• Title/Summary/Keyword: Structural Model Test

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Parameter calibrations and application of micromechanical fracture models of structural steels

  • Liao, Fangfang;Wang, Wei;Chen, Yiyi
    • Structural Engineering and Mechanics
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    • v.42 no.2
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    • pp.153-174
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    • 2012
  • Micromechanical facture models can be used to predict ductile fracture in steel structures. In order to calibrate the parameters in the micromechanical models for the largely used Q345 steel in China, uniaxial tensile tests, smooth notched tensile tests, cyclic notched bar tests, scanning electron microscope tests and finite element analyses were conducted in this paper. The test specimens were made from base metal, deposit metal and heat affected zone of Q345 steel to investigate crack initiation in welded steel connections. The calibrated parameters for the three different locations of Q345 steel were compared with that of the other seven varieties of structural steels. It indicates that the toughness index parameters in the stress modified critical strain (SMCS) model and the void growth model (VGM) are connected with ductility of the material but have no correlation with the yield strength, ultimate strength or the ratio of ultimate strength to yield strength. While the damage degraded parameters in the degraded significant plastic strain (DSPS) model and the cyclic void growth model (CVGM) and the characteristic length parameter are irrelevant with any properties of the material. The results of this paper can be applied to predict ductile fracture in welded steel connections.

Data Model for Hybrid Structural Experiments (하이브리드 구조실험을 위한 데이터 모델)

  • Lee, Chang-Ho;Marullo, Thomas;Sause, Richard
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.22 no.5
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    • pp.391-401
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    • 2009
  • The hybrid approach for structural experiments decomposes a structure into independent substructures that can be tested or simulated. The results from the decomposed substructures are combined to predict the behaviors of the entires structure. The hybrid approach is especially useful for the hybrid pseudo-dynamic tests that overcome the limitations of size of a test structure present in a shaking table test. The development of a computer system for the hybrid experiment requires a data model that formally organizes the information involved in the hybrid experiments. This paper provides the data model for representing the information involved in the hybrid experiments, by modifying the classes and attributes for the hybrid experiments in the Lehigh Model that is one of the data models for structural experiments. The data model for the hybrid experiments includes the classes for the physical substructures being tested and the analytical substructures being analyzed, and the simulation coordinator managing the overall experiments. Some objects for classes are implemented as an example to show the links among the classes. The data model presented in this paper can be applied for developing a computer system that helps structural engineers and researchers store, share, and access the information for the hybrid experiments.

Reliability Analysis of Steel Fiber Reinforced Concrete Beams (강섬유 보강 철근콘크리트보의 신뢰성 해석)

  • 유한신;곽계환;장화섭
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2004.04a
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    • pp.479-486
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    • 2004
  • The purpose of this study is to practical use with increase safety, usablility and economical. In this study, the property of fatigue behavior was tested by comparing reinforced concrete and steel fiber reinforced concrete. The basic test, the static test and fatigue test were used as the research methods. Basic on the test, the material compressive strength test and split tensile strength test ware conducted 7 days and 28 days after the concrete was poured. In the static test, there ware four types of experimental variables of the steel fiber mixing ratio : 0.00%, 0.75%, 1.00%, and 1.25%. The ultimate load initial diagonal tension crack, and initial load of flexural cracking were all observed by static test. A methodology for the probabilistic assement of steel fiber reinforced concrete(SFRC) which takes into account material variability, confinement model uncertainty and the uncertainty in local and globa failure criteria is applied for the derivation of vulnerability curves for the serviceability and ultimate limit states, the reliability of SFRC using the proposed practical linear limit state model is evaluated by using the AFOSM(Advanced First Order Second Moment) method and MCS(monte-Calrosimulation) method.

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Structural Joint Integrity Monitoring of Steel Frame Structures Using Impulse Responses (충격응답을 이용한 철골 구조물 접합부의 구조건전성 모니터링)

  • Yi, Jin-Hak;Lee, Kwang-Soo
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2008.04a
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    • pp.145-150
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    • 2008
  • This study proposes an improved AR-model based structural joint integrity monitoring method and a new damage sensitive feature using RMS values of impulse responses. The proposed methods were applied for joint integrity monitoring of a model scale 2-bay and 4-story steel frame structure and it was found that the AR coefficients could be more consistently estimated by adopting the band-pass filter and cross-correlation function to the raw acceleration signals and the joint damages could be successfully monitored by the proposed methods.

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A neural network model to assess the hysteretic energy demand in steel moment resisting frames

  • Akbas, Bulent
    • Structural Engineering and Mechanics
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    • v.23 no.2
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    • pp.177-193
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    • 2006
  • Determining the hysteretic energy demand and dissipation capacity and level of damage of the structure to a predefined earthquake ground motion is a highly non-linear problem and is one of the questions involved in predicting the structure's response for low-performance levels (life safe, near collapse, collapse) in performance-based earthquake resistant design. Neural Network (NN) analysis offers an alternative approach for investigation of non-linear relationships in engineering problems. The results of NN yield a more realistic and accurate prediction. A NN model can help the engineer to predict the seismic performance of the structure and to design the structural elements, even when there is not adequate information at the early stages of the design process. The principal aim of this study is to develop and test multi-layered feedforward NNs trained with the back-propagation algorithm to model the non-linear relationship between the structural and ground motion parameters and the hysteretic energy demand in steel moment resisting frames. The approach adapted in this study was shown to be capable of providing accurate estimates of hysteretic energy demand by using the six design parameters.

Stability evaluation model for loess deposits based on PCA-PNN

  • Li, Guangkun;Su, Maoxin;Xue, Yiguo;Song, Qian;Qiu, Daohong;Fu, Kang;Wang, Peng
    • Geomechanics and Engineering
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    • v.27 no.6
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    • pp.551-560
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    • 2021
  • Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

Development of a Structural Equation Model for Children's Adaptation in Divorced Families (회복력 요인 중심의 이혼가정 아동 적응모형)

  • Shin, Sung-Hee
    • Journal of Korean Academy of Nursing
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    • v.40 no.1
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    • pp.127-138
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    • 2010
  • Purpose: This study was designed to develop and test a structural model for children's adaptation in divorced families. The hypothetical model was constructed based on the Family Resilience Model by McCubbin and McCubbin. Methods: Data were collected using self-report questionnaires from 219 children (3-6th grade) in divorced families. The children attended one of 22 community agencies, 8 after-school programs, 3 elementary schools in three cities in South Korea. The collected data were analyzed using LISREL program to test the hypothetical model. Results: The modified model was constructed by deleting four paths in accordance with the statistical and theoretical criteria. Compared to the hypothetical model, the revised one had a better fit to the data. Self-esteem, and beliefs about parental divorce had direct effects, and family communication and internal control had indirect effects on children's adaptation in divorced families. These variables explained 56% of the variance in children's adaptation. Conclusion: The modified model was supported by empirical data. This model could be applied to family nursing interventions with divorced families or any other suffering family transition. When working with children experiencing parental divorce, it is important for nurses to enhance children's self-esteem, family communication and to decrease children's negative beliefs about parental divorce to help in their adaptation.

Grouting effects evaluation of water-rich faults and its engineering application in Qingdao Jiaozhou Bay Subsea Tunnel, China

  • Zhang, Jian;Li, Shucai;Li, Liping;Zhang, Qianqing;Xu, Zhenhao;Wu, Jing;He, Peng
    • Geomechanics and Engineering
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    • v.12 no.1
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    • pp.35-52
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    • 2017
  • In order to evaluate the grouting effects of water-rich fault in tunnels systematically, a feasible and scientific method is introduced based on the extension theory. First, eight main influencing factors are chosen as evaluation indexes by analyzing the changes of permeability, mechanical properties and deformation of surrounding rocks. The model of evaluating grouting effects based on the extension theory is established following this. According to four quality grades of grouting effects, normalization of evaluation indexes is carried out, aiming to meet the requirement of extension theory on data format. The index weight is allocated by adopting the entropy method. Finally, the model is applied to the grouting effects evaluation in water-rich fault F4-4 of Qingdao Jiaozhou Bay Subsea Tunnel, China. The evaluation results are in good agreement with the test results on the site, which shows that the evaluation model is feasible in this field, providing a powerful tool for systematically evaluating the grouting effects of water-rich fault in tunnels.

Construction of a Structural Equation Model on Attitudes to Science Using LISREL (LISREL을 이용한 과학에서의 태도에 관한 구조방정식모델의 구축)

  • Lee, Kyung-Hoon
    • Journal of The Korean Association For Science Education
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    • v.17 no.3
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    • pp.301-311
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    • 1997
  • The purpose of this study is to construct a structural equation model and to analyze causal relationships among variables related to attitudes to science using structural equation modeling(SEM) with LISREL VII. The sample consisted of 483 10th grade boys from a general high school in Pusan, Korea. The questionnaires (ABC-attitude scale: affection, behavioral intention, cognition scale of attitude towards science) were developed by the researcher through a pilot study. And other instruments have modified previous ones. Five instruments were used in this study: GALT(group assessment of logical thinking), MTSlS(modified test of science inquiry skill), ABC-attitude scale, MSAS(modified scientific attitude scale), CSAT(common science achievement test). Structural equation modeling with LISREL VII($J\ddot{o}reskog$ & $S\ddot{o}rbom,$ 1993) was employed to estimate the causal inferences about hypothesized relationships among observed data sets. Three competing models consisted of five latent variable(scientific thinking ability, science inquiry skill, attitude towards science, scientific attitude, science achievement) - lP(inquiry preceding) model, AP(attitude preceding) model and AM(attitude mediating) model - were developed. Among these competing models, IP model satisfied the observed data sets. The causal relationships among "attitudes to science" and other latent variables were reliably identified. According to the results of the present study, science inquiry skill was the most significant variable that can predict science achievement. But scientific thinking ability has not directly influenced science achievement. This study suggests that inquiry based teaching-learning processes should be offered to students for improvement of science achievement. At the same time, it seems to be important to develop positive attitude towards science. Understanding of relationships among variables related to attitudes to science will be helpful to the development of science curriculum and to the design of science teaching and learning process. LISREL has been recognized as a useful approach in testing a SEM. However, in this study, LISREL approach was estimated as much more useful method for research design.

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Structural Analysis Model to Evaluate the Mechanical Reliability of Large-area Photovoltaic Modules (대면적 태양광 모듈의 기계적 신뢰성 평가를 위한 모델)

  • Noh, Yo Han;Jeong, Jeong Ho;Lee, Jaehyeong
    • Current Photovoltaic Research
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    • v.10 no.2
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    • pp.56-61
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    • 2022
  • Recently, the expansion of the domestic solar market due to the promotion of eco-friendly and alternative energy-related policies is promising, and it is expected to lead the high-efficiency/high-power module market based on M10 or larger cells to reduce LCOE, 540-560W, M12 based on M10 cells Compared to the existing technology with an output of 650-700W based on cells, it is necessary to secure competitiveness through the development of modules with 600W based on M10 cells and 750W based on M12 cells. For the development of high efficiency/high-power n-type bifacial, it is necessary to secure a lightweight technology and structure due to the increase in weight of the glass to glass module according to the large area of the module. Since the mechanical strength characteristics according to the large area and high weight of the module are very important, design values such as a frame of a new structure that can withstand the mechanical load of the Mechanical Load Test and the location of the mounting hole are required. In this study, a structural analysis design model was introduced to secure mechanical reliability according to the enlargement of the module area, and the design model was verified through the mechanical load test of the actual product. It can be used as a design model to secure the mechanical reliability required for PV modules by variables such as module area, frame shape, and the location and quantity of mounting holes of the structural analysis model verified. A relationship of output drop can be obtained.