• Design & Manufacturing
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• v.14 no.3
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• pp.50-56
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• 2020

Ceramic tile is widely used as a floor or interior decoration of buildings. The main processes are raw material blending, molding, drying, firing, etc., and since dimensional and quality stability are very important, they are generally molded by a dry press method. In ceramic tile molds, there is a liner that can be easily replaced in case of wear. The liner is constantly abrasion due to a continuous pressing process during tile forming, and it is required to be replaced every certain period. Even in the liner, use a wear-resistant fitting material only in areas where wear is concentrated. However, there was a risk that the fitting material was applied to large-sized tile molding due to problems such as damage to the molding machine and decrease in productivity when detached during the actual tile molding process due to weak fitting strength with the liner. Therefore, in this study, thermal-structural analysis for fitting tolerance analysis and structural analysis for fitting force analysis were performed for the shrink fit process of the fitting material.

• Steel and Composite Structures
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• v.21 no.6
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• pp.1183-1210
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• 2016

Viscoelastic sandwich structures (VSSs) are widely used in mechanical equipment, but in the service process, they always suffer from aging which affect the whole performance of equipment. Therefore, aging state recognition of VSSs is significant to monitor structural state and ensure the reliability of equipment. However, non-stationary vibration response signals and weak state change characteristics make this task challenging. This paper proposes a novel method for this task based on adaptive second generation wavelet packet transform (ASGWPT) and multiwavelet support vector machine (MWSVM). For obtaining sensitive feature parameters to different structural aging states, the ASGWPT, its wavelet function can adaptively match the frequency spectrum characteristics of inspected vibration response signal, is developed to process the vibration response signals for energy feature extraction. With the aim to improve the classification performance of SVM, based on the kernel method of SVM and multiwavelet theory, multiwavelet kernel functions are constructed, and then MWSVM is developed to classify the different aging states. In order to demonstrate the effectiveness of the proposed method, different aging states of a VSS are created through the hot oxygen accelerated aging of viscoelastic material. The application results show that the proposed method can accurately and automatically recognize the different structural aging states and act as a promising approach to aging state recognition of VSSs. Furthermore, the capability of ASGWPT in processing the vibration response signals for feature extraction is validated by the comparisons with conventional second generation wavelet packet transform, and the performance of MWSVM in classifying the structural aging states is validated by the comparisons with traditional wavelet support vector machine.

• Steel and Composite Structures
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• v.49 no.3
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• pp.337-348
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• 2023

Successive wetting and drying cycles of concrete due to weather changes can endanger the safety of engineering structures over time. Considering wetting and drying cycles in concrete tests can lead to a more correct and reliable design of engineering structures. This study aims to provide a model that can be used to estimate the resistance properties of concrete under different wetting and drying cycles. Complex sample preparation methods, the necessity for highly accurate and sensitive instruments, early sample failure, and brittle samples all contribute to the difficulty of measuring the strength of concrete in the laboratory. To address these problems, in this study, the potential ability of six machine learning techniques, including ANN, SVM, RF, KNN, XGBoost, and NB, to predict the concrete's tensile strength was investigated by applying 240 datasets obtained using the Brazilian test (80% for training and 20% for test). In conducting the test, the effect of additives such as glass and polypropylene, as well as the effect of wetting and drying cycles on the tensile strength of concrete, was investigated. Finally, the statistical analysis results revealed that the XGBoost model was the most robust one with R2 = 0.9155, mean absolute error (MAE) = 0.1080 Mpa, and variance accounted for (VAF) = 91.54% to predict the concrete tensile strength. This work's significance is that it allows civil engineers to accurately estimate the tensile strength of different types of concrete. In this way, the high time and cost required for the laboratory tests can be eliminated.

• Advances in nano research
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• v.16 no.4
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• pp.375-394
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• 2024

The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.

• Wind and Structures
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• v.31 no.4
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• pp.373-380
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• 2020

For large-scale 5MW offshore wind turbines, the discrete equation of fluid domain and the motion equation of structural domain with geometric nonlinearity were built, the three-dimensional modeling of the blade considering fluid-structure interaction (FSI) was achieved by using Unigraphics (UG) and Geometry modules, and the numerical simulation and the analysis of the vibration characteristics for wind turbine structure under rotating effect were carried out based on ANSYS software. The results indicate that the rotating effect has an apparent effect on displacement and Von Mises stress, and the response and the distribution of displacement and Von Mises stress for the blade in direction of wingspan increase nonlinearly with the equal increase of rotational speeds. Compared with the single blade model, the blade vibration period of the whole machine model is much longer. The structural coupling effect reduces the response peak value of the blade displacement and Von Mises stress, and the increase of rotational speed enhances this coupling effect. The maximum displacement difference between two models decreases first and then increases along wingspan direction, the trend is more visible with the equal increase of rotational speed, and the boundary point with zero displacement difference moves towards the blade root. Furthermore, the Von Mises stress difference increases gradually with the increase of rotational speed and decreases nonlinearly from the blade middle to both sides. The results can provide technical reference for the safe operation and optimal design of offshore wind turbines.

• Steel and Composite Structures
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• v.19 no.3
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• pp.569-583
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• 2015

Recent years, explosive welding structures have been widely used in many engineering fields. The bonding state detection of explosive welding structures is significant to prevent unscheduled failures and even catastrophic accidents. However, this task still faces challenges due to the complexity of the bonding interface. In this paper, a new method called dual-tree complex wavelet transform based permutation entropy (DTCWT-PE) is proposed to detect bonding state of such structures. Benefiting from the complex analytical wavelet function, the dual-tree complex wavelet transform (DTCWT) has better shift invariance and reduced spectral aliasing compared with the traditional wavelet transform. All those characters are good for characterizing the vibration response signals. Furthermore, as a statistical measure, permutation entropy (PE) quantifies the complexity of non-stationary signals through phase space reconstruction, and thus it can be used as a viable tool to detect the change of bonding state. In order to more accurate identification and detection of bonding state, PE values derived from DTCWT coefficients are proposed to extract the state information from the vibration response signal of explosive welding structure, and then the extracted PE values serve as input vectors of support vector machine (SVM) to identify the bonding state of the structure. The experiments on bonding state detection of explosive welding pipes are presented to illustrate the feasibility and effectiveness of the proposed method.

• Steel and Composite Structures
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• v.48 no.3
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• pp.305-320
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• 2023

The mechanical properties of polymeric composites are degraded under elevated temperatures due to the effect of temperature on the mechanical behavior of the resin and resin fiber interfaces. In this study, the effect of temperature on the impact response of the carbon fiber reinforced plastics (CFRP) was investigated at low-velocity impact (LVI) using a drop-weight impact tester machine. All the composite plates were fabricated using a vacuum infusion process with a stacking sequence of [45/0_2/-45/90_2]s, and a thickness of 2.9 mm. A group of the specimens was exposed to an environment with a temperature cycling at the range of -30 ℃ to 65 ℃. In addition, three other groups of the specimens were aged at ambient (28 ℃), -30 ℃, and 65 ℃ for ten days. Then all the conditioned specimens were subjected to LVI at three energy levels of 10, 15, and 20 J. To assess the behavior of the damaged composite plates, the force-time, force-displacement, and energy-time diagrams were analyzed at all temperatures. Finally, radiography, optical microscopy, and scanning electron microscopy (SEM) were used to evaluate the effect of the temperature and damages at various impact levels. Based on the results, different energy levels have a similar effect on the LVI behavior of the samples at various temperatures. Delamination, matrix cracking, and fiber failure were the main damage modes. Compared to the samples tested at room temperature, the reduction of temperature to -30 ℃ enhanced the maximum impact force and flexural stiffness while decreasing the absorbed energy and the failure surface area. The temperature increasing to 65 ℃ increased the maximum impact force and flexural stiffness while decreasing the absorbed energy and the failure surface area. Applying 200 thermal cycles at the range of -30 ℃ to 65 ℃ led to the formation of fine cracks in the matrix while decreasing the absorbed energy. The maximum contact force is recorded under cyclic temperature as 5.95, 6.51 and 7.14 kN, under impact energy of 10, 15 and 20 J, respectively. As well as, the minimum contact force belongs to the room temperature condition and is reported as 3.93, 4.94 and 5.71 kN, under impact energy of 10, 15 and 20 J, respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.7
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• pp.721-727
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• 2015

The mechanical components for wind turbines are mainly manufactured using open-die forging. This research introduces an advanced forging method to produce the door frame of the tubular wind turbine tower. The advantages of this new forging method are an increase in the raw material utilization ratio and a reduction in energy cost. In the conventional method, the door frame is hot forged with a hydraulic press and amounts of material are machined out because of the shape difference between the forged and final machine products. The proposed forging method is composed of hot forging and ring rolling processes to increase the material utilization ratio. The effectiveness of this new forging method is deeply related to the ring rolled blank dimension before the final forging. To get the optimal ring rolled blank, forged shape prediction using the finite element analysis method was applied. The forged dimensions produced by the new forging method were verified through the first article production.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.5
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• pp.131-136
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• 2016

Currently, an EDM tapping procedure has comprised some parts of the engraving discharge process for the press die. Usually, tapping has been used in cases where we are unable to mechanically machine using steelwork processes due to an increase in the hardness of a material after heat treatment in relation to a design change or missing process. Here, we analyze the influence of discharge tap shape on discharge time, discharge current, and the number of repetition conditions when a cold-work tool steel (STD11) has been treated with a discharge tapped by a screw-shaped cu electrode. The most important influence on processing condition has been determined to be the number of discharge repetitions. As this number increases, the angle reduction of a thread closes to an angle of the electrode via a power generation reduction. The optimal combination of conditions has been determined to be three discharge repetitions, $180{\mu}s$ of discharge time (same as existing regulations), and 25.4A of peak current. A 0.2749db advantage has emerged after comparing between this combination of optimal conditions and the SN rate of existing regulations.

• Composites Research
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• v.35 no.3
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• pp.182-187
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• 2022

In this paper, the thickness of a multilayer PCB was predicted through an empirical formulation based on the physical properties of the prepreg used in multilayer PCB. Since the thickness of prepreg reduction when manufacturing a PCB due to the physical properties and copper foil residual rate, it is necessary to accurately predict the thickness of the PCB through the thickness empirical formulation. To determine the density of the prepreg, the mass and thickness of the prepreg were measured. To manufacture the CCL, the prepreg and copper foil were laminated using a hot press machine, and the thickness was measured using a microscope and micrometer. An 8-layerd PCB was designed with different circuit densities to measure the change in the thickness with the copper foil residual ratio, and the proposed empirical formulation was verified by comparing the measured thickness with the value obtained using the empirical formulation. As a result, the errors for the CCL and multilayer PCB were 2.56% and 4.48%, respectively, which demonstrated the reliability of the empirical formulation.