• Geomechanics and Engineering
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• v.25 no.3
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• pp.233-243
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• 2021

Rib spalling is a major issue affecting the safety of steeply inclined coal seam. And the failure coal face and support system can be affected with each other to generate a vicious cycle along with inducing large-scale collapse of surrounding rock in steeply inclined coal seam. In order to analyze failure mechanism and propose the corresponding prominent control measures of steeply inclined coal working face, mechanical model based on coal face-support-roof system and mechanical model of coal face failure was established to reveal the disaster mechanism of rib spalling and the sensitive analysis of related factors was performed. Furthermore, taking 3402 working face of Chen-man-zhuang coal mine as engineering background, numerical model by using FLAC3D was built to illustrate the propagation of displacement and stress fields in steeply inclined coal seam and verify the theory analysis as mentioned in this study. The results show that the coal face slide body in steeply inclined working face can be observed as the failure height of upper layer smaller than that of lower layer exhibiting with an irregular quadrilateral pyramid shape. Moreover, the cracks were originated from the upper layer of sliding body and gradually developed to the lower layer causing the final rib spalling. The influence factors on the stability of coal face can be ranked as overlying strata pressure (P) > mechanical parameters of coal body (e.g., cohesion (c), internal fraction angle (φ)) > support strength (F) > the support force of protecting piece (F') > the false angle of working face (Θ). Moreover, the corresponding control measures to maintain the stability of the coal face in the steeply inclined working face were proposed.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.365-372
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• 2022

The accurate object recognition is important for the precise and accurate manipulation. To enhance the recognition performance, we can use various types of sensors. In general, acquired data from sensors have a high sampling rate. So, in the past, the RNN-based model is commonly used to handle and analyze the time-series sensor data. However, the RNN-based model has limitations of excessive parameters. CNN-based model also can be used to analyze time-series input data. However, CNN-based model also has limitations of the small receptive field in early layers. For this reason, when we use a CNN-based model, model architecture should be deeper and heavier to extract useful global features. Thus, traditional methods like RN N -based and CN N -based model needs huge amount of learning parameters. Recently studied result shows that Fast Fourier Convolution (FFC) can overcome the limitations of traditional methods. This operator can extract global features from the first hidden layer, so it can be effectively used for feature extracting of sensor data that have a high sampling rate. In this paper, we propose the algorithm to recognize objects using tactile sensor data and the FFC model. The data was acquired from 11 types of objects to verify our posed model. We collected pressure, current, position data when the gripper grasps the objects by random force. As a result, the accuracy is enhanced from 84.66% to 91.43% when we use the proposed FFC-based model instead of the traditional model.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.

• Steel and Composite Structures
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• v.44 no.2
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• pp.199-210
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• 2022

This study build finite element analysis (FEA) models describing the bending events of coiled tubing (CT) at the wellhead and trips into the hole, accurately provide the state of stress and strain while the CT is in service. The bending moment and axial force history curves are used as loads and boundary conditions in the diametrical growth models to ensure consistency with the actual working conditions in field operations. The simulation diametrical growth results in this study are more accurate and reasonable. Analysis the factors influencing fatigue and diametrical growth shows that the internal pressure has a first-order influence on fatigue, followed by the radius of the guide arch, reel and the CT diameter. As the number of trip cycles increase, fatigue damage, residual stress and strain cumulatively increase, until CT failure occurs. Significant residual stresses remain in the CT cross-section, and the CT exhibits a residual curvature, the initial residual bending configuration of CT under wellbore constraints, after running into the hole, is sinusoidal. The residual stresses and residual bending configuration significantly decrease the buckling load, making the buckling and buckling release of CT in the downhole an elastic-plastic process, exacerbating the helical lockup. The conclusions drawn in this study will improve CT models and contribute to the operational and economic success of CT services.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.33-38
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• 2022

As the intense heat continues, many cases of highway pavement blow up and bridge expansion joints damages have been inspected. Especially, Expansion joint closure of bridges is an important problem that can threat the safety of the bridge structure or reduce long-term durability. This paper proposed a structural analysis method for bridges having expansion joint closure and structural analysis was performed to verify the effects according to bridge types. Analysis bridges were divided into four types: concrete and steel bridges, shallow and piled foundations. To induce the situation of abutments and bridge decks are jammed, the following loads were additionally considered; lateral flow pressure, pavement expansion by alkali-aggregate reaction, creep settlement of backfill. The structural analysis method was verified by comparing the structural analysis results with the actually measured joint gap data. In addition, behavioral analysis due to joint closure was conducted to confirm the change in safety ratio by type of superstructure as the axial force increased.

• Tribology and Lubricants
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• v.38 no.6
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• pp.267-273
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• 2022

Surface texturing is the latest technology for processing grooves or dimples on the friction surface of a machine. When appropriately applied, it can reduce friction and significantly increase durability. Despite many studies over the past 20 years, most are isothermal (ISO) analyses in which the viscosity of the lubricant is constant. In practice, the viscosity changes significantly owing to the heat generated by the viscous shear of the lubricant and film-temperature boundary condition (FTBC). Although many thermohydrodynamic (THD) analyses have been performed on various sliding bearings, only few results for surface-textured bearings have been reported. This study investigates the effects of the FTBC and groove number on the THD lubrication characteristics of a surface-textured parallel thrust bearing with multiple rectangular grooves. The continuity, Navier-Stokes, and energy equations with temperature-viscosity-density relations are numerically analyzed using a commercial computational fluid dynamics code, FLUENT. The results show the pressure and temperature distributions, variations of load-carrying capacity (LCC), and friction force with four FTBCs. The FTBCs greatly influence the lubrication characteristics of surface-textured parallel thrust bearings. A groove number that maximizes the LCC exists, which depends on the FTBC. ISO analysis overestimates the LCC but underestimates friction reduction. Additional analysis of various temperature boundary conditions is required for practical applications.

• Physical Therapy Korea
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• v.29 no.4
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• pp.269-273
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• 2022

Background: Neuromuscular electrical stimulation (NMES) is used for muscle strengthening. While voluntary muscle contraction follows Henneman et al.'s size principle, the NMES-induced muscle training disrespects the neurophysiology, which may lead to unwanted changes (i.e., declined balance ability). Objects: We examined how the balance was affected by abdominal muscle training with the NMES. Methods: Fifteen young adults (10 males and 5 females) aged between 21 and 30 received abdominal muscle strengthening with NMES for 23 minutes. Before and after the training, participants' balance was measured through one leg standing on a force plate with eyes open or closed. Outcome variables included mean distance (MDIST), root mean square distance (RDIST), total excursion (TOTEX), mean velocity (MVELO), and 95% confidence circle area (AREA) of center of pressure data. Two-way repeated measures analysis of variance was used to test if these outcome variables were associated with time (pre and post) and vision. Results: All outcome variables were not associated with time (p > 0.05). However, all outcome variables were associated with vision (p = 0.0001), and MVELO and TOTEX were 52.4% (45.5 mm/s versus 95.6 mm/s) and 52.4% (364.1 mm versus 764.5 mm) smaller, respectively, in eyes open than eyes closed (F = 55.8, p = 0.0005; F = 55.8, p = 0.0005). Furthermore, there was no interaction between time and vision (F = 0.024, p = 0.877). Conclusion: Despite the different neurophysiology of muscle contraction, abdominal muscle strengthening with NMES did not affect balance.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.27-32
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• 2022

There has always been a demand for orthodontic treatment. Orthodontic treatment allows tooth to be arranged by flexible arch wire fixed with tooth-attached brackets. Arch wire generate constant pressure to tooth brackets which moves the teeth to proper place. When the bracket transmits force, the braced wing of the bracket may deform. Deformed tie wing will lead to lost tension of elastic ligature. Then, lacking grip between tie wing and ligature might delay the tooth movement. Furthermore, tooth brackets used for orthodontic treatment make contact with in direct oral surface and this cause feeling of irritation that comes from height of tooth braces. This study suggests an optimal teethe bracket design to make up for inconvenience by shorten the height of bracket and complement the shape of bracket to reduce strain rate using finite element analysis. As a result, new optimal design of teethe bracket indicates lower strain rate of the bracket wing and takes good effects of shorten body height in terms of convenience.

• Physical Therapy Korea
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• v.29 no.3
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• pp.187-193
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• 2022

Background: Neuromuscular electrical stimulation (NMES) is a physical modality used to activate skeletal muscles for strengthening. While voluntary muscle contraction (VMC) follows the progressive recruitment of motor units in order of size from small to large, NMES-induced muscle contraction occurs in a nonselective and synchronous pattern. Therefore, the outcome of muscle strengthening training using NMES-induced versus voluntary contraction might be different, which might affect balance performance. Objects: We examined how the NMES training affected balance and proprioception. Methods: Forty-four young adults were randomly assigned to NMES and VMC group. All participants performed one-leg standing on a force plate and sat on the Biodex (Biodex R Corp.) to measure balance and ankle proprioception, respectively. All measures were conducted before and after a training session. In NMES group, electric pads were placed on the tibialis anterior, gastrocnemius, and soleus muscles for 20 minutes. In VMC group, co-contraction of the three muscles was conducted. Outcome variables included mean distance, root mean square distance, total excursion, mean velocity, 95% confidence circle area acquired from the center of pressure data, and absolute error of dorsi/plantarflexion. Results: None of outcome variables were associated with group (p > 0.35). However, all but plantarflexion error was associated with time (p < 0.02), and the area and mean velocity were 37.0% and 18.6% lower in post than pre in NMES group, respectively, and 48.9% and 16.7% lower in post than pre in VMC group, respectively. Conclusion: Despite different physiology underlying the NMES-induced versus VMC, both training methods improved balance and ankle joint proprioception.

• Design & Manufacturing
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• v.16 no.4
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• pp.34-39
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• 2022

Sustained economic development around the world is accelerating resource depletion. Research and development of secondary batteries that can replace them is also being actively conducted. Secondary batteries are emerging as a key technology for carbon neutrality. The core of an electric vehicle is the battery (secondary battery). Therefore, in this study, the temperature change by the heat source of the hammer and the rotational speed (rpm) of the abrasive disc of the Classifier Separator Mill (CSM) was repeatedly calculated and analyzed using the heat flow simulation STAR-CCM+. As the rotational speed (rpm) of the abrasive disk increases, the convergence condition of the iteration increases. Under the condition that the inlet speed of the Classifier Separator Mill (CSM) and the heat source value of the disc hammer are the same, the disc rotation speed (rpm) and the hammer temperature are inversely proportional. As the rotational speed (rpm) of the disc increases, the hammer temperature decreases. However, since the wear rate of the secondary battery material increases due to the strong impact of the crushing rotational force, it is determined that an appropriate rpm setting is necessary. In CSM (Classifier Separator Mill), it is judged that the flow rate difference is not significantly different in the direction of the pressure outlet (Outlet 1) right above the classifier wheel with the fastest flow rate. Because the disc and hammer attachment technology is adhesive, the attachment point may deform when the temperature of the hammer rises. Therefore, it is considered necessary to develop high-performance adhesives and other adhesive technologies.