• Title, Summary, Keyword: Capability Reinforcement

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Fatigue performance monitoring of full-scale PPC beams by using the FBG sensors

  • Wang, Licheng;Han, Jigang;Song, Yupu
    • Smart Structures and Systems
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    • v.13 no.6
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    • pp.943-957
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    • 2014
  • When subjected to fatigue loading, the main failure mode of partially prestressed concrete (PPC) structure is the fatigue fracture of tensile reinforcement. Therefore, monitoring and evaluation of the steel stresses/strains in the structure are essential issues for structural design and healthy assessment. The current study experimentally investigates the possibility of using fiber Bragg grating (FBG) sensors to measure the steel strains in PPC beams in the process of fatigue loading. Six full-scale post-tensioned PPC beams were exposed to fatigue loading. Within the beams, the FBG and resistance strain gauge (RSG) sensors were independently bonded onto the surface of tensile reinforcements. A good agreement was found between the recorded results from the two different sensors. Moreover, FBG sensors show relatively good resistance to fatigue loading compared with RSG sensors, indicating that FBG sensors possess the capability for long-term health monitoring of the tensile reinforcement in PPC structures. Apart from the above findings, it can also be found that during the fatigue loading, there is stress redistribution between prestressed and non-prestressed reinforcements, and the residual strain emerges in the non-prestressed reinforcement. This phenomenon can bring about an increase of the steel stress in the non-prestressed reinforcement.

Numerical experimentation for the optimal design for reinforced concrete rectangular combined footings

  • Velazquez-Santilla, Francisco;Luevanos-Rojas, Arnulfo;Lopez-Chavarria, Sandra;Medina-Elizondo, Manuel;Sandoval-Rivas, Ricardo
    • Advances in Computational Design
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    • v.3 no.1
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    • pp.49-69
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    • 2018
  • This paper shows an optimal design for reinforced concrete rectangular combined footings based on a criterion of minimum cost. The classical design method for reinforced concrete rectangular combined footings is: First, a dimension is proposed that should comply with the allowable stresses (Minimum stress should be equal or greater than zero, and maximum stress must be equal or less than the allowable capacity withstand by the soil); subsequently, the effective depth is obtained due to the maximum moment and this effective depth is checked against the bending shear and the punching shear until, it complies with these conditions, and then the steel reinforcement is obtained, but this is not guaranteed that obtained cost is a minimum cost. A numerical experimentation shows the model capability to estimate the minimum cost design of the materials used for a rectangular combined footing that supports two columns under an axial load and moments in two directions at each column in accordance to the building code requirements for structural concrete and commentary (ACI 318S-14). Numerical experimentation is developed by modifying the values of the rectangular combined footing to from "d" (Effective depth), "b" (Short dimension), "a" (Greater dimension), "${\rho}_{P1}$" (Ratio of reinforcement steel under column 1), "${\rho}_{P2}$" (Ratio of reinforcement steel under column 2), "${\rho}_{yLB}$" (Ratio of longitudinal reinforcement steel in the bottom), "${\rho}_{yLT}$" (Ratio of longitudinal reinforcement steel at the top). Results show that the optimal design is more economical and more precise with respect to the classical design. Therefore, the optimal design presented in this paper should be used to obtain the minimum cost design for reinforced concrete rectangular combined footings.

Q-learning to improve learning speed using Minimax algorithm (미니맥스 알고리즘을 이용한 학습속도 개선을 위한 Q러닝)

  • Shin, YongWoo
    • Journal of Korea Game Society
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    • v.18 no.4
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    • pp.99-106
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    • 2018
  • Board games have many game characters and many state spaces. Therefore, games must be long learning. This paper used reinforcement learning algorithm. But, there is weakness with reinforcement learning. At the beginning of learning, reinforcement learning has the drawback of slow learning speed. Therefore, we tried to improve the learning speed by using the heuristic using the knowledge of the problem domain considering the game tree when there is the same best value during learning. In order to compare the existing character the improved one. I produced a board game. So I compete with one-sided attacking character. Improved character attacked the opponent's one considering the game tree. As a result of experiment, improved character's capability was improved on learning speed.

Experimental Study on Flexural Behavior of PC Beam Column Joint with Spliced Strand (강선 이음길이에 따른 PC 보-기둥 접합부의 휨 거동에 관한 실험적 연구)

  • 하상수;김승훈;문정호;이리형;이강철;김익배
    • Proceedings of the Korea Concrete Institute Conference
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    • pp.207-210
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    • 2003
  • As reviewing of current trend on PC connection details, owing to effective stress transfer in the connection, it grow to increase that use of mechanical splices, reinforcements or welded splices, and prestressing. However such devices as reinforcement, mechanical splices entail not only more cost resulted from materials but also extra construction process so as to cause PC used method to lower competition against conventional method. Therefore more enhanced connection details which help working process simplified and construction cost reduced. In this research, as replace 9.3mm 7strand for reinforcement, it is attempt to devise connection detail which makes workability improve and confirm effective stress transfer in the region of connection. The experimental research is proceeded by partial tension test of specimen. The splice lengths of 7strand is decided to be variations. The flexural capability is verified to depend on spice length. An an appropriate splice length could be also determined as a precedent research on improving PC connection detail.

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Solving Continuous Action/State Problem in Q-Learning Using Extended Rule Based Fuzzy Inference System

  • Kim, Min-Soeng;Lee, Ju-Jang
    • Transactions on Control, Automation and Systems Engineering
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    • v.3 no.3
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    • pp.170-175
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    • 2001
  • Q-learning is a kind of reinforcement learning where the agent solves the given task based on rewards received from the environment. Most research done in the field of Q-learning has focused on discrete domains, although the environment with which the agent must interact is generally continuous. Thus we need to devise some methods that enable Q-learning to be applicable to the continuous problem domain. In this paper, an extended fuzzy rule is proposed so that it can incorporate Q-learning. The interpolation technique, which is widely used in memory-based learning, is adopted to represent the appropriate Q value for current state and action pair in each extended fuzzy rule. The resulting structure based on the fuzzy inference system has the capability of solving the continuous state about the environment. The effectiveness of the proposed structure is shown through simulation on the cart-pole system.

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A Study on the Strategy of Products Development for Mass Housing (공동주택 상품개발 전략에 관한 연구)

  • Yang, Young-Keun
    • Journal of The Korean Digital Architecture Interior Association
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    • v.10 no.2
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    • pp.31-38
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    • 2010
  • This study is to suggest a strategy and trend of products development by major construction companies to form a trend and to set the trend in housing market through investigation about brand image campaign for TV ad, individual design items, result of products development and special plans. It is the strategy for products development of construction companies surveyed to be divided into five kinds. First, the change from in the unit to outside. Second, centralization of design powers about products development through submit and the wining of a prize in the domestic & foreign design fair to publicize a excellent quality in a roundabout way. Third, reinforcement of service for support the habitability and design manual for secure uniform quality. Forth, investment in the environment-friendly housing and new recycling energy. Fifth, reinforcement of organizational power for improving production capability.

Analysis of the in-plane shear behaviour of FRP reinforced hollow brick masonry walls

  • Gabor, A.;Ferrier, E.;Jacquelin, E.;Hamelin, P.
    • Structural Engineering and Mechanics
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    • v.19 no.3
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    • pp.237-260
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    • 2005
  • This paper presents an experimental as well as a numerical analysis of the in-plane shear behaviour of hollow, $870{\times}840{\times}100mm$ masonry walls, externally strengthened with FRP composites. The experimental approach is devoted to the evaluation of the effectiveness of different composite strengthening configurations and the methodology consists in the diagonal compression of masonry walls. The numerical study assesses the stress and strain state distribution in the unreinforced and strengthened panels using a commercial finite element code. The effect of FRP reinforcement on the masonry behaviour and the capability of modelling to forecast a representative failure mode of the unreinforced and reinforced masonry walls is investigated.

A method of global-local analyses of structures involving local heterogeneities and propagating cracks

  • Kurumatani, Mao;Terada, Kenjiro
    • Structural Engineering and Mechanics
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    • v.38 no.4
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    • pp.529-547
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    • 2011
  • This paper presents the global-local finite cover method (GL-FCM) that is capable of analyzing structures involving local heterogeneities and propagating cracks. The suggested method is composed of two techniques. One of them is the FCM, which is one of the PU-based generalized finite element methods, for the analysis of local cohesive crack growth. The mechanical behavior evaluated in local heterogeneous structures by the FCM is transferred to the overall (global) structure by the so-called mortar method. The other is a method of mesh superposition for hierarchical modeling, which enables us to evaluate the average stiffness by the analysis of local heterogeneous structures not subjected to crack propagation. Several numerical experiments are conducted to validate the accuracy of the proposed method. The capability and applicability of the proposed method is demonstrated in an illustrative numerical example, in which we predict the mechanical deterioration of a reinforced concrete (RC) structure, whose local regions are subjected to propagating cracks induced by reinforcement corrosion.

Experimental Verification of Resistance-Demand Approach for Shear of HSC Beams

  • El-Sayed, Ahmed K.;Shuraim, Ahmed B.
    • International Journal of Concrete Structures and Materials
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    • v.10 no.4
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    • pp.513-525
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    • 2016
  • The resistance-demand approach has emerged as an effective approach for determining the shear capacity of reinforced concrete beams. This approach is based on the fact that both the shear resistance and shear demand are correlated with flexural tensile strain from compatibility and equilibrium requirements. The basic shear strength, under a given loading is determined from the intersection of the demand and resistance curves. This paper verifies the applicability of resistance-demand procedure for predicting the shear capacity of high strength concrete beams without web reinforcement. A total of 18 beams were constructed and tested in four-point bending up to failure. The test variables included the longitudinal reinforcement ratio, the shear span to depth ratio, and the beam depth. The shear capacity of the beams was predicted using the proposed procedure and compared with the experimental values. The results of the comparison showed good prediction capability and can be useful to design practice.

Reinforcement of Rubber Properties by Carbon Black and Silica Fillers: A Review

  • Seo, Gon;Kim, Do-Il;Kim, Sun Jung;Ryu, Changseok;Yang, Jae-Kyoung;Kang, Yong-Gu
    • Elastomers and Composites
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    • v.52 no.2
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    • pp.114-130
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    • 2017
  • Enhancing the properties of rubber, such as the tensile strength, modulus, and wear abrasion, by the addition of carbon black and silica as fillers is very important for improving the performance of rubber products. In this review, we summarize the general features of 'the reinforcement of rubber by fillers' and the equations for representing the reinforcement phenomena. The rubber reinforcement was attributed to enhancement of the following: the rubber, bound rubber, formation of networks, and combination between rubber chains and silica followed by entanglement. The reinforcement capability of silica species with different surface and networked states demonstrated the importance of the connection between the silica particles and the rubber chains in achieving high reinforcement. The model involving combination followed by entanglement can provide a plausible explanation of the reinforcement of rubber by carbon black and silica because the combination facilitates the concentration of rubber chains near the filler particles, and entanglement of the rubber chains around the filler particles enforces the resistance against deformation and breakage of rubber compounds, resulting in high reinforcement.