin Shen , Yupeng Gao , Yuxuan Liu

The aim of our work is to analyze size distributions of particles and their agglomerates in imagery from astrophysical microgravity experiments. The data acquired in these experiments are given by sequences consisting of several hundred…

Instrumentation and Detectors · Physics 2025-08-12 Shima Shabani , Michael Breuß , Marvin Kahra , Jens Teiser , Gretha Swantje Völke , Nico Wenders

In this letter, measurements of the shared momentum fraction ($z_{\rm{g}}$) and the groomed jet radius ($R_{\rm{g}}$), as defined in the SoftDrop algorihm, are reported in \pp collisions at $\sqrt{s} = 200$ GeV collected by the STAR…

High Energy Physics - Experiment · Physics 2021-01-07 STAR Collaboration , J. Adam , L. Adamczyk , J. R. Adams , J. K. Adkins , G. Agakishiev , M. M. Aggarwal , Z. Ahammed , I. Alekseev , D. M. Anderson , A. Aparin , E. C. Aschenauer , M. U. Ashraf , F. G. Atetalla , A. Attri , G. S. Averichev , V. Bairathi , K. Barish , A. Behera , R. Bellwied , A. Bhasin , J. Bielcik , J. Bielcikova , L. C. Bland , I. G. Bordyuzhin , J. D. Brandenburg , A. V. Brandin , J. Butterworth , H. Caines , M. Calderón de la Barca Sánchez , D. Cebra , I. Chakaberia , P. Chaloupka , B. K. Chan , F-H. Chang , Z. Chang , N. Chankova-Bunzarova , A. Chatterjee , D. Chen , J. H. Chen , X. Chen , Z. Chen , J. Cheng , M. Cherney , M. Chevalier , S. Choudhury , W. Christie , H. J. Crawford , M. Csanád , M. Daugherity , T. G. Dedovich , I. M. Deppner , A. A. Derevschikov , L. Didenko , X. Dong , J. L. Drachenberg , J. C. Dunlop , T. Edmonds , N. Elsey , J. Engelage , G. Eppley , R. Esha , S. Esumi , O. Evdokimov , A. Ewigleben , O. Eyser , R. Fatemi , S. Fazio , P. Federic , J. Fedorisin , C. J. Feng , Y. Feng , P. Filip , E. Finch , Y. Fisyak , A. Francisco , L. Fulek , C. A. Gagliardi , T. Galatyuk , F. Geurts , A. Gibson , K. Gopal , D. Grosnick , W. Guryn , A. I. Hamad , A. Hamed , J. W. Harris , S. He , W. He , X. He , S. Heppelmann , S. Heppelmann , N. Herrmann , E. Hoffman , L. Holub , Y. Hong , S. Horvat , Y. Hu , H. Z. Huang , S. L. Huang , T. Huang , X. Huang , T. J. Humanic , P. Huo , G. Igo , D. Isenhower , W. W. Jacobs , C. Jena , A. Jentsch , Y. JI , J. Jia , K. Jiang , S. Jowzaee , X. Ju , E. G. Judd , S. Kabana , M. L. Kabir , S. Kagamaster , D. Kalinkin , K. Kang , D. Kapukchyan , K. Kauder , H. W. Ke , D. Keane , A. Kechechyan , M. Kelsey , Y. V. Khyzhniak , D. P. Kikoła , C. Kim , B. Kimelman , D. Kincses , T. A. Kinghorn , I. Kisel , A. Kiselev , A. Kisiel , M. Kocan , L. Kochenda , L. K. Kosarzewski , L. Kramarik , P. Kravtsov , K. Krueger , N. Kulathunga Mudiyanselage , L. Kumar , R. Kunnawalkam Elayavalli , J. H. Kwasizur , R. Lacey , S. Lan , J. M. Landgraf , J. Lauret , A. Lebedev , R. Lednicky , J. H. Lee , Y. H. Leung , C. Li , W. Li , W. Li , X. Li , Y. Li , Y. Liang , R. Licenik , T. Lin , Y. Lin , M. A. Lisa , F. Liu , H. Liu , P. Liu , P. Liu , T. Liu , X. Liu , Y. Liu , Z. Liu , T. Ljubicic , W. J. Llope , R. S. Longacre , N. S. Lukow , S. Luo , X. Luo , G. L. Ma , L. Ma , R. Ma , Y. G. Ma , N. Magdy , R. Majka , D. Mallick , S. Margetis , C. Markert , H. S. Matis , J. A. Mazer , N. G. Minaev , S. Mioduszewski , B. Mohanty , M. M. Mondal , I. Mooney , Z. Moravcova , D. A. Morozov , M. Nagy , J. D. Nam , Md. Nasim , K. Nayak , D. Neff , J. M. Nelson , D. B. Nemes , M. Nie , G. Nigmatkulov , T. Niida , L. V. Nogach , T. Nonaka , G. Odyniec , A. Ogawa , S. Oh , V. A. Okorokov , B. S. Page , R. Pak , A. Pandav , Y. Panebratsev , B. Pawlik , D. Pawlowska , H. Pei , C. Perkins , L. Pinsky , R. L. Pintér , J. Pluta , J. Porter , M. Posik , N. K. Pruthi , M. Przybycien , J. Putschke , H. Qiu , A. Quintero , S. K. Radhakrishnan , S. Ramachandran , R. L. Ray , R. Reed , H. G. Ritter , J. B. Roberts , O. V. Rogachevskiy , J. L. Romero , L. Ruan , J. Rusnak , N. R. Sahoo , H. Sako , S. Salur , J. Sandweiss , S. Sato , W. B. Schmidke , N. Schmitz , B. R. Schweid , F. Seck , J. Seger , M. Sergeeva , R. Seto , P. Seyboth , N. Shah , E. Shahaliev , P. V. Shanmuganathan , M. Shao , F. Shen , W. Q. Shen , S. S. Shi , Q. Y. Shou , E. P. Sichtermann , R. Sikora , M. Simko , J. Singh , S. Singha , N. Smirnov , W. Solyst , P. Sorensen , H. M. Spinka , B. Srivastava , T. D. S. Stanislaus , M. Stefaniak , D. J. Stewart , M. Strikhanov , B. Stringfellow , A. A. P. Suaide , M. Sumbera , B. Summa , X. M. Sun , Y. Sun , Y. Sun , B. Surrow , D. N. Svirida , P. Szymanski , A. H. Tang , Z. Tang , A. Taranenko , T. Tarnowsky , J. H. Thomas , A. R. Timmins , D. Tlusty , M. Tokarev , C. A. Tomkiel , S. Trentalange , R. E. Tribble , P. Tribedy , S. K. Tripathy , O. D. Tsai , Z. Tu , T. Ullrich , D. G. Underwood , I. Upsal , G. Van Buren , J. Vanek , A. N. Vasiliev , I. Vassiliev , F. Videbæk , S. Vokal , S. A. Voloshin , F. Wang , G. Wang , J. S. Wang , P. Wang , Y. Wang , Y. Wang , Z. Wang , J. C. Webb , P. C. Weidenkaff , L. Wen , G. D. Westfall , H. Wieman , S. W. Wissink , R. Witt , Y. Wu , Z. G. Xiao , G. Xie , W. Xie , H. Xu , N. Xu , Q. H. Xu , Y. F. Xu , Y. Xu , Z. Xu , Z. Xu , C. Yang , Q. Yang , S. Yang , Y. Yang , Z. Yang , Z. Ye , Z. Ye , L. Yi , K. Yip , H. Zbroszczyk , W. Zha , D. Zhang , S. Zhang , S. Zhang , X. P. Zhang , Y. Zhang , Y. Zhang , Z. J. Zhang , Z. Zhang , J. Zhao , C. Zhong , C. Zhou , X. Zhu , Z. Zhu , M. Zurek , M. Zyzak

Convolutional Neural Networks (CNN) have been employed for displacement estimation in ultrasound elastography (USE). High-quality axial strains (derivative of the axial displacement in the axial direction) can be estimated by the proposed…

Image and Video Processing · Electrical Eng. & Systems 2023-07-11 Ali K. Z. Tehrani , Hassan Rivaz