V. Plevris, "Assessing Uncertainty in Image-Based Monitoring: Addressing False Positives, False Negatives, and Base Rate Bias in Structural Health Evaluation", Stochastic Environmental Research and Risk Assessment (DOI: 10.1007/s00477-024-02898-7), 2025.

Abstract:
This study explores the limitations of image-based structural health monitoring (SHM) techniques in detecting structural damage. Leveraging machine learning and computer vision, image-based SHM offers a scalable and efficient alternative to manual inspections. However, its reliability is impacted by challenges such as false positives, false negatives, and environmental variability, particularly in low base rate damage scenarios. The Base Rate Bias plays a significant role, as low probabilities of actual damage often lead to misinterpretation of positive results. This study uses both Bayesian analysis and a frequentist approach to evaluate the precision of damage detection systems, revealing that even highly accurate models can yield misleading results when the occurrence of damage is rare. Strategies for mitigating these limitations are discussed, including hybrid systems that combine multiple data sources, human-in-the-loop approaches for critical assessments, and improving the quality of training data. These findings provide essential insights into the practical applicability of image-based SHM techniques, highlighting both their potential and their limitations for real-world infrastructure monitoring.

V. Plevris and A. Ahmad, "Deriving Analytical Solutions Using Symbolic Matrix Structural Analysis: Part 2 – Plane Trusses", Heliyon, 11(4), Article ID e42372, 19 pages (DOI: 10.1016/j.heliyon.2025.e42372), 2025.

Abstract:
This study extends the use of symbolic computation in matrix structural analysis to plane trusses, expanding on previous work that focused on continuous beams. We present a fully open-source MATLAB program, available on GitHub, that performs symbolic analysis of 2D trusses subjected to point loads, applicable to any truss configuration. Using the Symbolic Math Toolbox, the program derives closed-form analytical expressions for displacements, support reactions, and axial forces, providing deeper insight into structural behavior. A key advantage of the symbolic approach is its ability to perform sensitivity analysis efficiently by computing partial derivatives of structural responses with respect to input parameters. This feature enhances design exploration and optimization by allowing direct evaluation of parameter influences. Moreover, the framework is highly scalable, capable of generating symbolic solutions even for large-scale truss structures, something previously unattainable using traditional methods due to computational limitations. The tool serves both engineering practice and education, offering clear insights into parameter relationships and strengthening conceptual understanding in structural mechanics. To ensure accuracy, the symbolic results were rigorously validated against two commercial finite element software programs and results from the literature, with complete agreement. These validations confirm the reliability, scalability, and general applicability of the proposed methodology.

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.