• Computers and Concrete
• /
• v.33 no.2
• /
• pp.175-193
• /
• 2024

Researchers have embarked on an active investigation into the feasibility of adopting alternative materials as a solution to the mounting environmental and economic challenges associated with traditional concrete-based construction materials, such as reinforced concrete. The examination of concrete's mechanical properties using laboratory methods is a complex, time-consuming, and costly endeavor. Consequently, the need for models that can overcome these drawbacks is urgent. Fortunately, the ever-increasing availability of data has paved the way for the utilization of machine learning methods, which can provide powerful, efficient, and cost-effective models. This study aims to explore the potential of twelve machine learning algorithms in predicting the tensile strength of geopolymer concrete (GPC) under various curing conditions. To fulfill this objective, 221 datasets, comprising tensile strength test results of GPC with diverse mix ratios and curing conditions, were employed. Additionally, a number of unseen datasets were used to assess the overall performance of the machine learning models. Through a comprehensive analysis of statistical indices and a comparison of the models' behavior with laboratory tests, it was determined that nearly all the models exhibited satisfactory potential in estimating the tensile strength of GPC. Nevertheless, the artificial neural networks and support vector regression models demonstrated the highest robustness. Both the laboratory tests and machine learning outcomes revealed that GPC composed of 30% fly ash and 70% ground granulated blast slag, mixed with 14 mol of NaOH, and cured in an oven at 300°F for 28 days exhibited superior tensile strength.

• Advances in concrete construction
• /
• v.16 no.6
• /
• pp.277-290
• /
• 2023

In order to study the mechanical properties of basalt fiber reinforced ultra-fine fly ash concrete (BFUFARC), the effects of ultra-fine fly ash (UFA) content, basalt fiber content, basalt fiber length and water reducing agent content on the compressive strength, splitting tensile strength and flexural strength of the composite material were studied through experimental and theoretical analysis. Also, a scanning electron microscope (SEM) was employed to analyze the mesoscopic structure in the fracture surface of composite material specimens at magnifications of 500 and 3500. Besides, the energy release rate (G_c) and surface free energy (γ_s) of crack tip cracking on BFUFARC in different basalt fiber content were studied from the perspective of fracture mechanics. Further, the cracking resistance, reinforcement, and toughening mechanisms of basalt fibers on concrete substrate were revealed by surface free energy of BFUFARC. The experimental results indicated that basalt fiber content is the main influence factor on the splitting tensile strength of BFUFARC. In case that fiber content increased from 0 to 0.3%, the concrete surface free energy at the tip of single-sided crack showed a trend of increased at first and then decreased. The surface free energy reached at maximum, about 3.59 × 10^-5 MN/m. During the process of increasing fiber content from 0 to 0.1%, G_C-2_γS showed a gradually decreasing trend. As a result, an appropriate amount of basalt fiber can play a preventing cracking role by increasing the concrete surface free energy, further effectively improve the concrete splitting tensile performance.

• The Journal of Engineering Geology
• /
• v.34 no.1
• /
• pp.107-115
• /
• 2024

This study assesses forest fire susceptibility in Gangwon-do, South Korea, which hosts the largest forested area in the nation and constitutes ~21% of the country's forested land. With 81% of its terrain forested, Gangwon-do is particularly susceptible to wildfires, as evidenced by the fact that seven out of the ten most extensive wildfires in Korea have occurred in this region, with significant ecological and economic implications. Here, we analyze 480 historical wildfire occurrences in Gangwon-do between 2003 and 2019 using 17 predictor variables of wildfire occurrence. We utilized three machine learning algorithms—random forest, logistic regression, and support vector machine—to construct wildfire susceptibility prediction models and identify the best-performing model for Gangwon-do. Forest and soil map data were integrated as important indicators of wildfire susceptibility and enhanced the precision of the three models in identifying areas at high risk of wildfires. Of the three models examined, the random forest model showed the best predictive performance, with an area-under-the-curve value of 0.936. The findings of this study, especially the maps generated by the models, are expected to offer important guidance to local governments in formulating effective management and conservation strategies. These strategies aim to ensure the sustainable preservation of forest resources and to enhance the well-being of communities situated in areas adjacent to forests. Furthermore, the outcomes of this study are anticipated to contribute to the safeguarding of forest resources and biodiversity and to the development of comprehensive plans for forest resource protection, biodiversity conservation, and environmental management.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.3
• /
• pp.845-849
• /
• 2024

Currently, rail surface defects are increasing due to the aging of urban railway rails, but in the detailed guidelines for track performance evaluation established by the country, rail surface damage is inspected with the naked eye of an engineer and with simple measuring tools. It is very important to discover defects in the rail surface through periodic track tours and visual inspection. However, evaluating the severity of defects on the rail surface based on the subjective judgment of the inspector has significant limitations in predicting damage inside the rail. In this study, the characteristics of cracks inside the rail due to rail surface damage were studied. In field measurements, rail surface damage was selected, old rail samples were collected in the acceleration and braking sections, and a scanning electron microscope (SEM) was used to evaluate the rail surface damage was used to analyze the crack characteristics. As a result of the analysis, the crack mechanism caused by the running train and the crack characteristics of the acceleration section where cracks occur at an angle rising toward the rail surface were experimentally proven.

• Journal of Drive and Control
• /
• v.21 no.2
• /
• pp.36-43
• /
• 2024

The yield is basic and necessary information in precision agriculture that reduces input resources and enhances productivity. Yield information is important because it can be used to set up farming plans and evaluate farming results. Yield monitoring systems are commercialized in the United States and Japan but not in Korea. Therefore, such a system must be developed. This study was conducted to develop a yield monitoring system that improved performance by correcting a previously developed flow sensor using a grain tank-weighing system. An impact-plated type flow sensor was installed in a grain tank where grains are placed, and grain tank-weighing sensors were installed under the grain tank to estimate the weight of the grain inside the tank. The grain flow rate and grain weight prediction models showed high correlations, with coefficient of determinations (R2) of 0.9979 and 0.9991, respectively. A main controller of the yield monitoring system that calculated the real-time yield using a sensor output value was also developed and installed in a combine harvester. Field tests of the combine harvester yield monitoring system were conducted in a rice paddy field. The developed yield monitoring system showed high accuracy with an error of 0.13%. Therefore, the newly developed yield monitoring system can be used to predict grain weight with high accuracy.

• Steel and Composite Structures
• /
• v.51 no.3
• /
• pp.337-349
• /
• 2024

The growing quantity of tires and building trash piling up in landfills poses a serious threat to the stability of the ecosystem. Researchers are exploring ways to reduce and use such byproducts of the construction industry in an effort to promote greener building practices. Thus, using recycled crumb rubber from scrap tires in concrete manufacturing is important for the industry's long-term viability. This study examines the proportion of waste rubber in fiber form, specifically at weight percentages of 5%, 10%, and 15%. Moreover, the study examines the shear behavior of reinforced concrete beams. A total of twelve RC beam specimens, each sized 100 mm by 150 mm by 1000 mm (w × d × L), were constructed and positioned to the test. Various mixtures were designed with different levels of scrap tire rubber content (0%, 5%, 10%, and 15%) and Stirrup Vol. Ratio (2.10, 2.80, and 3.53) in reinforced concrete beams. The findings indicate that the inclusion of scrap rubber in concrete leads to a decrease in both the mechanical characteristics and weight of the material. This is mostly attributed to the lower strength and stiffness of the rubberized concrete. Furthermore, estimations generated by a variety of design codes were examined alongside the obtained data. In order to make a comparison between the estimates provided by the different codes such as ACI 318-14, CEB-FIB and Iranian national building codes, a calculation was done to determine the ratio of the experimental shear strength to the anticipated shear strength for each code.

• Maritime Security
• /
• v.8 no.1
• /
• pp.73-102
• /
• 2024

The recent rise of China has the potential to intensify competition for hegemony between the U.S. and China. China is strengthening its influence in the region through maritime military actions represented by Anti-Access/Area Denial(A2/AD). The U.S. is establishing a new concept of operation to respond to China's A2/AD and achieve superiority in the U.S - China competition. In particular, this study focused on the U.S. Marine Corps' contribution to naval operations as a means of sea denial through Expeditionary Advanced Base Operation(EABO), which mainly centered on islands, and changes to strengthen its influence in the sea. By applying these changes in the U.S. Marine Corps to the ROK Marine Corps, the future direction of the ROK Marine Corps' offensive island area operations that can contribute to joint and naval operations was suggested. This study is meaningful in that it presents the ROK Marine Corps' offensive island area operations using the strategic value of the island from the perspective of sea denial. However, by presenting the direction of operational performance and military power construction / development conceptually, specific discussions of this aspect are needed in the future. I hope that this study will be the starting point.

• Steel and Composite Structures
• /
• v.52 no.2
• /
• pp.145-163
• /
• 2024

This paper presents six novel hybrid machine learning (ML) models that combine support vector machines (SVM), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), extreme gradient boosting (XGB), and categorical gradient boosting (CGB) with the Harris Hawks Optimization (HHO) algorithm. These models, namely HHO-SVM, HHO-DT, HHO-RF, HHO-GB, HHO-XGB, and HHO-CGB, are designed to predict the ultimate strength of both rectangular and circular reinforced concrete (RC) columns. The prediction models are established using a comprehensive database consisting of 325 experimental data for rectangular columns and 172 experimental data for circular columns. The ML model hyperparameters are optimized through a combination of cross-validation technique and the HHO. The performance of the hybrid ML models is evaluated and compared using various metrics, ultimately identifying the HHO-CGB model as the top-performing model for predicting the ultimate shear strength of both rectangular and circular RC columns. The mean R-value and mean a20-index are relatively high, reaching 0.991 and 0.959, respectively, while the mean absolute error and root mean square error are low (10.302 kN and 27.954 kN, respectively). Another comparison is conducted with four existing formulas to further validate the efficiency of the proposed HHO-CGB model. The Shapely Additive Explanations method is applied to analyze the contribution of each variable to the output within the HHO-CGB model, providing insights into the local and global influence of variables. The analysis reveals that the depth of the column, length of the column, and axial loading exert the most significant influence on the ultimate shear strength of RC columns. A user-friendly graphical interface tool is then developed based on the HHO-CGB to facilitate practical and cost-effective usage.

• Structural Engineering and Mechanics
• /
• v.91 no.3
• /
• pp.315-324
• /
• 2024

An expansive soil in 4970 special railway line in Dangyang City, China, has encountered a series of landslides due to the expansion characteristics of expansive soil over the past 50 years. Thereafter, a sheet-pile retaining structure was adopted to fortify the expansive soil slope after a comprehensive discussion. In order to evaluate the efficacy of engineering measure of sheet-pile retaining structure, the field test was carried out to investigate the lateral pressure and pile bending moment subjected to construction and service conditions, and the local daily rainfall was also recorded. It took more than 500 days to carry out the field investigation, and the general change laws of lateral pressure and pile bending moment versus local daily rainfall were obtained. The results show that the effect of rainfall on the moisture content of backfill behind the wall decreases with depth. The performance of sheet-pile retaining structure is sensitive to the intensity of rainfall. The arching effect is reduced significantly by employing a series of sheet behind piles. The lateral pressure behind the sheet exhibits a single-peak distribution. The turning point of the horizontal swelling pressure distribution is correlated with the self-weight pressure distribution of soil and the variation of soil moisture content. The measured pile bending moment is approximately 44% of the ultimate pile capacity, which indicates that the sheet-pile retaining structure is in a stable service condition with enough safety reserve.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.10 no.5
• /
• pp.129-138
• /
• 2006

Composite deck plate using a pre-assembled re-bar truss for slab with corrugated zinc galvanized sheet iron at manufactory, is given the improvement on design, manufacture, and performance for construction work of cast-in-place reinforced concrete slab by enabling to cast concrete directly without the form work. There are two methods in analyzing composite deck : Simplified 2D analysis and 3D analysis. Although simplified 2D analysis is being used up to date, the use of 3D analysis, allowing for the vierendeel behavior of composite deck by real configuration correlating to bar reducing, is demanded. To compare the simplified 2D analysis applied to allowable stress design with 3D analysis applied to limit state design, 8 specimen are manufactured. Main variables include the depth of slab, the length of span, the diameter of bottom bar and lattice bar, and the presence of corrugated zinc galvanized sheet iron. The comparison from the experimental result and analytical result indicates that applying of simplified 2D analysis is possible for the use of D10 with bottom bar. However, it is more reasonable to apply 3D analysis which allows to indicate vierendeel behavior considered the real configuration.