• Composites Research
• /
• v.30 no.5
• /
• pp.280-287
• /
• 2017

The complex deformation of the swept composite wing occurs due to the torsional load and bending load during the flight. Therefore, prediction for displacement of swept composite wing is required for structural health monitoring. Wing displacements can be predicted by using relationship between displacements and strains. The strain distributions on the fixed-end are complex due to the geometric shape of the swept wing. Because of those strain distribution, the wing displacement can be diversely predicted by the strain sensing locations. In this paper, displacements prediction of swept composite wing was performed by considering complex strain distributions. The predicted displacements under various loading condition were consistent with those calculated by FEA and verified through the bending test.

• Journal of the Society of Disaster Information
• /
• v.13 no.4
• /
• pp.491-498
• /
• 2017

The primary objective of this research is to develop a rutting performance prediction model of flexible pavement. Extensive laboratory testings were conducted to achieve the objective. A new test method employing repetitive axial loading with confinement was also adopted to estimate the rutting performance of asphalt concrete in the research. The rutting prediction model employes a layer-strain theory. The required rutting coefficients for the prediction model were determined through the laboratory rutting characterizations of the asphalt concrete layer materials. Within the limits of this study, a laboratory rutting prediction model of flexible pavement using repetitive axial loading test was presented. It is noted that the developed rutting prediction model simulates propery the behaviors of flexible pavement layer materials.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.44 no.1
• /
• pp.1-11
• /
• 2016

The information about the deformations of high-aspect-ratio wings is needed for the real-time monitoring of structural responses. Wing deformation in flight can be predicted by using relationship between the curvatures and the strains on the wing skin. It is also necessary to consider geometric nonlinearity when the large deformation of wing is occurred. The strain distribution on fixed-end is complex in the chordwise direction because of the geometric shape of fixed-wings on fuselages. Hence, the wing displacement can be diversely predicted by the location of the strain sensing lines in the chordwise direction. We conducted a study about prediction method of displacements regardless of the chordwise strain sensing locations. To correct spanwise strains, the ratio of spanwise strain to chordwise strain, Poisson's ratio, and the ratio of the plate strain to the beam strain were used. The predicted displacements using the strain correction were consistent with those calculated by the FEA and verified through the bending testing.

• Journal of the Korea Concrete Institute
• /
• v.13 no.5
• /
• pp.466-475
• /
• 2001

The potential shear strength of reinforced concrete beams decreases after flexural yielding due to the decrease of the effective compressive strength of concrete in plastic hinge zone. A truss model considering shear deterioration in the plastic hinge zone was proposed in order to evaluate the ductile capacity of reinforced concrete beams failing in shear after flexural yielding This model can determine the potential shear strength of the beam by using a truss model. The potential shear strength gradually decreases as the increase of the axial strain of member. When the calculated potential shear strength decreases up to the flexural yielding strength, the corresponding rotation angle is defined as the ductile capacity of the beam. The predicted ductile capacity of reinforced concrete beams is shown to be in a good agreement with experimental results.

• International Journal of Highway Engineering
• /
• v.7 no.4 s.26
• /
• pp.1-8
• /
• 2005

Permanent Deformation is one of the most important load-related pavement distresses in asphalt pavements. The Korean Pavement Design Guide currently being developed adopted the mechanistic-empirical approach and needed the pavement distress prediction models. This study intends to develop the model for prediction of permanent deformation in the asphalt layer and estimate the pavement performance. The objectives of this paper are to figure out the factors affecting the permanent deformation and then develop the permanent deformation prediction model for asphalt mixtures. The repeated triaxial load test was Performed on the 19mm dense graded asphalt mixture with variation of temperature and air void. Results from the laboratory tests showed that temperature and air void in asphalt mixtures have significantly influenced on the factors in prediction model. The permanent deformation prediction model for 19m dense grade asphalt mixtures has been developed using the multiple regression approach and validated the proposed permanent deformation prediction model.

• Journal of Welding and Joining
• /
• v.6 no.1
• /
• pp.11-20
• /
• 1988

이 글에서는 Butt joint에서 발생되는 가로수축, 각변형 그리고 bowing의 관찰을 통해 mechanism을 서술하였고, box beam, damper blade, bulk head, ball tank, 그리고 cylindrical column 등 실구조물의 변형문제에 접근하여 변형예측, 측정 data제시, 그리고 그 해석을 통해 구조물의 변형 크기를 인식케 하고, 동일한 구조물의 제작에 guide가 되고자 하였다. 변형에 대해서는 일률적인 방지방법이 없기 때문에 우선은 구조물의 제작시마다 변형의 크기와 향상에 대한 예측과 함께 변형계측이 계속되어 data가 축적된다면 차후 그 이용 및 응용 효과는 지대할 것이다.

• Tunnel and Underground Space
• /
• v.28 no.3
• /
• pp.277-291
• /
• 2018

LSTM (Long Short-Term Memory) algorithm which is a kind of recurrent neural network was used to establish a model to predict the stress-strain curve of an material under uniaxial compression. The model was established from the stress-strain data from uniaxial compression tests of silica-gypsum specimens. After training the model, it can predict the behavior of the material up to the failure state by using an early stage of stress-strain curve whose stress is very low. Because the LSTM neural network predict a value by using the previous state of data and proceed forward step by step, a higher error was found at the prediction of higher stress state due to the accumulation of error. However, this model generally predict the stress-strain curve with high accuracy. The accuracy of both LSTM and tangential prediction models increased with increased length of input data, while a difference in performance between them decreased as the amount of input data increased. LSTM model showed relatively superior performance to the tangential prediction when only few input data was given, which enhanced the necessity for application of the model.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.20 no.6
• /
• pp.113-119
• /
• 2016

In this study, the method to predict the lateral response by using strain data is presented on the steel moment frame. For this, the reliability of the proposed method by applying the example of five-story frame structure were verified. Using the strain value of columns, it predicted the lateral response of structure. It is assumed that all of four strain sensors for one column set up and the strain responses of both end of the column are utilized. The lateral response of member is calculated by using the slope deflection method. Also, using the acceleration response of the one layer, the stiffness of the rotation spring located in the supporting point is predicted. As a result, it was effective to understand the lateral displacement and acceleration responses and to predict local damage and location.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
• /
• 2000.09a
• /
• pp.166-170
• /
• 2000

연안역에서의 파랑운동 모형개발에 있어 봉착하는 가장 중요한 문제는 쇄파대에서의 파고변형의 예측이라 할 수 있다. 쇄파대에서의 파고변형 예측 모형의 재발은 파동에너지 손실의 평가를 이용한 Le Mehaute(1962)의 해석적 방법 이후로 예측모델을 개발하기 위한 많은 연구가 수행되어져 왔다. (중략)

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.40 no.12
• /
• pp.1027-1035
• /
• 2016

In this study, a strain-controlled fatigue test of widely-used 316L stainless steel with excellent corrosion resistance and mechanical properties was conducted, in order to assess its fatigue life. Low cycle fatigue behaviors were analyzed at room temperature, as a function of the strain amplitude and strain ratio. The material was hardened during the initial few cycles, and then was softened during the long post period, until failure occurred. The fatigue life decreased with increasing strain amplitude. Masing behavior in the hysteresis loop was shown under the low strain amplitude, whereas the high strain amplitude caused non-Masing behavior and reduced the mean stress. Low cycle fatigue life prediction based on the cyclic plastic energy dissipation theory, considering Masing and non-Masing effects, showed a good correlation with the experimental results.