Journal of the Korean Society of Fisheries and Ocean Technology
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v.50
no.3
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pp.233-243
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2014
The difference of mooring tension by type of buoy was investigated in the circulating water channel and the wave tank for deducting the most stable buoy from the current and the wave condition. 5 types of buoy made up of short cylinder laid vertically (CL-V), short cylinder laid horizontally (CL-H), capsule (CS), sphere (SP) and long cylinder (CL-L) were used for experiments. A mooring line and a weight were connected with each buoy. A tensile gauge was installed between a mooring line and a weight. All buoy's mooring tension was measured at the same time for the wave test with periods of 1.5~3.0 sec and wave heights of 0.1~0.3 m, and the current test with flow speeds of 0.2~1.0 m/sec. As a result, the order of tension value in the wave test was CL-H > CL-V > SP > CS > CL-L. In the current test CL-V and CL-H were recorded in the largest tension value, whereas SP has the smallest tension value. So it seems that SP buoy is the most effective in the location affected by fast current. CS is predicted to be suitable for a location that influence of wave is important more than that of current if practical use in the field is considered. And it was found that the difference of mooring tension among buoys in wave is related to the product of the cross sectional area and the drag coefficient for the buoy's bottom side in high wave height. The factor for the current condition was not found. But it was supposed to be related to complex factors like a dimension and a shape by buoy's posture to flow.
In this work, we report a delta rosette strain sensor based on highly stretchable silver nanowire (AgNW) percolation piezoresistors. The proposed rosette strain sensors were easily prepared by a facile two-step fabrication route. First, three identical AgNW piezoresistive electrodes were patterned in a simple and precise manner on a donor film using a solution-processed drop-coating of the AgNWs in conjunction with a tape-type shadow mask. The patterned AgNW electrodes were then entirely transferred to an elastomeric substrate while embedding them in the polymer matrix. The fabricated stretchable AgNW piezoresistors could be operated at up to 20% strain without electrical or mechanical failure, showing a maximum gauge factor as high as 5.3, low hysteresis, and high linearity ($r^2{\approx}0.996$). Moreover, the sensor responses were also found to be highly stable and reversible even under repeated strain loading/unloading for up to 1000 cycles at a maximum tensile strain of 20%, mainly due to the mechanical stability of the AgNW/elastomer composites. In addition, both the magnitude and direction of the principal strain could be precisely characterized by configuring three identical AgNW piezoresistors in a delta rosette form, representing the potential for employing the devices as a multidimensional strain sensor in various practical applications.
Proceedings of the Korea Water Resources Association Conference
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2015.05a
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pp.236-236
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2015
Flood is one of the major natural disasters affecting millions of people. Thailand also, frequently faces with this type of disaster. Especially, 2011 mega flood in Central Thailand, inundated highway severely attributed to the failure of national economic and risk to life. Lesson learned from such an extreme event caused flood monitoring and warning becomes one of the sound mitigations. The highway flood hazard mapping accomplished in this research is one of the strategies. This is due to highway flood is the potential risk to life and limb, and potential damage to property. Monitoring and warning therefore help reducing live and property losses. In this study, degree of highway flood hazard was assessed by weighting factors for each cause of the highway flood using Multi Criteria Analysis (MCA) based Analytic Hierarchy Process (AHP). These weighting factors are the essential information to classify the degree of highway flood hazard to enable pinpoint on flood monitoring and flood warning in hazard areas. The highway flood causes were then investigated. It was found that three major factors influence to the highway flood are namely the highway characteristics, the hydrological characteristics and the land topography characteristics. The weight of importance for each cause of the highway flood in the whole country was assessed by weighting 3 major factors influence to the highway flood. According to the result of MCA analysis, the highway, the hydrological and the land topography characteristics were respectively weighted as 35, 35 and 30 percent influence to the cause of highway flood. These weighting factors were further utilized to classify the degree of highway flood hazard. The Weight Linear Combination (WLC) method was used to compute the total score of all highways according to each factor. This score was later used to categorize highway flood as high, moderate and low degree of hazard levels. Highway flood hazard map accomplished in this research study is applicable to serve as the handy tool for highway flood warning. However, to complete the whole warning process, flood water level monitoring system for example the camera gauge should be installed in the hazard highway. This is expected to serve as a simple flood monitor as part of the warning system during such extreme or critical event.
Elastic resistive pressure sensor is fabricated by a direct spray coating of silver nanowires (AgNWs) on uncured polydimethylsiloxane (PDMS) and an additional coating of a conductive polymer, poly(3,4-ethylenedioxythiophene): poly (styrene sulfonate) (PEDOT:PSS). To improve the sensitive and stability, we have fabricated sandwich-structured AgNW/polymer sensor where two AgNW/polymer-coated PDMS films are laminated with the conducting surfaces contacted by pressure lamination. It shows a resistance decrease upon loading due to the formation of dense network of AgNWs. It is demonstrated that the sandwich-structured AgNW/polymer sensor exhibits very high sensitivity ($2.59kPa^{-1}$) and gauge factor (37.8) in the low pressure regime. It can also detect a subtle placement and removal of a weight as low as 3.4 mg, the corresponding pressure of which is about 5.4 Pa. It is shown that the protrusion of AgNWs from PDMS is suppressed substantially by the over-coated PEDOT:PSS layer, thereby reducing hysteresis and rendering the sensor more stable.
Journal of the Korean Society of Propulsion Engineers
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v.22
no.6
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pp.111-117
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2018
In this study, an MEMS thrust measurement system was designed and a study on the performance prediction of system was performed to evaluate the performance of micro thruster. Thrust measurement system consists of beam, membrane, and piezoresistive sensor. An FEM analysis was carried out to verify the stability of the system, confirm the stress variation at the beam, and position the piezoresistive sensor. The stability of the designed system was verified by comparing the yield strength of the material with the maximum stress. The piezoresistive sensor was designed to be 20% of the length of the beam to obtain a high gauge factor. The size of the membrane and the beam of the reference model were designed to be $15mm{\times}15mm$, and $500{\mu}m{\times}500{\mu}m$, respectively.
This study aimed to develop a smart wearable device for assessing the risk angle associated with turtle neck syndrome in patients with Video Display Terminal (VDT) syndrome. Turtle neck syndrome, characterized by forward head posture resulting from upper cross syndrome, leads to thoracic kyphosis. In this research, a stretch sensor was used to monitor the progression of turtle neck syndrome, and the sensor data was analyzed using a Universal Testing Machine (UTM) and the Gauge Factor (GF) calculation method. The scapula and cervical spine angles were measured at five stages, with 15-degree increments from 0° to 60°. During the experimental process, the stretch sensor was attached to the thoracic spine in three different lengths: 30mm, 50mm, and 100mm. Among these, the attachment method yielding the most reliable data was determined by measuring with three techniques (General Trim Adhesive, PU film, and Heat Transfer Machine), and clothing using the heat transfer machine was selected. The experimental results confirmed that the most significant change in thoracic kyphosis occurred at approximately 30° of forward head posture. Prolonged deformity can lead to various issues, highlighting the need for textile sensor solutions. The developed wearable device aims to provide users with real-time feedback on their turtle neck posture and incorporate features that can help prevent or improve the condition.
Xue-Mei Lin;Michael C.H. Yam;Ke Ke;Binhui,Jiang;Qun He
Steel and Composite Structures
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v.46
no.3
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pp.403-416
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2023
This paper summarised and re-examined the theoretical basis of the commonly used design rule developed by Cochrane in the 1920s to consider staggered bolt holes in tension members, i.e., the s2/4g rule. The rule was derived assuming that the term two times the bolt hole diameter (2d0) in Cochrane's original equation could be neglected, and assuming a value of 0.5 for the fractional deduction of a staggered hole in assessing the net section area. Although the s2/4g rule generally provides good predictions of the staggered net section area, the above-mentioned assumptions used in developing the rule are doubtful, in particular for a connection with a small gauge-to-bolt-hole diameter (g/d0) ratio. It was found that the omission of 2d0 in Cochrane's original equation appreciably overestimates the net section area of a staggered bolted connection with a small g/d0 ratio. However, the assumed value of 0.5 for the fractional deduction of a staggered hole underestimates the staggered net section area for small g/d0 ratios. To improve the applicability of the above two assumptions, a modified design equation, which covers a full range of g/d0 ratio, was proposed to accurately predict the staggered net section area and was validated by the existing test data from the literature and numerical data derived from this study. Finally, a reliability analysis of the test and numerical data was conducted, and the results showed that the reliability of the modified design equation for evaluating the net section resistance of staggered bolted connections can be achieved with the partial factor of 1.25.
In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R2) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.
Journal of the Microelectronics and Packaging Society
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v.31
no.1
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pp.1-6
/
2024
Spiders detect even tiny vibrations through their vibrational sensory organs. Leveraging their exceptional vibration sensing abilities, they can detect vibrations caused by prey or predators to plan attacks or perceive threats, utilizing them for survival. This paper introduces a nanoscale crack-based sensor mimicking the spider's sensory organ. Inspired by the slit sensory organ used by spiders to detect vibrations, the sensor with the cracks detects vibrations and pressure with high sensitivity. By controlling the depth of these cracks, they developed a sensor capable of detecting external mechanical signals with remarkable sensitivity. This sensor achieves a gauge factor of 16,000 at 2% strain with an applied tensile stress of 10 N. With high signal-to-noise ratio, it accurately recognizes desired vibrations, as confirmed through various evaluations of external force and biological signals (speech pattern, heart rate, etc.). This underscores the potential of utilizing biomimetic technology for the development of new sensors and their application across diverse industrial fields.
Purpose: This research delves into the various factors that influence the performance of restaurant businesses on social commerce platforms in Bangkok, Thailand. The study considers both internal and external factors, including but not limited to business characteristics and location. Moreover, this research also analyzes the effects of employing multiple social commerce platforms on business efficiency and explores the underlying reasons for such effects. Research design, data, and methodology: Restaurants can be classified into different price ranges: low, medium, and high. To further investigate, we employed natural language processing AI to analyze online reviews and evaluate algorithm performance using machine learning techniques. We aimed to develop a model to gauge customer satisfaction with restaurants across different price categories effectively. Results: According to the research findings, several factors significantly impact restaurant groups in the low and mid-price ranges. Among these factors are population density and the number of seats at the restaurant. On the other hand, in the mid-and high-price ranges, the price levels of the food and drinks offered by the restaurant play a crucial role in determining customer satisfaction. Furthermore, the correlation between different social commerce platforms can significantly affect the business performance of high-price range restaurant groups. Finally, the level of online review sentiment has been found to influence customer decision-making across all restaurant types significantly. Conclusions: The study emphasizes that restaurants' characteristics based on their price level differ significantly, and social commerce platforms have the potential to affect one another. It is worth noting that the sentiment expressed in online reviews has a more significant impact on customer decision-making than any other factor, regardless of the type of restaurant in question.
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