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The purpose of this paper is the development of a new density-based (DB) semi-Lagrangian method to speed up the conventional pressure-based (PB) semi-Lagrangian methods.

The semi-Lagrangian-based solvers are typically PB, i.e. semi-Lagrangian pressure-based (SLPB) solvers, where a Poisson equation is solved for obtaining the pressure field and ensuring a divergence-free flow field. As an elliptic-type equation, the Poisson equation often relies on an iterative solution, so it can create a challenge of parallel computing and a bottleneck of computing speed. This study proposes a new DB semi-Lagrangian method, i.e. the semi-Lagrangian artificial compressibility (SLAC), which replaces the Poisson equation by a hyperbolic continuity equation with an added artificial compressibility (AC) term, so a time-marching solution is possible. Without the Poisson equation, the proposed SLAC solver is faster, particularly for the cases with more computational cells, and better suited for parallel computing.

The study compares the accuracy and the computing speeds of both SLPB and SLAC solvers for the lid-driven cavity flow and the step-flow problems. It shows that the proposed SLAC solver is able to achieve the same results as the SLPB, whereas with a 3.03 times speed up before using the OpenMP parallelization and a 3.35 times speed up for the large grid number case (512 × 512) after the parallelization. The speed up can be improved further for larger cases because of increasing the condition number of the coefficient matrixes of the Poisson equation.

This paper proposes a method of avoiding solving the Poisson equation, a typical computing bottleneck for semi-Lagrangian-based fluid solvers by converting the conventional PB solver (SLPB) to the DB solver (SLAC) through the addition of the AC term. The method simplifies and facilitates the parallelization process of semi-Lagrangian-based fluid solvers for modern HPC infrastructures, such as OpenMP and GPU computing.

The purpose of this paper is to study the soot formation and evolution by using this newly developed Lagrangian particle tracking with weighted fraction Monte Carlo (LPT-WFMC) method.

The weighted soot particles are used in this MC framework and is tracked using Lagrangian approach. A detailed soot model based on the LPT-WFMC method is used to study the soot formation and evolution in ethylene laminar premixed flames.

The LPT-WFMC method is validated by both experimental and numerical results of the direct simulation Monte Carlo (DSMC) and Multi-Monte Carlo (MMC) methods. Compared with DSMC and MMC methods, the stochastic error analysis shows this new LPT-WFMC method could further extend the particle size distributions (PSDs) and improve the accuracy for predicting soot PSDs at larger particle size regime.

Compared with conventional weighted particle schemes, the weight distributions in LPT-WFMC method are adjustable by adopting different fraction functions. As a result, the number of numerical soot particles in each size interval could be also adjustable. The stochastic error of PSDs in larger particle size regime can also be minimized by increasing the number of numerical soot particles at larger size interval.

This paper aims to provide discussions of a numerical method for bubbly flows and the interaction between a vortex ring and a bubble plume.

Small bubbles are released into quiescent water from a cylinder tip. They rise under the buoyant force, forming a plume. A vortex ring is launched vertically upward into the bubble plume. The interactions between the vortex ring and the bubble plume are numerically simulated using a semi-Lagrangian–Lagrangian approach composed of a vortex-in-cell method for the fluid phase and a Lagrangian description of the gas phase.

A vortex ring can transport the bubbles surrounding it over a distance significantly depending on the correlative initial position between the bubbles and the core center. The motion of some bubbles is nearly periodic and gradually extinguishes with time. These bubble trajectories are similar to two-dimensional-helix shapes. The vortex is fragmented into multiple regions with high values of Q, the second invariant of velocity gradient tensor, settling at these regional centers. The entrained bubbles excite a growth rate of the vortex ring's azimuthal instability with a formation of the second- and third-harmonic oscillations of modes of 16 and 24, respectively.

A semi-Lagrangian–Lagrangian approach is applied to simulate the interactions between a vortex ring and a bubble plume. The simulations provide the detail features of the interactions.

This study aims to provide discussions of the numerical method and the bubbly flow characteristics of an annular bubble plume.

The bubbles, released from the annulus located at the bottom of the domain, rise owing to buoyant force. These released bubbles have diameters of 0.15–0.25 mm and satisfy the bubble flow rate of 4.1 mm³/s. The evolution of the three-dimensional annular bubble plume is numerically simulated using the semi-Lagrangian–Lagrangian (semi-L–L) approach. The approach is composed of a vortex-in-cell method for the liquid phase and a Lagrangian description of the gas phase.

First, a new phenomenon of fluid dynamics was discovered. The bubbly flow enters a transition state with the meandering motion of the bubble plume after the early stable stage. A vortex structure in the form of vortex rings is formed because of the inhomogeneous bubble distribution and the fluid-surface effects. The vortex structure of the flow deforms as three-dimensionality appears in the flow before the flow fully develops. Second, the superior abilities of the semi-L–L approach to analyze the vortex structure of the flow and supply physical details of bubble dynamics were demonstrated in this investigation.

The semi-L–L approach is applied to the simulation of the gas–liquid two-phase flows.

Some existing finite difference methods for the numerical solution of convection dominated diffusion equations are compared. Two semi‐implicit methods, Lagrangian based and applied on an Eulerian grid system, are then derived and discussed. The new methods are demonstrated to be transportive and unconditionally stable. Moreover, the artificial diffusion and the spurious oscillations of these methods are also analysed and compared. Extensions to n‐space variables and to non‐linear equations are indicated, along with various applications.

The purpose of this paper is to evaluate the health‐states of unit under test (UUT) in aerospace systems by means of unreliable test outcomes, and the evaluation results can provide a guide for engineers to carry out proper maintenance prior to total failure.

In this paper, the authors formulate the health‐state evaluation (HSE) problem with unreliable test outcomes based on Bayes rule, and develop the Lagrangian relaxation and adaptive genetic algorithm (LRAGA) to solve it. The solution scheme can be viewed as a two‐level coordinated solution framework for the HSE problem. At the top level, the Lagrange multipliers are updated by using AGA. At the bottom level, each of the sub‐problems is solved by using AGA.

The experimental results show that the HSE model appears promising and the LRAGA can obtain the higher quality solution and converge to it at a faster rate than conventional methods (i.e. Lagrangian relaxation (LR), genetic algorithm (GA), simulated annealing (SA) and Lagrangian relaxation and genetic algorithm (LRGA).

The proposed method for the HSE problem of large‐scale systems which include thousands of faults and tests needs to be verified further.

The HSE results for aerospace systems can help engineers to carry out a schedule for prompt maintenance prior to UUTs' failure, to avoid the consequences of total failure. It is important to improve aerospace systems' safety, reliability, maintainability, affordability, and reduce life cycle cost.

This paper constructs the HSE model with unreliable test outcomes based on the Bayes rule and proposes a method based on LRAGA to solve the HSE problem.

This article presents a geometrically non-linear finite element formulation for the analysis of planar two-layer beam-columns taking into account the inter-layer slip and uplift.

The co-rotational method is adopted, in which the motion of the element is decomposed into a rigid body motion and a small deformational one. The geometrically linear formulation can be used in the local frame and automatically be transformed into a geometrically nonlinear one. In co-rotational frame, both layers are assumed to be discretely connected at the element ends. Slips and uplifts are assumed to be small. Consequently, the condition of non interpenetration between the layers can be treated using a node-to-node contact algorithm. The resolution methods such as penalty (PM) and augmented Lagrangian method (ALM) with Uzawa updating scheme can be used.

The non-penetration condition between the layers of composite beams can be formulated by using contact law. It is found that despite a low convergence rate of augmented Lagrangian method compared to penalty method, the former prevents the unrealistic penetration. Besides, it is shown that the buckling load of the composite beam-column is largely affected by the uplift stiffness of the connectors.

The proposed finite element model is capable of simulating accurately the geometrically non-linear behavior of planar two-layer beam-columns taking into account the inter-layer slip and uplift. Regarding uplift, the non-penetration condition is strictly enforced by considering rigorous contact conditions at the interface. The constraint problem is solved using the penalty method or the augmented Lagrangian method with the Uzawa updating scheme.

The cross-docking strategy has a significant influence on supply chain and logistics efficiency. This paper aims to investigate the most suitable and efficient way to schedule the transfer of logistics activities and present a meta-heuristic method of the truck scheduling problem in cross-docking logistics. A truck scheduling problem with products time window is investigated with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks.

This research proposed a meta-heuristic method for the truck scheduling problem with products time window. To solve the problem, a lower bound of the problem is built through a novel two-stage Lagrangian relaxation problem and on account of the NP-hard nature of the truck scheduling problem, the novel red deer algorithm with the mechanism of the heuristic oscillating local search algorithm, as well as adaptive memory programming was proposed to overcome the inferior capability of the original red deer algorithm in the aspect of local search and run time.

Theory analysis and simulation experiments on an industrial case of a cross-docking center with a product’s time window are conducted in this paper. Satisfactory results show that the performance of the red deer algorithm is enhanced due to the mechanism of heuristic oscillating local search algorithm and adaptive memory programming and the proposed method efficiently solves the real-world size case of truck scheduling problems in cross-docking with product time window.

The consideration of products time window has very realistic significance in different logistics applications such as cold-chain logistics and pharmaceutical supply chain. Furthermore, the novel adaptive memory red deer algorithm could be modified and applied to other complex optimization scheduling problems such as scheduling problems considering energy-efficiency or other logistics strategies.

For the first time in the truck scheduling problem with the cross-docking strategy, the product’s time window is considered. Furthermore, a mathematical model with objectives of minimizing the total product transshipment time and earliness and tardiness cost of outbound trucks is developed. To solve the proposed problem, a novel adaptive memory red deer algorithm with the mechanism of heuristic oscillating local search algorithm was proposed to overcome the inferior capability of genetic algorithm in the aspect of local search and run time.

The simulation of the fluid–solid interaction (FSI) problem is important for both academic studies and engineering applications. However, the numerical approach for simulating the FSI problems is a great challenge owing to the large discrepancy of material properties and inconsistent description of grid motion between the fluid and solid domains. The difficulties will be further increased if there are multiple materials in the fluid region. In these complicated applications, interface reconstruction, multi-material advection and FSI must be all taken into account. This paper aims to present an effective integrated work of multi-material arbitrary Lagrangian Eulerian (MMALE) method, finite element (FE) method and the continuum analogy method to simulate the complex FSI problems involving multi-material flow. The coupled method is used to simulate the three-dimensional CONT test and the blast-plate interaction. The numerical results show good agreement with the benchmark and the experiment data, which indicates that the presented method is effective for solving the complicated FSI problems.

MMALE and FE methods are used to simulate fluid and solid regions, respectively. The interfacial nodes of fluid and solid are required to be coincident in the whole simulation so the interacted force can be easily and accurately calculated. To this end, the continuum analogy method is used in the rezoning phase.

The coupled method is used to simulate the three-dimensional CONT test and the blast-plate interaction. The numerical results show good agreement with the benchmark and the experiment data, which indicates that the presented method is effective for solving the complicated FSI problems.

To the best of the authors’ knowledge, this is the first time that the ALE method, moment of fluid interface reconstruction method, continuum analogy method and the FE method are combined to solve complicated practical problems.

Moving interface problems exist commonly in nature and industry, and the main difficulty is to represent the interface. The purpose of this paper is to capture the accurate interface, a novel three-dimensional one-layer particle level set (OPLS) method is presented by introducing Lagrangian particles to reconstruct the seriously distorted level set function.

First, the interface is captured by the level set method. Then, the interface is corrected with only one-layer particles advected with the flow to ensure that the level set function value of the particle is equal to 0. When interfaces are merged, all particles in merged regions are deleted, while the added particles near the generated interface are used to determine the interface as the interface is separated.

The OPLS method is validated with well-known benchmark examples, such as the long-term advection of a sphere, the rotation of a three-dimensional slotted disk and sphere, single vortex in a box, sphere merging and separation, deformation of a sphere. The simulation results indicate that the proposed method is found to be highly reliable and accurate.

This method exhibits excellent conservation of the area bounded by the interface. The extraordinary performance is also shown in dealing with complex interface topological changes.