• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.133-142
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• 2006

This paper evaluates the moment equations in the 2000 Canadian highway bridge code (CHBDC) for soil-metal box structures, which are applicable to the span less than 8 m. Finite element analyses carried out for soil-metal box structures having spans of 3-12 m using the deep corrugated metal plates under three construction stages; backfill up to the crown, backfill up to the cover depth, and live loading. The coefficients of moment equations are newly proposed based on the results of numerous finite element analyses considering various design variables, such as span length, soil depth, backfill conditions. The validity of the proposed coefficients in the moment equations of the 2000 CHBDC is investigated by the comparison with the existing coefficients and numerical results of finite element analyses. The comparisons show that the moments of the 2000 CHBDC give good predictions for the span less than 8m, but underestimate for the span greater than 8m, whereas the proposed moments give good estimates of numerical results for the spans of 3-12 m. In addition, this study suggests the use of high strength steel to satisfy the requirement of design bending strength for the span greater than 8 m.

• Journal of the Korea Institute of Construction Safety
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• v.6 no.1
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• pp.7-11
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• 2024

Pump car is an equipment that transports concrete products as needed to the place where they are poured. In order to pour a large amount of concrete in a short period of time, using a pump car is the most efficient in terms of economic efficiency and quality control. However, recently, many casualties have occurred due to boom damage during concrete pouring, so this study suggests that improvements are needed in the equipment manufacturing stage, inspection standards for old equipment, and equipment rental system. The reason is that, as a result of the finite element analysis of the pump car, the significant stress acting at the second stage of the boom and the maximum stress at the top of the boom were found to be 895.39 MPa, and M.S. Since it was evaluated the lowest at 0.04, the need for reinforcement was recognized. And it was confirmed that the 2nd stage boom was the most stressful and vulnerable part of the 1st to 5th stage booms. Therefore, it is necessary to increase the thickness and rigidity of members at the design and manufacturing stage, and to reinforce the steel plates of currently used equipment. In addition, it is urgent to establish a system that makes non-destructive testing mandatory for all general construction machinery and holds inspection agencies responsible for missing boom defects during non-destructive testing and regular inspections.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.7-11
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• 2024

The bedsore prevention cushion serves to prevent the skin on the buttocks of a wheelchair user from being damaged through friction with the wheelchair seat. This is because it absorbs some of the weight applied to the wheelchair seat and allows the weight to be applied evenly to the entire contact surface. For the impact test, which is part of the performance testing of bedsore prevention cushions, a hip model that represents the sitting posture of a wheelchair user is required. In this study, a hip model was manufactured for impact testing of bedsore prevention cushions for wheelchairs. Performance tests for pressure bedsore prevention cushions for wheelchairs include KSP 0236, a Korean standard, and KS P ISO 16840-2, an ISO international standard. The hip model proposed in KS P ISO 16840-2 was more suitable for impact testing of bedsore prevention cushions for wheelchairs. However, the guidelines for making hip models proposed by international standards need to be modified to reflect the advancement of model making technology and use easier methods. We propose a new hip model production method that produces a hip model out of plastic all at once and additionally attaches SS-41 steel plates processed into the shape of the hip to make the mass of the model similar to the human body.

• Journal of Yeungnam Medical Science
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• v.7 no.1
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• pp.81-93
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• 1990

The author fractographically analyized the cause of metal failure(the first time this procedure has been used for this metal failure)and also analyized it clinically. In this study, I selected eight cases which have been analyized fractographically. In all these cases, the analysis was done after treatment of metal failure of implants internally fixed to femur shaft fractures at the Department of Orthopedic Surgery, Yeung-Nam University Hospital during the six year period from May 1983 to September 1989. 1. Metal failure occured in five dynamic-compression plates, one Jewett nail, one screw in Rowe plate, and one interlocking nail. 2. The clinical cause of metal failure was deficiency of medial butress in five cases, incorrect position of implant in one case, and incorrect selection of implant in two cases. 3. The time interval between internal fixation and metal failure was four months in one case, between five months to twelve months in six cases, three years in one case. 4. The fractographically analytical cause of metal failure was ; first, impact failure, one case, second, fatigue failure, six cases, machining mark(stress liser), four cases type : low consistent cyclic fatigue failure irregular cyclic fatigue failure third, stress corrosion crack, one case. 5. 316L Stainless Steel has good resistance to corrosion. However, when its peculiar surface film is destroyed by fretting, it shows pitting corrosion. This is, perhaps, the main cause of metal failure. 6. It is possible that mechanical injury occured in implants during the manufacturing of implants or that making a screw hole is the main cause of metal failure.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.