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Hexahedral meshing is one of the most important steps in performing an accurate simulation using the finite element analysis (FEA). However, the current hexahedral meshing method in the industry is a nonautomatic and inefficient method, i.e. manually decomposing the model into suitable blocks and obtaining the hexahedral mesh from these blocks by mapping or sweeping algorithms. The purpose of this paper is to propose an almost automatic decomposition algorithm based on the 3D frame field and model features to replace the traditional time-consuming and laborious manual decomposition method.

The proposed algorithm is based on the 3D frame field and features, where features are used to construct feature-cutting surfaces and the 3D frame field is used to construct singular-cutting surfaces. The feature-cutting surfaces constructed from concave features first reduce the complexity of the model and decompose it into some coarse blocks. Then, an improved 3D frame field algorithm is performed on these coarse blocks to extract the singular structure and construct singular-cutting surfaces to further decompose the coarse blocks. In most modeling examples, the proposed algorithm uses both types of cutting surfaces to decompose models fully automatically. In a few examples with special requirements for hexahedral meshes, the algorithm requires manual input of some user-defined cutting surfaces and constructs different singular-cutting surfaces to ensure the effectiveness of the decomposition.

Benefiting from the feature decomposition and the 3D frame field algorithm, the output blocks of the proposed algorithm have no inner singular structure and are suitable for the mapping or sweeping algorithm. The introduction of internal constraints makes 3D frame field generation more robust in this paper, and it can automatically correct some invalid 3–5 singular structures. In a few examples with special requirements, the proposed algorithm successfully generates valid blocks even though the singular structure of the model is modified by user-defined cutting surfaces.

The proposed algorithm takes the advantage of feature decomposition and the 3D frame field to generate suitable blocks for a mapping or sweeping algorithm, which saves a lot of simulation time and requires less experience. The user-defined cutting surfaces enable the creation of special hexahedral meshes, which was difficult with previous algorithms. An improved 3D frame field generation method is proposed to correct some invalid singular structures and improve the robustness of the previous methods.

This paper aims to propose a bed and breakfast (B&B) recommendation method that takes into account review timeliness and user preferences to help consumers choose the most satisfactory B&B.

This paper proposes a B&B ranking method based on improved intuitionistic fuzzy sets. First, text mining and cluster analysis are combined to identify the concerns of consumers and construct an attribute set. Second, an attribute-level-based text sentiment analysis is established. The authors propose an improved intuitionistic fuzzy set, which is more in line with the actual situation of sentiment analysis of online reviews. Next, subjective-objective combinatorial assignments are applied, considering the consumers’ preferences. Finally, the vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) algorithm, based on the improved score function, is advised to evaluate B&Bs.

A case study is presented to illustrate the use of the proposed method. Comparative analysis with other multi-attribute decision-making (MADM) methods proves the effectiveness and superiority of the VIKOR algorithm based on the improved intuitionistic fuzzy sets proposed in this paper.

Proposing a B&B recommendation method that takes into account review timeliness and user customization is the innovation of this paper. In this approach, the authors propose improved intuitionistic fuzzy sets. Compared with the traditional intuitionistic fuzzy set, the improved intuitionistic fuzzy set increases the abstention membership, which is more in line with the actual situation of attribute-level sentiment analysis of online reviews.

Despite the technological paradigm shift presented to the architecture, engineering, construction and operations sector (AECO), the full-fledged acceptance of the building information modelling (BIM) methodology has been slower than initially anticipated. Indeed, this study aims to acknowledge the need for increasing supportive technologies enabling the use of BIM, attending to available human resources, their requirements and their tasks.

A complete case study is described, including the development process centred on design science research methodology followed by the usability assessment procedure validated by construction projects facility management operational staff.

Results show that participants could interact with BIM using openBIM processes and file formats naturally, as most participants reached an efficiency level close to that expected for users already familiar with the interface (i.e. high-efficiency values). These results are consistent with the reported perceived satisfaction and analysis of participants’ discourses through 62 semi-structured interviews.

The contributions of the present study are twofold: a proposal for a virtual reality openBIM framework is presented, particularly for the semantic enrichment of BIM models, and a methodology for evaluating the usability of this type of system in the AECO sector.

This study aims to investigate the factors affecting (i.e. determinants) the continuance of mobile learning adoption in an informal setting among higher education learners from a rural region in the Philippines. It assesses the extent of the determinants of mobile learning adoption continuance and their interrelationships and the role of a personality trait (e.g. locus of control) on its determinants.

This study used a rigorous literature review method that led to a mobile learning adoption continuance model. This proposed model analyzed the perceptions of higher education learners’ experiences on mobile learning adoption during the COVID-19 pandemic (i.e. informal setting). The data collection was self-administered using an online survey from a convenience sample size of 434 using adapted questionnaire instruments. The study used factor analysis by using a structural package for social sciences (SPSS) and analysis of the moment of the structure. The effect sizes of the direct effect, simple and serial mediation and interaction effects in a path model were analyzed by using user-defined estimand and orthogonalized approaches.

The findings indicate that the effect of perceived security risks along with perceived functional benefit and learner value affect the mobile learning adoption continuance. The perceived learner value mediates the perceived functional benefit relationship on mobile learning adoption continuance. Perceived security risk indirectly affects mobile learning adoption continuance through perceived functional benefit and learner value. In addition to this, the internal locus of control strengthens the positive relationship between perceived functional benefit and mobile learning adoption continuance. However, it dampens the positive relationship of perceived learner value.

The study provides an essential foundation on the mobile learning adoption model that focuses on its continuance. This model integrated perceived security risks, functional benefits and learner value aspects of continuance intention that higher education institutions may consider in their mobile learning initiative. It further provides evidence to intensify the important moderating role of locus of control that intervenes on the determinants of mobile learning adoption continuance.

Innovation is critical for businesses to stay competitive in today's world, as it allows them to constantly look for new ways to differentiate their products or services from their competitors as well as improve cost-effectiveness. This study explore the role of strategic human resource practices in developing organizations' competitive capabilities-differentiation and cost-effectiveness, which, improves their innovation performance to create a competitive advantage.

The authors collected data from 387 employees from 25 knowledge-intensive information technology organizations in India through a questionnaire-based survey. After checking for biases, reliability and validity, the hypothesized relationships were tested by structural equational modeling using AMOS 26.

Strategic HR practices have a significant and positive effect on innovation performance and both competitive capabilities-differentiation and cost-effectiveness. While the differentiation capability had a strong positive effect on innovation performance, cost-effectiveness capability was not significantly related to innovation performance. The differentiation capability mediates the relationship between strategic HR practices and innovation performance link, whereas the cost-effectiveness capability did not have a mediating effect.

This study provides practical insights to HR and knowledge managers to focus on development of human capital and invest in hiring, training, development, strategic performance management practices to enhance employees' knowledge behaviors, which, stimulates innovation performance.

The paper adds to the strategic HRM paradigm by clarifying the underlying process of how strategic HR practices leads to higher innovation. It affirms the vitality of choosing appropriate competitive capabilities, and supporting organizational factor for business's success. It fills an important research gap by providing original empirical evidence from knowledge intensive information technology organizations in the emerging economy of India.

The purpose of this study was to develop and test a research model that explored leader psychological capital (LPsyCap) as a predictor of follower creative performance (FCRP). The model also investigated follower job crafting (FJC) and follower knowledge collecting (FKC) and follower knowledge donating (FKD) behaviors as the multiple mediators of the trickle-down effect of LPsyCap on FCRP in a sequential manner.

Data were obtained from hotel employees in Korea. The hypotheses were tested using structural equation modeling with the user-defined estimands function.

LPsyCap boosted employees’ FCRP. FJC and FKC behaviors mediated the trickle-down effect of LPsyCap on FCRP in a sequential manner. As predicted, FKC behavior parallelly mediated the effect of FJC on FCRP.

Hotel firms should boost a workplace that would encourage employees to redefine and redesign their jobs. To achieve this, the presence of structural (e.g. learning new things in the workplace) and social (e.g. supervisor coaching) job resources and challenging job demands (e.g. willingly taking on additional tasks) would pay dividends.

This paper is one of its kind focusing on unexplored parallel and sequential multiple mediation effects that highlight FJC and FKC as the two potential mediators in the association between LPsyCap and FCRP.

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

This paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.

Fiber reinforced additive manufacturing (FRAM) is an emerging technology that combines additive manufacturing and composite materials. As a result, design freedom offered by the manufacturing process can be leveraged in design optimization. The purpose of the study is to propose a novel method that improves structural performance by optimizing 3D print orientation of FRAM components.

This work proposes a two-part design optimization method that optimizes 3D global print orientation and topology of a component to improve a structural objective function. The method considers two classes of design variables: (1) print orientation design variables and (2) density-based topology design variables. Print orientation design variables determine a unique 3D print orientation to influence anisotropic material properties. Topology optimization determines an optimal distribution of material within the optimized print orientation.

Two academic examples are used to demonstrate basic behavior of the method in tension and shear. Print orientation and sequential topology optimization improve structural compliance by 90% and 58%, respectively. An industry-level example, an aerospace component, is optimized. The proposed method is used to achieve an 11% and 15% reduction of structural compliance compared to alternative FRAM designs. In addition, compliance is reduced by 43% compared to an equal-mass aluminum design.

Current research surrounding FRAM focuses on the manufacturing process and neglects opportunities to leverage design freedom provided by FRAM. Previous FRAM optimization methods only optimize fiber orientation within a 2D plane and do not establish an optimized 3D print orientation, neglecting exploration of the entire orientation design space.

A computational fluid dynamics based parametric analysis for shell and helical tube heat exchanger (SHTHE) using CuO/water and Al₂O₃/water nanofluids is the main purpose of the present work. The parameters having impact on the performance of a heat exchanger have been studied in depth. As the solid nanoparticle shows higher thermal conductivity compared to liquid particles, inclusion of this nanoparticle into the base fluid significantly enhances the thermal conductivity of the liquid. Incorporation of nanofluid in the heat exchanger can increase its performance.

The simulation is performed in Solid-Works flow simulation, and the performance of SHTHE is observed by varying the pitch of helical tube from 0.013 to 0.018 m and coil diameter from 0.0813 to 0.116 m, keeping the other parameters constant. The tube side and shell side flow rate is kept as 2 LPM.

The results indicate that the effectiveness of the heat exchanger increases with the increase of pitch and coil diameter. The maximum effectiveness of 0.5022 for CuO/water and 0.4928 for Al₂O₃/water nanofluid is observed at a pitch of 0.018 m and the coil diameter of 0.116 m.

It is observed that CuO/water nanofluid shows better performance compared with Al₂O₃/water nanofluid. For a coil diameter of 0.116 m and pitch of 0.018 m, the SHTHE with CuO/water nanofluid shows 1.82% greater effectiveness compared to the effectiveness with Al₂O₃/water nanofluid.

The purpose of this paper is to investigate the impact of near-wall treatment approaches, which are crucial parameters in predicting the flow characteristics of open channels, and the influence of different vegetation covers in different layers.

Ansys Fluent, a computational fluid dynamics software, was used to calculate the flow and turbulence characteristics using a three-dimensional, turbulent (k-e realizable), incompressible and steady-flow assumption, along with various near-wall treatment approaches (standard, scalable, non-equilibrium and enhanced) in the vegetated channel. The numerical study was validated concerning an experimental study conducted in the existing literature.

The numerical model successfully predicted experimental results with relative error rates below 10%. It was determined that nonequilibrium wall functions exhibited the highest predictive success in experiment Run 1, standard wall functions in experiment Run 2 and enhanced wall treatments in experiment Run 3. This study has found that plant growth significantly alters open channel flow. In the contact zones, the velocities and the eddy viscosity are low, while in the free zones they are high. On the other hand, the turbulence kinetic energy and turbulence eddy dissipation are maximum at the solid–liquid interface, while they are minimum at free zones.

This is the first study, to the best of the author’s knowledge, concerning the performance of different near-wall treatment approaches on the prediction of vegetation-covered open channel flow characteristics. And this study provides valuable insights to improve the hydraulic performance of open-channel systems.