• Composites Research
• /
• 제26권2호
• /
• pp.79-84
• /
• 2013

본 연구에서는 적층판 시편의 피로손상 균열진전 시험결과와 적층보강판 구조의 응력강도 해석결과를 기초로 충격손상을 모사한 원공과 노치손상을 내재한 보강재 본딩접합 적층보강판 구조의 피로손상 균열진전 수명예측에 대하여 고찰하였다. 그리고 적층보강판 구조시편에 대한 손상허용 시험결과와 손상진전 수명예측 해석결과를 비교분석한 결과 손상균열 길이 변화에 따라 최종파단에 대한 잔여강도를 예측하고 손상허용성 평가를 할 수 있었다.

• Journal of Ecology and Environment
• /
• 제48권3호
• /
• pp.374-381
• /
• 2024

Background: There is a wide range of phenotypic plasticity in plants that respond to tissue damage. Compensatory growth after physical damage may function as a part of tolerance to herbivory, which is affected by resource limitations and/or damage properties. Results: Under different light availability (unshaded and shaded) and damaged leaf ontogeny (control, young leaf- and mature leaf-damaged), compensatory growth was examined for the herbal vine Aristolochia contorta. Under the unshaded treatment, compensatory growth on leaf and branch emergence was strongly induced compared to the shaded treatment. Damage to young leaves induced leaf emergence more strongly than damage to old leaves. Conclusions: It appears that light availability acted as a limiting factor in the compensatory growth of A. contorta after the damage despite its vigorous growth under the shade treatment. Under the shade, leaf damage led to altered biomass allocation as indicated by a decrease in specific leaf area and an increase in root mass fraction. The present study contributes to the understanding of the phenotypic plasticity of vine species under different environmental conditions and damaged tissue, which may differ depending on the species' habitat range.

• 한국정밀공학회지
• /
• 제16권7호
• /
• pp.168-177
• /
• 1999

Fatigue damage is the phenomena which is accumulated gradually with loading cycle in material. It is represented by fatigue crack growth rate da/dN and fatigue life ratio $N/N_{f}$. Fracture mechanical parameters estimating large crack growth behavior can calculate quantitative amount of fatigue crack growth resistance in engineering material. But fatigue damage has influence on various load, material and environment. Therefore, In this study, we propose that artificial intelligent fatigue damage model can predicts fatigue crack growth rate da/dN and fatigue life ratio $N/N_{f}$ simultaneously using fracture mechanical and nondestructive parameters.

• Structural Engineering and Mechanics
• /
• 제72권3호
• /
• pp.313-327
• /
• 2019

Damage evolution in the form of void nucleation, propagation and coalescence is the primary cause that is responsible for the ductile failure of microalloyed steels. The Gurson-Tvergaard-Needleman (GTN) damage model has proven to be extremely robust for characterizing the microscopic damage behavior of ductile metals. Nonetheless, successful applications of the model on a given metal type are limited by the correct identification of damage parameters as well as the validation of the calculated void growth rate. The purpose of this study is two-fold. First, we aim to identify the damage parameters of the GTN model for Q345 steel (Chinese code), due to its extensive application in mechanical and civil industries in China. The identification of damage parameters is facilitated by the well-suited response surface methodology, followed by a complete analysis of variance for evaluating the statistical significance of the identified model. Second, taking notched Q345 cylinders as an example, finite element simulations implemented with the identified GTN model are performed in order to analyze their microscopic damage behavior. In particular, the void growth rate predicted from the simulations is successfully correlated with experimentally measured acoustic emissions. The quantitative correlation suggests that during the yielding stage the void growth rate increases linearly with the acoustic emissions, while in the strain-hardening and softening period the dependence becomes an exponential function. The combined experimental and finite element approach provides a means for validating simulated void growth rate against experimental measurements of acoustic emissions in microalloyed steels.

• Structural Engineering and Mechanics
• /
• 제7권2호
• /
• pp.225-240
• /
• 1999

This paper presents a mechanistic approach to uniaxial viscoelastic constitutive modeling of asphalt concrete that accounts for damage evolution under cyclic loading conditions. An elasticviscoelastic correspondence principle in terms of pseudo variables is applied to separately evaluate viscoelasticity and time-dependent damage growth in asphalt concrete. The time-dependent damage growth in asphalt concrete is modeled by using a damage parameter based on a generalization of microcrack growth law. Internal state variables that describe the hysteretic behavior of asphalt concrete are determined. A constitutive equation in terms of stress and pseudo strain is first established for controlled-strain mode and then transformed to a controlled-stress constitutive equation by simply replacing physical stress and pseudo strain with pseudo stress and physical strain. Tensile uniaxial fatigue tests are performed under the controlled-strain mode to determine model parameters. The constitutive equations in terms of pseudo strain and pseudo stress satisfactorily predict the constitutive behavior of asphalt concrete all the way up to failure under controlled-strain and -stress modes, respectively.

• Journal of Mechanical Science and Technology
• /
• 제19권7호
• /
• pp.1393-1404
• /
• 2005

Fatigue crack growth and life have been estimated based on established empirical equations. In this paper, an alternative method using artificial neural network (ANN) -based model developed to predict fatigue damages simultaneously. To learn and generalize the ANN, fatigue crack growth rate and life data were built up using in-plane bending fatigue test results. Single fracture mechanical parameter or nondestructive parameter can't predict fatigue damage accurately but multiple fracture mechanical parameters or nondestructive parameters can. Existing fatigue damage modeling used this merit but limited real-time damage monitoring. Therefore, this study shows fatigue damage model using backpropagation neural networks on the basis of X -ray half breadth ratio B / $B_o$, fractal dimension $D_f$ and fracture mechanical parameters can estimate fatigue crack growth rate da/ dN and cycle ratio N / $N_f$ at the same time within engineering limit error ($5\%$).

• 한국환경생태학회지
• /
• 제25권6호
• /
• pp.893-902
• /
• 2011

본 연구의 목적은 마을 주변의 전통 소나무숲을 선정하여 숲의 구조와 생장실태를 조사하고, 양호한 생장과 보전을 위한 관리방안을 수립하는 것이었다. 연구대상 소나무숲은 강원도 영서지역에 분포하는 12개소를 선정하였다. 숲의 조성시기는 개소별로 최소 50~최대 200년 전이었고, 소나무의 평균 흉고직경과 밀도는 각각 27~52cm, 0.5~9.3주/$100m^2$이었다. 생장기반인 토양환경은 소나무 생장에 대개 양호한 편이었으나, 토성이 사토로서 보비력이 낮은 2개소의 경우 토양양분이 현저하게 낮았다. 일부 숲은 복토, 답압 등으로 인해 근계생장 장해에 따른 수세저하가 나타났다. 수간의 수피탈저 및 공동피해가 6개소에서 발생하였고, 그 원인은 인위적 외상, 전정 부주의, 동해 등이었다. 병해는 그을음잎마름병, 갈색무늬병 등이 6개소에서 발생하였고 피해정도는 경미하였다. 충해의 경우는 솔잎혹파리에 의한 피해로서 피해정도는 6개소에서 경미하였으나, 2개소에서는 상대적으로 더 현저하였다. 이와 같이, 연구대상 소나무숲의 생장저해를 야기하는 주 요인은 양분부족, 복토 및 답압, 수간훼손, 병충해 등이었다. 이들 원인별 문제점을 개선하여 해당 소나무숲을 보전할 관리방안을 모색하였다. 관리방안은 유기물과 석회 시용, 복토 제거, 토양굴기와 자갈포설, 목도설치 또는 우드칩 포장, 목책 및 보호틀 제공, 수간 외과수술, 수세강화, 수간주사 등 생장환경을 개선하거나 수간훼손과 병충해를 제어할 대책을 포함하였다.

• 한국군사과학기술학회지
• /
• 제5권4호
• /
• pp.67-77
• /
• 2002

This paper introduces the calibration results of the fatigue crack growth models for damage tolerance analysis of the aircraft structures. Generalized Willenborg model and Wheeler model are calibrated with experimental data tested under the load spectrum of a trainer. The retardation factors such as, shut-off ratio in Generalized Willenborg model and shaping exponent in Wheeler model, are evaluated for aluminum alloys AL2024-T3511, AL7050-T7451 and AL7075-T73511. It is shown that the retardation effect of the crack growth rate depends on the yield strength of material and the maximum stress in the load spectrum. Generalized Willenborg model and Wheeler model give satisfactory prediction of crack growth life but the calibration of the experimental parameters with test is required.

• 한국자동차공학회논문집
• /
• 제7권6호
• /
• pp.258-269
• /
• 1999

It is important to evaluate fatigue damage of in-service material in respect to assure safety and remaining fatigue life in structure and mechanical components under cyclic load . Fatigue damage is represented by mathematical modelling with crack growth rate da/dN and cycle ration N/Nf and is detected by X-ray diffraction and ultrasonic wave method etc. But this is estimated generally by single parameter but influenced by many test conditions The characteristics of it indicates fatigue damage has complex fracture mechanism. Therefore, in this study we propose that back-propagation neural networks on the basis of ration of X-ray half-value breath B/Bo, fractal dimension Df and fracture mechanical parameters can construct artificial intelligent networks estimating crack growth rate da/dN and cycle ratio N/Nf without regard to stress amplitude Δ $\sigma$.

• 한국정밀공학회지
• /
• 제13권10호
• /
• pp.130-138
• /
• 1996

In general, the scattler is observed in fatigue test data due to the nonhomogeneity of a material. Consequently. It is necessary to use the statistical method to describe the fatigue crack growth process precisely. Bogdanoff and Kozin suggested and developed the B-model which is the probabilistic models of cumulative damage using the Markov process in order to describe the damage process. But the B-model uses only constant probability ratior(r), so it is not consistent with the actual damage process. In this study, the r-decreasing model using a monotonic decreasing function is introduced to improve the B-model. To verify the model, thest data of fatigue crack growth of A12024-T351 and A17075-T651 are used. Compared with the empirical distribution of test data, the distribution from the r-decreasing model is satisfactory and damage process is well described from the probabilistic and physical viewpoint.