• International conference on construction engineering and project management
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• 2013.01a
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• pp.390-390
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• 2013

Use of recycled aggregates in portland cement concrete construction can offer benefits associated with both economy and sustainability. Testing performed to date indicates that RBMA can be used as a 100% replacement for conventional coarse aggregate in concrete that exhibits acceptable mechanical properties for use in structural and pavement elements, including satisfactory performance in some durability tests. RBMAC is currently not used in any type of construction in the United States. However, use of RBMAC could become a viable construction strategy as sustainable building practices become the norm. Rating systems such as LEED offer points for reuse of building materials (particularly on-site) and use of recycled materials. If renovations at an existing facility call for the demolition of existing brick masonry constructions, the rubble could be included as RBMA in new concrete pavement, sidewalks, or curb and gutter. Other potential uses for RBMAC could include those in the precast concrete industry, particularly in architectural precast concrete applications. In addition to providing acceptable strength and economy, the color of RBMA could be an attractive component of architectural precast concrete panels or other façade components. This paper explores the feasibility of use of RBMAC in several types of sustainable construction initiatives, based upon the findings of previous work with RBMAC produced from construction and demolition waste from a case study site. Guidance for obtaining and using RBMA is presented, along with a summary of material properties of RBMAC that will be useful to construction professionals.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.6
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• pp.460-472
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• 2023

This study was conducted based on the case of an accident (excessive deformation) that occurred during the hydraulic test of a shipboard tank manufactured in accordance with the design regulations. Over-pressure phenomenon was noted as the main cause of accidents in the process of testing tanks without physical damage, which can be found in external factors such as cross-sectional difference between inlet pipe and air pipe and higher water filling rate than the recommended one. The main goal of this paper is to establish a safe water filling rate according to the range of sectional area ratio(SAR) reduced below the regulations for each test situation. The simulation was conducted in accordance with the hydraulic test procedure specified in the Ship Safety Act, and the main situation was divided into two types: filling the tank with water and increasing the water head to the test pressure. The structural safety evaluation of the pressure generated inside the tank and the effect on the structure during the test was reviewed according to the SAR range. Based on the results, guidelines for the optimal filling rate applicable according to SAR during the hydraulic test were presented for the shipboard tanks used in this study.

• Steel and Composite Structures
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• v.49 no.2
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• pp.161-180
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• 2023

In the previous research, the axial compressive capacity models for the glass fiber-reinforced polymer (GFRP)-reinforced circular concrete compression elements restrained with GFRP helix were put forward based on small and noisy datasets by considering a limited number of parameters portraying less accuracy. Consequently, it is important to recommend an accurate model based on a refined and large testing dataset that considers various parameters of such components. The core objective and novelty of the current research is to suggest a deep learning model for the axial compressive capacity of GFRP-reinforced circular concrete columns restrained with a GFRP helix utilizing various parameters of a large experimental dataset to give the maximum precision of the estimates. To achieve this aim, a test dataset of 61 GFRP-reinforced circular concrete columns restrained with a GFRP helix has been created from prior studies. An assessment of 15 diverse theoretical models is carried out utilizing different statistical coefficients over the created dataset. A novel model utilizing the group method of data handling (GMDH) has been put forward. The recommended model depicted good effectiveness over the created dataset by assuming the axial involvement of GFRP main bars and the confining effectiveness of transverse GFRP helix and depicted the maximum precision with MAE = 195.67, RMSE = 255.41, and R2 = 0.94 as associated with the previously recommended equations. The GMDH model also depicted good effectiveness for the normal distribution of estimates with only a 2.5% discrepancy from unity. The recommended model can accurately calculate the axial compressive capacity of FRP-reinforced concrete compression elements that can be considered for further analysis and design of such components in the field of structural engineering.

• Structural Engineering and Mechanics
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• v.88 no.4
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• pp.389-403
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• 2023

In order to explore the influence of tooth root cracks on the dynamic characteristics of multi-stage planetary gear transmission systems, a concentrated parameter method was used to construct a nonlinear dynamic model of the system with 30-DOF in bending and torsion, taking into account factors such as crack depth, length, angle, error, time-varying meshing stiffness (TVMS), and damping. In the model, the energy method was used to establish a TVMS model with cracks, and the influence of cracks on the TVMS of the system was studied. By using the Runge- Kutta method to calculate the differential equations of system dynamics, a series of system vibration diagrams containing cracks were obtained, and the influence of different crack parameters on the vibration of the system was analyzed. And vibration testing experiments were conducted on the system with planetary gear cracks. The results show that when the gear contains cracks, the TVMS of the system will decrease, and as the cracks intensify, the TVMS will decrease. When cracks appear on the II-stage planetary gear, the system will experience impact effects with intervals of rotation cycles of the II-stage planetary gear. There will be obvious sidebands near the meshing frequency doubling, and the vibration trajectory of the gear will also become disordered. These situations will become more and more obvious as the degree of cracks intensifies. Through experiments, the theoretical results are in good agreement with experimental results, verifying the correctness of the theoretical model. This provides a theoretical basis for fault diagnosis and reliability research of the system.

• Computers and Concrete
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• v.32 no.4
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• pp.351-363
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• 2023

Reducing the self-weight of reinforced concrete structures problem is discussed in this paper by using two types of self-weight reduction, the first is by using lightweight coarse aggregate (crushed brick) and the second is by using styropor block. Experimental and Numerical studies are conducted on (LWAC) lightweight aggregate reinforced concrete slabs, having styropor blocks with various sizes of blocks and the ratio of shear span to the effective depth (a/d). The experimental part included testing eleven lightweight concrete one-way simply supported slabs, comprising three as reference slabs (solid slabs) and eight as styropor block slabs (SBS) with a total reduction in cross-sectional area of (43.3% and 49.7%) were considered. The holes were formed by placing styropor at the ineffective concrete zones in resisting the tensile stresses. The length, width, and thickness of specimen dimensions were 1.1 m, 0.6 m, and 0.12 m respectively, except one specimen had a depth of 85 mm (which has a cross-sectional area equal to styropor block slab with a weight reduction of 49.7%). Two shear spans to effective depth ratios (a/d) of (3.125) for load case (A) and (a/d) of (2) for load case (B), (two-line monotonic loads) are considered. The test results showed under loading cases A and B (using minimum shear reinforcement and the reduction in cross-sectional area of styropor block slab by 29.1%) caused an increase in strength capacity by 60.4% and 54.6 % compared to the lightweight reference slab. Also, the best percentage of reduction in cross-sectional area is found to be 49.7%. Numerically, the computer program named (ANSYS) was used to study the behavior of these reinforced concrete slabs by using the finite element method. The results show acceptable agreement with the experimental test results. The average difference between experimental and numerical results is found to be (11.06%) in ultimate strength and (5.33%) in ultimate deflection.

• Journal of Aerospace System Engineering
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• v.18 no.3
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• pp.56-64
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• 2024

In this study, a drop impact tester was developed to comprehensively conduct basic testing and academic research on the drop impact characteristics of aerospace structures. A drop tester enables accurate assessment of the dynamic stresses and deformations that occur when an aircraft collides with the ground, thereby enabling the verification of important design factors, such as safety and mechanical strength. The drop tester consists of an electromagnet to attach and drop the test object, a crane to adjust the drop height of the test object, and a drop support structure for vertical drops. Numerical analysis of the drop test object for the test was performed, and basic tests were performed using the drop impact tester. Through the analysis and test results, the structural shape of the landing gear was analyzed, and the behavior of each part was evaluated.

• Journal of Industrial Convergence
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• v.22 no.6
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• pp.25-39
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• 2024

Because small and medium-sized businesses lack capabilities and resources, they must effectively procure, share, and utilize scarce resources from outside, and as a result, the importance of networks with external organizations is gradually increasing. In this study, we verified the influence of small and medium-sized enterprises' network capabilities and network characteristics on market performance and financial performance. As a result of testing the hypothesis through a structural equation model, network capabilities were found to have a significant partial impact on financial performance, and all sub-factors of network characteristics such as strength, size, and diversity were found to affect financial performance. Additionally, network capabilities and network characteristics were found to have a significant partial effect on market performance. Market performance was found to have a partial mediating effect in the relationship between network capabilities and financial performance, and a partial mediating effect in the relationship between network characteristics and financial performance. Unlike previous studies, this study simultaneously analyzed the impact of two factors, network capabilities and network characteristics, on corporate performance and presented a new research perspective by analyzing the mediating effect of market performance, which is recognized as a leading factor in financial performance.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.23-42
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• 2024

Purpose: This study aims to investigate the impact of two types of information quality, which are platform-oriented information quality and customer-oriented information quality, on customers' decision-making processes in the Online to offline (O2O) platform environment. Grounded in the product brokering efficiency model, which encompasses screening cost, evaluation cost, and decision quality, a model framework was developed. Furthermore, this study explores how these decision-making processes affect customer loyalty. Methods: Given that food delivery apps are the most widely used O2O service in Korea, this study targeted users of these apps for data analysis. We conducted hypothesis testing through a purposive sampling methodology focusing on food delivery app users. A Partial Least Squares Structural Equation Modeling analysis was conducted to analyze the data. The data collection occurred via an online survey from October to December 2021, with a total of 212 respondents participating. Results: The results of this study revealed the significant role of information quality in helping customers' decision processes while using food delivery apps. Specifically, it was found that platform-oriented information positively influences decision quality, while customer-oriented information significantly affects both the reduction of evaluation cost and the enhancement of decision quality. Additionally, the study indicated that lower evaluation costs and higher decision quality lead to increased platform loyalty. However, a reduction in screening cost did not have a significant impact on platform loyalty. Conclusion: While previous studies have overlooked the existence of two sides, service provider and user, in a platform, this research holds significance in its analysis of how information quality impacts loyalty by utilizing the two kinds of information quality. Practitioners can enhance customer loyalty to the platform by enriching customer-oriented information, thereby reducing customers' evaluation costs and encouraging more loyal usage of the platform.

• Steel and Composite Structures
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• v.51 no.5
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• pp.509-527
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• 2024

Bonding carbon fiber-reinforced polymer (CFRP) laminates have been extensively employed in the restoration of steel constructions. In addition to the mechanical properties of the CFRP, the bond strength (P_U) between the CFRP and steel is often important in the eventual strengthened performance. Nonetheless, the bond behavior of the CFRP-steel (CS) interface is exceedingly complicated, with multiple failure causes, giving the P_U challenging to forecast, and the CFRP-enhanced steel structure is unsteady. In just this case, appropriate methods were established by hybridized Random Forests (RF) and support vector regression (SVR) approaches on assembled CS single-shear experiment data to foresee the P_U of CS, in which a recently established optimization algorithm named Aquila optimizer (AO) was used to tune the RF and SVR hyperparameters. In summary, the practical novelty of the article lies in its development of a reliable and efficient method for predicting bond strength at the CS interface, which has significant implications for structural rehabilitation, design optimization, risk mitigation, cost savings, and decision support in engineering practice. Moreover, the Fourier Amplitude Sensitivity Test was performed to depict each parameter's impact on the target. The order of parameter importance was t_c> L_c > E_A > t_A > E_c > b_c > f_c > f_A from largest to smallest by 0.9345 > 0.8562 > 0.79354 > 0.7289 > 0.6531 > 0.5718 > 0.4307 > 0.3657. In three training, testing, and all data phases, the superiority of AO - RF with respect to AO - SVR and MARS was obvious. In the training stage, the values of R² and VAF were slightly similar with a tiny superiority of AO - RF compared to AO - SVR with R² equal to 0.9977 and VAF equal to 99.772, but large differences with results of MARS.

• Journal of the Korean Geosynthetics Society
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• v.23 no.1
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• pp.17-25
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• 2024

The Voids in the Mineral Aggregate (VMA) within asphalt mixtures play a crucial role in defining the mixture's structural integrity, durability, and resistance to environmental factors. Accurate prediction and optimization of VMA are essential for enhancing the performance and longevity of asphalt pavements, particularly in varying climatic and environmental conditions. This study introduces a novel machine learning framework leveraging ensemble machine learning model for predicting VMA in asphalt mixtures. By analyzing a comprehensive set of variables, including aggregate size distribution, binder content, and compaction levels, our framework offers a more precise prediction of VMA than traditional single-model approaches. The use of advanced machine learning techniques not only surpasses the accuracy of conventional empirical methods but also significantly reduces the reliance on extensive laboratory testing. Our findings highlight the effectiveness of a data-driven approach in the field of asphalt mixture design, showcasing a path toward more efficient and sustainable pavement engineering practices. This research contributes to the advancement of predictive modeling in construction materials, offering valuable insights for the design and optimization of asphalt mixtures with optimal void characteristics.