Multiscale universal interface: a concurrent framework for coupling heterogeneous solvers. Concurrently coupled numerical simulations using heterogeneous solvers are powerful tools for modeling multiscale phenomena. However, major modifications to existing codes are often required to enable such simulations, posing significant difficulties in practice. In this paper we present a C++ library, i. e. the Multiscale Universal Interface (MUI), which is capable of facilitating the coupling effort for a wide range of multiscale simulations. The library adopts a header-only form with minimal external dependency and hence can be easily dropped into existing codes. A {it data sampler} concept is introduced, combined with a hybrid dynamic/static typing mechanism, to create an easily customizable framework for solver-independent data interpretation. The library integrates MPI MPMD support and an asynchronous communication protocol to handle inter-solver information exchange irrespective of the solvers’ own MPI awareness. Template metaprogramming is heavily employed to simultaneously improve runtime performance and code flexibility. We validated the library by solving three different multiscale problems, which also serve to demonstrate the flexibility of the framework in handling heterogeneous models and solvers. In the first example, a Couette flow was simulated using two concurrently coupled Smoothed Particle Hydrodynamics (SPH) simulations of different spatial resolutions. In the second example, we coupled the deterministic SPH method with the stochastic Dissipative Particle Dynamics (DPD) method to study the effect of surface grafting on the hydrodynamics properties on the surface. In the third example, we consider conjugate heat transfer between a solid domain and a fluid domain by coupling the particle-based energy-conserving DPD (eDPD) method with the Finite Element Method (FEM).

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  1. Benjamin Rodenberg, Ishaan Desai, Richard Hertrich, Alexander Jaust, Benjamin Uekermann: FEniCS-preCICE: Coupling FEniCS to other simulation software (2021) not zbMATH
  2. Blumers, Ansel L.; Yin, Minglang; Nakajima, Hiroyuki; Hasegawa, Yosuke; Li, Zhen; Karniadakis, George Em: Multiscale parareal algorithm for long-time mesoscopic simulations of microvascular blood flow in zebrafish (2021)
  3. Zhao, Lifei; Li, Zhen; Wang, Zhicheng; Caswell, Bruce; Ouyang, Jie; Karniadakis, George Em: Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows (2021)
  4. Fournier, Yvan: Massively parallel location and exchange tools for unstructured meshes (2020)
  5. Houzeaux, G.; Garcia-Gasulla, M.; Cajas, J. C.; Borrell, R.; Santiago, A.; Moulinec, C.; Vázquez, M.: Parallel multiphysics coupling: algorithmic and computational performances (2020)
  6. Longshaw, S. M.; Pillai, R.; Gibelli, L.; Emerson, D. R.; Lockerby, D. A.: Coupling molecular dynamics and direct simulation Monte Carlo using a general and high-performance code coupling library (2020)
  7. Blumers, Ansel L.; Li, Zhen; Karniadakis, George Em: Supervised parallel-in-time algorithm for long-time Lagrangian simulations of stochastic dynamics: application to hydrodynamics (2019)
  8. Bian, Xin; Deng, Mingge; Karniadakis, George Em: Analytical and computational studies of correlations of hydrodynamic fluctuations in shear flow (2018)
  9. Zhao, Lifei; Li, Zhen; Caswell, Bruce; Ouyang, Jie; Karniadakis, George Em: Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows (2018)
  10. Yazdani, Alireza; Deng, Mingge; Caswell, Bruce; Karniadakis, George Em: Flow in complex domains simulated by dissipative particle dynamics driven by geometry-specific body-forces (2016)
  11. Bian, Xin; Li, Zhen; Karniadakis, George Em: Multi-resolution flow simulations by smoothed particle hydrodynamics via domain decomposition (2015)
  12. Tang, Yu-Hang; Kudo, Shuhei; Bian, Xin; Li, Zhen; Karniadakis, George Em: Multiscale universal interface: a concurrent framework for coupling heterogeneous solvers (2015)