• Title/Summary/Keyword: Prediction of Strain

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Fatigue Life Prediction Model of 12% Cr Rotor Steel (12% 크롬 로터강의 피로수명 예측 모델에 관한 연구)

  • 장윤석;오세욱;오세규
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.14 no.5
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    • pp.1349-1355
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    • 1990
  • By examining the fatigue deformation properties of 12% Cr rotor steel which has been proved to have high fatigue and creep rupture strength around 600deg. C, authors reviewed major fatigue life prediction models such as Manson, Langer and Morrow equations, and following results were obtained. (1) A simple life prediction model for 12% Cr rotor steel was obtained as follows : DELTA..epsilon.$_{t}$ =2.18+.sigma.$_{u}$ /E+ $N^{-0.065}$+ $e^{0.6}$ $N^{-0.025}$ This equation shows that fatigue life, N, can be easily determined when total strain range, DELTA..epsilon.$_{t}$ and ultimate tensile strength, .sigma.$_{u}$ are known by simple tension test on the given test conditions. (2) Life prediction equation with equivalent maximum stress, DELTA..sigma./2, corresponding maximum strain in one cycle at room temperature is as follows: DELTA..sigma./w=-7.01logN+96.69+96.69

A Prediction Model for Low Cycle and High Cycle Fatigue Lives of Pre-strained Fe-18Mn TWIP Steel (Fe-18Mn TWIP강의 Pre-strain에 따른 저주기 및 고주기 피로 수명 예측 모델)

  • Kim, Y.W.;Lee, C.S.
    • Transactions of Materials Processing
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    • v.19 no.1
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    • pp.11-16
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    • 2010
  • The influence of pre-strain on low cycle fatigue behavior of Fe-18Mn-0.05Al-0.6C TWIP steel was studied by conducting axial strain-controlled tests. As-received plates were deformed by rolling with reduction ratios of 10 and 30%, respectively. A triangular waveform with a constant frequency of 1 Hz was employed for low cycle fatigue test at the total strain amplitudes in the range of ${\pm}0.4\;{\sim}\;{\pm}0.6$ pct. The results showed that low-cycle fatigue life was strongly dependent on the amount of pre-strain as well as the strain amplitude. Increasing the amount of prestrain, the number of reversals to failure was significantly decreased at high strain amplitudes, but the effect was negligible at low strain amplitudes. A new model for predicting fatigue life of pre-strained body has been suggested by adding ${\Delta}E_{pre-strain}$ to the energy-based fatigue damage parameter. Also, high-cycle fatigue lives predicted using the low-cycle fatigue data well agreed with the experimental ones.

Estimation of Strain at Elastic System Using Acceleration Response (가속도 데이터를 활용한 선형 시스템의 변형률 예측)

  • Kim, Chan-Jung;Lee, Bong-Hyun;Jeon, Hyun-Cheol;Jo, Hyeon-Ho;Kang, Yeon-June
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.22 no.1
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    • pp.9-14
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    • 2012
  • This paper investigates the prediction of the dynamic strain response using acceleration response only. Two methods are proposed for the strain prediction; one is based on beam theory and the other is calculated by the frequency response function between acceleration and strain. First, it is estimated the dynamics of the simple notched beam, including the non-linearity, through the uni-axial vibration testing. Then, the dynamic strain response is predicted under two different methods using acceleration response. The validation of proposed methods is conducted by the comparison between measured strain and predicted values. The comparison reveals that the proposed method based on the FRF between acceleration and strain is more reliable one than that stemmed from beam theory and the maximum relative error is less than 8 %.

Prediction of the Stress-Strain Curve of Materials under Uniaxial Compression by Using LSTM Recurrent Neural Network (LSTM 순환 신경망을 이용한 재료의 단축하중 하에서의 응력-변형률 곡선 예측 연구)

  • Byun, Hoon;Song, Jae-Joon
    • Tunnel and Underground Space
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    • v.28 no.3
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    • pp.277-291
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    • 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.

Displacement Prediction of Swept Composite Cantilevered Panel Wings Using Strains (변형률을 이용한 복합재 평판 후퇴익 구조물의 변위 예측)

  • Kim, Mun-Guk;You, Je-Gyun;Kim, So-Young;Kim, In-Gul;Kim, Geun-Sang;Jeon, Min-Hyeok
    • Composites Research
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    • v.30 no.5
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    • pp.280-287
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    • 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.

Evaluation on the Creep Life Prediction Using Initial Strain Method (초기 연신율법을 이용한 크리프 수명예측 평가)

  • Kong, Yu-Sik;Lim, Man-Bae;Lee, Sang-Pill;Yoon, Han-Ki;Oh, Sae-Kyoo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.6
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    • pp.1069-1076
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    • 2002
  • The high temperature creep behavior of heat machine systems such as aircraft engines, boilers and turbines in power plants and nuclear reactor components have been considered as an important and needful fact. There are considerable research results available for the design of high temperature tube materials in power plants. However, few studies on the Initial Strain Method (ISM) capable of securing repair, maintenance, cost loss and life loss have been made. In this method, 3 long time prediction Of high temperature creep characteristics can be dramatically induced through a short time experiment. The purpose of present study is to investigate the high temperature creep lift of Udimet 720, SCM 440-STD61 and 1Cr-0.5Mo steel using the ISM. The creep test was performed at 40$0^{\circ}C$ to $700^{\circ}C$ under a pure loading. In the prediction of creep life for each materials, the equation of ISM was superior of Larson-Miller Parameter(LMP). Especially, the long time prediction of creep life was identified to improve the reliability.

Study on Friction Welding Properties and Creep Life Prediction for Heat Resisting Steels of SUH3 and SUH35 - Creep Properties and ISM (내열강재 SUH3과 SUH35 마찰용접재의 ISM에 의한 크리프 수명예측에 관한 연구)

  • 양형태;오세규;김헌경;이연탁;공유식
    • Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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    • 2000.10a
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    • pp.101-108
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    • 2000
  • In this paper, the real-time prediction of high temperature creep life was carried out for the friction welded joints of dissimilar heat resisting steels(SUH3-SUH35). Various life prediction methods such as LMP(Larson-Miller Parameter) and ISM(initial strain method) were applied : The creep behaviors of those steels and the welds under static load were examined by ISM combined with LMP at 500, 600 and $700^{\circ}C$, and the relationship between these two methods was investigated. A real-time creep life( $t_{r}$ , hr) prediction equation by initial strain($\varepsilon$$_{0}$ , %) under any creep stress ($\sigma$, MPa) at any high temperature(T, K) was developed as follows : $t_{r}$ =$\alpha$$\varepsilon$$_{0}$ $^{\beta}$$\sigma$$^{1}$ where, (equation omitted) for SUH3-SUH35 friction weld of =16mm and =20mm, respectively.

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Machine learning techniques for prediction of ultimate strain of FRP-confined concrete

  • Tijani, Ibrahim A.;Lawal, Abiodun I.;Kwon, S.
    • Structural Engineering and Mechanics
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    • v.84 no.1
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    • pp.101-111
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    • 2022
  • It is widely known that axially loaded fiber-reinforced polymer (FRP) confined concrete presents significant and enhanced mechanical properties with reference to the unconfined concrete. Therefore, to predict the mechanical behavior of FRP-confined concrete two quantities-peak strength and ultimate strain are required. Despite the significant advances, the determination of the ultimate strain of FRP-confined concrete is one of the most challenging problems to be resolved. This is often attributed to our persistence in desiring the conventional methods as the sole technique to examine this phenomenon and the complex nature of the ultimate strain of FRP-confined concrete. To bridge the research gap, this study adopted two machine learning (ML) techniques-artificial neural network (ANN) and Gaussian process regression (GPR)-to analyze observations obtained from 627 datasets of FRP-confined concrete circular and non-circular sections under axial loading test. Besides, the techniques are also used to predict the ultimate strain of FRP-confined concrete. Seven parameters namely width/diameter of the specimens, corner radius ratio, the strength of concrete, FRP elastic modulus, FRP thickness, FRP tensile rupture strain, and the axial strain of unconfined concrete-are the input parameters used to predict the ultimate strain of FRP-confined concrete. The results of the current study highlight the merit of using AI techniques in structural engineering applications given their extraordinary ability to comprehend multidimensional phenomena of FRP-confined concrete structures with ease, low computational cost, and high performance over the existing empirical models.

A prediction model for strength and strain of CFRP-confined concrete cylinders using gene expression programming

  • Sema, Alacali
    • Computers and Concrete
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    • v.30 no.6
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    • pp.377-391
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    • 2022
  • The use of carbon fiber-reinforced polymers (CFRP) has widely increased due to its enhancement in the ultimate strength and ductility of the reinforced concrete (RC) structures. This study presents a prediction model for the axial compressive strength and strain of normal-strength concrete cylinders confined with CFRP. Besides, soft computing approaches have been extensively used to model in many areas of civil engineering applications. Therefore, the genetic expression programming (GEP) models to predict axial compressive strength and strain of CFRP-confined concrete specimens were used in this study. For this purpose, the parameters of 283 CFRP-confined concrete specimens collected from 38 experimental studies in the literature were taken into account as input variables to predict GEP based models. Then, the results of GEP models were statistically compared with those of models proposed by various researchers. The values of R2 for strength and strain of CFRP-confined concrete were obtained as 0.897 and 0.713, respectively. The results of the comparison reveal that the proposed GEP-based models for CFRP-confined concrete have the best efficiency among the existing models and provide the best performance.

Characteristics of the Method to Predict Strain Responses from the Measurements of Displacement Responses (변위응답의 측정으로부터 변형률응답을 예측하는 방법의 특성)

  • Lee, Gun-Myung;Ko, Jae-Heung
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.11a
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    • pp.844-848
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    • 2005
  • A method to predict the strain responses from the measurements of displacement responses is considered. The method uses a transformation matrix which is composed of a displacement modal matrix and a strain modal matrix. The method can predict strains at points where displacements are not measured as well as at displacement measuring points. One of the drawbacks of the strain prediction method is that the displacement responses must be measured at many points on a structure simultaneously. This difficulty can be overcome by measuring the FRFs between displacements at a reference point and other point in sequence with a two channel measuring equipment This procedure is based on the assumption that the characteristics of excitation applied to the structure do not vary with time.

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