Journal of Civil Engineering Beyond Limits (CEBEL)

Mohammed Kusay Ebrahım AL-DULAYME Ahmet Budak

The escalating demand for efficient transportation infrastructure necessitates the construction of numerous tunnels, particularly in densely populated areas. However, their response to dynamic loads, like earthquakes, remains a critical concern. This study utilizes numerical modeling to assess the dynamic behavior of tunnels embedded in various silty soil types under seismic excitation. Employing Abaqus software and the finite element method, tunnels were modeled within three distinct silty soils: silty stone, silty sand, and low plasticity silty clay. Ground motion data from the 1994 Northridge earthquake was used as input to evaluate tunnel displacements. The results demonstrated significant variations in tunnel behavior based on the surrounding soil. Notably, low-plasticity silty clay exhibited the largest displacements, followed by silty sand and silty stone. This emphasizes the crucial influence of soil properties on tunnel stability during seismic events. Future investigations could expand upon this work by incorporating additional soil parameters and utilizing more intricate soil models to yield even more precise predictions of tunnel response under dynamic loading conditions.

https://doi.org/10.36937/cebel.2024.1896

Edanur KOÇ İsmail YILDIZ

The use of mild materials shows an increasing tendency in industrial areas. These materials are also preferred to reduce the unit weight of the building elements in the construction sector. Various light aggregates are used to produce light concrete with a lower density than normal concrete, and the properties of these light aggregates significantly affect the properties of the concrete. In this study, the use of expanded clay aggregate (ECA) produced in the Söğüt region in structural lightweight concrete was examined. Expanded clay, sand, and crushed stone aggregate were used as aggregates in concrete mixtures. The mixture granulometry was kept the same for each group. For this purpose, 60 samples were prepared for a total of 4 mixtures with different contents. Slump and unit volume weight tests were carried out on fresh concrete samples, and compressive, flexural, and splitting tensile strength tests were carried out on 7- and 28-day-hardened concrete samples. Some of the concrete mixture samples were subjected to tests after being kept in the curing pool for 7 days, and some for 28 days. As a result of the experiments, the unit weight and compressive strength values obtained from the samples produced with ECA as coarse and fine aggregate in order to achieve the highest strength target are 1413 kg/m³ and 30 MPa, respectively. The same values were found to be 1652 kg/m³ and 39 MPa in the samples produced with river sand as fine aggregate and ECA as coarse aggregate. In the samples produced using ECA as fine aggregate and crushed stone aggregate as coarse aggregate, these values were also found to be 1689 kg/m³ and 50 MPa.

https://doi.org/10.36937/cebel.2024.1901

Sesugh Terlumun ONYIA M.E. OKAFOR, F.O. OGBIYE A.S. ABUBAKAR S.H.

ABSTRACT Bamboo is a rapidly replenishing resource that is used as a practical building material in many nations. However, it is not commonly used in the United States or other western nations, in part because building codes and safety standards have not yet included it. The mechanical characteristics of bamboo must be thoroughly comprehended and recorded in order to develop these. Major variables, including age, bamboo species, density, moisture content, post-harvest treatment, and the testing standards used, affects its properties greatly. This work presents a comparative study of the effects of treatment methods on the tensile performance of bamboo. In this research, bamboo samples of size 12x12mm, 14x12mm, 16x12mm and 20x12mm were prepared, some of the samples were treated with epoxy, bitumen emulsion, binding wire and some were treated by combining binding wire and either of epoxy or bitumen emulsion while few were untreated. Tensile strength test was carried out on both samples and the results shows that the tensile strength of bamboo samples was greatly increased in all the treatment methods used. Tensile strength of bamboo is also a function of size, from the research, it was observed that size 20mmx12mm possess higher strength. Hence, it is recommended for construction works, bamboo treated with epoxy has higher strength other treatment methods. However, a combination of binding wire and other treatment techniques give superior strength, epoxy was observed to have demonstrated higher strength than bitumen and binding wire alone.

https://doi.org/10.36937/cebel.2024.1899

Rowland Adewumi Wasiu Kayode Sulaiman Adeniyi Shola

Pavement deterioration poses multifaceted challenges, encompassing safety hazards, operational disruptions, and escalating maintenance costs. A significant contributing factor to this issue lies in the inadequate assessment of subgrade materials. This study focuses on investigating the geotechnical variables influencing pavement degradation along the Ikare-Arigidi Road in Ondo State, Nigeria. Through the analysis of California Bearing Ratio (CBR) values, segments such as CH.4+500RHS and CH.8+500RHS are identified as potential weak points, exhibiting notably low CBR values of 1.920. Moreover, moisture content and Atterberg limits emerge as critical factors affecting pavement stability, with section CH.6+500LHS demonstrating exceptional stability characteristics. The AASHTO soil classification system further elucidates variations in soil quality, highlighting segments classified as A-2-4 (CH.4+500RHS, CH.8+500RHS) as potentially having poorer soil conditions compared to A-6 sections. Consequently, segments such as CH.4+500RHS and CH.8+500RHS are anticipated to present challenges, while sections including CH.0+500RHS, CH.2+500LHS, CH.10+500LHS, and CH.12+500RHS exhibit potential for stability. By carefully considering these findings, targeted interventions can be implemented to effectively mitigate pavement degradation hazards. This may involve implementing appropriate soil stabilization measures, optimizing pavement design parameters, and prioritizing maintenance efforts in vulnerable segments. A comprehensive understanding of the geotechnical factors influencing pavement degradation is essential for devising sustainable strategies to enhance roadway performance and ensure the safety and longevity of transportation infrastructure.

https://doi.org/10.36937/cebel.2024.1903

Osman Nuri Akarsu Oğuzhan Akarsu Abdulkadir Cüneyt Aydın

This article presents a bibliometric review of earthquake research and its integration with machine learning techniques. Over the past two decades, there has been a growing interest in using machine learning to enhance earthquake prediction and research. The review collected 1172 scholarly articles from the Web of Science database, focusing on the keywords "earthquake" and "machine learning." Machine learning has shown promise in improving earthquake forecasting models and aiding decision-making in disaster management, infrastructure design, and emergency response. However, it is noted that the application of machine learning in earthquake engineering is still in its early stages and requires further exploration. Key findings of this review include the increasing importance of certain keywords in earthquake and machine learning research, such as "prediction," "neural network," "classification," "logistic regression," and "performance." These keywords highlight the central areas of research focus within this field. The review also identifies research trends and gaps, including the need for more exploration of large-scale, high-dimensional, nonlinear, non-stationary, and heterogeneous spatiotemporal data in earthquake engineering. It emphasizes the necessity for novel machine learning algorithms tailored specifically for earthquake prediction and analysis. Furthermore, it highlights the need for addressing uncertainty in earthquake research and improving forecasting models. The review underscores the growth in interest and collaboration in earthquake research and machine learning, evident in the increasing number of scholarly contributions over the years. In summary, this bibliometric review highlights the importance of accurate forecasting and the potential of machine learning techniques in advancing this field.

https://doi.org/10.36937/cebel.2024.1908