2571-1075ISSN (Online)
Purpose - Reinforced concrete (RC) shear walls are critical lateral-load resisting elements; however, reliable prediction of their axial–flexural interaction behavior remains difficult, particularly for irregular geometries and nonuniform reinforcement layouts. This study aims to develop an accurate and versatile analytical framework to evaluate the global axial–flexural response of RC shear walls. Design/methodology/approach - A fully nonlinear, code-independent numerical framework is formulated based on strain compatibility, equilibrium enforcement, and curvature-controlled sectional analysis. The model incorporates advanced stress–strain relationships for confined and unconfined concrete, a bilinear steel constitutive law, and a high-resolution fiber discretization scheme capable of representing arbitrary cross-sectional shapes. The framework generates complete moment–curvature responses and axial–moment (P–M) interaction diagrams under uniaxial bending. Findings - The results exhibit strong agreement with established analytical models and reported experimental trends. The framework accurately captures nonlinear degradation, neutral-axis migration, confinement effects, and the influence of reinforcement distribution on axial–flexural capacity. Practical implications - The proposed model provides a reliable tool for performance-based assessment, design, and optimization of RC shear walls beyond simplified code provisions. Originality/value - The study introduces a geometry-independent, fully nonlinear modeling approach that enables detailed evaluation of irregular RC shear walls with enhanced accuracy and practical applicability.
Read MoreDoi: https://doi.org/10.54216/IJBES.110201
Vol. 11 Issue. 2 PP. 01-19, (2025)
The study put forward an integrated artificial intelligence-based approach to the analysis and prediction of contracting disputes in Engineering Projects, especially through Machine Learning methods and Deep Learning methods. Current ways of managing contracts cannot effectively deal with the complicated nature of Legal Texts and do not provide for early identification of potential disputes. This developed System was built using the Python Programming Language, using key libraries for Natural Language Processing (NLP) and Machine Learning (ML). The cache of Contract Documents in all formats was transformed into numerical vectors using TF-IDF once all Document Processing and Clean-up Procedures were completed. Multiple Models were built, with trained versions of each, including Logistic Regression, SVM, Voting Classifiers and an MLP (Multi-Layer Perceptron) based Neural Network model. Since each Contracting Dispute was modelled separately to improve overall prediction accuracy, initial recommendations for resolution are generated. Results show that the MLP performed in a SUPERIOR fashion, with an Overall Model Accuracy of 88%, and F1 Score of 0.874, effectively classifying Contracting Disputes relating to Delays, Payments and Scope Variations. The application of this framework to an actual example taken from the construction industry in Syria reaffirmed the capability of automating contract text review and improving risk management. This reinforces the importance of artificial intelligence as a tool for increasing proactive decision-making and minimizing conflict in engineering projects.
Read MoreDoi: https://doi.org/10.54216/IJBES.110202
Vol. 11 Issue. 2 PP. 13-24, (2025)
Purpose – ISO 19650 plays the most important part within the current digital transformation of the construction sector. However, the implementation of this ISO 19650 standard faces major challenges that primarily involve organizational and personal aspects. Based on this context, the current research aims to fill the "digital leadership gap" through exploration of critical factors for effective implementation from the perspective of interrelations between different leadership styles and change management strategies. Design Methodology – This current research used a mixed-methods design that combined quantitative and qualitative research. The case information was collected from 104 participants who answered the questionnaire. Additionally, seven in-depth interviews were conducted with experts from the sector. These were stratified because they targeted two opposing contexts: on one side the United Kingdom (because the motivation is obligatory for the whole organization), while on the other side Saudi Arabia (due to motivational ambitions that fall into the framework of "Vision 2030"). Results – The quantitative results showed that transformational leadership style and effective systematic change management were the most essential factors that influence successful implementation. Furthermore, the results confirmed that the directive style was not significant on the whole. These results were deepened from the quantitative results using the complementary information that showed that leaders who use "behavioral flexibility" have better potential to balance transformational (to create vision), participative (to induce ownership), and directive (as tactics on critical points) approaches. Results demonstrated that the initial context of leadership had significant influence on the initial phase of change management. Practical Implications – Given the findings from this current research, the ILCM (Integration of Leadership and Change Management) framework was proposed. According to the results, it was clear that the key factor to ensure the achievement of change management in any organizational context was the strategic integration of leadership qualities. These findings led to providing specific advice that urged all organizations to improve "leadership flexibility" among their leaders and change management strategies embodied in plan design. These advice urged researchers and designers of change management strategies to incorporate leadership strategies into every stage of change management. Additionally, they considered the specific context depending on the motivations. Originality Value - The originality and value addition of this research work arise from its ability to offer an integrated model that captures the dynamic interplay between the theory of leadership and change management in order to fill the gap that exists between theory and practical applications in the construction industry. The research also adds to the existing knowledge base through its comparison approach that gives an accurate interpretation of how the digital transformation routes are affected by the impact of numerous factors of influence.
Read MoreDoi: https://doi.org/10.54216/IJBES.110203
Vol. 11 Issue. 2 PP. 25-40, (2025)