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The purpose of this paper is to develop parallel algorithms for moving boundary simulations by local remeshing and compose them to a fully parallel simulation cycle for the solution of problems with engineering interests.

The moving boundary problems are solved by unsteady flow computations coupled with six-degrees-of-freedom equations of rigid body motion. Parallel algorithms are developed for both computational fluid dynamics (CFD) solution and grid deformation steps. Meanwhile, a novel approach is developed for the parallelization of the local remeshing step. It inputs a distributed mesh after deformation, then marks low-quality elements to be deleted on the respective processors. After that, a parallel domain decomposition approach is used to repartition the hole mesh and then to redistribute the resulting sub-meshes onto all available processors. Then remesh individual sub-holes in parallel. Finally, the element redistribution is rebalanced.

If the CFD solver is parallelized while the remaining steps are executed in sequential, the performance bottleneck of such a simulation cycle is observed when the simulation of large-scale problem is executed. The developed parallel simulation cycle, in which all of time-consuming steps have been efficiently parallelized, could overcome these bottlenecks, in terms of both memory consumption and computing efficiency.

A fully parallel approach for moving boundary simulations by local remeshing is developed to solve large-scale problems. In the algorithm level, a novel parallel local remeshing algorithm is present. It repartitions distributed hole elements evenly onto all available processors and ensures the generation of a well-shaped inter-hole boundary always. Therefore, the subsequent remeshing step can fix the inter-hole boundary involves no communications.

The purpose of this paper is to propose a partitioned approach by coupling the smoothed profile method (SPM) and the Euler tension beam model in simulating a vortex-induced vibration of both rigid and flexible cylinders at various reduced velocities.

For the fluid part, SPM in the framework of the spectral element method is adopted to simulate the flow. The advantage of SPM lies in modelling multiple complex shapes as it uses a fixed computational mesh without conformation to the geometry of the particles. For the structure part, an elastic-mounted rigid cylinder is considered in two-dimensional (2D) simulations, while a flexible cylinder with a Euler tension beam model is used in three-dimensional simulations.

Firstly, in the flow past a freely vibrating cylinder, the maximum vibration responses of the cylinder are about 0.73D and 0.1D in the y and x directions, respectively, which occur at the point U_r = 5.75 and are much higher than U_r = 5 in 2D simulations. It is found that the numerical results from the SPM solver are very consistent with those from the NEKTAR-Arbitrary Lagrangian Eulerian method (NEKTAR-ALE) solver or the NEKTAR-Fourier solver. Furthermore, the flow past the tandem cylinders is also investigated, where the upstream cylinder is static while the downstream one is free to vibrate. Specifically, the beating behaviour is captured from the vibration response of the freely vibrating cylinder under the reduced velocity of U_r = 6 with a gap distance of L = 3.5D.

The originality of the paper lies in coupling the SEM with the Euler beam model in simulating the vortex induced vibration (VIV) of flexible cylinders.

When a reflected shock interacts with the boundary layer in a shock tube, the shock bifurcation occurs near the walls. Although the study of the shock bifurcation has been carried out by many researchers for several decades, little attention has been devoted to investigate the instability pattern of the bifurcation. This research work aims to successfully capture the asymmetry of the whole flow field, and attempt to achieve the instability mechanism of the shock bifurcation by a direct numerical simulation of the reflected shock wave/boundary layer interaction at Ma = 1.9. In addition, the reason for the formation of the bifurcated structure is also explored.

The spatial and temporal evolution of the shock bifurcation is obtained by solving the two-dimensional compressible Navier–Stokes equations using a seventh-order accurate weighted essentially non-oscillatory (WENO) scheme and a three-step Runge–Kutta time advancing approach.

The results show that the formation of shock bifurcation is mainly because of the shock/gradient field interaction, and the height of the bifurcated foot increases with the growth of the shock intensity and the gradient field. The unsteady asymmetry of the upper and bottom shock bifurcated structures is because of the vortex shedding with high frequency in the rear recirculation zone, which leads to the fluctuation of the recirculation area. The vortex shedding process behind the bifurcated structure closely resembles the Karman vortex street formed by the flow around the cylinder. The dimensionless vortex shedding frequency varies between 0.01 and 0.02. In comparison to the scenario at Ma = 1.9, the occurring time of instability is delayed and the upper and bottom bifurcated feet intersect in a relatively short time at Ma = 3.5. The region behind the bifurcated shock is a transitional flow field containing obvious cell structures and “isolated islands.”

This paper discovers an unsteady flow pattern of the shock bifurcation, and the mechanism of this instability in the reflected shock/boundary layer interaction is revealed in detail.

Sizing functions are crucial inputs for unstructured mesh generation since they determine the element distributions of resulting meshes to a large extent. Meanwhile, automating the procedure of creating a sizing function is a prerequisite to set up a fully automatic mesh generation pipeline. In this paper, an automatic algorithm is proposed to create a high-quality sizing function for an unstructured surface and volume mesh generation by using a triangular mesh as the background mesh.

A practically efficient and effective solution is developed by using local operators carefully to re-mesh the tessellation of the input Computer Aided Design (CAD) models. A nonlinear programming (NLP) problem has been formulated to limit the gradient of the sizing function, while in this study, the object function of this NLP is replaced by an analytical equation that predicts the number of elements. For the query of the sizing value, an improved algorithm is developed by using the axis-aligned bounding box (AABB) tree structure.

The local operations of re-meshing could effectively and efficiently resolve the banding issue caused by using the default tessellation of the model to define a sizing function. Experiments show that the solution of the revised NLP, in most cases, could provide a better solution at the lower cost of computational time. With the help of the AABB tree, the sizing function defined at a surface background mesh can be also used as the input of volume mesh generation.

Theoretical analysis reveals that the construction of the initial sizing function could be reduced to the solution of an optimization problem. The definitions of the banding elements and surface proximity are also given. Under the guidance of this theoretical analysis, re-meshing and ray-casting technologies are well-designed to initial the sizing function. Smoothing with the revised NLP and querying by the AABB tree, the paper provides an automatic method to get a high-quality sizing function for both surface and volume mesh generation.

Currently, the Covid-19 pandemic is changing how consumers shop, encouraging deeper levels and increased reliance on e-commerce systems and social media such as online communities. The online interaction of consumers is more important and brings many uncertainties, which impact the original commerce environment. This study aim to investigate the ethical consideration of information credibility and perceived privacy risk from a psychology perspective in marketing, this study draws on social support theory from social psychology to develop a research model to investigate the role of information credibility and perceived privacy risk on social commerce websites.

This study investigated social commerce websites and communities. The research data of this study was collected through a questionnaire from consumers on three famous social commerce platforms. Using PLS-SEM to perform data analysis, this study research the importance of information credibility, perceived privacy risk and trust on social commerce websites.

The findings discuss individuals' reaction to privacy issues and to understand the motives to disclose or reveal personal information within a marketing or consumption context. The research also explores the theoretical implications by integrating theories from information systems and social psychology to investigate ethical issues in social commerce.

Covid-19 makes peer-to-peer communication in online communities is developing collaborative consumption, and information produced in these communities can influence the decisions of consumers. Covid-19 has exacerbated such a change in social commerce environment. Therefore, information credibility plays an important role in developing online communities. It is important to look at the psychological antecedents that drive consumers' willingness to share their personal information when using online communities. The author has clarified which aspects of trust in social commerce should be strategized, including information trustworthiness, perceived privacy risks, social support and information sharing. These are the details that companies should pay more attention to when operating social commerce. Only by paying more attention to these details and giving consumers a positive feeling can consumers' trust be maintained or enhanced, ultimately leading to a successful trust economy.

Based on the error analysis, the authors proposed a new kind of high accuracy boundary element method (BEM) (HABEM), and for the large-scale problems, the fast algorithm, such as adaptive cross approximation (ACA) with generalized minimal residual (GMRES) is introduced to develop the high performance BEM (HPBEM). It is found that for slender beams, the stress analysis using iterative solver GMRES will difficult to converge. For the analysis of slender beams and thin structures, to enhance the efficiency of GMRES solver becomes a key problem in the development of the HPBEM. The purpose of this paper is study on the preconditioning method to solve this convergence problem, and it is started from the 2D BE analysis of slender beams.

The conventional sparse approximate inverse (SAI) based on adjacent nodes is modified to that based on adjacent nodes along the boundary line. In addition, the authors proposed a dual node variable merging (DNVM) preprocessing for slender thin-plate beams. As benchmark problems, the pure bending of thin-plate beam and the local stress analysis (LSA) of real thin-plate cantilever beam are applied to verify the effect of these two preconditioning method.

For the LSA of real thin-plate cantilever beams, as GMRES (m) without preconditioning applied, it is difficult to converge provided the length to height ratio greater than 50. Even with the preconditioner SAI or DNVM, it is also difficult to obtain the converged results. For the slender real beams, the iteration of GMRES (m) with SAI or DNVM stopped at wrong deformation state, and the computation failed. By changing zero initial solution to the analytical displacement solution of conventional beam theory, GMRES (m) with SAI or DNVM will not be stopped at wrong deformation state, but the stress error is still difficult to converge. However, by GMRES (m) combined with both SAI and DNVM preconditioning, the computation efficiency enhanced significantly.

This paper presents two preconditioners: DNVM and a modified SAI based on adjacent nodes along the boundary line of slender thin-plate beam. In the LSA, by using GMRES (m) combined with both DNVM and SAI, the computation efficiency enhanced significantly. It provides a reference for the further development of the 3D HPBEM in the LSA of real beam, plate and shell structures.

This paper conducted a study on the energy-saving potential of a developed thermotropic window. Office buildings in different climate regions of China were compared in terms of heating, cooling and lighting energy demands. Results show that annual heating and cooling energy demands for office buildings differ largely, while lighting energy demand at different climates keeps a significant percentage of the total energy demand, ranging from 36.1% to 66.3%. Meanwhile, thermotropic windows achieve a great advantage in improving daylighting performance and in reducing the overall energy demand, by reducing the overall energy demand by 2.27%-8.7% and 10.1%-21.72%, respectively, compared to movable shading devices and Low-E windows. This means that this kind of thermotropic windows have a great potential in applications in different climatic regions and can be considered as a good substitute of solar shading devices and Low-E windows.

A large number of residential buildings in hot summer and cold winter zone of China are non-energy efficient with poor indoor thermal conditions. Retrofitting residential buildings with energy efficiency measures is thus important for residents. However, this work progressed slowly because practically applicable measures that not only have high energy savings but also improve indoor thermal performance have not been studied. Thus, this paper carried out a simulation study on the selection of suitable energy saving measures for residential buildings in hot summer and cold winter zone of China. Five potential energy saving options are considered and the energy, indoor thermal comfort and economic performance are compared. The results show that adding movable solar shades is the optimum option with all performance indices ranking first. Meanwhile, this measure is also the only acceptable energy saving solution for residents since its payback period is less than the lifespan of a building. As a conclusion, it is recommended to use movable solar shades as a first priority when retrofitting residential buildings.

This study investigated the building energy, glare and daylight performance of overhang using building simulation software Energyplus in order to identify an optimal depth in hot summer and cold winter zone. A typical building with different window-to-wall ratios (WWR) was modeled and different overhang depths were considered. Results showed that the optimal overhang depths are 0.9m (WWR=0.15), 1.16m (WWR=0.3) and 1.62m (WWR=0.57), respectively. The total energy savings from overhang design can be ranging from about 3% to 24% depending on WWR and overhang depth. Moreover, the regression relationship between optimal overhang depth and WWR is given to help identify the best overhang dimension at the design stage. The potential energy saving performance for different WWRs then can be roughly inferred according to a total energy saving chart without building energy simulation. In conclusion, to be applicable in buildings, an overhang depth of 0.6-0.8m is suitable in this region since it has a balance in energy performance and aesthetic appearance.

Location-based services (LBS) have become an effective commercial marketing tool. However, regarding retail store location selection, it is challenging to collect analytical data. In this study, location-based social network data are employed to develop a retail store recommendation method by analyzing the relationship between user footprint and point-of-interest (POI). According to the correlation analysis of the target area and the extraction of crowd mobility patterns, the features of retail store recommendation are constructed.

The industrial density, area category, clustering and area saturation calculations between POIs are designed. Methods such as Kernel Density Estimation and K-means are used to calculate the influence of the area relevance on the retail store selection.

The coffee retail industry is used as an example to analyze the retail location recommendation method and assess the accuracy of the method.

This study is mainly limited by the size and density of the datasets. Owing to the limitations imposed by the location-based privacy policy, it is challenging to perform experimental verification using the latest data.

An industrial relevance questionnaire is designed, and the responses are arranged using a simple checklist to conveniently establish a method for filtering the industrial nature of the adjacent areas. The New York and Tokyo datasets from Foursquare and the Tainan city dataset from Facebook are employed for feature extraction and validation. A higher evaluation score is obtained compared with relevant studies with regard to the normalized discounted cumulative gain index.