• Steel and Composite Structures
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• v.43 no.1
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• pp.19-30
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• 2022

The static strength and fatigue crack resistance of the aircraft skin structures depend on the materials used and joint type. Most of the commercial aircraft's skin panel structures are made from aluminium alloy and carbon fibre reinforced epoxy. In this study, the fatigue resistance of four joint configurations (metal/metal, metal/composite, composite/composite and composite/metal) with riveted, adhesive bonded, and hybrid joining techniques are investigated with experiments and finite element analysis. The fatigue tests were tension-tension because of the typical nature of the loads on aircraft skin panels susceptible of experimenting fatigue. Experiment results suggest that the fatigue life of hybrid joints is superior to adhesive bonded joints, and these in turn much better than conventional riveted joints. Thanks to the fact that, for hybrid joints, the adhesive bond provides better load distribution and ensures load-carrying capacity in the event of premature adhesive failure while rivets induce compressive residual stresses in the joint. Results from FE tool ABAQUS analysis for adhesive bonded and hybrid joints agrees with the experiments. From the analysis, the energy release rate for adhesive bonded joints is higher than that of hybrid joints in both opening (mode I) and shear direction (mode II). Most joints show higher energy release rate in mode II. This indicates that the joints experience fatigue crack in the shear direction, which is responsible for crack opening.

• Smart Structures and Systems
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• v.29 no.2
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• pp.301-309
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• 2022

Protective coatings are most widely used anticorrosive structures for steel structures. The corrosion under the coating damages the host material, but this damage is completely hidden. Therefore, a field-applicable under-coating-corrosion visualization method has been desired for a long time. Laser ultrasonic technology has been studied in various fields as an in situ nondestructive inspection method. In this study, a comparative analysis was carried out between a guided-wave ultrasonic propagation imager (UPI) and pulse-echo UPI, which have the potential to be used in the field of under-coating-corrosion management. Both guided-wave UPI and pulse-echo UPI were able to successfully visualize the corrosion. Regarding the field application, the guided-wave UPI performing Q-switch laser scanning and piezoelectric sensing by magnetic attachment exhibited advantages owing to the larger distance and incident angle in the laser measurement than those of the pulse-echo UPI. Regarding the corrosion visualization methods, the combination of adjacent wave subtraction and variable time window amplitude mapping (VTWAM) provided acceptable results for the guided-wave UPI, while VTWAM was sufficient for the pule-echo UPI. In addition, the capability of multiple sensing in a single channel of the guided-wave UPI could improve the field applicability as well as the relatively smaller size of the system. Thus, we propose a guided-wave UPI as a tool for under-coating-corrosion management.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2001.11a
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• pp.37-37
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• 2001

TiN coatings were applied for VarIOUS application fields, because of a good wear-resistance and a high hardness. Typically, TiN thin films show the hardness of 25GPa and friction coefficient of 0.6. However, in many field, one is looking for a more improved tool which has low friction coefficient and high wear resistance. The main motivation of this study is to characterize the influence of copper dopant content on TiN thin films. Ti-Cu-N thin films were deposited onto D2 steel substrates by PVD processing with various magnetron current densities (Cu contents). In this work, we synthesized titanium nitride films similar with reported typical titanium nitride films and synthesized Ti-Cu-N thin films with the addition of elemental copper which is measured improved hardness more than pure TiN films with copper content variables. This films has preferred oriented films of (111) direction. In addition, It was found that there is a strong correlation between content of various metal and film characteristics such as preferred orientation, grain size, hardness and friction coefficient and so, in future study, improved mechanical properties of TiN films can be controlled by change in target current density. The Ti-Cu-N film will show apparent hardness improvement and mechanical properties enhancement, when doping element is added onto TiN thin films. Film structure, chemical composition, mechanical properties were investigated by means of X-ray diffraction(XRD), scanning electron microscopy(SEM), transmission electron microscopy (TEM), energy dispersive spectroscopy(EDS), wear resistance tester and nanohardness tester.

• Steel and Composite Structures
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• v.48 no.2
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• pp.179-190
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• 2023

Many recent attempts have sought accurate prediction of pile pullout resistance (P_ul) using classical machine learning models. This study offers an improved methodology for this objective. Adaptive neuro-fuzzy inference system (ANFIS), as a popular predictor, is trained by a capable metaheuristic strategy, namely equilibrium optimizer (EO) to predict the P_ul. The used data is collected from laboratory investigations in previous literature. First, two optimal configurations of EO-ANFIS are selected after sensitivity analysis. They are next evaluated and compared with classical ANFIS and two neural-based models using well-accepted accuracy indicators. The results of all five models were in good agreement with laboratory P_uls (all correlations > 0.99). However, it was shown that both EO-ANFISs not only outperform neural benchmarks but also enjoy a higher accuracy compared to the classical version. Therefore, utilizing the EO is recommended for optimizing this predictive tool. Furthermore, a comparison between the selected EO-ANFISs, where one employs a larger population, revealed that the model with the population size of 75 is more efficient than 300. In this relation, root mean square error and the optimization time for the EO-ANFIS (75) were 19.6272 and 1715.8 seconds, respectively, while these values were 23.4038 and 9298.7 seconds for EO-ANFIS (300).

• Steel and Composite Structures
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• v.45 no.2
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• pp.205-218
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• 2022

Proper calculation of splitting tensile strength (STS) of concrete has been a crucial task, due to the wide use of concrete in the construction sector. Following many recent studies that have proposed various predictive models for this aim, this study suggests and tests the functionality of three hybrid models in predicting the STS from the characteristics of the mixture components including cement compressive strength, cement tensile strength, curing age, the maximum size of the crushed stone, stone powder content, sand fine modulus, water to binder ratio, and the ratio of sand. A multi-layer perceptron (MLP) neural network incorporates invasive weed optimization (IWO), cuttlefish optimization algorithm (CFOA), and electrostatic discharge algorithm (ESDA) which are among the newest optimization techniques. A dataset from the earlier literature is used for exploring and extrapolating the STS behavior. The results acquired from several accuracy criteria demonstrated a nice learning capability for all three hybrid models viz. IWO-MLP, CFOA-MLP, and ESDA-MLP. Also in the prediction phase, the prediction products were in a promising agreement (above 88%) with experimental results. However, a comparative look revealed the ESDA-MLP as the most accurate predictor. Considering mean absolute percentage error (MAPE) index, the error of ESDA-MLP was 9.05%, while the corresponding value for IWO-MLP and CFOA-MLP was 9.17 and 13.97%, respectively. Since the combination of MLP and ESDA can be an effective tool for optimizing the concrete mixture toward a desirable STS, the last part of this study is dedicated to extracting a predictive formula from this model.

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

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.4
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• pp.109-120
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• 2007

In this study, a bridge maintenance system is developed to generate performance-based optimum maintenance strategy by considering the life-cycle cost. A multi-objective combinatorial optimization problem is formulated to generate a tradeoff maintenance scenarios which satisfies the balance among the conflicting objectives such as the performance and cost during the bridge lifetime and a genetic algorithm is applied to the system. By using the developed program, this study proposes a process of optimum maintenance scenario applying to the steel girder bridge of national road. The developed system improves the current methods of establishing the bridge maintenance strategy and can be utilized as an efficient tool to provide the optimum bridge maintenance scenario corresponding to the various constraints and requirements of bridge agency.

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.2
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• pp.37-46
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• 2009

In this study, the seismic performance of the Buckling Restrained Knee Bracing (BRKB) system was evaluated through a pin-connected 1-bay 1-story frame. The BRKB system using a bolted channel section developed was composed of a steel plate as a load-resisting core member and two channel sections as a restrainment of the local and global buckling of the core plate. The main purpose of the BRKB system is to be used as an effective tool to re-strengthen/rehabilitate old low- and mid-rise RC frame buildings, which do not have enough seismic resistance to earthquake loadings. The main variables for the test specimens were the size of the core plates, stiffeners and the use of guide plates. The test results showed that the size of the core plate, which was the main element for the load-resisting member, was the most important parameter to achieve ductile behavior under tension as well as compression, until the maximum displacement exceed twice the design drift limit given by the AISC Seismic Provisions.

• Korean Journal of Construction Engineering and Management
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• v.11 no.6
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• pp.89-99
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• 2010

Military Barracks and Bachelor Officer's Quarters are public buildings representing architectural characteristics with repeating the same room modules. These buildings require easy dismantling and reusing for the next generation' military re-organization. For these reasons, since 2005, the modular construction has been applied to military buildings. The most important factors required for modular military buildings are standardization, lowcost construction and reusable construction method. However, conventional modular building system have not been matched with these requirements. This study suggests a new modular system for Bachelor Officer's Quarters using Six-sigma design tool. To reflect the voices of customers, market study and surveys were carried out. Through the QFD, the voices of customers were converted into quality characteristics of building system for BOQ. The various design concepts meeting customer's requirement were derived by the QFD and Pugh matrix methodology. The proposed modular building system shows 80% increased factory production rate and 62% decreased weight of steel frame as compared with the conventional modular building system.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2003.11a
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• pp.660-664
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• 2003

The exposure dose form recycling on a large amount of the steel scrap from the KRR-1&2 decommissioning activities was evaluated, and also the clearance level was derived. The maximum individual dose and collective dose were evaluated by modifying internal dose conversion factor which was based on the concept of effective dose in ICRP 60, applied to the RESRAD-RECYCLE ver 3.06 computing code, IAEA Safety Series III-P-1.1 and NUREG-1640 as the assessment tool. The result of assessment for individual dose and collective dose is 23.9 ${\mu}Sv$ per year and 0.11 man$\cdot$Sv per year respectively. The clearance levels were ultimately determined by extracting the most conservative value form the results of the generic assessment and specific assessment methodologies. The result of clearance level for radionuclides($Co^60$, $Cs^137$) is less than $1.67{\times}10^{-1}$ Bq/g to comply with the clearance criterion(maximum individual dose : 10 $\muSv$ per year, collective dose : 1 man$\cdot$Sv per year) provided for Korea Atomic Energy Act and relevant regulations.