Journal of Structural Engineering & Applied Mechanics

Bugra Sen Alper Polat Abdullah Kapicioglu Hikmet Esen

In the present study, energy is harvested from vibrations in bridge structures caused by vehicle passages using piezoelectric energy harvesters (PEHs). In order to maximize the energy harvested, it was aimed to specify the optimal locations of PEHs. In the study, energy harvesting from vibrations in bridge structures was achieved using three different vehicle loads and three different piezoelectric materials. The project of the Kuşsarayı-2 bridge, located in Kuşsarayı village in Baskil, Elazığ, was modelled in the ANSYS program using real measurements. The bridge was analyzed for modal, harmonic, and piezoelectric energy harvesting, respectively. The type with the highest energy production was determined using three different piezoelectric materials (PZT-4, PZT-5A, and PZT-8) for a total of 9 PEHs, and a total of 13 different analyses were performed under three different vehicle loads (60 kN, 90 kN, and 120 kN) to compare the results. The maximum total power obtained from all nine PEHs was 1.484 µW under the 120 kN load with PZT-5A. The maximum power obtained from a single PEH (PEH-1) was 0.49 µW. This power achieved will be adequate for wireless sensor systems used for monitoring the structural health of bridges, and considering that energy harvesting through vibration is independent of meteorological elements, unlike energy sources such as solar and wind, the environmental damage caused by waste batteries in existing systems will be prevented with the dissemination of these systems. With the development of these systems, the energy needs of services such as lighting and traffic signs can be supplied. The results provide an important foundation for the development of vibration-based energy harvesting systems in bridge structures. Thus, the study stands out as an innovative step toward sustainable energy generation in structural engineering.

https://doi.org/10.31462/jseam.2026.630

Ali Mortazavi Erdinç Sarıbaş

This study presents a novel Golden Ratio Optimization (GRO) algorithm integrated with Quadratic Approximation (QA) and Lévy Flight (LF) mechanisms to enhance global search efficiency and solution accuracy in structural optimization problems. The proposed method employs the golden ratio principle to guide search balance between exploration and exploitation, while the quadratic approximation model locally estimates the objective landscape to refine candidate solutions. The Lévy flight mechanism introduces adaptive random perturbations to prevent premature convergence and improve diversity within the population. The integrated approach is tested on benchmark truss optimization problems considering stress, displacement, and buckling constraints. Results demonstrate that the proposed method achieves superior convergence speed and robustness compared to conventional metaheuristic algorithms, providing lighter and more efficient structural designs. The findings highlight the potential of the proposed approach as a reliable tool for solving complex structural optimization problems.

https://doi.org/10.31462/jseam.2026.658

Erdi Gülbahçe

Reducing vibration can be very challenging in plate like structures with multiple modes triggered due to broadband loading and considerable constraints on additional mass. This study presents a hybrid approach to the placement and evaluation of distributed resonators attached on a fully clamped plate. The method combines finite element analysis based modal data with a reduced order analytical model. Instead of traditional parameter optimization, resonator locations are calculated by a methodical approach guided by weighted modal displacement maps. Three weighting approaches are applied such as uniform weighting, effective modal mass weighting, and a displacement based weighting inspired by the physics inherent in the MIL-STD-810H standard. The final designs are evaluated using displacement frequency response functions. The results show how the chosen weighting clearly specifies the overall vibration suppression across the spectrum as well as the spatial distribution of resonators.

https://doi.org/10.31462/jseam.2026.660

Hüseyin İlcan

Optimized grinding enhances material reactivity while reducing processing time and energy demand, supporting more sustainable and cost-effective construction. In this context, construction and demolition waste (CDW), widely landfilled due to its low reactivity, represents a promising candidate for upgrading. Accordingly, this study investigates the valorization potential of CDW-derived concrete waste (CW) as a value-added raw material. Vertical stirred mill was employed to investigate influences of grinding parameters, media filling ratio (MF = 50% and 70%) and grinding duration (5 min and 30 min), on features of CW. Particle size distribution (PSD) and specific surface area (SSA) were tested, while flow table and compressive strength tests were performed to investigate effect of CW on cementitious systems. Grinding reduced the median particle size (D50) from approximately 197 µm to 14–34 µm and increased the SSA by nearly 3–4 times. Replacing 20% of cement with untreated CW led to a significant reduction in workability and compressive strength, whereas ground CW mixtures exhibited improved mechanical performance. Although all CW mixtures remained below the reference, grinding enhanced compressive strength substantially compared to untreated CW. The effect of prolonged grinding varied with media filling ratio; while extended milling at 50% filling did not enhance performance, it contributed positively at 70%. The findings demonstrate that strength development is governed not only by fineness but also by agglomeration behavior and effective particle packing within the matrix.

https://doi.org/10.31462/jseam.2026.671

Oguzhan Akarsu Abdulkadir Cüneyt Aydın

This Erratum is issued to correct and clarify specific elements of the above-mentioned article in order to ensure full consistency between the manuscript text and the reference list, improve transparency regarding AI-assisted tool usage, and enhance the clarity of dataset description. As outlined in this document, the revisions concern four main sections of the article: (i) Introduction, (ii) Database, (iii) Declaration of Generative AI and AI-assisted technologies, and (iv) References. These corrections are limited to citation alignment, clarification of data sourcing, and refinement of disclosure statements, and do not affect the scientific results, analyses, or conclusions of the study. The online version of the article has been updated accordingly, and this Erratum provides a transparent record of the changes. The detailed corrections corresponding to each of these sections are presented below, with the revised passages provided in their updated form for clarity and traceability. The online version of the article has been updated accordingly, and this Erratum provides a transparent record of the changes.

https://doi.org/10.31462/jseam.2026.703