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These scales may range from the size of individual particles to the entire domain of interest. Traditionally, large scale systems can only be simulated using averaging approaches that filter out the locations of individual particles. In this work, the Euler\u2013Lagrange method is used to simulate large-scale dense particle systems in which each individual particle is tracked. In order to accomplish this, the highly scalable spectral element code nek5000 has been extended to handle the multiple levels of multiphase coupling in these systems. These levels include what has been called one-, two-, and four-way coupling. Here, each level has been separated to detail the computational impact of each stage. A binned ghost particle algorithm has also been developed to efficiently handle the challenges of two- and four-way coupling in a parallel processing context. The algorithms and their implementations are then shown to scale to 65,536 Message Passing Interface (MPI) ranks in both the strong and weak limits. After this, validation is performed through simulation of a small-scale fluidized bed. Lastly, a large-scale fluidized bed is simulated with 65,536 MPI ranks and is able to capture the unique physics of the onset of fluidization.<\/jats:p>","DOI":"10.1177\/1094342019867756","type":"journal-article","created":{"date-parts":[[2019,8,12]],"date-time":"2019-08-12T23:15:53Z","timestamp":1565651753000},"page":"316-339","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":64,"title":["A scalable Euler\u2013Lagrange approach for multiphase flow simulation on spectral elements"],"prefix":"10.1177","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5329-6341","authenticated-orcid":false,"given":"David","family":"Zwick","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3619-3695","authenticated-orcid":false,"given":"S","family":"Balachandar","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2019,8,12]]},"reference":[{"key":"bibr1-1094342019867756","volume-title":"Computer Simulation of Liquids","author":"Allen MP","year":"1987","edition":"1"},{"key":"bibr2-1094342019867756","doi-asserted-by":"publisher","DOI":"10.1021\/i160024a007"},{"key":"bibr3-1094342019867756","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmultiphaseflow.2009.02.013"},{"key":"bibr4-1094342019867756","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.fluid.010908.165243"},{"key":"bibr5-1094342019867756","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9991(89)90224-6"},{"key":"bibr6-1094342019867756","doi-asserted-by":"publisher","DOI":"10.1137\/S0036144502417715"},{"key":"bibr7-1094342019867756","unstructured":"Boman E, Devine K, Fisk LA et al. 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