Darzin International Company Multidisciplinary Engineering Science Open 2 Serial Number 2 2024 08 01 Exascale CFD/CSM Coupling: Partitioned vs. Monolithic Solvers, Load Balancing, and I/O at Scale Exascale CFD/CSM Coupling: Partitioned vs. Monolithic Solvers, Load Balancing, and I/O at Scale 1 13 EN Journal Article 2024 05 24 <p>This review aims to synthesize and critically evaluate recent advancements in coupling computational fluid dynamics (CFD) and computational structural mechanics (CSM) at exascale levels, focusing on solver paradigms, load balancing, algorithmic scalability, and data management challenges in massively parallel environments. A qualitative systematic review design was employed to consolidate insights from cutting-edge studies on exascale multiphysics coupling. Sixteen peer-reviewed articles published between 2018 and 2025 were selected from Scopus, Web of Science, IEEE Xplore, and ScienceDirect, using keywords such as “exascale CFD,” “CSM coupling,” “monolithic solver,” “partitioned framework,” “load balancing,” and “parallel I/O.” Data collection was conducted exclusively through literature analysis, and coding was performed using Nvivo 14 software. Thematic analysis followed open, axial, and selective coding to extract conceptual relationships among solver architectures, scalability bottlenecks, and I/O strategies. Analytical saturation was reached after the sixteenth study, ensuring comprehensive thematic convergence across the dataset. Five dominant themes emerged: (1) solver coupling paradigms, (2) load balancing and parallel scalability, (3) I/O and data management, (4) algorithmic and numerical scalability, and (5) emerging trends and future directions. Results indicate that partitioned solvers provide modularity and flexibility but struggle with communication overhead at large node counts, while monolithic frameworks achieve greater numerical robustness at higher computational costs. Dynamic load balancing and hybrid MPI + OpenMP or GPU parallelism were identified as key enablers of exascale scalability. Efficient I/O frameworks such as ADIOS2 and HDF5, along with in-situ data processing and hierarchical storage, were critical for maintaining performance sustainability. The integration of machine learning, fault tolerance, and hybrid coupling strategies defines the next frontier of CFD/CSM research. Exascale CFD/CSM coupling requires co-designed strategies that integrate solver stability, load adaptivity, and efficient data movement. The review underscores that achieving exascale readiness is less a matter of hardware scale and more a function of algorithmic intelligence, communication efficiency, and workflow resilience.</p> https://jmesopen.com/index.php/jmesopen/article/download/19/17