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T.G. Wakjira, A. Abushanab, M. Shahria Alam, W. Alnahhal* and V. Plevris, "Explainable Machine Learning-Aided Efficient Prediction Model and Software Tool for Bond Strength of Concrete with Corroded Reinforcement", Structures, 59, Article ID 105693 (DOI: 10.1016/j.istruc.2023.105693), 2024.

Abstract:

The bond strength between concrete and reinforcement is crucial for the composite action and serviceability of reinforced concrete (RC) structures. However, it is vulnerable to deterioration from the corrosion of reinforcement bars, especially in marine structures. Thus, a precise and reliable model for the bond strength in corrosive environments is necessary to evaluate the serviceability and structural performance of corroded RC members. This study employs explainable machine learning (ML) techniques to assess the bond strength between concrete and corroded bars. Eight ML models are developed to establish the best predictive model for bond behavior, considering seven input parameters: corrosion level (CL), steel yield strength, compressive strength of concrete, concrete cover-to-bar diameter ratio, bar diameter-to-bonded length ratio, reinforcement type, and test type. The super learner (SL) model, integrating three ML models, outperforms other models and analytical methods with a large R2 value (98% on the test set) and minimal statistical errors. The SHapley Additive exPlanation (SHAP) technique identifies CL as the most influential parameter on bond strength, while the reinforcement and test types have the least effect. Finally, a user-friendly graphical user interface (GUI) tool is established to facilitate the practical implementation of the developed model and support accurate bond strength prediction in concrete with steel reinforcement under corrosive environments.

Keywords:
Machine learning; Bond strength; Concrete; Corrosion; SHAP; Graphical user interface.

V. Plevris, “From Integrity to Inflation: Ethical and Unethical Citation Practices in Academic Publishing”, Journal of Academic Ethics (DOI: 10.1007/s10805-025-09631-1), 2025.

Abstract:
Citation counts are a key metric in academic success, influencing career advancement and funding. However, the pressure to increase these counts has led to unethical practices such as citation inflation through manipulation. This paper examines strategies such as excessive self-citation, coercive citation demands by reviewers, and overuse of unpublished works, which distort the academic record and undermine scholarly integrity. The paper also explores ethical approaches to increasing citation counts, emphasizing high-quality research, appropriate journal selection, and active dissemination through reputable channels. A quantitative analysis of self-citation practices across different countries and fields revealed significant disparities, with some nations exhibiting high levels of self-citation among top scientists, while others showed more restrained behaviors. These findings suggest that citation practices may be influenced by various factors, including national research policies, cultural norms and others. The study highlights the potential long-term consequences of these behaviors for academic careers and the scientific community. Practical solutions to curb citation manipulation, such as stricter editorial oversight and improved journal collaboration, are proposed. The study aims to raise awareness of ethical challenges in academic publishing and offers strategies to maintain integrity in citation practices, ensuring that metrics reliably measure scholarly impact.

 

A. Jiménez Rios, V. Plevris and M. Nogal, “Towards Industry 5.0: A Stakeholder Analysis to Understand the Human Role in the Adoption of a Heritage Bridge Human-Centric Digital Twin Framework”, Structure and Infrastructure Engineering, Article ID 2490126 (DOI: 10.1080/15732479.2025.2490126), 2025.

Abstract:
The adoption of a novel industry paradigm is an untamed problem that requires strong social consensus and involves a high degree of technological uncertainty. To solve this problem a multi-actor engagement and agreement are needed. In this article, the methodology and the findings obtained after conducting a stakeholder analysis to understand how different actors could work together towards the adoption of Industry 5.0 principles and enabling technologies are presented. The analysis has been framed within a case study dealing with the conservation of historical bridges in the city of Oslo, Norway. The education institutions of the city were assumed as the problem owners. This research indicates that the Ministry of Transport and the Ministry of Climate and Environment, along with their subordinate agencies (Statens Vegvesen and Riksantikvaren, respectively) together with Oslo Kommune and its Cultural Heritage Office, possess the critical financial and regulatory resources necessary for adopting this paradigm. Their leadership and capacity to mobilise resources are pivotal in incentivising other stakeholders. Such resources should be driven towards a suitable business model, the adoption of human-centric digital twins as enabling technology, the establishment of interdisciplinary collaborations between the identified stakeholders, and the up-skilling/re-skilling of the industry workforce.

 

A. Jiménez Rios, V. Plevris, M. Nogal and W. Admiraal, “Scholarship of Teaching and Learning in Civil and Structural Engineering. A Systematic Literature Review”, Journal of Civil Engineering Education, 151(3) (DOI: 10.1061/JCEECD.EIENG-2103), 2025.

Abstract:
The Scholarship of Teaching and Learning (SoTL) pertains to scholarly endeavors centered on the pedagogical aspects of teaching and learning, and its principal objective is the enhancement of students’ educational experiences. This systematic literature review addresses the following questions: (1) In what capacity do educators within the field of civil and structural engineering (CaSE) engage with SoTL?, and (2) What are the benefits of implementing a SoTL for CaSE educators? The scope of the review encompasses SoTL studies specifically developed by CaSE educators and implemented within CaSE teaching and learning environments. Findings are synthesized and disseminated via a bibliometric analysis and a narrative synthesis. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. It was found that CaSE educators participate in SoTL endeavors through diverse approaches; however, such involvement remains more of an exception than a common practice. The insufficiency of existing benefits and incentives, if any, serves as a barrier hindering broader engagement and participation in SoTL activities.

 

V. Plevris and A. Ahmad, “Deriving analytical solutions using symbolic matrix structural analysis for continuous beams”, Scientific Reports, 15, Article ID 15897 (DOI: 10.1038/s41598-025-98023-x), 2025.

Abstract:
This study investigates the use of symbolic computation in Matrix Structural Analysis (MatSA) for continuous beams, using the MATLAB Symbolic Math Toolbox. By employing symbolic MatSA, analytical expressions for displacements, support reactions, and internal forces are derived, offering deeper insights into structural behavior. This approach facilitates efficient and scalable sensitivity analysis, where partial derivatives of outputs concerning input parameters can be directly computed, enhancing design exploration. The development includes an open-source MATLAB program, hosted on GitHub, enabling symbolic analysis of continuous beams subjected to point and uniform loads. This approach is valuable for both engineering practice and pedagogy, enriching the understanding of structural mechanics and aiding in education by illustrating clear parameter relationships. The program supports deriving influence lines and identifying maximum response values.

 

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