{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/125505"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/125505","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Advancing hybrid fluid-kinetic methods for plasma simulation","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","abstract_has_math":false,"creators":["Meredith, Logan Tate"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Physics","degree_department":null,"school":null,"contributors":["Curreli, Davide","Gammie, Charles F","Uddin, Rizwan","Kramer, Richard M"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05-20","date_published":"2024-05-20","updated_at":"2026-07-22T22:25:02Z","subjects":["Plasma","Hybrid Methods","Particle-in-cell","Fluid"],"languages":["en","eng"],"rights":["Copyright 2024 Logan Tate Meredith"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/125505","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Curreli, Davide","Gammie, Charles F","Uddin, Rizwan","Kramer, Richard M"]},{"key":"dc:creator","label":"Author","values":["Meredith, Logan Tate"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-05-20","2024-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Physics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Plasma","Hybrid Methods","Particle-in-cell","Fluid"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Logan Tate Meredith"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/125505"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","The student, Logan Meredith, accepted the attached license on 2024-05-14 at 11:12.","The student, Logan Meredith, submitted this Dissertation for approval on 2024-05-14 at 11:18.","This Dissertation was approved for publication on 2024-05-20 at 11:12.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20797 on 2025-02-04 at 21:03:19","The complex, multiscale nature of plasmas necessitated the early adoption of computers by plasma physicists to model their behavior more than half a century ago. Their limited computational resources demanded fast, efficient algorithms for simulating plasmas. In general, these algorithms fall into two categories: kinetic and fluid. Kinetic algorithms retain much detailed information about how velocities are distributed in particles of the plasma, and as a consequence, they are very widely applicable but computationally expensive. In contrast, fluid algorithms discard much of this information to reduce computational cost, but must make assumptions about the plasma to compensate. Such algorithms have kept pace with developments in computing technology and are still in wide use today, owing to their inherent parallelizability. However, as high-performance computing moves into the exascale era, plasma physicists have become inspired to attempt increasingly large simulations, as evidenced by the trend toward whole-device modeling in the study of magnetic confinement fusion. The widening of the computational bottleneck has exposed flaws in the traditional paradigm of using either purely kinetic or purely fluid algorithms. It is now clear that a hybrid approach, combining the strengths of both kinetic and fluid methods, is necessary to continue efficiently modeling plasmas at the largest desired scales. Although the study of hybrid techniques is not new, the problems associated with kinetic or fluid simulations of large systems all but necessitates their accelerated development. To that end, this work is broadly concerned with the construction and implementation of hybrid methods for plasma simulation on modern high-performance computing systems. A framework for the hybridization of kinetic and fluid methods is presented. This framework was then developed into the hPIC2 plasma simulation code, which overcomes the difficulty of targeting many computing architectures through the use of the Kokkos performance portability library. hPIC2 incorporates a number of innovations deemed indispensable for large-scale plasma simulation, including a novel fault tolerance scheme and advanced finite element methods furnished by the MFEM library. This work also explores conversions between fluid and kinetic descriptions. A method was developed that identifies when a kinetically modeled portion of a plasma satisfies the fluid assumptions and dynamically converts it into a fluid, which is of particular utility in highly collisional hybrid plasma simulations. The algorithms and code presented here permit the simultaneous use of fluid and kinetic descriptions for the plasma in a single simulation and adaptive conversion between them. They have been designed for and tested on architectures composing the largest supercomputers currently available. The result of this work is a significant step toward the realization of plasma simulations spanning many scales. This is particularly important for pulsed-power physics and magnetic confinement fusion, whose devices are large and complex and stress the limits of the traditional, non-hybrid approach."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Advancing hybrid fluid-kinetic methods for plasma simulation"]}]}],"canonical_facts":{"dc:contributor":["Curreli, Davide","Gammie, Charles F","Uddin, Rizwan","Kramer, Richard M"],"dc:creator":["Meredith, Logan Tate"],"dc:date":["2024-05-20","2024-08"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","The student, Logan Meredith, accepted the attached license on 2024-05-14 at 11:12.","The student, Logan Meredith, submitted this Dissertation for approval on 2024-05-14 at 11:18.","This Dissertation was approved for publication on 2024-05-20 at 11:12.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20797 on 2025-02-04 at 21:03:19","The complex, multiscale nature of plasmas necessitated the early adoption of computers by plasma physicists to model their behavior more than half a century ago. Their limited computational resources demanded fast, efficient algorithms for simulating plasmas. In general, these algorithms fall into two categories: kinetic and fluid. Kinetic algorithms retain much detailed information about how velocities are distributed in particles of the plasma, and as a consequence, they are very widely applicable but computationally expensive. In contrast, fluid algorithms discard much of this information to reduce computational cost, but must make assumptions about the plasma to compensate. Such algorithms have kept pace with developments in computing technology and are still in wide use today, owing to their inherent parallelizability. However, as high-performance computing moves into the exascale era, plasma physicists have become inspired to attempt increasingly large simulations, as evidenced by the trend toward whole-device modeling in the study of magnetic confinement fusion. The widening of the computational bottleneck has exposed flaws in the traditional paradigm of using either purely kinetic or purely fluid algorithms. It is now clear that a hybrid approach, combining the strengths of both kinetic and fluid methods, is necessary to continue efficiently modeling plasmas at the largest desired scales. Although the study of hybrid techniques is not new, the problems associated with kinetic or fluid simulations of large systems all but necessitates their accelerated development. To that end, this work is broadly concerned with the construction and implementation of hybrid methods for plasma simulation on modern high-performance computing systems. A framework for the hybridization of kinetic and fluid methods is presented. This framework was then developed into the hPIC2 plasma simulation code, which overcomes the difficulty of targeting many computing architectures through the use of the Kokkos performance portability library. hPIC2 incorporates a number of innovations deemed indispensable for large-scale plasma simulation, including a novel fault tolerance scheme and advanced finite element methods furnished by the MFEM library. This work also explores conversions between fluid and kinetic descriptions. A method was developed that identifies when a kinetically modeled portion of a plasma satisfies the fluid assumptions and dynamically converts it into a fluid, which is of particular utility in highly collisional hybrid plasma simulations. The algorithms and code presented here permit the simultaneous use of fluid and kinetic descriptions for the plasma in a single simulation and adaptive conversion between them. They have been designed for and tested on architectures composing the largest supercomputers currently available. The result of this work is a significant step toward the realization of plasma simulations spanning many scales. This is particularly important for pulsed-power physics and magnetic confinement fusion, whose devices are large and complex and stress the limits of the traditional, non-hybrid approach."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/125505"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Logan Tate Meredith"],"dc:subject":["Plasma","Hybrid Methods","Particle-in-cell","Fluid"],"dc:title":["Advancing hybrid fluid-kinetic methods for plasma simulation"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Physics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:02Z"}