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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.

This study aims to assess each of the seven segments of the Akbarieh Garden as the World Heritage Cultural Landscape. First, we wanted to identify the macro elements that dominated one's perception within each area. Then, we wanted to identify the micro elements that support the vista in its entirety.

To acquire data, we used a Participant Observer (PO) method as part of a Continuous/Stop-Motion (CSM) procedure. The identification of macro elements came from retrospective recollections derived from the continuous walk method—the stop-walk method allowed for the identification of micro elements. The data gained from this method is then used to understand how one interprets and responds to large—multi-segmented sites such as the Akbarieh Garden.

The results of this study show the Continuous/Stop-Motion method yielded predictable results with macro elements and elements of interest being easily recalled. However, the use of photographing for the stop-walk method revealed a similar focus on the macro element. We had hypothesized that the micro elements would be the elements of fascination and discovered when the person remained in the area to photograph scenes of interest. However, the PO photographed the macro elements. It wasn't until the post photo analysis that the PO identified some of the micro elements would be the elements of fascination and discovered when the person remained in the area to photograph scenes of interest. However, the PO photographed the macro elements. It wasn't until the post photo analysis that the PO identified some of the micro elements. The post photo discoveries suggest that real-time experience of micro elements is undervalued.

There is no general discussion on this topic yet amongst professionals. The initiative of the Participant Observer (PO) method as a tool for perception the historic gardens and landscapes identified that gap and its related necessity to provide guidance. As is true for exploratory studies, these results provide a foundation for further study. The use of the Continuous/Stop-Motion method was ideal for this study.

Identifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.

A numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.

The results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.

This workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.

This paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.

Testing business processes is crucial to assess the compliance of business process models with requirements. Automating this task optimizes testing efforts and reduces human error while also providing improvement insights for the business process modeling activity. The primary purposes of this paper are to conduct a literature review of Business Process Model and Notation (BPMN) testing and formal verification and to propose the Business Process Evaluation and Research Framework for Enhancement and Continuous Testing (bPERFECT) framework, which aims to guide business process testing (BPT) research and implementation. Secondary objectives include (1) eliciting the existing types of testing, (2) evaluating their impact on efficiency and (3) assessing the formal verification techniques that complement testing.

The methodology used is based on Kitchenham's (2004) original procedures for conducting systematic literature reviews.

Results of this study indicate that three distinct business process model testing types can be found in the literature: black/gray-box, regression and integration. Testing and verification approaches differ in aspects such as awareness of test data, coverage criteria and auxiliary representations used. However, most solutions pose notable hindrances, such as BPMN element limitations, that lead to limited practicality.

The databases selected in the review protocol may have excluded relevant studies on this topic. More databases and gray literature could also be considered for inclusion in this review.

Three main originality aspects are identified in this study as follows: (1) the classification of process model testing types, (2) the future trends foreseen for BPMN model testing and verification and (3) the bPERFECT framework for testing business processes.

Bootstrapping is a practitioner-based term adopted in entrepreneurship to describe the techniques employed in micro, small and medium-sized enterprises (MSMEs) to minimise the need for external funding by securing resources at little or no cost and applying strategies to effectively use resources. Working capital management (WCM) is a term used in financial management to define a set of practices used to manage business resources, including cash management. This paper explores the overlap and divergence between these two disciplinary distinct concepts.

A dual methodology is employed. First, the usage of the two terms in prior literature is analysed and synthesised. Second, the study uses factor analysis to explore how bootstrapping practices described by owners of 167 established MSMEs relate to the components of WCM in financial management.

The factor analysis identifies two main bootstrapping practices employed by MSMEs: (1) delaying payments and owner-related bootstrapping and (2) customer-related bootstrapping. Delaying payments is an integral practice in trade payables management and customer-related bootstrapping includes practices that are integral to trade receivables management. Therefore, links between bootstrapping practices and WCM practices are firmly established.

The study is not without limitations. Based on cross-sectional evidence for established firms in Ireland only, future studies could explore cross-country longitudinal panel data to fully examine life cycle and sectoral effects, as well as other external shocks (for example, COVID-19) on bootstrapping and WCM practices. This study does not explain why some factors (for example, joint utilisation and inventory management) are present in some bootstrapping studies and not in others; further case study research might help explain this. Finally, changes in the business environment facing start-ups and established enterprise, including increased digitalisation, online trading, self-employment, remote hub working and sustainability, offer new avenues for bootstrapping research.

This is the first study to comprehensively explore the conceptual and empirical links between bootstrapping and WCM. This study will enable researchers and practitioners in these two distinct disciplines to learn from each other. Accounting researchers and practitioners can broaden their understanding of how WCM “works” in MSME settings. Similarly, entrepreneurship researchers and practitioners can deepen their understanding of how bootstrapping can be adopted by businesses to manage resources effectively.

This study investigates the fitting techniques for notch fatigue curves, seeking a more reliable method to predict the lifespan of welded structures.

Building on the fatigue test results of butt and cruciform joints, this research delves into the selection of fitting methods for the notch fatigue curve of welded joints. Both empirical formula and finite element methods (FEMs) were employed to assess the notch stress concentration factor at the toe and root of the two types of welded joints. Considering the mean stress correction and weld misalignment coefficients, the notch fatigue life curves were established using both direct and indirect methods.

An engineering example was employed to discern the differences between the direct and indirect approaches. The findings highlight the enhanced reliability of the indirect method for fitting the fatigue life curve.

While the notch stress approach is extensively adopted due to its accurate prediction of component fatigue life, most scholars have overlooked the importance of its curve fitting methods. Existing literature scantily addresses the establishment of these curves. This paper offers a focused examination of fatigue curve fitting techniques, delivering valuable perspectives on method selection.

This study aims to derive a novel spatial numerical method based on multidimensional local Taylor series representations for solving high-order advection-diffusion (AD) equations.

The parabolic AD equations are reduced to the nonhomogeneous elliptic system of partial differential equations by utilizing the Chebyshev spectral collocation method (ChSCM) in the temporal variable. The implicit-explicit local differential transform method (IELDTM) is constructed over two- and three-dimensional meshes using continuity equations of the neighbor representations with either explicit or implicit forms in related directions. The IELDTM yields an overdetermined or underdetermined system of algebraic equations solved in the least square sense.

The IELDTM has proven to have excellent convergence properties by experimentally illustrating both h-refinement and p-refinement outcomes. A distinctive feature of the IELDTM over the existing numerical techniques is optimizing the local spatial degrees of freedom. It has been proven that the IELDTM provides more accurate results with far fewer degrees of freedom than the finite difference, finite element and spectral methods.

This study shows the derivation, applicability and performance of the IELDTM for solving 2D and 3D advection-diffusion equations. It has been demonstrated that the IELDTM can be a competitive numerical method for addressing high-space dimensional-parabolic partial differential equations (PDEs) arising in various fields of science and engineering. The novel ChSCM-IELDTM hybridization has been proven to have distinct advantages, such as continuous utilization of time integration and optimized formulation of spatial approximations. Furthermore, the novel ChSCM-IELDTM hybridization can be adapted to address various other types of PDEs by modifying the theoretical derivation accordingly.

Numerous attempts at installing six sigma (SS) have faced challenges and fallen short of the desired success. Thus, it becomes vital to identify the critical factors and characteristics that play a pivotal role in achieving successful adoption. In this study the research has aimed to highlight that a considerable number of corporate SS initiatives, around 60%, fail primarily due to the improper incorporation of essential elements and flawed assumptions.

To validate the influence of critical success factors (CSFs) on SS accomplishment, the study employed a research design combining exploratory and mixed-methods approaches. A Likert-scale questionnaire was utilized, and a simple random sampling method was employed to gather data. Out of the 2,325 potential participants approached, 573 responses were received, primarily from Germany, the United Kingdom and Sweden. The analysis focused on 260 completed questionnaires and statistical methods including structural equation modeling (SEM), exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) were utilized for data analysis.

The study acknowledged four essential components of CSFs that are imperative for sustaining the success of SS: (1) Competence of belt System employees; (2) Project management skills; (3) Organizational economic capability and (4) Leadership commitment and engagement. These factors were identified as significant contributors to the maintenance of SS’s success.

The practical implications of this research imply that institutions, practitioners, and researchers can utilize the four identified factors to foster the sustainable deployment of SS initiatives. By incorporating these factors, organizations can enhance the effectiveness and longevity of their SS practices.

The investigation's originality lies in its contribution to assessing CSFs in SS deployment within the European automobile industry, utilizing a mixed-methods research design supplemented by descriptive statistics.

Business models are increasingly recognized as a concept to support innovation in organizations. The implementation and operation of a new or altered business model involves the (re-)design of an organization's business processes and their successful execution. This study reviews and synthesizes the existing body of literature to guide organizations in systematically moving from a business model design to the implementation and operation of the business model through their underlying business processes.

A systematic literature review of the methods that bridge business models and business processes is performed. The selected 34 studies are classified according to the method's characteristics and the support in the design, implementation and operation of business models.

The results of the systematic review provide an overview of existing methods that organizations can adopt when moving from business model design into the implementation and operation of their business model using processes.

This work provides a comprehensive overview and detailed insight into the existing methods that align business models and business processes. It increases the understanding on how these two concepts can be synthesized to support more effective digital innovation in organizations. Based on the review results, knowledge gaps are identified and an agenda for future research bridging the fields of business models and business processes is proposed.