• Geomechanics and Engineering
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• v.38 no.4
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• pp.381-395
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• 2024

With the wide application of urban subway tunnels, the foundation pits of new stations and existing subway tunnels are becoming increasingly close, and even zero-distance close-fitting construction has taken place. To optimize the construction support scheme, the existing tunnel's vertical displacement is theoretically analyzed using the two-stage analysis method to understand the action mechanism of the construction of zero-distance deep large foundation pits on both sides of the existing stations; a three-dimensional numerical calculation is also performed for further analysis. First, the additional stress field on the existing tunnel caused by the unloading of zero-distance foundation pits on both sides of the tunnel is derived based on the Mindlin stress solution of a semi-infinite elastic body under internal load. Then, considering the existing subway tunnel's joints, shear stiffness, and shear soil deformation effect, the tunnel is regarded as a Timoshenko beam placed on the Kerr foundation; a sixth-order differential control equation of the tunnel under the action of additional stress is subsequently established for solving the vertical displacement of the tunnel. These theoretical calculation results are then compared with the numerical simulation results and monitoring data. Finally, an optimized foundation pit support scheme is obtained considering the pit corner effect and external corner failure mode. The research shows a high consistency between the monitoring data,analytical and numerical solution, and the closer the tunnel is to the foundation pit, the more uplift deformation will occur. The internal corner of the foundation pit can restrain the deformation of the tunnel and the retaining structure, while the external corner can cause local stress concentration on the diaphragm wall. The proposed optimization scheme can effectively reduce construction costs while meeting the safety requirements of foundation pit support structures.

• Journal of Korean Academy of Nursing
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• v.47 no.4
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• pp.488-498
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• 2017

Purpose: The focus of the study was on the selection-optimization-compensation (SOC) strategy to predict successful aging mediated by dyspnea symptoms in older adults with chronic obstructive pulmonary disease. The model was constructed based on the hypotheses that coping strategy and social support of the elders predict successful aging through the SOC strategies. Methods: Participants were 218 outpatients with chronic obstructive pulmonary disease recruited for the study. Data collection was done from March 25 to September 11, 2015, and analyzed using SPSSWIN 22.0 and AMOS 21.0. Results: The hypothetical model appeared to be fit to the data. Seven of eight hypotheses selected for hypothetical model were statistically significant. The SOC strategy has only significant indirect effects through dyspnea symptoms on successful aging. Coping strategy, social support, SOC strategies and dyspnea symptoms explained 62% of variance in successful aging. Conclusion: The SOC strategies with social support and dyspnea symptoms significantly explained successful aging among patients with chronic obstructive pulmonary disease. Nursing strategies should be focused on social support and coping strategies to optimize SOC strategies so that older adults with chronic obstructive pulmonary disease are able to manage dyspnea symptoms and eventually achieve successful aging.

• Structural Engineering and Mechanics
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• v.62 no.3
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• pp.297-302
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• 2017

Structural reanalysis is frequently utilized to reduce the computational cost so that the process of design or optimization can be accelerated. The supports can be regarded as the design variables and may be modified in various types of structural optimization problems. The location, number, and type of supports can make a great impact on the performance of the structure. This paper presents a unified method for structural static reanalysis with imposition or relaxation of some support constraints. The information from the initial analysis has been fully utilized and the computational time can be significantly reduced. Numerical examples are used to validate the effectiveness of the proposed method.

• Journal of the Korean Institute of Navigation
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• v.23 no.4
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• pp.63-76
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• 1999

This paper aims at developing an integrated fleet management support system for industrial carriers who usually control the vessels of their own or on a time charter to minimize the cost of shipping their cargoes. The work is mainly concerned with the operational management problem of the fleet owned by a major oil company, a typical industrial carrier. The optimal fleet management problem for the major oil company can be divided into two phase problem. The front end corresponds to the production operation problem of the transportation of crude oil, the refinery operation, and the distribution of product oil to comply with the demand of the market. The back end is to tackle the fleet scheduling problem to meet the seaborne transportation demand derived from the front end. Relevant optimization models for each phase are proposed and described briefly. Then a user-friendly integrated fleet management support system is built based on the proposed optimization models for both ends under Windows environment. A case study reflecting the practices of fleet management problem for the major oil company is carried out by using the system.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.162.1-162.1
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• 2005

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.1113-1114
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• 2011

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.447-454
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• 2014

In many practical machine learning and data mining applications, unlabeled training examples are readily available but labeled ones are fairly expensive to obtain. Therefore semi-supervised learning algorithms have attracted much attentions. However, previous research mainly focuses on classication problems. In this paper, a semi-supervised regression method based on support vector regression (SVR) formulation that is proposed. The estimator is easily obtained via the dual formulation of the optimization problem. The experimental results with simulated and real data suggest superior performance of the our proposed method compared with standard SVR.

• The KIPS Transactions:PartA
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• v.13A no.7 s.104
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• pp.589-598
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• 2006

In this paper, we describe the development and optimization of an embedded Biuetooth solution on an SoC platform for real-time audio streaming over a Bluetooth wireless link. The solution includes embedded Bluetooth protocol stack and profile simplemented on a virtual operating system for portability, and other optimization techniques to fully exploit the benefits of multimedia-oriented SoC. The optimization techniques implemented in this paper are memory access minimization by using on-chip scratch pad memory, codec library optimization with DSP and parallel memory access instruction set, and dynamic audio quality adjustment regarding current wireless link status. Experimental results show that the optimized solution presented in this paper can support high-qualify audio streaming without the support of external memory.

• Structural Engineering and Mechanics
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• v.19 no.4
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• pp.361-379
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• 2005

Reinforced concrete deep beams have useful applications in tall buildings and foundations. Over the past two decades, numerous design models for deep beams were suggested. However even the latest design manuals still offer little insight into the design of deep beams in particular when complexities exist in the beams like web openings. A method commonly suggested for the design of deep beams with openings is the strut-and-tie model which is primarily used to represent the actual load transfer mechanism in a structural concrete member under ultimate load. In the present study, the development of the strut-and-tie model is transformed to the topology optimization problem of continuum structures. During the optimization process, both the stress and displacement constraints are satisfied and the performance of progressive topologies is evaluated. The influences on the strut-and-tie model in relation to different size, location and number of openings, as well as different loading and support conditions in deep beams are examined in some detail. In all, eleven deep beams with web openings are optimized and compared in nine groups. The optimal strut-and-tie models achieved are also compared with published experimental crack patterns. Numerical results have shown to confirm the experimental observations and to efficiently represent the load transfer mechanism in concrete deep beams with openings under ultimate load.

• Geomechanics and Engineering
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• v.32 no.3
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• pp.271-291
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• 2023

Settlement estimation in cohesion materials is a crucial topic to tackle because of the complexity of the cohesion soil texture, which could be solved roughly by substituted solutions. The goal of this research was to implement recently developed machine learning features as effective methods to predict settlement (S_m) of shallow foundations over cohesion soil properties. These models include hybridized support vector regression (SVR), random forests (RF), and coot optimization algorithm (COM), and black widow optimization algorithm (BWOA). The results indicate that all created systems accurately simulated the S_m, with an R² of better than 0.979 and 0.9765 for the train and test data phases, respectively. This indicates extraordinary efficiency and a good correlation between the experimental and simulated S_m. The model's results outperformed those of ANFIS - PSO, and COM - RF findings were much outstanding to those of the literature. By analyzing established designs utilizing different analysis aspects, such as various error criteria, Taylor diagrams, uncertainty analyses, and error distribution, it was feasible to arrive at the final result that the recommended COM - RF was the outperformed approach in the forecasting process of S_m of shallow foundation, while other techniques were also reliable.