[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-81810-en":3,"doc-seo-81810-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},81810,137441390410,"Hazel","https://ap-avatar.wpscdn.com/avatar/2000252f4ab5702993?_k=1776741390130283984",8,"Research & Report","FUSE A Partitioned Field Exchange Framework for Coupling Physics Simulations in FEBio","Computational biomechanics increasingly demands coupled models spanning mechanics, transport, chemistry, and biological regulation across multiple spatial and temporal scales. While FEBio offers open-source multiphysics capabilities through monolithic formulations, assembling independently developed physics models into reproducible workflows remains difficult. FUSE (FEBio Unified Simulation and Exchange) is a partitioned coupling plugin that enables structured field exchange between separate FEBio models, using a time-decoupled strategy and reusable FEBio data maps with filtering.","FUSE: A Partitioned Field-Exchange Framework for Coupling  \nPhysics Simulations in FEBio  \nSteve A. Maas+1 , Farhan Muhib+1 , Jeffrey A. Weiss 1*  \n1Department of Biomedical Engineering, and  \nScientific Computing and Imaging Institute,  \nUniversity of Utah, Salt Lake City, UT  \n+ co-first authors  \n*Corresponding Author:  \nJeffrey A. Weiss  \nDepartment of Bioengineering  \nUniversity of Utah  \n72 South Central Campus Drive, Rm. 2646  \nSalt Lake City, UT 84112  \n[jeff.weiss@utah.edu](jeff.weiss@utah.edu)  \nKeywords: FEBio, Finite Element, Biomechanics, Multiphysics Simulation, Partitioned Solution  \nAbstract  \nComputational biomechanics increasingly requires models that combine mechanics, transport, chemistry, and biological regulation across different spatial and temporal scales. The FEBio simulation software (Finite Elements for Biomechanics and Biophysics) provides extensive opensource capabilities for modeling these processes using monolithic approaches. However, assembling independently developed physics models into reproducible coupled workflows remains challenging. Existing approaches often require custom scripts or external software pipelines, which can limit model reuse and complicate development. We present FUSE, the FEBio Unified Simulation and Exchange framework, a partitioned coupling plugin that enables separately defined FEBio models to communicate through structured field exchange. FUSE is designed for problems that are best solved independently, particularly when fast mechanical responses influenceslower biological or chemical evolution. The framework uses a time-decoupled strategy in which a primary model advances on the longer time scale, while one or more secondary models are repeatedly initialized, supplied with updated fields, solved over shorter time horizons, with results returned to the primary model. Field exchange utilizes existing FEBio data maps, output fields, and user-specified filters, allowing coupled workflows to be constructed without modifying the underlying solvers. The framework was able to reproduce reference coupled solutions while handling bidirectional transfer, spatial field mapping, and filtered exchange of model variables. Example applications demonstrated coupling between mechanical loading and chemical degradation in injured cartilage and interaction between biological tissue formation and mechanical feedback during bone healing. By separating coupling logic from physics implementation, FUSE provides a practical mechanism for building maintainable multiphysics workflows within FEBio.  \n1. Introduction  \nMany problems in computational biomechanics are inherently multiphysics and multiscale, and accurate prediction increasingly depends on coordinated treatment of mechanics, transport, chemistry, and cell-mediated regulation rather than isolated treatment of a single process [1-3] . Importantly, the physical processes within a single multiphysics model often unfold over dramatically different time scales. One example arises in biological tissues, where catabolic and anabolic processes are regulated through the combined interaction among mechanical, chemical, and biological systems [1, 2, 4]. In hydrated tissues, deformation alters fluid flow, solute transport, and reaction kinetics, while evolving chemical and cellular states regulate growth, remodeling, damage, and degeneration [5-7]. This is particularly evident in load-bearing tissues during growth and healing, where transport and chemistry do not simply accompany deformation but participate directly in setting tissue state and function [5, 7] . Furthermore, mechanical loading and the associated strain fields typically evolve over relatively short time scales, whereas downstream biological processes such as cell migration, proliferation, apoptosis, and matrix turnover may evolve over hours, days, or longer in applications such as fracture healing, angiogenesis, and tissue degeneration [7-9] .  \nThis scientific need is accompanied b","cbCaiufrpwfrdKB7","https://ap.wps.com/l/cbCaiufrpwfrdKB7","pdf",1270777,2,1,31,"English","en",105,"# Abstract\n# 1. 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