State-of-the-art numerical fluid–structure interaction methods for aortic and mitral heart valves simulations: A review

Numerical fluid–structure interaction (FSI) methods have been widely used to predict the cardiac mechanics and associated hemodynamics of native and artificial heart valves (AHVs). Offering a high degree of spatial and temporal resolution, these methods circumvent the need for cardiac surgery to assess the performance of heart valves. Assessment of these FSI methods in terms of accuracy, realistic modeling, and numerical stability is required, which is the objective of this paper. FSI methods could be classified based on how the computational domain is discretized, and on the coupling techniques employed between fluid and structure domains. The grid-based FSI methods could be further classified based on the kinematical description of the computational fluid (blood) grid, being either fixed grid, moving grid, or combined fixed–moving grid methods. The review reveals that fixed grid methods mostly cause imprecise calculations of flow parameters near the blood–leaflet interface. Moving grid methods are more accurate, however they require cumbersome remeshing and smoothing. The combined fixed–moving grid methods overcome the shortcomings of fixed and moving grid methods, but they are computationally expensive. The mesh-free methods have been able to encounter the problems faced by grid-based methods; however, they have been only limitedly applied to heart valve simulations. Among the coupling techniques, explicit partitioned coupling is mostly unstable, however the implicit partitioned coupling not only has the potential to be stable but is also comparatively cheaper. This in-depth review is expected to be helpful for the readers to evaluate the pros and cons of FSI methods for heart valve simulations.

Numerical study on trajectory of released store with manipulation of grid connections

Purpose This study aims to present a moving grid method based on the manipulation of connections. Design/methodology/approach In this study, the grid’s connections were manipulated to simulate a released store’s displacement. The selected model in this research is the EGLIN test case. In the introduced method, connections are modified in specific nodes of the grid. Governing flow equations were solved with the finite volume method. The major characteristic of this technique is using the averaging method for calculating the flux of cells. Findings This method maintains the grid’s quality even in large displacements of the released store. The three-dimensional simulation was carried out in transonic and supersonic regimes. Comparison of the results with experimental data were highly satisfactory. Research limitations/implications Using this moving grid method is recommended for simulating other models. Practical implications Prediction of store trajectory released from air vehicles is one of the most critical issues under study especially in the design of new stores. Originality/value The most prominent advantage of this method is maintaining the grid quality simultaneous with large displacements of the released store.

Online Prediction of Ship Roll Motion in Waves Based on Auto-Moving Gird Search-Least Square Support Vector Machine

A novel method based on auto-moving grid search-least square support vector machine (AGS-LSSVM) is proposed for online predicting ship roll motion in waves. To verify the method, simulation data are used, which are obtained by solving the second-order nonlinear differential equation of ship roll motion using the fourth-order Runge–Kutta method, while the Pierson–Moskowitz spectrum (P–M spectrum) is used to simulate the irregular waves. Combining the sliding time window with the least square support vector machine (LS-SVM), the samples in the time window are used to train the LS-SVM model, and the model hyperparameters are optimized online by the auto-moving grid search (AGS) method. The trained model is used to predict the roll motion in the next 30 seconds, and the prediction results are compared with the simulation data. It is shown that the AGS-LSSVM is an effective method for online predicting ship roll motion in waves.