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This paper aims to investigate the performance of two novel numerical methods, the face-based smoothed finite element method (FS-FEM) and the edge-based smoothed finite element method (ES-FEM), which employ linear tetrahedral elements, for the purpose of strength assessment of a high-speed train hollow axle.

The calculation of stress for the wheelset, comprising an axle and two wheels, is facilitated through the application of the European axle strength design standard. This standard assists in the implementation of loading and boundary conditions and is exemplified by the typical CRH2 high-speed train wheelset. To evaluate the performance of these two methods, a hollow cylinder cantilever beam is first used as a benchmark to compare the present methods with other existing methods. Then, the strength analysis of a real wheelset model with a hollow axle is performed using different numerical methods.

The results of deflection and stress show that FS-FEM and ES-FEM offer higher accuracy and better convergence than FEM using linear tetrahedral elements. ES-FEM exhibits a superior performance to that of FS-FEM using linear tetrahedral elements, showing accuracy and convergence close to FEM using hexahedral elements.

This study channels the novel methods (FS-FEM and ES-FEM) in the static stress analysis of a railway wheelset. Based on the careful testing of FS-FEM and ES-FEM, both methods hold promise as more efficient tools for the strength analysis of complex railway structures.

This study aims to propose and numerically assess different ways of discretising a very weak formulation of the Poisson problem.

We use integration by parts twice to shift smoothness requirements to the test functions, thereby allowing low-regularity data and solutions.

Various conforming discretisations are presented and tested, with numerical results indicating good accuracy and stability in different types of problems.

This is one of the first articles to propose and test concrete discretisations for very weak variational formulations in primal form. The numerical results, which include a problem based on real MRI data, indicate the potential of very weak finite element methods for tackling problems with low regularity.

The purpose of the study is to provide a dataset about geometrical constructions of early Ottoman tombs for conservation studies. Thus, a proposal for the restitution phase of the damaged tombs aims to develop.

The study is composed of four phases. First, the representative plan and section drawings of early Ottoman Tombs were redrawn; second, a geometrical analysis was made, a proposal table was prepared for the restitution of the damaged tombs; and last, this table was applied to tomb examples and restitution drawings are verified with the original situation of the tombs.

Early Ottoman tombs may be interpreted through geometric shapes, including the square, circle, triangle, octagon, arsin grid and quadrature systems. The arsin grid system provides information about the position of the domes and the height of the drums and windows. Quadrature establishes the highest point of domes and entrances. The proposal table, developed from the obtained results, facilitated the identification of the original elements, including the dome, drum, window and portal. This information is crucial for conducting further studies on restitution.

The abundance and dispersed nature of tomb structures compared to other architectural designs pose challenges in their scholarly examination. The early Ottoman tombs, which experienced an increase in numbers following the Conquest of Istanbul, serve as the initial expressions and embodiments of novel architectural endeavors. Thus, the determination of design ideas of the early Ottoman tombs sheds light on Ottoman architectural practice, which has remained largely unknown and guided the conservation studies of the tombs that have lost their integrity and originality.

There is an increasing interest in the use of knowledge graphs to represent real-world knowledge and a common need to manage imprecise knowledge in many real-world applications. This paper aims to study approaches to solve flexible queries over knowledge graphs.

By introducing fuzzy logic in the query answering process, the authors are able to obtain a novel algorithm to solve flexible queries over knowledge graphs. This approach is implemented in the FUzzy Knowledge Graphs system, a software tool with an intuitive user-graphical interface.

This approach makes it possible to reuse semantic web standards (RDF, SPARQL and OWL 2) and builds a fuzzy layer on top of them. The application to a use case shows that the system can aggregate information in different ways by selecting different fusion operators and adapting to different user needs.

This approach is more general than similar previous works in the literature and provides a specific way to represent the flexible restrictions (using fuzzy OWL 2 datatypes).

This article aims to present a direct solution to handle linear constraints in finite element (FE) analysis without penalties or the Lagrange multipliers introduced.

First, the system of linear equations corresponding to the linear constraints is solved for the leading variables in terms of the free variables and the constants. Then, the reduced system of equilibrium equations with respect to the free variables is derived from the finite-dimensional virtual work equation. Finally, the algorithm is designed.

The proposed procedure is promising in three typical cases: (1) to enforce displacement constraints in any direction; (2) to implement local refinements by allowing hanging nodes from element subdivision and (3) to treat non-matching grids of distinct parts of the problem domain. The procedure is general and suitable for 3D non-linear analyses.

The algorithm is fitted only to the Galerkin-based numerical methods.

The proposed procedure does not need Lagrange multipliers or penalties. The tangential stiffness matrix of the reduced system of equilibrium equations reserves positive definiteness and symmetry. Besides, many contemporary Galerkin-based numerical methods need to tackle the enforcement of the essential conditions, whose weak forms reduce to linear constraints. As a result, the proposed procedure is quite promising.

Accurate presentation of the rock microstructure is critical to the grain-scale analysis of rock deformation and failure in numerical modelling. 3D granite microstructure modelling has only been used in limited studies with the mineral pattern often remaining poorly constructed. In this study, the authors developed a new approach for generating 2D and 3D granite microstructure models from a 2D image by combining a heterogeneous material reconstruction method (simulated annealing method) with Voronoi tessellation.

More specifically, the stochastic information in the 2D image is first extracted using the two-point correlation function (TPCF). Then an initial 2D or 3D Voronoi diagram with a random distribution of the minerals is generated and optimised using a simulated annealing method until the corresponding TPCF is consistent with that in the 2D image. The generated microstructure model accurately inherits the stochastic information (e.g. volume fraction and mineral pattern) from the 2D image. Lastly, the authors compared the topological characteristics and mechanical properties of the 2D and 3D reconstructed microstructure models with the model obtained by direct mapping from the 2D image of a real rock sample.

The good agreements between the mapped and reconstructed models indicate the accuracy of the reconstructed microstructure models on topological characteristics and mechanical properties.

The newly developed reconstruction method successfully transfers the mineral pattern from a granite sample into the 2D and 3D Voronoi-based microstructure models ready for use in grain-scale modelling.

The purpose of this study is to identify and prioritize the critical success factors (CSFs) of knowledge management (KM) implementation through a novel hybrid model, namely, Fuzzy Delphi method (FDM), interpretive structural modeling (ISM) and revised Simos, which is one of group decision-making (GDM) approaches.

The CSFs of KM implementation were identified through a systematic literature review. FDM was adopted to determine the CSFs in the Iranian oil industry. Then, a novel hybrid model consisting of ISM and revised Simos techniques were used to classify and prioritize the CSFs.

The obtained results suggest that there are 13 CSFs of KM implementation. The result of ISM shows that the CSFs of KM implementation were classified into five levels. The result of revised Simos reveals that the “human resources management” obtained the highest priority and “leadership commitment and support” and “intellectual capital” ranked second and third, respectively.

As this research was performed in the Iranian oil industry, caution should be taken regarding the generalizability of the obtained results.

The top managers of the surveyed companies could get acquainted with CSFs of KM implementation in their organization and use a GDM technique that has various advantages to solve the relevant problems.

This paper provides a twofold contribution to expand KM and GDM literature and to the best knowledge of the authors, it is a novel hybrid GDM model of its kind.

Supplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).

The proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.

A fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.

QFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.

The purpose of this study is to establish a hierarchy of critical success factors to develop a framework for evaluating the performance of smart grids from a sustainability perspective.

The fuzzy analytical hierarchy process is used in this study to assess and determine the relative weight of economic, operational and environmental criteria. At the same time, the evidential reasoning algorithm is used to determine the belief degree of expert’s opinion, and the expected utility theory for the crisp value of success factors in performance estimation.

The finding reveals that success factors associated with the economic criteria receive significantly more attention from the expert group. Sensitivity analysis indicates the ranking of consumer satisfaction remains stable no matter how criteria weights are changed, which verifies the robustness and effectiveness of the proposed model and evaluation results.

The study presents a solid mathematical framework for collaborative system modeling and systematic analysis. Managers and stakeholders may use the proposed technique as a flexible tool to improve the energy system’s resiliency in a systematic way.

With the emergence of the basis of intellectual capital, competitive advantage was considered as the focus of competitive strategies, and the knowledge resulting from this approach became the basis for the development and strategic directions of companies in various fields of the company such as finance and accounting. The purpose of this study is sustainable intellectual capital reporting framework and evaluation of key examples in the context of capital market companies.

The methodology of this study was exploratory from the point of view of the developmental result and based on the type of objective and qualitative and quantitative basis was used to collect the data. The statistical population in the qualitative part was university experts and in the quantitative part financial managers of capital market companies. Data collection tools were interviews in the qualitative part and fuzzy scales and language comparison checklists in the quantitative part. Therefore, first through three stages of coding, the dimensions of the model were identified, and based on the fuzzy Delphi analysis, the reliability level was determined through the average between the first round and the second round of Delphi. Finally, through the default tests, the appropriate fuzzy model was first determined, and then hierarchical fuzzy analysis based on TODIM's approach was used to determine the most favorable axis of sustainable intellectual capital reporting.

The results in the qualitative part indicate the existence of 3 categories and 6 components and 39 conceptual themes in the form of a six-dimensional model. In the quantitative part, the results showed that by confirming the dimensions identified through fuzzy Delphi analysis, the most desirable axis of intellectual capital reporting is the component of technological capital reporting, which can play a more effective role in sustainable reporting.

This study, relying on the importance of the consequences of sustainable intellectual capital reporting, tries to evaluate the consequences of this field of financial reporting due to the lack of a coherent theoretical framework about capital market companies. In addition, the framework presented in this study promotes integrated thinking for firms to it would provide some level of incentive to those charged with governance concerning the voluntary compliance with the sustainable intellectual capital reporting framework.